Engineering Commons^™

Turbine Passage Design Methodology To Minimize Entropy Production-A Two-Step Optimization Strategy, Paht Juangphanich, Cis De Maesschalck, Guillermo Paniagua

School of Aeronautics and Astronautics Faculty Publications

Rapid aerodynamic design and optimization is essential for the development of future turbomachinery. The objective of this work is to demonstrate a methodology from 1D mean-line-design to a full 3D aerodynamic optimization of the turbine stage using a parameterization strategy that requires few parameters. The methodology is tested by designing a highly loaded and efficient turbine for the Purdue Experimental Turbine Aerothermal Laboratory. This manuscript describes the entire design process including the 2D/3D parameterization strategy in detail. The objective of the design is to maximize the entropy definition of efficiency while simultaneously maximizing the stage loading. Optimal design trends are …

Breakage Modeling Of Needle-Shaped Particles Using The Discrete Element Method, Rohit Kumar, William Ketterhagen, Avik Sarkar, Jennifer S. Curtis, Carl Wassgren

School of Mechanical Engineering Faculty Publications

This paper models the breakage of large aspect ratio particles in an attrition cell using discrete element method (DEM) and population balance (PB) models. The particles are modeled in DEM as sphero-cylinders. The stresses within each particle are calculated along the particle length using beam theory and the particle breaks into two parts if the stress exceeds a critical value. Thus, the size distribution changes with time within the DEM model. The DEM model is validated against previously published experimental data.

The simulations demonstrate that particle breakage occurs primarily in front of the attrition cell blades, with the breakage rate …

Improving Human-Machine Collaboration Through Transparency-Based Feedback – Part I: Human Trust And Workload Model, Kumar Akash, Katelyn Polson, Neera Jain

School of Mechanical Engineering Faculty Publications

In this paper, we establish a partially observable Markov decision process(POMDP) model framework that captures dynamic changes in human trust and workload for contexts that involve interactions between humans and intelligent decision-aid systems. We use a reconnaissance mission study to elicit a dynamic change in human trust and workload with respect to the system’s reliability and user interface transparency as well as the presence or absence of danger. We use human subject data to estimate transition and observation probabilities of the POMDP model and analyze the trust-workload behavior of humans. Our results indicate that higher transparency is more likely to …

Improving Human-Machine Collaboration Through Transparency-Based Feedback – Part Ii: Control Design And Synthesis, Kumar Akash, Tahira Reid, Neera Jain

School of Mechanical Engineering Faculty Publications

To attain improved human-machine collaboration, it is necessary for autonomous systems to infer human trust and workload and respond accordingly. In turn, autonomous systems require models that capture both human trust and workload dynamics. In a companion paper, we developed a trust-workload partially observable Markov decision process (POMDP) model framework that captured changes in human trust and workload for contexts that involve interaction between a human and an intelligent decision-aid system. In this paper, we defne intuitive reward functions and show that these can be readily transformed for integration with the proposed POMDP model. We synthesize a near-optimal control policy …