Calculated thermodynamic efficiencies for various fuels under different thermodynamic cycles [26].
\r\n\tThe emergence of novel prion strains in animals, which include the only evidenced zoonotic prion C-BSE causing vCJD in humans, has created an important public health concern. Currently, new threats to human and animals may develop because of the plausible zoonotic properties of scrapie, L-BSE and the recently emerging chronic wasting disease in Europe.
\r\n\tThis book will gather experts in prion diseases and present new scientific advances in the field and relations with other amyloid neuropathologies.
Despite decades of research and engineering works on urban flood disaster prevention and reduction, flooding-caused death and economic loss continue to rise. On a global scale, flood disasters affected 2 billion people in the period between 1998 and 2017 [1]. A report by UNISDR [2] revealed that 43% of natural disasters occurred during the period of 1995–2015 were related to floods. These events affected more than half (56%) of all people who suffered from any type of natural disaster with a flood-induced death rate of about 26%. Data from the Emergency Events Database (EM-DAT) also clearly indicates that flood disaster events have increased significantly in the number over the last decade. On a regional scale, the Expected Annual Damage (EAD) from river flooding reaches €6.4 billion and the Expected Annual Population (EAP) exposure to flooding is about 195.000 people in Europe [3]. Between 2000 and 2005, Europe suffered nine major flood disasters, which caused 155 casualties and economic losses of more than €35 billion [4]. On a national scale, for example, direct flood damages for the water year 2016 totaled US $57 billion in China [5]. In Japan, a torrential downpour in July 2018 caused 223 deaths and inundated 29,766 houses with the total economic damage as high as 1,158,000,000,000 JPY according to the Ministry of Land, Infrastructure, Transport and Tourism, Japan [6].
\nThese water-related disasters were not solely caused by natural hazards. Rather, most of the major risks and disasters are triggered by vulnerable conditions of societies. Additionally, the lack of resilience and adaptive capacity are factors that make societies or social-ecological systems unable to deal with changing environmental conditions and natural hazards effectively. Thus, there is a growing need to better understand the effectiveness of efforts and investments in resilience building that can help to minimize losses and assure a quick recovery during and after a natural hazard event.
\nIn the 20th century, the main approach to deal with flood risk has often been the adoption of control-centered strategies, attempting to prevent flood disasters from happening. This approach is evidenced by the worldwide development of water infrastructure such as dam, levee, and diversion channel. Although this approach can provide substantial protection against floods, including reducing flood fatality significantly, it does not cope with changing environments. With climate change, the magnitude of a 100-year flood in the future may become much higher than a 100-year flood today. Consequently, a levee designed to resist a 100-year flood today could fail to function in the near future. More importantly, levee creates dilemmas because building stronger levee to reduce flood risk in turn may encourage more development in flood-prone areas, resulting in high flood risk. As more people and assets are concentrated in flood-prone areas, a higher levee to resist a large flood may cause higher damage should the levee breach. A study by Ferdous et al. shows that flood death rates associated with the 2017 flooding in Bangladesh were lower in the areas with lower protection level. Indeed, various studies so far have led to a general notion that a sole focus on resistance to flooding can be costly in terms of human life, property, and infrastructure. In places where the infrastructure or regulatory controls fail to provide adequate protection against unexpected events, flood risk management should rely more on the combination of hard and soft countermeasures.
\nThus, the development of new approaches to deal with flood risk or the pursuit of paradigm shift in flood risk management is an urgent demand. In recent years, the concept of resilience has been gaining more recognition and momentum and is evolving to become a cornerstone for new approaches in flood risk management [7, 8, 9, 10, 11]. Building a flood-resilient city is a strategy for building a future in which we can live with floods and has become a widely known catch phrase. Streetscapes for vulnerable and resilient cities are illustrated in Figure 1. A vulnerable city may suffer from flood disaster, but a resilient city may allow residents to enjoy flood watching. As a matter of fact, resilience is explicitly incorporated in the United Nations (2015) Agenda for Sustainable Development: Goal 11 encompasses making cities and human settlements inclusive, safe, resilient, and sustainable.
\nVulnerable and resilient cities (drawn by Alice Wang based on [12]).
The resilience is a relatively new notion referring to the ability of a system, community, society to defend, react and recover quickly and easily from the damaging effect of realized hazards. The large amount of research works has contributed to the development of better understanding of the concept and its applications is currently being discussed in various fields from flood management, transportation, drinking water supply to power supply with the recognition of the difficulty of defining resilience precisely. Restemeyer et al. [13] attempted to develop a strategy-based framework to allow scientists and governmental bodies to evaluate the flood resilience of cities, whereas van der Vaart et al. [14] tried to crystallize suggestions for some of the core bottlenecks of the implementation of flood resilience strategies via an expert group workshop.
\nAlthough the concept of resilience has obtained a foothold in international academia and practice, playing increasingly important roles in the fields of ecology, spatial planning, social science, structural engineering and flood risk management as demonstrated by an ever increasing number of entries in scientific books and articles, its implementation in practice remains not always to be a matter of course. For example, a review work of resilience practice in New Taipei City showed that although New Taipei City government actively promotes resiliency in various sectors, particular townships are facing different challenging such as rapid urbanization and the lack of emergent facilities [15].
\nA technical issue, which could be considered a barrier to the development of resilience-based risk management approach, is that the definition of resilience varies from engineering, ecology to sociology. It may not necessary or even not possible to have an unanimous definition of resilience for all fields, an assessment of major definitions of resilience and its relationship with other concepts such as vulnerability and coping capacity will promote cross-sector communication and contribute to refinement of the concept and establishment of resilience-based or resilience-centered risk management discipline.
\nTherefore, the general aim of this chapter is to provide a concise analysis of different definitions of resilience in relation to flood risk management and to explain the commons and differences between conventional flood risk management and resilience-based flood management. Besides, it is intended to present a mathematical formulation of resilience for better understanding and assisting in-depth discussion. Moreover, it gives an account of the current application of resilience-based flood risk management concept. Nevertheless, it should be mentioned here that the analysis of definitions and discussion of current applications is not aimed to be comprehensive but selective.
\nWhile it appears intuitive to most people, the notion of resilience proved to be extremely difficult, if not impossible to define in a general and comprehensive way. Numerous qualitative and quantitative definitions have been proposed in different fields from ecology, engineering, social sciences to psychology. Some of them were explained as follows.
\nIn ecology, the concept of resilience was first introduced by Holling [16], which states that the resilience is defined as “the magnitude of disturbance that can be absorbed before the system changes its structure by changing the variables and processes that control behavior.” Another definition is “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks” [17]. The focus of this definition is on the dynamics of the system when it is disturbed far from its modal state. As explained by Holling [17], the first definition concentrates on stability near an equilibrium steady state, where resistance to disturbance and speed of return to the equilibrium are used to measure the property, and such a notion may be termed engineering resilience. The second definition emphasizes conditions far from any equilibrium steady state, where instabilities can flip a system into another regime of behavior, which can be termed ecological resilience. Wording differently, ecological resilience is not just about being persistent in a certain state but also allowing the evolution of the system to new equilibrium states.
\nMeanwhile, Youn et al. [18] defined engineering resilience as “the sum of the passive survival rate (reliability) and proactive survival rate (restoration) of a system.” Similarly, the American Society of Mechanical Engineers (ASME) defined resilience as “a system’s ability to rapidly recover to the full function after disruption.” Haimes [19, 20] defined resilience as “the ability of system to withstand a major disruption within acceptable degradation parameters and to recover with a suitable time and reasonable costs and risks,” which highlights the recovery time and associated cost. He stressed that the resilience of a system is threat-dependent, and some particular states of a system are inherently more resilient than others. This notion requires the characterization and assessment of resilience to be specific to the threat under consideration. A system may be resilient to certain types of hazard but may not be so to another type of hazard. For example, flood-tolerant evergreen tree species of the Amazonian floodplain forests may suffer from seedling mortality due to draught. A poor coastal community in the Mekong Delta area may be resilient to damage from storm surge but could be very vulnerable to water pollution. A population might have resilience (immunity) to flu A but could be easily infected by Covid-19.
\nIn addition to the type of threat, the present work suggests the explicit consideration of the maximum magnitude of the threat or the upper limit of disturbance that a system can withstand before it loses all functions. For instance, the IPCC story of “1.5 degrees Celsius limit” [21] tells greatly increased risks if global warming exceeds 1.5°C above pre-industrial levels and even “catastrophic” impacts to our world if we warm more than the target.
\nAn underlying assumption in resilience study is that all systems have a certain degree of resilience. A system loses its resilience or loses its structure and functions only when the disturbance is too large to be coped with by system’s capacity. However, how the largeness of disturbance should be defined remains little explored. In other words, the critical point is not easy to determine. Up to now, resilience study has been largely disconnected to threshold assessment. So, a dilemma is how we could quantify resilience without knowing the conditions under that a system would collapse and lose it all functions. Besides, the upper limit or elasticity of a system depends on the type of threat because the system responds to different type of threat differently. Furthermore, system capacity is time-dependent and may be affected by surrounding conditions. Therefore, there could be a spatial–temporal variation in the upper limit of a system to withstand disturbance. As a result, the determination of the upper limit or quantification of system capacity considering its spatial–temporal variation in relation to the type of threat is an important step to operationalize the concept of resilience.
\nAllenby and Fink [22] defined resilience as “the capability of a system to maintain its functions and structure in the face of internal and external change and to degrade gracefully when it must.” A new and important point in this definition is its inclusion of exit strategy. However, this important aspect has received little attention in the field of flood risk management so far. The idea of degrading gracefully when it must also serve as a call for more in-depth study on the upper limit of a system to different types of hazards.
\nIn social sciences, Adger [23] defined social resilience as “ability of groups or communities to cope with external stresses and disturbances as a result of social, political, and environmental change.” The Community and Regional Resilience Institute [24] defined the resilience as “the capability to predict risk, restrict adverse consequences, and return rapidly through survival, adaptability, and growth in the face of turbulent changes.” Keck and Sakdapolrak [25] defined social resilience as “comprised of three dimensions: coping capacities, adaptive capacities, and transformative capacities.” What is important is that people are included in socio-ecological resilience discourse and such a coupling added new values to classical ecology in which humans are treated as external.
\nIn economics, resilience is defined as “the inherent ability and adaptive response that enables firms and regions to avoid maximum potential losses” [26]. It can be further classified into static and dynamics resilience. Static economic resilience is referred as the capability of an entity or system to continue its functionality like producing under a severe shock, while dynamic economic resilience is defined as the speed at which a system recovers from a severe shock to achieve a steady state [27].
\nVugrin et al. [28] defined system resilience as “given the occurrence of a particular disruptive event (or set of events), the resilience of a system to that event (or events) is the ability to reduce efficiently both the magnitude and duration of the deviation from targeted system performance levels.” There are three key factors in this definition: (1) the disruptive event, (2) the efficiency of recovery of the system, and (3) the system performance.
\nIt can be noted that a common feature among ecological, economic, and social resilience is that they do not demand the return to its original state but allow for regime change.
\nBased on these above-mentioned explanations, a graphic all-inclusive representation of resilience is provided in Figure 2. It is important to note that the social-ecological resilience may lead to a new equilibrium state depending on the combined effects of human restoration efforts and the workings of nature.
\nGraphic illustration of different concepts of resilience.
Conventional flood risk management focuses on the reduction of both flood probability and flood-caused damage. Flood probability reduction is pursued by technical measures such as dam and levee construction to keep flood waters in river channels. Resistance is a keyword to describe this practice. On the other hand, flood damage reduction is pursued by vulnerability reduction. Vulnerability is a concept that originated from social sciences and evolved to be a major framework in risk science and management and related academic fields, although a general and unanimous definition of vulnerability remains non-existent. One of the widely known definitions is given by the United Nations Development Program (UNDP), which describes vulnerability as “a human condition or process resulting from physical, social, economic and environmental factors, which determines the likelihood and scale of damage from the impact of a given hazard” [29]. A mathematical expression of vulnerability may be given as below
\nwhere exposure is defined as the degree, duration, and extent to which a system is subject to perturbation. Susceptibility refers to the factors and attributes that make a community or society more or less likely to be negatively affected by perturbation. Coping capacity is defined as the ability to cope with, or absorb and adapt to, hazard impacts [30].
\nAs resilience is the capacity to absorb, to recover and to adapt, the coping capacity of vulnerability bears some similarity with resilience. Wording differently, there is a resilience thinking to a certain extent in conventional flood risk management. Nevertheless, the prevailing notion in conventional flood risk management is stability and persistence while the socio-ecological resilience does not only stress absorption and recovery but also emphasize the adaptation and transformation to a new equilibrium state. Such an evolutional perspective can be considered as one of the most important difference between conventional flood risk management and resilience-based approach. As pointed out by Chaffin et al. [31] that social-ecological systems should be managed holistically for either increased resistance to undesirable change or the ability to transform a system to a more desirable state.
\nThe difference between resistance and the ability to absorb in resilience concept deserves some more discussions. The ability to absorb can be considered having two parts: ability to resist and ability to tolerate. Therefore, the ability to absorb in the concept of resilience may be interpreted as the ability to resist to external force first and then to bend if the force is too strong to resist but not to break. Because of the existence of various flood defense infrastructure, this interpretation is crucial for development and application of resilience-based management approaches at the top of conventional measures.
\nResistance-centered flood control approach does not consider maximum possible resistance and assume the level of resistance is limitless with technology development and economic growth. To be specific, levees are traditionally designed based on a quantity named probable maximum flood at the location, which is the level of protection levees are supposed to provide. Up until recently, many river managers believed that the level of protection can be raised high enough as long as the societal capacity to commit resources to levee construction becomes available. With or without consideration of resistance limit is one of the separation points between resistance-centered and resilience-based approaches.
\nThus, in developing resilience-based flood management approaches, the concept of engineering resilience or resistance can be applied to design and assessment for structures such as dam and levee while the concept of social-ecological resilience is useful in formulating flood adaptation strategy and determining acceptable level of risk and designing ways to deal with residual risk. Such an understanding can obviously help decision-makers do better flood management. The old mindset of confining flood waters in river channels and belief that levees can be constructed high enough to prevent overflow and strong enough to prevent any breach are wishful thinking. River overflow and levee breach have been occurring across the world even without climate change, and climate change is increasing its frequency and intensifying the magnitude. In light of the inevitable, the confinement or resistance approach appears not sustainable and a shift from confinement to living with water is indispensable.
\nBased on the afore-mentioned definitions and analysis, a mathematic formulation was proposed here to facilitate in-depth discussion of resilience, which follows a logistic equation as below
\nWhere R is the state of recovery (mathematically R = N/Nin: N: current state, Nin: original state), r is recovery rate, K is the carrying capacity of a system.
\nIntegration of Eq. (2) yields
\nwhere R0\n = N0/Nin is the deviated state of the system due to disturbance. Since R asymptotically approaches the carrying capacity K as time approaches infinity, it means a full recovery to the original state when K=Nin. It indicates partial recovery if K < Nin, and a new and better equilibrium if K > Nin. This can be interpreted as that a large carrying capacity is a premise for a system to have ecological resilience. If the capacity is not large enough, the achievable state of recovery is back to the normal at the best or even worse as being repaired. On the other hand, the speed of recovery may be expressed as
\nwhere T is the intrinsic time of recovery, which is a function of local attributes including local natural landscape and local community structure. Res is the external resources used for restoration, which is a function of the magnitude of disturbance and local attributes as well. Resin is the internal resources available for restoration. This indicates that the less time the system uses for recovery, and the less the amount of external resources needed for recovery, the more resilient the system is. The availability of Resin is carrying capacity-related, and it depends to a large extent on governmental polies and decisions of how to mobilize internal sources. It also implies that the recovery rate may largely depend on external help if disturbance is too large for the internal mechanism to function. An illustration of resilience-dependent recovery based on Eq. (3) is given in Figure 3.
\nVisual representation of resilience-dependent recovery process (low resilience: Repair; good resilience: Restoration; high resilience: Enhancement).
Compared to previous studies, such a mathematical expression of resilience can be used for both qualitative and quantitative discussions and to analyze the effects of more factors, especially the time of recovery and the amount of potentially used resources. For example, the recovery processes of vulnerable developing countries tend to rely largely on international aids, which reflects low resilience according to Eq. (4). Moreover, the outcomes are often superficial reconstruction without resilience building due to its limited capacity as can be explained by Eq. (2). As a result, recipients of relief aid lose their initiative to fend for themselves and repeat the cycle of disaster-aid-reconstruction-disaster. Quantitative or semi-quantitative assessment of the dependency of recovery rate on external source using mathematical formulas can certainly facilitate better decision-making regarding the long-term resilience building.
\nThe earthquake and tsunami that hit Japan in 2011 cost $235 billion economic damage according to the World Bank. Six years later, Japan’s Reconstruction agency announced that out of the 150,000 evacuees who lost their homes, 50,000 of them were still living in temporary housing. The reason behind the delay is the lack of construction workers and rising cost of building materials. This case proved that large dependence on external resources could delay the recovery process greatly and resilience building should be promoted to reduce a system’s dependency on external sources.
\nThe importance of resilience building in flood risk management has been well recognized as evidenced by large amounts of academic articles on resilience. In practice, however, resilience concept tends to be only marginally applied as a supplement to flood risk management. There are several well-known initiatives such as Rockefeller Foundation’s 100 Resilient Cities programme (100RC) [32], the UNISDR Making Cities Resilient campaign, and the OECD Resilient Cities project [33]. These programs are mainly intended to promote resilience as a source of policy inspiration, and the development of policy instruments for cities to address immediate shocks and long-term stresses that undermine the functions of cities.
\nIn the paper by Gralepois et al. [34], the flood defense strategies in six European countries (Belgium, England, France, the Netherlands, Poland, and Sweden) are analyzed. Although they do not find radical changes in either of the countries, they do find that the defense strategy in all countries has created more room for local, private, and individual responsibilities. In all countries except Sweden, defense remains the primary method of protection, leading the authors to conclude that flood defense has remained a cornerstone of European flood risk management.
\nThe paper by Gersonius et al. [35] addresses the debate as to how transformations from resistance-based to resilience-based approaches can be achieved by studying the implementation of various measures that aim to enhance the flood resilience of the Dutch “Island of Dordrecht.” The case illustrates that a multilayered, i.e., diversified, approach is more effective and efficient than its resistant, i.e., flood defense dominated, counterpart and provides substantial co-benefits. However, it is incompatible with the existing institutional framework. Such an incompatibility may be considered a challenge that will also be present in other countries with an established institutional framework for resistance-based approaches. Then, the authors recommend searching for ways to reinterpret existing frameworks and applying them differently by setting up pilots and experiments to foster social learning.
\nThe paper by Hegger et al. [36] assesses the now prominent assumption that a diversification of flood risk management strategies leads to resilience. They propose that the resilience concept should be operationalized into three capacities: capacity to resist, capacity to absorb and recover, and capacity to adapt and transform, and they compared six countries’ achievements in terms of these capacities. The work found that having a diverse portfolio of strategies in place contributes to resilience, especially in terms of the capacity to absorb/recover and the capacity to adapt and transform. However, the authors also stated in this work that they see different ways to be resilient. The importance of explicating the normative starting points of flood risk governance in a country, considering the unavoidable trade-offs between the three capacities, and assessing strategies’ fit with existing physical circumstances and institutional frameworks was further elucidated in the work.
\nDespite various efforts to adopt resilience-based approach to flood risk management, the actual application or the operationalization of the resilience concept remains to be explored, planned, tested, and evaluated. At present, many flood-prone regions have good pre-disaster preparation such as flood hazard map, evacuation plan and early warning system. However, few municipalities have resilience-based post-disaster recovery plan or guideline prepared before disaster. Instead, what was often seen is ad hoc recovery plans after disasters.
\nThe Cedar Falls is a residential community located in Eastern Iowa. A good practice of the city is that it has a hazard mitigation plan, which includes a series of future hazard mitigation activities involving a wide range of hazards including floods [37]. Although one of the goals of the plan is to return to pre-disaster or improved conditions as soon as possible after a disaster occurs, the emphasis is placed on prevention than rebuilding. Technical advices on recovery process are limited and general. Suggestions such as “Continue membership with the National Flood Insurance Program (NFIP)” or “Establish and/or maintain Continuity of Government plans to handle post disaster operations (i.e. animal disposal, clean-up, demolition) are important but insufficient.
\nEPA developed a Flood Resilience Checklist [38] to help communities identify ways to improve their resilience to future floods. It includes five areas: (1) Overall strategies to improve flood resilience; (2) Conserve land and discourage development in flood-prone river corridors; (3) Protect people, businesses, and facilities in vulnerable settlements; (4) Plan for and encourage new development in safer areas; (5) Implement and coordinate stormwater management techniques throughout the whole watershed. The five areas can be regrouped as overall strategies (area 1) as well as specific strategies (areas 2–5).
\nThe area of Overall Strategies to Enhance Flood Resilience is designed to promote the integration of the community’s comprehensive plan and other community’s plans such as open space or park plans with a flood management plan including both structural and non-structural measures. It also promotes community participate in the National Flood Insurance Program Community Rating System. For specific strategies such as Incentives for restoring riparian and wetland vegetation in areas subject to erosion and flooding and Acquisition of land (or conservation easements on land) to allow for stormwater absorption, their importance are well recognized and have been pursued in various ways. A representative case is the Room for the Rivers program along the Rhine and Meuse Rivers, which started from 2006 with a $3.3 billion budget from the Dutch government. Flood risk management strategies in the Netherlands have traditionally focused on reducing the probability of flooding [39] by means of dikes, pumps, and canals. After experiencing severe flooding in the 1990s, the Dutch government decided to safeguard flood-prone areas by stepping back from the river to enable the rivers to safely discharge far greater volumes of water. The program resulted in a reduction of water levels by 10–19 cm during high water in target river reaches. Although the primary goal of the Room for the River program is flood attenuation, it also recognizes the importance of esthetics and cultural and ecological elements and has increased biodiversity as the project transformed 4576 acres of land back to natural conditions. Therefore, such an initiative functions as an opportunity rather than a solely means to fix a problem because it is designed not only for river management, but also for social and economic advances.
\nIn the meantime, some U.S. communities have also implemented their own Room for the River strategies to deal with flooding. The Iowa River Corridor Project [40], begun after a severe flood in 1993, compensates farmers who permanently stop farming fields in floodplains. Much of the 50,000 acres involved have reverted into natural wetlands, grassland, and bottomland forest, and provide habitat for wildlife. The Napa River in California often floods between November and April. The $400 million Napa River/Napa Creek Flood Control Project is lowering dikes, creating floodplains and a bypass, relocating bridges, and restoring 900 acres of wetlands according to “living river” principles. Floodplain and wetlands restoration projects are also ongoing in other parts of the U.S. such as Illinois, Massachusetts, Missouri, North Dakota, Minnesota, Oklahoma, and Wisconsin.
\nOn the other hand, studies focusing solely on disaster recovery have also progressed greatly in parallel to resilience research. Smith and Wenger [41] defined the disaster recovery process as “the differential process of restoring, rebuilding, and reshaping the physical, social, economic, and natural environment through pre-event planning and post-event actions,” while Schwab et al. [42] defined recovery as “Recovery includes restoring housing, transportation, and public services; restarting economic activity; and fostering long-term community redevelopment and improvements. The definition adopted by the UN Office of Disaster Risk Reduction is “decisions and actions aimed at restoring or improving livelihoods, health, as well as economic, physical, social, cultural and environmental assets, systems and activities, of a disaster-affected community or society, aligning with the principles of sustainable development, including build back better to avoid or reduce future disaster risk.” This definition emphasizes both returning the community to normality, which is a short-term objective and sustainable development to be less vulnerable and more capable of dealing with future disaster risk, which is a long-term goal and this long-term goal implies building back a better state, similar to the multi-equilibrium state concept in socio-ecological resilience. Therefore, the dialog between flood resilience researchers and disaster recovery planners should be promoted because it can deepen the understanding of resilience by resilience researchers and contribute to better recover planning for long-term resilience. In other words, the integration of conventional disaster recovery planning with resilience concept is a pathway for resilience building.
\nScience has revealed that the human immune system has 2 broad functions: (1) defending our body’s health and (2) maintaining our body’s health. Similarly, resilience can be viewed as urban’s or community’s immune system to natural disasters, possessing two functions: (1) resisting to disturbance and (2) maintain its viability. To date, resilience has been mainly understood as the system’s capacity to restore its structure and functions. However, we chose to use the word of viability to emphasize our understanding that resilience is not limited to bouncing back but can bounce forward. In general, there are three options for a damaged system: (1) full restoration, (2) repair, which means the restoration with replacement, and (3) restoration with enhancement. For example, if the life of a city once flooded is now fully back to pre-disaster conditions, then such a situation is full restoration. If the disaster’s impacts can never be fully erased from the city, it is a case of repair. For example, the city of New Orleans was severely damaged by Hurricane Katrina in 2005. Fifteen years after the disaster, the population of New Orleans has shrunk from 10 to 15 per cent, especially it lost many African Americans residents, who were either killed in the hurricane or could not afford to come back. This situation led some researchers to declare the housing recovery in New Orleans a secondary disaster [43, 44]. The Great East Japan Earthquake of 2011 and the vicious tsunami that followed it caused widespread destruction in the Tohoku region. Rikuzentakata City in Iwate Prefecture is one of the most badly hit cities in the disaster. The recovery plan focuses equally on reconstructing and improving damaged transport networks along the coastline, re-establishing affected local businesses and empowering the disaster-struck agricultural and fishing industries which used to thrive in the area. For the restoration of urban districts, it promoted the introduction of universal design, aiming to create more opportunities for people with disabilities and the elderly to work and do sports as well. Furthermore, residential houses and hospitals have been moved to much less disaster-prone locations. As shown in Figure 4, it is a large-scale project. In total, 298 ha of residential areas were relocated to relatively higher grounds. Such a scale of disaster-mitigation-driven relocation is unprecedented in Japanese history. Furthermore, the coastal protection system has been resigned innovatively. As illustrated in Figure 5, it consists of a double-dike structure with a vegetation zone in-between and submerged breakwater at the front. In light of these developments, Rikuzentakata City can be considered a successful case of restoration with enhancement.
\nRelocation from low-lying lands (light blue) to high grounds (brown) in the city of Rikuzentakata after the Great East Japan earthquake (source: the city office).
New protection system along the coast of the city (source: the city office).
A critical issue in choosing recovery path is the financial cost. The cost of each option may vary greatly, so that resilience building could be constrained by local economic condition. In general, sustainable, resilient water management can be considered costly since it involves engineering and land use challenges and often a long-term process. The financial sustainability of resilience building and enhancement has been largely neglected up to now and deserves serious in-depth study. It is our belief that resilience building should be pursued in relation to economic growth in developing countries. In developed countries, solutions harnessing flood risk while unlocking further development potential should be explored, which require innovation. However, as we may face multiple pathways for building a resilient tomorrow, further studies should be conducted to develop optimal design approaches for resilience building with more than one objective.
\nFinally, it should be mentioned that conventional flood risk management is probability-based. It deals with the magnitude of potential consequences due to an event or disturbance with a chosen probability of occurrence. It provides little insights into the nature’s or society’s self-restoring or anti-disturbance function and is unable to cope with events with magnitudes of impact exceeding the chosen level. By contrast, resilience-based management is not constrained by likelihood of occurrence and can accept extremely large shocks by allowing adaption to new regimes. Therefore, it is more capable of and more flexible in restoring or reestablishing an affected system. Furthermore, resilience enhancement strategy can lead to better knowledge fusion than conventional flood risk management approach.
\nThis work was supported by Sophia Research Branding Project.
\nThe authors declare no conflict of interest.
Detonative combustion is a potential propulsion method for aerospace systems, offering high efficiency and low mechanical complexity. In comparison, deflagration is generally considered easier to control and has therefore dominated both experimental and real world engine applications. Research into detonation engines has been limited due to the lack of the necessary tools required to design and analyse such systems [1, 2]. As such, practical development of detonation engines, notably the pulsed detonation engine (PDE) and the rotating or rotational detonation engine (RDE), has been limited [3]. Nevertheless, the application of detonation engines for propulsion is very promising, already proving to be compact, whilst providing highly efficient thrust generation [3, 4, 5, 6, 7]. This supersonic thrust could be utilised independently as a rocket engine, or as part of a gas turbine system. Interest in the development of RDE technology has grown and the challenges of utilising a more thermodynamically-efficient cycle have become better understood [8, 9].
\nCombustion can occur at both subsonic and supersonic velocities, known as deflagration and detonation, respectively. Deflagration is typified by a regular flame, which propagates at less than the speed of sound. The heat release may be used to expel the resulting products, generating thrust. Deflagration has been used in a broad range of applications to produce power. However, in theory, deflagration lacks the thermodynamic efficiency of a detonation system, which is a system where combustion is initiated suddenly and “propagates utilising most, if not all, of the heat from combustion in an incredibly rapid shock wave” [10]. The heat generated by the exothermic chemical reaction sustains the shock wave. The concept of using detonation as a propulsion source has been proposed since the 1840s [11], but no substantial work had been completed until the 1950s when the development of models and concepts for a more lightweight and compact engine began [12]. The mechanisms that drive the detonation engine were not well understood at that time, so much of the research over the following decades was centred on the theoretical development of the engine.
\nAs the name implies, the pulse detonation engine (PDE) has been proposed for propulsion using detonations [12, 13]. In a PDE, a detonation chamber is filled with a fuel/oxidiser mixture, which is subsequently detonated. The accelerating detonation propels the exhaust from the chamber, thereby generating thrust. The chamber is then re-primed with fresh reactants, and re-detonated. With sufficiently high cycle speeds, large amounts of thrust may be generated in a small engine [14, 15]. This type of engine has been found to be particularly efficient [3, 16, 17].
\nDevelopment of the concept of a rotating detonation engine (RDE) began as a result of further work into detonative propulsion. This engine type is characterised by one or more detonation waves contained within an open-ended annular chamber. A fuel/oxidiser mixture is fed into one end of the chamber, and the detonation wave consumes these reactants azimuthally, expelling reactants from the open end of the annulus. In some literature, this type of engine may also be referred to as a continuous detonation wave engine (CDWE) or a spin detonation engine [6].
\nEarly research into rotating detonations was conducted in the 1950s [18], with attempts to document the structure of detonation shock waves, including those in spinning detonations, with further developments through the 1960s [1]. Subsequent research has been conducted into the effects of geometry, rotation characteristics, spiralling of the wave, and other variables [6, 19, 20, 21, 22]. Another advancement in general detonation research is improvements in deflagration to detonation transitions (DDTs), leading to a greater understanding of the consumption of fuel in the chamber [23, 24, 25]. Further work has developed prototype RDEs to measure the thrust of small-scale units as a baseline for larger model behaviour, utilising the results from experimental work to verify theoretical results, and to generate new results [26, 27, 28, 29, 30].
\nIn this review, several aspects of RDEs will be examined, starting with a brief comparison of RDEs and PDEs. This will be followed by further exploration into RDE operation, and methods of analysing RDEs, both experimentally and with numerical modelling. Finally, there will be an overview of areas still requiring further work.
\nThe majority of gas turbines that operate with a deflagration follow the Brayton (B) cycle: an isobaric (constant pressure) process, as shown in Figure 1 [31]. In contrast, a detonation is almost isochoric (constant volume) and may be modelled with the Humphrey (H) cycle, or, preferably, with the Fickett-Jacobs (FJ) cycle, which models detonation [3, 31]. The H cycle assumes that combustion occurs in a fixed volume, resulting in a pressure spike as the products expand. Differentiation between the H and FJ cycles in Figure 1 can be seen through the state changes of 2–\n
Thermodynamic cycles: Humphrey, Brayton, and Fickett-Jacobs. Adapted from Wolański [31].
where \n
Fuel | \nBrayton (%) | \nHumphrey (%) | \nFickett-Jacobs (%) | \n
---|---|---|---|
Hydrogen (H2) | \n36.9 | \n54.3 | \n59.3 | \n
Methane (CH4) | \n31.4 | \n50.5 | \n53.2 | \n
Acetylene (C2H2) | \n36.9 | \n54.1 | \n61.4 | \n
Calculated thermodynamic efficiencies for various fuels under different thermodynamic cycles [26].
In a PDE, such as that shown in Figure 2, a detonation chamber is filled with a fuel/oxidiser mixture and then ignited. The deflagration of the reactants accelerates, and through a deflagration-to-detonation transition (DDT), generates a shock wave. The products are accelerated from the end of the chamber, carried by the detonation front, generating thrust [30, 31]. For each cycle, the chamber must be purged and then refilled with fresh fuel/oxidiser mixture and then detonated again, limiting the maximum practical frequency of operation to an order of 100 Hz [32]. This results in poor efficiency when scaled to high thrust levels as the discontinuous thrust cycles may not be fast enough to approximate the continuity required for propulsion purposes [32, 33, 34, 35]. In some designs, it is also necessary to purge the chamber with an inert gas due to some residual combustion products remaining stagnant in the detonation chamber that interfere with the next detonation cycle. This process further restricts the operating frequency to approximately 50 Hz [3, 16].
\nLabelled schematic of a PDE. Adapted from [15].
In order to provide a more compact device, obstacles may be placed in the chamber to accelerate the DDT, but these reduce the specific impulse (\n
An RDE, such as the one shown as a cutaway in Figure 3, consists of an annular combustion chamber, into which fuel and oxidiser, either premixed or non-premixed, are fed through a series of orifices [3, 26, 36]. Each fuel/oxidiser mix requires a slightly different orifice geometry for optimal operation, so some devices have an adjustable injector plate [37, 38].
\nCross-section of a typical rotating detonation engine [38].
A detonation wave is initiated in the chamber, most commonly utilising a high speed flame that undergoes DDT by the time it enters the chamber [39, 40]. As this wave propagates around the chamber, it consumes the fuel, generating a high pressure zone behind it. This zone expands, and due to the geometric constraints, exits the chamber, generating thrust [35, 41]. An example of a CFD representation of the propagating wave can be seen in Figure 4 [42]. Behind the wave, fresh fuel enters the chamber at a constant rate, priming that section of the chamber for the wave to continue on the next revolution, thus making a self-sustaining wave as long as fresh mixture is supplied [35, 43]. The detonation waves generally propagate close to the Chapman-Jouguet velocity (discussed in Section 3.2) for each fuel type (typically 1500–2500 m s−1), so the effective operational frequency of current RDEs is approximately 1–10 kHz. Frequency is dependent on the chamber geometry, fuel, and thermal and frictional losses [31, 44]. The result is quasi-continuous thrust that approximates a continuous thrust through high frequency rotations, suitable for both direct propulsion applications and in the combustor of a gas turbine [31, 32, 45].
\n3D model of the detonation wave propagation in an RDE [42]. The short arrows indicate the flow of fuel/oxidiser into the engine, and the long arrow indicates the direction of detonation propagation.
Important areas of RDE research include determining the wave characteristics, geometric constraints, the effects of pressure on the injection characteristics, determining fuel flow properties, and examining the geometry and structure of the detonation wave [3, 4, 30, 31, 41, 42, 44]. Additionally, there has been research into potential applications of detonation engines in which an RDE may be applied, such as air-breathing vehicles and gas turbines [46]. Despite a growing body of work on RDEs, there are still large gaps in current understanding that restrict practical application. Notably, optimising the system for wave stability, ensuring reliable detonation initiation, and ensuring the RDE does not overheat, are significant challenges facing engine development prior to commercial applications. Further development in this area would allow an engine to operate reliably over extended durations, with well-designed chamber and fuel supply.
\nMost experimental RDEs are geometrically similar in design, consisting of an annulus made up of coaxial cylinders [5, 38, 47]. The chamber width, characterised by \n
There is reasonable consistency across published designs in the methods of initiating detonation waves in the RDE. Detonator tubes, in which a high-speed flame is encouraged to transition from deflagration to detonation, have been regularly and reliably used [26, 31, 32, 39, 49, 51]. It has been shown that the success of the detonation tube makes it an excellent initiator, producing a self-sustaining rotating detonation 95% of the time [26].
\nLike all jet-thrust reaction-based engines, the exhaust from a RDE may be channelled through a nozzle to increase thrust. Outlet and nozzle designs have varied across different RDEs. Many have not attached any nozzle, whilst some have chosen to utilise an aerospike [30, 31, 52]. The use of an aerospike increases performance through higher expansion area ratios, although the increased surface area results in higher heat flux and thus a loss of efficiency from the additional heat transfer [53]. Aerospikes may be directly attached to the end of the reaction chamber [31]. A diverging nozzle was found to increase the specific impulse, although the thrust increase was small, and for angles greater than 10°, the increase with angle was negligible [53]. None have made use of converging or converging-diverging nozzles, because the exhaust is typically flowing at supersonic velocities and thus could be choked through the converging cross-section. This would result in a loss of energy that would decrease the overall efficiency of the system.
\nA typical RDE, 90.2 mm in diameter, has been tested on a thrust sled [54]. It produced a thrust of 680 N using 176 g s−1 of C2H4/O2 propellant at an equivalence ratio of 1.48 [54]. As can be seen from Table 2, this is well below that required for typical supersonic flight applications. The specific impulse (\n
Engine | \nApplication | \nThrust | \nThrust to weight | \n
---|---|---|---|
Rolls-Royce Olympus 593 | \nBAC Concorde | \n38,000 lb (169,000 N) | \n5.4:1 [55] | \n
Teledyne CAE J402 | \nMcDonnell Douglas Harpoon | \n660 lb (2900 N) | \n6.5:1 [56] | \n
Pratt and Whitney F135 | \nLockheed Martin F-35 | \n191,300 N | \n11.47:1 (dry) [57] | \n
General Electric F414-400 | \nBoeing F/A-18E/F | \n98,000 N | \n9:1 [58] | \n
Experimental RDE | \nNone | \n680 N | \n3.47:1* [54] | \n
Thrusts and applications of various engines.
This is the thrust to weight ratio calculated using a pre-weight load cell system.
RDEs have been found to be successfully operable with a range of gaseous fuels including hydrogen, acetylene and butane, as well as various jet fuels [30, 31]. Air, pure oxygen, and oxygen-enriched air have all be used as oxidisers [31]. Each of these has a variety of advantages and disadvantages, in both performance characteristics, and ease of obtaining, transporting, and storing the oxidiser. Particular difficulty is noted in the transport of gases such as H2 and O2 due to the high risk regarding transportation and significant compression of these chemical species [59]. In the case of transporting liquid fuels such as LH2 and LOx cryogenic units are also required, adding to the already challenging process. The performance characteristics for several of these fuel types will be discussed further in Section 4.4.
\nThe detonation wave velocity in operational H2/air RDEs has been found to be on the order of 1000 m s−1 [30, 39]. In these RDEs, the operational frequencies are on the order of 4000 Hz, which produces quasi-continuous thrust [3, 32]. As wave speed is a key factor in the development of thrust, stable waves with high speeds are ideal for propulsion purposes. Stable detonation waves have reached maximum speeds in the range of 1500–2000 m s−1 in most designs using a H2/air or H2/O2 fuel/oxidiser combination (more commonly the former), suggesting that there is open research into whether there is upper limit for detonation wave speed, and subsequently the thrust that may be produced [3, 22, 26, 60]. However, at very high frequencies (19–20 kHz), there may be multiple waves rotating around the annulus [60, 61, 62]. Multiple wave modes of propagation appear to be affected by fuel/oxidant equivalence ratio as well as total mass flow rate through the system. The high frequencies are a result of multiple waves travelling at approximately the same speed as the normal single wave. This phenomenon has the potential to provide more continuous thrust, though the higher frequency may limit \n
There are several methods of recording data from an operating RDE. Thrust generated may be measured with a thrust plate, and the flow rates of fuel and oxidiser may be measured or controlled within the supply lines [30]. The details of the shock may be recorded with pressure sensors attached to the chamber head, and external cameras [30]. Pressure sensors record the increased pressure generated by the shock, and by using multiple sensors, the detonation wave propagation velocity may be determined. A high-speed camera may be set up to capture the operation of the engine, allowing various parameters to be recorded, including the detonation wave propagation velocity, although this method is limited by spatial resolution, as the channel width can be quite small [30, 39]. A camera may also be used to image from the side, if the outer surface of the annulus is made of a transparent material [63]. Additionally, OH* chemiluminescence may be used to detect, record, and analyse the detonation waves in UV-transparent optically-accessible RDEs [64, 65]. These radicals are indicative of the reaction zone, and so, by analysis of their chemiluminescence, the structure of the detonation can be inferred. Often this detection is done through a quartz side window integrated into the RDE [63]. Peak intensity of the OH* chemiluminescence indicates the location of the detonation front, and so the effects of varying factors such as equivalence ratio and chamber geometries can be documented. Images are often phase-averaged and can by “unwrapped” for comparison to equivalent two-dimensional, “linearised”, simulations and designs.
\nThe structure of shock waves in gases was examined in detail by Voitsekhovskii in 1969, including those of shock waves in spinning detonations [66]. These examinations resulted in the first diagram of the structure of a spinning shock wave, and the identification of a number of features, which are identified from the computational model of an RDE shown in Figure 5 [32]. This model used premixed hydrogen/air as the fuel/oxidiser mixture and has been “unwrapped” into two-dimensions (this approach is described in Section 5.1). Feature A is the primary detonation front; Feature B is an oblique shock wave that propagates from the top of the detonation wave; Feature C is a slip line between the freshly detonated products and older products from the previous cycle; Feature D is a secondary shock wave; Feature E is a mixing region between the fresh premixture and the product gases, where deflagration may occur [67]; Feature F is the region where the injector nozzles are blocked; and Feature G is the unreacted premixture.
\nPressure contour indicating the cell structure of a detonation wave in an RDE with a premixed supply, taken from a computational modelling study [32]. (a) Pressure contour indicating the full structure of detonation in an RDE, “unwrapped” into two dimensions. Feature A is the detonation wave, Feature B is the oblique shock wave, Feature C is the slip line between the freshly detonated products and products, Feature D is a secondary shock wave, Feature E is a mixing region between the fresh premixture and the product gases, Feature F is the region with blocked injector nozzles, and Feature G is the unreacted premixture. The arrow denotes the direction of travel of the detonation wave. (b) A close-up image of the detonation front.
In both Figure 5b and Figure 8c (Section 4.3) the detonation cell structure can be seen, with high pressure zones outlining each cell. These lines of high pressure contain triple points, where the transverse and oblique shocks meet the Mach stem of the detonation wave [68, 69]. The concentrated pressure at these triple points is the point of maximum energy release, and the subsequent pressure spike when two triple points collide generates new detonation cells [68, 70]. While this generation is the main reason behind the propagation of detonation waves, the triple points still require further investigation as to the effects they have on the overall characteristics of a detonation wave [70]. The direction of these triple points can be seen as the white lines in Figure 8c with trailing high pressure zones forming the walls of the detonation cells. As the detonation cell width is defined by the geometry of the system and the chemical composition of the detonating fuel, it seems that the triple point velocity and direction must also directly relate to these factors, although limited research has been done to formally connect these points.
\nIn an RDE, the detonation wave remains attached to the base of the annulus, as illustrated in Figure 5b and in Figure 6 [3, 6, 71]. This is due to the continuous fuel/oxidant supply [3, 71], as a premixture or allowed to mix in the chamber ahead of the detonation wave [32, 39]. There is also some evidence that stable, lifted waves may also be possible if there is insufficient mixing between the fuel and oxidant [27, 44]. The propagating detonation wave combusts the reactants [32, 39] which generates a region of extremely high pressure immediately behind the wave. This pressure is on the order of 15–30 times higher than the pressure ahead of the detonation, preventing flow through the injectors [3]. The high pressure zone expands in a Prandtl–Meyer fan, allowing fresh fuel and oxidiser to enter the chamber [35]. This expansion propels the mixed products axially along the engine, generating thrust. In addition to the primary shock, an oblique shock and a secondary attached shock are also generated (Features B and D in Figure 5a).
\nDiagram showing the general structure of the detonation in an unwrapped RDE [3].
At the interface between the premixed reactants and the combustion products, there is a significant difference between the conditions of the unburnt fuel/oxidiser mixture and the products. This causes some deflagration along the slip line, as shown in Figure 6, generating Kelvin-Helmholz instabilities, which vary the detonation propagation velocity [3, 22, 72, 73]. This decrease in the propagation velocity results in an increase in the pressure, disturbing the oncoming shock wave and forcing the sonic flow directly behind the shock wave to undergo supersonic flow acceleration [74]. As shown in Figure 6 there is a section of injector flow blockage that occurs as the wave passes the fuel array. The high pressure front from the shock wave causes stagnation of the injector flow, or even back-flow which, if not handled, could cause catastrophic failure of the system [3, 6, 36]. This back-flow is a strong reason as to why the fuel and oxidants should not be premixed in practical systems or experimental investigations as it can result in flashback.
\nThe Chapman-Jouguet (CJ) condition can be defined as the requirements for the leading shock of a detonation to not be weakened by the rarefactions of the upstream detonation products [75]. This sonic plane then acts to allow the supersonic expansion of the detonated gases to occur without disturbance by rarefactions downstream of the flow [75]. The CJ condition can be used to approximate the detonation velocities in three-dimensional models but is better suited to a one dimensional analysis with an infinitesimally thin detonation front [76]. Despite this, it is used in most instances of numerical modelling as a guide as to whether the wave is performing as expected for the given parameters of the RDE [4, 6, 27, 31, 32, 42, 75, 77]. Chapman and Jouguet’s theory only applies to kinetic energy, disregarding the chemical energy of the reacting species, and hence, the Zel’Dovich-von Neumann-Doring (ZND) model is used as a more complete representation of the shock, taking into account the finite chemical reaction area directly upstream of the leading shock [3, 21, 45, 75, 78, 79, 80].
\nThere are two methods which may be used to initiate the detonative shock in an RDE—directly in the chamber, or indirectly via a high speed flame in a deflagration to detonation transition (DDT) tube [26, 31, 39, 49, 51]. These tubes are very similar in structure to a PDE. Directly initiating the detonation in the chamber via commercial spark plugs has been found to be generally unreliable, with only a 40% success rate for shock initiation when using CH4 in O2 [26]. Particular difficulty is noted in ensuring the detonation travels in the desired direction [26, 32]. In contrast, indirect initiation via a DDT tube has had a 95% success rate for the same fuel/oxidant combination [26, 31]. The indirect method involves using a detonator tube that can be set up in any orientation relative to the chamber, although tangential is favoured for initiating the detonation direction. Initiation is then caused by a small volume of a highly detonative mixture being ignited by spark plugs before DDT occurs, thus initiating the RDE. Perpendicular initiation can also be used, but this often results in the development of two detonation waves that rotate around the chamber in opposite directions [31]. Collision of these opposing waves usually destabilises the system as the waves weaken and reflect back in the direction of origin [31]. Desired direction also appears to be affected by initial total pressure and ignition distribution around the fuel plenum [27, 81]. For a desired single wave direction and propagation, tangential initiation is the most suitable method. Although slightly less compact due to the initiator tube, this may be reduced by placing obstacles in the tube to accelerate the DDT, or by using a more detonative fuel than that used in the primary process [31, 48, 62, 82, 83]. Using an initiator tube, however, may produce small wavelets ahead of the main detonation front, which, if present, reduce the detonation propagation velocity by up to 60% [84]. Once the main detonation is running, the interface between the initiator tube and main chamber must be closed off prior to the shock completing a revolution of the chamber [84]. Additionally, there may be a slight delay, on the order of milliseconds, between the detonation exiting the DDT tube and the commencement of full RDE operation in order to purge the spent reactants from the DDT process [85]. This delay seems to only be transient with no large effects on shock structure or stability, and the excess products are expelled along with the rest of the exhaust [85].
\nThree-dimensional modelling has shown that increasing the width of the channel—whilst maintaining the equivalence ratio, injection pressure, chamber length, and injector configuration—increases the detonation velocity, but the transverse shock wave ceases to be aligned with the radial direction [22, 27, 86]. As can be seen in Figure 7, the point of contact with the inner wall begins to lead the detonation wave as the channel width increases [22]. This phenomenon generates reflected shocks from the outer annulus wall, which may produce instabilities in the primary shock. It has been suggested through qualitative observation, however, that the effect of upstream reflected shocks on the shock structure may only be minimal [39, 87]. Once the channel becomes sufficiently wide, as shown in Figure 7c, the shock wave detaches from the inner wall, briefly forming a horseshoe shape against the outer wall [22]. This allows significant amounts of fuel to pass through the engine without combusting, and produces large instabilities and fragmentation in the detonation wave, which causes the structure to collapse [22]. These lead to a significant loss of performance, and secondary detonations in the exhaust [22]. It has been noted that increasing the channel width also results in increased variance of \n
Schematic of three different RDE designs showing the effect of varying the channel width on detonation structure. Arrows show detonation wave propagation direction. The red line is detonation wave, indicative only. Based on research from [22]. (a) Narrow channel, (b) mid-sized channel, and (c) wide channel.
It has been found that using a fuel-rich mixture produces stable waves with high detonation velocity and efficiency [80, 88]. Higher mass flow rates have also been attributed to increasing the chance of a stable wave being formed [6, 89]. Additionally, it has been shown that the equivalence ratio has a strong influence on the effectiveness of detonation and the stability of the system [80]. Detailed investigation has shown that the stability of the system is improved with increased equivalence ratio, but indicated a maximum equivalence ratio of 1.27, before the detonation wave became short-lived and transient, which is unsuitable for practical purposes [60]. Whether this is a universal limit, or a limit of that particular investigation is unclear, and requires further research. Furthermore, the findings indicated that lower equivalence ratio influences the number of wave fronts produced, with stoichiometric seeming to be a transition point to a stable one wave propagation mode [60, 86, 90]. It is interesting to note that for lean mixtures, the initial channel pressure needs to be higher for a stable detonation to propagate [88].
\nThe wave propagation velocity varies with the fuel/oxidiser combination. A variety of mixtures have been tested in a detonation tube of an RDE, with their wave propagation velocities and wavefront pressures shown in Table 3, which is indicative of their varying performance in an RDE. It should be noted that the pressure, energy and specific impulse in Table 3 are determined with a detonation tube, and provide a numerical comparison between each fuel/oxidiser combination. Hydrogen/oxygen mixes have been ideal for modelling purposes due to the simple chemistry involved, and are often used in experimental work due to the predictable behaviour. Additionally, the high detonation propagation velocity and wavefront pressure of hydrogen makes it a suitable fuel for real applications. Another common fuel choice is methane, due to the satisfactory propagation velocity and specific impulse in testing [31]. As mentioned in Section 2, the theoretical \n
Fuel mixture | \nDetonation speed (m s−1) | \nWavefront pressure (atm) | \n\n\n | \n\n\n | \n
---|---|---|---|---|
Hydrogen/oxygen | \n2836 | \n18.5 | \n8.43 | \n289.39 | \n
Hydrogen/air | \n1964 | \n15.5 | \n3.48 | \n200.41 | \n
Ethylene/oxygen | \n2382 | \n31.9 | \n5.23 | \n243.06 | \n
Ethylene/air | \n1821 | \n18.2 | \n2.85 | \n185.82 | \n
Ethane/oxygen | \n2257 | \n29.0 | \n4.87 | \n230.31 | \n
Ethane/air | \n1710 | \n15.8 | \n2.49 | \n174.49 | \n
Propane/oxygen | \n2354 | \n34.2 | \n5.18 | \n240.20 | \n
Propane/air | \n1797 | \n17.5 | \n2.80 | \n183.37 | \n
Fuels, wave propagation velocities and pressures, heat of combustion (\n
Transportability of fuel, and maintenance of fuel lines, are deciding factors in determining which fuels can be used. These issues are especially important for aerospace applications. Gases such as H2 and O2 are particularly volatile and reactive, hence can be difficult to transport in the large quantities needed for use in an RDE. Therefore, gaseous fuels and non-air oxidisers are challenging and largely unsuitable for real world applications [5]. However, H2 does have a high heat of combustion that is not matched by liquid hydrocarbon fuels. Jet fuel, kerosene, octane and other long-chain hydrocarbons provide a practical alternative to the H2/O2 mixture though. High volumetric energy density as a result of liquid state, as well as greater ease of transportability makes these hydrocarbons a more feasible fuel choice.
\nThere are several issues regarding fuel choice that deserve further discussion. In particular, the use of cryogenic fuels for cooling the engine is a beneficial approach, increasing thermal efficiency, as well as reducing the thermal load on other components such as mounting systems [3]. Another advantage is a higher volumetric energy density that comes from the compression of normally gaseous fuel sources. Testing of liquid oxygen (LOx) and gaseous or liquid hydrogen (GH2/LH2) fuel/oxidant systems for viability has been performed, but implementation in real world scenarios is challenging [92, 93]. Liquid hydrocarbons require further investigation to demonstrate their effectiveness in producing thrust through detonation [30], particularly because of the need for flash vapourisation to avoid multiphase effects in the mixing process [30, 51].
\nAn axial fuel injection process through a circumferential orifice plate was consistent across most simulations and real world models as an injection scheme [5, 6, 22, 26, 30, 32, 36, 38, 39, 41, 42, 42, 52, 61, 62, 82, 86, 88, 92, 94, 95, 96, 97, 98, 99]. Further research is required into fuel blockage effects due to the high pressure of the shock wave, with particular emphasis on the effects of increasing fuel pressure to alleviate blockage and increase overall engine performance [100]. In the majority of numerical and physical models, such as Figure 3, fuel and oxidiser are injected through an orifice place around the annulus, allowing them to continually feed the propagating detonation wave. Typically, the fuel and oxidiser are fed in separately, and allowed to mix in the chamber [26]. This design is also used in most numerical models, although some have used premixed fuel/oxidiser as a simplified boundary condition. Almost all physical designs have been built without a premixed fuel/oxidant injection scheme due to concerns with flashback [99]. In a premixed design, the shock wave may propagate into the injection plenum, carrying with it the reaction front. With sufficient pressure though, typically 2.3–3 times the chamber pressure, this can be avoided [32].
\nInvestigation into flow characteristics of a turbulent inflow have shown that there are specific zones within the chamber which favour different forms of combustion: some zones favour deflagration, and others favour detonation [101]. The larger deflagration zones created reduce the thermodynamic efficiency of the engine, indicating that fuel flowrate influences the reliability of an RDE [101]. It has been suggested that high inlet velocities generate incomplete combustion and hot spots, reducing detonation wave stability and reducing system efficiency, although further research is required [102]. As indicated in Section 3.3, the introduction of instabilities in the flow profile can decrease the efficiency of the engine as well as disrupt the detonation wave itself. Further findings indicate that increasing the fuel injection area, particularly by increasing the number of orifices, results in more efficient pressure gain [86, 97, 99, 103]. This produces a larger expansion wave of the previous combustion reactants, generating higher thrust, without disrupting the flow-field characteristics [98]. However, with lower fuel injection velocities comes an increased risk of flashback. There is, therefore, some optimal fuel injection area for operation which requires further work to verify [98]. Finally, the pressure ratio between the inlets and the engine outlet also has an effect on the \n
Existing RDEs tend to be relatively small, and therefore may need to be scaled up, or arranged in parallel, to produce thrust required for practical applications, such as those listed in Table 2. One method of scaling RDEs is to run multiple identical devices in parallel, in a similar manner to that used to run multiple PDEs [34, 104]. However, this would require more complex plumbing, increasing the weight of the overall system, and thus decreasing the thrust-to-weight ratio. However, this solution has not been explored in any depth and its viability is unknown.
\nIn order to make larger RDEs, in-depth research into the geometry of the combustion chamber is required. A number of relationships between the critical detonation wave height and the various dimensions have been identified [27, 30]. Detonation structure, as described in Section 3.1 is composed of small diamond shaped detonation cells that make up the front. The widths of these cells are dependent on the energy of the detonation (related to the fuel in use) as well as the available geometry for detonation. In this way, the equivalence ratio can be a large determining factor [30, 105, 106]. Critical minimum fill height is the minimum mixture height required for a detonation wave to propagate through a given fuel/oxidiser mixture. It has been found that the critical minimum fill height, \n
and the minimum channel width, \n
Finally, the minimum axial length of an RDE, \n
although lengths under 2–3 times the minimum result in reduced efficiency due to incomplete combustion [27]. However, in simulations, it has been suggested that for low inlet-nozzle pressure ratios the wave the wave height grew with the chamber length, reducing the \n
Geometric parameters of an RDE. The red area is the area filled by the fuel/oxidiser mix in which the detonation propagates. (a) Top view, (b) side view, and (c) detonation cell width adapted from [79].
There is not yet any theoretical data for \n
Modelling a large-scale RDE presents a challenge due to increasing computational requirements with increasing size, so limited work has been done in this area. Nevertheless, a larger scale experimental RDE has been demonstrated [5]. This RDE had an outer chamber diameter of 406 mm, and a channel width of 25 mm, and an air inlet slit that could be varied across the range 2–15 mm [5]. It produced a consistent thrust of 6 kN with a combined fuel/oxidiser flow rate of 7.5 kg s−1, whilst also producing an \n
The design used in most simulations and experimental work is a coaxial cylinder structure [3, 27, 31, 35]. This simple geometry is advantageous for both modelling and manufacturing. Design variations including using nozzles, aerospikes such as that shown in Figure 9, or an entirely hollow cylinder, have been utilised in several RDE designs [5, 52].
\nExample of an aerospike nozzle configuration [52].
Alternative chamber geometries have been largely limited to adjustments in the diameters of the chamber [4, 42], including with different sized engines [15, 31, 39, 54]. Other work has been conducted on a single RDE with interchangeable outer wall sections [22, 30]. As noted in Section 2 and Section 3, both of these factors influence the stability and the performance of RDEs. The effect of varying the length of the chamber on the detonation propagation has been investigated, which led to the previously mentioned requirement that the chamber be at least twice, and preferably four to six times, the fuel fill height [4, 96].
\nHollow RDEs, dubbed “centrebodiless” designs, have been tested with two different designs [50, 61]. One design was identical to a conventional RDE 100 mm across, but the inner cylinder terminated parallel to the fuel/oxidiser injectors [61]. In this design, tested with 169.7 g s−1 of CH4/O2 at an equivalence ratio of 1.154, it was found that the detonation was unstable [61]. The fuel and oxidiser were free to move into the space usually occupied by the centre body, and thus insufficiently mixed to sustain a stable detonation [61]. However, when the same geometry was tested with 253.3 g s−1 of CH4/O2 at an equivalence ratio of 0.665, the mixture became sufficiently mixed to sustain a stable four-wave detonation structure [61]. Another design was completely hollow, allowing oxygen-enriched air to be pumped through the centre of the chamber, and fuel was supplied around the edge [50]. In this design, stable detonations, operating at \n
The attachment of turbines to RDEs has been proposed [8, 9, 31, 32, 45]. It has also been noted that there is a secondary shock propagating from the detonation, which exits the outlet of the chamber [32]. However, turbine blades are sensitive to shocks. As such, the effect of the secondary shocks on the blades of potential turbines must be investigated. It is worth noting that an experimental PDE array has been tested with an attached turbine, in the form of an automotive turbocharger [31]. In that case, a buffer chamber was inserted between the PDE and the turbine [31], and such a technology may be suitable for RDEs.
\nComputational fluid dynamics (CFD) modelling is a powerful tool for the analysis of rotating detonations prior to, or in tandem with, experimental systems. The majority of numerical studies have aimed to provide in-depth understanding and details of the detonation structure [22, 41, 62, 67, 72, 94, 107, 108] or assess the physical and modelling factors influencing performance [32, 67, 73, 109].
\nComputational models of the azimuthal detonations in RDEs may use full three-dimensional geometries [20, 22, 67, 94, 95, 107, 110] or simplified, two-dimensional geometries [6, 32, 41, 43, 62, 72, 73, 108, 109, 111, 112, 113, 114]. The former, higher-fidelity, approach can incorporate complex geometric and flow features, although require \n
Two-dimensional modelling of RDEs assumes that the flowfield along the centre of the channel is representative of shock and deflagration structure across the entire width. Consequently, this inherently assumes slip-wall conditions and that the detonation-front is normal to the two-dimensional geometry. In the unwrapped two-dimensional geometry, all fuel is injected axially from one edge (the bottom edge in Figure 5a [32]) and is exhausted through the opposite edge (the top edge in Figure 5a) [6, 32, 72, 111]. It therefore follows that all exhaust products must leave the domain axially, due to conversation of angular momentum. This was confirmed in early two-dimensional modelling, which found that the density-averaged azimuthal velocity was less than 3% of the axial velocity [41]. Such a criterion could be extended to assessing whether a three-dimensional model, at some fixed radius within the channel, could be treated as an unwrapped planar domain.
\nDetonation wave curvature, imperfect mixing, three-dimensional turbulent structures and transverse shocks are features reported in three-dimensional computational modelling [22, 67, 79, 94, 107] and experimental studies [62]. These features arise from the effects of channel size [22], discrete injectors [79] and interactions between transverse waves and walls [62, 79]. These features are inherently three-dimensional and cannot be captured using planar, periodic models, and require more complex computational geometries.
\nFuel/oxidiser inlets may be modelled as simple points, lines, surfaces or complex, discrete injectors. The latter may be treated as a series of inlets in two-dimensional models, assuming upstream micro-mixing [109, 112]. Differences in the injector configuration can lead to differences in detonation pressure [112], or lifted flame behaviour in the event of poor mixing in a partially premixed system [109]. The study which observed the latter phenomenon, however, was undertaken using the Euler equations, which may affect the fidelity of modelled mixing (discussed later in this section), and a simplified induction parameter model (described in Section 5.4) [109], although this has also been observed experimentally in C2H2-fuelled RDEs [115].
\nInlet boundary conditions in premixed models, are often defined by inlet throat-to-nozzle-exit ratios. These, and the set upstream pressure, control whether the inlets are blocked, subsonic or choked and are chosen to range from 0.1–0.2 [6, 109, 110, 112], although ranges as large as 0.07–0.3 have shown little effect on \n
Rotating detonation engines have often been numerically modelled using the compressible Euler Equations [6, 20, 32, 41, 43, 62, 72, 95, 108, 110, 111, 112]. The Euler equations conserve momentum, mass and energy, but do not account for viscosity, following the assumption that the detonation structure dominates viscous dissipation. Viscous effects may, however, be incorporated into numerical studies of RDEs through the use Reynolds-averaged Navier Stokes (RANS) modelling [107, 113], LES, LES-RANS hybrids such as [improved] delayed detached eddy simulations (IDDES) [67, 94], or DNS [22]. Of these approaches, Euler, IDDES and DNS studies [22, 41, 67] have all been able to capture Kelvin-Helmholtz instabilities in the unreacted/reacted and the post-shock mixing layers (see Figure 5a as an example), using sufficiently small element sizing in both two- and three-dimensional models.
\nThe grid required to resolve large structures in RDE mixing layers is dependent on the size of the geometry. Elements of 200 μm have been shown to predict shear layer instabilities using either Euler equations or IDDES in an RDE with a mid-channel diameter of 90 mm [67] and an \n
Both viscosity and species diffusion have been stated as critical features in non-premixed models of RDEs, promoting the use of IDDES or LES in modelling studies [67]. In contrast, a negligible dependence of detonation velocity or \n
Although the Euler equations cannot account for viscous effects, such as wall shear-stress and heat transfer, these have a small, but non-negligible, effect (\n
Incorporating viscosity and thermal wall-effects into IDDES simulations requires significant computational resources. One such study required a computational mesh of \n
The majority of numerical RDEs works to date targeted H2/air and H2/O2 systems [6, 20, 22, 41, 62, 72, 73, 79, 94, 95, 111, 112, 118, 121, 122], given their relatively simple chemistry in comparison with both small and large hydrocarbons. Nevertheless, limited data are also available for linearised CH4/air and C2H4/air systems [114].
\nThe simplest approach to describe the chemistry is that of a one-step irreversible reaction [6, 43, 62, 95, 108, 109]. This assumption has been widely used to numerically investigate various aspects of fully premixed canonical RDE cases and useful insights have been gained [6, 32, 95]. However, it is well known that such a simplification is not able to accurately quantify many detonation responses of interest (e.g. upstream deflagration phenomena [109], triple shocks structure [79, 116]), mainly due to the sensitive Arrhenius nature of the reaction rate to temperature variations. Also, the use of ad hoc correlations of the experimental data with adjustable kinetic parameters (e.g. reaction order, activation energy) are only valid for a limited range of the system and thermodynamic parameters [116].
\nSimplified approaches to chemical kinetics may employ a one-step reversible reaction [20, 62] or a two-step mechanism [22, 41] to describe the chemistry within a system. In particular, for the one-step case, the forward reaction rate is calculated using the classical Arrhenius equation with the reaction rate constants tuned from a reference case while the backward reaction rate is calculated from the assumption of local chemical equilibrium [20, 62]. This approach has been validated against detailed chemistry for a 1D model [20]. For canonical 2D premixed RDEs, a one-step reversible reaction is not able to accurately capture the post-detonation temperature while it is able to predict both the experimental pressure and velocity fields [20]. In addition, it was also found that this approach can be successfully implemented to describe stratification effects in three-dimensional non-premixed RDE systems [62].
\nFor the one-step case, a number of two- and three-dimensional premixed RDE simulations employ an induction-time parameter model (IPM) to compute the chemical source terms [6, 32, 43, 109]. The IPM has shown reasonable accuracy for the prediction of detonation wave propagation in premixed systems [108], as the induction time is derived from the same configuration as the CJ wave-speed [116]. In addition, it is computationally inexpensive as a global induction parameter allows for release of energy over a finite period of time. Nevertheless, the IPM lacks the flexibility to accurately describe the physics occurring in more realistic non-premixed systems [94]. The thermodynamic properties of the single product species employed in this model are dependent upon the equivalence ratio of the fuel/air mixture. Therefore, this approach cannot easily handle the spatially varying local equivalence ratio occurring in a non-premixed system [116]. This model also lacks the capability to capture the low-pressure heat release and the change in equilibrium chemistry of post-detonation products. Finally, this method requires a priori calculation of the CJ induction time, but the computed detonation velocities in detailed simulations can be significantly higher than that of CJ velocity [94]. If this approach is extended to a two-step reaction model (consisting of an induction reaction followed by an exothermic recombination reaction), two progress variables are obtained and need to be solved in lieu of individual species concentrations. This approach is termed two-parameter progress variable, and it has been successfully applied for premixed systems [22, 41]. Nevertheless, the variation of the two source terms is extremely sensitive to the choice of the constants adopted [22]. Global chemistry has also been implemented through the well-known PDF method [107], although this approach is generally used for detailed chemistry in combustion processes [123].
\nFinite-rate kinetics and the associated kinetic mechanisms are needed to capture complex phenomena such as near-limit propagation leading to quenching of the detonation wave [116]. This is mainly because the use of a one-step reaction precludes the influence of chain-branching-termination mechanisms that are invariably multi-step in nature. In this regard, an advanced approach is the induction-length model, which concerns determining the induction length for adiabatic propagation and using it to estimate global detonation parameters such as the cell size of steady propagation and the wave curvature at quenching [116]. This study showed that at least a four-step mechanism is required to achieve acceptable predictions in CJ detonation.
\nModels of RDEs using H2/air, H2/O2, CH4/air and C2H4/air mixtures have employed detailed chemistry and simplified configurations [68, 72, 73, 79, 111, 112, 114, 118, 122], although only limited studies are available in comparison with simplified (one- or two-step) chemistry, given the relatively large computational expense required and the current computational resources. A set of 8–9 chemical species and 18–21 elementary reactions are generally employed for H2 systems [72, 112], while 21–22 species and 34–38 reactions are used for simple hydrocarbons systems [114]. These studies highlighted that the use of detailed chemistry is needed to accurately predict the energy-release pattern in RDEs and complex characteristics, including re-ignition, number of triple points and transverse waves [68].
\nA linearised model may be constructed to simulate the operation of an RDE [79, 124]. These models, shown in Figure 10, are known as linearised model detonation engines (LMDEs). In this model, fuel is fed into the chamber, and a transverse shock wave propagates through it. This occurs in much the same manner as in an RDE. However, the chamber is rectangular, and so the detonation only makes a single pass through the chamber [79, 124]. Both computer models and practical experiments have been run in three different modes, all using fresh supplies [79, 125]:
The chamber is pre-filled with premixed fuel/oxidiser, and then the detonation is initiated.
The chamber is pre-filled with an inert gas, then premixed fuel/oxidiser is injected and the detonation is initiated simultaneously.
The chamber is pre-filled with oxidiser, then fuel is injected and the detonation is initiated simultaneously.
An example linearised model detonation engine [79].
LMDEs have been used to characterise the detonation process, by allowing both sides of the chamber to be imaged through quartz walls, or the density field imaged through the use of the Schlieren technique [79, 126]. It has been found that the critical fill height of an LMDE is about \n
Computer modelling of an LMDE indicated that the propagation of a detonation wave was not affected by the turbulence caused by in-chamber mixing of fuel and oxidiser [118]. However, the presence of this turbulence did cause the reaction zone to trail the detonation wave [118]. A model of an LMDE was also used to test the result of applying different back pressures, such as might occur if a nozzle or a turbine was attached to an RDE [114]. This indicated that increased back pressure also increased the detonability of the fuel mixture, but also restricted the acceleration of the products, which, in some cases, led to the production of tertiary shock waves to sufficiently compress the flow to match the exit plane conditions [114]. However, as noted previously in Section 2, nozzles have very limited benefit [53], and, as noted in Section 4 the effect of secondary and tertiary shocks on a turbine may be problem.
\nRotating detonation engines have the potential to provide a significantly more efficient combustion cycle than deflagration-based engines. The application of this technology to turbines promises to increase the thermodynamic efficiency of these engines to previously unattainable levels. Additionally, RDEs as a standalone engine hold significant promise for both air-breathing and air-independent rocket propulsion. However, there exists a large body of research and development work still-to-be undertaken, including:
Nozzles have been shown to have limited benefit to the thrust generated by RDEs. However, varying the angles of the walls of an RDE, either independently or together, may simulate the effect of a nozzle to provide a slight benefit to performance. It remains unknown what effect such modifications to the conventional cylinder might have.
Comparisons of thrust to weight ratios between experimental RDEs and conventional rocket engines show similar values, indicating that an RDE could represent a method of propulsion in space. This has not been widely explored as an option, and would benefit from experimental work in vacuum conditions or microgravity conditions.
It has been suggested that there may be a maximum equivalence ratio at which an RDE will operate, but further investigation is required to determine if this is a universal limit, and identify ways to lower the limit.
Triple points appear to have significant effect on the propagation of the detonation wave but little work has been done on determining the constraints, besides chemical composition, on the formation of stable and consistent triple points as well as the effect of those parameters on other characteristics of the triple points such as peak pressure and propagation direction. Findings would be beneficial in terms of properly defining the parameters that affect \n
Very few studies have provided a mathematical relationship between the detonation cell width and the geometry requirements of the chamber. More supporting work to help refine and verify or dispute the relationships that have been established needs to be done, so that in the future, specialised design needs can be catered for through knowing the geometry and cell width of fuel types.
Varying the channel width has been noted to affect the stability of the detonation wave in an RDE. As such, this is likely to affect the performance of such devices. Further research is required to determine what the optimal width would be for different design requirements.
It is established that RDE chambers need to be at least twice as long as the fuel fill height, and increasing the length four to six times the fill height improves the efficiency. However, depending on the ratio of inlet pressure to nozzle pressure, such a length increase may also result in reduced \n
So-called “centrebodiless” designs have been explored, and proposed for use in afterburners. However, they have not been modelled or tested with heated high velocity air, as would be typically found at the outlet of a conventional jet engine, so their potential performance remains unknown.
It has been demonstrated that the thrust produced by RDEs scales non-linearly with engine size, but they are not yet approaching the size required to replace most existing gas turbines. It remains unknown if an RDE can be scaled up sufficiently to provide the thrust levels offered by contemporary gas turbine engines.
It has been suggested that a turbine could be attached to an RDE. However, the effects of the various shocks on a turbine have not been explored. In particular, the oblique shock (Feature B in Figure 5a) has been shown to propagate out of the chamber, and is likely to have significant effect on the viability of using a turbine.
The invsicid Euler equations have been demonstrated to over-predict deflagration in three-dimensional computational models of premixed RDEs, even with the use of detailed chemistry. Their validity in non-premixed RDE configurations, with deflagration upstream of the detonation and the potential to produce lifted detonation waves, still requires rigorous assessment.
Viscous and thermal wall-effects in RDEs have significant effect on RDE performance characteristics, and may be essential in accurately reproducing experimentally measured values. Understanding of the appropriate numerical modelling approaches of these effects, however, is still immature, owing to the computational resources required for sufficiently fine resolution of near-wall grids.
The computationally predicted wave-speeds and plenum pressures in RDEs are significantly different to those measured experimentally. It has been proposed that this could be partially due to baroclinic vorticity, resulting from interactions between detonation waves, fresh reactants, deflagration reaction-zones and post-combustion products, although this is yet to be analysed in detail in either full RDEs or linearised models.
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
",metaTitle:"IntechOpen Women in Science Program",metaDescription:"Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.",metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"At IntechOpen, we’re laying the foundations for the future by publishing the best research by women in STEM – Open Access and available to all. Our Women in Science program already includes six books in progress by award-winning women scientists on topics ranging from physics to robotics, medicine to environmental science. Our editors come from all over the globe and include L’Oreal–UNESCO For Women in Science award-winners and National Science Foundation and European Commission grant recipients.
\\n\\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
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\\n\\nAdvantages of Publishing with IntechOpen
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\n\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
\n\nAll project proposals go through a two-stage peer review process and are selected based on the following criteria:
\n\nPlus, we want this project to have an impact beyond scientific circles. We will publicize the research in the Women in Science program for a wider general audience through:
\n\nInterested? If you have an idea for an edited volume or a monograph, we’d love to hear from you! Contact Ana Pantar at book.idea@intechopen.com.
\n\n“My scientific path has given me the opportunity to work with colleagues all over Europe, including Germany, France, and Norway. Editing the book Graph Theory: Advanced Algorithms and Applications with IntechOpen emphasized for me the importance of providing valuable, Open Access literature to our scientific colleagues around the world. So I am highly enthusiastic about the Women in Science book collection, which will highlight the outstanding accomplishments of women scientists and encourage others to walk the challenging path to becoming a recognized scientist." Beril Sirmacek, TU Delft, The Netherlands
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USA, CRC Press Taylor & Francis, Asia Pacific, Trans Tech Publications Ltd., Switzerland, and Materials Science Forum, USA. 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Omar obtained\nhis Bachelor degree in electrical and\nelectronics engineering from Universiti\nSains Malaysia in 2002, Master of Science in electronics\nengineering from Open University\nMalaysia in 2008 and PhD in optical physics from Universiti\nSains Malaysia in 2012. His research mainly\nfocuses on the development of optical\nand electronics systems for spectroscopy\napplication in environmental monitoring,\nagriculture and dermatology. He has\nmore than 10 years of teaching\nexperience in subjects related to\nelectronics, mathematics and applied optics for\nuniversity students and industrial engineers.",institutionString:null,institution:{name:"Universiti Sains Malaysia",country:{name:"Malaysia"}}},{id:"191072",title:"Prof.",name:"A. K. M. Aminul",middleName:null,surname:"Islam",slug:"a.-k.-m.-aminul-islam",fullName:"A. K. M. Aminul Islam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191072/images/system/191072.jpg",biography:"Prof. Dr. A. K. M. 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Conducting research on the development of hybrid vegetables, hybrid Brassica napus using CMS system, renewable energy research with Jatropha curcas.",institutionString:"Bangabandhu Sheikh Mujibur Rahman Agricultural University",institution:{name:"Bangabandhu Sheikh Mujibur Rahman Agricultural University",country:{name:"Bangladesh"}}},{id:"91977",title:"Dr.",name:"A.B.M. Sharif",middleName:null,surname:"Hossain",slug:"a.b.m.-sharif-hossain",fullName:"A.B.M. Sharif Hossain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Malaya",country:{name:"Malaysia"}}},{id:"97123",title:"Prof.",name:"A.M.M.",middleName:null,surname:"Sharif Ullah",slug:"a.m.m.-sharif-ullah",fullName:"A.M.M. 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