Publication

Modeling & Simulation, Testing & Validation (MSTV)
2010

Durability Analysis for Off-Road Vehicle Stowage Systems

by Nammalwar Purushothaman; James Critchley; Jessica Hulings; Amarendra Joshi

Abstract

Durability analysis as applied to high mobility off-road ground vehicles involves simulating the vehicle on rough terrains and cascading the loads throughout the structure to support the verification of various components. For components within the hull structure, the rigid body accelerations of the hull are transformed to the component location producing a prescribed g-load time history. This modeling method works extremely well for items which are bolted in place but is inappropriate for stowage systems such as boxes and shelves where cargo can experience intermittent contact and impacts. One solution is to create a dynamic contact nonlinear finite element model of the stowage solution with supported cargo and subject them to the same acceleration profile. This approach effectively resolves the stresses needed to perform fatigue evaluations but is a computationally and labor intensive process. The resources required for single design point verification cannot be justified for simple stowage elements, not to mention the possibility of design iteration. To address the need for rapid assessment of stowage systems, a simplified model is presented then tuned and validated relative to the finite element contact model. This model uses a set of particles to represent the stowed component and interacts with the stowage surface through an effective stiffness, allowing it to be thrown free of the surface and collide generating increased loads. All three approaches (transformed g-loads, FE contact, and particle approximation) are demonstrated with loose cargo in a stowage box. The three models demonstrate similar performance for mild excitations and more vigorous inputs result in larger loads from the two contact models. The load profiles generated by the particle approximation are demonstrated to be consistent with the variability of the overall durability process, justifying their use as an independent predictive tool.