Computational Engineering Commons^™

Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka

Graduate Theses, Dissertations, and Problem Reports

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO₂ is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO₂ build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO₂ capture and use of hydrogen as a fuel for power generation. These two solutions can also …

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …

Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler

SMU Data Science Review

This study presents a novel approach to price optimization in order to maximize revenue for the distribution market of non-perishable products. Data analysis techniques such as association mining, statistical modeling, machine learning, and an automated machine learning platform are used to forecast the demand for products considering the impact of pricing. The techniques used allow for accurate modeling of the customer’s buying patterns including cross effects such as cannibalization and the halo effect. This study uses data from 2013 to 2019 for Super Premium Whiskey from a large distributor of alcoholic beverages. The expected demand and the ideal pricing strategy …

A Reduced Model For Microbial Electrolysis Cells, Dina Aboelela, Moustafa A. Soliman, Ibrahim Ashour

Chemical Engineering

Microbial electrolysis cells (MECs) are breakthrough technology of cheap hydrogen production with high efficiency. In this paper differential-algebraic equation (DAE) model of a MEC with an algebraic constraint on current was studied, simulated and validated by implementing the model on continuous-flow MECs. Then sensitivity analysis for the system was effectuated. Parameters which have the predominating influence on the current density and hydrogen production rate were defined. This sensitivity analysis was utilized in modeling and validation of the batch-cycle of MEC. After that parameters which have less influence on MEC were eliminated and simplified reduced model was obtained and validated. Finally, …

Toward A Fast And Accurate Modeling Strategy For Thermal Management In Air-Cooled Data Centers, Long Tran Bao Phan

FIU Electronic Theses and Dissertations

Computational fluid dynamics (CFD) has become a popular tool compared to experimental measurement for thermal management in data centers. However, it is very time-consuming and resource-intensive when used to model large-scale data centers, and may not be ready for real-time thermal monitoring. In this thesis, the two main goals are first to develop rapid flow simulation to reduce the computing time while maintaining good accuracy, and second, to develop a whole building energy simulation (BES) strategy for data center modeling. To achieve this end, hybrid modeling and model training methodologies are investigated for rapid flow simulation, and a multi-zone model …

Foundations For A Game Theoretic Framework For Agile Acquisition, Scott Rosen, Kelly Horinek, Alexander Odeh, Les Servi, Andreas Tolk

VMASC Publications

This article investigates the concept of developing a game theoretic framework that is based on the application of buyer and seller utility functions to support the bidding process in government acquisition. The results of a literature survey of utility function approaches, with potential to provide a suitable foundation to a game theory framework for acquisition, are presented. The utility function methods found most promising were further adapted and tested: the Best-Worst method, the Multi-Swing Method, and Functional Dependency for Network Analysis. To test the scalability of the approach, the Best-Worst method is applied to a larger problem to show the …

Optimizing The Distributed Hydrology Soil Vegetation Model For Uncertainty Assessment With Serial, Multicore And Distributed Accelerations, Andrew Adriance

Master's Theses

Hydrology is the study of water. Hydrology tracks various attributes of water such as its quality and movement. As a tool Hydrology allows researchers to investigate topics such as the impacts of wildfires, logging, and commercial development. With perfect and complete data collection researchers could answer these questions with complete certainty. However, due to cost and potential sources of error this is impractical. As such researchers rely on simulations.

The Distributed Hydrology Soil Vegetation Model(also referenced to as DHSVM) is a scientific mathematical model to numerically represent watersheds. Hydrology, as with all fields, continues to produce large amounts of data …

Whitespace Exploration, Jason Lloyd Daniel

Master's Theses

As engineering systems grow in complexity so too must the design tools that we use evolve and allow for decision makers to efficiently ask questions of their model and obtain meaningful answers. The process of whitespace exploration has recently been developed to aid in engineering design and provide insight into a design space where traditional design exploration methods may fail. In an effort to further the research and development of whitespace exploration algorithms, a software package called Thalia has been created to allow for automated data collection and experimentation with the whitespace exploration methodology.

In this work, whitespace exploration is …

Corgi: Compute Oriented Recumbent Generation Infrastructure, Christopher Allen Hunt

Master's Theses

Creating a bicycle with a rideable geometry is more complicated than it may appear, with today’s mainstay designs having evolved through years of iteration. This slow evolution coupled with the bicycle’s intricate mechanical system has lead most builders to base their new geometries off of previous work rather than expand into new design spaces. This crutch can lead to slow bicycle iteration rates, often causing bicycles to all look about the same. To combat this, several bicycle design models have been created over the years, with each attempting to define a bicycle’s handling characteristics given its physical geometry. However, these …

Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis

The Summer Undergraduate Research Fellowship (SURF) Symposium

Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …

Improving Ventricular Catheter Design Through Computational Fluid Dynamics, Sofy Hefets Weisenberg

Masters Theses

Cerebrospinal fluid (CSF) shunts are fully implantable medical devices that are used to treat patients suffering from conditions characterized by elevated intracranial pressure, such as hydrocephalus. In cases of shunt failure or malfunction, patients are often required to endure one or more revision surgeries to replace all or part of the shunt. One of the primary causes of CSF shunt failure is obstruction of the ventricular catheter, a component of the shunt system implanted directly into the brain's ventricular system. This work aims to improve the design of ventricular catheters in order to reduce the incidence of catheter obstruction and …

Optimization Of Blalock-Taussig Shunt And Anastomotic Geometry For Vascular Access Fistula Using A Genetic Algorithm, Guangyu Bao

McKelvey School of Engineering Theses & Dissertations

Blalock-Taussig (BT) shunts are used for defects that affect the flow of blood from the right ventricle, through the pulmonary artery, and to the lungs. Arteriovenous (AV) fistula is one type of vascular access which is a surgically created vein used to remove and return blood during hemodialysis. Plastic grafts used in the above two reconstructions may result in areas of non-physiologic flow in the grafts leading to risk of stenosis (blocked area) and thrombosis, which is the single major cause for access morbidity. The focus of this thesis is to study BT shunts and anastomoses models using Computational Fluid …

Role Based Hedonic Games, Matthew Spradling

Theses and Dissertations--Computer Science

In the hedonic coalition formation game model Roles Based Hedonic Games (RBHG), agents view teams as compositions of available roles. An agent's utility for a partition is based upon which role she fulfills within the coalition and which additional roles are being fulfilled within the coalition. I consider optimization and stability problems for settings with variable power on the part of the central authority and on the part of the agents. I prove several of these problems to be NP-complete or coNP-complete. I introduce heuristic methods for approximating solutions for a variety of these hard problems. I validate heuristics on …