Virtual Reality Interactive Design Utilizing Meshless Stress Re-Analysis

Interactive design gives engineers the ability to modify the shape of a part and immediately see the changes in the part’s stress state. Virtual reality techniques are utilized to make the process more intuitive and collaborative. The results of a meshless stress analysis are superimposed on the original design. As the engineer modifies the design using subdivision volume free-form deformation, the stress state for the modified design is computed using a Taylor series approximation. When the designer requests a more accurate analysis, a stress re-analysis technique based on the pre-conditioned conjugate gradient method is used with parallel processing to quickly compute an accurate approximation of the stresses for the new design

Distributed Virtual Reality Simulation Assisted Steering Controller Design for Off Road Vehicle and Implement Tracking

For virtual reality simulation of off--road vehicles, real--time simulation must be achieved in spite of the heavy computational load from 3D graphics generation and numerical analysis of the dynamic model. In this work, a distributed architecture was developed for off--road vehicle and implement dynamic model and 3D graphics visualization to distribute the overall computational load of the system across two or more machines. This architecture consists of three major components: a dynamic model simulator, a virtual reality simulator for 3D graphics, and an interface to the controller hardware elements. Several off--road vehicle dynamics models have been developed with varying degrees of fidelity, as well as automatic guidance controller models and an interface to automatic guidance hardware. A towed implement model and an implement tracking steering controller developed. The performance of an implement position and heading feedback controller was similar to that of a tractor position and heading feedback controller. These models provide understanding into the behavior of automatically guided tractor--implement systems. In addition, the simulation and visualization system was effectively used to examine the practical limitations that the designed controller may face and to design the controller gains to adjust for those limitations

Modeling, identification and analysis of tractor and single axle towed implement system

Increased and sustained agricultural productivity is a key to meet the globally increasing demands for food and energy. Automation of agricultural machinery is one of the ways to improve the efficiency and productivity of various field operations. Because a field implement performs most of these operations, accurate implement guidance is needed to reduce production cost, increase yield, and improve sustainability. Model-based guidance controller design and virtual prototyping techniques can be used in automatic guidance controller development to improve the accuracy and robustness of the guidance controller while reducing the development time and cost. Hence, development and analysis of accurate tractor and implement system models are needed to support automatic tractor and implement guidance controller development. Real-time vehicle model simulation capability allows engineers and users to intuitively interact with the realistic virtual prototypes and to evaluate the performance of physical hardware. As the model complexity is increased to improve the model accuracy and/or fidelity, the computational need will also increases thus increasing the challenge to meet real-time constraints. In this regard, it is important to minimize the computational load to a Virtual Reality (VR)-based real-time dynamics model simulation system. In this dissertation, various strategies were investigated to reduce the computational burden on the dynamics model simulation so that real-time simulation could be achieved for increasingly complex models. A distributed architecture was developed for a virtual reality-based off-road vehicle real-time simulator to distribute the overall computational load of the system across multiple machines. Multi-rate model simulation was also used to simulate various system dynamics with different integration time steps so that the computational power can be distributed more intelligently. It is also important to study the trade-off between the model accuracy/fidelity and model complexity. Three different tractor-and-single-axle-towed-implement system models with varying degrees of fidelity, namely a kinematic model, a dynamic model, and a dynamic model with tire relaxation length, were developed, and the simulated transient and steady state responses were compared at various forward velocities and input frequencies. Both open and closed loop system characteristics were studied. Field experiments were also carried out to characterize the input-output relationship of the tractor-implement steering system. The responses from all three models were similar at lower forward velocities and with low frequency steering inputs (\u3c 0.2 Hz). However, when the system was operated at higher forward velocities or with higher frequency steering inputs, the responses from the three models varied substantially. In this case, the dynamic model with tire relaxation length best represented the experimental system responses. The system model contained various uncertain or varying parameters. It was important to understand and quantify the effect of parameter variation on system responses. Sensitivity analysis was used to identify the effect of variation in tire cornering stiffness, tire relaxation length, and implement inertial parameters on simulated system responses. Overall, the system was most sensitive to the tire cornering stiffness and least sensitive to the implement inertial parameters. In general, the uncertainty in the input parameters and the output variables were related in a non-linear fashion. At 4.5 m/s forward velocity, a 10% uncertainty in cornering stiffness caused a 2% average output uncertainty whereas a 50% uncertainty in cornering stiffness caused a 20% output uncertainty. Finally, a parameter identification method was used to estimate the uncertain model parameters from measured field data. The accuracy of the model responses improved substantially when the model was simulated with the estimated parameters. It was concluded that a dynamic model with tire relaxation length will represent a tractor and single axle towed implement system with reasonable accuracy. The study also helped improve the understanding of the relative importance of various model parameters, which will help to more judiciously allocate resources for estimating system parameters. Moreover, the analysis indicated that various vehicle parameters can be estimated with reasonable accuracy using a dynamic model, experimental data, and a parameter estimation method. The work will provide a framework for off-road vehicle and implement simulation through which engineers and scientists can determine to which parameters the system is most sensitive and how a model would perform with estimated model parameters

Visual Analysis of In-Car Communication Networks

Analyzing, understanding and working with complex systems and large datasets has become a familiar challenge in the information era. The explosion of data worldwide affects nearly every part of society, particularly the science, engineering, health, and financial domains. Looking, for instance at the automotive industry, engineers are confronted with the enormously increased complexity of vehicle electronics. Over the years, a large number of advanced functions, such as ACC (adaptive cruise control), rear seat entertainment systems or automatic start/stop engines, has been integrated into the vehicle. Thereby, the functions have been more and more distributed over the vehicle, leading to the introduction of several communication networks. Overlooking all relevant data facets, understanding dependencies, analyzing the flow of messages and tracking down problems in these networks has become a major challenge for automotive engineers. Promising approaches to overcome information overload and to provide insight into complex data are Information Visualization (InfoVis) and Visual Analytics (VA). Over the last decades, these research communities spent much effort on developing new methods to help users obtain insight into complex data. However, few of these solutions have yet reached end users, and moving research into practice remains one of the great challenges in visual data analysis. This situation is particularly true for large company settings, where very little is known about additional challenges, obstacles and requirements in InfoVis/VA development and evaluation. Users have to be better integrated into our research processes in terms of adequate requirements analysis, understanding practices and challenges, developing well-directed, user-centered technologies and evaluating their value within a realistic context. This dissertation explores a novel InfoVis/VA application area, namely in-car communication networks, and demonstrates how information visualization methods and techniques can help engineers to work with and better understand these networks. Based on a three-year internship with a large automotive company and the close cooperation with domain experts, I grounded a profound understanding of specific challenges, requirements and obstacles for InfoVis/VA application in this area and learned that “designing with not for the people” is highly important for successful solutions. The three main contributions of this dissertation are: (1) An empirical analysis of current working practices of automotive engineers and the derivation of specific design requirements for InfoVis/VA tools; (2) the successful application and evaluation of nine prototypes, including the deployment of five systems; and (3) based on the three-year experience, a set of recommendations for developing and evaluating InfoVis systems in large company settings. I present ethnographic studies with more than 150 automotive engineers. These studies helped us to understand currently used tools, the underlying data, tasks as well as user groups and to categorize the field into application sub-domains. Based on these findings, we propose implications and recommendations for designing tools to support current practices of automotive network engineers with InfoVis/VA technologies. I also present nine InfoVis design studies that we built and evaluated with automotive domain experts and use them to systematically explore the design space of applying InfoVis to in-car communication networks. Each prototype was developed in a user-centered, participatory process, respectively with a focus on a specific sub-domain of target users with specific data and tasks. Experimental results from studies with real users are presented, that show that the visualization prototypes can improve the engineers’ work in terms of working efficiency, better understanding and novel insights. Based on lessons learned from repeatedly designing and evaluating our tools together with domain experts at a large automotive company, I discuss challenges and present recommendations for deploying and evaluating VA/InfoVis tools in large company settings. I hope that these recommendations can guide other InfoVis researchers and practitioners in similar projects by providing them with new insights, such as the necessity for close integration with current tools and given processes, distributed knowledge and high degree of specialization, and the importance of addressing prevailing mental models and time restrictions. In general, I think that large company settings are a promising and fruitful field for novel InfoVis applications and expect our recommendations to be useful tools for other researchers and tool designers