scholarly journals Modeling of Hypervelocity Impact Experiments Using Gamma-SPH Technique

2017 ◽  
Author(s):  
Jérôme Limido ◽  
Mohamed Trabia ◽  
Shawoon Roy ◽  
Brendan O’Toole ◽  
Richard Jennings ◽  
...  
Keyword(s):  
Computation Time ◽  
3D Models ◽  
Hypervelocity Impact ◽  
Side Impact ◽  
Particle Methods ◽  
Computational Time ◽  
Back Surface ◽  
Tensile Instability ◽  
Particle Hydrodynamics ◽  
And Performance

A series of experiments were performed to study plastic deformation of metallic plates under hypervelocity impact at the University of Nevada, Las Vegas (UNLV) Center for Materials and Structures using a two-stage light gas gun. In these experiments, cylindrical Lexan projectiles were fired at A36 steel target plates with velocities range of 4.5–6.0 km/s. Experiments were designed to produce a front side impact crater and a permanent bulging deformation on the back surface of the target without inducing complete perforation of the plates. Free surface velocities from the back surface of target plate were measured using the newly developed Multiplexed Photonic Doppler Velocimetry (MPDV) system. To simulate the experiments, a Lagrangian-based smooth particle hydrodynamics (SPH) is typically used to avoid the problems associated with mesh instability. Despite their intrinsic capability for simulation of violent impacts, particle methods have a few drawbacks that may considerably affect their accuracy and performance including, lack of interpolation completeness, tensile instability, and existence of spurious pressure. Moreover, computational time is also a strong limitation that often necessitates the use of reduced 2D axisymmetric models. To address these shortcomings, IMPETUS Afea Solver® implemented a newly developed SPH formulation that can solve the problems regarding spurious pressures and tensile instability. The algorithm takes full advantage of GPU Technology for parallelization of the computation and opens the door for running large 3D models (20,000,000 particles). The combination of accurate algorithms and drastically reduced computation time now makes it possible to run a high fidelity hypervelocity impact model.

scholarly journals A Hybrid Greedy Algorithm and Simulated Annealing for Single Container Loading Problem: A Case Study

2019 ◽  
Vol 20 (2) ◽  
pp. 89
Author(s):  
Gede A Widyadana ◽  
Audrey Tedja Widjaja ◽  
Kun Jen Wang
Keyword(s):  
Greedy Algorithm ◽  
Three Dimensional ◽  
Computation Time ◽  
Computational Time ◽  
Container Loading ◽  
Flexible Packaging ◽  
Loading Problem ◽  
And Performance ◽  
Container Loading Problem

A single container loading problem is a problem to effectively load boxes in a three-dimensional container. There are many researchers in this problem try to find the best solution to solve the problem with feasible computation time and to develop some models to solve real case problem. Heuristics are the most method used to solve this problem since the problem is an NP-hard. In this paper, we introduce a hybrid greedy algorithm and simulate annealing algorithm to solve a real container loading problem in one flexible packaging company in Indonesia. Validation is used to show that the method can be applied practically. We use seven real cases to check the validity and performance of the model. The proposed method outperformed the solution developed by the company in all seven cases with feasible computational time.

scholarly journals Quadric SFDI for Laplacian Discretisation in Lagrangian Meshless Methods

2020 ◽  
Vol 19 (3) ◽  
pp. 362-380
Author(s):  
Shiqiang Yan ◽  
Q. W. Ma ◽  
Jinghua Wang
Keyword(s):  
Finite Difference ◽  
Least Square Method ◽  
Least Square ◽  
Particle Methods ◽  
Computational Time ◽  
Initial State ◽  
Patch Tests ◽  
Moving Least Square ◽  
Particle Hydrodynamics ◽  
Convergent Rate

Abstract In the Lagrangian meshless (particle) methods, such as the smoothed particle hydrodynamics (SPH), moving particle semi-implicit (MPS) method and meshless local Petrov-Galerkin method based on Rankine source solution (MLPG_R), the Laplacian discretisation is often required in order to solve the governing equations and/or estimate physical quantities (such as the viscous stresses). In some meshless applications, the Laplacians are also needed as stabilisation operators to enhance the pressure calculation. The particles in the Lagrangian methods move following the material velocity, yielding a disordered (random) particle distribution even though they may be distributed uniformly in the initial state. Different schemes have been developed for a direct estimation of second derivatives using finite difference, kernel integrations and weighted/moving least square method. Some of the schemes suffer from a poor convergent rate. Some have a better convergent rate but require inversions of high order matrices, yielding high computational costs. This paper presents a quadric semi-analytical finite-difference interpolation (QSFDI) scheme, which can achieve the same degree of the convergent rate as the best schemes available to date but requires the inversion of significant lower-order matrices, i.e. 3 × 3 for 3D cases, compared with 6 × 6 or 10 × 10 in the schemes with the best convergent rate. Systematic patch tests have been carried out for either estimating the Laplacian of given functions or solving Poisson’s equations. The convergence, accuracy and robustness of the present schemes are compared with the existing schemes. It will show that the present scheme requires considerably less computational time to achieve the same accuracy as the best schemes available in literatures, particularly for estimating the Laplacian of given functions.

Automatic Parametric Modeling From Non-Feature Based Designs for Additive Manufacturing

2021 ◽  
Author(s):  
Xinyi Xiao ◽  
Byeong-Min Roh
Keyword(s):  
Additive Manufacturing ◽  
3D Models ◽  
Parametric Modeling ◽  
Parametric Models ◽  
Performance Simulation ◽  
Cad Modeling ◽  
3D Cad ◽  
Feature Based ◽  
And Performance ◽  
The Given

Abstract The integration of Topology optimization (TO) and Generative Design (GD) with additive manufacturing (AM) is becoming advent methods to lightweight parts while maintaining performance under the same loading conditions. However, these models from TO or GD are not in a form that they can be easily edited in a 3D CAD modeling system. These geometries are generally in a form with no surface/plane information, thus having non-editable features. Direct fabricate these non-feature-based designs and their inherent characteristics would lead to non-desired part qualities in terms of shape, GD&T, and mechanical properties. Current commercial software always requires a significant amount of manual work by experienced CAD users to generate a feature-based CAD model from non-feature-based designs for AM and performance simulation. This paper presents fully automated shaping algorithms for building parametric feature-based 3D models from non-feature-based designs for AM. Starting from automatically decomposing the given geometry into “formable” volumes, which is defined as a sweeping feature in the CAD modeling system, each decomposed volume will be described with 2D profiles and sweeping directions for modeling. The Boolean of modeled components will be the final parametric shape. The volumetric difference between the final parametric form and the original geometry is also provided to prove the effectiveness and efficiency of this automatic shaping methodology. Besides, the performance of the parametric models is being simulated to testify the functionality.

Methodology Development for Simulating Full Frontal and Offset Frontal Impacts Using Full Vehicle MADYMO Models

1999 ◽  
Author(s):  
Bala Deshpande ◽  
Gunasekar TJ ◽  
Russell Morris ◽  
Sudhanshu Parida ◽  
Mostafa Rashidy ◽  
...  
Keyword(s):  
Rigid Body ◽  
Joint Stiffness ◽  
Side Impact ◽  
Computational Time ◽  
Test Results ◽  
Vehicle Interior ◽  
Significant Saving ◽  
Methodology Development ◽  
Full Vehicle ◽  
Frontal Impacts

Abstract MADYMO articulated full vehicle models of the 1992 Ford Taurus, 1995 Chevrolet Lumina and the 1994 Dodge Intrepid for frontal and side impact modes have been developed and validated against test data. MADYMO (Mathematical Dynamic Model) is typically used to model occupants in the environment of the vehicle interior and thus finds application mainly in assessing occupant injuries. In this study however, MADYMO has been employed not only to model the occupants but also to represent the major load bearing structures in the vehicles. Input for the MADYMO models consisting of rigid body joint stiffness was obtained from corresponding full vehicle Finite Element (FE) models. Model validation was done by comparing the vehicle and dummy numbers with the New Car Assessment Program (NCAP) test results. Models correlated very well with both test and FE data. This modeling approach demonstrates the utility of rigid body based full car models for crashworthiness analysis. Such models result in significant saving in computational time and resources. In this paper, we describe the simulation of two different crash modes: full frontal and offset frontal impacts using the full vehicle MADYMO models. These simulations were validated with the corresponding test results in full frontal mode and IIHS offset mode. The models are useful for simulating a variety of impact situations, for example, with different occupant sizes, occupant positions, impact velocities, and in car to car impacts for performing compatibility studies.

Sign in / Sign up

Export Citation Format

Share Document