Engineering Commons^™

Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Systems Science Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health outcome. Dynamics ...

Reactive Navigation In Partially Known Non-Convex Environments, Vasileios Vasilopoulos, Daniel E. Koditschek

Departmental Papers (ESE)

This paper presents a provably correct method for robot navigation in 2D environments cluttered with familiar but unexpected non-convex, star-shaped obstacles as well as completely unknown, convex obstacles. We presuppose a limited range onboard sensor, capable of recognizing, localizing and (leveraging ideas from constructive solid geometry) generating online from its catalogue of the familiar, non-convex shapes an implicit representation of each one. These representations underlie an online change of coordinates to a completely convex model planning space wherein a previously developed online construction yields a provably correct reactive controller that is pulled back to the physically sensed representation to generate ...

Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang

Theses and Dissertations

Regression analysis fits predictive models to data on a response variable and corresponding values for a set of explanatory variables. Often data on the explanatory variables come at a cost from commercial databases, so the available budget may limit which ones are used in the final model.

In this dissertation, two budget-constrained regression models are proposed for continuous and categorical variables respectively using Mixed Integer Nonlinear Programming (MINLP) to choose the explanatory variables to be included in solutions. First, we propose a budget-constrained linear regression model for continuous response variables. Properties such as solvability and global optimality of the proposed ...

Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy

Purdue Journal of Service-Learning and International Engagement

Apoorva Sulakhe and Shefali Rana are graduate students in the School of Industrial Engineering at Purdue. They have both been teaching assistants under their coauthor, Dr. Vincent Duffy, while supervising multiple projects. Coauthors Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, and Alyssa Zielinski are listed in alphabetical order. They were all seniors in School of Industrial Engineering at the time of this project in 2017. The purpose of their study, described in this article, was to develop an application to provide users with accurate information about diseases spreading in their geographic locations.

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching ...

Quantifying The Effect Of Uncertainty In The Gas Spot Price On Power System Dispatch Costs With Estimated Correlated Uncertainties, Dan Hu, Sarah M. Ryan

Sarah M. Ryan

Reactive Velocity Control Reduces Energetic Cost Of Jumping With A Virtual Leg Spring On Simulated Granular Media, Sonia F. Roberts, Daniel E. Koditschek

Departmental Papers (ESE)

Robots capable of dynamic locomotion behaviors and high-bandwidth sensing with their limbs have a high cost of transport, especially when locomoting over highly dissipative substrates such as sand. We formulate the problem of reducing the energetic cost of locomotion by a Minitaur robot on sand, reacting to robot state variables in the inertial world frame without modeling the ground online. Using a bulk-behavior model of high-velocity intrusions into dry granular media, we simulated single jumps by a one-legged hopper using a Raibert-style compression-extension virtual leg spring. We compose this controller with a controller that added damping to the leg spring ...

Statistical Reliability Of Wind Power Scenarios And Stochastic Unit Commitment Cost, Didem Sari, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

Probabilistic wind power scenarios constitute a crucial input for stochastic day-ahead unit commitment in power systems with deep penetration of wind generation. To minimize the cost of implemented solutions, the scenario time series of wind power amounts available should accurately represent the stochastic process for available wind power as it is estimated on the day ahead. The high computational demands of stochastic programming motivate a search for ways to evaluate scenarios without extensively simulating the stochastic unit commitment procedure. The statistical reliability of wind power scenario sets can be assessed by approaches extended from ensemble forecast verification. We examine the ...

Supporting Shrinkage: Better Planning And Decision-Making For Legacy Cities, Michael P. Johnson Jr., Justin B. Hollander, Eliza Davenport Whiteman

Michael P. Johnson

Evaluating The Effect Of Shear Stress On Graft-To Zwitterionic Polycarboxybetaine Coating Stability Using A Flow Cell, Andrew Belanger, Andre Decarmine, Shaoyi Jiang, Keith Cook, Kagya Amoako

Mechanical and Industrial Engineering Faculty Publications

The effect of surface coatings on the performance of antifouling activity under flow can be influenced by the flow/coating interactions. This study evaluates the effect of surface coatings on antifouling activity under different flows for the analyses of coating stability. This was done by exposing DOPA-PCB-300/dopamine coated polydimethylsiloxane (PDMS) to physiological shear stresses using a recirculation system which consisted of dual chamber acrylic flow cells, tygon tubing, flow probe and meter, and perfusion pumps. The effect of shear stress induced by phosphate buffered saline flow on coating stability was characterized with differences in fibrinogen adsorption between control (coated ...

Issues In Reproducible Simulation Research, Ben G. Fitzpatrick

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Buenaventura "Ven" Basco

No abstract provided.

Retention Of Female Faculty Members, Susan L. Murray, Mariesa Crow, Suzanna M. Rose

Suzanna Rose

The recruitment and the retention of female undergraduate and graduate students into engineering courses is discussed. A similar challenge lies in recruiting female faculty member from the limited pool of candidates in several fields at most universities. It is found that about half the females who were hired did not stay at the university. It is suggested that programs should be introduced to encourage mentoring and career development as such improvements would benefit all faculty members both female and male.

Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes

Donald C. Wunsch

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.

Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Donald C. Wunsch

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.

Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani

Donald C. Wunsch

This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate ...

Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani

Donald C. Wunsch

In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller ...

Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow

Donald C. Wunsch

A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set.

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Donald C. Wunsch

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of ...

Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow

Donald C. Wunsch

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly ...

Sensor-Based Reactive Execution Of Symbolic Rearrangement Plans By A Legged Mobile Manipulator, Vasileios Vasilopoulos, T. Turner Topping, William Vega-Brown, Nicholas Roy, Daniel E. Koditschek

Departmental Papers (ESE)

We demonstrate the physical rearrangement of wheeled stools in a moderately cluttered indoor environment by a quadrupedal robot that autonomously achieves a user's desired configuration. The robot's behaviors are planned and executed by a three layer hierarchical architecture consisting of: an offline symbolic task and motion planner; a reactive layer that tracks the reference output of the deliberative layer and avoids unanticipated obstacles sensed online; and a gait layer that realizes the abstract unicycle commands from the reactive module through appropriately coordinated joint level torque feedback loops. This work also extends prior formal results about the reactive layer ...

Inertial Velocity And Attitude Estimation For Quadrotors: Supplementary Material, James B. Svacha Jr, Kartik Mohta, Michael Watterson, Giuseppe Loianno, Vijay Kumar

Departmental Papers (ESE)

No abstract provided.

Minutes & Seconds: The Scientists, Patrick Aievoli

Zea E-Books

Minutes & Seconds, is a captivating intelligible read for those who strive to understand where the “what if” moment has gone. Succeeding his other captivating books, Aievoli’s deep introspective lens dials his readers in to awaken the proverbial sleeping giant inside of our consciousness. He designs an insightful exciting romp through the surreal landscape of our society and illustrates how various pioneers have lead us to a crossroads. I’m truly impressed with Aievoli’s perspicacious comprehension of where digital has taken us through the hands of these select individuals. --Sequoyah Wharton

In creating Minutes & Seconds, Aievoli has assembled an ...

Operational Squadron Scheduling, Khaled A. Almannaei

Theses and Dissertations

The 28th Operational Weather Squadron (28th OWS) is responsible for producing and disseminating mission planning and execution weather analyses and forecasts. The squadron must prepare schedules that meet the needs of their mission while dealing with real-world constraints such as time windows, task priorities, and intermittent recurring missions. The 28th OWS's manning consists of active duty, deployed in-place, reserve, civilian and contract personnel. In this research, a scheduling model and algorithm are provided as an approach to crew scheduling for the 28th Operational Weather Squadron. Scheduling in the 28th OWS is complex and can be time consuming. This model ...

Modular Crates – A Holistic Design Approach For Optimizing Cube Size In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Global market is a field where all industries strive to provide personalized product for every customer demand in order to compete with their competitors in the business battlefield. Product personalization varies with customer to customer which increases the product variety. When the product size variability is vast, producing packages for every individual product is not only difficult but also increases the design time, production time, total manufacturing cost and inventory cost. For the present scenario, Industrial packages does not opt customizability for variable product sizes. Customized package for personalized product is achievable only by redesigning the existing distribution package with ...

Distributed Methods For Composite Optimization: Communication Efficiency, Load-Balancing And Local Solvers, Chenxin Ma

Theses and Dissertations

The scale of modern datasets necessitates the development of efficient distributed opti- mization methods for composite problems, which have numerous applications in the field of machine learning. A critical challenge in realizing this promise of scalability is to develop efficient methods for communicating and coordinating information between distributed ma- chines, taking into account the specific needs of machine learning algorithms. Recent work in this area has been limited by focusing heavily on developing highly specific methods for the distributed environment. These special-purpose methods are often unable to fully leverage the competitive performance of their well-tuned and customized single machine counterparts ...

Human Factors And Ergonomics In Diversity, Inclusion And Social Justice Research, Rupa Valdez, Enid Montague, Mattie N. Milner, Michael C. Dorneich, Rod Roscoe

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

The Human Factors and Ergonomics Society Diversity Committee is entering its second year and continuing to explore ways to increase the diversity of the society. Following last year’s panel on “Challenges and Opportunities for Involvement,” we, and others, recognized that human factors and ergonomics (HFE) professionals are equipped and able to advance diversity, inclusion and social justice issues. This panel will bring together researchers to discuss experiences addressing these issues to highlight existing work, spark excitement about conducting new work and share advice. This panel will discuss and share lessons learned in a range of projects, including an HFE ...

The Wearer, The Device, And Its Use: Advances In Understanding The Social Acceptability Of Wearables, Norene Kelly, Stephen B. Gilbert

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

The WEAR Scale was used to collect data on the social acceptability of three wearable devices from 1,387 participants from the US Midwest and Silicon Valley. The most notable result was that a head-worn “medical device” was rated as more socially acceptable (d=0.78) than the same device described as a “brain fitness tool,” which was the opposite of what was hypothesized. Also, as hypothesized, Silicon Valley participants found the wearables more socially acceptable than Midwestern U.S. participants. The Scale and these results enable industry to better predict the human factors affecting social acceptability of wearables throughout ...

Developing An Optimized Ui For Traffic Incident Managers, Andrina Helgerson, Jamiahus Walton, Celia Loya, Christopher Kawell, Katherine Atwell, Quinn Monaghan, Lakshay Ahuja, Hesham Hassan, Stephen B. Gilbert, Anuj Sharma

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Traffic Incident Managers (TIMs) coordinate first responders and help resolve traffic-related incidents. Currently, some use over fifteen different software applications with unique functionalities across three monitors to manage incidents, leading to redundant data entry, unnecessary task switching, and delayed responses. 40 hours of TIMs’ screens were recorded during their normal work hours at the Iowa Department of Transportation (DoT). The resulting task analysis from these videos greatly influenced the design of a simplified, web-based, user interface (UI) prototype. The new UI offers a 42.9% reduction in the steps required to manage an incident by combining the functionality of the ...