Engineering Commons^™

In Situ Chlorine Generation And Rare Earth Chlorination By Molten Salt Electrolysis, Mark Schvaneveldt, Tyler Williams, Ranon Fuller, Devin Rappleye

Faculty Publications

Chloride volatility processes for purifying actinide and rare earth elements have historically required the use of Cl₂ tanks. To minimize the hazards associated with these processes, an apparatus was designed to produce Cl₂ via molten salt electrolysis. Within this apparatus, one can generate Cl₂, chlorinate metals, and consume excess Cl₂. Here, electrode materials were tested for their ability to generate Cl₂, the composition of the gaseous electrolysis product was evaluated using a quadrupole mass spectrometer, and a Ce foil sample was successfully chlorinated using the electrochemically generated Cl₂.

Consumers' Acceptance To Buy And Dispose Of Recycling Textile Products, Roa Alsayed

Theses and Dissertations

The textile industry is the second most polluting worldwide, following food manufacturing. It is one of the industries that is rarely scrutinized in the Middle East and North Africa (MENA) region. This work analyzes the fashion industry from the perspective of consumer attitudes towards the purchase and disposal of clothing, and their behavior with regards to old garments. The study was conducted in Saudi Arabia and Egypt, two countries that achieved similar results in the fashion industry. The methodology is divided into three phases. First, the manuscript begins with a review of topics such as sustainability, consumer behavior in the …

The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin

Faculty Publications

Analyzing plastic flow in refractory alloys is relevant to many different commercial and technological applications. In this study, screw dislocation statics and dynamics were studied for various compositions of the body-centered cubic binary alloy tungsten–molybdenum (W–Mo). The core structure did not appear to change for different alloy compositions, consistent with the literature. The pure tungsten and pure molybdenum samples had the lowest plastic flow, while the highest dislocation velocities were observed for equiatomic, W_0.5Mo_0.5 alloys. In general, dislocation velocities were found to largely align with a well-established dislocation mobility phenomenological model supporting two discrete dislocation mobility regimes, …

Joint Time-Frequency Analysis: Taking Charge Penetration Depth And Current Spatial Distribution In The Single Pore As An Example, Nan Wang, Qiu-An Huang, Wei-Heng Li, Yu-Xuan Bai, Jiu-Jun Zhang

Journal of Electrochemistry

In recent years, joint time-frequency analysis has once again become a research hotspot. Supercapacitors have high power density and long service life, however, in order to balance between power density and energy density, two key factors need to be considered: (i) the specific surface area of the porous matrix; (ii) the electrolyte accessibility to the intra-pore space of porous carbon matrix. Electrochemical impedance spectra are extensively used to investigate charge penetration ratio and charge storage mechanism in the porous electrode for capacitance energy storage. Furthermore, similar results could be obtained by different methods such as stable-state analysis in the frequency …

Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng

Journal of Electrochemistry

Redox potentials and acidity constants are key properties for evaluating the performance of energy materials. To achieve computational design of new generation of energy materials with higher performances, computing redox potentials and acidity constants with computational chemistry have attracted lots of attention. However, many works are done by using implicit solvation models, which is difficult to be applied to complex solvation environments due to hard parameterization. Recently, ab initio molecular dynamics (AIMD) has been applied to investigate real electrolytes with complex solvation. Furthermore, AIMD based free energy calculation methods have been established to calculate these physical chemical properties accurately. However, …

Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles

Journal of Electrochemistry

This study identifies, for the first time, critical calculation errors made by Nathan Lewis and his co-authors, in their study presented on May 1, 1989, at the American Physical Society meeting in Baltimore, Maryland. Lewis et al. analysed calorimetrically measured heat results in nine experiments reported by Martin Fleischmann and his co-authors. According to the Lewis et al. analysis, each of the experiments, where calculated for no recombination, showed anomalous power losses. When we used the same raw data, our corrected calculations indicate that each experiment showed anomalous power gains. As such, these data suggest the possibility of a new, …

Text Summarization, Varun Gottam, Anusha Vunnam, Purna Sarovar Puvvada

Symposium of Student Scholars

The current era is known as the information era. Every day, millions of gigabytes of data are being transferred from one point to another. As the creation of data became easy, it became hard to keep track of the important points and the gist of data especially in areas such as research and news. To solve this conundrum, text summarization is introduced. This is a process of summarizing text from across different documents or large datasets such that it can be read and understood easily by both humans and machines.

Yieldnet: Intelligent Fruit Yield Estimation For Selected Orchards Using Deep Learning Based Semantic Segmentation, Maheswari P

Theses and Dissertations

Agriculture contributes more resources for developing sustainable economic growth of the nation. Precision agriculture employs advanced techniques (machine learning and deep learning) for developing the intelligent systems of various agricultural applications. Among various agricultural tasks, yield estimation of crops plays a vital role in decision-making such as harvesting, marketing, cultivation practices, etc. Traditionally yield estimation is performed manually which has major drawbacks i.e., needs experts opinion, time-consuming and it is a challenging task for big orchards. To overcome these issues, an intelligent yield estimation model using neural network-based systems is required.

Some of the literature works have been explored for …

Investigation Of Fault Detection And Redundant Control Strategy For Model Predictive Control Of Distillation Column, Rajalakshmi R

Theses and Dissertations

Model Predictive Controller (MPC) is one of the industrial-ready control systems and an ideal choice for complex, slow-varying, and energy-intense Distillation Columns (DC). However, MPCs are subjected to failures and their performance degrades with faults and disturbances. Hence, there is a need for a redundant control strategy to ensure the continuous operation of MPC-controlled DC, which is investigated in this work.

A pilot-plant binary DC used to separate methanol and water is implemented with a computer-controlled system and is subjected to Pseudorandom Binary Excitation Signals (PRBS). The output response acquired is used to develop a MIMO (Multi-Input Multi- Output) state-space …

Research And Optimization Of Yolo-Based Method For Automatic Pavement Defect Detection, Hui Yao, Yaning Fan, Xinyue Wei, Yanhao Liu, Dandan Cao, Zhanping You

Michigan Tech Publications

According to the latest statistics at the end of 2022, the total length of highways in China has reached 5.3548 million kilometers, with a maintenance mileage of 5.3503 million kilometers, accounting for 99.9% of the total maintenance coverage. Relying on inefficient manual pavement detection methods is difficult to meet the needs of large-scale detection. To tackle this issue, experiments were conducted to explore deep learning-based intelligent identification models, leveraging pavement distress data as the fundamental basis. The dataset encompasses pavement micro-cracks, which hold particular significance for the purpose of pavement preventive maintenance. The two-stage model Faster R-CNN achieved a mean …

Dynamics Of Nanocluster Aerosol In The Indoor Atmosphere During Gas Cooking, Satya S. Patra, Jinglin Jiang, Xiaosu Ding, Chunxu Huang, Emily K. Reidy, Vinay Kumar, Paige Price, Connor Keech, Gerhard Steiner, Philip Stevens, Nusrat Jung, Brandon E. Boor

Purdue University Libraries Open Access Publishing Fund

Nanocluster aerosol (NCA: particles in the size range of 1–3 nm) are a critically important, yet understudied, class of atmospheric aerosol particles. NCA efficiently deposit in the human respiratory system and can translocate to vital organs. Due to their high surface area-to-mass ratios, NCA are associated with a heightened propensity for bioactivity and toxicity. Despite the human health relevance of NCA, little is known regarding the prevalence of NCA in indoor environments where people spend the majority of their time. In this study, we quantify the formation and transformation of indoor atmospheric NCA down to 1 nm via high-resolution online …

Classification Of Human Learning Stages Via Kernel Distribution Embeddings, Madeleine Shuhn-Tsuan Yuh, Kendric Ray Ortiz, Kylie Sue Sommer-Kohrt, Meeko Oishi, Neera Jain

School of Mechanical Engineering Faculty Publications

Adaptive automation, automation which is responsive to the human's performance via the alteration of control laws or level of assistance, is an important tool for training humans to attain new skills when operating dynamical systems. When coupled with cognitive feedback, adaptive automation has the potential to further facilitate human training, but requires precise assessments of human progression through various learning stages. This is challenging because of the underlying dynamics, as well as the stochasticity inherent to human action. We propose a data-driven approach to assess learning stages in a complex quadrotor landing task that is responsive to stochastic, human-in-the-loop quadrotor …

Granular Estimation Of User Cognitive Workload Using Multi-Modal Physiological Sensors, Jingkun Wang, Christopher Stevens, Winston Bennett, Denny Yu

Purdue University Libraries Open Access Publishing Fund

Mental workload (MWL) is a crucial area of study due to its significant influence on task performance and potential for significant operator error. However, measuring MWL presents challenges, as it is a multi-dimensional construct. Previous research on MWL models has focused on differentiating between two to three levels. Nonetheless, tasks can vary widely in their complexity, and little is known about how subtle variations in task difficulty influence workload indicators. To address this, we conducted an experiment inducing MWL in up to 5 levels, hypothesizing that our multi-modal metrics would be able to distinguish between each MWL stage. We measured …

Formulation And Aerosol Jet Printing Of Nickel Nanoparticle Ink For High-Temperature Microelectronic Applications And Patterned Graphene Growth, Nicholas Mckibben, Michael Curtis, Olivia Maryon, Mone’T Sawyer, Maryna Lazouskaya, Josh Eixenberger, Zhangxian Deng, David Estrada

Materials Science and Engineering Faculty Publications and Presentations

Aerosol jet printing (AJP) is an advanced manufacturing technique for directly writing nanoparticle inks onto target substrates. It is an emerging reliable, efficient, and environmentally friendly fabrication route for thin film electronics and advanced semiconductor packaging. This fabrication technique is highly regarded for its rapid prototyping, the flexibility of design, and fine feature resolution. Nickel is an attractive high-temperature packaging material due to its electrical conductivity, magnetism, and corrosion resistance. In this work, we synthesized nickel nanoparticles and formulated an AJP ink, which was printed on various material surfaces. Thermal sintering experiments were performed on the samples to explore the …

Path-Bigbird: An Ai-Driven Transformer Approach To Classification Of Cancer Pathology Reports, Mayanka Chandrashekar, Isaac Lyngaas, Heidi A. Hanson, Shang Gao, Xiao Cheng Wu, John Gounley

School of Public Health Faculty Publications

PURPOSE: Surgical pathology reports are critical for cancer diagnosis and management. To accurately extract information about tumor characteristics from pathology reports in near real time, we explore the impact of using domain-specific transformer models that understand cancer pathology reports. METHODS: We built a pathology transformer model, Path-BigBird, by using 2.7 million pathology reports from six SEER cancer registries. We then compare different variations of Path-BigBird with two less computationally intensive methods: Hierarchical Self-Attention Network (HiSAN) classification model and an off-the-shelf clinical transformer model (Clinical BigBird). We use five pathology information extraction tasks for evaluation: site, subsite, laterality, histology, and behavior. …

A Study On High-Frequency Bending Fatigue, Microhardness, Tensile Strength, And Microstructure Of Parts Made Using Atomic Diffusion Additive Manufacturing (Adam) And Additive Friction Stir Deposition (Afsd), Hamed Ghadimi

LSU Doctoral Dissertations

This dissertation reports the findings of several studies on the mechanical and microstructural properties of parts made using atomic diffusion additive manufacturing (ADAM) and additive friction stir deposition (AFSD). The design of a small-sized bending-fatigue test specimen for an ultrasonic fatigue testing system is reported in Chapter 1. The design was optimized based on the finite element analysis and analytical solution. The stress–life (S–N) curve is obtained for Inconel alloy 718. Chapter 2 presents the findings of ultrasonic bending-fatigue and tensile tests carried out on the ADAM test specimens. The S-N curves were created in the very high-cycle fatigue regime. …

Evaluation Of Fendiline Treatment In Vp40 System With Nucleation-Elongation Process: A Computational Model Of Ebola Virus Matrix Protein Assembly, Xiao Liu, Monica Husby, Robert V. Stahelin, Elsje Pienaar

Purdue University Libraries Open Access Publishing Fund

Ebola virus (EBOV) infection is threatening human health, especially in Central and West Africa. Limited clinical trials and the requirement of biosafety level-4 laboratories hinder experimental work to advance our understanding of EBOV and the evaluation of treatment. In this work, we use a computational model to study the assembly and budding process of EBOV and evaluate the effect of fendiline on these processes in the context of fluctuating host membrane lipid levels. Our results demonstrate for the first time that the assembly of VP40 filaments may follow the nucleation-elongation theory, as this mechanism is critical to maintaining a pool …

Developing And Forecasting The Egyptian Construction Cost Index, Mayada Elsaied

Theses and Dissertations

Accurate cost estimation is pivotal for the success of construction projects, yet the industry grapples with challenges related to cost overruns. Uncertainties and unforeseen variables often introduce discrepancies, particularly during the planning phase. Economic changes, considered uncontrollable risks, significantly influence these fluctuations. Various research endeavors have quantified the impact of economic conditions on construction costs, emphasizing the correlation between economic indicators and project expenses. Addressing these challenges, the Construction Cost Index (CCI), a tool introduced by Engineering News Record (ENR), accurately delineates the correlation between economic changes and construction costs. Despite its global efficacy, an Egyptian Construction Cost Index is …

Artificial Neural Network Modeling Applied For Predicting Reformate Yield And Research Octane Number In The Reforming Process, Badiea S. Babaqi, Abdelrigeeb Ali Al-Gathe, Mohd S. Takriff, Hassimi Abu Hasan, Mohammed H. Al-Douh

Hadhramout University Journal of Natural & Applied Sciences

The prediction model of the continuous catalytic regeneration reforming process was developed for expecting the reformate yield and research octane number using an Artificial Neural Network technique (ANN) to improve the process performance. The proposed model includes temperatures, pressures, and hydrogen to hydrocarbon molar ratio as input parameters while the output of the process represents reformate yield and research octane number. The ANN model was carried out to estimate the process behavior based on the Levenberg-Marquardt Algorithm, which included the nine input parameters, two hidden layers (10-5 neurons), and two parameters as network outputs. The results obtained were that the …

Table Of Contents, The Editors

Coal Geology & Exploration

No abstract provided.

Deep Coalbed Methane Production Technology For The Eastern Margin Of The Ordos Basin: Advances And Their Implications, Zeng Wenting, Xu Fengyin, Zhang Lei, Sun Weiwei, Wang Qian, Liu Yinhua, Yu Lizhu, Ji Liang, Zeng Quanshu, Zhang Kang

Coal Geology & Exploration

Contrasting with shallow to moderately deep coalbed methane (CBM) reservoirs, deep CBM reservoirs exhibit favorable coal structures, high formation pressure, high free gas ratios, and high contents of total dissolved solids (TDS) and CO₂. Extensive fracturing allows for CBM flowing at the initial stage, while the production parameters vary significantly throughout the CBM production. This requires wide technological boundaries of the main production technologies. Compared to shale gas and tight gas, deep CBM manifests different production mechanisms and relatively low free gas ratios, which lead to short flowing cycles of CBM. This necessitates timely water withdrawal for CBM …

Differences In Geological Conditions Of Deep And Shallow Coalbed Methane And Their Formation Mechanisms, Xu Hao, Tang Dazhen, Tao Shu, Li Song, Tang Shuling, Chen Shida, Zong Peng, Dong Yu

Coal Geology & Exploration

Deep coalbed methane (CBM) boasts abundant resources and great potential for exploitation. However, there is a lack of in-depth studies on the internal connections between deep and shallow CBM. This study investigated the Upper Paleozoic coalbed in the Ordos Basin. From the perspective of coalbed formation and evolution, it obtained three burial depth evolution modes of coalbed through summaries: both the maximum and present burial depths exceeding 2000 m, the maximum burial depth over 2000 m while the present burial depth less than 2000 m, and both the maximum and present burial depths less than 2000 m. This study systematically …

Occurrence Mechanism, Environment And Dynamic Evolution Of Gas And Water In Deep Coal Seams, Li Yong, Xu Lifu, Liu Yu, Wang Ziwei, Gao Shuang, Ren Ci

Coal Geology & Exploration

Accurately understanding of the occurrence states, relative content, and distribution characteristics of gas - water under deep conditions has important guiding significance for efficient exploration and development of coalbed methane (CBM). Based on the theoretical model, molecular simulation and systematic analysis of gas-water, the occurrence states of gas-water in coal seam is clarified, and the boundary and dynamic evolution process of gas-water dynamic migration and accumulation are revealed. Considering the coal - water interface interaction, the mobility and occurrence states of water, the coalbed water can be divided into movable water (gravity water and capillary water), bound water (adsorbed water, …

Effects Of Depth On Gas-Bearing Properties Of Coal Reservoirs And Their Coupling Relationships With Coalbed Methane Accumulation, Chen Shida, Hou Wei, Tang Dazhen, Li Xiang, Xu Hao, Tao Shu, Li Song, Tang Shuling

Coal Geology & Exploration

Burial depth serves as a comprehensive factor influencing coalbed methane (CBM) accumulation. Understanding the effects of depth on gas-bearing properties is critical for ascertaining the occurrence states and accumulation mechanisms of deep/shallow CBM. Based on the present situation of CBM exploration and the dissection of data from CBM exploration wells on the eastern margin of the Ordos Basin, this study explored the effects of burial depth on the gas content, saturated adsorbed gas capacity, and gas saturation of coal seams, as well as their coupling relationship with accumulation processes, using conventional and unconventional petroleum accumulation. The results indicate that CBM …

Deep Coalbed Methane Resources In The Shenmu-Jiaxian Block, Ordos Basin, China: Geological Characteristics And Potential For Exploration And Exploitation, Li Guoyong, Yao Yanbin, Wang Hui, Meng Lingjian, Li Peijie, Zhang Yongchao, Wang Jianwei, Ma Limin

Coal Geology & Exploration

China boasts abundant coalbed methane (CBM) resources in deep layers (burial depths: greater than 2000 m), with considerable potential for CBM exploration and development. Compared to medium and shallow CBM, deep CBM differs significantly in enrichment and accumulation patterns and exploitation means. Therefore, there is an urgent need to dissect key CBM blocks. The Shenmu-Jiaxian block, situated in the northeastern Ordos Basin, is currently in the early stages of deep CBM exploration, with enrichment characteristics and exploration potential remaining undefined. Based on recently obtained seismic data, logging data from over 300 wells, and analytical results from four cored wells, this …

Potential For The Production Of Deep To Ultradeep Coalbed Methane Resources In The Upper Permian Longtan Formation, Sichuan Basin, Ming Ying, Sun Haofei, Tang Dazhen, Xu Liang, Zhang Benjian, Chen Xiao, Xu Chang, Wang Jiaxian, Chen Shida

Coal Geology & Exploration

Breakthroughs have been achieved in the high-yield gas flow of coalbed methane (CBM) wells with burial depths ranging from 1000 to 2500 m in the Cainan area of the Junggar Basin and the Daning-Jixian and southern Yanchuan blocks on the eastern margin of the Ordos Basin, signifying the enormous potential for the production of deep CBM. In the Sichuan Basin, the thin to moderately thick coal seam groups (7‒15 layers) in the Upper Permian Longtan Formation primarily exhibit burial depths ranging between 2000 and 4500 m. In the central Sichuan Basin, characterized by north-dipping monoclines and local low-amplitude uplifts, deep …

Geological Characteristics And Favorable Area Evaluation Of Deep Coalbed Methane In Wangfu Fault Depression, Southern Songliao Basin, Shen Xia, Gong Haitao, Shao Mingli, Yang Minfang, Huo Wanguo

Coal Geology & Exploration

The Wangfu fault depression in the southern Songliao Basin is rich in coalbed methane (CBM) resources. However, CBM exploration in this area has been restricted by the low-level exploration of deep CBM and a lack of systematic studies on the geological characteristics of CBM, primary factors controlling CBM enrichment and accumulation, and the selection of favorable targets. Therefore, based on the systematical analysis of the geological characteristics of coal-bearing strata, this study identified the major factors controlling deep CBM accumulation, established the index system for favorable area selection, and predicted the favorable areas of CBM enrichment. The results show that: …

Moderately Deep Coalbed Methane Reservoirs In The Southern Qinshui Basin: Characteristics And Technical Strategies For Exploitation, Zhang Cong, Li Mengxi, Hu Qiujia, Jia Huimin, Li Kexin, Wang Qi, Yang Ruiqiang

Coal Geology & Exploration

This study investigated the northern Zhengzhuang-western Qinnan block for the purpose of achieving effective exploitation of moderately deep coalbed methane (CBM) reservoirs in the southern Qinshui Basin. Based on results from the analyses and tests of parametric wells, including core analysis and tests, injection/falloff tests, and in situ stress cyclic tests, as well as a large amount of dynamic and static data, this study expounded on the characteristics of moderately deep CBM reservoirs in the study area by comparison with shallow counterparts. Then, it explored the technical improvements in fracturing through vertical wells and staged fracturing through horizontal wells for …

A Calculation Model Of Free Gas Saturation In Deep Coalbed Methane Reservoirs And Its Application, Shi Juntai, Cao Jingtian, Xu Fengyin, Xiong Xianyue, Huang Hongxing, Sun Zheng, Jia Yanran, Ma Shurui, Zheng Haohang, Deng Ting, Li Jing, Li Xiangfang

Coal Geology & Exploration

In recent years, breakthroughs have been achieved in the exploration of deep coalbed methane (CBM) in China based on fine-scale geological research and techniques such as multistage hydraulic fracturing using proppants in a horizontal well. As a result, some wells yielded daily gas production of up to 100000 m³, inspiring confidence again in the CBM industry. However, since deep coal reservoirs occur in a complex geological environment characterized by high in-situ stress, high geotemperature, high pore pressure, and low permeability, there is an urgent need to reveal the typical parameters of coal reservoirs at different depths and the …

Mechanisms And Technological Parameter Optimization Of Near-Wellbore Laser Thermal Fracturing For Deep Coal Seams, Zhao Haifeng, Yang Ziyi, Liang Wei, Zhong Junbing

Coal Geology & Exploration

China boasts abundant deep coalbed methane (CBM) resources, which play a significant role in further CBM production. However, deep coal seams exhibit low porosities and ultra-low permeabilities due to intricate geological conditions. In the drilling process, drilling fluids enter the reservoirs, prone to cause near-wellbore contamination. Although conventional hydraulic fracturing technology tends to create fractures in the direction of the maximum horizontal principal stress, it is challenging for this technology to achieve blockage removing throughout the whole borehole. Laser thermal fracturing technology can break rocks in a short time. Furthermore, it allows for the laser irradiation angle to change freely …