Xu Han

Bio: Xu Han is an academic researcher from Hebei University of Technology. The author has contributed to research in topics: Finite element method & Battery (electricity). The author has an hindex of 50, co-authored 248 publications receiving 7758 citations. Previous affiliations of Xu Han include National University of Singapore & Hunan University.

Computational Inverse Techniques in Nondestructive Evaluation

Abstract: INTRODUCTION Forward and Inverse Problems Encountered in Structural Systems General Procedures to Solve Inverse Problems Outline of the Book FUNDAMENTALS OF INVERSE PROBLEMS A Simple Example: A Single-Bar A Slightly Complex Problem: A Composite Bar Type III Ill-Posedness Types of Ill-Posed Inverse Problems Explicit Matrix Systems Inverse Solution for Systems with Matrix Form General Inversion by Singular Value Decomposition (SVD) Systems in Functional Forms: Solution by Optimization Choice of the Outputs or Effects Simulated Measurement Examination of Ill-Posedness REGULARIZATION FOR ILL-POSED PROBLEMS Tikhonov Regularization Regularization by SVD Iterative Regularization Method Regularization by Discretization (Projection) Regularization by Filtering CONVENTIONAL OPTIMIZATION TECHNIQUES1 The Role of Optimization in Inverse Problems Optimization Formulations Direct Search Gradient-Based Methods Nonlinear Least Squares Method Some References for Optimization Methods GENETIC ALGORITHMS Introduction Basic Concept of GAs Micro-GAs Intergeneration Project Genetic Algorithm (IP-GA) Improved IP-GA IP-GA with Three Parameters (IP3-GA) GAs with Search Space Reduction (SR-GA) GA Combined with the Gradient-Based Method Other Minor Tricks in the Implementation of GAs for Inverse Problems Some References for GA NEURAL NETWORKS General Concepts of Neural Networks Role of Neural Networks in Solving Inverse Problems Multilayer Perceptrons Performance of MLP A Progressive Learning Neural Network A Simple Application of NN References on Neural Networks INVERSE IDENTIFICATION OF IMPACT LOADS Introduction Displacement as System Effects Identification of Impact Loads on the Surface of Beams Line Loads on the Surface of Composite Laminates Point Loads on the Surface of Composite Laminates Ill-Posedness Analysis INVERSE IDENTIFICATION OF MATERIAL CONSTANTS OF COMPOSITES Introduction Statement of the Problem Using the Uniform mGA Using the Real mGA Using the Combined Optimization Method Using the Progressive NN for Identifying Elastic Constants INVERSE IDENTIFICATION OF MATERIAL PROPERTY OF FUNCTIONALLY GRADED MATERIALS Introduction Statement of the Problem Rule-of-Mixture Use of Gradient-Based Optimization Methods Use of Uniform mGA Use of Combined Optimization Method Use of Progressive NN Model INVERSE DETECTION OF CRACKS IN BEAMS USING FLEXURAL WAVES Introduction Beams with a Horizontal Delamination Beam Model of Flexural Wave Beam Model of for Transient Response to an Impact Load Extensive Experimental Study Inverse Crack Detection Using Uniform mGA Inverse Crack Detection Using Progressive NN INVERSE DETECTION OF DELAMINATIONS IN COMPOSITE LAMINATES Introduction Statement of the Problem Delamination Detection Using Uniform mGA Delamination Detection Using the IP-GA Delamination Detection Using the Improved IP-GA Delamination Detection Using the Combined Optimization Method Delamination Detection Using the Progressive NN INVERSE DETECTION OF FLAWS IN STRUCTURES Introduction Inverse Identification Formulation Use of Uniform mGA Use of Newton's Root Finding Method Use of Levenberg -Marquardt Method OTHER APPLICATIONS Coefficients Identification for Electronic Cooling System Identification of the Material Parameters of a PCB Identification of Material Property of Thin Films Crack Detection Using Integral Strain Measured by Optic Fibers Flaw Detection in Truss Structure Protein Structure Prediction Fitting of Interatomic Potentials Parameter Identification in Valve-Less Micropumps TOTAL SOLUTION FOR ENGINEERING SYSTEMS: A NEW CONCEPT Introduction Approach Towards a Total Solution Inverse Algorithms Numerical Examples

A linearly conforming point interpolation method (lc-pim) for 2d solid mechanics problems

Abstract: A linearly conforming point interpolation method (LC-PIM) is developed for 2D solid problems. In this method, shape functions are generated using the polynomial basis functions and a scheme for the selection of local supporting nodes based on background cells is suggested, which can always ensure the moment matrix is invertible as long as there are no coincide nodes. Galerkin weak form is adopted for creating discretized system equations, and a nodal integration scheme with strain smoothing operation is used to perform the numerical integration. The present LC-PIM can guarantee linear exactness and monotonic convergence for the numerical results. Numerical examples are used to examine the present method in terms of accuracy, convergence, and efficiency. Compared with the finite element method (FEM) using linear triangle elements and the radial point interpolation method (RPIM) using Gauss integration, the LC-PIM can achieve higher convergence rate and better efficiency.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Abstract: Smoothed particle hydrodynamics (SPH) is a meshfree particle method based on Lagrangian formulation, and has been widely applied to different areas in engineering and science. This paper presents an overview on the SPH method and its recent developments, including (1) the need for meshfree particle methods, and advantages of SPH, (2) approximation schemes of the conventional SPH method and numerical techniques for deriving SPH formulations for partial differential equations such as the Navier-Stokes (N-S) equations, (3) the role of the smoothing kernel functions and a general approach to construct smoothing kernel functions, (4) kernel and particle consistency for the SPH method, and approaches for restoring particle consistency, (5) several important numerical aspects, and (6) some recent applications of SPH. The paper ends with some concluding remarks.

Modeling and Analysis of Functionally Graded Materials and Structures

Abstract: This paper presents a review of the principal developments in functionally graded materials (FGMs) with an emphasis on the recent work published since 2000. Diverse areas relevant to various aspects of theory and applications of FGM are reflected in this paper. They include homogenization of particulate FGM, heat transfer issues, stress, stability and dynamic analyses, testing, manufacturing and design, applications, and fracture. The critical areas where further research is needed for a successful implementation of FGM in design are outlined in the conclusions. DOI: 10.1115/1.2777164

A Smoothed Finite Element Method for Mechanics Problems

Abstract: In the finite element method (FEM), a necessary condition for a four-node isoparametric element is that no interior angle is greater than 180° and the positivity of Jacobian determinant should be ensured in numerical implementation. In this paper, we incorporate cell-wise strain smoothing operations into conventional finite elements and propose the smoothed finite element method (SFEM) for 2D elastic problems. It is found that a quadrilateral element divided into four smoothing cells can avoid spurious modes and gives stable results for integration over the element. Compared with original FEM, the SFEM achieves more accurate results and generally higher convergence rate in energy without increasing computational cost. More importantly, as no mapping or coordinate transformation is involved in the SFEM, its element is allowed to be of arbitrary shape. Hence the restriction on the shape bilinear isoparametric elements can be removed and problem domain can be discretized in more flexible ways, as demonstrated in the example problems.