Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Adaptive Sampling Trust-Region Methods For Derivative-Based And Derivative-Free Simulation Optimization Problems, Sara Shashaani
Adaptive Sampling Trust-Region Methods For Derivative-Based And Derivative-Free Simulation Optimization Problems, Sara Shashaani
Open Access Dissertations
We consider unconstrained optimization problems where only “stochastic” estimates of the objective function are observable as replicates from a Monte Carlo simulation oracle. In the first study we assume that the function gradients are directly observable through the Monte Carlo simulation. We propose ASTRO, which is an adaptive sampling based trust-region optimization method where a stochastic local model is constructed, optimized, and updated iteratively. ASTRO is a derivative-based algorithm and provides almost sure convergence to a first-order critical point with good practical performance. In the second study the Monte Carlo simulation is assumed to provide no direct observations of the …
Investigation Of Digital Pump/Motor Control Strategies, Farid El Breidi
Investigation Of Digital Pump/Motor Control Strategies, Farid El Breidi
Open Access Dissertations
A pump is the heart of fluid power systems, it has a significant impact on the efficiency of many fluid power systems. Motors are the most common rotary actuators in fluid power systems. State-of-the-art pump/motor units can achieve efficiencies higher than 90% when operating at maximum displacement; however, as the displacement drops, the efficiency of these units drops to below 50%. A new digital pump/motor design aims at increasing these efficiencies by utilizing two electrically controlled high speed on/off valves per displacement chamber; these valves provide the ability to achieve variable displacement and allow freedom in choosing operating strategies. Such …