Engineering Commons^™

Issue 15: From The Guest Editor, Mary Frost

Online Journal of Space Communication

Editorial by Mary Frost, Guest Editor

A Construction Workforce Training Partnership Between The State Of Wyoming, Industry, And University During Covid-19, Francois Jacobs, Renxiang Lu

Online Journal for Workforce Education and Development

Objective: To illustrate the development and implementation of a statewide construction workforce training program between the state, industry, and university during the COVID-19 pandemic. Background: Over the last 20 years, there has been a statewide construction workforce shortage, which not only creates an imbalance on the demands in this sector but impairs the profitability of Wyoming-based construction companies. Method: The team developed and implemented an online training platform, consisting of five modules, in support of training for construction companies and their workers across the state. Results: 149 successful learners received certificates of completion for the online training modules. The success …

Epics Lakota: Promoting Food Sovereignty On Pine Ridge Indian Reservation, Samantha Bijonowski, Kathleen Johnson, Jonathan Damon

Purdue Journal of Service-Learning and International Engagement

EPICS Team Lakota was started as a way for students to help promote food sovereignty and combat loss of cultural knowledge as felt by the residents of Pine Ridge Reservation, which is located in one of the poorest counties in the United States and is a food desert. In partnership with EPICS students at Oglala Lakota College (OLC) and South Dakota School of Mines (SDSM), students at Purdue came up with the idea of putting up a greenhouse on the Rapid City Campus of OLC. This greenhouse was meant not as a direct solution to food scarcity, but as a …

Adapting Global Service-Learning Project And Community Partnership Outcomes Using A “Tele-Engineering” Approach In Response To The Covid-19 Pandemic, Christiane Ley, Danielle Angert, Tessa Hudelson, Jordan Harris

Purdue Journal of Service-Learning and International Engagement

The Water Supply in Developing Countries (WSDC) service-learning course at Purdue University has fostered a strong partnership with the La Vega region in the Dominican Republic since 2012. During this time, an interdisciplinary group of engineering and science students has helped design drinking water treatment systems and the group has developed water, sanitation, and health (WASH) education materials. These WASH education and water safety approaches often have been conducted in person in the past. However, with the state of the COVID-19 pandemic and the inability to travel in the fall and spring semesters of the 2020–2021 academic year, the students …

Creating Reel Designs: Reflecting On Arthrogryposis Multiplex Congenita In The Community, Iris Layadi

Purdue Journal of Service-Learning and International Engagement

Because of its extreme rarity, the genetic disease arthrogryposis multiplex congenita (AMC) and the needs of individuals with the diagnosis are often overlooked. AMC refers to the development of nonprogressive contractures in disparate areas of the body and is characterized by decreased flexibility in joints, muscle atrophy, and developmental delays. Colton Darst, a seven-year-old boy from Indianapolis, Indiana, was born with the disorder, and since then, he has undergone numerous surgical interventions and continues to receive orthopedic therapy to reduce his physical limitations. His parents, Michael and Amber Darst, have hopes for him to regain his limbic motion and are …

Systems Level Roadmap For Solvent Recovery And Reuse In Industries, Emmanuel A. Aboagye, John D. Chea, Kirti M. Yenkie

Henry M. Rowan College of Engineering Departmental Research

Recovering waste solvent for reuse presents an excellent alternative to improving the greenness of industrial processes. Implementing solvent recovery practices in the chemical industry is necessary, given the increasing focus on sustainability to promote a circular economy. However, the systematic design of recovery processes is a daunting task due to the complexities associated with waste stream composition, techno-economic analysis, and environmental assessment. Furthermore, the challenges to satisfy the desired product specifications, particularly in pharmaceuticals and specialty chemical industries, may also deter solvent recovery and reuse practices. To this end, this review presents a systems-level approach including various methodologies that can …

Extending Multi-Beam Sonar With Structure From Motion Data Of Shorelines For Complete Pool Bathymetry Of Reservoirs, Izaak Brandt Cooper

Theses and Dissertations

Bathymetric mapping is an important tool for reservoir management, typically completed before reservoir construction. Historically, bathymetric maps were produced by interpolating between points measured at a relatively large spacing throughout a reservoir, typically on the order of a few, up to 10, meters or more depending on the size of the reservoir. These measurements were made using traditional survey methods before the reservoir was filled, or using sonar surveys after filling. Post-construction issues such as sedimentation and erosion can change a reservoir, but generating updated bathymetric maps is difficult as the areas of interest are typically in the sediment deltas …

Mechanical Engineering News, Georgia Southern University

Mechanical Engineering: News & Publications (2013-2023)

• Viking Ax Cast by Students

High-Entropy Alloys Properties Prediction Model By Using Artificial Neural Network Algorithm, Sanggyu Choi, Sung Yi, Junghan Kim, Byungsue Shin, Soongkeun Hyun

Mechanical and Materials Engineering Faculty Publications and Presentations

A new approach method has been studied for the efficient and accurate prediction of high-entropy alloys (HEAs) properties. The artificial neural network (ANN) algorithm was employed to predict the mechanical properties such as yield strength, microstructure, and elongation of the alloy by training from the mole fraction and post-process information that has an influence on the mechanical properties. The mean error rate of prediction for the yield strength was 19.6%. Microstructure predictions were consistent for all test data. On the other hand, the ANN model trained only with mole fraction data had a yield strength prediction error of 33.9%. Omission …

Research And Applications Of Artificial Neural Network In Pavement Engineering: A State-Of-The-Art Review, Xu Yang, Jinchao Guan, Ling Ding, Zhanping You, Vincent C.S. Lee, Mohd Rosli Mohd Hasan, Xiaoyun Cheng

Michigan Tech Publications, Part 1

Given the great advancements in soft computing and data science, artificial neural network (ANN) has been explored and applied to handle complicated problems in the field of pavement engineering. This study conducted a state-of-the-art review for surveying the recent progress of ANN application at different stages of pavement engineering, including pavement design, construction, inspection and monitoring, and maintenance. This study focused on the papers published over the last three decades, especially the studies conducted since 2013. Through literature retrieval, a total of 683 papers in this field were identified, among which 143 papers were selected for an in-depth review. The …

Synergistic Anticancer Response Of Curcumin And Piperine Loaded Lignin-G-P (Nipam-Co-Dmaema) Gold Nanogels Against Glioblastoma Multiforme, Xinyi Zhao, Bilal Javad, Daxing Cui, James Curtin, Furong Tian

Articles

Glioblastoma multiforme (GBM) is the most aggressive and commonly diag- 11 nosed brain cancer and presents a strong resistance to routine chemotherapeutic drugs. 12 The present study involves the synthesis of Lignin-g- p (NIPAM-co-DMAEMA) gold 13 nanogel, loaded with curcumin and piperine to treat GBM. The application has three 14 functions: (1) overcome the limitations of biodistribution, (2) enhance the toxicity of an- 15 ticancer drugs against GBM, (3) identify the uptake pathway. Atom transfer radical 16 polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with 17 the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and …

Enhanced Anticancer Response Of Curcumin- And Piperine-Loaded Lignin-G-P (Nipam-Co-Dmaema) Gold Nanogels Against U-251 Mg Glioblastoma Multiforme, Bilal Javed, Xinyi Zhao, Daxiang Cui, James Curtin, Furong Tian

Articles

Glioblastoma multiforme (GBM) is the most aggressive and commonly diagnosed brain cancer and is highly resistant to routine chemotherapeutic drugs. The present study involves the synthesis of Lignin-g-p (NIPAM-co-DMAEMA) gold nanogel, loaded with curcumin and piperine, to treat GBM. The ongoing study has the application potential to (1) overcome the limitations of drugs biodistribution, (2) enhance the toxicity of anticancer drugs against GBM, and (3) identify the drugs uptake pathway. Atom transfer radical polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and morphological analysis confirmed that the …

Pairwise Correlation Analysis Of The Alzheimer’S Disease Neuroimaging Initiative (Adni) Dataset Reveals Significant Feature Correlation, Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’S Disease Neuroimaging Initiative, The Alzheimer’S Disease Metabolomics Consortium, Justin B. Miller

Sanders-Brown Center on Aging Faculty Publications

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the …

Faster Post-Earthquake Damage Assessment Based On 1d Convolutional Neural Networks, Xinzhe Yuan, Dustin Tanksley, Liujun Li, Haibin Zhang, Genda Chen, Donald C. Wunsch

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Contemporary deep learning approaches for post-earthquake damage assessments based on 2D convolutional neural networks (CNNs) require encoding of ground motion records to transform their inherent 1D time series to 2D images, thus requiring high computing time and resources. This study develops a 1D CNN model to avoid the costly 2D image encoding. The 1D CNN model is compared with a 2D CNN model with wavelet transform encoding and a feedforward neural network (FNN) model to evaluate prediction performance and computational efficiency. A case study of a benchmark reinforced concrete (r/c) building indicated that the 1D CNN model achieved a prediction …

The Effects Of The Visual Environment On K-12 Student Achievement, Michael Kuhlenengel, Iason Konstantzos, Clarence E. Waters

Durham School of Architectural Engineering and Construction: Faculty Publications

The varying indoor environments among educational buildings can have an impact on students’ ability to learn. This study looks at field data from 220 classrooms in the Midwest, United States, over a two-year period, to analyze the effects of the visual environment on student achievement. The visual environmental metrics considered within this scope include the three new view metrics introduced within the EN 17037 “Daylight of Buildings” standard (Horizontal Sight Angle, Outside Distance of View, and Number of View Layers), as well as standard daylight and electric lighting metrics, focusing on light availability and glare. To capture student achievement, math …

Forcespun Polyvinylpyrrolidone/Copper And Polyethylene Oxide/Copper Composite Fibers And Their Use As Antibacterial Agents, Md Toukir Hasan, Ramiro Gonzalez, Ari Alexis Munoz, Luis Materon, Jason Parsons, Mataz Alcoutlabi

Mechanical Engineering Faculty Publications

Copper nanoparticles (CuNPs) embedded in polyvinylpyrrolidone (PVP) and polyethylene oxide (PEO) fiber-matrices were prepared through centrifugal spinning of PVP/ethanol and PEO/aqueous solutions, respectively. The prime focus of the current study is to investigate the antibacterial activity of composite fibers against Escherichia coli (E. coli) and Bacillus cereus (B. cereus) bacteria. During the fiber formation, the centrifugal spinning parameters such as spinneret rotational speed, spinneret to collector distance, and relative humidity were carefully chosen to obtain long and continuous fibers. The structural and morphological analyses of both composite fibers were investigated using scanning electron microscopy, X-ray diffraction, …

Data-Based Estimation And Simulation Of Compressible Pulsating Flow With Reverse Flow Through An Orifice, Indranil Brahma, Satbir Singh

Faculty Journal Articles

Highly compressible pulsating flows are often encountered in devices where knowledge of the flow rate is required but elimination of pulsations is not an option. The current work is a continuation of a previous investigation that characterized the orifice discharge coefficient Cd as a function of dimensionless groups based on pulsation characteristics. The experimental apparatus has been rebuilt in the current work to mitigate temperature and vibration problems, allowing pressure and ΔP measurements to be made very close to the test section with 159-mm of nylon tubing. Data was acquired for 77 operating conditions spanning a range of …

Regularized Heuristic Method For Activation Monitor Neutron Spectrum Unfolding, Nicholas J. Quartemont, James E. Bevins

Faculty Publications

his paper describes an activation foil measurement based neutron flux unfolding method utilizing a heuristic optimization approach. A regularization parameter based on the differential neutron flux was introduced into the optimization cost function to remove large nonphysical oscillations in the unfolded neutron energy spectrum. The procedure was completed for two example case studies ranging from thermal energies up to 20 MeV demonstrating recovery of neutron flux energy information on radiation environments where a model was partially missing or there was a discrepancy in a reaction channel. The unfolded results provided a distribution of unfolded spectra that conformed to the activation …

Third Party Risk Management And Cyber Supply Chain Risk Management, Jerald Garner

Operations Management Presentations

Today’s business environment continues to be a challenge. Businesses whether small, or large leverage third-party vendors to provide critical services like data handling (security, transmitting, and storage), cloud storage/applications, and systems security monitoring.

Each business must ask themselves a few simple questions about one of their most valuable assets “Data”. If or when it leaves your secure working environment:

• How secure is your customer data in transit and storage?
• Do your third-party vendors handle your “critical information”?
  • Provide a secure environment for processing?
  • Comply with a proven Cyber Security Framework?
  • Perform a “Due Diligence” on-boarding step for the Nth vendors …

Enhancement Of Power Generation And Organic Removal In Double Anode Chamber Designed Dual-Chamber Microbial Fuel Cell (Dac-Dcmfc), Ganjar Samudro, Tsuyoshi Imai, Yung-Tse Hung

Civil and Environmental Engineering Faculty Publications

One of the important factors in enhancing the performance of microbial fuel cells (MFCs) is reactor design and configuration. Therefore, this study was conducted to evaluate the regressors and their operating parameters affecting the double anode chamber–designed dual-chamber microbial fuel cell (DAC-DCMFC) performance. Its primary design consists of two anode chamber compartments equipped with a separator and cathode chamber. The DAC-DCMFCs were parallelly operated over 8 days (60 days after the acclimation period). They were intermittently pump-fed with the different organic loading rates (OLRs), using chemically enriched sucrose as artificial wastewater. The applied OLRs were adjusted at low, medium, and …

Systematic Evaluation Of A Novel Self-Healing Poly(Acrylamide-Co-Vinyl Acetate)/Alginate Polymer Gel For Fluid Flow Control In High Temperature And High Salinity Reservoirs, Jingyang Pu, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preferential fluid flow often occurs when water and CO₂ is injected into mature oilfields, sig-nificantly reducing their injection efficiency. Particle gels have been evaluated and applied to control the short circulation problems. This study systematically investigated a novel poly(acrylamide-co-vinyl acetate)/alginate-based interpenetrated gel system (Alg-IPNG) which is designed to control the preferential fluid flow problems in high-temperature reservoirs. Chromium acetate was incorporated into the gel system to provide the delayed crosslinking feature of the particle gels. The alginate polymer system can also take advantage of the Ca²⁺ ions in the formation water, which exist in most reservoirs, to reinforce …

Pairing Experimental And Mathematical Modeling Studies On Fluidized Beds For Enhancement Of Models Predictive Quality: A Current Status Overview, Sebastián Uribe, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Modeling of gas-solid fluidized systems has been a prevailing challenge over the last few decades. With different approaches and implementing different sub-models to capture the essential multiphase and multiscale phenomena in these systems, major advances have been achieved, even though most models are only subject to a practical validation of macroscopic parameters. The current description of fluidized beds through mathematical models relies on the inclusion of vast sub-models, leading to an unquantifiable degree of uncertainty on the models' applicability for extrapolation studies. Furthermore, each closure and fitting parameter in the model represents a possible source of deviation, and their optimization, …

A Reduced-Order Lumped Model For Li-Ion Battery Packs During Operation, Paul T. Coman, Eric C. Darcy, Brad Strangways, Ralph E. White

Faculty Publications

Modeling heat distribution in Li-ion battery packs can be challenging, especially if the battery pack is large and the cells are operated at high C-rates, which usually requires high-order physics-based mathematical models. Reduced and simplifying models can, however, be used at lower rates. This paper presents a fast novel reduced lumped model (RLM) that can be used to calculate the temperature increase during the high-current discharge of cylindrical Li-ion cells in a subscale of a battery pack. By reducing the PDE utilized to calculate the state of charge (SoC) to ODE's and solving them analytically, the reduced model can be …

Developing A Monte Carlo Simulation For Time- Series Analysis Of Actinium-225 Decay, Victoria Wood

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

This report describes the development of a script programmed in the Python language designed to simulate radioactive decay using Monte Carlo methods. This is to conduct analysis on the equilibrium behavior of a specific radioactive decay chain, replacing the traditional method of deriving a mathematical representation via differential equations. The resulting script produces a stacked histogram illustrating the decay of Actinium-225 over time and more closely models the potential for irregularities in the natural phenomenon. The script has potential applications in nuclear imaging and medical physics.

Modeling The Motion Of A Volleyball With Spin, Julian Ricardo

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

Though a qualitative understanding of how spin affects a ball’s trajectory can be easily developed, a quantitative one is relatively difficult to hone. Additionally, although projectile motion is an extensively covered topic in introductory physics courses, friction and drag—let alone spin—receive little to no attention. Here we use a volleyball and video modeling software to compare the behavior of a non-spinning ball with one that has topspin in order to assess the accuracy of our various models incorporating drag and the Magnus effect.

Electrical And Magnetic Properties Of High Temperature Superconductors Using Varying Forms Of Data Acquisition, Aryn M. Hays, Lindsay Bechtel, Colton Turbeville, Anthony Johnsen, Chris A. Tanner

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

High temperature superconductors (HTS) are materials that display superconducting properties at temperatures above that of liquid nitrogen. Possible applications and ease of use in a typical physics laboratory make them interesting systems to study. In this experiment we measured the critical temperatures of two samples made of different HTS materials. We also devised a method that makes taking data automated.

Shape And Size Matter For Projectile Drag, Daniel Gordon Ang

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

Newtonian mechanics is a fundamental building block of physics education, allowing us to characterize the motion of various objects in every day life. Here, we set out to investigate the effect of air resistance on projectile motion. We use high-speed cameras to record the flight of three different projectiles and compare this motion to a trajectory generated based on our theoretical model. We find that we are able to fit our model to the actual trajectory reasonably well, and find evidence that drag depends on the size and shape of the projectile.

Modeling A Swinging Atwood Machine, Parker W. Moody

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

The motion of a Swinging Atwood Machine is a difficult to solve for using Newtonian Mechanics. Lagrangian Mechanics, on the other hand, is extremely useful tool for a system that can seem overwhelmingly difficult to solve in Newtonian Mechanics. In this Lab we find the Lagrangian for this Swinging Atwood system, solve for the equation of motion, and compare our model to that of the observed motion of the system. Our model provides a good approximation of the motion, with small discrepancies due to the unknown mass of our pulley and dissipative forces.

Atomic Force Microscopy, Tyler Lane

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

The goal of this experiment is to use the Atomic Force Microscope (AFM) to get images of selected items and determine some distances of the characteristics of each sample. The ultimate goal is to measure the length of a nanotube, but unfortunately there were none left on the slide that was supposed to contain them. From the results of the lab and the lab manual of “companies” with possible lengths for each sample, Lindaas-Lahti Industries seems to have the best fit overall.

Decay Time Of A Damped Pendulum, Scott D. Froehle

The Journal of Advanced Undergraduate Physics Laboratory Investigations, JAUPLI-B

A number of labs have been conducted to find the equation for a damped pendulum. A damped pendulum's behavior will be analyzed and fit to this equation. This lab focused on tau, the decay constant. It was hypothesized that the decay constant would be greater with increasing initial angles, ultimately because of the pendulum's greater velocity. A pendulum was hung on a rotary motion sensor to detect its activity when released from different angles from the vertical. Its behavior was observed and fit to the equation for the behavior of a damped pendulum. It was found that decay time and …