Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

Application of micropolar plasticity to post failure analysis in geomechanics

A micropolar elastoplastic model for soils is formulated and a series of finite element analyses are employed to demonstrate the use of a micropolar continuum in overcoming the numerical difficulties encountered in application of finite element method in standard Cauchy–Boltzmann continuum. Three examples of failure analysis involving a deep excavation, shallow foundation, and a retaining wall are presented. In all these cases, it is observed that the length scale introduced in the polar continuum regularizes the incremental boundary value problem and allows the numerical simulation to be continued until a clear collapse mechanism is achieved. The issue of grain size effect is also discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

An explicit representation of steady state response of a beam on an elastic foundation to moving harmonic line loads

A closed‐form deflection response of a beam rest is presented in this paper using the integral transform method. The theory of linear partial differential equations is used to represent the deflection of beam subjected to a moving harmonic line load in integration form. The solution is finally carried out using the inverse Fourier transform. To evaluate the integration analytically, poles of the integrand are identified with the help of algebraic equation theory. Residue theorem is then utilized to represent the integration as a contour integral in the complex plane. Closed‐form deflections and numerical results are provided for different combinations of load frequency and velocity. Copyright © 2002 John Wiley & Sons, Ltd.     

Atmospheric radiative transfer simulation for atmospheric correction of remote sensing data

IntroductionThe radiance leaving the earth-atmosphere sys-tem which can be sensed by a satellite borne ra-diometer is the sum of radiation emission fromtheearth surface and each atmospheric level that aretransmittedtothe top of the atmosphere.The radia-tion emissionfromthe earthsurface andthe radianceof each atmospheric level can be separated fromtheradiance at the top the atmospheric level a satellitemeasured.Thus,the earth surface parameters willbe retrieved from the surface radiance after a…     

应用ATA的对数周期馈源方案于FAST的可能性探讨

介绍应用于美国凤凰计划的Allen望远镜阵(ATA)的对数周期馈源(LPA)概况，初步给出此种馈源的基本参数及性能，仿真估算了其驻波比和方向图，并结合正在进行中的我国500m孔径球面射电望远镜(FAST)计划，探讨了应用这种宽带馈源的可能性及其限制。     

A qualitative and quantitative evaluation of experimental model catchment evolution

Due to the geological time scales required for observation of catchment evolution, surrogates or analogues of field data are necessary to understand long‐term processes. To investigate long‐term catchment behaviour, two experimental model catchments that developed without rigid boundaries under controlled conditions are examined and a qualitative and quantitative analysis of their evolution is presented. Qualitatively, the experimental catchments have the visual appearance of field scale data. Observation demonstrates that changes in catchment shape and network form are conservative. Quantitative analysis suggests that the catchments reach an equilibrium form while a reduction in the channel network occurs. While the catchments are laboratory scale models, the results provide insights into field scale behaviour. Copyright © 2003 John Wiley & Sons, Ltd.     

THE CHARACTERISTIC OF MARINE ENVIRONMENT IN LINGDINGYANG ESTUARY

1 HYDROLOGIC FEATURES Lingdingyang Estuary, located at the middle south of Guangdong Province, is a bell-shaped estuary with a north-south direction. Its area is about 2100km2. The north of Qi′ao Island and Inner-Lingding Island, and the south of Humen are grouped as Neilingdingyang Estuary, having an area of 1041km2. Affected by topography, runoff and tide, its dynamic condition is very complicated. Different water areas have different hydrologic features. The topography under …     

THE SIMULATED STORAGE CAPACITY OF FLOOD AND WATERLOGGING IN THE TYPICAL AGRICULTURAL REGION IN JIANGHAN PLAIN

１ＩＮＴＲＯＤＵＣＴＩＯＮＪｉａｎｇｈａｎＰｌａｉｎｉｓｏｎｅｏｆｔｈｅｉｍｐｏｒｔａｎｔｂａｓｅｓｏｆＣｈｉｎａ′ｓａｇｒｉｃｕｌｔｕｒａｌｐｒｏｄｕｃｔｉｖｉｔｙｌｏｃａｔｅｄｉｎｔｈｅｍｉｄｄｌｅＣｈａｎｇｊｉａｎｇＲｉｖｅｒｖａｌｌｅｙｏｆｃｅｎｔｒａｌＣｈｉｎａ．ＴｈｅＪｉａｎｇｈａｎｐｌａｉｎａｐｐｒｏｘｉｍａｔｅｌｙ６．６×１０４ｋｍ２ｉｎａｒｅａａｎｄｏｖｅｒ３０ｍｉｌｌｉｏｎｉｎｐｏｐｕｌａｔｉｏｎｉｓｔｈｅｒｅｎｏｗｎｅｄ“ｃｏｕｎｔｒｙｏｆｆｉｓｈａｎｄｒｉｃｅ＂ｉｎ…     

重力插值方法研究

为了根据离散观测数据构制连续空间重力变化图像，分析和讨论了３种数值插值方法，计算结果表明多面函数方法插值精度最高。由于逐步回归分析筛选核函数中心点的计算繁琐，文中提出根据分形理论和Ｓｈａｎｎｏｎ取样定理来确定核函数中心点。对滇西试验场进行模拟试算，插值精度可达到４～５（１０－８ｍｓ－２）。