Browse Topic: Finite element analysis
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
Calibrated Accelerated Life Testing (CALT) is a sequential and quantitative method for Accelerated Life Testing (ALT). Its design aims to optimize test efficiency by minimizing both test duration and sample size while estimating product life. In the CALT context, the focus is on testing samples under three or more distinct stresses or loads to estimate the life span/BX life, which is a crucial parameter in reliability estimation. Determining the first load in CALT typically involves exploratory testing on a limited number of specimens and relies heavily on engineering judgments such as analyzing Finite Element Analysis (FEA) outcomes, referencing test data from comparable designs and materials, and considering stiffness results etc. This often leads to challenges in accurately identifying the first load/stress. To address this issue, we propose a systematic step-stress test approach instead of exploratory testing. This approach aims to efficiently identify the first load in CALT. The
ABSTRACT Conceptual design of automotive structures has received substantial research attention in recent years in order to speed up vehicle development and innovation. Although several structural optimization methods have been employed in concept design, there still exists lack of efficient design tools to produce initial design shapes with less problem dependency, less computation-intensive analysis and more design flexibility. In this paper, an innovative Computer Aided Engineering (CAE) approach based on an integrated Genetic Algorithms(GA) and Finite Element (FE) optimization system has been studied and implemented for efficient conceptual design of automotive suspension system related structural part. Integration of GA provides the method a great amount of design flexibility and robustness that increases possibility of finding more efficient and innovative design shapes of the structure
ABSTRACT FBS Inc. is working with the TARDEC Electrified Armor Lab to develop a nondestructive structural health monitoring technology for composite armor panels that utilizes an array of embedded ultrasonic sensors for guided wave tomographic imaging. This technology would allow for periodic or real-time monitoring of armor integrity while being minimally intrusive and adding negligible weight. The technology is currently being developed and tested in pseudo composite armor panels and efforts are focused on reducing sensor array density, improving sensor integration procedures, and maximizing system sensitivity to damage. In addition to experimental testing and development, FBS is developing a highly-automated finite element model generation and analysis program to be used in conjunction with Abaqus/Explicit commercial finite element software. This program is specifically dedicated to modeling guided wave propagation in pseudo composite armor panels between embedded ultrasonic sensors
ABSTRACT Researchers at Caterpillar have been using Finite Element Analysis or Method (FEA or FEM), Mesh Free Models (MFM) and Discrete Element Models (DEM) extensively to model different earthmoving operations. Multi-body dynamics models using both flexible and rigid body have been used to model the machine dynamics. The proper soil and machine models along with the operator model can be coupled to numerically model an earthmoving operation. The soil – machine interaction phenomenon has been a challenging matter for many researchers. Different approaches, such as FEA, MFM and DEM are available nowadays to model the dynamic soil behavior; each of these approaches has its own limitations and applications. To apply FEA, MFM or DEM for analyzing earthmoving operations the model must reproduce the mechanical behavior of the granular material. In practice this macro level mechanical behavior is not achieved by modeling the exact physics of the microfabric structure but rather by
Abstract: An idealized concept of a v-hull vehicle design for blast analysis has been studied in two different commercial software packages and results are compared to one another. The two software packages are different in nature: one code is an Eulerian Computational Fluid Dynamics (CFD) Finite Volume Solver while the other code is a Lagrangian Finite Element Analysis (FEA) Solver with the ability to couple structures to fluids through a special technique called Arbitrary Lagrangian Eulerian (ALE). The simulation models in this paper have been set up for both CFD and FEA using a commercial pre-processing tool to study the effect of an idealized blast on the vehicle configuration: A pressure blast charge has been placed under the center of the vehicle at the symmetry line. The charge is composed of a prescribed pressure and a temperature pulse in a medium with the properties of air. In the CFD solver, an explicit unsteady solver has been chosen for analysis purposes. This was done
ABSTRACT The modeling of a buried charge is a very complex engineering task since many Design Variables need to be considered. The variables in question are directly related to the method chosen to perform the analysis and the process modeled. In order to have a Predictive Tool two main objectives have to be carried out, the first is a verification of the numerical approach with experimental data, the second objective is a sensitivity study of the numerical and process parameters. The emphasis of the present study covers the second objective. To perform this task a comprehensive sensitivity study of fourteen Design Variables was completed which required 1000+ computational hours. The modeling approach that was chosen was the Discrete Particle Method (DPM) to model the Soil and HE and the Finite Element Method for the Structure. The basis for the study was a blast event applied to a model of the TARDEC Generic Vehicle Hull. The Response Parameter was chosen to be the Total Blast Impulse
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