arXiv: Computational Engineering, Finance, and Science最新文献

YIELD OPTIMIZATION BASED ON ADAPTIVE NEWTON-MONTE CARLO AND POLYNOMIAL SURROGATES 基于自适应牛顿-蒙特卡罗和多项式替代的成品率优化

arXiv: Computational Engineering, Finance, and Science Pub Date : 2020-10-11 DOI: 10.1615/int.j.uncertaintyquantification.2020033344

Mona Fuhrländer, Niklas Georg, U. Römer, S. Schöps

{"title":"YIELD OPTIMIZATION BASED ON ADAPTIVE NEWTON-MONTE CARLO AND POLYNOMIAL SURROGATES","authors":"Mona Fuhrländer, Niklas Georg, U. Römer, S. Schöps","doi":"10.1615/int.j.uncertaintyquantification.2020033344","DOIUrl":"https://doi.org/10.1615/int.j.uncertaintyquantification.2020033344","url":null,"abstract":"In this paper we present an algorithm for yield estimation and optimization exploiting Hessian based optimization methods, an adaptive Monte Carlo (MC) strategy, polynomial surrogates and several error indicators. Yield estimation is used to quantify the impact of uncertainty in a manufacturing process. Since computational efficiency is one main issue in uncertainty quantification, we propose a hybrid method, where a large part of a MC sample is evaluated with a surrogate model, and only a small subset of the sample is re-evaluated with a high fidelity finite element model. In order to determine this critical fraction of the sample, an adjoint error indicator is used for both the surrogate error and the finite element error. For yield optimization we propose an adaptive Newton-MC method. We reduce computational effort and control the MC error by adaptively increasing the sample size. The proposed method minimizes the impact of uncertainty by optimizing the yield. It allows to control the finite element error, surrogate error and MC error. At the same time it is much more efficient than standard MC approaches combined with standard Newton algorithms.","PeriodicalId":178066,"journal":{"name":"arXiv: Computational Engineering, Finance, and Science","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134493900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

ENHANCED ADAPTIVE SURROGATE MODELS WITH APPLICATIONS IN UNCERTAINTY QUANTIFICATION FOR NANOPLASMONICS 增强自适应代理模型及其在纳米等离子体不确定度定量中的应用

arXiv: Computational Engineering, Finance, and Science Pub Date : 2018-07-19 DOI: 10.1615/int.j.uncertaintyquantification.2020031727

Niklas Georg, Dimitrios Loukrezis, U. Römer, S. Schöps

引用次数: 6

On an implicit return-mapping operator in Mohr-Coulomb plasticity and its derivation via subdifferential theory 莫尔-库仑塑性中的隐式返回映射算子及其子微分理论推导

arXiv: Computational Engineering, Finance, and Science Pub Date : 2015-08-29 DOI: 10.1002/zamm.201600215

S. Sysala, M. Čermák

{"title":"On an implicit return-mapping operator in Mohr-Coulomb plasticity and its derivation via subdifferential theory","authors":"S. Sysala, M. Čermák","doi":"10.1002/zamm.201600215","DOIUrl":"https://doi.org/10.1002/zamm.201600215","url":null,"abstract":"The paper is devoted to the numerical solution of an elastoplastic constitutive initial value problem containing the Mohr-Coulomb yield criterion, a nonassociative plastic flow rule, and a nonlinear isotropic hardening. The constitutive problem is discretized by the implicit Euler method. Instead of the conventional Koiter formulations, we define the plastic flow rule using the subdifferential of the plastic potential to keep just one plastic multiplier and derive some formulas regardless a type of the return to the yield surface. This idea simplifies the solution scheme so that one can a priori decide about the return type even if the nonlinear hardening is introduced. Moreover, one can easily analyze the mathematical properties of the stress-strain operator and consequently simplify construction of the consistent tangent operator. These operators are used for solving the corresponding incremental boundary-value problem by the semismooth Newton method. The remaining part of the paper is focused on incremental limit analysis. The direct and also indirect controls of the loading process are considered and used in 2D and 3D numerical experiments on slope stability. The related Matlab codes are available.","PeriodicalId":178066,"journal":{"name":"arXiv: Computational Engineering, Finance, and Science","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116309477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

A Study of Speed of the Boundary Element Method as applied to the Realtime Computational Simulation of Biological Organs 边界元法在生物器官实时计算仿真中的应用研究

arXiv: Computational Engineering, Finance, and Science Pub Date : 2013-11-18 DOI: 10.14713/EJBE.V12I2.1841

K. Kumara

引用次数: 1

Preface - Proc. Wivace 2013 - Italian Workshop on Artificial Life and Evolutionary Computation 前言- Proc Wivace 2013 -人工生命和进化计算意大利研讨会

arXiv: Computational Engineering, Finance, and Science Pub Date : 2013-09-27 DOI: 10.4204/EPTCS.130

Alex Graudenzi, G. Caravagna, G. Mauri, M. Antoniotti

引用次数: 0

Algorithmic Data Analytics, Small Data Matters and Correlation versus Causation 算法数据分析，小数据问题和相关性与因果关系

arXiv: Computational Engineering, Finance, and Science Pub Date : 2013-09-05 DOI: 10.1007/978-3-658-12153-2_22

H. Zenil

引用次数: 21

Proceedings Fourth International Workshop on Computational Models for Cell Processes 第四届细胞过程计算模型国际研讨会论文集

arXiv: Computational Engineering, Finance, and Science Pub Date : 2011-09-06 DOI: 10.4204/EPTCS.67

I. Petre, E. D. Vink

引用次数: 1

An optimization strategy on prion AGAAAAGA amyloid fibril molecular modeling 朊病毒AGAAAAGA淀粉样纤维分子模型的优化策略

arXiv: Computational Engineering, Finance, and Science Pub Date : 2010-12-23 DOI: 10.2478/s11535-011-0088-7

Jiapu Zhang

{"title":"An optimization strategy on prion AGAAAAGA amyloid fibril molecular modeling","authors":"Jiapu Zhang","doi":"10.2478/s11535-011-0088-7","DOIUrl":"https://doi.org/10.2478/s11535-011-0088-7","url":null,"abstract":"X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy are two powerful tools to determine the protein 3D structure. However, not all proteins can be successfully crystallized, particularly for membrane proteins. Although NMR spectroscopy is indeed very powerful in determining the 3D structures of membrane proteins, same as X-ray crystallography, it is still very time-consuming and expensive. Under many circumstances, due to the noncrystalline and insoluble nature of some proteins, X-ray and NMR cannot be used at all. Computational approaches, however, allow us to obtain a description of the protein 3D structure at a submicroscopic level. \u0000To the best of the author's knowledge, there is little structural data available to date on the AGAAAAGA palindrome in the hydrophobic region (113--120) of prion proteins, which falls just within the N-terminal unstructured region (1--123) of prion proteins. Many experimental studies have shown that the AGAAAAGA region has amyloid fibril forming properties and plays an important role in prion diseases. However, due to the noncrystalline and insoluble nature of the amyloid fibril, little structural data on the AGAAAAGA is available. This paper introduces a simple optimization strategy approach to address the 3D atomic-resolution structure of prion AGAAAAGA amyloid fibrils. Atomic-resolution structures of prion AGAAAAGA amyloid fibrils got in this paper are useful for the drive to find treatments for prion diseases in the field of medicinal chemistry.","PeriodicalId":178066,"journal":{"name":"arXiv: Computational Engineering, Finance, and Science","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121046921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Opportunity Cost Algorithms for Combinatorial Auctions 组合拍卖的机会成本算法

arXiv: Computational Engineering, Finance, and Science Pub Date : 2000-09-19 DOI: 10.1007/978-1-4757-3613-7_23

Akcoglu Karhan, A. James, D. Bhaskar, Ming-Yang

引用次数: 45