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Active steering systems can help the driver to master critical driving situations. This paper presents a fuzzy logic control strategy on active steering vehicle based on a multi-body vehicle dynamic model. The multi-body vehicle dynamic model using ADAMS can accurately predict the dynamic performance of the vehicle. A new hybrid steering scheme including both active front steering (applying an additional front steering angle besides the driver input) and rear steering is presented to control both yaw velocity and sideslip angle. A set of fuzzy logic rules is designed for the active steering controller, and the fuzzy controller can adjust both sideslip angle and yaw velocity through the co-simulation between ADAMS and the Matlab fuzzy control unit with the optimized membership function. To ensure the design of high-quality fuzzy control rules, a rule optimization strategy is introduced.

A general methodology and associated computational algorithm for predicting realistic postures of digital humans (mannequins) in a virtual environment is presented. The basic plot for this effort is a task-based approach, where we believe that humans assume different postures for different tasks. The underlying problem is characterized by the calculation (or prediction) of the joint displacements of the human body in such a way to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized subject to a number of constraints. The problem is formulated as a multi-objective optimization algorithm where one or more cost functions are considered as objective functions that drive the model to a solution.

This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks.

The slope discontinuity in C° contact formulation is known as the cause of iteration convergence difficulty in sliding contact. In this paper, a smooth contact surface representation is introduced to remove the slope discontinuity in a C° contact formulation. The non-uniqueness in the solution of closest point projection near the junction of C° surfaces is eliminated by this new approach. The smooth surface representation is incorporated into meshfree formulation to yield a consistent tangent operator for frictional contact problems. The proposed method is successfully applied to a sheet metal deep drawing problem involving large sliding contact and a sheet metal stamping problem.

Two mathematical models for the catalyst layer of a PEMFC, i.e. the macro-homogenous model and the agglomerate model are evaluated in this paper. The characteristics of both models and the application of both models to optimal design of catalyst layer are discussed. The one-dimensional governing equations of both models are solved analytically or numerically using the finite difference method. A simplified, analytic solution of the macro-homogenous model under ideal conditions is derived. Parametric study and sensitivity analyses are performed for the agglomerate model to identify the parameters that have significant influences on the performance of a PEMFC. Several parameters including the electrolyte thickness, porosity, oxygen permeability, and layer thickness are found to affect the limiting current significantly. A solid model is developed to visualize the structure of a catalyst layer. This solid model is used to estimate effective transport properties.

We propose an algorithm of predicting dynamic biped motions of Santos™ human model. An alternative and efficient formulation of the Zero-Moment Point (ZMP) for dynamic balance and the approximated ground reaction forces/moments are derived from the resultant reaction loads, which includes the gravity, the externally applied loads, and the inertia. The optimization problem is formulated to address the redundancy of the human task, where the general biped and the task-specific constraints are imposed depending on the task requirements. The proposed method is fully predictive and generates physically feasible human-like motions from scratch without any input reference from motion capture or animation. The resulting generated motions demonstrate how a human reacts effectively to different external load conditions in performing a given task by showing realistic features of cause and effect.