Статті в журналах з теми "Models and simulations of design"
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Wortmann, Thomas, Alberto Costa, Giacomo Nannicini, and Thomas Schroepfer. "Advantages of surrogate models for architectural design optimization." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 29, no. 4 (October 7, 2015): 471–81. http://dx.doi.org/10.1017/s0890060415000451.
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AbstractClimate change, resource depletion, and worldwide urbanization feed the demand for more energy and resource-efficient buildings. Increasingly, architectural designers and consultants analyze building designs with easy-to-use simulation tools. To identify design alternatives with good performance, designers often turn to optimization methods. Randomized, metaheuristic methods such as genetic algorithms are popular in the architectural design field. However, are metaheuristics the best approach for architectural design problems that often are complex and ill defined? Metaheuristics may find solutions for well-defined problems, but they do not contribute to a better understanding of a complex design problem. This paper proposes surrogate-based optimization as a method that promotes understanding of the design problem. The surrogate method interpolates a mathematical model from data that relate design parameters to performance criteria. Designers can interact with this model to explore the approximate impact of changing design variables. We apply the radial basis function method, a specific type of surrogate model, to two architectural daylight optimization problems. These case studies, along with results from computational experiments, serve to discuss several advantages of surrogate models. First, surrogate models not only propose good solutions but also allow designers to address issues outside of the formulation of the optimization problem. Instead of accepting a solution presented by the optimization process, designers can improve their understanding of the design problem by interacting with the model. Second, a related advantage is that designers can quickly construct surrogate models from existing simulation results and other knowledge they might possess about the design problem. Designers can thus explore the impact of different evaluation criteria by constructing several models from the same set of data. They also can create models from approximate data and later refine them with more precise simulations. Third, surrogate-based methods typically find global optima orders of magnitude faster than genetic algorithms, especially when the evaluation of design variants requires time-intensive simulations.
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Szufel, Przemysław, Bogumił Kamiński, and Piotr Wojewnik. "Controllling Simulation Experiment Design for Agent-Based Models Using Tree Representation of Parameter Space." Foundations of Computing and Decision Sciences 38, no. 4 (December 1, 2013): 277–98. http://dx.doi.org/10.2478/fcds-2013-0014.
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Abstract An important aspect of the simulation modelling process is sensitivity analysis. In this process, agent-based simulations often require analysis of structurally different parameter specifications - the parameters can be represented as objects and the object-oriented simulation configuration leads to nesting of simulation parameters. The nested parameters are naturally represented as a tree rather than a flat structure. The standard tools supporting multi-agent simulations only allow only the representation of the parameter space as a Cartesian product of possible parameter values. Consequently, their application for the required tree representation is limited. In this paper an approach to tree parameter space representation is introduced with an XML-based language. Furthermore, we propose a set of tools that allows one to manage parameterization of the simulation experiment independently of the simulation model.
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Rugenstein, Maria, Jonah Bloch-Johnson, Ayako Abe-Ouchi, Timothy Andrews, Urs Beyerle, Long Cao, Tarun Chadha, et al. "LongRunMIP: Motivation and Design for a Large Collection of Millennial-Length AOGCM Simulations." Bulletin of the American Meteorological Society 100, no. 12 (December 1, 2019): 2551–70. http://dx.doi.org/10.1175/bams-d-19-0068.1.
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Abstract We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1,000+ years) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time- and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1,000 years. LongRunMIP is an MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of October 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submissions of more simulations in the future.
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BERNASCHI, MASSIMO, and FILIPPO CASTIGLIONE. "COMPUTATIONAL FEATURES OF AGENT-BASED MODELS." International Journal of Computational Methods 02, no. 01 (March 2005): 33–48. http://dx.doi.org/10.1142/s0219876205000399.
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Agent-based modeling allows the description of very complex systems. To run large scale simulations of agent-based models in a reasonable time, it is crucial to carefully design data structures and algorithms. We describe the main computational features of agent-based models and report about the solutions we adopted in two applications: The simulation of the immune system response and the simulation of the stock market dynamics.
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Surendranath, H., and M. Dunbar. "Parallel Computing for Tire Simulations." Tire Science and Technology 39, no. 3 (September 1, 2011): 193–209. http://dx.doi.org/10.2346/1.3637743.
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Abstract Over the last few decades, finite element analysis has become an integral part of the overall tire design process. Engineers need to perform a number of different simulations to evaluate new designs and study the effect of proposed design changes. However, tires pose formidable simulation challenges due to the presence of highly nonlinear rubber compounds, embedded reinforcements, complex tread geometries, rolling contact, and large deformations. Accurate simulation requires careful consideration of these factors, resulting in the extensive turnaround time, often times prolonging the design cycle. Therefore, it is extremely critical to explore means to reduce the turnaround time while producing reliable results. Compute clusters have recently become a cost effective means to perform high performance computing (HPC). Distributed memory parallel solvers designed to take advantage of compute clusters have become increasingly popular. In this paper, we examine the use of HPC for various tire simulations and demonstrate how it can significantly reduce simulation turnaround time. Abaqus/Standard is used for routine tire simulations like footprint and steady state rolling. Abaqus/Explicit is used for transient rolling and hydroplaning simulations. The run times and scaling data corresponding to models of various sizes and complexity are presented.
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Brown, Alan S. "Role Models." Mechanical Engineering 121, no. 07 (July 1, 1999): 44–49. http://dx.doi.org/10.1115/1.1999-jul-1.
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This article focuses on the fact that by inserting digital humans into that virtual world—or stepping into it themselves—engineers have found new ways to test designs for ergonomics, manufacturability, maintainability, safety, and style. The goal, of course, is to design better, higher quality products faster and cheaper by getting everyone from manufacturing and quality through safety and maintenance involved in the process before settling on a design. The approach, called concurrent engineering, has been talked about since the quality revolution in the 1980s. Digital humans provide important insights into the design of production and assembly equipment. By simulating the task with large digital populations, safety engineers can determine before a machine goes into production whether anyone is likely to circumvent its safety features. One way to overcome behavior barriers is to put real people in simulations.
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Kustron, Kamila, Vaclav Horak, Radek Doubrava, and Zdobyslaw Jan Goraj. "New hail impact simulation models on composite laminated wing leading edge." Aircraft Engineering and Aerospace Technology 91, no. 3 (March 4, 2019): 457–65. http://dx.doi.org/10.1108/aeat-02-2018-0089.
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Purpose The risk of hail-impact occurrence that can decrease local strength property must be taken into account in the design of primary airframe structures in aviation, energy and space industries. Because of the high-speed of hail impact in operation, it can affect the load carrying capacity. Testing all impact scenarios onto real structure is expensive and impractical. The purpose of this paper is to present a cost-effective hybrid testing regime including experimental tests and FEM-based simulations for airframe parts that are locally exposed to the impacting hail in flight. Design/methodology/approach Tested samples (specimens) are flat panels of laminated and sandwich carbon/epoxy composites that are used in designing lightweight new airframes. The presented numerical simulations provide a cost effective and convenient tool for investigating the hail impact scenarios in the design process. The smoothed particle hydrodynamics (SPH) technique was selected for the simulation of projectiles. The most commonly used shape of projectiles in hail impact tests is the ice ball with a defined diameter. The proposed simulation technique was verified and validated in tests on flat composite panels (specimens). Findings Integration of the numerical analyses with high-speed impact tests of hail onto flat laminated and sandwich composite shells has been presented, and a developed simulation model for impact results assessment was obtained. Originality/value The tested coupons (specimens) are flat panels as representative of structural design deployed in real aircraft structures. These numerical simulations provide a cost effective and convenient tool for hail impact scenarios in the design process.
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Khan, M. Ashraf, Jason M. Kulick, David Kopp, Patrick Fay, Alfred M. Kriman, and Gary H. Bernstein. "Design and Robustness of Quilt Packaging Superconnect." Journal of Microelectronics and Electronic Packaging 10, no. 1 (January 1, 2013): 8–14. http://dx.doi.org/10.4071/imaps.358.
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Quilt packaging (QP) is a novel high-speed super-connect (i.e., direct interchip interconnect), developed to improve electrical performance—signal delay, power loss, and so on. Ultrahigh bandwidth has already been demonstrated for QP, but its unique structure requires thermal reliability issues to be studied. To this end, simulation models were developed to study the robustness of QP. QP structures were fabricated, and thermal cycling tests were performed focusing on the reliability for various shapes of nodules, the basic physical interconnect unit of QP. Simulations were performed to determine stress over a range of temperatures and estimate low cycle fatigue lifetimes. Simulations considered two types of solder and several adhesives. Thermal cycling experiments indicate that QP provides a robust structure, in agreement with the simulation results.
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Khan, M. Ashraf, Jason M. Kulick, Alfred M. Kriman, and Gary H. Bernstein. "Design and Robustness of Quilt Packaging Superconnect." International Symposium on Microelectronics 2012, no. 1 (January 1, 2012): 000524–30. http://dx.doi.org/10.4071/isom-2012-poster_khan.
Повний текст джерелаАнотація:
Quilt Packaging (QP) is a novel high-speed superconnect (i.e. direct interchip interconnect), developed to improve electrical performance — signal delay, power loss, etc. Ultrahigh bandwidth has already been demonstrated for QP, but its unique structure requires thermal reliability issues to be studied. To this end, simulation models were developed to study the robustness of QP. QP structures were fabricated, and thermal cycling tests were performed focusing on the reliability for various shapes of nodules, the basic physical interconnect unit of QP. Simulations were performed to determine stress over a range of temperatures and estimate low cycle fatigue lifetimes. Simulations considered two types of solder and several adhesives. Thermal cycling experiments indicate that QP provides a robust structure, in agreement with the simulation results.
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Khadke, Aniruddha, Somnath Ghosh, and Ming Li. "Numerical Simulations and Design of Shearing Process for Aluminum Alloys." Journal of Manufacturing Science and Engineering 127, no. 3 (July 21, 2004): 612–21. http://dx.doi.org/10.1115/1.1951787.
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This work combines experimental studies with finite element simulations to develop a reliable numerical model for the simulation of shearing process in aluminum alloys. The critical concern with respect to product quality in this important process is burr formation. Numerical simulations are aimed at understanding the role of process variables on burr formation and for recommending process design parameters. The commercial code ABAQUS-Explicit with the arbitrary Lagrangian-Eulerian kinematic description is used in this study for numerical simulations. An elastic-plastic constitutive model with experimentally validated damage models are incorporated through the user subroutine VUMAT in ABAQUS, for modeling deformation and ductile fracture in the material. Macroscopic experiments with microscopic observations are conducted to characterize the material and to calibrate the constitutive and damage models. Parametric study is done to probe the effect of process parameters and finally, a genetic algorithm (GA) based design method is used to determine process parameters for minimum burr formation.
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Diekmann, Uwe, Werner Homberg, Jens Prehm, Tim Rostek, Nils Schönhoff, Dmitri Tabakajew, Andreea Trasca, and Haris Uysal. "Optimization of Tooling Design for Hot Mandrel Bending of Pipe Elbows." Materials Science Forum 918 (March 2018): 159–64. http://dx.doi.org/10.4028/www.scientific.net/msf.918.159.
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This paper presents the finite element model developed for the simulation of pipe elbow production by the so-called ‘Hamburg process’ in order to improve productivity and resource efficiency. To optimize the tooling design, a sensitivity analysis of the tool parameters that influence the quality of pipe elbows, such as mandrel height and length, is conducted. Different materials data sets including damage models were considered. Using numerical simulations, it is possible to determine an optimized tool geometry for the production of specific pipe elbow dimensions. Furthermore, as a result of the experiments and numerical simulations conducted, it is possible to increase the production velocity of the serial plant. Along with deformation, damage models are included in simulations in order to identify the right process boundaries. Finally, an experimentally validated model is developed for increasing resource efficiency in pipe elbow fabrication.
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Kochanski, Adam, Aimé Fournier, and Jan Mandel. "Experimental Design of a Prescribed Burn Instrumentation." Atmosphere 9, no. 8 (July 29, 2018): 296. http://dx.doi.org/10.3390/atmos9080296.
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Observational data collected during experiments, such as the planned Fire and Smoke Model Evaluation Experiment (FASMEE), are critical for evaluating and transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM into operational use. Historical meteorological data, representing typical weather conditions for the anticipated burn locations and times, have been processed to initialize and run a set of simulations representing the planned experimental burns. Based on an analysis of these numerical simulations, this paper provides recommendations on the experimental setup such as size and duration of the burns, and optimal sensor placement. New techniques are developed to initialize coupled fire-atmosphere simulations with weather conditions typical of the planned burn locations and times. The variation and sensitivity analysis of the simulation design to model parameters performed by repeated Latin Hypercube Sampling is used to assess the locations of the sensors. The simulations provide the locations for the measurements that maximize the expected variation of the sensor outputs with varying the model parameters.
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Miková, Ľubica, Michal Kelemen, Ivan Virgala, and Maroš Michna. "Simulation Model of Manipulator for Model Based Design." Applied Mechanics and Materials 611 (August 2014): 175–82. http://dx.doi.org/10.4028/www.scientific.net/amm.611.175.
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The subject of creation of simulation and mathematical models is nowadays more and more current and its application is in almost every aspect of life. The article deals with compiling a mathematical model of a pivoting arm using Lagrange equations of the second kind. Subsequently, the model will be created in the simulation program Matlab/Simulink. The simulation model will as well be assembled in the program Adams. The results of these simulations will be compared in the conclusion. This article presents a procedure for resolving a mechanical system from the beginning, from creation of a mathematical model through creation of a simulation model up to evaluation of the simulation results. This paper presents a procedure for resolving mechanical system from the beginning. Thus, it is done by creating a mathematical model through the creation of a simulation model to evaluate the results of the simulation. According to these simulations will produce a working model of the manipulator, which could be used for teaching purposes.
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Kleinjung, Jens, and Franca Fraternali. "Design and application of implicit solvent models in biomolecular simulations." Current Opinion in Structural Biology 25 (April 2014): 126–34. http://dx.doi.org/10.1016/j.sbi.2014.04.003.
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Alme, K. J., and S. Mylvaganam. "Electrical Capacitance Tomography—Sensor Models, Design, Simulations, and Experimental Verification." IEEE Sensors Journal 6, no. 5 (October 2006): 1256–66. http://dx.doi.org/10.1109/jsen.2006.881409.
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Zorn, Max, Natasha Catunda, Luisa Claus, Natalia Kobylinska, Manuel Frey, and Thomas Wortmann. "Replacing energy simulations with surrogate models for design space exploration." Bauphysik 44, no. 6 (December 2022): 311–16. http://dx.doi.org/10.1002/bapi.202200034.
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Gaidarski, Ivan, and Pavlin Kutinchev. "Transformation of UML Design Models of Information Security System into Agent-based Simulation Models." Information & Security: An International Journal 53 (2022): 65–77. http://dx.doi.org/10.11610/isij.5305.
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Ma, Lanssie Mingyue, and Karen M. Feigh. "Jumpstarting Modelling Systems Design: A Generalized Xml Abstraction Of Simulation Model." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 718–22. http://dx.doi.org/10.1177/1541931213601665.
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While many complex models and simulations exist, tools to help evaluate the structure of work between humans and autonomous systems are underdeveloped. There is a need to understand what concepts of operations and function allocations of system(s) imply about the system' efficiency and outcome. In this paper, we define key elements necessary to capture in an abstraction schematic, a formal representation, of “work” for simulation systems, implemented with an example simulation system, Work Models that Compute (WMC5). This generalization has many applications in evaluating the understanding key cognitive domains in autonomy, coherency, function allocation, and more. We provide a simple methodology to generate an abstraction schematic for simulations and walk through building such a schematic for a simulation. This system creates a template (e.g. defining skeletons classes, objects, and methods) for programmers to further develop. This paper demonstrates the importance of abstraction schematics for model evaluation through several examples applications of the schematic to drastically reduce workflow for developing WMC5 code, and further investigate the model through graph network structures. Abstraction schemas, as we demonstrate, are simple to develop, useful for evaluating system structure, and help validate interactions between agents and autonomous systems. Abstraction schemas jumpstart system designers in developing models of work prior to simulation development.
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Hattori, Hiromitsu, Yuu Nakajima, and Shohei Yamane. "Massive Multiagent-Based Urban Traffic Simulation with Fine-Grained Behavior Models." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 2 (March 20, 2011): 233–39. http://dx.doi.org/10.20965/jaciii.2011.p0233.
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As it is getting easier to obtain reams of data on human behavior via ubiquitous devices, it is becoming obvious that we must work on two conflicting research directions for realizing multiagent-based social simulations; creating large-scale simulations and elaborating fine-scale human behavior models. The challenge in this paper is to achievemassively urban traffic simulations with fine-grained levels of driving behavior. Toward our objective, we show the design and implementation of a multiagent-based simulation platform, that enables us to execute massive but sophisticated multiagent traffic simulations. We show the capability of the developed platform to reproduce the urban traffic with a social experiment scenario. We investigate its potential to analyze the traffic from both macroscopic and microscopic viewpoints.
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Peri, Daniele, and Emilio F. Campana. "High-Fidelity Models and Multiobjective Global Optimization Algorithms in Simulation-Based Design." Journal of Ship Research 49, no. 03 (September 1, 2005): 159–75. http://dx.doi.org/10.5957/jsr.2005.49.3.159.
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This work presents a simulation-based design environment for the solution of optimum ship design problems based on a global optimization (GO) algorithm that prevents the optimizer from being trapped into local minima. The procedure, illustrated in the framework of multiobjective optimization problems, makes use of high-fidelity, CPU-time-expensive computational models, including a free surface-capturing Reynolds-averaged Navier Stokes equation (RANSE) solver. The optimization process is composed of a global and a local phase. In the global stage of the search, a few computationally expensive simulations are needed for creating analytical approximations(i.e., surrogate models) of the objective functions. Tentative designs, created to explore the design space, are then evaluated with these inexpensive approximations. The more promising designs are then clustered and locally minimized and eventually verified with high-fidelity simulations. New exact values are used to improve the surrogate models, and repeated cycles of the algorithm are performed. A decision maker strategy is finally adopted to select the more interesting solution, and a final local refinement stage is performed by a gradient-based local optimization technique. A key point in the algorithm is the introduction of the surrogate models for the reduction of the overall time needed for the objective functions evaluation and their dynamic evolution and refinement along the optimization process. Moreover, an attractive alternative to adjoint formulations, the approximation management framework (AMF), based on a combined strategy that joins variable fidelity models and trust region techniques, is tested. Numerical examples are given demonstrating both the validity and usefulness of the proposed approach.
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Glenn, Floyd. "The Case for Micro-models." Proceedings of the Human Factors Society Annual Meeting 33, no. 18 (October 1989): 1228–32. http://dx.doi.org/10.1177/154193128903301813.
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This paper examines the appropriate role of human performance micro-models in simulations of human-machine system operations. Requirements for general human micro-models are considered relative to the objectives of simulation studies, the conditions under which simulations are constructed and used, the status of human performance data bases and models, and the features provided with general-purpose simulation software. This investigation focuses particularly on a new simulation tool for simulating human-machine systems; it is known as the Human Operator Simulator – Version V (HOS-V). A general design principle of HOS-V has been to provide embedded human performance micro-models for the basic performance processes that seem most pervasive and interactive with other processes. These include representations for processes of body movement, cognition, and attention. Key to these representations are the substructures in each area. Body movement models describe locations of body parts and constraints on their movement. Cognition models describe how the human processes information through perception, memory, decision-making, and action initiation. The attention model describes how a limited attentional resource is allocated to the various body movement and cognition processes, each of which has a defined attentional requirement. Plans for implementation of micro-model components of HOS-V are discussed.
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Qian, Zhiguang, Carolyn Conner Seepersad, V. Roshan Joseph, Janet K. Allen, and C. F. Jeff Wu. "Building Surrogate Models Based on Detailed and Approximate Simulations." Journal of Mechanical Design 128, no. 4 (June 7, 2005): 668–77. http://dx.doi.org/10.1115/1.2179459.
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Preliminary design of a complex system often involves exploring a broad design space. This may require repeated use of computationally expensive simulations. To ease the computational burden, surrogate models are built to provide rapid approximations of more expensive models. However, the surrogate models themselves are often expensive to build because they are based on repeated experiments with computationally expensive simulations. An alternative approach is to replace the detailed simulations with simplified approximate simulations, thereby sacrificing accuracy for reduced computational time. Naturally, surrogate models built from these approximate simulations are also imprecise. A strategy is needed for improving the precision of surrogate models based on approximate simulations without significantly increasing computational time. In this paper, a new approach is taken to integrate data from approximate and detailed simulations to build a surrogate model that describes the relationship between output and input parameters. Experimental results from approximate simulations form the bulk of the data, and they are used to build a model based on a Gaussian process. The fitted model is then “adjusted” by incorporating a small amount of data from detailed simulations to obtain a more accurate prediction model. The effectiveness of this approach is demonstrated with a design example involving cellular materials for an electronics cooling application. The emphasis is on the method and not on the results per se.
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Santos, Aladir Horacio, Eduardo Bearzoti, Daniel Furtado Ferreira, and João Luís da Silva Filho. "Simulation of mixed models in augmented block design." Scientia Agricola 59, no. 3 (September 2002): 483–89. http://dx.doi.org/10.1590/s0103-90162002000300012.
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The augmented block design is widely used in breeding programs, with non-replicated treatments generally being selection units, and replicated treatments being standard cultivars. Originally, an intrablock analysis (fixed model) was proposed. Although non-replicated treatments and/or blocks can be considered of random nature, mixed linear models could be used instead. This work evaluated such an approach, using computer simulation. Populations consisted of sets of randomly generated inbred lines. Molecular marker data were also simulated to allow the estimation of the genetic covariance matrix. Different conditions were considered, varying heritability and the coefficient b of Smith of soil heterogeneity. For each condition 100 simulations were performed, considering four linear models, varying respectively the nature of the effects of blocks and non-replicated treatments (fixed - F, or random - R): FF, FR, RF and RR. In relation to FF, the mixed models were more efficient under low to intermediate heritability and high b. Mixed models could improve inference in breeding programs using the augmented block design and the choice of the model should rely on the kind of selection. If this is truncated, the RF model should be preferred; if it is not, then the RR model would be more suitable.
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Kalla, Subhash, and Christopher David White. "Efficient Design of Reservoir Simulation Studies for Development and Optimization." SPE Reservoir Evaluation & Engineering 10, no. 06 (December 1, 2007): 629–37. http://dx.doi.org/10.2118/95456-pa.
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Summary Development studies examine geologic, engineering, and economic factors to formulate and optimize production plans. If there are many factors, these studies are prohibitively expensive unless simulation runs are chosen efficiently. Experimental design and response models improve study efficiency and have been widely applied in reservoir engineering. To approximate nonlinear oil and gas reservoir responses, designs must consider factors at more than two levels—not just high and low values. However, multilevel designs require many simulations, especially if many factors are being considered. Partial factorial and mixed designs are more efficient than full factorials, but multilevel partial factorial designs are difficult to formulate. Alternatively, orthogonal arrays (OAs) and nearly-orthogonal arrays (NOAs) provide the required design properties and can handle many factors. These designs span the factor space with fewer runs, can be manipulated easily, and are appropriate for computer experiments. The proposed methods were used to model a gas well with water coning. Eleven geologic factors were varied while optimizing three engineering factors. An NOA was specified with three levels for eight factors and four levels for the remaining six factors. The proposed design required 36 simulations compared to 26,873,856 runs for a full factorial design. Kriged response surfaces are compared to polynomial regression surfaces. Polynomial-response models are used to optimize completion length, tubinghead pressure, and tubing diameter for a partially penetrating well in a gas reservoir with uncertain properties. OAs, Hammersley sequences (HSs), and response models offer a flexible, efficient framework for reservoir simulation studies. Complexity of Reservoir Studies Reservoir studies require integration of geologic properties, drilling and production strategies, and economic parameters. Integration is complex because parameters such as permeability, gas price, and fluid saturations are uncertain. In exploration and production decisions, alternatives such as well placement, artificial lift, and capital investment must be evaluated. Development studies examine these alternatives, as well as geologic, engineering, and economic factors to formulate and optimize production plans (Narayanan et al. 2003). Reservoir studies may require many simulations to evaluate the many factor effects on reservoir performance measures, such as net present value (NPV) and breakthrough time. Despite the exponential growth of computer memory and speed, computing accurate sensitivities and optimizing production performance is still expensive, to the point that it may not be feasible to consider all alternative models. Thus, simulation runs should be chosen as efficiently as possible. Experimental design addresses this problem statistically, and along with response models, it has been applied in engineering science (White et al. 2001; Peng and Gupta 2004; Peake et al. 2005; Sacks et al. 1989a) toMinimize computational costs by choosing a small but statistically representative set of simulation runs for predicting responses (e.g., recovery)Decrease expected error compared with nonoptimal simulation designs (i.e., sets of sample points)Evaluate sensitivity of responses to varying factorsTranslate uncertainty in input factors to uncertainty in predicted performance (i.e., uncertainty analysis)Estimate value of information to focus resources on reducing uncertainty in factors that have the most significant effect on response uncertainty to help optimize engineering factors.
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Keane, Andy J., and Ivan I. Voutchkov. "Robust design optimization using surrogate models." Journal of Computational Design and Engineering 7, no. 1 (February 1, 2020): 44–55. http://dx.doi.org/10.1093/jcde/qwaa005.
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Abstract The use of surrogate models (response surface models, curve fits) of various types (radial basis functions, Gaussian process models, neural networks, support vector machines, etc.) is now an accepted way for speeding up design search and optimization in many fields of engineering that require the use of expensive computer simulations, including problems with multiple goals and multiple domains. Surrogates are also widely used in dealing with uncertainty quantification of expensive black-box codes where there are strict limits on the number of function evaluations that can be afforded in estimating the statistical properties of derived performance quantities. Here, we tackle the problem of robust design optimization from the direction of Gaussian process models (Kriging). We contrast two previously studied models, co-Kriging and combined Kriging (sometimes called level 1 Kriging), and propose a new combined approach called combined co-Kriging that attempts to make best use of the key ideas present in these methods.
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McDaniel, James G., and Allison Kaminski. "Surrogate models of complex dynamic systems from energy distributions." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A134. http://dx.doi.org/10.1121/10.0015795.
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Engineers who design complex dynamic systems do not have the luxury of iteration. Numerical analysis of a single design, typically by finite element analysis, requires enormous amounts of CPU time. Therefore, improving a design by trying out many design modifications is impossible. Moreover, it is also impossible to identify which subsystem designs have the largest effects on the dynamic response of the system. The present work addresses this challenge by constructing surrogate models from energy distributions in a nominal design. These surrogate models are surprisingly effective at identifying subsystems that have the largest effects on the dynamic response, and therefore guide engineers to design modifications that matter most. A significant advantage of these surrogate models is the very low cost of creating them, as they are created directly from the frequency response of a nominal design and therefore do not require additional linear solves or other time-intensive calculations. This presentation begins with an analytical justification for considering energy distributions as surrogate models. Next, Monte Carlo Simulations are presented to show strong correlations between energy distributions and the effects of design changes on dynamic responses. These simulations include random structures as well as beams. Work supported by ONR under Grant N00014-19-1-2100.
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Illingworth, Simon J., Aimee S. Morgans, and Clarence W. Rowley. "Feedback control of cavity flow oscillations using simple linear models." Journal of Fluid Mechanics 709 (August 29, 2012): 223–48. http://dx.doi.org/10.1017/jfm.2012.330.
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AbstractUsing data from direct numerical simulations, linear models of the compressible flow past a rectangular cavity are found. The emphasis is on forming simple models which capture the input–output behaviour of the system, and which are useful for feedback controller design. Two different approaches for finding a linear model are investigated. The first involves using input–output data of the linearized cavity flow to form a balanced, reduced-order model directly. The second approach is conceptual, and involves modelling each element of the flow physics separately using simple analytical expressions, the parameters of which are chosen based on simulation data at salient points in the cavity’s computational domain. Both models are validated: first in the time domain by comparing their impulse responses to that of the full system in direct numerical simulations; and second in the frequency domain by comparing their frequency responses. Finally, the validity of both linear models is shown most clearly by using them for feedback controller design, and then applying each controller in direct numerical simulations. Both controllers completely eliminate oscillations, and demonstrate the advantages of model-based feedback controllers, even when the models upon which they are based are very simple.
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Zheng, Jun, Hao Bo Qiu, and Xiao Lin Zhang. "Variable-Fidelity Multidisciplinary Design Optimization Based on Analytical Target Cascading Framework." Advanced Materials Research 544 (June 2012): 49–54. http://dx.doi.org/10.4028/www.scientific.net/amr.544.49.
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ATC provides a systematic approach in solving decomposed large scale systems that has solvable subsystems. However， complex engineering system usually has a high computational cost , which result in limiting real-life applications of ATC based on high-fidelity simulation models. To address these problems, this paper aims to develop an efficient approximation model building techniques under the analytical target cascading (ATC) framework, to reduce computational cost associated with multidisciplinary design optimization problems based on high-fidelity simulations. An approximation model building techniques is proposed: approximations in the subsystem level are based on variable-fidelity modeling (interaction of low- and high-fidelity models). The variable-fidelity modeling consists of computationally efficient simplified models (low-fidelity) and expensive detailed (high-fidelity) models. The effectiveness of the method for modeling under the ATC framework using variable-fidelity models is studied. Overall results show the methods introduced in this paper provide an effective way of improving computational efficiency of the ATC method based on variable-fidelity simulation models.
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Tzotzis, Anastasios, César García-Hernández, José-Luis Huertas-Talón, and Panagiotis Kyratsis. "CAD-Based Automated Design of FEA-Ready Cutting Tools." Journal of Manufacturing and Materials Processing 4, no. 4 (November 1, 2020): 104. http://dx.doi.org/10.3390/jmmp4040104.
Повний текст джерелаАнотація:
The resources of modern Finite Element Analysis (FEA) software provide engineers with powerful mechanisms that can be used to investigate numerous machining processes with satisfying results. Nevertheless, the success of a simulation, especially in three dimensions, relies heavily on the accuracy of the cutting tool models that are implemented in the analyses. With this in mind, the present paper presents an application developed via Computer-Aided Design (CAD) programming that enables the automated design of accurate cutting tool models that can be used in 3D turning simulations. The presented application was developed with the aid of the programming resources of a commercially available CAD system. Moreover, the parametric design methodology was employed in order to design the tools according to the appropriate standards. Concluding, a sample tool model was tested by performing a number of machining simulations based on typical cutting parameters. The yielded results were then compared to experimental values of the generated machining force components for validation. The findings of the study prove the functionality of the tool models since a high level of agreement occurred between the acquired numerical results and the experimental ones.
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Zapata Usandivaras, José Felix, Annafederica Urbano, Michael Bauerheim, and Bénédicte Cuenot. "Data Driven Models for the Design of Rocket Injector Elements." Aerospace 9, no. 10 (October 12, 2022): 594. http://dx.doi.org/10.3390/aerospace9100594.
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Improving the predictive capabilities of reduced-order models for the design of injector and chamber elements of rocket engines could greatly improve the quality of early rocket chamber designs. In the present work, we propose an innovative methodology that uses high-fidelity numerical simulations of turbulent reactive flows and artificial intelligence for the generation of surrogate models. The surrogate models that were generated and analyzed are deep learning networks trained on a dataset of 100 large eddy simulations of a single-shear coaxial injector chamber. The design of experiments was created considering three design parameters: chamber diameter, recess length, and oxidizer–fuel ratio. The paper presents the methodology developed for training and optimizing the data-driven models. Fully connected neural networks (FCNNs) and U-Nets were utilized as surrogate-modeling technology. Eventually, the surrogate models for the global quantity, average, and root mean square fields were used in order to analyze the impact of the length of the post’s recess on the performances obtained and the behavior of the flow.
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FJELDLY, TOR A., and MICHAEL S. SHUR. "SIMULATION AND MODELING OF COMPOUND SEMICONDUCTOR DEVICES." International Journal of High Speed Electronics and Systems 06, no. 01 (March 1995): 237–84. http://dx.doi.org/10.1142/s0129156495000079.
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We review the simulation and modeling techniques used for popular compound semiconductor devices such as the Heterostructure Field Effect Transistor (HFET), the Metal Semiconductor Field Effect Transistor (MESFET), and the Heterostructure Bipolar Transistor (HBT). Starting with the basic transport theory and the numerical simulation techniques based on this theory, we proceed to give examples of Monte Carlo simulations and of 2D balance equation simulations for investigating fundamental device properties and for exploring new design concepts. Next, we present analytical HFET and MESFET models suitable for circuit simulations. These models are based on the so-called universal FET modeling concept, and accurately reproduce FET I-V and C-V characteristics. Finally, we review basic simulation and modeling issues for HBTs.
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Zhang, Chao, and Matthew Janeway. "Optimization of Turbine Blade Aerodynamic Designs Using CFD and Neural Network Models." International Journal of Turbomachinery, Propulsion and Power 7, no. 3 (June 30, 2022): 20. http://dx.doi.org/10.3390/ijtpp7030020.
Повний текст джерелаАнотація:
Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.
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Miljanović, Dejan, Milka Potrebić, and Dejan V. Tošić. "Design of Microwave Multibandpass Filters with Quasilumped Resonators." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/647302.
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Design of RF and microwave filters has always been the challenging engineering field. Modern filter design techniques involve the use of the three-dimensional electromagnetic (3D EM) solvers for predicting filter behavior, yielding the most accurate filter characteristics. However, the 3D EM simulations are time consuming. In this paper, we propose electric-circuit models, instead of 3D EM models, suitable for design of RF and microwave filters with quasilumped coupled resonators. Using the diakoptic approach, the 3D filter structure is decomposed into domains that are modeled by electric networks. The coupling between these domains is modeled by capacitors and coupled inductors. Furthermore, we relate the circuit-element values to the physical dimensions of the 3D filter structure. We propose the filter design procedure that is based on the circuit models and fast circuit-level simulations, yielding the element values from which the physical dimensions can be obtained. The obtained dimensions should be slightly refined for achieving the desired filter characteristics. The mathematical problems encountered in the procedure are solved by numerical and symbolic computations. The procedure is exemplified by designing a triple-bandpass filter and validated by measurements on the fabricated filter. The simulation and experimental results are in good agreement.
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Tellier, C. R., T. G. Leblois, and S. Durand. "Computer aided design of Langasite resonant cantilevers: analytical models and simulations." European Physical Journal Applied Physics 50, no. 2 (March 31, 2010): 20303. http://dx.doi.org/10.1051/epjap/2010039.
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Durga Prasad, G. V., G. Gopa Kishor, Manmohan Pandey, and Uday S. Dixit. "Numerical Simulations and Design Optimization of the PHT Loop of Natural Circulation BWR." Science and Technology of Nuclear Installations 2008 (2008): 1–12. http://dx.doi.org/10.1155/2008/690357.
Повний текст джерелаАнотація:
Mathematical modeling and numerical simulation of natural circulation boiling water reactor (NCBWR) are very important in order to study its performance for different designs and various off-design conditions and for design optimization. In the present work, parametric studies of the primary heat transport loop of NCBWR have been performed using lumped parameter models and RELAP5/MOD3.4 code. The lumped parameter models are based on the drift flux model and homogeneous equilibrium mixture (HEM) model of two-phase flow. Numerical simulations are performed with both models. Compared to the results obtained from the HEM model, those obtained from the drift flux model are closer to RELAP5. The variations of critical heat flux with various geometric parameters and operating conditions are thoroughly investigated. The material required to construct the primary heat transport (PHT) loop of NCBWR has been minimized using sequential quadratic programming. The stability of NCBWR has also been verified at the optimum point.
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Tang, Wenjie, Wentong Cai, Yiping Yao, Xiao Song, and Feng Zhu. "An alternative approach for collaborative simulation execution on a CPU+GPU hybrid system." SIMULATION 96, no. 3 (November 14, 2019): 347–61. http://dx.doi.org/10.1177/0037549719885178.
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In the past few years, the graphics processing unit (GPU) has been widely used to accelerate time-consuming models in simulations. Since both model computation and simulation management are main factors that affect the performance of large-scale simulations, only accelerating model computation will limit the potential speedup. Moreover, models that can be well accelerated by a GPU could be insufficient, especially for simulations with many lightweight models. Traditionally, the parallel discrete event simulation (PDES) method is used to solve this class of simulation, but most PDES simulators only utilize the central processing unit (CPU) even though the GPU is commonly available now. Hence, we propose an alternative approach for collaborative simulation execution on a CPU+GPU hybrid system. The GPU supports both simulation management and model computation as CPUs. A concurrency-oriented scheduling algorithm was proposed to enable cooperation between the CPU and the GPU, so that multiple computation and communication resources can be efficiently utilized. In addition, GPU functions have also been carefully designed to adapt the algorithm. The combination of those efforts allows the proposed approach to achieve significant speedup compared to the traditional PDES on a CPU.
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Liu, Mao Fu, Xiong Hua Guo, and Hui Xian Han. "A Design-Analysis and Simulation Approach of Ball-End Cutter Based on OpenGL." Advanced Materials Research 139-141 (October 2010): 1281–84. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1281.
Повний текст джерелаАнотація:
A design-analysis and simulation approach of complex ball-end cutter was proposed by using computer graphics and OpenGL control in this paper. The mathematical models of rake face and flank face of a complex ball-end cutter were built as the simulation condition. A computer-aided design and simulation processing system of complex tool was presented through pre-modeling OpenGL control. Some 3D simulation models of complex ball-end cutter including spiral cylinder, ball-head (including rake face, chip groove, first flank face and second flank face) and grinding wheel were created respectively. According to mathematical models and VC++ software platform, transformation and machining animation simulations of ball-end cutter were designed and realized visually using OpenGL control interface technique. The results of Three-dimensional design and simulation will offer sufficient theory foundation for virtually manufacturing ball-end cutter.
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Hollaus, Karl, Susanne Bauer, Michael Leumüller, and Christian Türk. "Measurement and modeling of effective cable parameters of unshielded conductors." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 41, no. 3 (February 16, 2022): 1041–51. http://dx.doi.org/10.1108/compel-03-2021-0098.
Повний текст джерелаАнотація:
Purpose Cables are ubiquitous in electronic-based systems. Electromagnetic emission of cables and crosstalk between wires is an important issue in electromagnetic compatibility and is to be minimized in the design phase. To facilitate the design, models of different complexity and accuracy, for instance, circuit models or finite element (FE) simulations, are used. The purpose of this study is to compare transmission line parameters obtained by measurements and simulations. Design/methodology/approach Transmission line parameters were determined by means of measurements in the frequency and time domain and by FE simulations in the frequency domain and compared. Finally, a Spice simulation with lumped elements was performed. Findings The determination of the effective permittivity of insulated wires seems to be a key issue in comparing measurements and simulations. Originality/value A space decomposition technique for a guided wave on an infinite configuration with constant cross-section has been introduced, where an analytic representation in the direction of propagation is used, and the transversal fields are approximated by FEs.
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Petersen, Steffen, Victor Hartvig Mortensen, and Eddie Kiholm. "Archetype EnergyPlus Models for Verifying the Thermal Performance of Danish Office Buildings." E3S Web of Conferences 362 (2022): 03003. http://dx.doi.org/10.1051/e3sconf/202236203003.
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This paper presents the research efforts that seek to improve the efficiency of conducting advanced thermal simulations in the detailed design stage of the design process. A prototype for an application that facilitates a quick and inexpensive setup of EnergyPlus (EP) models of Danish office buildings was developed in a co-creation process involving simulation practitioners. The prototype is designed to mitigate barriers to migrating from current tools to EP; however, further research is needed to investigate this aspect.
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Gill, Lewis, E. Abigail Hathway, Eckart Lange, Ed Morgan, and Daniela Romano. "Coupling Real-Time 3D Landscape Models with Microclimate Simulations." International Journal of E-Planning Research 2, no. 1 (January 2013): 1–19. http://dx.doi.org/10.4018/ijepr.2013010101.
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With urban design, it is becoming increasingly important to both visualise spatial changes and quantify the effect of these changes on the local microclimate: the former often for public consultation and the latter to develop landscapes that provide resilience to warmer weather thus reducing the urban heat island effect. It is possible to automatically construct 3D landscape models from vector site plans and height data sources through procedural generation. However, the generation of the inputs for microclimate models remains a time consuming process even though 3D visualisations or site plans may already exist. In this paper, a method to link procedurally generated 3D landscape models to microclimate simulations is demonstrated. Using this method, a case study is presented that allows initial calibration of the model and then several distinct alterations in the base design are tested alongside the variation in weather conditions looking forward to 2080. Finally, graphics card shaders are used to incorporate the temperature data within the interactive 3D procedural models, allowing both real-time manipulation of view point and simulation time.
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Jovanovic, Kosta, Jovana Vranic, and Nadica Miljkovic. "Hill’s and Huxley’s muscle models - tools for simulations in biomechanics." Serbian Journal of Electrical Engineering 12, no. 1 (2015): 53–67. http://dx.doi.org/10.2298/sjee1501053j.
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Numerous mathematical models of human skeletal muscles have been developed. However, none of them is adopted as a general one and each of them is suggested for some specific purpose. This topic is essential in humanoid robotics, since we firstly need to understand how human moves and acts in order to exploit human movement patterns in robotics and design human like actuators. Simulations in biomechanics are intensively used in research of locomotion, safe human-robot interaction, development of novel robotic actuators, biologically inspired control algorithms, etc. This paper presents two widely adopted muscle models (Hill?s and Huxley?s model), elaborates their features and demonstrates trade-off between their accuracy and efficiency of computer simulations. The simulation setup contains mathematical representation of passive muscle structures as well as mathematical model of an elastic tendon as a series elastic actuation element. Advanced robot control techniques point out energy consumption as one of the key issues. Therefore, energy store and release mechanism in elastic elements in both tendon and muscle, based on the simulation models, are considered.
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Wang, Tian, Ping Xi, and Bifu Hu. "Multiphysics Modeling of Gas Turbine Based on CADSS Technology." Shock and Vibration 2020 (October 19, 2020): 1–21. http://dx.doi.org/10.1155/2020/8816453.
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Product modeling has been applied in product engineering with success for geometric representation. With the application of multidisciplinary analysis, application-driven models need specific knowledge and time-consuming adjustment work based on the geometric model. This paper proposes a novel modeling technology named computer-aided design-supporting-simulation (CADSS) to generate multiphysics domain models to support multidisciplinary design optimization processes. Multiphysics model representation was analyzed to verify gaps among different domain models’ parameters. Therefore, multiphysics domain model architecture was integrated by optimization model, design model, and simulation model in consideration of domain model’s parameters. Besides, CADSS uses requirement space, domain knowledge, and software technology to describe the multidisciplinary model’s parameters and its transition. Depending on the domain requirements, the CADSS system extracts the required knowledge by decomposing product functions and then embeds the domain knowledge into functional features using software technology. This research aims to effectively complete the design cycle and improve the design quality by providing a consistent and concurrent modeling environment to generate an adaptable model for multiphysics simulation. This system is demonstrated by modeling turbine blade design with multiphysics simulations including computational fluid dynamics (CFD), conjugate heat transfer (CHT), and finite element analysis (FEA). Moreover, the blade multiphysics simulation model is validated by the optimization design of the film hole. The results show that the high-fidelity multiphysics simulation model generated through CADSS can be adapted to subsequent simulations.
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Humbird, K. D., and J. L. Peterson. "Transfer learning driven design optimization for inertial confinement fusion." Physics of Plasmas 29, no. 10 (October 2022): 102701. http://dx.doi.org/10.1063/5.0100364.
Повний текст джерелаАнотація:
Transfer learning is a promising approach to create predictive models that incorporate simulation and experimental data into a common framework. In this technique, a neural network is first trained on a large database of simulations and then partially retrained on sparse sets of experimental data to adjust predictions to be more consistent with reality. Previously, this technique has been used to create predictive models of Omega [Humbird et al., IEEE Trans. Plasma Sci. 48, 61–70 (2019)] and NIF [Humbird et al., Phys. Plasmas 28, 042709 (2021); Kustowski et al., Mach. Learn. 3, 015035 (2022)] inertial confinement fusion (ICF) experiments that are more accurate than simulations alone. In this work, we conduct a transfer learning driven hypothetical ICF campaign in which the goal is to maximize experimental neutron yield via Bayesian optimization. The transfer learning model achieves yields within 5% of the maximum achievable yield in a modest-sized design space in fewer than 20 experiments. Furthermore, we demonstrate that this method is more efficient at optimizing designs than traditional model calibration techniques commonly employed in ICF design. Such an approach to ICF design could enable robust optimization of experimental performance under uncertainty.
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Högblom, Olle, and Ronnie Andersson. "Multiphysics CFD Simulation for Design and Analysis of Thermoelectric Power Generation." Energies 13, no. 17 (August 22, 2020): 4344. http://dx.doi.org/10.3390/en13174344.
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The multiphysics simulation methodology presented in this paper permits extension of computational fluid dynamics (CFD) simulations to account for electric power generation and its effect on the energy transport, the Seebeck voltage, the electrical currents in thermoelectric systems. The energy transport through Fourier, Peltier, Thomson and Joule mechanisms as a function of temperature and electrical current, and the electrical connection between thermoelectric modules, is modeled using subgrid CFD models which make the approach computational efficient and generic. This also provides a solution to the scale separation problem that arise in CFD analysis of thermoelectric heat exchangers and allows the thermoelectric models to be fully coupled with the energy transport in the CFD analysis. Model validation includes measurement of the relevant fluid dynamic properties (pressure and temperature distribution) and electric properties (current and voltage) for a turbulent flow inside a thermoelectric heat exchanger designed for automotive applications. Predictions of pressure and temperature drop in the system are accurate and the error in predicted current and voltage is less than 1.5% at all exhaust gas flow rates and temperatures studied which is considered very good. Simulation results confirm high computational efficiency and stable simulations with low increase in computational time compared to standard CFD heat-transfer simulations. Analysis of the results also reveals that even at the lowest heat transfer rate studied it is required to use a full two way coupling in the energy transport to accurately predict the electric power generation.
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Olondriz, Joannes, Wei Yu, Josu Jugo, Frank Lemmer, Iker Elorza, Santiago Alonso-Quesada, and Aron Pujana-Arrese. "Using Multiple Fidelity Numerical Models for Floating Offshore Wind Turbine Advanced Control Design." Energies 11, no. 9 (September 18, 2018): 2484. http://dx.doi.org/10.3390/en11092484.
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This paper summarises the tuning process of the Aerodynamic Platform Stabiliser control loop and its performance with Floating Offshore Wind Turbine model. Simplified Low-Order Wind turbine numerical models have been used for the system identification and control tuning process. Denmark Technical University’s 10 MW wind turbine model mounted on the TripleSpar platform concept was used for this study. Time-domain simulations were carried out in a fully coupled non-linear aero-hydro-elastic simulation tool FAST, in which wind and wave disturbances were modelled. This testing yielded significant improvements in the overall Floating Offshore Wind Turbine performance and load reduction, validating the control technique presented in this work.
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Rudra, Monojit, P. Soni Reddy, Rajatsubhra Chakraborty, and Partha Pratim Sarkar. "Design of frequency selective surface comprising of dipoles using artificial neural network." International Journal of Advances in Applied Sciences 9, no. 4 (December 1, 2020): 276. http://dx.doi.org/10.11591/ijaas.v9.i4.pp276-283.
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<span>This paper depicts the design of Frequency Selective Surface (FSS) comprising of dipoles using Artificial Neural Network (ANN). It has been observed that with the change of the dimensions and periodicity of FSS, the resonating frequency of the FSS changes. This change in resonating frequency has been studied and investigated using simulation software. The simulated data were used to train the proposed ANN models. The trained ANN models are found to predict the FSS characteristics precisely with negligible error. Compared to traditional EM simulation softwares (like ANSOFT Designer), the proposed technique using ANN models is found to significantly reduce the FSS design complexity and computational time. The FSS simulations were made using ANSOFT Designer v2 software and the neural network was designed using MATLAB software.</span>
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Peart, Tanya, Nicolas Aubin, Stefano Nava, John Cater, and Stuart Norris. "Multi-Fidelity Surrogate Models for VPP Aerodynamic Input Data." Journal of Sailing Technology 6, no. 01 (February 9, 2021): 21–43. http://dx.doi.org/10.5957/jst/2021.6.1.21.
Повний текст джерелаАнотація:
Predicting the performance of a sail design is important for optimising the performance of a yacht, and Velocity Prediction Programs (VPPs) are commonly used for this purpose. The aerodynamic force data for a VPP is often calculated using Computational Fluid Dynamics (CFD) models, but these can be computationally expensive. A full VPP analysis for sail design is therefore usually restricted to high-budget design projects or research activities and is not practical for many industry projects. This work presents a method to reduce the computational cost of creating lift and drag force coefficient curves for input into a VPP using both multi-fidelity kriging surrogate modelling and data from existing sail designs. This method is shown to reduce the number of CFD simulations required for a desired accuracy when compared to a single-fidelity model. A maximum reduction in the required computational effort of 57% was achieved for model-scale symmetric spinnaker sails. For the same number of simulations, the accuracy of the model predictions was improved by up to 72% for scale-symmetric spinnaker sails, and 90% for asymmetric spinnakers.
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Hellerstein, Joseph L., Stanley Gu, Kiri Choi, and Herbert M. Sauro. "Recent advances in biomedical simulations: a manifesto for model engineering." F1000Research 8 (March 5, 2019): 261. http://dx.doi.org/10.12688/f1000research.15997.1.
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Biomedical simulations are widely used to understand disease, engineer cells, and model cellular processes. In this article, we explore how to improve the quality of biomedical simulations by developing simulation models using tools and practices employed in software engineering. We refer to this direction as model engineering. Not all techniques used by software engineers are directly applicable to model engineering, and so some adaptations are required. That said, we believe that simulation models can benefit from software engineering practices for requirements, design, and construction as well as from software engineering tools for version control, error checking, and testing. Here we survey current efforts to improve simulation quality and discuss promising research directions for model engineering.
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Ivanovic, R. F., L. J. Gregoire, M. Kageyama, D. M. Roche, P. J. Valdes, A. Burke, R. Drummond, W. R. Peltier, and L. Tarasov. "Transient climate simulations of the deglaciation 21–9 thousand years before present; PMIP4 Core experiment design and boundary conditions." Geoscientific Model Development Discussions 8, no. 10 (October 21, 2015): 9045–102. http://dx.doi.org/10.5194/gmdd-8-9045-2015.
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Abstract. The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21–9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given, but no ice sheet or iceberg meltwater should be prescribed in the Core simulation. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will focus on shorter durations around specific events to allow the more computationally expensive models to take part.
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Liu, Chia-Chang, and Chung-Biau Tsay. "Mathematical Models and Contact Simulations of Concave Beveloid Gears." Journal of Mechanical Design 124, no. 4 (November 26, 2002): 753–60. http://dx.doi.org/10.1115/1.1517563.
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This study presents two mathematical models of concave beveloid gears ground by Mitome’s grinding method and by the novel grinding method proposed by the authors. Based on the developed mathematical models, the contact simulations are performed and the characteristics of concave beveloid gear pairs are investigated. Simulation results indicate that our novel grinding method ameliorates the drawback of Mitome’s grinding method by eliminating the transmission error of the helical concave beveloid gear pairs. In contrast to conventional beveloid gear pairs, the gears ground by the proposed novel grinding method not only have larger contact ellipses, but also mesh conjugately with non-parallel axes, although assembly errors exist.