Relevant bibliographies by topics / Monte Carlo method Vector mesons

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Monte Carlo method Vector mesons'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Monte Carlo method Vector mesons"

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Makarova, K. V., A. G. Makarov, M. A. Padalko, V. S. Strongin, and K. V. Nefedev. "Multispin Monte Carlo Method." Dal'nevostochnyi Matematicheskii Zhurnal 20, no. 2 (November 25, 2020): 212–20. http://dx.doi.org/10.47910/femj202020.

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The article offers a Monte Carlo cluster method for numerically calculating a statistical sample of the state space of vector models. The statistical equivalence of subsystems in the Ising model and quasi-Markov random walks can be used to increase the efficiency of the algorithm for calculating thermodynamic means. The cluster multispin approach extends the computational capabilities of the Metropolis algorithm and allows one to find configurations of the ground and low-energy states.
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CHIN, SIU A. "HAMILTONIAN LATTICE STUDIES OF CHIRAL MESON FIELD THEORIES." International Journal of Modern Physics B 13, no. 05n06 (March 10, 1999): 721–29. http://dx.doi.org/10.1142/s0217979299000618.

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The latticization of the non-linear sigma model reduces a chiral meson field theory to an O(4) spin lattice system with quantum fluctuations. The result is an interesting marriage between quantum many-body theory and classical spin systems. By solving the resulting lattice Hamiltonian by Monte Carlo methods, the dynamics and thermodynamics of pions can be determined non-perturbatively. In a variational 16 3 lattice study, the ground state chiral phase transition is shown to be first order. Moreover, as the chiral phase transition is approached, the mass gap of pionic collective modes with quantum number of the "ω" vector meson drops toward zero.
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Rymarczyk, Tomasz, and Grzegorz Kłosowski. "SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD." Informatics Control Measurement in Economy and Environment Protection 7, no. 4 (December 21, 2017): 20–23. http://dx.doi.org/10.5604/01.3001.0010.7244.

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In this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.
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Goldberg, A., and S. D. Bloom. "Monte Carlo Algorithms for Moments of Transition Arrays." International Astronomical Union Colloquium 102 (1988): 79–81. http://dx.doi.org/10.1017/s0252921100107468.

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AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV> for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV>. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.
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Shiina, Takayuki. "Capacity Expansion Problem by Monte Carlo Sampling Method." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 6 (November 20, 2009): 697–703. http://dx.doi.org/10.20965/jaciii.2009.p0697.

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We consider the stochastic programming problem with recourse in which the expectation of the recourse function requires a large number of function evaluations, and its application to the capacity expansion problem. We propose an algorithm which combines an L-shaped method and a Monte Carlo method. The importance sampling technique is applied to obtain variance reduction. In the previous approach, the recourse function is approximated as an additive form in which the function is separable in the components of the stochastic vector. In our approach, the approximate additive form of the recourse function is perturbed to define the new density function. Numerical results for the capacity expansion problem are presented.
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Koch, K. R. "Bayesian statistics and Monte Carlo methods." Journal of Geodetic Science 8, no. 1 (February 1, 2018): 18–29. http://dx.doi.org/10.1515/jogs-2018-0003.

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Abstract The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes’ theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.
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Mikhailov, G. A., and I. N. Medvedev. "Vector estimators of the Monte Carlo method: Dual representation and optimization." Numerical Analysis and Applications 3, no. 4 (October 2010): 344–56. http://dx.doi.org/10.1134/s1995423910040063.

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Churmakov, D. Yu, V. L. Kuz'min, and I. V. Meglinskii. "Application of the vector Monte-Carlo method in polarisation optical coherence tomography." Quantum Electronics 36, no. 11 (November 30, 2006): 1009–15. http://dx.doi.org/10.1070/qe2006v036n11abeh013339.

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ABDALLA, AREEG, and JAMES BUCKLEY. "MONTE CARLO METHODS IN FUZZY NON-LINEAR REGRESSION." New Mathematics and Natural Computation 04, no. 02 (July 2008): 123–41. http://dx.doi.org/10.1142/s1793005708000982.

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We apply our new fuzzy Monte Carlo method to certain fuzzy non-linear regression problems to estimate the best solution. The best solution is a vector of triangular fuzzy numbers, for the fuzzy coefficients in the model, which minimizes an error measure. We use a quasi-random number generator to produce random sequences of these fuzzy vectors which uniformly fill the search space. We consider example problems to show that this Monte Carlo method obtains solutions comparable to those obtained by an evolutionary algorithm.
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Pan, Qiujing, and Daniel Dias. "An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation." Structural Safety 67 (July 2017): 85–95. http://dx.doi.org/10.1016/j.strusafe.2017.04.006.

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Dissertations / Theses on the topic "Monte Carlo method Vector mesons"

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Junnarkar, Parikshit Manoj. "Monte-Carlo simulation of photoproduction of Omega meson." Master's thesis, Mississippi State : Mississippi State University, 2006. http://library.msstate.edu/etd/show.asp?etd=etd-07312006-013358.

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Segundo, Evandro Oliveira Andrade. "Produção de mésons vetoriais em colisões ultra-periféricas com o código de Monte Carlo CRISP." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/43/43134/tde-09112015-160031/.

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Este trabalho é dedicado ao estudo da fotoprodução de mésons vetoriais em colisões ultra-periféricas. Este estudo foi realizado por meio do código de Monte Carlo CRISP, o qual recebeu atualizações e implementações a fim de permitir o cálculo das colisões. Foi elaborado um modelo para a geração do espectro de energia dos fótons equivalentes que deve interagir com o alvo, bem como foram introduzidos novos canais de foto-absorção para a fotoprodução de múltiplos píons, os quais são essenciais à reprodução dos fenômenos nucleares em altas energias. Ao todo 84 canais foram introduzidos. Foi estudada, em particular, a produção do méson J/$\\psi$ em colisões Pb-Pb a $\\sqrt = 2.76$ TeV e em colisões Au-Au a $\\sqrt = 200$ GeV.
This work is dedicated to the study of the photoproduction of vector mesons in ultra-peripheral collisions. This study was accomplished by means of the Monte Carlo code CRISP which gained updates and implementations in order to allow the calculation of the collisions. A model for the generation of the spectrum of equivalent photons that interact with the target was designed. Also, new photo-absorption channels for the multipion photoproduction were introduced in the code. They are essential to the description of the nuclear environment at high energies. Altoghether, 84 channels were implemented. In particular, the production of the J/$\\psi$ vector meson in Pb-Pb collision at $\\sqrt = 2.76$ TeV and in Au-Au collisions at $\\sqrt = 200$ GeV was studied.
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Borkar, Milind. "A distributed Monte Carlo method for initializing state vector distributions in heterogeneous smart sensor networks." Diss., Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22680.

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The objective of this research is to demonstrate how an underlying system's state vector distribution can be determined in a distributed heterogeneous sensor network with reduced subspace observability at the individual nodes. We show how the network, as a whole, is capable of observing the target state vector even if the individual nodes are not capable of observing it locally. The initialization algorithm presented in this work can generate the initial state vector distribution for networks with a variety of sensor types as long as the measurements at the individual nodes are known functions of the target state vector. Initialization is accomplished through a novel distributed implementation of the particle filter that involves serial particle proposal and weighting strategies, which can be accomplished without sharing raw data between individual nodes in the network. The algorithm is capable of handling missed detections and clutter as well as compensating for delays introduced by processing, communication and finite signal propagation velocities. If multiple events of interest occur, their individual states can be initialized simultaneously without requiring explicit data association across nodes. The resulting distributions can be used to initialize a variety of distributed joint tracking algorithms. In such applications, the initialization algorithm can initialize additional target tracks as targets come and go during the operation of the system with multiple targets under track.
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Arcila, Gago Manuel Felipe 1987. "Modelo de juntas soldadas por FSW utilizando métodos de aprendizagem de máquina através de dados experimentais." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/265022.

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Orientador: Janito Vaqueiro Ferreira
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
Made available in DSpace on 2018-08-23T16:12:48Z (GMT). No. of bitstreams: 1 ArcilaGago_ManuelFelipe_M.pdf: 7192169 bytes, checksum: 7b23a08769656a07765344e20d1f6ad4 (MD5) Previous issue date: 2013
Resumo: A variedade de materiais no setor aeronáutico para redução de peso e custo tem se proliferado a um grau intensivo, onde têm sido revisadas diferentes pesquisas para encontrar outros tipos de materiais de fácil maneabilidade para construção de peças que satisfazem as restrições impostas. Assim, existe uma procura constante de soluções para facilitar a produção, e ao mesmo tempo aumentar a segurança das aeronaves levando em consideração pontos importantes como a fadiga e ruptura do material. Um material frequentemente utilizado que atende a estes requisitos devido a suas propriedades de densidade e resistência é o alumínio, e é neste ambiente que existe um processo de manufatura utilizado para a soldagem conhecido como "Friction Stir Welding" (FSW). No presente momento, estudos para criação de modelos que representem características mecânicas utilizadas em projetos em função de parâmetros do processo tem sido pesquisados. Embora este processo seja de difícil modelagem devidos as suas complexidades, tem sido estudado e utilizado diferentes algoritmos que possibilitem o melhoramento da representação do modelo, tais como os relacionados com máquinas de aprendizagem (ML) e suas diferentes otimizações. Neste contexto, a presente pesquisa tem seu foco na obtenção de um modelo baseado no algoritmo de aprendizagem de Máquina de Vetores de Suporte (SVM), e também com outros algoritmos tais como Regressão Polinomial (RP) e Rede Neural Artificial (RNA), buscando encontrar modelos que representem o processo de soldagem por FSW através das propriedades mecânicas obtidas pelos ensaios de tração e por análise de variância (ANOVA), entendendo suas vantagens e, posteriormente, recomendar quais dos algoritmos de aprendizagem tem maior beneficio
Abstract: In the aerospace industry to reduce weight and cost, a great quantity of materials has been used, which has generated research to find types of materials, that have been better maneuverability and to guarantee the properties required to development of pieces for the industry. Thus, the studies look for optimize between production easiness and increase the aircraft safety, taking into consideration important issues such as fatigue and fracture of the materials. One of the most common approach used is aluminum by their mechanical properties (density and strength), although it has many problems to be welding with the traditional methods. Currently, the Friction Stir Welding (FSW) process is used in the industry, as well in the academy. However, the FSW is difficult to model by the complexities in the physical phenomenal occurred during the weld process, as result, has been studied and used different algorithms that allow enhance the model representation. The Machine Learning (ML) is a methodology studied to obtain the model optimized. In this context, the present research focus by to obtain a model-based in learning algorithm using Support Vector Machine (SVM). Although comparisons were made with other algorithms such as Polynomial Regression (PR) and Artificial Neural Network (ANN), searching to find models that represent the FSW process weld using the mechanical properties obtained by tensile tests and analysis of variance (ANOVA). Finally, conclusions to understand the advantages learning algorithms are presented
Mestrado
Mecanica dos Sólidos e Projeto Mecanico
Mestre em Engenharia Mecânica
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Buba, Ondřej. "Praktické testování metod analýzy spolehlivosti v konkrétních obvodových aplikacích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-241037.

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This diploma thesis deals with the method which are useful for analysis of reliability in specific circuit applications. It also deals with fault analysis in frequency, time and DC domain. Methods for these domains are described in other chapter of this thesis. Finally methods for diagnostics analog circuit are evaluated based on simulation and practical testing of selected methods.
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Calvat, Pascal. "Mesure des observables de polarisation dans la photoproduction des mésons pseudoscalaires à GRAAL : préparation des programmes d'analyse et premiers résultats expérimentaux." Grenoble 1, 1997. http://www.theses.fr/1997GRE10005.

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L'experience de physique nucleaire graal installee a grenoble aupres du synchroton europeen (esrf) produit, par retrodiffusion compton, un faisceau de gammas polarises lineairement ou circulairement. Les caracteristiques d'un tel faisceau rendent possible l'etude des reactions de photoproduction de mesons pseudoscalaires (pion, eta, kaon) dont certains aspects theoriques sont explicites dans le cadre de cette these. Une description precise des programmes d'analyse permet de comprendre le traitement complet des informations depuis l'acquisition des donnees jusqu'a la presentation des resultats preliminaires sur l'asymetrie du faisceau pour les reactions de photoproduction du pion et du eta dans le domaine d'energie situe entre 700 et 1100 mev. Des methodes d'extraction des observables de polarisation de la reaction de photoproduction d'un kaon, associe a un lambda, ont ete mises au point a partir de la simulation monte-carlo. La reproduction precise des trois observables de simple de polarisation ainsi que des quatre observables de double polarisations faisceau-recul, pour un ensemble de donnees simulees correspondant a 100000 reactions de photoproduction du kaon, montre que ces quantites peuvent etre mesurees dans l'experience graal
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Huster, Carl R. "A parallel/vector Monte Carlo MESFET model for shared memory machines." Thesis, 1992. http://hdl.handle.net/1957/37306.

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The parallelization and vectorization of Monte Carlo algorithms for modelling charge transport in semiconductor devices are considered. The standard ensemble Monte Carlo simulation of a three parabolic band model for GaAs is first presented as partial verification of the simulation. The model includes scattering due to acoustic, polar-optical and intervalley phonons. This ensemble simulation is extended to a full device simulation by the addition of real-space positions, and solution for the electrostatic potential from the charge density distribution using Poisson's equation. Poisson's equation was solved using the cloud-in-cell scheme for charge assignment, finite differences for spatial discretization, and simultaneous over-relaxation for solution. The particle movement (acceleration and scattering) and the solution of Poisson's are both separately parallelized. The parallelization techniques used in both parts are based on the use of semaphores for the protection of shared resources and processor synchronization. The speed increase results for parallelization with and without vectorization on the Ardent Titan II are presented. The results show saturation due to memory access limitations at a speed increase of approximately 3.3 times the serial case when four processors are used. Vectorization alone provides a speed increase of approximately 1.6 times when compared with the nonvectorized serial case. It is concluded that the speed increase achieved with the Titan II is limited by memory access considerations and that this limitation is likely to plague shared memory machines for the forseeable future. For the program presented here, vectorization is concluded to provide a better speed increase per day of development time than parallelization. However, when vectorization is used in conjunction with parallelization, the speed increase due to vectorization is negligible.
Graduation date: 1993
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Cadien, Adam Samuel. "Applications of the Wavelet Transform to B Mixing Analysis." 2008. http://hdl.handle.net/2429/868.

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Abstract The neutral B mesons B0 and B0s can under go flavor changing oscillations due to interactions by the weak force. Experiments which measure the frequency of these state transitions produce extremely noisy results that are difficult to analyse. A method for extracting the frequency of B mesons oscillations using the continuous wavelet transform is developed here. In this paper the physics of B meson mixing is related, leading to the derivation of a function describing the expected amount of mixing present in B0 and B0s meson decays. This result is then used to develop a new method for analysing the underlying frequency of oscillation in B mixing. An introduction to wavelet theory is provided in addition to details on interpreting daughter wavelet coefficient diagrams. Finally, the effectiveness of the analysis technique produced, referred to as the Template Fitting Method, is investigated through an application to data generated using Monte Carlo methods.
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Books on the topic "Monte Carlo method Vector mesons"

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Huster, Carl R. A parallel/vector Monte Carlo MESFET model for shared memory machines. 1992.

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United States. National Aeronautics and Space Administration., ed. Particle/continuum hybrid simulation in a parallel computing environment: Final report for the period August 1, 1994 to September 30, 1996 ... grant no. NCC2-5072. Stanford, Calif: Department of Aeronautics and Astronautics, Stanford University, 1991.

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Book chapters on the topic "Monte Carlo method Vector mesons"

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Tsai, Liang-Ting, Chih-Chien Yang, and Timothy Teo. "Weighting Imputation for Categorical Data." In Encyclopedia of Business Analytics and Optimization, 2706–16. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5202-6.ch241.

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This article aims to propose the Learning Vector Quantization (LVQ) approach to impute missing group membership and sampling weights in inferring the accuracy of population parameters of confirmatory factor analysis (CFA) models with categorical questionnaires. Survey data with missing group memberships, for example, gender, age, or ethnicity, are very familiar. However, the group memberships of examinees are critical for calculating the stratum sampling weights. Asparouhov (2005), Tsai and Yang (2008), and Yang and Tsai (2008) have described that appropriate imputation can further improve the precision of CFA model estimations. Questionnaires with categorical responses are not well established yet. In this study, a Monte Carlo simulation was conducted to compare the LVQ method with the other three existing methods (e.g., listwise-deletion, weighting-class adjustment, non-weighted). Four experimental factors, such as missing data rates, sampling sizes, disproportionate sampling, and different populations, were used to examine the performance of these four methods. The results showed that the LVQ method outperformed the other three methods in terms of accuracy of parameters of CFA model with binary or 5-category responses. The conclusion and discussion sections of this article provide for some practical guidelines.
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Conference papers on the topic "Monte Carlo method Vector mesons"

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Chen, Chuan, and Wei Gao. "Estimating parameter uncertainties using hybrid Monte Carlo-Least Squares Support Vector Machine method." In 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010). IEEE, 2010. http://dx.doi.org/10.1109/car.2010.5456735.

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Min Wang, Yongjiu Zhao, Tian Hong Loh, Qian Xu, and Yonggang Zhou. "Efficient Uncertainty Evaluation of Vector Network Analyser Measurements Using Two-Tier Bayesian Analysis and Monte Carlo Method." In 12th European Conference on Antennas and Propagation (EuCAP 2018). Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/cp.2018.0649.

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Chen, Chong, Zhenfei Zhan, Huili Yu, and Hui Zhao. "A Relevance Vector Regression Based Uncertainty Quantification Method for Robustness Design." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71842.

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Metamodel based robustness design is commonly used to mitigate the consequences of variability without removing its underlying sources. However, uncertainties introduced by metamodels should be properly addressed before conducting design optimization. In addition, the measurable data uncertainties from physical tests and computer simulations are also unneglectable. Relevance Vector Regression (RVR) is a probability model based on the Bayesian learning framework. It shows potential in estimating the prediction uncertainty. This paper proposes an alternative RVR based robustness design procedure considering the design variables uncertainty, data uncertainty and metamodeling uncertainty. Based on the fundamental theory of RVR, simplified expressions of the response mean and variance is derived for robustness design accounting for three kinds of uncertainties. The formulation of RVR based robustness design is then built. Double loop Monte Carlo sampling is used to solve this optimization problem. An engineering example is used to demonstrate the proposed method and comparative studies are conducted between the proposed method and traditional robustness design.
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Deodatis, George, Radu Popescu, and Jean H. Prevost. "Simulation of Stochastic Processes and Fields for Monte Carlo Simulation Applications: Some Recent Developments." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0341.

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Abstract Two of the latest developments concerning the spectral representation method (used to simulate stochastic processes and fields) are presented in this paper. The first one introduces an extension of the spectral representation method to simulate non-stationary stochastic vector processes with evolutionary power. The proposed simulation formula is simple and straightforward and generates sample functions of the vector process according to a prescribed non-stationary cross-spectral density matrix. The second development introduces another extension of the spectral representation method to simulate multi-dimensional, multi-variate, non-Gaussian stochastic fields. In this case, sample functions are generated according to a prescribed cross-spectral density matrix and prescribed (non-Gaussian) probability distribution functions. Numerical examples are provided for both developments.
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Jones, Oliver, Kevin Ewans, and Stanley Chuah. "A Monte Carlo Approach for Estimating Extreme Currents in the Singapore Straits." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11147.

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Utilizing the independency of tide, through-flow, surge and high-frequency currents in the Singapore Straits, a Monte Carlo simulation method of combining the different components is proposed, expanding the horizon of available measured and modelled data and facilitating the definition of design current speeds. The statistical model proceeds by, first, making N number of random picks from the non-exceedence probability distributions of the surge, through-flow and high-frequency components. The number of random picks made in a given year for each component, N, is defined by assuming its occurrence rate is Poisson-distributed around a known annual mean value. N number of random start times are then chosen from each year and the maximum value of tidal current predicted over an ensuring 3-day window is combined with the randomly sampled component (either surge, through-flow or high-frequency current). Assuming an intended design life of 50 years, this process is repeated N number of times in each of the 50 years and for each current component, yielding 50 annual maximum values. For random 3-day windows that overlap, the model takes the vector sum of the maximum tidal current and the 2 (or 3) concurrent components. The process is repeated 1000 times, producing 1000 * 50 values of annual maxima which are then assigned non-exceedence probabilities. Return Period levels are obtained directly from the non-exceedence probabilities. The method provides a reduction in design current when compared to values derived by multiplying the exceedence probabilities of the varying independent contributions directly.
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Gao, Jinsong, Kenneth W. Chase, and Spencer P. Magleby. "Comparison of Assembly Tolerance Analysis by the Direct Linearization and Modified Monte Carlo Simulation Methods." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0047.

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Abstract Two methods for performing statistical tolerance analysis of mechanical assemblies are compared: the Direct Linearization Method (DLM), and Monte Carlo simulation. A selection of 2-D and 3-D vector models of assemblies were analyzed, including problems with closed loop assembly constraints. Closed vector loops describe the small kinematic adjustments that occur at assembly time. Open loops describe critical clearances or other assembly features. The DLM uses linearized assembly constraints and matrix algebra to estimate the variations of the assembly or kinematic variables, and to predict assembly rejects. A modified Monte Carlo simulation, employing an iterative technique for closed loop assemblies, was applied to the same problem set. The results of the comparison show that the DLM is accurate if the tolerances are relatively small compared to the nominal dimensions of the components, and the assembly functions are not highly nonlinear. Sample size is shown to have great influence on the accuracy of Monte Carlo simulation.
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Golbayani, Hami, and Kazem Kazerounian. "An Improved Risk Based Design Method Based on a Novel Upper Bound Formulation." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48413.

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In this work, a novel framework is proposed for the risk based design optimization of engineering systems by minimizing the demand on the system components’ accuracy (which directly relates to their cost). The fundamental development of this work is an analytical upper bound for calculating the probability of failure. This is in contrast with First Order Reliability Method (FORM), where a lower bound is used in calculating the probability of failure. FORM is one of the most popular methods for reliability analysis of engineering systems. In this paper, we show that FORM results in an optimistic measure of risk, hence potentially catastrophic in engineering design. A more accurate measure of failure is proposed by utilizing an analytical upper bound for the distribution of reliability index (the length of the most probable point vector to origin). This distribution is a function of the eigenvalues of the linearized limit state function in the normal space which results in a better understanding of failure phenomenon. The proposed formulation is computationally efficient and straightforward to solve, since it only involves finding eigenvalues in each iteration. This algorithm is applicable to any linearizable continuous limit state function with any type of distribution for the design variables. The method is applied to two examples and its accuracy is compared with the Monte Carlo simulation and FORM, demonstrating its effectiveness and value.
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8

Song, Hyeongjin, K. K. Choi, Ikjin Lee, Liang Zhao, and David Lamb. "Sampling-Based RBDO Using Probabilistic Sensitivity Analysis and Virtual Support Vector Machine." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70715.

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In this paper, a sampling-based RBDO method using a classification method is presented. The probabilistic sensitivity analysis is used to compute sensitivities of probabilistic constraints with respect to random variables. Since the probabilistic sensitivity analysis requires only the limit state function, and not the response surface or sensitivity of the response, an efficient classification method can be used for a sampling-based RBDO. The proposed virtual support vector machine (VSVM), which is a classification method, is a support vector machine (SVM) with virtual samples. By introducing virtual samples, VSVM overcomes the deficiency in existing SVM that uses only classification information as their input. In this paper, the universal Kriging method is used to obtain locations of virtual samples to improve the accuracy of the limit state function for highly nonlinear problems. A sequential sampling strategy effectively inserts new samples near the limit state function. In sampling-based RBDO, Monte Carlo simulation (MCS) is used for the reliability analysis and probabilistic sensitivity analysis. Since SVM is an explicit classification method, unlike implicit methods, computational cost for evaluating a large number of MCS samples can be significantly reduced. Several efficiency strategies, such as the hyper-spherical local window for generation of the limit state function and the Transformations/Gibbs sampling method to generate uniform samples in the hyper-sphere, are also applied. Examples show that the proposed sampling-based RBDO using VSVM yields better efficiency in terms of the number of required samples and the computational cost for evaluating MCS samples while maintaining accuracy similar to that of sampling-based RBDO using the implicit dynamic Kriging (D-Kriging) method.
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Shen, Zhengshu, Gaurav Ameta, Jami J. Shah, and Joseph K. Davidson. "A Comparative Study of Tolerance Analysis Methods." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57699.

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This paper reviews four major methods for tolerance analysis and compares them. The methods discussed are (1) 1D tolerance charts, (2) variational analysis based on Monte Carlo simulation, (3) vector loop (or kinematic) based analysis, and (4) ASU T-Maps© based tolerance analysis. Tolerance charts deal with tolerance analysis in one direction at a time and ignore possible contributions from the other directions. Manual charting is tedious and error-prone, hence attempts have been made for automation. Monte Carlo simulation based tolerance analysis is based on parametric solid modeling; its inherent drawback is that simulation results highly depend on the user-defined modeling scheme, and its inability to obey all Y14.5 rules. The vector loop method uses kinematic joints to model assembly constraints. It is also not fully consistent with Y14.5 standard. ASU T-Maps based tolerance analysis method can model geometric tolerances and their interaction in truly 3-dimensional context. It is completely consistent with Y14.5 standard but its use by designers may be quite challenging. T-Maps based tolerance analysis is still under development. Despite the shortcomings of each of these tolerance analysis methods, each may be used to provide reasonable results under certain circumstances. No guidelines exist for such a purpose. Through a comprehensive comparison of these methods, this paper will develop some guidelines for selecting the best method to use for a given tolerance accumulation problem.
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Zimmerman, David C., and Timothy T. Cao. "Effects of Noise on Measured Ritz Vectors." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-4230.

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Abstract Ritz vectors offer many advantages over the traditional mode shapes in the areas of model reduction and structural dynamic simulation. Building upon the recent development of an experimental method to extract Ritz vectors from measured dynamic response data, these vectors were also demonstrated to offer great potential in the areas of finite element model correlation and structural damage detection. In this paper, a Monte Carlo simulation is performed to study the accuracy and stability of Ritz vectors extracted from this new procedure using noise corrupted response data. The statistical variation of Ritz parameters and modal parameters extracted from the same data is made to assess the sensitivity of Ritz vector extraction to measured noise.
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