On three-dimensional SPH modelling of large-scale landslides

Lagrangian particle-based smoothed particle hydrodynamics (SPH) is increasingly widely used in landslide modelling. This paper investigates four important issues not addressed by previous studies on SPH modelling of large-scale landslides, i.e., convergence property, influence of constitutive parameters, scale effect and friction reduction, and influence of different treatments of the viscous effect. The GPU-acceleration technique is employed to achieve high-resolution three-dimensional (3D) modelling. The Baige landslide is investigated by comparing numerical results with field data, and detailed analyses on the four issues are provided. Suggestions on particle resolution, constitutive parameter, and formulations of viscous discretization are also presented for future SPH modelling of large-scale landslides.

A Neural Network Inverse Optimization Procedure for Constitutive Parameter Identification and Failure Mode Estimation of Laterally Loaded Unreinforced Masonry Walls

A new Neural Network Optimization (NNO) algorithm for constitutive material parameter identification based on inverse analysis of experimental tests of small-scale masonry prisms under compressive loads is presented. The Concrete Damaged Plasticity (CDP) constitutive model is used for the brick and mortar of the Unreinforced Masonry (URM) walls. By comparisons with experimental data taken from laboratory tests, it is demonstrated that the constitutive parameters calibrated by application of the proposed inverse optimization procedure on the small-scale (prism) experimental results are sufficiently accurate to allow for the prediction of the mechanical response of large-scale URM walls subject to compressive and lateral loads. This eliminates the need for large-scale URM wall experimental tests for the identification of their material properties, making the calibration process more economic. After verifying the accuracy of the calibrated constitutive parameters based on the above comparisons, a numerical parametric study is performed for the investigation of the effect of material behavior and geometrical aspect ratios on the failure mechanisms of large-scale URM walls.

Description of the Expansion of a Two-Layer Tube: An Analytic Plane-Strain Solution for Arbitrary Pressure-Independent Yield Criterion and Hardening Law

The main objective of the present paper is to provide a simple analytical solution for describing the expansion of a two-layer tube under plane-strain conditions for its subsequent use in the preliminary design of hydroforming processes. Each layer’s constitutive equations are an arbitrary pressure-independent yield criterion, its associated plastic flow rule, and an arbitrary hardening law. The elastic portion of strain is neglected. The method of solution is based on two transformations of space variables. Firstly, a Lagrangian coordinate is introduced instead of the Eulerian radial coordinate. Then, the Lagrangian coordinate is replaced with the equivalent strain. The solution reduces to ordinary integrals that, in general, should be evaluated numerically. However, for two hardening laws of practical importance, these integrals are expressed in terms of special functions. Three geometric parameters for the initial configuration, a constitutive parameter, and two arbitrary functions classify the boundary value problem. Therefore, a detailed parametric analysis of the solution is not feasible. The illustrative example demonstrates the effect of the outer layer’s thickness on the pressure applied to the inner radius of the tube.

Mechanical properties characterization of fiber reinforced composites by nonlinear constitutive parameter optimization in short beam shear specimens

This work presents a novel approach to quantify the nonlinear shear stress-strain behavior of carbon fiber reinforced polymer composites without finite element stress calculation. Full-field noncontact deformation measurements using Digital Image Correlation are used to measure surface strains in Short Beam Shear IM7/8552 specimens. The presented spline-based optimization technique solves the inverse problem of generating both axial and shear stress-strain curves without ad hoc assumptions on the material model. Accuracy of the analysis method was verified by finite element analysis (FEA). This method improves on available closed-form and iterative FEA based solutions due to flexibility and accuracy without the computational expense.

Constitutive Parameter Optimization Method of Obliquely Incident Reflectivity for Conformal PML

The conformal perfectly matched layer (PML), i.e., an efficient absorbing boundary condition, is commonly employed to address the open-field scattering problem of electromagnetic wave. To develope a conformal PML exhibiting a significant absorption effect and small reflection error, the present study proposes the constitutive parameter optimization method of obliquely incident reflectivity in terms of the conformal PML. First, the recurrence formula of obliquely incident reflectivity is desired. Subsequently, by the sensitivity analysis of constitutive parameters, the major optimal design variables are determined for the conformal PML. Lastly, with the reflectivity of the conformal PML as the optimization target, this study adopts the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to optimize the constitutive parameters of the conformal PML. As revealed from the results, the optimization method is capable of significantly reducing the reflection error and applying to the parameter design of conformal PML.

Optimized Polynomial Virtual Fields Method for Constitutive Parameters Identification of Orthotropic Bimaterials

Heterogeneous materials are widely applied in many fields. Owing to the spatial variation of its constitutive parameters, the mechanical characterization of heterogeneous materials is very important. The virtual fields method has been used to identify the constitutive parameters of materials. However, there is a limitation: constitutive parameters of one material have to be a priori; then, constitutive parameters of the other one can be identified. Aiming at this limitation, this article presents a method to identify the constitutive parameters of heterogeneous orthotropic bimaterials under the condition that constitutive parameters of both materials are all unknown from a single test. A constitutive parameter identification method of orthotropic bimaterials based on optimized virtual field and digital image correlation is proposed. The feasibility of this method is verified by simulating the deformation fields of a two-layer material under three-point bending load. The results of numerical experiments with FEM simulations show that the weighted relative error of the constitutive parameter is less than 1%. The results suggest that the variation coefficient-to-noise ratio can perform a priori evaluation of a confidence interval on the identified stiffness components. The results of numerical experiments with DIC simulations show that the weighted relative error is 1.44%, which is due to the noise in the strain data calculated by DIC method.

Stress-Softening in Particle-Filled Polyurethanes under Cyclic Compressive Loading

Elastomer compositions containing various particulate fillers can be formulated according to the specific functions required of them. Stress softening—which is also known as the Mullins effect—occurs during high loading and unloading paths in certain supramolecular elastomer materials. Previous experiments have revealed that the load–displacement response differs according to the filler used, demonstrating an unusual model of correspondence between the constitutive materials. Using a spherical indentation method and numerical simulation, we investigated the Mullins effect on polyurethane (PU) compositions subjected to cyclic uniaxial compressive load. The PU compositions comprised rigid particulate fillers (i.e., nano-silica and carbon black). The neo-Hooke model and the Ogden–Roxburgh Mullins model were used to describe the nonlinear deformation behavior of the soft materials. Based on finite element methods and parameter optimization, the load–displacement curves of various filled PUs were analyzed and fitted, enabling constitutive parameter prediction and inverse modeling. Hence, correspondence relationships between material components and constitutive parameters were established. Such relationships are instructive for the preparation of materials with specific properties. The method described herein is a more quantitative approach to the formulation of elastomer compositions comprising particulate fillers.