首站-论文投稿智能助手
典型文献
A bayesian optimisation methodology for the inverse derivation of viscoplasticity model constants in high strain-rate simulations
文献摘要:
We present an inverse methodology for deriving viscoplasticity constitutive model parameters for use in explicit finite element simulations of dynamic processes using functional experiments,i.e.,those which provide value beyond that of constitutive model development.The developed methodology utilises Bayesian optimisation to minimise the error between experimental measurements and numerical sim-ulations performed in LS-DYNA.We demonstrate the optimisation methodology using high hardness armour steels across three types of experiments that induce a wide range of loading conditions:ballistic penetration,rod-on-anvil,and near-field blast deformation.By utilising such a broad range of conditions for the optimisation,the resulting constitutive model parameters are generalised,i.e.,applicable across the range of loading conditions encompassed the by those experiments(e.g.,stress states,plastic strain magnitudes,strain rates,etc.).Model constants identified using this methodology are demonstrated to provide a generalisable model with superior predictive accuracy than those derived from conventional mechanical characterisation experiments or optimised from a single experimental condition.
文献关键词:
作者姓名:
Shannon Ryan;Julian Berk;Santu Rana;Brodie McDonald;Svetha Venkatesh
作者机构:
Applied Artificial Intelligence Institute(A2I2),Deakin University,75 Pigdons Rd,Waurn Ponds,VIC,3216,Australia;Defence Science and Technology Group,506 Lorimer Street,Fishermans Bend,VIC,3207,Australia
文献出处:
引用格式:
[1]Shannon Ryan;Julian Berk;Santu Rana;Brodie McDonald;Svetha Venkatesh-.A bayesian optimisation methodology for the inverse derivation of viscoplasticity model constants in high strain-rate simulations)[J].防务技术,2022(09):1563-1577
A类:
viscoplasticity,utilises,armour,generalised,generalisable
B类:
bayesian,optimisation,methodology,inverse,derivation,model,constants,high,strain,simulations,We,present,deriving,constitutive,parameters,use,explicit,finite,element,dynamic,processes,using,functional,experiments,those,which,provide,value,beyond,that,development,developed,Bayesian,minimise,error,between,experimental,measurements,numerical,performed,LS,DYNA,hardness,steels,across,three,types,induce,wide,range,loading,conditions,ballistic,penetration,rod,anvil,near,field,blast,deformation,By,utilising,such,broad,resulting,are,applicable,encompassed,by,stress,states,magnitudes,rates,etc,Model,identified,this,demonstrated,superior,predictive,accuracy,than,derived,from,conventional,mechanical,characterisation,optimised,single
AB值:
0.563249
相似文献
Mechanical behavior and deformation mechanism of shape memory bulk metallic glass composites synthesized by powder metallurgy
Tianbing He;Tiwen Lu;Daniel ?opu;Xiaoliang Han;Haizhou Lu;Kornelius Nielsch;Jürgen Eckert;Nevaf Ciftci;Volker Uhlenwinkel;Konrad Kosiba;Sergio Scudino-Leibniz IFW Dresden,Institute for Complex Materials,Helmholtzstra?e 20,01069 Dresden,Germany;Guangdong Key Laboratory for Advanced Metallic Materials Processing,South China University of Technology,Guangzhou 510640,China;Erich Schmid Institute of Materials Science,Austrian Academy of Sciences,Jahnstra?e 12,Leoben A-8700,Austria;Leibniz IFW Dresden,Institute for Metallic Materials,Helmholtzstraf?e 20,01069 Dresden,Germany;TU Dresden,Institute of Materials Science,01062 Dresden,Germany;TU Dresden,Institute of Applied Physics,01062 Dresden,Germany;Department Materials Physics,Montanuniversitat Leoben,Jahnstra?e 12,A-8700 Leoben,Austria;Leibniz Institute for Materials Engineering IWT,28359 Bremen,Germany;University of Bremen,Faculty of Production Engineering,28359 Bremen,Germany
In situ neutron diffraction unravels deformation mechanisms of a strong and ductile FeCrNi medium entropy alloy
L.Tang;F.Q.Jiang;J.S.Wróbel;B.Liu;S.Kabra;R.X.Duan;J.H.Luan;Z.B.Jiao;M.M.Attallah;D.Nguyen-Manh;B.Cai-School of Metallurgy and Materials,University of Birmingham,B15 2TT,United Kingdom;Institute of Metal Research,Chinese Academy of Sciences,Shenyang 110016,China;Faculty of Materials Science and Engineering,Warsaw University of Technology,ul.Wo?oska 141,Warsaw 02-507,Poland;State Key Laboratory for Powder Metallurgy,Central South University,Changsha 410083,China;Rutherford Appleton Laboratory,ISIS Facility,Didcot OX11 0QX,United Kingdom;Department of Materials Science and Engineering,City University of Hong Kong,Kowloon,Hong Kong,China;Department of Mechanical Engineering,The Hong Kong Polytechnic University,Hung Hom,Hong Kong,China;CCFE,United Kingdom Atomic Energy Authority,Abingdon,Oxfordshire OX14 3DB,United Kingdom
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。