Highly-simplified models of walking and running can show passive dynamic (i.e. mechanical) stability[1-2]. Although these models capture many important aspects of locomotor dynamics, the extent to which they can describe the stability properties of human locomotion is still unclear. Human locomotion involves coordinating many degrees of freedom (DOFs), which are coupled (mechanically, kinematic...

It is extremely important for manufacturing industries to reduce their design process period in order to keep a competitive position in worldwide markets. CAE has been and will have an even more important role in shortening the design process. To effectively use CAE as a part of the design process, the ability of doing analysis in an affordable way, using large-scale real life problems is commo...

This report describes the kinematic and dynamic modeling of a hexapod robot. The 6-DOF (degrees of freedom) analytical kinematic and dynamic equations of motion are derived following the classical Newtonian mechanics. Under certain task-specific assumption, it is shown that the complex 6-DOF model can be simplified, resulting in an abstract model. Specifically, the motion of the robot on the ho...

Computational fluid dynamics (CFD) flow simulations are extremely expensive in terms of CPU time and memory. In this study, parallel computing and grid adaptation techniques are employed to achieve high efficiency and accuracy in a hybrid unstructured flow solver. However, adaptive local grid refinement/coarsening causes the unequal distribution of workload among the processors at run time. A s...

A Recurrent Trainable Neural Network (RTNN) with a two layer canonical architecture and a dynamic Backpropagation learning method are applied for local identification and local control of complex nonlinear plants. The RTNN model is incorporated in Hierarchical Fuzzy-Neural Multi-Model (HFNMM) architecture, combining the fuzzy model flexibility with the learning abilities of the RTNNs. A direct ...

Risk-averse mixed-integer multi-stage stochastic programming forms a class of extremely challenging problems since the problem size grows exponentially with the number of stages, the problem is non-convex due to integrality restrictions and the objective function is a dynamic measure of risk. For this reason, we propose a scenario tree decomposition approach, namely group subproblem approach, t...

In this paper, we investigate the problem of robust dynamic parameter-dependent output feedback (RDP-DOF) stabilization underH∞ performance index for a class of linear time invariant parameter-dependent (LTIPD) systems with multi-time delays in the state vector and in the presence of normbounded non-linear uncertainties. Using Hamiltonian–Jacobi–Isaac (HJI) method and the idea of polynomial par...

Analysis of the dynamic response ships in accident scenarios requires a realistic idealisation environmental and operational conditions by multi-physics models. This paper presents procedure that simulates influence strongly coupled FSI effects on involved typical collision grounding events. Our method couples an explicit 6-DoF structural finite element scheme with hydrodynamic accounting for (...