University of Wisconsin
Recently I gave a presentation at the MSC VPD conference 2009 in Phoenix, Arizona about a class taught by Professor Dan Negrut at the University of Wisconsin - Madison. The class is called "Kinematic and Dynamics of Machine Systems", and the presentation was about using ADAMS/View and Adams/Solver to help teach and reinforce the usefulness of approaching dynamics problems in a way that allow them to be easily solved on a computer.
I took this class as an undergraduate at the UW three semesters ago, and have continued studying at UW as a graduate student under Prof. Negrut in the fields of multibody and structural dynamics simulation. ADAMS has been a tremendously helpful tool for myself and others who work in the lab (Simulation Based Engineering Lab, http://sbel.wisc.edu/). I have used it as a learning and research tool for many projects. Research projects include:
- A GAUSSIAN PROCESS BASED APPROACH FOR HANDLING UNCERTAINTY IN VEHICLE DYNAMICS SIMULATION
Kyle Schmitt was the lead author for this project, and I assisted with the ADAMS/Car simulations. The result was a conference paper which was presented at the 2008 ASME International Mechanical Engineering Congress and Exposition November 2-6, 2008, Boston, Massachusetts. Paper No. IMECE2008-66664.
Project description: Randomly distributed patches of ice arising naturally on roadways adversely affect a driver's ability to navigate a determined path; among the escalated risks in icy conditions are yaw instability (spinning out) and slippage from desired path. The anomalous and often unpredictable distribution of ice makes predictive results from traditional modeling methods inaccurate. In collaboration with Dr. Mihai Anitescu (Argonne National Lab), we employ Gaussian processes to form high fidelity, interpolative models of spatial friction coefficients from a limited data set (achievable with satellite imaging, sensors, or inter-vehicle communication). We work with a non-linear vehicle model on the ice models to a) quantify the effect of ice on a vehicle's trajectory and b) to identify high risk speeds and turn radii on surveyed roadways. Simulation methods, first developed and verified in MATLAB, are implemented in ADAMS/Car and results are compared. Further investigation into this problem will develop control methods robust to the stochastic nature of the conditions. Furthermore, the inverse problem of going from trajectory to friction values will be addressed. This capability would allow for inter-vehicle communication of road friction data in the era of onboard sensing and in turn would make our methodology of data interpolation more relevant.
- A Stochastic Approach to Integrated Vehicle Reliability Prediction
This is an ongoing research project in conjunction with industry and U.S. Army TARDEC. I created a physically realistic ADAMS/Car model of the U.S. Army's HMMWV using army technical report data. A co-simulation environment between ADAMS/Car and FTire was set up to a) be able to use a high-fidelity tire model, and b) to simulate extremely long lengths of roads. The road profiles, driver paths/speeds and suspension parameters were varied over a range of values to introduce uncertainty in the system. Hundreds of vehicle simulations were run in batches, and selected A/Car simulation results were sent to a colleague who used the dynamic loading data to run series of Finite-element analyses on the suspension subsystem to determine the reliability and life prediction of each road/driver/vehicle model combination.
The result of the first year of work has yielded a conference paper which will be presented at the ASME 2009 International Design Engineering Technical Conference, August 30 - September 2, 2009, San Diego, California. Paper No. DETC2009-87487
Project description: This project addresses some aspects of an on-going multiyear research project of GP Technologies in collaboration with University of Wisconsin-Madison for US Army TARDEC. The focus of this research project is to enhance the overall vehicle reliability prediction process. A combination of stochastic models for both the vehicle and operational environment are utilized to determine the range of the system dynamic response. These dynamic results are used as inputs into a finite element analysis of stresses on subsystem components. Finally, resulting stresses are used for damage modeling and life and reliability predictions. This paper describes few selected aspects of the new integrated ground vehicle reliability prediction approach. The integrated approach combines the computational stochastic mechanics predictions with available statistical experimental databases for assessing vehicle system reliability. Such an integrated reliability prediction approach represents an essential part of an intelligent virtual prototyping environment for ground vehicle design and testing. Note: There are nice animations available at http://sbel.wisc.edu/Animations/index.htm
- An ADAMS/Simulink Co-Simulation tool for P&H mining company.
Project Description: This project was a joint effort between myself and another student in the lab, Martin Tupy. The P&H mining company (Milwaukee, WI) was interested in using ADAMS to simulate their electric shovels, and wanted to compare the time it took for the shovel to complete a dig cycle using different types of motors. We used Solid modeling data provided by P&H to create a multibody model of the electric shovel in ADAMS/View, and Simulink to represent the motors and controls. ADAMS/Controls was used to link the two models, and we were able to successfully co-simulate the mining shovel.
Figure. 4100 XPC in ADAMS (left) and SolidWorks (right)
Figure. Simulink Model
Figure 1: Excavator Model in ADAMS/View
Justin Madsen, University of Wisconsin student