Engineering Commons^™

Investigating The Effects Of Foreign Direct Investment (Fdi) On Croatian Business, Yonghee Cho, Tugrul U. Daim, Marina Dabic

Joseph Cho

A Decision Support Tool For Building Integrated Renewable Energy Microgrids Connected To A Smart Grid, Damilola A. Asaleye, Michael D. Murphy, Michael Breen

Publications

The objective of this study was to create a tool that will enable renewable energy microgrid (REμG) facility users to make informed decisions on the utilization of electrical power output from a building integrated REμG connected to a smart grid. A decision support tool for renewable energy microgrids (DSTREM) capable of predicting photovoltaic array and wind turbine power outputs was developed. The tool simulated users’ daily electricity consumption costs, avoided CO₂ emissions and incurred monetary income relative to the usage of the building integrated REμG connected to the national electricity smart grid. DSTREM forecasted climate variables, which were used …

Modeling Performance, Cost, Delivery, And Trip Distribution Of Demand Responsive Transit Systems With Zoning, Mahour Rahimi

Doctoral Dissertations

Demand responsive transit (DRT) services are expensive to operate, so it is crucial to understand the factors that drive the agency costs and be able to investigate and predict the effect of possible changes in specific operating parameters as well as demand and service coverage areas on total costs. In this research, we adopt the concept of the analytical model proposed by Daganzo (1978) to present continuum approximation (CA) models that can estimate important service related factors. As the first step, we propose three analytical models to approximate the operation related variables of DRT services; Fleet Size, Vehicle Hours Traveled …

Theory And Practice Of Supply Chain Synchronization, Michael Prokle

Doctoral Dissertations

In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden. In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit …

Decision Analytical Methods For Robust Water Infrastructure Planning Under Deep Uncertainty, Mehmet Umit Taner

Doctoral Dissertations

Deep uncertainties resulting from climate change, demographic pressures, and rapidly evolving socioeconomic conditions are challenging the way that water planners design and operate large-scale infrastructure systems. Conventionally, water infrastructures have been developed using stationary methods, assuming that the underlying uncertainties can be derived from historical data or experience. However, these methods are less useful under deeply uncertain climate and socioeconomic conditions, in which the future can be substantially different from the past and cannot be expressed by well-defined probability distributions. The recognition of deep uncertainties in long-term water resources planning has led to the development of “decision-analytical” frameworks that do …

Modeling And Simulation Of Microgrid, Ahmad Alzahrani, Mehdi Ferdowsi, Pourya Shamsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

Complex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes, energy storage units, and distributed generators. The main idea behind microgrids is the ability to work even if the main grid is not supplying power. That is, the energy storage unit and distributed generation will supply power in that case, and if there is excess in power production from renewable energy sources, it will go to the energy storage unit. Therefore, the electric grid becomes decentralized in terms of control …

Chaotic Behavior In High-Gain Interleaved Dc-Dc Converters, Ahmad Alzahrani, Pourya Shamsi, Mehdi Ferdowsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, chaotic behavior in high gain dc-dc converters with current mode control is explored. The dc-dc converters exhibit some chaotic behavior because they contain switches. Moreover, in power electronics (circuits with more passive elements), the dynamics become rich in nonlinearity and become difficult to capture with linear analytical models. Therefore, studying modeling approaches and analysis methods is required. Most of the high-gain dc-dc boost converters cannot be controlled with only voltage mode control due to the presence of right half plane zero that narrows down the stability region. Therefore, the need of current mode control is necessary to …

Classification Of Rest And Active Periods In Actigraphy Data Using Pca, Isaac W. Muns, Yogesh Lad, Ivan G. Guardiola, Matthew S. Thimgan

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper we highlight a clustering algorithm for the purpose of identifying sleep and wake periods directly from actigraphy signals. The paper makes use of statistical Principal Component Analysis to identify periods of rest and activity. The aim of the proposed methodology is to develop a quick and efficient method to determine the sleep duration of an individual. In addition, a robust method that can identify sleep periods in the accelerometer data when duration, time of day varies by individual. A selected group of 10 individual's sensor data consisting of actigraphy from an accelerometer (3-axis), near body temperature, and …

An Optimal Milk Production Model Selection And Configuration System For Dairy Cows, Fan Zhang

PhDs

Milk production forecasting in the dairy industry has been an independent research topic since the early 20th century. The accurate prediction of milk yield can benefit both the processor (creameries) and the producer (dairy farmer) through developing short-term production schedules, planning long-term road maps, facilitating trade and investment in the dairy industry, improving business operations, optimising the existing infrastructure of the dairy industry, and reducing operating costs. Additionally, due to the innate characteristics of the milk production process, the accurate prediction of milk yield has been a challenging issue in the dairy industry. With the abolishment of EU milk quotas …

Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun

Computer Science Faculty Research & Creative Works

The utilization of onsite generation system with renewable sources in manufacturing plants plays a critical role in improving the resilience, enhancing the sustainability, and bettering the cost effectiveness for manufacturers. When designing the capacity of onsite generation system, the manufacturing energy load needs to be met and the cost for building and operating such onsite system with renewable sources are two critical factors need to be carefully quantified. Due to the randomness of machine failures and the variation of local weather, it is challenging to determine the energy load and onsite generation supply at different time periods. In this paper, …

Analysis Of Autonomous Unmanned Aerial Systems Based On Operational Scenarios Using Value Modelling, Akash Vidyadharan, Robert Philpott Iii, Benjamin J. Kwasa, Christina L. Bloebaum

Engineering Management and Systems Engineering Faculty Research & Creative Works

In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, …

A General Algorithm For Assessing Product Architecture Performance Considering Architecture Extension In Cyber Manufacturing, Md Monirul Islam, Zeyi Sun, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In modern manufacturing, the product architecture design options are usually restricted to those that can be produced with 100% confidence using those proven technologies to satisfy the existing customer requirement. As a result, the inefficiencies of architecture design are considerable due to such limitations. This issue is of particular interests in cyber manufacturing when exploring the tradeoff between generality and feasibility in product design and manufacturing. It can be expected that the improvement and extension of the existing product architecture may be required to meet new customer requirement when new technologies become available. An effective system performance assessment algorithm is …

Learning Curve Analysis Using Intensive Longitudinal And Cluster-Correlated Data, Xiao Zhong, Zeyi Sun, Haoyi Xiong, Neil Heffernan, Md Monirul Islam

Engineering Management and Systems Engineering Faculty Research & Creative Works

Intensive longitudinal and cluster-correlated data (ILCCD) can be generated in any situation where numerical or categorical characteristics of multiple individuals or study units are observed and measured at tens, hundreds, or thousands of occasions. The spacing of measurements in time for each individual can be regular or irregular, fixed or random, and the number of characteristics measured at each occasion may be few or many. Such data can also arise in situations involving continuous-time measurements of recurrent events. Generalized linear models (GLMs) are usually considered for the analysis of correlated non-normal data, while multivariate analysis of variance (MANOVA) is another …

Energy Consumption Modeling Of Stereolithography-Based Additive Manufacturing Toward Environmental Sustainability, Yiran Yang, Lin Li, Yayue Pan, Zeyi Sun

Engineering Management and Systems Engineering Faculty Research & Creative Works

Additive manufacturing (AM), also referred as three-dimensional printing or rapid prototyping, has been implemented in various areas as one of the most promising new manufacturing technologies in the past three decades. In addition to the growing public interest in developing AM into a potential mainstream manufacturing approach, increasing concerns on environmental sustainability, especially on energy consumption, have been presented. To date, research efforts have been dedicated to quantitatively measuring and analyzing the energy consumption of AM processes. Such efforts only covered partial types of AM processes and explored inadequate factors that might influence the energy consumption. In addition, energy consumption …

Reward/Penalty Design In Demand Response For Mitigating Overgeneration Considering The Benefits From Both Manufacturers And Utility Company, Md Monirul Islam, Zeyi Sun, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The high penetration of renewable sources in electricity grid has led to significant economic, environmental, and societal benefits. However, one major side effect, overgeneration, due to the uncontrollable property of renewable sources has also emerged, which becomes one of the major challenges that impedes the further large-scale adoption of renewable technology. Electricity demand response is an effective tool that can balance the supply and demand of the electricity throughout the grid. In this paper, we focus on the design of reward/penalty mechanism for the demand response programs aiming to mitigate the overgeneration. The benefits for both manufacturers and utility companies …

Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi

Electrical and Computer Engineering Faculty Research & Creative Works

Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …

Open Access, Open Access, How Does Your Catalog Grow? With Selection, Access, And Usage All In A Virtual Row!, David W. Schuster, Susan J. Martin

Charleston Library Conference

Much of the open access (OA) focus and discussion has been on journals (think Glossa), but the open access monograph has come fully into its own. University and scholarly publishers are providing high-quality books, often in areas that rely on long-form scholarship. However, open access monographs presented a challenge. How do they fit into the traditional models of selection, acquisition, cataloging, and tracking usage?

In the spring of 2016, Texas Woman’s University Libraries created a simple workflow to make open access monographs accessible through the libraries’ discovery layer using Google Sheets to track the workflow and EZproxy to track usage.

Analytical Modeling Of Radiation Attenuation And Heat Deposition In Propellant For Nuclear Thermal Rockets, Alexander Aueron

Von Braun Symposium Student Posters

No abstract provided.

Development Of A User-Friendly System Model And Simulation For An Amateur Liquid-Fueled Rocket, Daniel Corey, Thomas Bennett, Brendan Luke, James Biaglow

Von Braun Symposium Student Posters

No abstract provided.

Diagnosing Failures In Complex Engineered Systems, Jalyn Gariepy

Von Braun Symposium Student Posters

No abstract provided.

Expendable Rs-25 Engine Affordability Study, Adam Bower, Dale Thomas

Von Braun Symposium Student Posters

No abstract provided.

Evaluating Benefits Of Sysml In Creating Value Models Using Nasa's Nea Scout, Garima Bhatia

Von Braun Symposium Student Posters

No abstract provided.

Nasa Habitat: Framework For An Analysis Of Preference Communication, Giulia Palma

Von Braun Symposium Student Posters

No abstract provided.

Where Mbse And Plm Fit Into The Digital Thread, Zach Thomas

Von Braun Symposium Student Posters

No abstract provided.

Strengthening The Profession Through Diversity, Inclusion And Equity: Best Practices And Distinguished Practitioners, Michael P. Johnson Jr.

Michael P. Johnson

Improving Decision-Making Skills Of Nonprofit Professionals, Michael P. Johnson Jr., George Chichirau, Jason Wright

Michael P. Johnson

All Models Are Wrong; Some Models Are Harmful, David Hunt, Michael P. Johnson Jr.

Michael P. Johnson

Profile Interview With Vincent Duffy, Apoorva Sulakhe

Purdue Journal of Service-Learning and International Engagement

Dr. Vincent Duffy is an associate professor in the Department of Industrial Engineering at Purdue University holding a joint appointment with Agricultural and Biological Engineering. Duffy focuses on human factors engineering and ergonomic design. His interest in teaching began early when he was a teaching assistant for IE 386 at Purdue University while pursuing his master’s degree. As an industrial engineering master’s non-thesis student, Duffy realized he had a natural inclination toward teaching. This motivation, along with the support and mentorship of Ferdinand Leimkuhler, the head of the department, turned him toward the fi eld of research. He rejoined Purdue …

Answering Food Insecurity: Serving The Community With Food And Knowledge Using Technology, Courtney Simpson

Purdue Journal of Service-Learning and International Engagement

The courses of Tech120, CGT110, and ENGT 180/181 and Red Gold at Purdue collaborated to design a robot that would plant and water a garden for a local community charter school. The students centered the project on the users’ needs for fresh food, nutrition education, and early exposure to STEM for children. The school, Anderson Preparatory Academy (APA), is comprised of many children who come from low-income families and are in the free or reduced lunch program. Inspired from “Farm Bot,” a similar system that allows for almost hands-free gardening, the “Boiler Bot” is designed to be scalable so children …

Using Emerging Open Source Technolgies To Foster Reproducability In Research, Joe Olson

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.