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Academic literature on the topic 'Multi-fidelity Analysi'

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Published: 14 March 2023

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Journal articles on the topic "Multi-fidelity Analysi"

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Lee, Daeyeon, Nhu Van Nguyen, Maxim Tyan, Hyung-Geun Chun, Sangho Kim, and Jae-Woo Lee. "Enhanced multi-fidelity model for flight simulation using global exploration and the Kriging method." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 4 (August 6, 2016): 606–20. http://dx.doi.org/10.1177/0954410016641441.

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Using the global exploration and Kriging-based multi-fidelity analysis methods, this study developed a multi-fidelity aerodynamic database for use in the performance analysis of flight vehicles and for use in flight simulations. Athena vortex lattice, a program based on vortex lattice method, was used as the low-fidelity analysis tool in the multi-fidelity analysis method. The in-house high-fidelity AADL-3D code was based on the Navier–Stokes equations. The AADL-3D code was validated by comparing the data and the analysis results of the Onera M-6 wing and NACA TN 3649. The design of experiment method and the Kriging method were applied to integrate low- and high-fidelity analysis results. General data tendencies were established from the low-fidelity analysis results. The high-fidelity analysis results and the Kriging method were used to generate a surrogate model, from which the low-fidelity analysis results were interpolated. To reduce repeated calculations, three design points were simultaneously added for each calculation. The convergence of three design points was avoided by considering only the peak points as additional design points. The reliability of the final surrogate model was determined by applying the leave-one-out cross-validation method and by obtaining the cross-validation root mean square error. Using the multi-fidelity model developed in this study, a multi-fidelity aerodynamic database was constructed for use in the three degrees of freedom flight simulation of flight vehicles.
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Rumpfkeil, Markus P., Dean Bryson, and Phil Beran. "Multi-Fidelity Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Analytical Benchmark Problems." Algorithms 15, no. 3 (March 21, 2022): 101. http://dx.doi.org/10.3390/a15030101.

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In this article, multi-fidelity kriging and sparse polynomial chaos expansion (SPCE) surrogate models are constructed. In addition, a novel combination of the two surrogate approaches into a multi-fidelity SPCE-Kriging model will be presented. Accurate surrogate models, once obtained, can be employed for evaluating a large number of designs for uncertainty quantification, optimization, or design space exploration. Analytical benchmark problems are used to show that accurate multi-fidelity surrogate models can be obtained at lower computational cost than high-fidelity models. The benchmarks include non-polynomial and polynomial functions of various input dimensions, lower dimensional heterogeneous non-polynomial functions, as well as a coupled spring-mass-system. Overall, multi-fidelity models are more accurate than high-fidelity ones for the same cost, especially when only a few high-fidelity training points are employed. Full-order PCEs tend to be a factor of two or so worse than SPCES in terms of overall accuracy. The combination of the two approaches into the SPCE-Kriging model leads to a more accurate and flexible method overall.
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Forrester, Alexander I. J., András Sóbester, and Andy J. Keane. "Multi-fidelity optimization via surrogate modelling." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463, no. 2088 (October 2, 2007): 3251–69. http://dx.doi.org/10.1098/rspa.2007.1900.

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This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging . An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an intuitive manner, along with a new variance estimator to account for varying degrees of computational ‘noise’ in the multiple levels of analysis. A multi-fidelity wing optimization is used to demonstrate the methodology.
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Bonfiglio, Luca, Paris Perdikaris, and Stefano Brizzolara. "Multi-fidelity Bayesian Optimization of SWATH Hull Forms." Journal of Ship Research 64, no. 02 (June 1, 2020): 154–70. http://dx.doi.org/10.5957/jsr.2020.64.2.154.

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This study presents a multi-fidelity framework that enables the construction of surrogate models capable of capturing complex correlations between design variables and quantities of interest. Resistance in calm water is investigated for a SWATH hull in a multidimensional design space using a new method to derive high-quality response surfaces through machine learning techniques based on a low number of high-fidelity computations and a larger number of less-expensive low-fidelity computations. First, a verification and validation study is presented with the goal of comparing and ranking numerical methods against experiments performed on a conventional SWATH geometry. Then, the hull geometry of a new family of unconventional SWATH hull forms with twin counter-canted struts is parametrically defined and sequentially refined using multi-fidelity Bayesian optimization. Ship resistance in calm water is finally predicted using observations from two different fidelity levels. We demonstrate that the multi-fidelity optimization framework is successful in obtaining an optimized design using a small number of high-fidelity computations and a larger number of low-fidelity computations. Simulation and optimization costs are reduced by orders of magnitude, providing accurate certificates of fidelity for the performance of the proposed design.
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Thelen, Andrew S., Dean E. Bryson, Bret K. Stanford, and Philip S. Beran. "Multi-Fidelity Gradient-Based Optimization for High-Dimensional Aeroelastic Configurations." Algorithms 15, no. 4 (April 16, 2022): 131. http://dx.doi.org/10.3390/a15040131.

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The simultaneous optimization of aircraft shape and internal structural size for transonic flight is excessively costly. The analysis of the governing physics is expensive, in particular for highly flexible aircraft, and the search for optima using analysis samples can scale poorly with design space size. This paper has a two-fold purpose targeting the scalable reduction of analysis sampling. First, a new algorithm is explored for computing design derivatives by analytically linking objective definition, geometry differentiation, mesh construction, and analysis. The analytic computation of design derivatives enables the accurate use of more efficient gradient-based optimization methods. Second, the scalability of a multi-fidelity algorithm is assessed for optimization in high dimensions. This method leverages a multi-fidelity model during the optimization line search for further reduction of sampling costs. The multi-fidelity optimization is demonstrated for cases of aerodynamic and aeroelastic design considering both shape and structural sizing separately and in combination with design spaces ranging from 17 to 321 variables, which would be infeasible using typical, surrogate-based methods. The multi-fidelity optimization consistently led to a reduction in high-fidelity evaluations compared to single-fidelity optimization for the aerodynamic shape problems, but frequently resulted in a cost penalty for cases involving structural sizing. While the multi-fidelity optimizer was successfully applied to problems with hundreds of variables, the results underscore the importance of accurately computing gradients and motivate the extension of the approach to constrained optimization methods.
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Wei, Yunfei, and Shifeng Xiong. "Bayesian integrative analysis for multi-fidelity computer experiments." Journal of Applied Statistics 46, no. 11 (February 4, 2019): 1973–87. http://dx.doi.org/10.1080/02664763.2019.1575340.

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Klimczyk, Witold Artur, and Zdobyslaw Jan Goraj. "Analysis and optimization of morphing wing aerodynamics." Aircraft Engineering and Aerospace Technology 91, no. 3 (March 4, 2019): 538–46. http://dx.doi.org/10.1108/aeat-12-2017-0289.

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PurposeThe purpose of this paper is to present a method for analysis and optimization of morphing wing. Moreover, a numerical advantage of morphing airfoil wing, typically assessed in simplified two-dimensional analysis is found using higher fidelity methods.Design/methodology/approachBecause of multi-point nature of morphing wing optimization, an approach for optimization by analysis is presented. Starting from naïve parametrization, multi-fidelity aerodynamic data are used to construct response surface model. From the model, many significant information are extracted related to parameters effect on objective; hence, design sensitivity and, ultimately, optimal solution can be found.FindingsThe method was tested on benchmark problem, with some easy-to-predict results. All of them were confirmed, along with additional information on morphing trailing edge wings. It was found that wing with morphing trailing edge has around 10 per cent lower drag for the same lift requirement when compared to conventional design.Practical implicationsIt is demonstrated that providing a smooth surface on wing gives substantial improvement in multi-purpose aircrafts. Details on how this is achieved are described. The metodology and results presented in current paper can be used in further development of morphing wing.Originality/valueMost of literature describing morphing airfoil design, optimization or calculations, performs only 2D analysis. Furthermore, the comparison is often based on low-fidelity aerodynamic models. This paper uses 3D, multi-fidelity aerodynamic models. The results confirm that this approach reveals information unavailable with simplified models.
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Fu, Wenbo, Qiushi Li, Yongshun Song, Yaogen Shu, Zhongcan Ouyang, and Ming Li. "Theoretical analysis of RNA polymerase fidelity: a steady-state copolymerization approach." Communications in Theoretical Physics 74, no. 1 (December 10, 2021): 015601. http://dx.doi.org/10.1088/1572-9494/ac3993.

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Abstract The fidelity of DNA transcription catalyzed by RNA polymerase (RNAP) has long been an important issue in biology. Experiments have revealed that RNAP can incorporate matched nucleotides selectively and proofread the incorporated mismatched nucleotides. However, systematic theoretical researches on RNAP fidelity are still lacking. In the last decade, several theories on RNA transcription have been proposed, but they only handled highly simplified models without considering the high-order neighbor effects and the oligonucleotides cleavage both of which are critical for the overall fidelity. In this paper, we regard RNA transcription as a binary copolymerization process and calculate the transcription fidelity by the steady-state copolymerization theory recently proposed by us for DNA replication. With this theory, the more realistic models considering higher-order neighbor effects, oligonucleotides cleavage, multi-step incorporation and multi-step cleavage can be rigorously handled.
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Kandasamy, Kirthevasan, Gautam Dasarathy, Junier Oliva, Jeff Schneider, and Barnabás Póczos. "Multi-fidelity Gaussian Process Bandit Optimisation." Journal of Artificial Intelligence Research 66 (September 15, 2019): 151–96. http://dx.doi.org/10.1613/jair.1.11288.

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In many scientific and engineering applications, we are tasked with the maximisation of an expensive to evaluate black box function f. Traditional settings for this problem assume just the availability of this single function. However, in many cases, cheap approximations to f may be obtainable. For example, the expensive real world behaviour of a robot can be approximated by a cheap computer simulation. We can use these approximations to eliminate low function value regions cheaply and use the expensive evaluations of f in a small but promising region and speedily identify the optimum. We formalise this task as a multi-fidelity bandit problem where the target function and its approximations are sampled from a Gaussian process. We develop MF-GP-UCB, a novel method based on upper confidence bound techniques. In our theoretical analysis we demonstrate that it exhibits precisely the above behaviour and achieves better bounds on the regret than strategies which ignore multi-fidelity information. Empirically, MF-GP-UCB outperforms such naive strategies and other multi-fidelity methods on several synthetic and real experiments.
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Younis, Adel, and Zuomin Dong. "High-Fidelity Surrogate Based Multi-Objective Optimization Algorithm." Algorithms 15, no. 8 (August 7, 2022): 279. http://dx.doi.org/10.3390/a15080279.

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The employment of conventional optimization procedures that must be repeatedly invoked during the optimization process in real-world engineering applications is hindered despite significant gains in computing power by computationally expensive models. As a result, surrogate models that require far less time and resources to analyze are used in place of these time-consuming analyses. In multi-objective optimization (MOO) problems involving pricey analysis and simulation techniques such as multi-physics modeling and simulation, finite element analysis (FEA), and computational fluid dynamics (CFD), surrogate models are found to be a promising endeavor, particularly for the optimization of complex engineering design problems involving black box functions. In order to reduce the expense of fitness function evaluations and locate the Pareto frontier for MOO problems, the automated multiobjective surrogate based Pareto finder MOO algorithm (AMSP) is proposed. Utilizing data samples taken from the feasible design region, the algorithm creates three surrogate models. The algorithm repeats the process of sampling and updating the Pareto set, by assigning weighting factors to those surrogates in accordance with the values of the root mean squared error, until a Pareto frontier is discovered. AMSP was successfully employed to identify the Pareto set and the Pareto border. Utilizing multi-objective benchmark test functions and engineering design examples such airfoil shape geometry of wind turbine, the unique approach was put to the test. The cost of computing the Pareto optima for test functions and real engineering design problem is reduced, and promising results were obtained.
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Dissertations / Theses on the topic "Multi-fidelity Analysi"

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MAININI, LAURA. "Multidisciplinary and multi-fidelity optimization environment for wing integrated design." Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2500000.

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The Ph.D. program has been focused on the development of a multidisciplinary integrated environment for the design of wing for which large changes in shape are expected to be allowed during the flight in order to be better adapted for the different flight segments. The first phase of study has been dedicated to the investigation of the proper Multidisciplinary Design Optimization (MDO) architecture for the integrated management of the design process and a multilevel solution has been proposed and implemented. Such framework involves several disciplinary analysis and optimization loops: in particular aerodynamic analysis, structural analysis, material optimization and mission and performance evaluation are the main components considered for the preliminary design development for such a “morphing” wing. This stage addressed basically the multidisciplinarity and interdisciplinarity issues. The second phase has been dedicated to the investigation of possible techniques for the reduction of the computational burden that characterizes typically this kind of integrated design processes. For this purpose multi-fidelity analysis techniques have been considered involving the use of surrogate models. In particular the attention has been focused on the study of a proper methodology to build an approximated model for the estimation of aerodynamic coefficients to be used for performance evaluation in the mission optimization stage. In this case a procedure involving variables screening phase, data-fit surrogate models evaluation and assessment phase and a final crucial global correction phase of the best surrogate model has been proposed.
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Le, Gratiet Loic. "Multi-fidelity Gaussian process regression for computer experiments." Phd thesis, Université Paris-Diderot - Paris VII, 2013. http://tel.archives-ouvertes.fr/tel-00866770.

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This work is on Gaussian-process based approximation of a code which can be run at different levels of accuracy. The goal is to improve the predictions of a surrogate model of a complex computer code using fast approximations of it. A new formulation of a co-kriging based method has been proposed. In particular this formulation allows for fast implementation and for closed-form expressions for the predictive mean and variance for universal co-kriging in the multi-fidelity framework, which is a breakthrough as it really allows for the practical application of such a method in real cases. Furthermore, fast cross validation, sequential experimental design and sensitivity analysis methods have been extended to the multi-fidelity co-kriging framework. This thesis also deals with a conjecture about the dependence of the learning curve (ie the decay rate of the mean square error) with respect to the smoothness of the underlying function. A proof in a fairly general situation (which includes the classical models of Gaussian-process based metamodels with stationary covariance functions) has been obtained while the previous proofs hold only for degenerate kernels (ie when the process is in fact finite-dimensional). This result allows for addressing rigorously practical questions such as the optimal allocation of the budget between different levels of codes in the multi-fidelity framework.
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Muppana, Sai. "Multi-fidelity Design and Analysis of Single Hub Multi-rotor High Pressure Centrifugal Compressor." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1553517075653458.

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Venkatesan, Sreedhar, and Hanumantha Raju Hariprasad Banglore. "Probabilistic Analysis of Brake Noise : A Hierarchical Multi-fidelity Statistical Approach." Thesis, Linköpings universitet, Mekanik och hållfasthetslära, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151009.

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Computer Aided Engineering driven analysis is gaining grounds in automotive industry. Prediction of brake noise using CAE techniques has become populardue to its overall low cost as compared to physical testing. However, the presence of several uncertain parameters which affect brake noise and also the lack of basic understanding about brake noise, makes it difficult to make reliable decisions based on CAE analysis. Therefore, the confidence level in CAE techniques has to be increased to ensure reliability and robustness in the CAE solutions which support design work. One such way to achieve reliability in the CAE analysis isinvestigated in this thesis by incorporating the effects of different sources of uncertainty and variability in the analysis and estimating the probability of designfailure (probability of brake noise above a certain threshold). While incorporating the uncertainties in the CAE analysis ensures robustness, it is computationally intensive. This thesis work aims to gain an understanding about a brakenoise - creep groan, and to bring robustness into the CAE analysis along with reduction in computational time. A probabilistic analysis technique called hierarchical multi-fidelity statistical approachis explored in this thesis work, to estimate the probability of design failure or design robustness at a faster rate. It incorporates the stochasticity in the input parameters while running simulations. The method involves application of a hierarchy of approximations to the system response computed with variations in mesh resolution or variations in number of modes or changing solver time step,etc. And finally it uses the probability theory, to relate the information provided by approximate solutions to get the target failure estimation.Through this method, reliable data regarding the probability of design failure was approximated for every simulation and at a reduced computational time.Additionally, it provided information about critical parameters that influenced brake noise which was meritorious for design management. Estimation of probability of design failure by this method has been proved to be reliable in the case of brake noise according to the simulation results and the method can be considered robust.
Computer Aided Engineering (cae) driven analysis is gaining grounds in automotive industry. Brake noise is one such place where cae simulations are gaining more attention. The presence of several uncertain parameters which affect brake noises and also the lack of basic understanding about brake noise, makes it difficult to make reliable decisions based on cae deterministic analyses alone.Therefore, the confidence level in cae analyses has to be increased to ensure cae analysis robustness. One way to achieve this is by incorporating the effects of different sources of uncertainty and variability in the cae analysis and estimating the probability of design failure. Such a reliability measure (i.e. probability of noise event occurrence or exceedance of noise level than a threshold) can provide car manufacturers with an idea about the costs of warranty claims due to brake noise and can be used as a metric to evaluate different design solutions, before the final design goes to the production stage.  On one hand, using the high-fidelity models of brake/chassis system is generally computationally intensive, and thus, often only limited number of simula-tion runs are feasible for uncertainty analysis and design failure risk assessment. On the other hand, analyses on low-fidelity models, typically based on simplified assumptions during the development phase are fast but not always accu-rate. Striking for a good balance between efficiency and accuracy/robustness is an important task, when dealing with uncertainty/risk analysis of such complex dynamical systems To address these issues, a hierarchical multi-fidelity statistical approach has been adopted in this study, in order to estimate the probability of design failure. It employs a hierarchy of approximations to the system response computed with different fidelity by surrogate modelling, coarse spatial/temporal model mesh resolution variation, changing solver time step, etc., using probability theory, to relate information provided by approximate solu-tions to the target failure estimation. Using this approach opens up the possi-bility to use a low-fidelity models to accelerate the uncertainty quantification of complex brake/chassis systems, while granting unbiased estimation of system design failure risk/reliability. It also enables management of design changes, during fast iterations of the design process. This approach is used for studying one of the brake noise issue called creep groan, understand the root cause and providedesign proposals.
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Loupy, Gaëtan J. M. "High fidelity, multi-disciplinary analysis of flow in realistic weapon bays." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/9091/.

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To improve the stealthiness, and the efficiency of military aircraft, engineers moved carried weapons from external hand points, to weapons bays. However, the flow inside bays is turbulent, and characterised by strong broadband, and tonal noise. The open bay flow leads to variability in the released store trajectory, excites the missile, and bay structures, and reduces the aircraft stealthiness. This thesis aims to improve our understanding of real weapon bay flow, and suggests a method for quantifying the store trajectory variability. The main spatio-temporal characteristics of cavity flows are described using post-processing methods, like, SPL, OASPL, and wavelet transform. Also, the code HMB3 is validated for simulation of cavity flows, comparing Scale Adaptive (SAS) results with experiments. To further improve the understanding of the physics driving this flow, a simple model is presented, and compared to experiments. The results are promising, and the model is able to reproduce the cavity flow fluctuations both in space and time. To support measurements of the noise field around a cavity flow, beamforming is applied to the CFD results. This method was able of capturing the main sources of noise around the cavity, using a microphone array, and the mean flow to simulate the propagation of acoustic waves. Also, recommendations for future use of this technique are given. Developments were carried out for this thesis, and for the first time, a CFD code is reported to simulate the complete weapon bay operation, including door operation, store release, and store aeroelasticity. The different parts of the code are strongly coupled, and work together. Thanks to new capabilities of HMB3, this thesis shows more insight on the physics behind realistic weapon bay operation. The flow establishment during door opening is described, and appears to be important for store design, only if the doors are moving very fast. Store releases are simulated, and statistical analysis of the data is performed. A statistical metric was proposed to identify the minimum number of simulations necessary for capturing the mean and standard deviation of the trajectories. Using averaged, and filtered flow data, the trajectory phases were identified and the role of the pressure field inside the cavity was clarified. In addition, the aeroelasticity of the store was computed during carriage, door opening, and release phases, showing small deformations that may lead to structural fatigue. Thanks to the efficiency of the SAS method, a large number of simulations were performed, and more than 1800 cavity travel times were simulated. Simulation of the flow around a store in a supersonic flow, and at high attitude is described in an appendix of the thesis. Like a cavity, this flow has complex features that require advanced turbulence modelling to be simulated. In addition, novel cavity flow controls are investigated, and described in a restricted appendix of the thesis.
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Stults, Ian Collier. "A multi-fidelity analysis selection method using a constrained discrete optimization formulation." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31706.

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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Mavris, Dimitri; Committee Member: Beeson, Don; Committee Member: Duncan, Scott; Committee Member: German, Brian; Committee Member: Kumar, Viren. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Lawson, Stephen James. "High performance computing for high-fidelity multi-disciplinary analysis of weapon bays." Thesis, University of Liverpool, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.533992.

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Meckstroth, Christopher. "Incorporation of Physics-Based Controllability Analysis in Aircraft Multi-Fidelity MADO Framework." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575557306181006.

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Raj, Oliver Neal. "Multi-Fidelity Structural Modeling For Set Based Design of Advanced Marine Vehicles." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/83377.

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This thesis demonstrates that a parametrically-modifiable Advanced Marine Vehicle Structural (AMVS) module (that can be integrated into a larger framework of marine vehicle analysis modules) enables stakeholders, as a group, to complete structurally feasible ship designs using the Set-Based Design (SBD) method. The SBD method allows stakeholders to identify and explore multiple solutions to stakeholder requirements and only eliminating the infeasible poorer solutions after all solutions are completely explored. SBD offers the and advantage over traditional design methods such as Waterfall and Spiral because traditional methods do not adequately explore the design space to determine if they are eliminating more optimal solutions in terms of cost, risk and performance. The fundamental focus for this thesis was on the development of a parametrically modifiable AMVS module using a low-fidelity structural analysis method implemented using a numerical 2D Finite Element Analysis (FEA) applied to the HY2-SWATH. To verify the AMVS module accuracy, a high-fidelity structural analysis was implemented in MAESTRO to analyze the reference marine vehicle model and provide a comparison baseline. To explore the design space, the AMVS module is written to be parametrically modified through input variables, effectively generating a new vessel structure when an input is changed. AMVS module is used to analyze an advanced marine vessel in its two operating modes: displacement and foil-borne. AMVS demonstrates the capability to explore the design space and evaluate the structural feasibility of the advance marine vehicle designs through consideration of the material, stiffener/girder dimensions, stiffener/girder arrangement, and machinery/equipment weights onboard.
Master of Science
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Mola, Andrea. "Multi-physics and Multilevel Fidelity Modeling and Analysis of Olympic Rowing Boat Dynamics." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28057.

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A multidisciplinary approach for the modeling and analysis of the performance of Olympic rowing boats is presented. The goal is to establish methodologies and tools that would determine the effects of variations in applied forces and rowers motions and weights on mean surge speed and oscillatory boat motions. The coupling between the rowers motions with the hull and water forces is modeled with a system of equations. The water forces are computed using several fluid dynamic models that have different levels of accuracy and computational cost. These models include a solution of the Reynolds Averaged Navier--Stokes equations complemented by a Volume of Fluid method, a linearized 3D potential flow simulation and a 2D potential flow simulation that is based on the strip theory approximation. These results show that due to the elongated shape of the boat, the use of Sommerfeld truncation boundary condition does not yield the correct frequency dependence of the radiative coefficients. Thus, the radiative forces are not computed in the time-domain problem by means of a convolution integral, accounting for flow memory effects, but were computed assuming constant damping and added mass matrices. The results also show that accounting for memory effects significantly improves the agreement between the strip theory and the RANS predictions. Further improvements could be obtained by introducing corrections to account for longitudinal radiative forces, which are completely neglected in the strip theory. The coupled dynamical system and the multi-fidelity fluid models of the water forces were then used to perform a sensitivity analysis of boat motions to variations in rowers weights, exerted forces and cadence of motion. The sensitivity analysis is based on the polynomial chaos expansion. The coefficients of each random basis in the polynomial chaos expansion are computed using a non-intrusive strategy. Sampling, quadrature, and linear regression methods have been used to obtain the these coefficients from the outputs generated by the system at each sampling point. The results show that the linear regression method provides a very good approximation of the PCE coefficients. In addition, the number of samples needed for the expansion, does not grow exponentially with the number of varying input parameters. For this reason, this method has been selected for performing the sensitivity analysis. The sensitivity of output parameters to variations in selected input parameters of the system are obtained by taking the derivatives of the expansion with respect to each input parameter. Three test cases are considered: a light-weight female single scull, a male quad scull, and a male coxless four. For all of these cases, results that relate the effects of variations in rowers weights, amplitudes of exerted forces and cadence of rowing on mean boat speed and energy ratio, defined as the ratio of kinetic energy of the forward motion to that of the oscillatory motions, are presented. These results should be useful in the design of rowing boats as well as in the training of rowers.
Ph. D.
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Book chapters on the topic "Multi-fidelity Analysi"

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Tejika, Shintaro, Takahiro Fujikawa, and Koichi Yonemoto. "Multi-objective System Optimization of Suborbital Spaceplane by Multi-fidelity Aerodynamic Analysis." In Lecture Notes in Electrical Engineering, 283–96. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2689-1_21.

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Elham, Ali, and Michel J. L. van Tooren. "Trust Region Filter-SQP Method for Multi-Fidelity Wing Aerostructural Optimization." In Variational Analysis and Aerospace Engineering, 247–67. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45680-5_10.

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Tung, Y.-C., C.-T. Lin, K. Kurabayashi, and S. J. Skerlos. "High Fidelity and Low Cost Detection of Multi-Color Fluorescence from Biological Cells in a Micro Integrated Flow Cytometer (MIFC) with Disposable Observation Cell." In Micro Total Analysis Systems 2002, 254–56. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0295-0_85.

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Fitzgerald, John, Ken Pierce, and Peter Gorm Larsen. "Collaborative Development of Dependable Cyber-Physical Systems by Co-Modeling and Co-Simulation." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 1–28. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6194-3.ch001.

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The pace of innovation in Cyber-Physical Systems (CPSs) drives the need for multi-disciplinary methods and tools to support rapid and accurate assessment of design alternatives. In this chapter, the authors describe collaborative models (co-models) that link Discrete-Event (DE) models of control software with Continuous-Time (CT) models of controlled plant. They present methods and tools for co-modeling using VDM as the DE formalism, and bond graphs on the CT side, using the Crescendo platform to link existing simulators (Overture for VDM and 20-sim for bond graphs). The authors discuss the exploitation of co-models within the design flow, including their use with SysML, and the roles of Software-in the-Loop and Hardware-in-the-Loop simulation on the way to realising co-models in cyber and physical media. The authors identify research challenges in providing sufficient model fidelity and the evidence needed to support the engineering of certifiably dependable systems.
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Day, Kirsten. "John Ford’s The Searchers1." In Cowboy Classics. Edinburgh University Press, 2016. http://dx.doi.org/10.3366/edinburgh/9781474402460.003.0006.

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John Ford’s 1956 The Searchers has attracted more scholarly attention than any other Western, including that of receptions scholars who have noted its kinship with Homeric epic. This chapter enlarges on the most important of these arguments – Martin Winkler’s study of John Wayne’s Ethan Edwards as an Achilles figure and the author’s own analysis of the film as an Odyssean journey – recognizing the psychological identification between protagonist and enemy-as-alter-ego long noted by Western scholars as an important parallel with the dynamic found in ancient epic and expanding on the importance of women’s sexual fidelity to male honor and identity. This chapter then brings the Aeneid into the conversation, demonstrating that like Virgil’s epic, The Searchers is a self-questioning, multi-layered reflection on heroic achievement, offering a problematic hero and extolling the glories of empire while acknowledging the sacrifices inherent in its establishment. Finally, this chapter considers this film as a commentary on racial and Cold War tensions in 1950s America, reflecting on how this fits in with the larger comparison with ancient epic.
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Conference papers on the topic "Multi-fidelity Analysi"

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Balabanov, Vladmir, and Gerhard Venter. "Multi-Fidelity Optimization with High-Fidelity Analysis and Low-Fidelity Gradients." In 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.2004-4459.

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Fischer, Christopher C., and Ramana V. Grandhi. "Multi-Fidelity Design Optimization via Low-Fidelity Correction Technique." In 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-4293.

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Olson, Erik D. "Multi-Disciplinary, Multi-Fidelity Discrete Data Transfer Using Degenerate Geometry Forms." In 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-3208.

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Jain, Samarth, William A. Crossley, and Satadru Roy. "A Multi-Fidelity Approach to Address Multi-Objective Mixed-Discrete Nonlinear Programming Problems." In 2018 Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3414.

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Jaeggi, Daniel, Geoff Parks, William Dawes, and John Clarkson. "Robust Multi-Fidelity Aerodynamic Design Optimization Using Surrogate Models." In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-6052.

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Alonso, Juan, Patrick LeGresley, Edwin Van der Weide, Joaquim R. R. A. Martins, and James Reuther. "pyMDO: A Framework for High-Fidelity Multi-Disciplinary Optimization." In 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.2004-4480.

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Haimes, Robert, John Dannenhoffer, Nitin D. Bhagat, and Darcy L. Allison. "Multi-fidelity Geometry-centric Multi-disciplinary Analysis for Design." In AIAA Modeling and Simulation Technologies Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-4007.

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Nigam, Nikhil, Ankit Tyagi, Peter Chen, Juan J. Alonso, Francisco Palacios, Michael V. Ol, and John Byrnes. "Multi-Fidelity Multi-Disciplinary Propeller/Rotor Analysis and Design." In 53rd AIAA Aerospace Sciences Meeting. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-0029.

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Ghoreishi, Seyede Fatemeh, and Douglas L. Allaire. "Gaussian Process Regression for Bayesian Fusion of Multi-Fidelity Information Sources." In 2018 Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-4176.

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MacDonald, Timothy, Matthew Clarke, Emilio M. Botero, Julius M. Vegh, and Juan J. Alonso. "SUAVE: An Open-Source Environment Enabling Multi-Fidelity Vehicle Optimization." In 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2017. http://dx.doi.org/10.2514/6.2017-4437.

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Reports on the topic "Multi-fidelity Analysi"

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Ayoul-Guilmard, Q., S. Ganesh, M. Nuñez, R. Tosi, F. Nobile, R. Rossi, and C. Soriano. D5.4 Report on MLMC for time dependent problems. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.005.

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In this report, we study the use of Multi-Level Monte Carlo (MLMC) methods for time dependent problems. It was found that the usability of MLMC methods depends strongly on whether or not the underlying time dependent problem is chaotic in nature. Numerical experiments are conducted on both simple problems, as well as fluid flow problems of practical interest to the ExaQUte project, to demonstrate this. For the non-chaotic cases, the hypotheses that enable the use of MLMC methods were found to be satisfied. For the chaotic cases, especially the case of high Reynolds’ number fluid flow, the hypotheses were not satisfied. However, it was found that correlations between the different levels were high enough to merit the use of multi-fidelity or control-variate approaches. It was also noted that MLMC methods could work for chaotic problems if the time window of analysis were chosen to be small enough. Future studies are proposed to examine this possibility.
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