Discrete Element Modeling for the Development of a Real-Time Soil Model in a Virtual Reality Environment

摘要

Virtual Reality (VR) based methodology has important potential applications in engineering. Among the earliest engineering applications of VR are the advanced VR simulators with realistic force feedback in civilian and military aircraft design and in pilot training. Rapid advances in computer hardware, software and information technology now enable the use of VR environments with realistic force feedback for design and prototyping in a wide range of engineering fields. In the area of vehicle design, VR applications include testing for crashworthiness, ground-vehicle interaction and driver visibility. An important class of potential applications of VR environments with realistic force feedback is in machine-medium interaction problems. This class of problems includes the machine-medium interaction in heavy earthmoving equipment and off road vehicles. VR environments with realistic force feedback are potentially useful tool in the design cycle for new equipment. Early attempts in this field have had limited applications only in examining the issues of driver field of view. The primary difficulty in these early applications has been the lack of a realistic and real-time modeling of the medium-tool interaction. Realistic mechanic based models of granular materials have existed for a number of years. Discrete element method has been successfully used to model the flow of granular materials. The models are capable of correctly representing the mechanical behavior of masses of granular materials. However, these models cannot be used in virtual reality environments since they are computational very slow. We are proposing a new approach to this problem by using neural networks, The methodology is based on the premise that neural networks can learn to accurately describe the instantaneous motion of the particles in a mass of granular material. The methodology contain some DEM-based concepts and will be trained using data from DEM simulations.