More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\n
Our breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n
“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\n
Additionally, each book published by IntechOpen contains original content and research findings.
\\n\\n
We are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\n
Simba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\n
IntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\n
Since the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\n
Our breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n
“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\n
Additionally, each book published by IntechOpen contains original content and research findings.
\n\n
We are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n
\n\n
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\r\n\tHuman rights matter today more than ever. There is a need to understand what is meant by human rights at local level and in a global context. Human rights are moral principles or norms which provide an understanding of human behaviour, principles and practices which are protected as legal rights in municipal and international law. They are understood to apply to all human beings regardless of age, gender, ethnicity, religion, location or status.
\r\n
\r\n\tThey are a universal code of rights and require a respect of the human rights for all by all. The doctrine of human rights has been extremely influential within international law at universal level. The Universal Declaration of Human Rights was adopted by the United Nations General Assembly in 1948. Do we need to understand what human rights means today post World War II? This is especially in light of the 'Black Lives Matter' movement and in light of the changing demographics across the world.
\r\n
\r\n\tThis book evaluates the movements and trends which highlight the need to be more aware than ever of the egalitarian rights of all people across the world in achieving a just society for all.
",isbn:"978-1-83968-874-4",printIsbn:"978-1-83968-873-7",pdfIsbn:"978-1-83968-875-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"54f05b93812fd434f3962956d6413a6b",bookSignature:"Dr. Trudy Corrigan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9537.jpg",keywords:"Global Issues, Local Issues, Human Rights, Fundamental Universal Rights, Education, Knowledge, Consciousness Raising, Global Understanding, Regional Understanding, Historical and Understanding in Our Modern World, Equality, Freedom",numberOfDownloads:197,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 18th 2020",dateEndSecondStepPublish:"October 16th 2020",dateEndThirdStepPublish:"December 15th 2020",dateEndFourthStepPublish:"March 5th 2021",dateEndFifthStepPublish:"May 4th 2021",remainingDaysToSecondStep:"6 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Trudy Corrigan is an assistant professor at Dublin City University (DCU) School of Policy and Practice and a research fellow at the National Anti-Bullying Research and Resource Centre (ABC) at DCU. She is a pioneering researcher in the field of intergenerational learning; she was the Vice-Chair and a co-founder of the Age-Friendly University movement which began in DCU in 2012.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"197557",title:"Dr.",name:"Trudy",middleName:null,surname:"Corrigan",slug:"trudy-corrigan",fullName:"Trudy Corrigan",profilePictureURL:"https://mts.intechopen.com/storage/users/197557/images/system/197557.png",biography:"Dr. Trudy Corrigan is an assistant professor at Dublin City University (DCU) School of Policy and Practice and a research fellow at the National Anti-Bullying Research and Resource Centre (ABC) at DCU. Her research interests include adult education and lifelong learning, and ageism and bullying in learning and workplace environments. 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1. Introduction
1.1. Quadrupedal locomotion (walking on four extremities)
Locomotion is the movement of an organism from one place to another, often by the action of appendages such as flagella, limbs, or wings. In some animals, such as fish, a lumbering locomotion results from a wavelike series of muscle contractions (The American Heritage® Science Dictionary, 2005). Walking is travelling by foot; gait is the manner of locomotion; running is the act of travelling on foot at a fast pace; crawling is a slow mode of hand-knee or hand-foot locomotion. Walking on all four extremities (quadrupedal locomotion, QL) is the trait of the quadruped animals. Non-primate mammals usually utilize lateral-sequence QL, in which the hind limb touchdowns are followed by the ipsilateral forelimb touchdowns (symmetric gait). On the contrary, the non-human primates usually utilize a diagonal-sequence QL, in which the hind-limb moves with the contralateral forelimb in a diagonal couplet (asymmetric gait). Interestingly, only the animals exhibiting the diagonal-sequence QL with symmetrical gait evolved towards species with enlarged brains associated with highly complex neural circuits, till the emergence of human beings. The animals exhibiting lateral-sequence QL did not show such a phylogenetic progress compared to those with diagonal-sequence QL. Figure 1 shows the differences between lateral-(left) and diagonal-sequence (right) patterns of QL.
Figure 1.
Difference between walking styles of primate (right) and non-primate (left) mammals. Most non-primate animals utilize lateral-sequence locomotion, but most primates utilize diagonal-sequence locomotion. Notice the filled vs unfilled extremities during lateral (left) and diagonal (right) locomotion and the interference between the fore- and hind limbs on the left side during diagonal gait.
1.2. Evolutionarily preserved neural networks for QL
With regard to the origins of the diagonal-sequence QL, it is reasonable to conclude that the neural circuits for this kind of locomotion existed even in the most primitive tetrapods, lived in the Devonian period during transition from water to land. Thus, this type of locomotion is indeed phylogenetically the oldest locomotor trait, not the lateral-sequence QL. Namely, fossils due to the first fish-like tetrapods, lived approximately 395 MYA, were recently discovered on the Polish coast. From the fossil tracks left by a tetrapod, it was concluded that this most primitive quadruped animal walked with diagonal strides (see Figure 2), reflecting the lumbering locomotor movements as their ancestors lived in marine environments [1]. Interestingly, the quintessence of this diagonal-sequence coordination of the extremities during QL, did not change throughout the course of evolution, through salamanders and tuataras [2], to the emergence of non-human primates and even human beings during upright locomotion on two extremities [3, 4]. On the other hand, these results also suggest that the neural circuits responsible for the diagonal-sequence QL have been preserved for about 400 million years since the first emergence of QL in the fishlike tetrapods. In accord, the lumbering locomotor movements of tetrapods may even be visualized in human infants during crawling (see Figure 3), reasonably resulting from the activity of the ancestral neural networks still functioning approximately 400 million years later from the first emergence of the fishlike tetrapods. In accord, there are reports in the scientific literature supporting these considerations, i.e., the neural networks controlling the diagonal-sequence QL have been preserved throughout the evolutionary development for at least 395 million years since the emergence of the tetrapod-like fishes lived during the Devonian period [1,5,6].
Figure 2.
The trackway on the left (a) shows the hand and foot shapes in a diagonal stride pattern with a generic Devonian tetrapod fitted to this tackways (b). Notice the lumbering diagonal-sequence QL of this tetrapod, similar to its ancestral forms living in water.
Figure 3.
Diagonal-sequence QLs (see arrows) with lumbering in a generic Devonian tetrapod during the time of transition from water to land (A), proposed picture of a most primitive tetrapod, Acanthostego, with lumbering diagonal-sequence QL, a half fish, half reptile, lived in a swamp, 360 million years ago (MYA), see B. C, D: a contemporary human child crawling on all fours with accompanying lumbering movements, more or less similar to the very primitive Devonian animal lived almost 400 MYA.
As mentioned above, the neural networks playing a role in the emergence of the QL have been preserved for at least 395 million years since the Devonian tetrapod-like fishes [1]. Accordingly, it was reported an evolutionarily conserved daldh2 intronic enhancer in the frog, mouse, and chicken, being also involved in the formation of the neural tube throughout vertebrate species [7]. This evolutionary conservation of the enzyme playing a role in shaping the neural tube is essentially related to the evolutionary conservation of the neural networks for the diagonal-sequence QL. The mechanisms of this evolutionary preservation of the basic neural networks remain, however, unresolved. The genetic and/or epigenetic mechanisms contributing to the evolutionary development would shed some light on this subject.
2. Human beings with QL; Üner Tan Syndrome (UTS)
2.1. History
A human being habitually walking on all four extremities (quadrupedalism) was first discovered by Childs [8], the notable British traveler and writer, nearly a hundred years ago, on the famous Bagdad road near Havsa/Samsun on the middle Black Sea coast, at time of Ottoman Empire. This man probably belonged to a Greek family, since this region was populated by Greeks during this time. And, he probably was the son of a consanguineous family living in this closed Greek population with a high probability of consanguineous marriages. Childs described this man on page 29 of his book as follows:
“As we rose out of the next valley a donkey and a figure on the ground beside it attracted my attention…the figure moved in a curious fashion, and I went up to look more closely. And now it appeared I had fallen into the trap of a beggar…He sprang up and asked for alms, and because there were not immediately forthcoming went on all fours and showed a number of antics, imitating a dog and goat and other animals to admiration. Then I saw he was without thighs; that the knee-joint was at the hip, the leg rigid, and only half the usual length.”
Fig. 4 shows the man walking on all four extremities reported in 1917 for the first time in the scientific literature by Childs, a famous British traveler and writer.
Figure 4.
First man habitually walking on all four extremities, who was first discovered in Turkey during Ottoman Empire, in 1917, by Childs, the famous British traveler and writer, in Havsa/Samsun, Middle Black-Sea coast. The man was standing beneath his donkey, carrying torn trousers and shirt, pointing out his poverty.
Since the first discovery of a man with quadrupedalism, in 1917, not a similar human being was reported in the scientific literature, until the first description of five consanguineous kindred, resident in Southern Turkey, who exhibited a symptom complex with habitual QL, mental retardation, and dysarthric speech with limited conscious experience [9-15]. This pointed out a novel syndrome, which was referred to Uner Tan Syndrome (UTS) in some books, book chapters, and journal articles, accentuating the discovery’s name. This novel syndrome was first reported, in 2005, in front of the members of the Turkish Academy of Sciences, in Ankara and Istanbul [9,10], also being published in some Turkish and English journals [11-15, see for reviews [16, 17]. This remarkable syndrome soon sparked a world-wide interest (see for reviews [18,19,], mainly because of its relation to human evolution.
2.2. UTS type-I and type-II
According to the childhood hypotonia in skeletal muscles, two subgroups of cases exhibiting the UTS could be distinguished: (i) UTS Type I, which included UTS cases without childhood hypotonia. Of 32 cases hitherto discovered in Turkey, 25 (78.1%) patients had UTS Type I. (ii) UTS Type II, which included UTS cases with childhood hypotonia. This was observed in 7 (21.9%) cases, who had no early ambulation during childhood. However, the childhood hypotonia disappeared and replaced with normal muscle tonus accompanied with QL during adolescence (see for reviews [16,17]. Figure 5 illustrates some of the UTS Type-I cases exhibiting diagonal-sequence QL, with coincidence of limbs and feet on the same side (interference effect), which would be disadvantageous for proper walking and running on all four extremities.
2.3. Forelimb and hind limb weight supports during QL
Non-primate mammals usually support their body weight more on the forelimbs than their hind limbs during QL [20,21]. Contrarily, most primates support their body weight more on their hind limbs than their forelimbs during QL [20,22,23]. The decreased forelimb weight support in non-human primates was interpreted as an adaptation to reduce stress on the forelimb joints, and facilitate the forelimb motility, especially for arboreal locomotion [24,25]. However, the human beings with QL without arboreal habits showed similar body mass distribution on the footfall patterns, i.e., less support on their hands (24% of their body weight) than their feet (76.0% of their body weight). Similarly, monkeys also support less than 30.0% of their body weight on their forelimbs [24,26,28]. According to Reynolds [24], 30-45% of the body weight was exerted on the forelimbs during QL of eight primates. Thus, the human beings with habitual QL also support their body weight more on their hind limb than their forelimbs, like their close relatives, the non-human primates. This body weight support pattern on hands and feet in human quadrupeds is consistent with the hypothesis that less body weight exerted on the hands than on the feet would be beneficial for fine manual skills in primates. A complete freeing of hands of human beings due to upright walking would be entirely associated with their highly developed hand skills and their accompanying co-development of their brains, all resulting from the replacement of a weight carrying function with a cognitive function of human hands. The severe mental retardation associated with the habitual QL in UTS cases could, therefore, be considered as an evolutionary example for the coupling between locomotor and mental abilities. The close coupling between the manual skill and cognitive ability was previously reported in humans [29-31] and great apes [32], consistent with Tan’s psychomotor theory [33].
Figure 5.
UTS cases walking on all four extremities exhibiting diagonal-sequence QL. Notice the interference between arms and legs on the same side due to diagonal sequence QL. Straight lines, forward and dotted lines, backward motions of the contralateral extremities.
2.4. Neurological examinations
All of the UTS-cases could understand simple questions and demands, but 24 cases (75.0%) in 7 families had no expressive speech at all, so that they replied the simple questions with one or two simple sounds. Only 8 cases (25.0%) had a dysarthric speech with a very limited vocabulary. Cognitive tests showed a severe mental retardation in all cases. Brain MRI scans revealed a cerebello-vermial hypoplasia with mild gyral simplification in cerebral cortex, except one case with normal cerebellum and impaired peripheral vestibular system instead of the central vestibular system in other cases. Truncal ataxia was present in all cases, but muscle tone was normal with strong arms and legs in these adult cases. The results of the neurological examinations, MRI and PET scans, and cognitive tests were presented in two review articles [16,17]. The clinical characteristics of the affected cases of the families from Turkey are summarized in Table 1.
2.5. Gender differences
There were 19 men and 13 women with UTS from Turkey, 2 men and 1 women from Morocco, 4 brothers from Brazil, 2 men from Iraq, 1 man from Mexico and 1 man from Chile. The number of men (n = 29, 67.4%) exceeded that of women (n = 14, 32.6%), the difference (34.8%) being, however, only marginally significant (χ2 = 3.34, df = 1, p =.07).
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
Findings
\n\t\t\t
Iskend.Type-I
\n\t\t\t
AdanaType-I
\n\t\t\t
AntepType-I
\n\t\t\t
Canak.Type-I
\n\t\t\t
KarsType-I
\n\t\t\t
AfyonType-I
\n\t\t\t
Diyarb.Type-II
\n\t\t
\n\t\t
\n\t\t\t
N (QL) Men Women Age
\n\t\t\t
6 2 4 21-35
\n\t\t\t
3 2 1 29-39
\n\t\t\t
7 5 2 14-48
\n\t\t\t
4 2 2 24-64
\n\t\t\t
2 2 0 44-45
\n\t\t\t
3 2 1 12-24
\n\t\t\t
7 4 3 9-27
\n\t\t
\n\t\t
\n\t\t\t
Mutation
\n\t\t\t
17p.13
\n\t\t\t
13q.12
\n\t\t\t
9p.24
\n\t\t\t
9p.24
\n\t\t\t
(?)
\n\t\t\t
9p.24
\n\t\t\t
(?)
\n\t\t
\n\t\t
\n\t\t\t
Ves.Imp.
\n\t\t\t
Central
\n\t\t\t
Pripheral
\n\t\t\t
Central
\n\t\t\t
Central
\n\t\t\t
Central
\n\t\t\t
Central
\n\t\t\t
Central
\n\t\t
\n\t\t
\n\t\t\t
Cerebel.
\n\t\t\t
Hypopl.
\n\t\t\t
Normal
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t
\n\t\t
\n\t\t\t
Vermis
\n\t\t\t
Hypopl.
\n\t\t\t
Normal
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t\t
Hypopl.
\n\t\t
\n\t\t
\n\t\t\t
Cer.cort.
\n\t\t\t
Gy.simp
\n\t\t\t
Normal
\n\t\t\t
Gy.simp
\n\t\t\t
Gy.simp
\n\t\t\t
Gy.simp
\n\t\t\t
Gy.simp
\n\t\t\t
Gy.simp
\n\t\t
\n\t\t
\n\t\t\t
DTR upp
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t
\n\t\t
\n\t\t\t
Strength
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t\t
Normal
\n\t\t
\n\t\t
\n\t\t\t
Babinski
\n\t\t\t
+ (3/6)
\n\t\t\t
Absent
\n\t\t\t
+ (3/7)
\n\t\t\t
Absent
\n\t\t\t
+ (1/2)
\n\t\t\t
+ (1/3)
\n\t\t\t
+ (1/7)
\n\t\t
\n\t\t
\n\t\t\t
Tremor
\n\t\t\t
Mild
\n\t\t\t
Mild
\n\t\t\t
+ (1/7)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t
\n\t\t
\n\t\t\t
Nystag.
\n\t\t\t
(+)
\n\t\t\t
(+)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
+ (2/7)
\n\t\t
\n\t\t
\n\t\t\t
E.Hypoto
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(-)
\n\t\t\t
(+)
\n\t\t
\n\t\t
\n\t\t\t
Men.ret.
\n\t\t\t
Severe
\n\t\t\t
Severe
\n\t\t\t
Severe
\n\t\t\t
Mild
\n\t\t\t
Severe
\n\t\t\t
Severe
\n\t\t\t
Severe
\n\t\t
\n\t\t
\n\t\t\t
Speech
\n\t\t\t
Dysarth.
\n\t\t\t
Dysarth.
\n\t\t\t
No
\n\t\t\t
No
\n\t\t\t
No
\n\t\t\t
No
\n\t\t\t
No
\n\t\t
\n\t\t
\n\t\t\t
Standing
\n\t\t\t
Yes
\n\t\t\t
No (1/3)
\n\t\t\t
Yes
\n\t\t\t
Yes
\n\t\t\t
Yes
\n\t\t\t
Yes
\n\t\t\t
Yes
\n\t\t
\n\t\t
\n\t\t\t
Bip.walk
\n\t\t\t
(+)
\n\t\t\t
(-):(1/3)
\n\t\t\t
(+)
\n\t\t\t
(+)
\n\t\t\t
(+)
\n\t\t\t
(+)
\n\t\t\t
(-):(1/7)
\n\t\t
\n\t
Table 1.
Findings from families with UTS. Iskend.: Iskenderun (mutation in WDR81 gene), Adana (mutation in ATP8A2 gene), Canak.:Canakkale (mutation in VLDLR gene), Afyon (mutation in VLDLR gene), Diyarb.:Diyarbakir. Ves.Imp.:vestibular impairment; Cerebel.:cerebellum; Cer.cor.: cerebral cortex; DTR upp.: upper extremity deep tendon reflexes; DTR low: lower extremity deep tendon reflexes; M.tone: muscle tone; Nystag.:nystagmus; E.hypoto.: extremity hypotonia; Men.ret.: mental retardation; Bip.walk.: bipedal walking.
2.6. Cognitive tests
All of the patients exhibited severe mental retardation, according to the results of two cognitive tests. “Mini Mental State Examination Test” (MMSE), also known as the “Folstein test” [34], consisting of a 30-point questionnaire, testing for the individuals’ attention, calculation, recall, language and motor skills, showed severe mental retardation in all of the cases (range = 0 to 2 points). The healthy siblings of the affected individuals were relatively normal in the MMSE test, with scores ranging between 25 and 29 points, although tey all shared the same environment. The Wais-R (Wechsler Adult Intelligence Scale-Revised) showed also severe mental retardation in the UTS cases, who obtained “0” to “4” points of a total 30 points. The results of the MMSE test are summarized in Table 2.
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
Questions
\n\t\t\t
Patients’ answers
\n\t\t
\n\t\t
\n\t\t\t
What is today’s date? What is the month? What is the year? What is the day of the week today? What season is it?
\n\t\t\t
\n\t\t\t\tOrientation in time:\n\t\t\t\t They gave unrelated answers such as 80,90,house,cow,dog, or did not give an answer at all, except thinking.
\n\t\t
\n\t\t
\n\t\t\t
Whose house is this? What room is this? What city are we in? What country are we in?
\n\t\t\t
\n\t\t\t\tOrientation to place:\n\t\t\t\t Nobody could give a correct answer, or they replied with unrelated words such as summer, me, winter, cow, dog, mother, father, etc.
\n\t\t
\n\t\t
\n\t\t\t
Repeat:ball,flag,tree
\n\t\t\t
\n\t\t\t\tImmediate recall:\n\t\t\t\t Only a few of them could recall these words.
\n\t\t
\n\t\t
\n\t\t\t
Count backwards from 100 by 7
\n\t\t\t
\n\t\t\t\tAttention:\n\t\t\t\t They even could not count forwards from 0 to 10.
\n\t\t
\n\t\t
\n\t\t\t
Recall 3 words I asked previously
\n\t\t\t
\n\t\t\t\tDelayed verbal recall:\n\t\t\t\t Nobody could recall the words previously asked
\n\t\t
\n\t\t
\n\t\t\t
Name these items: watch, pencil
\n\t\t\t
\n\t\t\t\tNaming:\n\t\t\t\t Only some of them could name these items
\n\t\t
\n\t\t
\n\t\t\t
Repeat following: No if, ands, or buts
\n\t\t\t
\n\t\t\t\tRepetition:\n\t\t\t\t Nobody could repeat them
\n\t\t
\n\t\t
\n\t\t\t
Take the paper in your hand, fold it in half, and put it on the floor.
\n\t\t\t
\n\t\t\t\t3-stage command:\n\t\t\t\t Nobody could follow this command, and only some of them took the paper in the hand.
\n\t\t
\n\t
Table 2.
Questions from the MMSE test and patients’ answers.
2.7. Genetics
The UTS is genetically heterogeneous. Namely, we found missense mutations in the following genes: VLDLR in Canakkale and Gaziantep families [35], WDR81 in Iskenderun family [36], ATP8A2 in Adana family [37]. Interestingly, the mother of the affected siblings in the Iskenderun family had type-I diabetes, which may be associated with developmental malformations, such as caudal regression in mice [38]. The VLDLR gene is involved in the controlling neuroblast migration in the developing central nervous system, see [35]. This gene shows an evolutionary conservation for at least 200 million years [39]. WDR81 gene is evolutionarily highly conserved trans-membrane protein, which is highly expressed especially in cerebellum and corpus callosum, see [36]. However, different mutations in a single gene may lead to different expressions of the same phenotype (allelic heterogeneity). Moreover, similar genetic lesions can have entirely different phenotypes [40]. Thus, mutations in a single gene like VLDLR cannot be solely associated with quadrupedal locomotion in human beings. Given the genetic heterogeneity of the UTS, a specific gene directly responsible for the emergence of human quadrupedalism does not seem to be reasonable. Moreover, the missense mutations found in the affected cases may also be involved in neural functions other than the QL. Accordingly, missense mutation in VLDLR gene was also associated with congenital cerebellar hypoplasia [41], along with Norman-Roberts syndrome, characterized by microcephaly, hypertonia, hyperreflexia, severe mental retardation, and agyric cerebral cortex [42]. The VLDLR gene works with a protein, reelin, which is also associated with disorders such as Alzheimer’s disease, schizophrenia, and bipolar disorder.
Merlberg et al [43] re-evaluated the disequilibrium syndrome [44] in Swedish patients with non-progressive cerebellar ataxia, dysarthria, short stature, childhood hypotonia, and mental retardation, without VLDLR mutation. Interestingly, MRI showed a spectrum from normal to severe cerebellar hypoplasia. Similarly, the UTS cases of the Adana family did not exhibit cerebellar hypoplasia [13-15], despite a missense mutation in the ATP8A2 gene [37], suggesting no genetic association of the cerebellar hypoplasia in UTS.
Taking together, the genetic associations hitherto reported for the UTS seem to have no or only minor explanatory power, if any, for the origins of human quadrupedalism. In accord, Hall [45] argued how genetics failed to find solutions for the discrepancies concerning the so-called genetic diseases: evidence is growing that your DNA sequence does not determine your entire genetic fate.. Larger scale genomic studies over the past five years or so have mainly failed to turn up common genes that play a major role in complex human maladies. This argument seems to be also true for well-known disorders including diabetes, schizophrenia, and cancer, as Maher [46] stated: even when dozens of genes have been linked to a trait, both the individual and cumulative effects are surprisingly small and nowhere near enough to explain earlier estimates of heritability.
3. Darwinian medicine; UTS
Why are only some rare cases predisposed to walk on all four extremities similar to our early ancestors? The quest to find an answer to this and similar questions was the starting point for establishing a new discipline, “Darwinian medicine”, which is a novel concept providing a foundation for all medicine [47]. The aim of the Darwinian medicine is the evolutionary understanding of aspects of the body with regard to its vulnerability to disease(s), as Zampieri [47] stated: It tries to find evolutionary explanations for shared characteristics that leave all people vulnerable to a disease. Evolutionary or Darwinian medicine may be useful to understand better why diseases exist despite natural selection [48,49]. A number of diseases were considered as Darwinian disorders, such as tuberculosis, Huntington’s disease, depression, obesity, anxiety, pain, nausea, cough, fever, vomiting, fatigue, epilepsy, obsessive compulsive disorder, and schizophrenia [50-53]. In this framework, the UTS with the reappearance of the ancestral features such as quadrupedal locomotion and primitive cognition including no speech in most of the cases, and severe mental retardation may also be considered as a further example related to Darwinian medicine.
Rapoport [54] first introduced the concept of “phylogenic diseases”, such as Alzheimer’s disease as a “phylogenic regression”, comparing brain aging involution to the reversed phenomenon of Darwinian evolution [55. Accordingly, many neurodegenerative diseases such as Parkinson’s disease, schizophrenia, Alzheimer’s disease, and many highest level gait disorders including the UTS with ancestral QL, i.e., the re-emergence of old automatism of pre-human gait, may also be considered under these phylogenic diseases. In this context, the recently introduced paleoneurologic standpoint may help us to more deeply understand the pathogenesis of the neuropsychiatric diseases, provided that they are reconsidered under evolutionary perspective.
4. Complex systems; Self-organization
The word “complex” may be defined as “consisting of interconnected or interwoven parts” [56]. Many complex systems have the tendency to spontaneously generate novel and organized forms, such as ice crystals, galactic spirals, cloud formation, lightning flashes in the sky, or polygonal impressions in the earth. The spontaneously generated formation in the nature are in no way designed by anything, not even by natural selection, being entirely the art of nature with self-organizing properties within complex systems, following the principle, the sum of the parts is greater than the parts taken independently, Contrary to Isaac Newton’s arguments, …the whole is the sum of all the parts..
Complex systems have a strong tendency to self-organize, i.e., spontaneous formation of patterns in open nonequilibrium systems. This is also the quintessence of all living systems.
For instance, insects can spontaneously build their nests or hives, hunt in groups, and explore the food resources in their environment. The evolution of the biological forms and structures may also be associated with self-organization. Some authors have even questioned the centrality of natural selection in evolution, since Darwinism essentially ignores the principles of self-organization. Accordingly, Oudeyer [57] argued: Thus, the explanation of the origins of forms and structures in the living can not only rely on the principle of natural selection, which should be complemented by the understanding of physical mechanisms of rom generation in which self-organization plays a central role.
Self-organization is closely coupled with “emergence”, a fundamental property of complex systems, which is the unpredictable product of the system, resulting from interconnections and interactions between parts of a dynamical system; entities, interactions, and the environment are key contributors to emergence [58]. The main characteristic of the UTS, human quadrupedalism, may also be an emergent property of the locomotor development. In accord with the dynamical systems theory, and the principles of self-organization, it can be stated that no genetic or neural code may be the causative factor for the emergence of the human quadrupedalism. As mentioned above, we could not isolate a single gene responsible only for the QL in human beings, minimizing the role, if any, of any genetic code in the emergence of human QL.
Human quadrupedalism may be considered as a strange attractor, a state of a dynamical system toward which that system tends to evolve. For instance, the EEG may exhibit one type of strange attractor while a person is at rest, but another type of strange attractor during mathematical thinking. The common property of strange attractors is their unpredictability. The rarely occurring locomotor pattern in the UTS cases, i.e., QL, may be related to its unpredictability as a strange attractor. An entirely different locomotor strange attractor emerged in a man from Tanzania, who exhibited all of the symptoms of the UTS, including truncal ataxia and no upright ambulation with mental retardation and no speech. However, an entirely novel and unpredictable locomotor pattern emerged in this man as a strange attractor. Namely, his QL was upside down, i.e., in face-up position. He used his hands and feet for QL, but used palms and heels instead of the soles (see Fig. 6). This is the first reported case exhibiting the UTS with inverse QL.
Figure 6.
Tanzanian man with UTS, walking on all four extremities but with inverse quadrupedal locomotion: further example for a locomotor strange attractor.
In essence, the dynamical systems tend to control the outcome of the system to find which patterns can possibly be built from the systems components to begin with, and the structural constraints of the environment, the self-organizing phenomena being basic mechanisms for the emergence of any adaptive behavior, such as the adaptive self-organization phenomena playing a role in the developmental emergence of the human quadrupedalism.
5. Central Pattern Generators (CPG)
The locomotor system is closely related to CPGs embedded in the spinal cord, which is a set of motoneurons responsible for locomotion [59], probably also involved in the human QL. The spinal motor system seems to be similar in all quadrupeds and human beings [4]. Individuals with or without UTS may all share the same neural networks responsible for the diagonal-sequence quadrupedal locomotion as the nonhuman primates, because they all are using the common neuronal control mechanisms for locomotion [60]. However, the CPGs do not reflect the coordinated walking pattern in intact animals, since there are separate CPGs for each leg in the cat [61]. On the other hand, the presence of the CPGs in higher primates is much less convincing. This could be due to the increased role of the corticospinal tractus in primates, suppressing the spinal motor circuitry responsible for relatively rough locomotor movements, and facilitating the skilled hand movements. According to Duysens et al [61], CPGs have no direct equivalent in human beings.
The concept of CPGs did not find supporters among system theoreticians. For instance, Thelen and Smith [62] argued the notion of the CPGs as the essence of locomotion does not fit the data…They simply do not account for what we really observe in developing organisms..The fact of development is not explained by a list of innate ideas. Just as the assumption of a built-in CPG does not explain the development of walking. These authors further stated that real data from real frogs, chicks, cats, and humans render the construct of the CPG illusory.. If the program contains the instructions for the entire sequence of behaviors ahead of time, how can novel and adapted forms be generated? Actually, the CPGs exhibit one of the principles of biological self-organization as dynamic entities, i.e., different neural networks may induce similar outcomes, while similar neural networks can produce different outcomes. Namely, the CPGs are not static, previously hard-wired, firmly organized neural networks, they are rather loosely organized systems under the influence of the steadily changing chemical or sensory control, with newly emerged functional circuits [63]. Moreover, Neuronal networks within CPGs can change itself according to current conditions and exhibit transitions between functional states, resulting from dynamic instabilities occurring within the system with dynamic interactions at the neuronal, synaptic, and network levels [63].
6. Maturation theories
The concept of motor development showed a gradual shift from the traditional neuronal maturation theory towards the dynamic systems theory. It was believed, in the mid-1990s, that the development of the central nervous system occurred through the genetically predetermined neural networks and spinal reflexes, under the control of the cerebral cortex. Accordingly, the locomotor actions such as standing and walking in infants would result from the gradual maturation of the CNS under the influence of the cerebral cortex, not learnt by experience. The traditional maturation theory utilized the longitudinal studies to show the developmental sequence of motor behaviors in infants and young children. This was mainly elaborated by Gessel [64], Shirley [65], and McGraw [66,67], who searched for rules governing the order of changes during motor maturation. Konner [68] stated that motor development sequences are largely genetically programmed. The development of early motor behaviors was attributed to the maturation of the cortico-spinal pathways [69,70]. Despite some valuable information gained from the traditional maturation theory, it was far from explaining the dynamics of locomotor development. In this context, Ulrich [71] argued that it is not at all clear how genetic codes can be translated into even simple patterned neural organization…behavior is much more than a simple neural pattern (p.321).
Contrary to the traditional maturation theories, the contemporary approaches considered the properties of complex systems with many dynamically interacting subcomponents, to be able to solve the problems related to locomotor development. This dynamic systems theory considers the behavior of a system, not by taking it as separate parts, but by taking these parts to see under which circumstances they dynamically cooperate to produce the whole behavioral pattern such as locomotor functions. According to the dynamic systems theory, the behavioral patterns can emerge from the dynamic interactions of multiple subsystems; genetic or neural codes are not represented a priori in the brain, nor are locomotor patterns, such as walking and running. The emergence of locomotion is a self-organizing process, as in other complex systems. According to Ulrich [71, p.324], the coordination pattern emerges spontaneously and is self-organized and opportunistic. Taking together, there are two major but current and conflicting theories involved in the development of locomotor control: neuronal maturationist theory and the dynamic systems theory. According to the first theory, the maturation of the CNS occurred through the genetically predetermined neural networks; the locomotor development results from progressively maturated and hence increased cortical control on the spinal reflexes. Controversially, however, the system theoreticians did not accept the neural-maturationist theories, asking how can the timetable of motor solutions be encoded in the brain or in the genes. Accordingly, Kelso et al [72] utilized the dynamic systems theory to better explain the developmental emergence of locomotion in human beings. These authors argued that a behavior, such as a locomotor pattern may result from the combined dynamic actions of, for instance, muscle strength, body weight, postural support, motivation, and brain development, in addition to the environmental initial conditions and task requirements.
7. Neuronal group selection theory
In addition to the neuronal maturation theory and the dynamic systems theory, there is a third theory, the neuronal group selection theory (NGST) [73], which combines the “nature” part of the neural-maturationist theories with the “nurture” part of the dynamic systems theory. The neuronal groups are collections of many neurons interconnected by excitatory and/or inhibitory synapses as well as recurrent feedback circuits. According to the NGST, the structural and functional characteristics of these neuronal groups are determined by evolution. During locomotor development, behavior and experience produce afferent information for the central nervous system, which is used for the neuronal selection, according to the strength of the synaptic connections. The changed connectivity allows for a situation-specific selection of neuronal groups, which can be adapted to environmental constraints. The NGST emphasizes the role of the complex information processing originating from an intertwining of information from genes and the environment. This is not consistent with the “nature-nurture” debate. During motor development in early fetal life, the spontaneous fetal movements (primary variability), i.e., the self-generated motor activity with the consequent self-generated afferent information, may explore all the locomotor possibilities within the neurobiological and anthropometric constraints within the CNS, preserved during evolution.
During postnatal development, all of the intentional motor behaviors are within the frame of “primary variability”. The neuronal networks emerging during this developmental phase, especially prominent in the cerebral cortex are suitable for the selection of the appropriate locomotor circuits, responsible, for instance, for the infantile crawling. The most effective motor pattern gradually emerges following exploratory continuous information processing within the CNS. The time-sequence for the selection process changes with function, for instance, the second half year after birth for arm reaching. The postural activity of neck and truck muscles are direction specific before infants cat sir independently at about five months after birth. The most efficient selection for the postural balance occurs around 12-18 months of age.
The long duration of the developmental processes suggests that long-lasting motor experiences are needed for the establishment of the secondary neuronal networks. This may be associated with the late-onset quadrupedalism in some UTS cases [74]. Actually, exercise may be beneficial for the selection of the most effective neuronal pattern, by reducing the amount of secondary variation [75]. The reverse occurs in the absence of exercise, similar to the UTS cases without exercise at all.
The NGST for the locomotor development is closely related to the concept of the adaptive self-organization. Namely, the developmental selection is the differential survival of developmental units, which was proposed as an explanation for examples of self-organization [76].
8. Dynamics of locomotor development in humans
The contemporary views on the ontogenic development of locomotor skills accentuate the role of the self-organizing processes within the scope of complex systems. As mentioned above, the neural patterns playing a role in the emergence of the diagonal-sequence QL have existed since about 400 MYA during the Devonian period, having arisen with the first appearance of the ancestral tetrapods. That is, this type of locomotion is indeed phylogenetically the oldest locomotor trait of tetrapods. Interestingly, the quintessence of this locomotor activity did not change during evolution through salamanders and tuataras [2], till the emergence of non-human primates and even human beings exhibiting diagonal-sequence movements between arms and legs, even during their upright walking [3]. It may thus be concluded that the neural generators responsible for the diagonal-sequence QL may already be present in the complex locomotor systems of primates, including humans. Taking together, it may be argued that the neural patterns responsible for the QL in human beings may emerge through exploration of available solutions within the CNS, such as the ancestral neural generators for the QL and then selection of preferred patterns, such as the CPGs [77-79]. Following this ontogenetic theory, it may be concluded that the emergence of the diagonal-sequence QL in human beings may be the result of a prenatal exploration and subsequent neuronal group selection process following the principles of the self-organizing dynamic systems [80].
The cases exhibiting UTS seem to be unable to make the secondary selection for the neural networks appropriate for bipedal locomotion during infantile development. That is, they could not make the transition from the infantile stage of crawling on all fours to upright standing and bipedal walking. Their brain apparently explored the possible solutions for locomotion, but could not select the neural patterns for bipedal locomotion, because of the structural anomalies in their brain. Instead, their brain could select only one ancestral locomotor pattern available for their locomotion, which was already present since about 400 MYA. This is the ancestral neural network responsible for the diagonal-sequence QL, emerged during the Devonian period of evolution. This gait unstable initially apparently becomes stable with practice during childhood, so that they later move with great ease, speed, and well-developed balance. On the other hand, the locomotor self-organizing process may take a long time in some UTS cases with late emergence of QL at about puberty, see [16,17], a period associated with hormonal changes with beneficial effects on the motor system, accelerating the self-organizing processes, resulting in the emergence of a most suitable locomotor pattern to travel around, walking on all four extremities.
9. UTS vs socio-economic status
Neither the complex systems including the self-organizing processes nor the neuronal group selection mechanisms alone can be realized without considering the dramatic influence of the environmental factors on the holistic processes occurring in the emergence of the UTS. Namely, the single environmental factor shared by all of the cases was their extremely poor living conditions due to their very low socio-economic status. Accordingly, all of the hitherto discovered UTS cases all over the world lived in poverty, resident in developing countries. According to the Databank of the World Bank, the mean GDP (gross domestic product) of the developed countries where no UTS cases were found was 4520.00 US$, whereas the mean GDP of the developing countries where all of the UTS cases were found was 1202.7 US$. The above results suggest that the UTS is a disease of poverty. In other words, UTS with human quadrupedalism and severe mental retardation may be triggered by the environmental factor, low socio-economic status. In this context, the rates of the developmental disorders are almost twice as high in the poorer countries and in the lower income populations than the higher income groups. Over 80% of cases with intellectual disabilities are living in low- and middle-income developing countries [81] Actually there is strong relationship between poverty and common mental disorders, which were found to be about twice as frequent among the poor people compared to rich people [82], where some cases with UTS except Turkey were also found to be resident.
The malnutrition, due to low-income socio-economic status, may cause epigenetic changes, leading to impaired prenatal development of the CNS. A close association between epigenetic status as measured by global DNA methylation and socio-economic status was indeed recently reported [83]; the global DNA hypomethylation was associated with the most deprived group of individuals, compared to the least deprived group [84]. The close relationship between the epigenetic status and the socio-economic status may also be applied to the UTS, a multifactorial-complex disorder, similar to other neuropsychiatric and neurodegenerative diseases. Epigenetics refer to modifications in gene activity without changing the original DNA sequence, depending upon the environmental clues. Similar to other neurodegenerative diseases, the UTS may also comprise multifactorial processes, such as genetic, epigenetic, and environmental components [85] There are consistent reports suggesting the epigenetic mechanisms are responsive to environmental exposures during both pre- and post-natal development in humans. With regard to the most effective environmental factor, the under-nutrition due to low socio-economic status, Heijmans et al [86] reported that persons prenatally exposed to famine showed epigenetic changes compared to their unexposed same-sex siblings. Apparently, these results are consistent with the hypothesis that the triggering factor for the emergence of the UTS with quadrupedalism, mental retardation, and impaired speech may be the under-nutrition, which may detrimentally affect the pre- and postnatal psychomotor development through changing the epigenetic mechanisms.
10. Concluding remarks
The first man habitually walking on all four extremities was discovered nearly a hundred years ago in Turkey by the famous British traveler and writer, Childs, on the Black Sea coast, near Samsun, on the famous Baghdad Road, during the time of Ottoman Empire. After a silent period lasting for almost 100 years, in 2005, 6 cases with habitual quadrupedal locomotion (QL) were described in Southern Turkey. These individuals exhibited a never-before-described syndrome with habitual quadrupedal locomotion, severe mental retardation, and dysarthric speech without conscious experience, mostly cerebello-vermian hypoplasia and mildly simplified cortical gyri, referred to Uner Tan Syndrome (UTS). The number of men exceeded the number of women at p =.07 level, suggesting a male preponderance in the UTS. The syndrome showed genetic heterogeneity.
UTS can be considered within the framework of the autosomal recessive cerebellar ataxias, associated with different genetic mutations, such as the disequilibrium syndrome, Cayman ataxia, and Joubert syndrome. These closely related syndromes show overlapping symptoms, such as truncal ataxia, psychomotor delay, and dysarthric speech. These syndromes also show genetic heterogeneity, which is shared by many diseases. Thus, genetics alone cannot be informative for the origins of many syndromes, including the UTS. This is consistent with the dynamical systems theory, with the essential argument there may not be a single element, such as a genetic and/or a neural code, that predetermines the emergence of human quadrupedalism. Rather, the self-organizing processes occurring within a complex system may be involved in the developmental origins of the UTS, consisting of many decentralized and local interactions among neuronal, genetic, epigenetic, and environmental subsystems.
UTS was considered in two subgroups: Type-I and Type-II, the former exhibiting persistent early-onset QL without infantile hypotonia, the latter exhibiting late-onset QL with early-onset hypotonia in skeletal muscles. Comparison with other closely related syndromes such as dysequilibrium syndrome, Cayman ataxia, and Joubert syndrome, suggested that UTS may be differentiated from other similar ataxic syndromes by exhibiting early- or late-onset QL, no hypotonia in skeletal muscles, and no short stature, contrary to severe hypotonia without ambulation, and short stature, among others, in related syndromes, see [16].
Similar to non-human primates, but contrary to non-primate species, the UTS cases utilized the diagonal-sequence quadrupedal locomotion to travel around. The evolutionary advantage of this type of locomotion is obscure. Interestingly, however, only primates with this evolutionarily primary locomotor trait followed an evolutionary route favoring the emergence of higher primates till the human beings. The non-primate mammals with lateral-sequence QL did not follow such a phylogenetic progress. The diagonal-sequence QL was phylogenetically oldest type of locomotion, since the first tetrapods within the Devonian period utilized this kind of locomotion. This suggests that the neural networks for the diagonal-sequence QL were reserved during the evolution from first tetrapods till human beings since about 400 MYA.
A remarkable advantage of the primates with diagonal-sequence QL was that only they could utilize their hands for fine manipulations, freed from weight-bearing functions following erect posture and bipedal walking. The reduced body weight support on hands than feet in non-human primates and human beings with habitual QL (see above) would be beneficial for the development of fine uni- and bi-manual motor skills.
It was suggested that UTS may be considered as a phylogenetic regression in light of Darwinian medicine, associated with an evolutionary understanding of disorders using the principles of evolution, such as natural selection. In some UTS cases, prominent supraorbital tori were observed in cranial MRIs, more or less similar to those in non-human primates. In addition to the diagonal-sequence QL and the body weight support predominantly on the hind limbs more than the forelimbs, this was taken consistent with the theory of evolution in reverse, i.e., the reappearance of a lost function or structure that was typical of remote ancestors.
The developmental emergence of the human QL was related to the self-organizing processes occurring in complex systems, selecting one preferred behavioral state or locomotor trait out of many possible attractors. Since the dynamic systems provide enormous flexibilities in this respect, this is an unpredictable event. With regard to locomotor patterns, the dynamical systems of the developing child may prefer or create some kind of locomotion, resulting from interactions of the internal components and the environmental conditions, without a direct role of any causative factors, such as genetic and/or neural codes. The developmental emergence of human locomotion including QL is a developmental event in which the self-organization processes play the major role, no innate or previously prescribed codes being essential for the emergence of walking during locomotor development. In UTS with impaired balance, the system will find the most suitable and most comfortable, and hence preferred, mode of locomotion, spontaneously generating novel and organized forms and attractor states. These spontaneously occurring unpredictable attractors may result in the emergence of the face-down or face-up diagonal-sequence QL. In light of the dynamical systems theory, the contribution of single factors such as genetic and/or neural codes to the emergence of these locomotor patterns were rejected, considering the current scientific research in these fields, which are consistent with the concept of self-organization, suggesting no single element has causal priority.
The low socio-economic status leading to malnutrition in all UTS cases, all of them being from developing countries, was suggested as a triggering factor for the epigenetic changes occurring during the pre- and post-natal development of the brain. Namely, under-nutrition may trigger epigenetic changes in the brain, affecting the primary variability, in the first phase of locomotor development. In fetuses undergoing to epigenetic changes, the developing brain is then influenced by the aberrant proprioceptive information from fetus, resulting in impaired outcome of the developing brain, associated with psychomotor retardation and selection of the evolutionarily preserved neuronal groups with ancestral locomotor networks, leading a so-called reverse evolution in bipedal locomotion.
With regard to the neuronal group selection theory, the neural system can explore all motor possibilities by means of the self-generated, spontaneous motor activity, and with consequently self-generated afferent information transmission to CNS. The selection of the neuronal groups within the ancestral neural networks in the CNS, available since about 400 MYA, may then lead to the motor development in the next phase, i.e., the neuronal group selection by experience during infancy. In UTS cases, this phase of the locomotor development would stop because of the unavailability of the neuronal groups contributing to the postnatal emergence of bipedal locomotion, continuing ancestral locomotion on all four extremities, resulting from selection of the available ancestral neural networks for QL. So, the infants with UTS cannot select the appropriate neural networks for bipedal locomotion, since some of the neural structures necessary for the well-balanced upright locomotion are damaged in these infants, due to the cerebellar hypoplasia and cortical gyral simplification.
Following the phase of the ancestral neuronal groups responsible for human locomotion, the adaptive variability phase occurs at two to three years of age, with maturation in adolescence through experience. In cases with UTS within the same age range, this adaptive variability phase for bipedal locomotion cannot be accomplished, instead they keep the more primitive motor repertoires from the first variability and neuronal selection phase, resulting in persistence of the selection of the ancestral neuronal groups responsible for the very primitive diagonal-sequence quadrupedal locomotion, evolutionarily conserved since about 400 MYA.
Acknowledgments
This work was partly supported by the Turkish Academy of Sciences (Ankara, Turkey).
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Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Quadrupedal locomotion (walking on four extremities)",level:"2"},{id:"sec_2_2",title:"1.2. Evolutionarily preserved neural networks for QL",level:"2"},{id:"sec_4",title:"2. Human beings with QL; Üner Tan Syndrome (UTS)",level:"1"},{id:"sec_4_2",title:"2.1. History",level:"2"},{id:"sec_5_2",title:"2.2. UTS type-I and type-II",level:"2"},{id:"sec_6_2",title:"2.3. Forelimb and hind limb weight supports during QL",level:"2"},{id:"sec_7_2",title:"2.4. Neurological examinations",level:"2"},{id:"sec_8_2",title:"2.5. Gender differences",level:"2"},{id:"sec_9_2",title:"2.6. Cognitive tests",level:"2"},{id:"sec_10_2",title:"2.7. Genetics",level:"2"},{id:"sec_12",title:"3. Darwinian medicine; UTS",level:"1"},{id:"sec_13",title:"4. Complex systems; Self-organization",level:"1"},{id:"sec_14",title:"5. Central Pattern Generators (CPG)",level:"1"},{id:"sec_15",title:"6. Maturation theories",level:"1"},{id:"sec_16",title:"7. Neuronal group selection theory",level:"1"},{id:"sec_17",title:"8. Dynamics of locomotor development in humans",level:"1"},{id:"sec_18",title:"9. UTS vs socio-economic status",level:"1"},{id:"sec_19",title:"10. Concluding remarks",level:"1"},{id:"sec_20",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'NiedzwiedzkiGSzrekPet al2010Tetrapod trackways from the early Middle Devonian period of Poland. Nature,\n\t\t\t\t\t4634348'},{id:"B2",body:'ReillyS. MMcelroyE. Jet al2006Tuataras and salamanders show that walking and running are ancient features of tetrapod locomotion. Proc R Soc B, 27315631568'},{id:"B3",body:'DonkerS. FBeekP. Jet al2001Coordination between arm and leg movements during locomotion. J Mot Behav,\n\t\t\t\t\t3386102'},{id:"B4",body:'DietzV2002Human bipeds use quadrupedal coordination? Trends Neurosci,\n\t\t\t\t\t25462467'},{id:"B5",body:'DaeschlerE. BShubinN. Het al2006A devonian tetrapod-like fish and the Evolution of the tetrapod body plan. 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Başkent University, Adana Research and Training Center, Department of Neurology, Adana, Turkey
Çukurova University, Medical School, Department of Physiology, Adana, Turkey
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Phua",authors:[{id:"123050",title:"Dr.",name:"George",middleName:null,surname:"Christopoulos",fullName:"George Christopoulos",slug:"george-christopoulos"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"71605",title:"Research on Aeroelasticity Phenomenon in Aeronautical Engineering",doi:"10.5772/intechopen.91748",slug:"research-on-aeroelasticity-phenomenon-in-aeronautical-engineering",body:'
1. Introduction
Flutter is defined as the dynamic instability of aeroelasticity. Flutter is one of the most dangerous aeroelasticity phenomena as it could lead to a destroyed structure. The reason is the unsteady aerodynamic forces generated from elastic deformations of the structure that are usually involved with complicated phenomena such as the shock wave/boundary layer interaction, flow separation, nonlinear limited cycle oscillation, and more. Flutter is determined as a critical issue determining the reliability of the airplane wings or aircraft engine turbo-machine blades. Therefore, in the early phase of the structural design of the air vehicle, aircraft engine turbo-machinery, flutter problems should be calculate and predicted. However, accurate prediction of the flutter is very challenging due to the perplexing physical phenomena and the required large amount of computation [1, 2, 3, 4].
Coupled aeroelastic solution procedures use strongly coupled algorithms which contained sufficient interaction between computational fluid dynamics (CFD) and computational structural dynamics (CSD). As computer technology progresses, higher-order methods of CFD based on the Euler and the Navier-Stokes equations become more attractive due to the ability of the model and its more accurately transonic, nonlinear, and viscous effects. CFD has also advanced from two-dimensional problems to fully three-dimensional problems with or without coupled solution of the structural equations (CSD). The flow solvers used in aeroelastic analysis include 3D Euler and Navier-Stokes solvers which assumed inviscid flow.
The dynamic response of flutter characteristics of the first AGARD 445.6 wing standard aeroelastic configuration was studied using an unsteady Navier-Stokes algorithm in order to investigate a previously noted discrepancy between Euler flutter characteristics and the experimental data [5]. The 3D implicit upwind Euler/Navier-Stokes code (CFL3D Version 2.1) was previously modified for the time-marching aeroelastic analysis of wings using the unsteady Euler equations. A linear stability analysis and a time-marching aeroelastic analysis were used to determine the flutter characteristics of the isolated 45° swept-back wing. The flutter characteristics of the wing were determined using traditional V-g analysis. This stability analysis was determined at free-stream Mach numbers of 0.96 and 1.141 using the generalized aerodynamic forces calculated by solving the Euler equations and the Navier-Stokes equations.
Computational flutter required a fluid-structure interface as a common boundary to exchange the aerodynamic loads and structural displacements at the wing surface. But, the aerodynamic and structural grids were not coincident due to different systems used (fluent solver for aerodynamic grids and mechanical ADPL solver for structural grids). Therefore, the system coupling tool in ANSYS Workbench was used to transfer the aerodynamic pressure loads from the CFD grid points to the CSD grid points and vice versa, which ensured a conservative transfer of energy between the two systems [6].
Time-accurate aeroelastic simulations were carried out using the modal coupled aeroelastic implementation for a standard experimental test case: the AGARD 445.6 aeroelastic wind tunnel model in the subsonic and transonic regions [7]. A numerical methodology coupling Navier-Stokes equations and structural modal equations for predicting 3D transonic wing flutter was described in [8]. A modal approach is used for the structural response. The results indicate that the first five modes are sufficient to accurately model the wing structure response. In Ref. [9], an unsteady Reynolds-averaged Navier-Stokes (RANS) model was coupled with normal modes of structure to predict the flutter boundary for the AGARD 445.6 wing. A new integrated CFD-CSD simulation for flutter calculations based on a parallel, multiblock, multigrid flow solver for the Euler/Navier-Stokes equations using the ANSYS software was found in [10]. Computations were performed for a three-dimensional test case of AGARD 445.6 wing to validate and establish the usefulness of the simulation. Immersed boundary method solved Navier-Stokes equations for flow in couple with the Newton equation for structure movement under the effect of friction force exerted on the structure surface to carry out fluid–structure interaction (FSI). However, computational grids needed to be re-meshed in each time step due to changes of the structure position in time. To overcome this obstacle, immersed boundary method and finite volume methods were both invoked in solving the interaction between fluid flow and moving structure [11]. This research estimated the numerical and experimental results on the wing structure at a low speed with four different wing models such as two rectangular and two trapezoid 3D-shape wings, each 3D-shape wing had symmetric and asymmetric airfoil, respectively.
The subsonic aeroelastic stability of a two-dimensional panel resting on a continuous elastic foundation was investigated in Ref. [12]. Tests were conducted experimentally on a 104 × 24 × 0.018 in. rectangular aluminum panel in a low-speed wind tunnel. Comparison of experiment and theory showed a good agreement in flutter speed and wavelength but poor agreement in wave speed and frequency at flutter. This discrepancy was attributed to the limitations in the test setup as well as to the general difficulty of predicting the wave speed and frequency as accurately as the flutter speed. Reference [13] tested the first AGARD standard aeroelastic configuration for dynamic response, 445.6 wing, in the 16 foot transonic dynamics tunnel at the National Aeronautics and Space Administration (NASA) Langley Research Center. Several models of the wing were tested in the transonic dynamic tunnel including full-span and semispan models over a range of Mach number from 0.338 to 1.141. The NASA conducted experiments in wind tunnel to estimate the aeroelastic characteristics of new and advanced flight vehicles, including fixed-wing, rotary-wing, and space-launch configurations. Reviews and assessments were made regarding available facilities, measurement techniques, and other means and devices useful in testing. The needs and requirements for advances and improvements in testing capabilities for future experimental research and development programs are described [14].
In [15], aeroelastic concepts for increased aircraft performance were mentioned. Active aeroelastic concepts as well as robust analysis concepts aiming at efficient analysis were carried out using numerical models with uncertain or varying model parameters. A high aspect ratio wing in wind tunnel testing conditions was considered for exploitation of fluid-structure interaction of active aeroelastic structures. The structural flexibility was exploited by using multiple control surfaces such that the deformed wing shape gives minimum drag for different flight conditions. Two different drag minimization methods were carried out: one was to reduce induced drag based on numerical optimization techniques, and another was to reduce measured total drag using real-time optimization in the wind tunnel experiment.
An approach for the prediction of dynamic modal transient response and flutter characteristics of structures with unknown system parameters, such as stiffness and mass, using experimental modal parameters was remarked in [16]. A finite element model was created by using the actual material properties of the structure to study the correlation of the results. The computed transient responses and flutter velocities by the proposed method using experimental modal parameters observed that material properties were not a prerequisite.
In Ref. [17], transonic flutter characteristics of AGARD 445.6 wing between the numerical method [5] and the experimental data of NASA’s experiment were compared [13]. The comparison provided the basis for developing the numerical setup and the experimental setup to check out subsonic flutter characteristics of some simple wing structures (e.g., a thin plate). Aeroelasticity on airplane wing, which had supercritical airfoil, was carried out in [18]. The model wings were made from different materials and dimensions. Hence, varied wing structures were created to accomplish a comprehensive analysis, and the flutter velocity was also restricted to appropriate values within the working range of experiment devices. At the same time, infinite element method with the help of the ANSYS software was also conducted to simulate the phenomena on the same model wings as a verification for the precision of the experimental models.
2. Two-way FSI method
2.1 FSI method
The generalized equations of aeroelasticity motion:
E1
E2
where:
w: structural displacement at any time instant and position.
q: generalized displacement vector.
[M]: generalized mass matrice.
[C]: damping matrice.
[K]: stiffness matrices.
ϕ: normal modes of the structure.
N: total number of modes of the structure.
F: generalized force vector, which is responsible for linking the unsteady aerodynamics and inertial loads with the structural dynamics.
Eq. (1) shows that there are distinct terms representing the structure, aerodynamic, and dynamic disciplines. This equation was solved numerically by integrated CFD-CSD tool on the ANSYS software. This method was also called the two-way fluid-solid interaction (FSI). Aerodynamic loads were first calculated by CFD solver. Then, these loads were used to calculate the structural response of the wing structure through the fluid-solid interface. By using CSD solver, the structural deflection was estimated, and the mesh in each time step was deformed. The simulation of the two-way FSI is presented in Figure 1 [10].
Figure 1.
Two-way FSI algorithm.
Following [8], the first four modes of vibration were sufficient to accurately model the wing structure response. So, in order to determine the time step of the unsteady problem, a modal method was applied to estimate first the natural frequency of the first four modes and then calculate the time step using the following formula:
E3
where:
Δt: time step
f: natural frequency
The flutter velocity was estimated from the vibration of the wing tip position, the most dangerous position of the wing [5, 8, 9, 13]. From the variation of this position, the damping coefficient except the influence of structural damping was measured. It means that there was an effect of aerodynamic damping coefficient on the vibration of the wing structure. The aerodynamic damping coefficient was calculated as follows:
E4
where:
Xi: ith peak of vibration.
n: number of periods.
ζ: aerodynamic damping coefficient.
The damping coefficient increased/decreased when the air velocity decreased/increased. The type of vibration was distinguished from the value of damping coefficient:
ζ > 0: The vibration was convergent. The wing structure was stable.
ζ < 0: The vibration was divergent. The wing structure was unstable.
ζ = 0: The vibration was harmonic oscillation. The wing was in critical state. The air velocity was in the flutter velocity.
2.2 Wing model
AGARD 445.6 wing with aspect ratio of 1.65, taper ratio of 0.66, and 45o sweep angle at quarter chord line was studied as seen in Figure 2. The cross section of the wing was NACA65A004 airfoil in the stream-wise direction. This NACA65A004 airfoil was a symmetric airfoil with a maximum thickness of 4% of the local chord. The dimensions of the wing were root chord of 0.558 m, tip chord of 0.368 m, and semispan of 0.762 m. The wing model used in aeroelastic experiments [13] was constructed by laminated mahogany which was modeled as an orthotropic material with different material properties in different directions. The properties of the laminated mahogany are given in Table 1. The modal analysis was performed using mechanical APDLs solver to evaluate the accuracy of the constructed model.
Figure 2.
Semispan AGARD 445.6 wing model.
Material property
E11
E22
E33
G
υ
ρ
Value
3.151
0.416
0.416
0.439
0.310
397.5
Unit
GPa
GPa
GPa
GPa
N/m2
kg/m3
Table 1.
Mechanical properties for the weakened AGARD 445.6 wing.
The AGARD 445.6 wing was modeled at a zero attack angle and at altitudes of 9.65 and 14 km, the same conditions of experimental study in [13]. The wing was meshed in 9257 nodes and 1350 elements (Figure 3a). The fluid domain in CFD problem was meshed in 67,949 nodes and 279,535 elements (Figure 3b).
The free-stream air velocity was from 0.29 to 0.59 M at an altitude of 9.65 km and from 0.47 M to 0.73 M at an altitude of 14 km.
2.3 Results
2.3.1 Modal analysis
The mode shapes are obtained from the finite element analysis of the modeled wing. The deflection contours between the modal analysis and experiment [13] were compared as shown in Figure 4. The natural frequencies between the developed solution, experiment [13], and other researches were also compared as shown in Table 2. It could be concluded that the obtained results were in good agreement with the experimental results in [4, 6, 13] within an error relative of 8%. The frequency of the first mode was around 9.96 Hz. Following Eq. (3), the time step of the unsteady problem was estimated about 0.005 s.
Figure 4.
Comparison of the mode shapes. (a) Mode 1. (b) Mode 2. (c) Mode 3. (d) Mode 4.
At altitude 9.65 km, the Mach number of air velocity was varied from 0.29 to 0.59 (M = 0.29; 0.35; 0.41; 0.47; 0.53; 0.59). From Eq. (4), the aerodynamic damping coefficient was calculated and presented in Figure 5a. The zero damping coefficients were interpolated at Mach number 0.46. While the experimental zero damping was 0.499 in [13], the difference between simulation results and results of [13] was about 8%.
Figure 5.
Aerodynamic damping coefficients. (a) At altitude 9.65 km. (b) At altitude 14 km.
At altitude 14 km, the Mach numbers of air velocity were varied from 0.47 to 0.73 (M = 0.47; 0.53; 0.59; 0.65; 0.67; 0.73). From Eq. (4), the aerodynamic damping coefficient was calculated and presented in Figure 5b. The zero damping coefficients were interpolated at Mach number 0.58. While the experimental zero damping was 0.678 in [13], the difference within simulation results was about 14%.
In both the two considered altitudes (9.65 and 14 km), the numerical results agreed well with the experimental results of [13] with a relative error about 14%. This difference would be from the computation such as the quality of mesh and order of model in CFD and CSD.
For more details of the stability of the wing structure, the vibrated value of the wing tip position at three Mach numbers were plotted as shown in Figure 5.
At a Mach number smaller than the flutter value, the damping coefficient was positive, and the wing was stable (Figure 6a).
Figure 6.
Vibration of wing at altitude H = 9.65 km. (a) M = 0.29 – ζ = 0.0071. (b) M = 0.47 – ζ = −0.000125. (c) M = 0.53 – ζ = −0.006.
At a Mach number near the flutter value, the damping coefficient was zero, and the vibration was harmonic oscillation (Figure 6b).
At a Mach number greater than the flutter value, the damping coefficient was negative, and the vibration was divergent (Figure 6c). This divergent vibration would create the damage of the wing such as loss of control for the flap, aileron, fracture of wing, etc.
2.3.3 Simulation analysis
Dynamic aeroelastic analysis was a problem related to fluid-structure interaction over a period of time. Therefore, the quality of aerodynamic grid and the time step strongly influenced the results of aeroelastic analysis. These parameters were also two of the most important problems in the dynamic aeroelastic analysis.
In order to evaluate the quality of aerodynamic grid, the coefficient of pressure of AGARD 445.6 wing was first estimated at 26% semispan and at 75.5% semispan and then was compared with Ref. [6] as shown in Figure 7. The presented results were in good agreement with the results in Ref. [6]. It could be concluded that these simulation settings were appropriate for solving the transonic flow.
Figure 7.
Comparison of Cp distribution at M = 1.141, α = 0°. (a) 26 % semispan. (b) 75.5 % semispan.
To evaluate the time step size, three different time sizes were examined such as 0.001, 0.002, and 0.005 s. As it could be seen in Figure 8, the displacement of the wing tip was reduced with the reduction of time step size up to 0.002 s until the aeroelastic simulation did not change [6]. Therefore, the value 0.002 s of time step size in the numerical solution was chosen for both aerodynamic and structural analysis.
Figure 8.
Wing-tip oscillation depends on the selected time step.
The limit of flutter was identified by using damping estimations for a large test point at each Mach number. At M = 0.499, the oscillation of the displacement of the wing tip was harmonic (Figure 9), and it was considered as a flutter point. At this limit of flutter, the air speed was calculated as 174.26 m/s, and the density of air was calculated as 0.432 kg/m3. These values were very close to the experimental values: 172.46 m/s for flutter speed and 0.428 kg/m3 for density of air (Table 3). This remark illustrated that the developed solution could be used to specify the transonic flutter characteristics with errors less than 10%.
Figure 9.
Wing-tip oscillation of flutter point at M = 0.499.
The test model was set in AF6116 (M = 0.1) subsonic wind tunnel located at the Hanoi University of Science and Technology, which was of a blowdown type with a closed test section (0.4 × 0.5 × 1.0 m3). The wind speed could be arbitrarily varied up to 30 m/s, where the Reynolds number based on wing root chord was 106, which was driven by an 8 kW electric motor.
Flutter characteristics were determined with the help of the frequency meter and load cell, which allowed to specify the flutter frequency and root wing force, respectively. The oscillated frequency was measured by the DT-2234C+ frequency meter. The signal of measured frequency was averaged by five measurements. The force applied to the wing was measured by load cell system. In the experimental aeroelastic analysis, the flutter frequency and the flutter amplitude were measured at different velocities ranging from 10 to 30 m/s using an oscillator generator system.
3.2 Wing model
Two wing models with the parameter and dimension are shown in Figure 10 and Table 4. The non-structure wing had only balsa wood, while the structure wing had balsa wood for skin and carbon rod and hard wood for the inner parts.
Experimental results showed that a flutter phenomenon appeared with the non-structure wing (broken wing in Figure 10c), but this phenomenon did not happen with the structure wing model. It could be explained by the more durability of structure wing than that of the non-structure wing with the testing range of velocity. Experiments also demonstrated that the combination of multiple materials to more durability of structure of wing could be highly effective in preventing flutter phenomenon [18].
The measurement results of the non-structure wing were shown in Table 5. When the attack angle increased, the velocity of first oscillation, flutter velocity, and frequency decreased.
Attack angle (0)
Velocity of first oscillation (m/s)
Flutter velocity (m/s)
Frequency (Hz)
0
20
22
37.38
5
17.8
20.5
32.22
10
15.2
19.5
30.31
Table 5.
Flutter characteristics at different attack angles—Non-structure wing.
Figure 11 resumed the measurement of the force at the wing root in varying velocities from zero to flutter velocity and more by using the load cell system. After increasing the air velocity from zero to the limit of non-structure wing, the limit velocity of non-structure wing was found at 19.5 m/s. The load at the wing root of this wing at flutter velocity is shown in Figure 12. The maximum force was 5.44 N, and the minimum force was 4.32 N.
Figure 11.
Force at the wing root of the non-structure wing—Attack angle 10°.
Figure 12.
Force at the wing root of the non-structure wing—Attack angle 10° and velocity 19.5 m/s.
With structure wing, different modes of vibration appeared depending on the characteristics of the structure as remarked in [8]. With the help of the oscillator generator system, the specific oscillation frequencies of the first four modes were estimated as shown in Table 6.
Mode
Frequency (Hz)
Non-structure wing
Structure wing
1
24.3
23.5
2
67.0
63.0
3
103.6
115.3
4
132.0
139.0
Table 6.
Specific oscillation frequency of the non-structure and structure wings.
The frequencies of the first and second modes of the non-structure wing were higher than those of the structure wing, while the frequencies of third and fourth mode of structure wing were higher than those of non-structure wing (Table 6). Considering both wings in the first mode of oscillation, when the force was applied to the wing, the amplitude of the non-structure wing was higher than that of the structure wing (Figure 13). In conclusion, the non-structure wing was easier to resonate than the structure wing.
Figure 13.
Amplitude of oscillation of the structure wing—Mode 1.
4. IBM method
4.1 Methodology
Fluid flow and deformation of structure were governed by the following equations with assumption of linear elastic structure [11]:
E5
E6
E7
E8
E9
E10
where:
u: fluid velocity vector
p: fluid pressure
f: force that affected on wing
Re: Reynolds number
Uc: displacement velocity
ωp: angular velocity
xc: center of gravity
θp: rotation of wing r
mp: mass of wing
Ip: inertial moment of wing
F: force created by fluid passing through the wing
T: moment created by fluid passing through the wing
To solve out these equations using IBM method, the most important was that the velocity of fluid at fluid-solid interface was equal to the velocity of the wing. It means that the interaction force (f) between the wing and fluid was calculated such that the boundary condition of fluid was satisfied on the surface of the wing.
IBM method used the Cartesian grid and immersed boundary that were illustrated in Figure 14, in which the moving surface of wing was described by Lagrangian points (rounded points) and fixed points in fluid were called Eulerian points. Parameters of Lagrangian points were noted as capitalization.
Figure 14.
Cartesian grid and immersed boundary.
Discrete partial derivative of velocity over time in Eq. (5) with denote intermediate velocity at zero force of Lagrangian point, Ûk, force F of Lagrangian points were estimated as follows:
E11
where:
k: time step.
Uk+1: identified from the moving surface of wing, so this velocity was known as U(b).
Force was created from displacement and affected on the fluid element. Force was calculated using the following interpolation formula:
E12
where:
x: coordinate of Eulerian point.
N: set of Lagrangian points round Eulerian point l.
xl: coordinate of Lagrangian point.
∆Ul: volume of effect corresponding to Lagrangian point l.
δh: 3D delta function identified as follows:
E13
E14
φr=165−3r−1−31−r212≤r≤32131−3r2r≤120r≥32E15
Three-step Runge–Kutta method was applied to solve Navier-Stokes equations and Newton equations as follows:
Step 1: Calculate the instantaneous velocity at Eulerian points with no immersed boundary surface, i.e., f = 0:
Apply this instantaneous velocity to calculate Lagrangian velocity on the surface of the wing:
E17
This Lagrangian velocity was combined with wing velocity, U(b)xl, which was calculated from the dynamic equation of wing, to calculate forces of Lagrangian points (F) following Eq. (11). Then, apply this force of Lagrangian points to Eq. (12) to calculate force of Eulerian points (f).
Step 2: Solve out Navier-Stokes Eqs. (5) using calculated forces of Eulerian points to estimate the effect of flutter of the wing into the velocity field around the wing:
E18
To satisfy the continuity equation, a temporary pressure was described:
E19
Step 3: Solve Eq. (17), and calculate velocity and pressure at kth step of the Runge-Kutta method:
E20
E21
From the estimated forces at Lagrangian points, translational and angular movements of the wing were carried out by solving Eqs. (7) and (9):
E22
E23
After calculating the velocity of center of gravity (Uck) and angular velocity of wing (ωpk), coordinates of Lagrangian points were estimated by the same expressions.
4.2 Wing model
Four different wing models were carried out in order to analyze the effect of the wing structure. There were two rectangular and two trapezoid 3D-shape wings, and each 3D-shape wing had symmetric (NACA65A004) and asymmetric (supercritical) airfoil, respectively. The wings had the same area of 450 cm2 and the same semispan-wise length of 30 cm. Therefore, the rectangular wing had a chord length of 7.5 cm, while the trapezoidal wing has no sweep angle, and the leading edge line had a tip chord length of 5 cm and root chord length of 10 cm. The wings were made of aluminum (Figure 15).
Experiments were performed using a low-speed blowdown wind tunnel, which belongs to the Department of Aerospace Engineering at the Hanoi University of Science and Technology, Vietnam. This wind tunnel had a maximum free-stream velocity in empty test section of 30 m/s that corresponded to Reynolds number 106. The wind tunnel was operated continuously by an 8 kW electric motor. The turbulence level in test section was slightly less than 1%. Free-stream velocity was kept constant in test section within ±2%. Total pressure of free-stream and dynamic pressures were measured by pitot tube within ±2%. Ambient temperature was measured within ±1%. Both experimental and numerical researches were performed at air velocity of 20 m/s and attack angle of 5°.
For the experimental study, 160 pressure taps were applied on the wing model (Figure 15). These pressure taps were connected to an external digital manometer via stainless and silicon tubes. Each pressure tap was measured one time with waiting time of 5 s (average of about 1000 instant values) using the Keyence pressure measurement. The standard deviation of the Keyence pressure measurement errors was within ±0.001 Pa. Moreover, flutter of wing was captured with help of high performance camera.
4.3 Results
The results of IBM method were analyzed at three different instants (Figure 16):
Time T0: initial time when distortion did not occurred
Time T1: time between maximum deformation and non-deformation
The wing deformation was maximum at the tip of the wing and decreased gradually into the root of the wing over time. However, the normal stress was found to have an opposite tendency in comparison with deformation. The maximum normal stress was observed at the root of the wing, while the minimum normal stress was found at the tip of the wing (Figures 17 and 18). It could be explained by the fixed support with fuselage at the root of the wing and free support at the tip of the wing [13]. These remarks were in well agreement with the experimental results within a relative error less than 10% (Table 7).
Figure 17.
Instant normal stress—Rectangular wing.
Figure 18.
Instant normal stress—Trapezoidal wing.
Wing
IBM method (mm)
Experiment method (mm)
Relative error (%)
NACA65A004-rectangular
0.119
0.131
9.7
NACA65A004-trapezoidal
0.030
0.033
8.6
Supercritical-rectangular
0.035
0.039
9.9
Supercritical-trapezoidal
0.034
0.037
9.2
Table 7.
Maximum deformation of the wing tip.
At T0 instant, the normal stress had important value near the wing tip. During flutter behaviors of wing, this important normal stress propagated from the tip of the wing to the root of the wing. The maximum value of the normal stress was found out at the root of the wing and at T2 instant.
With the same airfoil, the rectangular wing was found to be more distorted and have higher maximum deformation and higher maximum normal stress than the trapezoid wing. Thus, 3D-shape wing contributed significantly to the deformation of wing when aeroelasticity phenomenon occurred (Table 7).
With the same 3D-shape wing, the maximum deformation and maximum normal stress of NACA65A004 rectangular wing were higher than those of the rectangle supercritical wing. Meanwhile, the maximum deformation and maximum normal stress of NACA65A004 trapezoidal wing were less than those of the supercritical trapezoidal wing. It could be concluded that the 3D shape of wing played an important role in the durability of the structure (Table 7).
5. Conclusions
The flutter phenomenon of AGARD 445.6 wing was determined by (a) a modal approach for a structural response; (b) an aerodynamic damping coefficient to predict the appearance of flutter phenomenon; (c) a strongly coupled FSI method to predict the aeroelastic response for subsonic and transonic flutter characteristics; (d) an experiment method to predict the aeroelastic response for subsonic flutter characteristics with wing structure; (e) and an IBM method to improve the interface between the fluid and solid of aircraft wing.
In brief, the major results could be summarized as follows:
Experimental results were in good agreement with numerical results within a relative error less than 10%.
During aeroelasticity phenomenon, deformation of the wing tip was maximum while it was minimum at the wing root. The tendency of normal stress was in contrast with deformation. The minimum normal stress was observed at the wing tip, while the maximum normal stress was observed at the wing root;
Geometry of wing (3D shape, airfoil) had a significantly contribution to the deformation of wing when aeroelasticity phenomenon occurred.
For further research of aeroelasticity in the future, both experimental and numerical researches at low and high speed should be performed.
Acknowledgments
A part of this work was supported by the Ministry of Science and Technology in Vietnam through the bilateral and multilateral research project HNQT/SPĐP/12.19.
Appendices and nomenclature
w
structural displacement at any time instant and position
q
generalized displacement vector
[M]
generalized mass matrice
[C]
damping matrice
[K]
stiffness matrices
ϕ
normal modes of the structure
N
total number of modes of the structure
F
generalized force vector
Xi
ith peak of vibration
n
number of period
ζ
aerodynamic damping coefficient
M
Mach number
u
fluid velocity vector
p
fluid pressure
f
force that affected on wing
Re
Reynolds number
Uc
displacement velocity
ωp
angular velocity
xc
center of gravity
θp
rotation of wing
mp
mass of wing
Ip
inertial moment of wing
F
force that created by fluid go pass through the wing
T
moment that created by fluid go pass through the wing
X
coordinate of Eulerian point
N
set of Lagrangian points round Eulerian point l
xl
coordinate of Lagrangian point
∆Ul
volume of effect corresponded to Lagrangian point l
δh
3D delta function
α γ ζ
coefficient of step Runge-Kutta calculation
υ
kinematic viscosity
E11
normal stress following x-coordinates
E22
normal stress following y-coordinates
E33
normal stress following z-coordinates
G
shear stress
ρ
density
Cp
coefficient of pressure
α
attack angle
\n',keywords:"aeroelasticity, flutter, FSI, IBM, ANSYS",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/71605.pdf",chapterXML:"https://mts.intechopen.com/source/xml/71605.xml",downloadPdfUrl:"/chapter/pdf-download/71605",previewPdfUrl:"/chapter/pdf-preview/71605",totalDownloads:186,totalViews:0,totalCrossrefCites:0,dateSubmitted:"December 10th 2018",dateReviewed:"February 13th 2020",datePrePublished:"April 30th 2020",datePublished:"February 10th 2021",dateFinished:"March 30th 2020",readingETA:"0",abstract:"Aeroelasticity phenomena arise when structural deformations induce changes on aerodynamic forces due to airplane structures that are not completely rigid. The additional aerodynamic forces cause an increase in the structural deformations, which leads to greater aerodynamic forces in a feedback process. These interactions may become smaller until reaching a condition of equilibrium or may diverge catastrophically if resonance occurs. Flutter is an instability aeroelasticity phenomenon which is the most difficult to predict. In this chapter, a numerical method and an experimental method were realized to predict aeroelastic response and characteristic parameters of a wing structure. The numerical method was firstly developed based on the interaction between computational fluid dynamic and computational structural dynamic methods using a coupling system, fluid–solid interaction (FSI), in the ANSYS software. Then, an experiment was set up in suitable conditions to study aeroelasticity characteristics with the goal of comparing the numerical results with the experimental results on the same wing structure at low speed. After that, a developed code based on immersed boundary method (IBM) was realized to predict aeroelasticity response and characteristic parameters of the wing structure. AGARD 445.6 wing model was chosen for this developed procedure at high speed. Obtained results were compared to other numerical and experimental results.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/71605",risUrl:"/chapter/ris/71605",signatures:"Hoang Thi Kim Dung and Nguyen Phu Khanh",book:{id:"8558",title:"Aerodynamics",subtitle:null,fullTitle:"Aerodynamics",slug:"aerodynamics",publishedDate:"February 10th 2021",bookSignature:"Mofid Gorji-Bandpy and Aly-Mousaad Aly",coverURL:"https://cdn.intechopen.com/books/images_new/8558.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83880-168-7",printIsbn:"978-1-83880-167-0",pdfIsbn:"978-1-83880-003-1",editors:[{id:"35542",title:"Prof.",name:"Mofid",middleName:null,surname:"Gorji-Bandpy",slug:"mofid-gorji-bandpy",fullName:"Mofid Gorji-Bandpy"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"288958",title:"Associate Prof.",name:"Hoang",middleName:null,surname:"Thi Kim Dung",fullName:"Hoang Thi Kim Dung",slug:"hoang-thi-kim-dung",email:"dung.hoangthikim@hust.edu.vn",position:null,institution:{name:"Hanoi University of Science and Technology",institutionURL:null,country:{name:"Vietnam"}}},{id:"290148",title:"Prof.",name:"Nguyen",middleName:null,surname:"Phu Khanh",fullName:"Nguyen Phu Khanh",slug:"nguyen-phu-khanh",email:"khanh.nguyenphu@hust.edu.vn",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Two-way FSI method",level:"1"},{id:"sec_2_2",title:"2.1 FSI method",level:"2"},{id:"sec_3_2",title:"2.2 Wing model",level:"2"},{id:"sec_4_2",title:"2.3 Results",level:"2"},{id:"sec_4_3",title:"Table 2.",level:"3"},{id:"sec_5_3",title:"2.3.2 Damping analysis",level:"3"},{id:"sec_6_3",title:"Table 3.",level:"3"},{id:"sec_9",title:"3. Experimental method",level:"1"},{id:"sec_9_2",title:"3.1 Experimental setup",level:"2"},{id:"sec_10_2",title:"3.2 Wing model",level:"2"},{id:"sec_11_2",title:"3.3 Results",level:"2"},{id:"sec_13",title:"4. IBM method",level:"1"},{id:"sec_13_2",title:"4.1 Methodology",level:"2"},{id:"sec_14_2",title:"4.2 Wing model",level:"2"},{id:"sec_15_2",title:"4.3 Results",level:"2"},{id:"sec_17",title:"5. Conclusions",level:"1"},{id:"sec_18",title:"Acknowledgments",level:"1"},{id:"sec_18",title:"Appendices and nomenclature",level:"1"}],chapterReferences:[{id:"B1",body:'Edwards JW. Computational Aeroelasticity Challenges and Resources. NASA Technical Report. N89-19264; 1989'},{id:"B2",body:'Liu DD, Sarhaddi D, Piolenc FM. Flutter Prevention Handbook: A Preliminary Collection. Technical report WL–TR–96–3111, Wright Laboratory; 1996'},{id:"B3",body:'Ramsey JK. NASA Aeroelasticity Handbook Volume 2: Design Guides Part 2. Technical Paper NASA/TP—2006-212490/VOL2/PART2, NASA Glenn Research Center; 2006'},{id:"B4",body:'Kolonay RM. Unsteady aeroelastic optimization in the transonic regime [Thesis]. Purdue University; 1996'},{id:"B5",body:'Lee-Rausch EM, Batina JT. Calculation of AGARD Wing 445.6 Flutter using Navier-Stokes Aerodynamics. AIAA Paper No. 93–3476; 1993'},{id:"B6",body:'Başkut E, Akgül A. Development of a closely coupled procedure for dynamic aeroelastic analyses. Scientific Technical Review. 2012;62(2):30-39'},{id:"B7",body:'Pahlavanloo P. Dynamic Aeroelastic Simulation of the AGARD 445.6 Wing using Edge. Technical report FOI-R--2259—SE; 2007'},{id:"B8",body:'Chen X, Zha G-C, Yang M-T. Numerical simulation of 3-D wing flutter with fully coupled fluid-structural interaction. AIAA Paper 2006–0697; 2006'},{id:"B9",body:'Liu F, Cai J, Zhu Y, Tsai HM, Wong ASF. Calculation of wing flutter by a coupled fluid-structure method. Journal of Aircraft. 2001;38(2):334-342'},{id:"B10",body:'Hoang TKD, Nguyen PK, Tran NM. Study of wing flutter by a coupled fluid-structure method. In: Proceeding of 14th Asia Congress of Fluid Mechanics. Vol. 1. 2013. pp. 144-148'},{id:"B11",body:'Hoang TKD, Pham VS, Tran NK, Nguyen DC, Nguyen PK. Aeroelastic analysis on wing structure using immersed boundary method. In: Lecture Notes in Mechanical Engineering. Springer; 2018. pp. P783-P792. DOI: 10.1007/978-981-10-7149-2_55'},{id:"B12",body:'Dugundji J, Dowell E, Perkin B. Subsonic Flutter of Panels on Continuous Elastic Foundations - Experiment and Theory. ASRL Technical Report No.74 4; 1962'},{id:"B13",body:'Yates EC. AGARD standard aeroelastic configurations for dynamic response I-wing 445.6. AGARD Report 765; 1988'},{id:"B14",body:'Ricketts RH. Experimental Aeroelasticity - History, Status and Future in Brief. NASA Technical Memorandum 102651; 1990'},{id:"B15",body:'Heinze S. Aeroelastic Concepts for Flexible Aircraft Structures [Thesis]. Royal Institute of Technology; 2007'},{id:"B16",body:'Achuthan CP, Shanthini G, Shivaprasad MV, Chandra N, Manjuprasad M. Dynamic response and flutter prediction of structures with unknown system parameters using experimental modal parameters. Innovative Systems Design and Engineering. 2011;2(4):23-39'},{id:"B17",body:'Nguyen PK, Mori K, Hoang TKD, Nguyen VH, Nguyen HA. Research on simulation and experiment of dynamic Aeroelastic analysis on wing structure. Applied Mechanics and Materials. 2015;798:541-545. DOI: 10.4028/www/scientific.net/AMM.798.541'},{id:"B18",body:'Tran NK, Dang DC, Dao DH, Nguyen PK, Hoang TKD. Experimental research on the effect of wing structure on aeroelasticity phenomenon. Applied Mechanics and Materials. 2019;889:403-409. DOI: 10.4028/www.scientific.net/AMM.889.403'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Hoang Thi Kim Dung",address:"dung.hoangthikim@hust.edu.vn",affiliation:'
School of Transportation Engineering, Hanoi University of Science and Technology, Vietnam
Faculty of Vehicle and Energy Engineering, Phenikaa University, Vietnam
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In addition, agent’s operations and their coordination within the MG arrangements have been focused by considering the supervision of the entire system autonomously. 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10,000 GBP Monograph - Long Form
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4,000 GBP Compacts Monograph - Short Form
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*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
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Services included are:
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An online manuscript tracking system to facilitate your work
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Personal contact and support throughout the publishing process from your dedicated Author Service Manager
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English language copyediting and proofreading, including the correction of grammatical, spelling, and other common errors
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XML Typesetting and pagination - web (PDF, HTML) and print files preparation
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Discoverability - electronic citation and linking via DOI
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Permanent and unrestricted online access to your work
What isn't covered by the Open Access Publishing Fee?
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If your manuscript:
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\\n\\t
Exceeds 20 pages (for chapters in Edited Volumes), an additional fee of 40 GBP per page will be required
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If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
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\\n\\n
Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
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Open Access Funding
\\n\\n
To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at oapf@intechopen.com for further details or assistance.
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For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
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Added Value of Publishing with IntechOpen
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Choosing to publish with IntechOpen ensures the following benefits:
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Indexing and listing across major repositories, see details ...
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Long-term archiving
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Visibility on the world's strongest OA platform
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Live Performance Metrics to track readership and the impact of your chapter
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Dissemination and Promotion
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Benefits of Publishing with IntechOpen
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Proven world leader in Open Access book publishing with over 10 years experience
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+5,200 OA books published
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Most competitive prices in the market
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Fully compliant with OA funding requirements
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Optimized processes, enabling publication between 8 and 12 months
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Personal support during every step of the publication process
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+146,150 citations in Web of Science databases
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Currently strongest OA platform with over 150 million downloads
As a gold Open Access publisher, an Open Access Publishing Fee is payable on acceptance following peer review of the manuscript. In return, we provide high quality publishing services and exclusive benefits for all contributors. IntechOpen is the trusted publishing partner of over 128,000 international scientists and researchers.
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The Open Access Publishing Fee (OAPF) is payable only after your full chapter, monograph or Compacts monograph is accepted for publication.
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OAPF Publishing Options
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1,400 GBP Chapter - Edited Volume
\n\t
10,000 GBP Monograph - Long Form
\n\t
4,000 GBP Compacts Monograph - Short Form
\n
\n\n
*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
\n\n
Services included are:
\n\n
\n\t
An online manuscript tracking system to facilitate your work
\n\t
Personal contact and support throughout the publishing process from your dedicated Author Service Manager
\n\t
Assurance that your manuscript meets the highest publishing standards
\n\t
English language copyediting and proofreading, including the correction of grammatical, spelling, and other common errors
\n\t
XML Typesetting and pagination - web (PDF, HTML) and print files preparation
\n\t
Discoverability - electronic citation and linking via DOI
\n\t
Permanent and unrestricted online access to your work
What isn't covered by the Open Access Publishing Fee?
\n\n
If your manuscript:
\n\n
\n\t
Exceeds 20 pages (for chapters in Edited Volumes), an additional fee of 40 GBP per page will be required
\n\t
If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
\n
\n\n
Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
\n\n
Open Access Funding
\n\n
To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at oapf@intechopen.com for further details or assistance.
\n\n
For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
\n\n
Added Value of Publishing with IntechOpen
\n\n
Choosing to publish with IntechOpen ensures the following benefits:
\n\n
\n\t
Indexing and listing across major repositories, see details ...
\n\t
Long-term archiving
\n\t
Visibility on the world's strongest OA platform
\n\t
Live Performance Metrics to track readership and the impact of your chapter
\n\t
Dissemination and Promotion
\n
\n\n
Benefits of Publishing with IntechOpen
\n\n
\n\t
Proven world leader in Open Access book publishing with over 10 years experience
\n\t
+5,200 OA books published
\n\t
Most competitive prices in the market
\n\t
Fully compliant with OA funding requirements
\n\t
Optimized processes, enabling publication between 8 and 12 months
\n\t
Personal support during every step of the publication process
\n\t
+146,150 citations in Web of Science databases
\n\t
Currently strongest OA platform with over 150 million downloads
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