426 resultados para simulation result


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In this paper, the initial stage of films assembled by energetic C36 fullerenes on diamond (001)–(2 × 1) surface at low-temperature was investigated by molecular dynamics simulation using the Brenner potential. The incident energy was first uniformly distributed within an energy interval 20–50 eV, which was known to be the optimum energy range for chemisorption of single C36 on diamond (001) surface. More than one hundred C36 cages were impacted one after the other onto the diamond surface by randomly selecting their orientation as well as the impact position relative to the surface. The growth of films was found to be in three-dimensional island mode, where the deposited C36 acted as building blocks. The study of film morphology shows that it retains the structure of a free C36 cage, which is consistent with Low Energy Cluster Beam Deposition (LECBD) experiments. The adlayer is composed of many C36-monomers as well as the covalently bonded C36 dimers and trimers which is quite different from that of C20 fullerene-assembled film, where a big polymerlike chain was observed due to the stronger interaction between C20 cages. In addition, the chemisorption probability of C36 fullerenes is decreased with increasing coverage because the interaction between these clusters is weaker than that between the cluster and the surface. When the incident energy is increased to 40–65 eV, the chemisorption probability is found to increased and more dimers and trimers as well as polymerlike-C36 were observed on the deposited films. Furthermore, C36 film also showed high thermal stability even when the temperature was raised to 1500 K.

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The deposition of small metal clusters (Cu, Au and Al) on f.c.c. metals (Cu, Au and Ni) has been studied by molecular dynamics simulation using Finnis–Sinclair (FS) potential. The impact energy varied from 0.01 to 10 eV/atom. First, the deposition of single cluster was simulated. We observed that, even at much lower energy, a small cluster with (Ih) icosahedral symmetry was reconstructed to match the substrate structure (f.c.c.) after deposition. Next, clusters were modeled to drop, one after the other, on the surface. The nanostructure was found by soft landing of Au clusters on Cu with increasing coverage, where interfacial energy dominates. While at relatively higher deposition energy (a few eV), the ordered f.c.c.-like structure was observed in the first adlayer of the film formed by Al clusters depositing on Ni substrate. This characteristic is mainly attributive to the ballistic collision. Our results indicate that the surface morphology synthesized by cluster deposition could be controlled by experimental parameters, which will be helpful for controlled design of nanostructure.

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In this paper, the influence of the impact energy on the initial fabrication of thin films formed by low energy cluster deposition was investigated by molecular dynamics simulation of All 3 clusters depositing on Ni(0 0 1) substrate. In the case of soft-landing, (0.01 eV/atom), clusters are rearranged from I-h symmetry into fcc-like clusters on the surface. Then they aggregate each other, which result in thin film growing in 3D island mode. While, growth will be in layer-by-layer mode at the impact energy of a few electron volt due to the transient lateral spread of cluster atoms induced by dense collision cascade. This effect has been traced to collision cascade inside the cluster. which is enhanced by collision with a hard Ni substrate. (C) 2002 Elsevier Science B.V. All rights reserved.

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Different types of defects can be introduced into graphene during material synthesis, and significantly influence the properties of graphene. In this work, we investigated the effects of structural defects, edge functionalisation and reconstruction on the fracture strength and morphology of graphene by molecular dynamics simulations. The minimum energy path analysis was conducted to investigate the formation of Stone-Wales defects. We also employed out-of-plane perturbation and energy minimization principle to study the possible morphology of graphene nanoribbons with edge-termination. Our numerical results show that the fracture strength of graphene is dependent on defects and environmental temperature. However, pre-existing defects may be healed, resulting in strength recovery. Edge functionalization can induce compressive stress and ripples in the edge areas of graphene nanoribbons. On the other hand, edge reconstruction contributed to the tensile stress and curved shape in the graphene nanoribbons.

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The first objective of this project is to develop new efficient numerical methods and supporting error and convergence analysis for solving fractional partial differential equations to study anomalous diffusion in biological tissue such as the human brain. The second objective is to develop a new efficient fractional differential-based approach for texture enhancement in image processing. The results of the thesis highlight that the fractional order analysis captured important features of nuclear magnetic resonance (NMR) relaxation and can be used to improve the quality of medical imaging.

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This paper develops analytical distributions of temperature indices on which temperature derivatives are written. If the deviations of daily temperatures from their expected values are modelled as an Ornstein-Uhlenbeck process with timevarying variance, then the distributions of the temperature index on which the derivative is written is the sum of truncated, correlated Gaussian deviates. The key result of this paper is to provide an analytical approximation to the distribution of this sum, thus allowing the accurate computation of payoffs without the need for any simulation. A data set comprising average daily temperature spanning over a hundred years for four Australian cities is used to demonstrate the efficacy of this approach for estimating the payoffs to temperature derivatives. It is demonstrated that expected payoffs computed directly from historical records are a particularly poor approach to the problem when there are trends in underlying average daily temperature. It is shown that the proposed analytical approach is superior to historical pricing.

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The Bus Rapid Transit (BRT) station is the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on BRT line capacity. This study uses microscopic traffic simulation modeling to treat the BRT station operation and to analyze the relationship between station bus capacity and BRT line bus capacity. First, the simulation model is developed for the limit state scenario and then a statistical model is defined and calibrated for a specified range of controlled scenarios of dwell time characteristics. A field survey was conducted to verify the parameters such as dwell time, clearance time and coefficient of variation of dwell time to obtain relevant station bus capacity. The proposed model for BRT bus capacity provides a better understanding of BRT line capacity and is useful to transit authorities in BRT planning, design and operation.

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This paper describes an investigation into the effectiveness of using spray-on nano-particle reinforced polymer and aluminium foam as new types of retrofit material to prevent the breaching and collapse of unreinforced concrete masonry walls subjected to blast over a whole range of dynamic and impulsive regimes. Material models from the LSDYNA material library were used to model the behaviors of each of the materials and its interface for retrofitted and unretrofitted masonry walls. Available test data were used to validate the numerical models. Using the validated LS-DYNA numerical models, the pressure-impulse diagrams for retrofitted concrete masonry walls were constructed. The efficiency of using these retrofits to strengthen the unreinforced concrete masonry unit (CMU) walls under various pressures and impulses was investigated using pressure-impulse diagrams. Comparisons were made to find the most efficient retrofits for masonry walls against blasts.

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The University of Queensland UltraCommuter concept is an ultra- light, low-drag, hybrid-electric sports coupe designed to minimize energy consumption and environmental impact while enhancing the performance, styling, features and convenience that motorists enjoy. This paper presents a detailed simulation study of the vehicle's performance and fuel economy using ADVISOR, including a detailed description of the component models and parameters assumed. Results from the study include predictions of a 0-100 kph acceleration time of ≺9s, and top speed of 170 kph, an electrical energy consumption of ≺67 Wh/km in ZEV mode and a petrol-equivalent fuel consumption of ≺2.5 L/100 km in charge-sustaining HEV mode. Overall, the results of the ADVISOR modelling confirm the UltraCommuter's potential to achieve high performance with high efficiency, and the authors look forward to a confirmation of these estimates following completion of the vehicle.

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Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

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The overarching aim of this programme of work was to evaluate the effectiveness of the existing learning environment within the Australian Institute of Sport (AIS) elite springboard diving programme. Unique to the current research programme, is the application of ideas from an established theory of motor learning, specifically ecological dynamics, to an applied high performance training environment. In this research programme springboard diving is examined as a complex system, where individual, task, and environmental constraints are continually interacting to shape performance. As a consequence, this thesis presents some necessary and unique insights into representative learning design and movement adaptations in a sample of elite athletes. The questions examined in this programme of work relate to how best to structure practice, which is central to developing an effective learning environment in a high performance setting. Specifically, the series of studies reported in the chapters of this doctoral thesis: (i) provide evidence for the importance of designing representative practice tasks in training; (ii) establish that completed and baulked (prematurely terminated) take-offs are not different enough to justify the abortion of a planned dive; and (iii), confirm that elite athletes performing complex skills are able to adapt their movement patterns to achieve consistent performance outcomes from variable dive take-off conditions. Chapters One and Two of the thesis provide an overview of the theoretical ideas framing the programme of work, and include a review of literature pertinent to the research aims and subsequent empirical chapters. Chapter Three examined the representativeness of take-off tasks completed in the two AIS diving training facilities routinely used in springboard diving. Results highlighted differences in the preparatory phase of reverse dive take-offs completed by elite divers during normal training tasks in the dry-land and aquatic training environments. The most noticeable differences in dive take-off between environments began during the hurdle (step, jump, height and flight) where the diver generates the necessary momentum to complete the dive. Consequently, greater step lengths, jump heights and flight times, resulted in greater board depression prior to take-off in the aquatic environment where the dives required greater amounts of rotation. The differences observed between the preparatory phases of reverse dive take-offs completed in the dry-land and aquatic training environments are arguably a consequence of the constraints of the training environment. Specifically, differences in the environmental information available to the athletes, and the need to alter the landing (feet first vs. wrist first landing) from the take-off, resulted in a decoupling of important perception and action information and a decomposition of the dive take-off task. In attempting to only practise high quality dives, many athletes have followed a traditional motor learning approach (Schmidt, 1975) and tried to eliminate take-off variations during training. Chapter Four examined whether observable differences existed between the movement kinematics of elite divers in the preparation phases of baulked (prematurely terminated) and completed take-offs that might justify this approach to training. Qualitative and quantitative analyses of variability within conditions revealed greater consistency and less variability when dives were completed, and greater variability amongst baulked take-offs for all participants. Based on these findings, it is probable that athletes choose to abort a planned take-off when they detect small variations from the movement patterns (e.g., step lengths, jump height, springboard depression) of highly practiced comfortable dives. However, with no major differences in coordination patterns (topology of the angle-angle plots), and the potential for negative performance outcomes in competition, there appears to be no training advantage in baulking on unsatisfactory take-offs during training, except when a threat of injury is perceived by the athlete. Instead, it was considered that enhancing the athletes' movement adaptability would be a more functional motor learning strategy. In Chapter Five, a twelve-week training programme was conducted to determine whether a sample of elite divers were able to adapt their movement patterns and complete dives successfully, regardless of the perceived quality of their preparatory movements on the springboard. The data indeed suggested that elite divers were able to adapt their movements during the preparatory phase of the take-off and complete good quality dives under more varied take-off conditions; displaying greater consistency and stability in the key performance outcome (dive entry). These findings are in line with previous research findings from other sports (e.g., shooting, triple jump and basketball) and demonstrate how functional or compensatory movement variability can afford greater flexibility in task execution. By previously only practising dives with good quality take-offs, it can be argued that divers only developed strong couplings between information and movement under very specific performance circumstances. As a result, this sample was sometimes characterised by poor performance in competition when the athletes experienced a suboptimal take-off. Throughout this training programme, where divers were encouraged to minimise baulking and attempt to complete every dive, they demonstrated that it was possible to strengthen the information and movement coupling in a variety of performance circumstances, widening of the basin of performance solutions and providing alternative couplings to solve a performance problem even when the take-off was not ideal. The results of this programme of research provide theoretical and experimental implications for understanding representative learning design and movement pattern variability in applied sports science research. Theoretically, this PhD programme contributes empirical evidence to demonstrate the importance of representative design in the training environments of high performance sports programmes. Specifically, this thesis advocates for the design of learning environments that effectively capture and enhance functional and flexible movement responses representative of performance contexts. Further, data from this thesis showed that elite athletes performing complex tasks were able to adapt their movements in the preparatory phase and complete good quality dives under more varied take-off conditions. This finding signals some significant practical implications for athletes, coaches and sports scientists. As such, it is recommended that care should be taken by coaches when designing practice tasks since the clear implication is that athletes need to practice adapting movement patterns during ongoing regulation of multi-articular coordination tasks. For example, volleyball servers can adapt to small variations in the ball toss phase, long jumpers can visually regulate gait as they prepare for the take-off, and springboard divers need to continue to practice adapting their take-off from the hurdle step. In summary, the studies of this programme of work have confirmed that the task constraints of training environments in elite sport performance programmes need to provide a faithful simulation of a competitive performance environment in order that performance outcomes may be stabilised with practice. Further, it is apparent that training environments can be enhanced by ensuring the representative design of task constraints, which have high action fidelity with the performance context. Ultimately, this study recommends that the traditional coaching adage 'perfect practice makes perfect", be reconsidered; instead advocating that practice should be, as Bernstein (1967) suggested, "repetition without repetition".

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This paper describes the development of an analytical model used to simulate the fatigue behaviour of roof cladding during the passage of a tropical cyclone. The model incorporated into a computer program uses wind pressure data from wind tunnel tests in combination with time history information on wind speed and direction during a tropical cyclone, and experimental fatigue characteristics data of roof claddings. The wind pressure data is analysed using a rainflow form of analysis, and a fatigue damage index calculated using a modified form of Miner's rule. Some of the results obtained to date and their significance in relation to the review of current fatigue tests are presented. The model appears to be reasonable for comparative estimation of fatigue life, but an improvement of Miner's rule is required for the prediction of actual fatigue life.

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Digital Human Models (DHM) have been used for over 25 years. They have evolved from simple drawing templates, which are nowadays still used in architecture, to complex and Computer Aided Engineering (CAE) integrated design and analysis tools for various ergonomic tasks. DHM are most frequently used for applications in product design and production planning, with many successful implementations documented. DHM from other domains, as for example computer user interfaces, artificial intelligence, training and education, or the entertainment industry show that there is also an ongoing development towards a comprehensive understanding and holistic modeling of human behavior. While the development of DHM for the game sector has seen significant progress in recent years, advances of DHM in the area of ergonomics have been comparatively modest. As a consequence, we need to question if current DHM systems are fit for the design of future mobile work systems. So far it appears that DHM in Ergonomics are rather limited to some traditional applications. According to Dul et al. (2012), future characteristics of Human Factors and Ergonomics (HFE) can be assigned to six main trends: (1) global change of work systems, (2) cultural diversity, (3) ageing, (4) information and communication technology (ICT), (5) enhanced competiveness and the need for innovation, and; (6) sustainability and corporate social responsibility. Based on a literature review, we systematically investigate the capabilities of current ergonomic DHM systems versus the ‘Future of Ergonomics’ requirements. It is found that DHMs already provide broad functionality in support of trends (1) and (2), and more limited options in regards to trend (3). Today’s DHM provide access to a broad range of national and international databases for correct differentiation and characterization of anthropometry for global populations. Some DHM explicitly address social and cultural modeling of groups of people. In comparison, the trends of growing importance of ICT (4), the need for innovation (5) and sustainability (6) are addressed primarily from a hardware-oriented and engineering perspective and not reflected in DHM. This reflects a persistent separation between hardware design (engineering) and software design (information technology) in the view of DHM – a disconnection which needs to be urgently overcome in the era of software defined user interfaces and mobile devices. The design of a mobile ICT-device is discussed to exemplify the need for a comprehensive future DHM solution. Designing such mobile devices requires an approach that includes organizational aspects as well as technical and cognitive ergonomics. Multiple interrelationships between the different aspects result in a challenging setting for future DHM. In conclusion, the ‘Future of Ergonomics’ pose particular challenges for DHM in regards to the design of mobile work systems, and moreover mobile information access.