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
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"3395",leadTitle:null,fullTitle:"Human Papillomavirus and Related Diseases From Bench to Bedside A Diagnostic and Preventive Perspective",title:"Human Papillomavirus and Related Diseases",subtitle:"From Bench to Bedside - A Diagnostic and Preventive Perspective",reviewType:"peer-reviewed",abstract:"Cervical cancer is the second most prevalent cancer among women worldwide, and infection with Human Papilloma Virus (HPV) has been identified as the causal agent for this condition. 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One of the least studied factors that affects neurogenesis are chromosomal aberrations. Down syndrome (DS) results from the extra copy of chromosome 21 occurring with a prevalence of 1 in 733 live births (Canfield et al., 2006). Subjects with DS show developmental regression, diminished cognitive ability, and autonomic dysfunction (Antonarakis & Epstein, 2006; Chapman & Hesketh, 2000). The DS brain is severely affected showing a reduction in both overall size and of particular areas (frontal cortex, hippocampus, cerebellum, and brainstem) due to a reduced number of neurons (Aylward et al., 1997, 1999; Kesslak et al., 1994; Pinter et al., 2001; Raz et al., 1995; Wisniewski et al., 1984).
1.1. Neurogenesis in subjects with DS
Very little data is available describing neurognesis in subjects with DS. In hippocampal DG and neocortex of fetuses with DS the number of proliferating cells was found to be significantly reduced (Contestabile et al., 2007). These reductions were mainly due to a reduced number of cycling cells in S phase (Contestabile et al., 2007). Both a reduction in neurogenesis and significantly higher incidence of apoptotic cell death in the hippocampal region of fetuses with DS has been noted (Guidi et al., 2008). Also, trisomy 21 significantly modify cell phenotypes producing higher numbers of cycling cells going to a glial phenotype and less cells expressing neuronal markers (Guidi et al., 2008). Detailed analysis of the consequences of both reduced neurogenesis and increased apoptosis in fetuses with DS, revealed a severe reduction in the volume and cell number of investigated brain areas (Guidi et al., 2008). More recently, significant neurogenesis impairments were also revealed in the cerebellum of fetuses with DS (Guidi et al., 2010). However, apoptotic cell death was similar in the cerebellum in fetuses with DS vs. controls (Guidi et al., 2010). The differences between the levels of apoptosis in hippocampus vs. cerebellum in fetuses with DS points to different mechanisms for the reduced cell number in hippocampus and cerebellum in DS. For the hippocampus, a reduction of neurogenesis, increased apoptosis and changing cell phenotypes in favor of glia may underlie reduced cell number in fetuses with DS. As for the cerebellum, only a reduction in neurogenesis may be the main factor in decreased cerebellar volume in fetuses with DS.
It seems that genetic dissections of mouse partial trisomy 16 (Ts65Dn model) did not restore reduced neurogenesis. Indeed, Ts1Cje and Ts2Cje mouse models of DS showed a similar degree of impairment in adult neurogenesis (Hewitt et al., 2010; Ishihara et al., 2010).
To solve these conflicting results in DS mouse models a recent study was initiated to examine young adult neurogenesis, and we also expanded this study to include DG, cortex and corpus callosum (CC) at three different levels. We chose to investigate whether or not trisomy has any affect on neurogenesis in Ts65Dn mice. To carry out this work we injected BrdU in 2N and Ts65Dn mice. Combining BrdU immunoreactivity and high resolution confocal microscopy, we examined the number of BrdU-positive (BrdU+) neurons in DG, cortex and CC at three different levels: rostral, middle and caudal. Comparing 2N and Ts65Dn mice, we discovered significant decreases in the density of BrdU+ cells in trisomic mice in the cortex and DG. We found that the number of cells per cluster was significantly reduced in both the rostral and the caudal parts of DG in the Ts65Dn vs. 2N. This change resulted in reduced cell density in the caudal DG, while the density of clusters was not altered. Our findings are evidence for decreased neurogenesis in young adult cortex and DG of Ts65Dn mice and indicate neurogenesis as a potential target for pharmacological intervention to avert neuronal plasticity in individuals with DS.
2. Materials and methods
All experiments were conducted in accordance with the National Institutes of Health guidelines for the care and use of animals and with an approved animal protocol from the Stanford University Institutional Animal Care and Use Committee. All efforts were made to minimize animal stress and discomfort.
2.1. Mice husbandry
Details of maintenance and using Ts65Dn mouse colony were described previously (Belichenko et al., 2004). The Ts65Dn mouse colony was maintained for more than 10 generations by crossing B6EiC3Sn-Ts(1716)65Dn females (Jackson Laboratory, Bar Harbor, ME) with B6EiC3Sn F1/J A/a males (Jackson Laboratory). This breeding scheme was used because trisomic mice breed very poorly or not at all when inbred; the B6C3 background has been the most successful. To distinguish 2N from Ts65Dn mice, genomic DNA was extracted from tail samples. A quantitative PCR protocol (provided by The Jackson laboratory) was used to measure Mx1 gene expression, which is present in three copies in Ts65Dn. Each mouse was genotyped twice. Male littermates mice were used in all studies at ages 2-3 months.
2.2. BrdU injections and immunofluorescent staining
In the beginning of experiment we weighed mice. Each animal was injected once a day for 6 consecutive days with 5-bromo-2′-deoxyuridine (BrdU, 10 mg/ml in saline, i.p.) (Cat. # B9285, Sigma-Aldrich Corp., St. Louis, MO, USA) to a final dose of 50 mg/kg body weight. Twenty four hours after the last injection, animals were deeply anesthetized with sodium pentobarbital (200 mg/kg i.p.) (Abbott Laboratories, North Chicago, IL, USA), again weighed, and transcardially perfused for 1 minute with 0.9% sodium chloride (10 ml) and then for 20 minutes with 4% paraformaldehyde in 0.1 M phosphate-buffered saline (PBS), pH 7.4 (200 ml). After perfusion, the brain was immediately removed and postfixed for another 24 hours. The weight of the entire brain (including the olfactory bulbs, cerebellum, and brainstem along with the cervical spinal cord through C1–C2) was recorded. The brain was then sectioned coronally at 100-μm with a Vibratome (series 1000, TPI Inc., St. Louis, MO, USA), and sections were placed in 0.9% NaCl solution. Immunofluorescence method with anti-BrdU antibody was used to reveal BrdU+ cells as follows. Free-floating sections were rinsed twice in saline (0.9 % NaCl) for 10 min at RT, and then pretreated with 1M HCl for 30 minutes at 37ºC. Sections were neutralized by rinsing 3 times in PBS and then pre-incubated in a solution of 0.1 M PBS containing 5% non-fat milk and 0.3% Triton-X 100 (PBS+), for 1 hour at room temperature. Then sections were incubated overnight at 4oC with primary rat anti-BrdU antibody (Cat. #MCA2060, Serotec, Raleigh, NC, USA) at a dilution 1:100 in PBS+. Sections were rinsed in PBS (20 minutes, three changes) and incubated for 1 hour at room temperature with biotinylated donkey anti-rat IgG (1:200; Jackson ImmunoResearch Labs, West Grove, PA). After being rinsed with PBS (20 minutes, three changes), sections were incubated with FITC-conjugated streptavidin (1:500; Jackson ImmunoResearch Labs, West Grove, PA) for 1 hour at room temperature. Following further careful rinsing, the sections were mounted on microscope glass slides and coverslipped with 90% glycerol in PB.
2.3. Confocal microscopy imaging, cell quantification, cluster and statistical analyses
To study cell proliferation and clustering in 2N and Ts65Dn mice we used confocal microscopy imaging of BrdU+ cells in the cortex, hippocampus and CC. Confocal imaging of brain slices labeled with one fluorophores was performed as previously described (Belichenko et al., 2004). In brief, slices with BrdU+ cells were examined and scanned in a Radiance 2000 confocal microscope (BioRad, Hertfordshire, United Kingdom) attached to a Nikon Eclipse E800 fluorescence microscope. LaserSharp software (Bio Rad) was used to establish optimal conditions for collecting images. The laser was an argon/krypton mixed gas laser with exciting wavelengths for FITC (488 λ). The emission was registered with HQ515/30 “green” filter. Sections with FITC staining of BrdU immunoreactivity were studied under the following optimal conditions: the lens was a x10 objective (Nikon; Plan Fluor x10/0.30); laser power was 10%; the zoom factor was 1; scan speed was 500 lines per second; each optical section was the result of 3 scans followed by Kalman filtering; the size of the image was 512 x 512 pixels (i.e., 1208 x 1208 µm).
LazerPix software (Bio Rad) analysis of confocal images was used to measure the area or length of investigated brain structures, and for quantitative analysis of BrdU+ cells. Three slices per mouse (500 μm apart) were used. The location of each coronal section was designated based on its relative position to bregma in mm (Hof et al., 2000). Rostral section was corresponded to bregma -1.60 mm level, middle section – to bregma -2.10 mm level, and caudal section to bregma -2.60 mm level. Entire DG at these three different locations was imaged. CC was imaged from midline and then for 1200 μm to the left or right extension at the same three different locations. Based on mouse brain atlas (Hof et al., 2000), cortex were correspondent to motor cortex at rostral and middle sections and to visual cortex at caudal section). Images from the both the left and right side for each mouse brain were analyzed. To count number of BrdU+ cells, we first outlined the area of interest and measure area or length (in a case of DG). Next, for each image, the intensity thresholds were estimated by analyzing the distribution of pixel intensities in the image areas that did not contain immunoreactivity. This value, the background threshold, was then subtracted and number of BrdU+ cells was counted. In addition each BrdU+ cells were traced manually and their XY coordinates were exported to Excel. The number of BrdU+ cell in each hemisphere was expressed for DG as per 100-μm length of neurogenic subgranule zone, and for cortex and CC as per 1 mm2. We also counted the occurrence of BrdU+ cell clusters. To quantify the number of clusters we used previously established criteria (Palmer et al., 2000), where cluster was defined as a contiguous group of cells separated by less than 25 μm. Special macro was design in Excel program for cluster counting. For every section, X and Y coordinates of individual BrdU+ cell were recorded using LaserPix software (BioRad). Distance between all pairs of the BrdU+ cells within one section were calculated using an Excel Microsoft macro, and the cells with distances < 25 μm were regarded as belonging to a cluster. All analyses were performed by the same investigator blinded to mice genotype.
Digital images were imported, enhanced for brightness and contrast, assembled and labeled in Adobe Photoshop CS2 9.0.2, and archived. Figures were printed with a Phaser 7300 color printer (Tektronix by Xerox, Norwalk, CT).
The data for body and brain weights, total number of BrdU+ cells, their coordinates and cluster evaluations were exported to Excel (Microsoft, Redmond, WA) and statistical comparisons were performed using two-way analysis of variance (ANOVA) and for two samples using two-tailed Student’s t-tests. All results are expressed as mean ± SEM, and P values < 0.05 were considered to be significant.
3. Results
3.1. Body and brain weights
The body weight of 2N and Ts65Dn mice at 2-3 months was similar (2N: 31.1 ± 1.6 g, n = 6; Ts65Dn = 26.7 ± 2.3 g, n = 5; P = 0.14). The brain weight was also unchanged (2N: 0.43 ± 0.01 g, n = 6; Ts65Dn = 0.43 ± 0.01 g, n = 5; P =0.60). Of note, there was no effect of the BrdU injection on changes in body weight during 6 day injections since no significant differences were found between 2N and Ts65Dn mice (2N: -0.60 ± 0.29 g, n = 6; Ts65Dn = -0.20 ± 0.51 g, n = 5; P =0.49). These mice also showed no aversive or any other neurological symptoms during injection.
3.2. Changes in BrdU+ cells number and in cell cluster density in Ts65Dn mice
We examined the density of BrdU+ cells in DG of hippocampus, cortex and CC in 2N and Ts65Dn male mice (Table 1, Figs. 1, 2). The BrdU+ cells were bright fluorescent, allowing for a detailed quantitative analysis by confocal microscopy (Figs. 1a,\n\t\t\t\t\t2a). For this analysis, the number of BrdU+ cells per 100 μm length of subgranule zone for DG or per 1 mm2 area of cortex or CC was counted to define cell density (Table 1). In addition we measured the number of cell cluster, the number of BrdU+ cells per cluster and the frequency distribution of BrdU+ cells per cluster (Table 1; Figs. 1 d, e; 2 d,e).
Comparing BrdU+ cell densities in 2N and Ts65Dn mice, there was a statistically significant decrease in the caudal part of DG (by 27%) and in the rostral part of motor cortex (by 36%; P < 0. 01; Table 1). Interestingly, BrdU+ neurons in the inferior blade were on average 30% fewer than in the superior blade for 2N, and 23% fewer for Ts65Dn mice (P < 0.01; Table 1). BrdU+ cell density were similar for CC in 2N and Ts65Dn mice, and 33% more in caudal then rostral CC for 2N mice (P < 0.01; Table 1).
Comparing BrdU+ cell cluster densities in 2N and Ts65Dn mice, there was a statistically significant decrease in the rostral part of motor cortex (by 29%; P < 0. 01; Table 1). In the inferior blade there were on average 9% fewer than in superior blade for 2N, and 25% fewer for Ts65Dn mice (P < 0.05; Table 1). Interestingly, in the DG the BrdU+ cell cluster density was not different in 2N and Ts65Dn mice (Table 1).
We next quantified the number of cells per cluster (Table 1). As compared to 2N mice, significantly lower numbers of BrdU+ cells per cluster were present in rostral (mainly due to superior blade, P < 0.003; Table 1) and in the caudal part of DG in Ts65Dn mice (P = 0.03; Table 1), and in the rostral part of motor cortex in Ts65Dn mice (P < 0.01; Table 1). Comparing the superior and inferior blades in 2N mice, numbers of cells per cluster were ~1.5 times higher in the rostral and middle parts of the superior blade of the DG in 2N mice (P < 0.02; Table 1).
In conclusion, significant differences in the number of BrdU+ cells, cell cluster densities, and in number of BrdU+ cells per cluster were evident for Ts65Dn mice as compared to their 2N cohorts. These findings are evidence for reduced neurogenesis in both DG and cortex due to mouse chromosome 16 trisomy.
Figure 1.
Morphometry of BrdU+ cells in dentate gyrus in 2N and Ts65Dn mice. (a) Confocal image of BrdU+ cells in caudal part of dentate gyrus of 2N and Ts65Dn mice. BrdU+ cell density in superior (b) and inferior blades (c) of dentate gyrus. Note a significant reduction of BrdU+ cell in caudal DG in Ts65Dn mice. The number of cells per cluster in rostral (d) and caudal (e) part of DG. Scale bar = 50 μm.
Figure 2.
Neurogenesis in cortex in 2N and Ts65Dn mice. (a) Confocal image of BrdU+ cells in the rostral part of cortex of 2N and Ts65Dn mice. (b) BrdU+ cell density in cortex. Note significant reduction of BrdU+ cell in rostral cortex in Ts65Dn mice. (c) The number of cells per cluster in rostral part of cortex. Scale bar = 100 μm.
cell density
cluster density
# cells per cluster
2N
Ts65Dn
2N
Ts65Dn
2N
Ts65Dn
Dentate gyrus
Rostral
Total
3.06 ± 0.27
2.87 ± 0.25
1.01 ± 0.08
1.22 ± 0.09
3.05 ± 0.22
2.39 ± 0.16a
Superior blade
3.61 ± 0.29
3.13 ± 0.36
1.02 ± 0.11
1.25 ± 0.09
3.69 ± 0.29
2.47 ± 0.21a
Inferior blade
2.55 ± 0.25b
2.55 ± 0.25
0.99 ± 0.08
1.19 ± 0.13
2.65 ± 0.29b
2.42 ± 0.37
Middle
Total
2.88 ± 0.17
2.77 ± 0.15
1.21 ± 0.05
1.17 ± 0.08
2.56 ± 0.20
2.52 ± 0.12
Superior blade
3.33 ± 0.21
3.01 ± 0.17
1.23 ± 0.05
1.24 ± 0.09
3.01 ± 0.26
2.66 ± 0.12
Inferior blade
2.28 ± 0.18b
2.46 ± 0.20c
1.19 ± 0.08
1.08 ± 0.14
1.96 ± 0.17b
2.51 ± 0.34
Caudal
Total
2.73 ± 0.19
2.00 ± 0.08a
1.13 ± 0.04
1.10 ± 0.08
2.59 ± 0.31
2.01 ± 0.12a
Superior blade
3.09 ± 0.27
2.31 ± 0.12a
1.21 ± 0.07
1.22 ± 0.10
2.84 ± 0.27
1.69 ± 0.16a
Inferior blade
2.20 ± 0.19b
1.55 ± 0.15a,c
1.10 ± 0.06b
0.92 ± 0.07c
2.21 ± 0.22
1.69 ± 0.16a
Cortex
Rostral
21.1 ± 2.2
14.6 ± 1.4a
14.4 ± 1.4
10.2 ± 1.2a
1.46 ± 0.04
1.24 ± 0.05a
Middle
22.3 ± 2.9
19.5 ± 1.8
15.9 ± 1.5
14.9 ± 1.7
1.25 ± 0.03
1.22 ± 0.02
Caudal
25.0 ± 2.5
19.7 ± 2.7
14.9 ± 1.7
13.9 ± 1.7
1.30 ± 0.03
1.26 ± 0.04
Corpus callosum
Rostral
74.7 ± 11.3
87.2 ± 12.6
56.7 ± 3.1
53.0 ± 5.6
1.15 ± 0.05
1.16 ± 0.03
Middle
96.1 ± 15.8
77.3 ± 13.4
64.1 ± 7.2
62.6 ± 7.6
1.28 ± 0.07
1.22 ± 0.03
Caudal
111.2 ± 11.8b
105.1 ± 16.1
73.8 ± 7.3
73.2 ± 9.4
1.36 ± 0.06
1.32 ± 0.04
The number of mice used was as follows: 2N/Ts65Dn = 6/5.
Each value represents the mean ± SEM.
BrdU+ cells and clusters densities are expressed as: for FD per 100 μm length of subgranule zone, for cortex and CC per 1 mm2.
a, P < 0.05, significantly different from 2N mice.
b, P < 0.05, significantly different between 2N mice.
c, P < 0.05, significantly different between Ts65Dn mice.
Our study in the Ts65Dn mouse model of DS presents novel evidence of altered neurogenesis in adult young mice (2-3 months of age). Significant increases in the number of clusters containing single BrdU+ cells in Ts65Dn mice point to severely affected cell proliferation. Our present data are in agreement with previous data (Clark et al., 2006) and conflicting with Rueda et al. (2005) data on young adult Ts65Dn mice. The discrepancy with the Rueda et al. (2005) results likely result from several factors including the different gender of mice (we used only male mice and no gender of studied mice were mentioned in Rueda et al., 2005), the different brain areas investigated (we studied rostral, middle, and caudal parts of hippocampus, cortex and CC separately, while in Rueda et al. (2005) the entire hippocampus was studied). The BrdU injection protocol was also different. We used standard a procedure with BrdU injection during 6 days, while Rueda et al., (2005) used a 12 days injection approach.
The majority of BrdU+ cells in adult brain during the proliferation phase formed clusters (Palmer et al., 2000; Seki et al., 2007). Data on neurogenesis in adult rat hippocampus suggests that newly-born cells appeared to stay in clusters for a few days and then migrate from clusters (Seki et al., 2007). Currently, little is known about the molecular mechanisms of cluster formation. Previous reports suggested that cell clustering supports intercellular contacts and/or signals that encourage neurogenesis (Seki et al., 2007). It is possible that the initial formation of a cluster is triggered by a certain factor, which is not affected in Ts65Dn mice. Thus, we have similar cluster density in Ts65Dn vs. 2N mice. The ‘just-divided’ cells could be divided further, thus resulting in a cluster (Seki et al., 2007). However, this could be only accomplished when the cell is going through all cycles. Indeed, as was shown previously (Contestabile et al., 2008) that the dividing in Ts65Dn cells are ‘stuck’ in S phase, thus decreasing the probability of cell cycle re-entry. This delay could suspend the second and the following divisions, thus resulting in a reduced number of the newly-born cells per cluster. Interestingly, we observed that the number of cells per cluster was reduced only in the rostral and caudal, but not in the middle part of the Ts65Dn hippocampus. The exact nature of this phenomenon is not clear yet, but may result from differences in the structure and function of hippocampus along the rostro-caudal axis. Indeed, neuronal network architecture is different in hippocampus (Witter et al., 2000).
Reduction in the number of cells per cluster leads to a reduction of total number of newly-born neurons in the Ts65Dn hippocampus. It was shown previously that LTP in the DG depends strongly on neurogenesis, and that a blockade of neurogenesis results in reduced synaptic plasticity (Snyder et al., 2001). Because we observed that LTP in the DG of Ts65Dn mice is significantly diminished (Kleschevnikov et al., 2004), it is tempting to assume that reduced neurogenesis is one of the factors contributing to this abnormality. It is clear that alteration in prenatal growth of the cortex and hippocampus in trisomic mice is due to a longer cell cycle and reduced neurogenesis (Chakrabarti et al., 2007; Contestabile et al., 2007).
We further propose that alteration of neurogenesis may also affect the balance between excitation and inhibition. Indeed, the putative young neurons are completely unaffected by GABA(A) inhibition (Wang et al., 2000). Reduced number of such disinhibited neurons in DG of Ts65Dn mice could thus result in elevation of the overall efficiency of the inhibitory system (Belichenko et al., 2009; Kleschevnikov et al., 2004). The excitatory/inhibitory neuron ratio could be affected also in other bran regions. The new granule cells of the DG, olfactory bulb, and cerebellum and the new cells in cortex are constantly produced during adult neurogenesis. However, there are many differences between these cells. For example, in the olfactory bulb and neocortex the newly-born cells are mainly inhibitory (GABAergic) (reviewed in Cameron & Dayer, 2008). Reduced neurogenesis in these regions could result in relative disinhibition and, thus, could be regarded as a factor contributing to epilepsy in DS (Goldberg-Stern et al., 2001; Menendez, 2005; Pueschel et al., 1991). In contrast, DG and cerebellar granule cells are excitatory (glutamatergic). However, this question needs to be studied in greater detail. The influence of chromosomal aberration on the transition from proliferating stage to differentiated stage into either glutamatergic or GABA-ergic neurons should be also studied.
Numerous factors can be implicated in the control of adult neurogenesis, including chromosomal aberrations. Although the exact mechanism(s) of influence of partial or complete trisomy on neurogenesis is not known, we can extract some data from the scattered information. Impaired neurogenesis has been described not only in Ts65Dn (Rueda et al., 2005; Clark et al., 2006; Lorenzi and Reeves, 2006; Constestabile et al., 2007; Chakrabarti et al., 2007; Bianchi et al., 2010) and Ts2Cje (Ishihara et al., 2010) mouse models of DS, but also in TsCje1 mice (Hewitt et al., 2010; Ishihara et al., 2010) with smaller triplicated chromosomal region. Genetic dissection approaches (Ts65Dn vs. Ts1Cje) point out to the same genes in smaller triplicated region, i.e. Itsn1, Dyrk1A, Olig2 may involve in neurogenesis (Hewitt et al., 2010; Ishihara et al., 2010). It has been proposed that overexpressions of Dyrk1A in trisomic segment may be responsible for impaired neurogenesis in Ts65Dn, Ts2Cje, and Ts1Cje mouse models of DS (Canzonetta et al., 2008; Ishihara et al., 2010). These authors also suggest that altered neurogenesis in the Ts1Cje mouse is due to a reduction in neuronal progenitors and neuroblasts rather than neural stem cells (Hewitt et al., 2010). The further identification and characterization of triplicated genes in altered neurogenesis may significantly contribute to understanding the neurobiology of DS and may lead to the development of pharmacotherapy for DS.
5. Conclusion
Down syndrome (DS) is a neurodevelopmental disorder caused by the triplication of chromosome 21. Few studies have explored neurogenesis in mouse models of DS and these have produced conflicting results on the alteration of neurogenesis. Using confocal microscopy analysis we have examined adult neurogenesis in the hippocampus (dentate gyrus, DG), motor cortex and corpus callosum (CC) of male wild-type (2N) and Ts65Dn mice at age 2-3 months. In Ts65D we found significant decreases in the BrdU+ cells density in DG and motor cortex. BrdU+ cell cluster density were higher in rostral motor cortex in Ts65Dn. Number of BrdU+ cells per cluster were significantly lower in DG and motor cortex of Ts65Dn mice, mainly due to the presence of single cell clusters. Density of BrdU+ cells was significantly lower in the inferior than in the superior blade of DG. Thus, we show for the first time a lower density of BrdU+ cells in Ts65Dn mice. Our findings are evidence on a deficiency of adult neurogenesis in Ts65Dn mouse model of DS. Moreover, we propose a correlation of the present data with our previously published data on alteration of LTP due to excessive inhibition in Ts65Dn mouse model of DS. The new findings can shed light on possible mechanisms underlying the changes in the Ts65Dn neurogenesis, synaptic structure and function that were described previously. Based on our data and recent studies we reasonable suggested that new complex therapies should improve neurogenesis, and as consequence also learning and memory.
Acknowledgments
We thank Dr. Theo D. Palmer and Dr. William C. Mobley for their critical inputs in the beginning of this work. We also thank Michael Maloney for critically reading the article. This work was supported by the Larry L Hillblom Foundation and by the Down Syndrome Research and Treatment Foundation.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/18444.pdf",chapterXML:"https://mts.intechopen.com/source/xml/18444.xml",downloadPdfUrl:"/chapter/pdf-download/18444",previewPdfUrl:"/chapter/pdf-preview/18444",totalDownloads:1818,totalViews:154,totalCrossrefCites:1,totalDimensionsCites:4,hasAltmetrics:0,dateSubmitted:"December 8th 2010",dateReviewed:"April 11th 2011",datePrePublished:null,datePublished:"August 29th 2011",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/18444",risUrl:"/chapter/ris/18444",book:{slug:"genetics-and-etiology-of-down-syndrome"},signatures:"Pavel V. Belichenko and Alexander M. Kleschevnikov",authors:[{id:"58261",title:"Prof.",name:"Pavel V.",middleName:"V.",surname:"Belichenko",fullName:"Pavel V. Belichenko",slug:"pavel-v.-belichenko",email:"pavel_belichenko@yahoo.com",position:null,institution:null},{id:"92944",title:"Prof.",name:"Alexander M.",middleName:"M.",surname:"Kleschevnikov",fullName:"Alexander M. Kleschevnikov",slug:"alexander-m.-kleschevnikov",email:"akleschevnikov@yahoo.com",position:null,institution:{name:"University of California, San Diego",institutionURL:null,country:{name:"United States of America"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Neurogenesis in subjects with DS ",level:"2"},{id:"sec_2_2",title:"1.2. Neurogenesis in mouse models of DS",level:"2"},{id:"sec_4",title:"2. Materials and methods",level:"1"},{id:"sec_4_2",title:"2.1. Mice husbandry",level:"2"},{id:"sec_5_2",title:"2.2. BrdU injections and immunofluorescent staining",level:"2"},{id:"sec_6_2",title:"2.3. Confocal microscopy imaging, cell quantification, cluster and statistical analyses",level:"2"},{id:"sec_8",title:"3. Results",level:"1"},{id:"sec_8_2",title:"3.1. Body and brain weights",level:"2"},{id:"sec_9_2",title:"3.2. Changes in BrdU+ cells number and in cell cluster density in Ts65Dn mice",level:"2"},{id:"sec_11",title:"4. Discussion ",level:"1"},{id:"sec_12",title:"5. Conclusion",level:"1"},{id:"sec_13",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'AntonarakisS. E.EpsteinC. J.2006The challenge of Down syndrome. Trends Mol Med,\n\t\t\t\t\t1210473479'},{id:"B2",body:'AylwardE. H.LiQ.HabbakQ. R.WarrenA.PulsiferM. B.BartaP. E.JerramM.PearlsonG.1997Basal ganglia volume in adults with Down syndrome. Psychiatry Res,\n\t\t\t\t\t7427382'},{id:"B3",body:'AylwardE. H.LiQ.HoneycuttN. A.WarrenA. C.PulsiferM. B.BartaP. E.ChanM. D.SmithP. D.JerramM.PearlsonG. D.1999MRI volumes of the hippocampus and amygdala in adults with Down’s syndrome with and without dementia. Am J Psychiatry,\n\t\t\t\t\t1564564568'},{id:"B4",body:'BelichenkoP. V.KleschevnikovA. 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R.2006Ablation of hippocampal neurogenesis impairs contextual fear conditioning and synaptic plasticity in the dentate gyrus. Proc Natl Acad Sci U S A,\n\t\t\t\t\t103461750117506'},{id:"B51",body:'SekiT.NambaT.MochizukiH.OnoderaM.2007Clustering, migration, and neurite formation of neural precursor cells in the adult rat hippocampus. J Comp Neurol,\n\t\t\t\t\t5022275290'},{id:"B52",body:'ShorsT. J.TownsendD. A.ZhaoM.KozorovitskiyY.GouldE.2002Neurogenesis may relate to some but not all types of hippocampal-dependent learning. Hippocampus,\n\t\t\t\t\t125578584'},{id:"B53",body:'SiareyR. J.StollJ.RapoportS. I.GaldzickiZ.1997Altered long-term potentiation in the young and old Ts65Dn mouse, a model for Down Syndrome. Neuropharmacology,\n\t\t\t\t\t3611-1215491554'},{id:"B54",body:'SingerB. H.GamelliA. E.FullerC. L.TemmeS. J.ParentJ. M.MurphyG. G.2011Compensatory network changes in the dentate gyrus restore long-term potentiation following ablation of neurogenesis in young-adult mice. 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T.WisniewskiT.2010The neuropathology of autism: defects of neurogenesis and neuronal migration, and dysplastic changes. Acta Neuropathol,\n\t\t\t\t\t1196755770'},{id:"B60",body:'WinnerB.KohlZ.GageF. H.2011Neurodegenerative disease and adult neurogenesis. Eur J Neurosci,\n\t\t\t\t\t33611391151'},{id:"B61",body:'WisniewskiK. E.Laure-KamionowskaM.WisniewskiH. M.1984Evidence of arrest of neurogenesis and synaptogenesis in brains of patients with Down’s syndrome. N Engl J Med,\n\t\t\t\t\t3111811871188'},{id:"B62",body:'WitterM. P.WouterloodF. G.NaberP. A.Van HaeftenT.2000Anatomical organization of the parahippocampal-hippocampal network. Ann N Y Acad Sci,\n\t\t\t\t\t911No., 124'},{id:"B63",body:'YoneyamaM.ShibaT.HasebeS.OgitaK.2011Adult Neurogenesis Is Regulated by Endogenous Factors Produced During Neurodegeneration. J Pharmacol Sci, Vol. No., 18'},{id:"B64",body:'YuY.HeJ.ZhangY.LuoH.ZhuS.YangY.ZhaoT.WuJ.HuangY.KongJ.TanQ.LiX. M.2009Increased hippocampal neurogenesis in the progressive stage of Alzheimer’s disease phenotype in an APP/PS1 double transgenic mouse model. Hippocampus,\n\t\t\t\t\t191212471253'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Pavel V. Belichenko",address:"",affiliation:'
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Ordonez, Gabriel Fornieles, Alejandra Camacho, Miguel A. Rosety, Antonio J Diaz, Ignacio Rosety, Natalia Garcia and Manuel Rosety-Rodriguez",authors:[{id:"156546",title:"Dr",name:"Francisco Javier",middleName:null,surname:"Ordonez",fullName:"Francisco Javier Ordonez",slug:"francisco-javier-ordonez"}]},{id:"43380",title:"Heart Diseases in Down Syndrome",slug:"heart-diseases-in-down-syndrome",signatures:"A. K. M. Mamunur Rashid",authors:[{id:"156647",title:"Dr.",name:"A K M Mamunur",middleName:null,surname:"Rashid",fullName:"A K M Mamunur Rashid",slug:"a-k-m-mamunur-rashid"}]},{id:"43381",title:"Myeloid Leukemia Associated with Down Syndrome",slug:"myeloid-leukemia-associated-with-down-syndrome",signatures:"Kazuko Kudo",authors:[{id:"155649",title:"Dr.",name:"Kazuko",middleName:null,surname:"Kudo",fullName:"Kazuko Kudo",slug:"kazuko-kudo"}]},{id:"43385",title:"Molecular Pathways of Down Syndrome Critical Region Genes",slug:"molecular-pathways-of-down-syndrome-critical-region-genes",signatures:"Ferdinando Di Cunto and Gaia Berto",authors:[{id:"157492",title:"Prof.",name:"Ferdinando",middleName:null,surname:"Di Cunto",fullName:"Ferdinando Di Cunto",slug:"ferdinando-di-cunto"},{id:"158844",title:"Dr.",name:"Gaia",middleName:null,surname:"Berto",fullName:"Gaia Berto",slug:"gaia-berto"}]},{id:"43386",title:"Risk Factors for Down Syndrome Birth: Understanding the Causes from Genetics and Epidemiology",slug:"risk-factors-for-down-syndrome-birth-understanding-the-causes-from-genetics-and-epidemiology",signatures:"Sujay Ghosh and Subrata Kumar Dey",authors:[{id:"31178",title:"Prof.",name:"Subrata",middleName:"Kumar",surname:"Dey",fullName:"Subrata Dey",slug:"subrata-dey"},{id:"125697",title:"Prof.",name:"Sujoy",middleName:null,surname:"Ghosh",fullName:"Sujoy Ghosh",slug:"sujoy-ghosh"}]},{id:"42500",title:"RCAN1 and Its Potential Contribution to the Down Syndrome Phenotype",slug:"rcan1-and-its-potential-contribution-to-the-down-syndrome-phenotype",signatures:"Melanie A. Pritchard and Katherine R. Martin",authors:[{id:"156218",title:"Dr.",name:"Melanie",middleName:null,surname:"Pritchard",fullName:"Melanie Pritchard",slug:"melanie-pritchard"}]},{id:"43392",title:"Laterality Explored: Atypical Hemispheric Dominance in Down Syndrome",slug:"laterality-explored-atypical-hemispheric-dominance-in-down-syndrome",signatures:"George Grouios, Antonia Ypsilanti and Irene Koidou",authors:[{id:"39181",title:"Prof.",name:"George",middleName:null,surname:"Grouios",fullName:"George Grouios",slug:"george-grouios"},{id:"45480",title:"Dr.",name:"Antonia",middleName:null,surname:"Ypsilanti",fullName:"Antonia Ypsilanti",slug:"antonia-ypsilanti"},{id:"162500",title:"Prof.",name:"Irene",middleName:null,surname:"Koidou",fullName:"Irene Koidou",slug:"irene-koidou"}]},{id:"43394",title:"Genetic and Epigenetic Mechanisms in Down Syndrome Brain",slug:"genetic-and-epigenetic-mechanisms-in-down-syndrome-brain",signatures:"Jie Lu and Volney Sheen",authors:[{id:"40911",title:"Dr.",name:"Volney",middleName:null,surname:"Sheen",fullName:"Volney Sheen",slug:"volney-sheen"},{id:"47427",title:"Dr.",name:"Jie",middleName:null,surname:"Lu",fullName:"Jie Lu",slug:"jie-lu"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"67310",title:"Aluminum Alloys Behavior during Forming",doi:"10.5772/intechopen.86077",slug:"aluminum-alloys-behavior-during-forming",body:'\n
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1. Introduction
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Formability is defined as plastic deformation ability to produce a part with definite requirements on mechanics, dimension, and appearance of a material during a forming process, being mainly limited by the occurrence of flow localization or variability. The formability of any sheet material depends on the material properties, process parameters, and strain bounding criteria. The formability can be evaluated through simulation tests like stretching, deep drawing and drawing processes, mechanical tests, limiting dome height (LDH), and forming limit diagrams at various conditions. Evaluating the formability of aluminum alloys is crucial for industries like aerospace and automotive due to their significant advantages over other materials. Aluminum alloys are majorly categorized as 1xxx, 2xxx, 3xxx, 4xxx, 5xxx, 6xxx, 7xxx, and 8xxx based on major alloying elements. Among all, 2xxx, 5xxx, 6xxx, and 7xxx are having majority of applications in any industry. Forming behavior of aluminum alloys has been evaluated through different processes including deep drawing, stretching, incremental forming, bending, hydroforming, etc., under different process conditions (cold, warm, and hot conditions) and process parameters. Each process has its own process feasibility to evaluate the formability without any forming defects in products. The significance of this chapter is to discuss and elaborate the effect of forming process parameters of different processes on various aluminum alloys. Specifically, the hot forming process, deep drawing process, incremental forming process, tube hydroforming process, and stretching process are discussed on different aluminum alloys.
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2. Aluminum alloy behavior during hot forming
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Hot forming of aluminum alloys is extensively used in the modern industry and has been explored by many researchers and scientists. The main intension to derive this process is to reduce in-flow stress, increase ductility, reduce work hardening, increase toughness of the material, etc. Furthermore, temperatures lower than those involved during hot forging make easier the obtaining of close tolerances and high surface finish [1]. To lead the hot forming process on different aluminum alloys, different process parameters were considered and the attachable results to the literature were derived.
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For details, high-temperature tensile deformation of AA 6082-T4 was experimented in the temperature range of 623–773 K at several strain rates in the range of 5 × 10−5 to 2 × 10−2 s−1. By this, stress exponent n of 7 during the ranges of temperatures and strain rates was tested. This is higher than what is usually observed in Al-Mg alloys under similar experimental conditions. Improvement in the strain exponent of any material leads to better formability [2]. Hot compression tests were performed on aluminum alloys 7150 and 2026 by varying the temperature from 300°C to 450°C and at a strain rate from 0.01 s−1 to 10 s−1 [3, 4]. Also, on AA 7075-T6 and AA 7085 aluminum alloy [5, 6] tested at different temperatures and strain rates (450, 500, 520, 550, 580°C and 0.004, 0.04 and 0.4 s−1 for AA 7075 and AA 7085 in the temperature range from 250°C to 450°C and at strain rate from 0.01 s−1 to 10 s−1 using Gleeble-1500 system, whereas hot deformation behavior was studied on aluminum alloys consisting of Al–6.2Zn–0.70Mg–0.3Mn–0.17Zr with temperature range of 623–773 K and strain rate of 0.01–20 s−1 [7]. Using the metallographic and transmission electron microscope, structural changes were studied. The results showed that the true stress-true strain curves exhibit a peak stress at a critical strain, after which the flow stresses decrease monotonically until high strains. The peak stress level decreases with increasing deformation temperature and decreasing strain rate. Similarly, Ag-containing 2519 aluminum alloy hot deformation behaviors were studied by isothermal compression at 300–500°C with strain rates from 0.01 to 10 s−1. Consequences indicated that by increasing the strain rate and decreasing the deformation temperature, the flow stress of the alloy increased. And also, at a strain rate lower than 10 s−1, the flow stress increases with increasing strain until the stress reached the peak value, and later on, a constant flow stress was noted [8]. Aluminum alloy of grade 7075 sheets fabricated by twin roll casting and deformation behavior was investigated at high temperature. At high temperatures from 350 to 500°C and strain rates from 1 × 10−3 to 1 × 10−2 s−1, hot tensile test was performed. The results showed that by increasing the strain rate and decreasing deformation temperature, flow stress was increased [9]. Similarly, three aluminum alloys containing different silicon contents were studied at a temperature range of 573–773 K with strain rates of 0.01, 0.1, 1 and 5 s−1 [10].
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Hot deformation behavior using processing map technique of stir cast 7075 alloy was studied. Based on the values of a dimensionless parameter like an efficiency index of energy dissipation, mapping was understood in terms of microstructural processes. Under the temperature and strain rate conditions, the processing map exhibited one distinct domain without any unstable flow conditions. In the processing map, the dynamic recrystallization zone and instable zones were identified. The processing maps can be used to select optimum strain rates and temperatures for effective hot deformation of 7075 alloy [11].
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Elevated temperature and strain rate were aimed by stamping of AA5083 sheet components. To evaluate mechanical properties and forming behavior, tensile and Nakajima-type tests were carried out. The material flow stress, ductility, and fracture limit sensitivity to temperature and strain rate were evaluated. And also, the optimal combination of process parameters for maximum formability and effective post-deformation mechanical properties were determined [12]. A special device was developed to investigate the hot forming-quenching integrated process of cold-rolled 6A02 aluminum alloy sheet. The strengthening effect was replicated by hardness and uniaxial tensile tests. Microstructure examination was also conducted to clarify the strengthening mechanism. Results showed that hardness increases with solution time increase, and improves significantly after artificial aging. The faster the cooling rate, the greater the strengthening effect. On the same alloy, hot forming-quenching integrated process at different temperatures from 50 to 350°C was investigated. Results showed that the Vickers hardness and tensile strength decreased with increasing forming-dies temperature. To obtain enough strengthening effect, the forming-dies temperature should not be more than 250°C [13].
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Springback and microstructure of the final products were analyzed and mechanical properties of the material were measured by tensile tests. The results show that HFSC can improve the formability of AA2024 aluminum alloy. After natural aging for 96 h at room temperature, the products were subjected to the hot bending process with synchronous cooling exhibiting a significant increase in strength. Springback of the aluminum alloy AA5754 under hot stamping conditions was characterized under stretch and pure bending conditions. It was found that elevated temperature stamping was beneficial for springback reduction, at hot dies [14, 15]. Hot stamping was developed for aluminum alloy to improve formability and avoid thermal distortion by combining hot forming and quenching. The effects of heating temperature on formability and strengthening of a solution treated with Al-Mg-Si alloy sheet, uniaxial tensile test, deep drawing test, and free bulging test were carried out at temperatures ranging from 25 to 500°C. It was observed that when temperature was raised to 400°C, the fracture strain and limiting bulging height were increased, whereas the limiting drawing ratio increased as temperature elevated to 200°C and declined subsequently. The mechanical property hardness was changed by increasing temperature and at 200 and 500°C, two peak hardness values were noted. Enhanced formability and strength were obtained simultaneously at 200 and 500°C, either of which can be chosen as appropriate forming temperatures for hot stamping [16]. At different solution heat treatment (SHT) temperatures, SHT time and lubricant stamping experiments were performed with 6061 and 7075 aluminum alloy sheets to investigate the formability and lubrication off a B-pillar. After trimming precision level, forming detections were also carried out. From these observations, the B-pillar wrinkled badly and cracked or even broke into pieces in cold stamping with or without lubricants [17].
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For AA 6061 tailor rolled blanks (TRBs), an integrated hot forming and heat treatment process was proposed to improve the formability and dimensional accuracy. The experimentation of this process for sheet forming of Al6061 TRB was evaluated by performing the Erichsen and V-bending tests. The integrated hot forming and heat treatment process was also compared with the conventional forming method in terms of formability, dimensional accuracy, and mechanical properties [18]. A hot AA6082 specimen and cold P20 tools were studied as a function of contact pressure, specimen thickness, and lubricant, using the inverse FE simulation method for the interfacial heat transfer coefficient (IHTC) evolutions. To predict IHTC evolutions with reductions of different lubricants of sliding distance at different contact pressures and sliding speeds as a function, an interactive model was developed. The interaction between the lubricant and IHTC was deducted such that it had three stages such as stage I: the lubricant is applied excessively and the IHTC is plateaued, stage II: in which the lubricant diminishes during sliding and the IHTC decreases, and stage III: lubricant breakdown occurs and the IHTC is equal to its values under dry conditions [19].
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3. Aluminum alloy behavior during deep drawing process
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The drawing of metal or “deep drawing” is the process by which a punch force is applied to sheet metal to flow between the surfaces of a punch die. By this, the sheet is formed into cylindrical, conic, or box-shaped parts. The development of the deep drawing process has paralleled scientific development, particularly in the aircraft and automotive industries. This process is more popular because of its swift press cycle times. Complex axisymmetric geometries and certain nonaxisymmetric geometries can be produced with a few operations. With respect to the functional perspective, the deep drawing process produces high-strength and lightweight parts as well as geometries unattainable with some other manufacturing processes [20]. A schematic illustration of these deep drawing processes is shown in Figure 1. This design is made in such a way that thickness reduction of the workpiece material has been avoided completely (Figure 1). For this process, the basic tools are the punch, the drawing die ring, and the blank holder.
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Figure 1.
Schematic illustration of deep drawing process [20].
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Figure 2 shows the important process parameters involved in the deep drawing process. In addition, material properties such as the strain hardening coefficient (n) and normal anisotropy (R) affect the deep drawing operation.
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Figure 2.
Significant variables in deep drawing [20].
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Instead of tool temperatures, forming temperature curves (FTCs) were characterized from AA5754-O as a workpiece temperature at the warm deep drawing (WDD) process. The distinctive behavior of these curves was examined under nonisothermal WDD of AA 5754-O. The process parameters were considered such as FTC, blank holder force, and punch velocity to assure deep drawability. Optimum conditions were investigated by evaluating the cup volume and springback parameters. In the findings, 330°C in the flange-die radius region and 100°C in the cup wall-punch bottom region were the ideal optimum temperatures for the warm deep drawing process [21]. The stress-strain response of AA2014, AA5052, and AA6082 aluminum alloys at four temperatures: 303, 423, 523 and 623 K, and three strain rates: 0.0022, 0.022, and 0.22 s−1 was evaluated through uniaxial tensile tests. It was found that the Cowper-Symonds model was not a robust constitutive model, and failed to predict the flow behavior. A comparative study was followed for modeling of three aluminum alloys under the mentioned strain rates and temperatures. For comparison, the capability of Johnson-Cook model, modified models of Zerilli-Armstrong and Arrhenius and artificial neural network were considered for constitutive behavior. Better formability of the materials was observed at an elevated temperature of 623 K in terms of cup height and maximum safe strains by conducting cylindrical cup deep drawing experiments under two different punch speeds of 4 and 400 mm/min [22]. Tensile tests of AA5754-H22 aluminum alloy were carried out at five different temperatures and three different strain rates to investigate the deformation behavior correlating with the Cowper-Symonds constitutive equation.
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When punch and die were heated to 200°C, the forming limit strain and dome height were improved. Significant enhancement was noted when the die and punch temperatures were maintained at 200 and 30°C, respectively, in deep drawn cup depth. Using a thermo-mechanical FE model, the forming behavior at different isothermal and nonisothermal conditions was predicted. In the FE model, temperature-dependent properties in Barlat-89 yield criterion and coupled with Cowper-Symonds hardening model were used. The validation had taken place using thinning/failure location in deformed cups by implementing the experimental limiting strains as damage model [23].
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Deep drawing of aluminum alloy AA6111 at elevated temperatures was analyzed with the effect of friction coefficient through experiments and finite element method. Results indicated that the friction coefficient and lubrication position influence the minimum thickness, the thickness deviation, and the failure mode of the formed parts. During the hot forming process, the failure modes were draw mode, stretch mode, and equi-biaxial stretch mode. Fracture occurred at the center of cup bottom or near the cup corner in a ductile mode or ductile brittle mixed mode [24]. Simulations of deep drawing tests at elevated temperatures were carried out with experimental validation on aluminum alloy 7075. For stamping operations, some of the important parameters such as blank holder force, stamping speed, blank temperature, and friction coefficient were considered. During the experimentation, stamping tests were performed at temperature between 350 and 500°C, 0 and 10 kN blank holding force, 50 and 150 mm/s stamping speed, and 0.1 and 0.3 frictional coefficient. At lower values of temperature, blank holder force and friction coefficient improvement were seen in thickness homogeneity whereas formability was improved with the well lubricated blank at about 400°C temperature and stamping speed 50 mm s−1 [25]. Tailor friction stir welded blanks (TFSWBs) of AA5754-H22 and AA5052-H32 sheet metals were fabricated using a tool with optimized design along with optimized process parameters. For optimization to design the friction stir welding experiments, Taguchi L9 orthogonal array was used. For the multi-objective optimization to maximize the weld strength and total elongation reducing the surface roughness and energy consumption, the gray relational analysis was applied. The formability was evaluated and compared with TFSWBs and parent materials using LDR tests. The analysis had proved that TFSWBs were comparable with parent materials more specifically without any failure in the weld zone area. For improvement in the LRD, a modified conical tractrix die was proposed and 27% improvement was observed.
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Simulations of cylindrical cup drawing were carried out with experimental validation on AA6111 aluminum alloy at elevated temperatures. The influence of four important process parameters, namely, punch velocity, blank holder force (BHF), friction coefficient, and initial forming temperature of blank on drawing characteristics was investigated using design of experiments (DOE), analysis of variance (ANOVA), and analysis of mean (ANOM). Based on the results of ANOVA, the BHF had the greatest influence on minimum thickness. The significance of punch velocity for thickness deviation, BHF, friction coefficient, and initial forming temperature of blank was 44.35, 24.88, 15.77, and 14.995% respectively. Further, the effect of each factor on forming characteristics was analyzed by ANOM [26].
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A design optimization problem was constructed to identify the formability window, in which the punch stroke was maximized subject to wrinkling and tearing. For this, the formability window of a difficult-to-draw material AA 5402 was explained with the pulsating blank holder force (PBHF) and the variable blank holder force (VBHF). Some parameters in the VBHF and PBHF were included and taken as the design variables. A sequential approximate optimization (SAO) using a radial basis function (RBF) network was used to determine the optimal parameter of PBHF and VBHF. From numerical simulation coupled with the SAO using the RBF network using the PBHF and VBHF, formability window was observed. It was identified that the proposed approach was highly useful for clarifying the formability window of a difficult-to-draw material [27]. The tailored heat treated blank (THTB) technique was demonstrated to create a material property gradient through a suitable artificial aging treatment carried out prior to the forming process on the effectiveness of combining the hydromechanical deep-drawing process. This method was coupled with a simple finite element model and a multi-objective optimization platform. For determining the effect of the aging treatment on the mechanical and deformative behavior of the AC170PX aluminum alloy, a preliminary experimental campaign was carried out. The adoption of aged blanks in the hydromechanical deep drawing allows to increase the limit drawing ratio and to simplify the process proved from the optimization results [28].
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For increasing the drawability of AA1200 aluminum alloy cylindrical cups, one technique was developed. For optimal process design, effects of die and punch along with fillet radius of die and punch on LDR, drawing load with respect to punch stroke and strain of the cup wall was investigated numerically. To determine the optimum LDR form numerical analysis, a commercial finite element simulation package, ANSYS 14.0, was used. The effects of the original blank on the various LDR and punch load were numerically investigated. This process successfully produced cylindrical cups with considerable drawing ratio [29]. The effect of pulsating blankholder system was investigated on improving the formability of aluminum 1050 alloy. Using ABAQUS6.7 software, the deep drawing process was simulated for cylindrical cup of AA 1050. Later on, experimental and numerical analyses were compared for depth of cup, tearing, and thickness distribution. The results indicated that with proper frequency and gap, the cup depth and thickness distribution can be improved by using the pulsating blankholder system. Further, good agreement was observed between simulation and experimental results [30]. An analytical model was proposed for the nonuniform fluid pressure distribution in the cavity and for the hydrodynamic flow of the fluid film between the blank and die for AA5086 aluminum alloy. From Reynolds equation solution, the hydrodynamic flow was calculated and model was implemented in ABAQUS/Explicit, finite element software. The approach was validated and investigated for the influences of the blank holder force and the fluid pressure on the formability of the blank metal. The results exhibited that the choice of an appropriate blank holder force reduced the strain in the blank and prevented the risk of fracture [31]. A study was made on deep drawing of SiCp/2024Al composite sheets by considering the effect of pulse current on heating performance and thermal. The high-intensity pulse current flows through the sheet and generates the tremendous Joule heat. The specimen temperature was kept around 673 K at a rate of 13.5 K/s under the current density of 21.7 A/mm2. The temperature difference was reduced by 73.3% by inserting the stainless-steel inserts. Besides, the SiCp/2024Al composite was successfully deep drawn with good surface quality [32]. Deep drawing process characteristics of AA 6xxx alloy sheet were discussed under different process parameters such as punch force, lubrication, fillet radius, punch speed etc., and the formability was evaluated [33, 34, 35, 36, 37].
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4. Aluminum alloy behavior during incremental forming
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Incremental sheet forming (ISF) is a flexible process in which a sheet of metal is formed by a progression of localized deformation. This process does not require any specialized tool; a simple tool moves over the surface of the sheet metal by which localized plastic deformation is initiated. Hence, many shapes can be formed by designing a proper path to a tool. The main motto of this process is to form a sheet metal without any manufacturing of specialized dies [38]. Figure 3 shows an example of the incremental forming. In this Figure 3, according to computer numerical control (CNC) machine program instructions, the ball tool moves on the sheet to form the required shape. Hence, the process is in CNC machine; the program can be edited as per the requirement. From the shown Figure 3, the hollow and square in cross section will be formed [39].
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Figure 3.
Incremental forming of an aluminum sheet on CNC milling machine [34].
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A few observations are made and discussed on incremental forming process. Incremental forming behavior of 6111-T4 an alloy was investigated for exterior body panel applications. Tensile testing data were used to simulate the incremental forming process. The heat treat regimen developed for uniaxial testing was then applied to a series of plane strain tests using a hemispherical punch [40]. The formability of AA-2024 sheets was investigated in the single-point incremental forming (SPIF) process. The process parameters, specifically step size, tool radius, and forming speed, of the SPIF process were varied over wide ranges. The formability was quantified through a response surface method. It was found that the interaction of step size and tool radius was very significant on the formability. The formability of pre-aged AA-2024 sheet decreases with the increase in the forming speed. Additionally, the annealed sheet shows higher formability than the pre-aged sheet [41].
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AA7075-O aluminum alloy sheet forming was investigated using experimental campaign and the forming process mechanism was understood. Tensile tests were carried out to characterize the mechanical properties with three different thicknesses. To illuminate the formability of AA7075-O aluminum alloy sheet, the effects of tool path with different incremental steps and the part height were evaluated. To understand the design limits for strain, a fracture forming limit diagram was developed. The influence of different draw angles, sheet thicknesses, step-down sizes, and sheet orientations was considered to analyze forming forces. The part draw angle and incremental steps of the tool path were more effectible on the formability as concluded from the experimental results. The influences of process parameters on tool forces provide further insights into the deformation mechanics of AA7075-O sheets [42]. The formability of AA5052 aluminum alloy at room temperature was studied through truncated square pyramid and cone formed using a CNC machine. For both the shapes, the forming limit diagram (FLD) and thickness distribution were predicted and compared. The FLD obtained through this process and conventional FLD were different. Comparison of FLD and thickness distribution showed that cone had higher forming limit than square cup and the thickness after forming was better in cone shapes than in square cups [43]. An investigation was made on the deformation characteristic of embossed aluminum sheet in the incremental sheet forming process in which the surface quality of tool path along outward and inward movement was compared and noted as surface quality is better in the outward movement. Using ABAQUS software, a finite element simulation, the experimental results and detailed forming mechanism of the 3D structured sheet were reviewed [44].
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Formability of friction welded blank made of aluminum 6061 was studied experimentally. Formability was evaluated through FLD, dome height, minimum thickness, and thickness distribution. Many experiments were conducted to know which joining direction caused higher formability and desired forming limit curve. Joints were prepared in three different rollings (0, 45, and 90°) and tested for formability test and compared with FLD, dome height, minimum thickness, and thickness distribution. From the formability comparison, the best joining direction was identified. Using the response surface methodology, the effect of welding process parameters such as rotational speed, plunge depth, and travel speed on formability of welded blanks was analyzed. After finding the effects, welded blanks with optimal parameter combination were fabricated and the effect of incremental forming parameters, that is, spindle speed, feeding rate, and axial step on thickness distribution was analyzed. From the results, it was obtained that joints with diagonal direction caused higher value of bowl height [45]. The effect of longitudinal ultrasonic vibrations on the performance of the incremental forming process of aluminum-1050 sheet was studied. In this technique, ultrasonic vibrations with high frequency and low amplitude were axially added to the movement of forming tool. This system is arranged with different parts including a mechanism attached into the chuck of CNC machine and ultrasonic power to the vibratory tool. Parameters like forming force and sheet formability were examined through straight groove test in both conventional and ultrasonic-assisted incremental forming process. The results showed that formability increased and forming force decreased with ultrasonic assistance [46].
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Using the finite element method, the behavior of the state of stresses and strains in the hot incremental sheet forming of 1050 aluminum alloy was evaluated, with and without pre-heating. With the assistance of RADIOSS software, numerical simulation was performed. The results were presented a deterioration in the force during electric hot incremental sheet forming compared to the electric hot incremental sheet forming [47].
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The formability of the AA2024-O aluminum alloy sheet material was evaluated with respect to the impact of forming tool shape, tool diameter, wall angle, step size, sheet thickness, and tool rotation. Forming depth was measured by scanning the components using a noncontact 3D scanner. Wall angle and step size had proved more significant factors which affect the formability greatly [48]. An attempt was made to optimize the incremental forming parameters (spindle speed, tool feed, and step size) for surface roughness to be least and wall thickness to be larger using the response surface method.
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The formability of AA5052 alloy sheets at room temperature was checked with pre-cut holes at the center with different diameters. In the forming operation, cone-shaped parts were formed with the optimized values. Formability was compared with sheet with smaller holes and larger holes and it was observed that smaller holes had better formability. Also, the thickness of the formed part wall without hole is less. As the diameter of the hole increases, the wall thickness also increases [49].
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To evaluate deformation behavior of AA-6061 aluminum alloy sheet, the single point incremental forming (SPIF) process was chosen. To form the sheet into the desired conical shape, the SPIF experiments and finite element method simulation were performed and to measure the major and minor strains, the digital image correlation (DIC) method was used. The major and minor strains in post deformation results were compared with FEM results for AA6061 thin sheet material. An experimental fracture forming limit diagram was assessed using the punch stretching test.
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Consequently, the effective plastic strains at the onset of fracture were predicted and compared with experimental data. In order to get insight into forming behavior and surface roughness, the microstructural examination on the truncated dome fabricated using optimized parameters was carried out through micro-texture analyses [50]. By using the electric hot incremental forming process (EHIF), the dimensional accuracy of parts has got more improvement compared to single-stage forming and double-stage forming at room temperature. The effect of EHIF process parameters, such as tool diameter, feed rate, step size, and current, on temperature was studied. For a cone of AA 1060, the maximum temperature, the average temperature, and the maximum temperature difference were measured. Besides, the response surface method and Box–Behnken design were employed, and they established corresponding models to predict targeted values [51].
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AA 7075-O sheets were formed into variable angle funnels and 45° wall angle cones by SPIF. The same material was deep drawn and a bulge test part was formed to compare with SPIF. Moreover, the formed parts were sectioned and characterized for texture and surface finish at equivalent strains. To compare the strain paths of SPIF and deep drawing, finite element models were used [52]. For AA 1050 sheet metal, the deformation characteristics, forming behavior, and deformation mechanism of the SPIF process were evaluated. For process deformation characteristics such as dimensional accuracy, thickness distribution, true surface strain, von Mises stress, and equivalent plastic strain, evolved at different forming stages, were estimated through experimental investigation and finite element analysis. Analysis was carried out to identify the reason of typical failure under biaxial strain mode [53].
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5. Aluminum alloy behavior during hydroforming process
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The metal forming process in which a pressurized fluid either plastically deforms or aids in deforming a given blank material (sheet or tube) into a desired shape as depicted is a hydroforming process. Figure 4 indicates the complete process. Using this process, more complex shapes with more strength and low cost can be manufactured as compared with stamping, forging, or casting processes [54].
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Figure 4.
Steps in a typical hydroforming process shown on a small tubular part [54].
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Tube hydroforming process on different aluminum alloys is discussed in the following sections. At different temperatures, tube hydroforming analysis of aluminum alloy AA1050 was studied and the effect of temperature on thickness distribution of the final product was investigated. Also, for evaluating numerical results, a warm hydroforming set-up had been designed and manufactured. Conferring to numerical and experimental results in the case of free bulging, increase of the process temperature causes more uniform thickness distribution which leads to better material formability. A viscoplastic model was developed to consider the influence of microscopic evolution and macroscopic deformation to represent the deformation behavior of aluminum alloy sheet AA7075-O in the warm hydroforming process. By using the pressure rate, the evolution of dislocation density and kinematic isotropic hardening on a hydroforming environment, a set of rate dependent constitutive equations was constructed and proposed to predict stress-strain response of the material. The hydraulic bulge experiments on aluminum alloy at warm temperature indicated that the deformation behavior of the material was more sensitive to pressure rate. To determine the optimum values of a set of free material constants associated with the proposed constitutive model, the genetic algorithm optimization technique was used. The computed data were in good agreement with the test data on the basis of the optimized material constants [55, 56].
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Friction stir welding (FSW) tube of 2024-O aluminum alloy rolled plates was coiled and produced by processing sequence. The plastic deformation characteristics were investigated experimentally and numerically during hydroforming with two types of end conditions. The performance of the FSW tubes was investigated by die-bulge forming with fixed ends. The wrinkling behavior during hydroforming was analyzed by employing axial feed on the tube ends. Severe thinning was observed at one quarter of the expansion zone from symmetry plane. Along the hoop direction, the base material near the weld observed a severe thinning. The thickness distribution greatly depends on the sequence of the contacting die and the variations of the curvature radius of the tube during hydroforming. Moreover, the weld shows an inhibitory effect for the generation of the wrinkles and decreases the number of the wrinkles as compared to the seamless tube during hydroforming [57].
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An experimental and numerical simulation was studied on 6063-T4 aluminum alloy cross member through the hydroforming process. Severe thinning and bursting were avoided during hydroforming, composite design method was carried out, and the significance of pre-form structural parameters was discussed on thinning. An experimental research was conducted on thickness distribution of typical sectional profiles and dimension accuracy as per the optimum pre-form shape.
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FEM simulations and experiments were conducted on the formability of aluminum alloy AA2024-O. The effects of strain rate on the formability during the active hydroforming process were investigated. Results indicated that aluminum alloy AA2024-O is not sensitive to pressure rate at room temperature. Furthermore, the deformation capacity of aluminum alloys can be improved effectively, and more uniform distribution of wall thickness can be obtained. The wrinkling behavior and thickness distribution of 5A06 aluminum alloy sheets in an annealed state was investigated numerically and experimentally under different hydraulic pressures in the hydroforming of single-layer and double-layer sheets. The upper, thicker sheet synchronously deforms with the lower, thinner sheet during hydroforming. When the double-layer sheets were separated, a thinner curved sheet part will be manufactured. From the simulation and experimental results, the upper, thicker sheet was effectively suppressing the wrinkles of the lower, thinner sheet and improved the thickness distribution. This was due to the increasing anti-wrinkle ability of the formed sheet and the interfacial friction between the double-layer sheets. In addition, the maximum hydraulic pressure was decreased via hydroforming of double-layer sheets. This method reduced the drawing force for large sheet parts and meets the requirement of energy conservation [58, 59, 60].
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A specialized hydroforming process set-up was designed for 2A12 aluminum alloy curved shell double-sided sheet. The influence of double-sided liquid pressure on the thickness distribution was evaluated. The thickness distribution of the formed shells was measured and compared under different loading paths. Using simulation analysis, the deformation mode and the stress state were analyzed to understand the mechanism of the thickness variation. It was shown that the forward pressure plays a negative role in the thickness distribution of the formed parts. The deformation mode of the shells varies slightly when forward pressures are added. The Von Mises stress and the effective strain of the components were improved when conducting the double-sided hydroforming process. The larger thinning phenomenon was noted by adding forward pressure and by increasing reduced third principle stress on the blank. Through a steam hydroforming process, an experimental formability study was carried out on aluminum sheet 2017A. The steam hydroforming process takes advantage of the coupling between the thermal and mechanical loads applied. The variation of the supplied electrical power on the hydroforming temperature and steam pressure effects was studied. The evolution of strains and stresses in metal sheets was analyzed. The experimental results showed that the supplied electrical power increases the heating rate and has no effect on bursting temperature or pressure. Furthermore, the evolution of the vapor pressure as a function of temperature was independent of the supplied electrical power and the deformation in the thin sheets under the steam pressure decreases the stress flow and raises the plastic deformation [61, 62].
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Using elliptical bulging dies under various temperatures and pressure rates, warm/hot sheet bulging tests were conducted on 2A16-O aluminum alloy. The macroscopic and microscopic influence of the pressure rate on the formability and microstructural evolution of hydrobulging parts during warm/hot sheet hydroforming was investigated. The results revealed that the forming limit of the aluminum alloy was influenced by the pressure rate as the temperature rose, wherein a lower pressure rate resulted in a higher forming limit. This study demonstrated that warm/hot sheet hydroforming of aluminum alloy may lead to an improved forming limit and inhibit microstructural degradation during processing [63]. A hydroforming analysis was made on extruded aluminum tubular specimen made up of AA 6063 alloy bulged from the diameter of 38–54 mm. The thickness distribution at bulging the region along lateral and longitudinal directions was analyzed. The parameters considered are axial feed, tube thickness, fluid pressure, and die semi-cone angle. The forming characteristics such as thickness distribution and bulged diameter were studied using toolmaker microscope and coordinate measuring machine. Maximum shear thinning is observed in the largest diameter of the bulged portion of the tube [64].
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6. Aluminum alloy behavior during bi-axial forming
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Here, some of the recent discussions are made based on the bi-axial forming process. It is also treated as a stretching process in which sheet material experiences the tensile load along plane direction in the same time.
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Biaxial warm forming behavior in the temperature range 200–350°C was investigated for three aluminum sheet alloys: Al 5754, Al 5182, and Al 6111-T4. The formability for all the three alloys improved at elevated temperatures; the strain hardened alloys Al 5754 and Al 5182 showed considerably greater improvement than the precipitation hardened alloy Al 6111-T4. Formability was studied by forming rectangular parts at a rapid rate using internally heated punch and die in both isothermal and nonisothermal conditions. The temperature effect on drawing of the sheet was found to have a large effect on formability. FLD under warm forming conditions was also determined, which showed results that are consistent with the evaluation of part depth. Biaxial forming behavior was investigated for three aluminum sheet alloys of Al 5182, Al 5754, and 6111-T4 using a heated die and punch in the warm forming temperature range of 200–350°C. It was found that all three alloys exhibited significant improvement in the formability compared with that at room temperature. The nonheat-treatable alloys of AA 5182 and AA 5754 showed a higher part depth than that of heat-treatable 6111-T4. The formidability characteristic was dependent on the blank holding pressure (BHP). When the BHP decreased, the formability increased, but increasing the forming temperature and/or BHP minimizes the wrinkling tendency and improves the forming performance. By increasing temperature and BHP, the stretchability of the sheet alloys was increased. Through setting the temperature 50°C higher than the punch temperature to enhance the drawing component, the optimum formability was achieved. Strain distribution was also improved with setting the die temperature higher than the punch temperature in a part in such a manner that postpones necking and fracture by altering the location of the greatest thinning [65].
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The Gurson-Tvergaard-Needleman (GTN) damage model combined with the finite element method was used to investigate the influence of double-sided pressure on the deformation behavior of biaxially stretched AA6111-T4 sheet metal. The Marciniak-Kuczynski (M-K) localized necking model was used to predict the right-hand side of the forming limit diagram (FLD) of sheet metal under superimposed double-sided pressure. The forming limit curve (FLC) of the biaxially stretched AA6111-T4 sheet metal under the superimposed double-sided pressure had improved and the fracture locus shifts to the left. Besides, the formability increase value is sensitive to the strain path [66].
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Through the numerical biaxial tensile tests of the sheet, the biaxial tensile deformation behavior of 5182 aluminum alloy sheet was predicted. From the numerical simulations, the stress-strain curves and the shapes of the contours of plastic work were calculated and were quantitatively verified by the experimental biaxial tensile test using the cruciform specimen. Using the results of experimental and numerical biaxial tensile tests, parameters of the Yld2000-2d yield function were identified. Von Mises’s and Hill’s yield functions were identified using the experimental data and were compared. The simulation results confirmed that the forming simulation using the Yld2000-2d yield function identified by the numerical biaxial tensile tests was better than that of the Mises’s and Hill’s yield functions and was comparable to that of the Yld2000-2d yield function calibrated experimentally [67].
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The forming limit strains at fracture for aluminum alloy 5086 were determined using an in-plane biaxial tensile test with a cruciform specimen. To identify the onset of fracture and the forming limit strains, a method based on the evolution of strain in the central area of the specimen and the observation of the macroscopic image of specimen surface was proposed. The forming limit strains at fracture were determined under different strain paths provided by the two independent axes of the experimental device. Finite element simulations were performed to determine and compare numerical forming limit strains with three ductile fracture criteria [68]. Warm temperature biaxial tension test apparatus was developed to achieve stress ratio and strain rate controls simultaneously. The warm temperature biaxial tension tests were conducted on AA5182-O aluminum alloy sheet with the thickness of 1 mm. The obtained results showed that the shapes of equi-plastic work loci did not have strong temperature dependency [69].
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7. Summary
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Forming behavior of different aluminum alloys is discussed in the above sections. The forming processes considered included the hot forming process, deep drawing process, incremental process, hydroforming process, and bi-axial forming. The effect of their parameters on aluminum alloys is realized. From each forming process and test, the forming limit strain is determined to quantify the formidability of each aluminum alloy. Moreover, the quantification of the formability of Al alloys can help the industries.
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\n\n',keywords:"ISF, hot forming, tube hydroforming, deep drawing, stretching",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/67310.pdf",chapterXML:"https://mts.intechopen.com/source/xml/67310.xml",downloadPdfUrl:"/chapter/pdf-download/67310",previewPdfUrl:"/chapter/pdf-preview/67310",totalDownloads:370,totalViews:0,totalCrossrefCites:0,dateSubmitted:"November 5th 2018",dateReviewed:"March 27th 2019",datePrePublished:"November 27th 2019",datePublished:"March 4th 2020",dateFinished:null,readingETA:"0",abstract:"Industrial revolution toward weight reduction and fuel efficiency of the automotive and aerospace vehicles is the major concern to replace heavy metals with light weight metals without affecting much strength. For this, aluminum alloys are the major contributors to those industries. Moreover, aluminum alloys are majorly categorized as 1xxx, 2xxx, 3xxx, 4xxx, 5xxx, 6xxx, 7xxx, and 8xxx based on major alloying elements. Among all, 2xxx, 5xxx, 6xxx, and 7xxx are having majority of applications in the abovementioned industries. For manufacturing any engineering deformable components, forming characteristics are must. Forming behavior of aluminum alloys has been evaluated through different processes including deep drawing, stretching, incremental forming, bending, hydro forming etc., under different process conditions (cold, warm, and hot conditions) and process parameters. Each process has its own process feasibility to evaluate the formability without any forming defects in products. The present chapter discusses a few important processes and their parameter effect on the aluminum alloys through the experimentations and simulation works.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/67310",risUrl:"/chapter/ris/67310",signatures:"Perumalla Janaki Ramulu",book:{id:"8862",title:"Aluminium Alloys and Composites",subtitle:null,fullTitle:"Aluminium Alloys and Composites",slug:"aluminium-alloys-and-composites",publishedDate:"March 4th 2020",bookSignature:"Kavian Omar Cooke",coverURL:"https://cdn.intechopen.com/books/images_new/8862.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"138778",title:"Dr.",name:"Kavian",middleName:"Omar",surname:"Cooke",slug:"kavian-cooke",fullName:"Kavian Cooke"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"283483",title:"Associate Prof.",name:"Perumalla",middleName:null,surname:"Janaki Ramulu",fullName:"Perumalla Janaki Ramulu",slug:"perumalla-janaki-ramulu",email:"perumalla.janaki@astu.edu.et",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Aluminum alloy behavior during hot forming",level:"1"},{id:"sec_3",title:"3. Aluminum alloy behavior during deep drawing process",level:"1"},{id:"sec_4",title:"4. Aluminum alloy behavior during incremental forming",level:"1"},{id:"sec_5",title:"5. Aluminum alloy behavior during hydroforming process",level:"1"},{id:"sec_6",title:"6. Aluminum alloy behavior during bi-axial forming",level:"1"},{id:"sec_7",title:"7. Summary",level:"1"}],chapterReferences:[{id:"B1",body:'Cavaliere P. Hot and warm forming of 2618 aluminium alloy. Journal of Light Metals. 2002;2(4):247-252. DOI: 10.1016/S1471-5317(03)00008-7\n'},{id:"B2",body:'El-Danaf EA, AlMajid AA, Soliman MS. Hot deformation of AA6082-T4 aluminum alloy. Journal of Materials Science. 2008;43(18):6324. DOI: 10.1007/s10853-008-2895-4\n'},{id:"B3",body:'Jin N, Zhang H, Han Y, Wu W, Chen J. Hot deformation behavior of 7150 aluminum alloy during compression at elevated temperature. 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Numerical investigation and optimization of pulsating and variable blank holder force for identification of formability window for deep drawing of cylindrical cup. The International Journal of Advanced Manufacturing Technology. 2016;82(1-4):583-593. DOI: 10.1007/s00170-015-7385-7\n'},{id:"B28",body:'Piccininni A, Di Michele G, Palumbo G, Sorgente D, Tricarico L. Improving the hydromechanical deep-drawing process using aluminum tailored heat treated blanks. Acta Metallurgica Sinica. 2015;28(12):1482-1489. DOI: 10.1007/s40195-015-0347-0\n'},{id:"B29",body:'Dwivedi R, Agnihotri G. Numerical simulation and experimental analysis on the deep drawing of cylindrical cups. Transactions of the Indian Institute of Metals. 2015;68(1):31-34. DOI: 10.1007/s12666-015-0598-5\n'},{id:"B30",body:'Liu ZY, Xiong BQ , Li XW, Yan LZ, Li ZH, Zhang YA, et al. Deep drawing of 6A16 aluminum alloy for automobile body with various blank-holder forces. Rare Metals. 2018;37:1-8. DOI: 10.1007/s12598-018-1146-3\n'},{id:"B31",body:'Abbadeni M, Zidane I, Zahloul H, Fatu A, Hajjam M. Finite element analysis of fluid-structure interaction in the hydromechanical deep drawing process. Journal of Mechanical Science and Technology. 2017;31(11):5485-5491. DOI: 10.1007/s12206-017-1043-y\n'},{id:"B32",body:'Wang B, Wang GF, Jiang SS, Zhang KF. Effect of pulse current on thermal performance and deep drawing of SiCp/2024Al composite sheet. The International Journal of Advanced Manufacturing Technology. 2013;67(1-4):623-627. DOI: 10.1007/s00170-012-4510-8\n'},{id:"B33",body:'Pranavi U, Reddy PV, Lavanya K, Charyulu NN, Ramulu PJ. Effect of mechanical properties on deep drawing formability prediction. International Journal of Current Engineering and Technology. 2014;2:303-305. DOI: 10.14741/ijcet/spl.2.2014.5\n'},{id:"B34",body:'Pranavi U, Ramulu PJ, Chandramouli C, Govardhan D, Prasad PR. Formability analysis of aluminum alloys through deep drawing process. 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