Engineering Commons^™

Career: Innovation For Inclusion: Transforming Engineering Through Scalable Accessibility, Cassandra J. Mccall

Funded Research Records

No abstract provided.

Finite Element Modeling And Analysis Of Rc Shear Walls With Cutting-Out Openings, Islam M. Saad, Mohamed Emara, Ayman El-Zohairy, Sherif El-Beshlawy

Faculty Publications

In recent decades, reinforced concrete (RC) shear walls have been one of the best structural solutions to resist lateral load in high-rise buildings. Shear wall openings are essential for preparations and architectural requirements, which weaken the wall, reducing bearing capacity, energy absorption, and stiffness while also causing stress concentrations. This paper presents a comprehensive finite element (FE) investigation of the behavior and performance of RC shear walls with openings and subjected to lateral loads. The study aims to evaluate the influence of various parameters, such as opening location, size, wall aspect ratio, axial load, and concrete strength, which affect the …

Performance-Tunable Thermal Barrier Coating For Carbon Fiber-Reinforced Plastic Composites Via Flame Spraying, Heejin Kim, Kandasamy Praveen, Min Wook Lee, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

Thermal barrier coatings (TBCs) are essential for improving the heat resistance of materials operating in high-temperature environments. This paper proposes a new method for manufacturing double-layered TBC with graded porosity for carbon fiber-reinforced plastic (CFRP) composites. The TBC was created by a flame spraying process, consisting of relatively dense and porous layers: (1) a dense layer was produced by spraying yttria-stabilized zirconia (YSZ) particles directly onto neat carbon fabric substrate and (2) a porous layer was prepared by co-spraying YSZ particles with sacrificial polyetheretherketone (PEEK) particles. The porosity of the porous layer was controlled by varying a PEEK injection distance …

Techno-Economic And Multi-Objective Optimization Of A Hydrogen Liquefaction Plant Based On Rbc Integrated With Orc For Waste Heat Recovery, Erfan Ghamati, Mehdi Khiadani, Barun Das

Research outputs 2022 to 2026

To comply with the trend of emission reduction and energy-saving in the industrial sector, a novel integration of the hydrogen liquefaction process based on reversed Brayton cycle (RBC) with the organic Rankine cycle (ORC), for waste heat recovery is proposed. The high temperature gas in the compressor outlet of RBC, which is typically wasted in air-coolers, is recovered in ORC and used as the heat source for power generation for the hydrogen liquefaction process. Thermodynamic analysis showed that compared to the conventional system COP increased by 17.95% from 0.11 to 0.14 and specific energy consumption (SEC) decreased by 16.33% from …

Jovian Vortex Hunter: A Citizen Science Project To Study Jupiter’S Vortices, Ramanakumar Sankar, Shawn R. Brueshaber, Lucy Fortson, Candice Hansen-Koharcheck, Chris Lintott, Kameswara Mantha, Cooper Nesmith, Glenn S. Orton

Michigan Tech Publications

The Jovian atmosphere contains a wide diversity of vortices, which have a large range of sizes, colors, and forms in different dynamical regimes. The formation processes for these vortices are poorly understood, and aside from a few known, long-lived ovals, such as the Great Red Spot and Oval BA, vortex stability and their temporal evolution are currently largely unknown. In this study, we use JunoCam data and a citizen science project on Zooniverse to derive a catalog of vortices, some with repeated observations, from 2018 May to 2021 September, and we analyze their associated properties, such as size, location, and …

Version 1 Noaa-20/Omps Nadir Mapper Total Column So2 Product: Continuation Of Nasa Long-Term Global Data Record, Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris Mclinden, Debora Griffin, Peter J.T. Leonard, Simon Carn, Colin Seftor, Alexander Vasilkov

Michigan Tech Publications

For nearly 2 decades, the Ozone Monitoring Instrument (OMI) aboard the NASA Aura spacecraft (launched in 2004) and the Ozone Mapping and Profiler Suite (OMPS) aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite (launched in 2011) have been providing global monitoring of SO2 column densities from both anthropogenic and volcanic activities. Here, we describe the version-1 NOAA-20 (N20)/OMPS SO2 product (10.5067/OMPS/OMPS_N20_NMSO2_PCA_L2_Step1.1, Li et al., 2023), aimed at extending the long-term climate data record. To achieve this goal, we apply a principal component analysis (PCA) retrieval technique, also used for the OMI and SNPP/OMPS SO2 products, to N20/OMPS. For volcanic …

Structural Changes Likely Cause Chemical Differences Between Empty And Full Aav Capsids, Caryn Heldt, Molly A. Skinner, Ganesh S. Anand

Michigan Tech Publications

Due to the success of adeno associated viruses (AAVs) in treating single-gene diseases, improved manufacturing technology is now needed to meet their demand. The largest challenge is creating a process to separate empty and full capsids. Patients received larger capsid doses than necessary due to the presence of empty capsids. By enabling the better separation of empty and full capsids, patients would receive the greatest therapeutic benefit with the least amount of virus capsids, thus limiting potential side effects from empty capsids. The two most common empty/full separation methods used in downstream processing are ultracentrifugation and anion exchange chromatography. Both …

Practical Insights And Advances In Concrete Pumping, Daniil Mikhalev, Siamak Fakhrayee Nejad, Serina Ng, Baishakhi Bose, Robin De Schryver, Ana Brunčič, Manu K. Mohan, Yanwei Wang, A. V. Rahul, Atta Ur Rehman, Dengwu Jiao, Viktor Mechtcherine, Geert De Schutter, Dimitri Feys

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This technical letter gives a concise overview of the state-of-the-art in concrete pumping. It outlines the different pump systems, briefly describes the general flow behavior of concrete in pipes and addresses the main challenges of pumping. It also elaborates upon factors influencing the pumping behavior and how to control the pumping process.

Exploring Social Networks: An Analysis Of Intra-Organizational Networks, Ximeng Chen, Yiding Cao, Jiachen Liu, Danushka Bandara, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in …

Exploring The Relationship Between Covid-19 Transmission And Population Mobility Over Time, Tanmoy Bhowmik, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

This study explores the dynamic relationship between COVID-19 transmission and transportation mobility, with an emphasis on understanding the time-varying bidirectional interplay across the different phases of the pandemic. To gain insight into this relationship, we analyzed county-level data on transmission and mobility patterns from the United States over a 74-week period using a comprehensive list of factors including: temporal factors, socio-demographics, health indicators, health care infrastructure attributes, and spatial factors. For our analysis, we proposed a simultaneous econometric model system that explicitly accounts for the bidirectional relationship between COVID-19 transmission and mobility patterns while also accounting for the influence of …

Nanofiber-Hydrogel Composite Scaffold Fabrication Methods For Peripheral Nerve Regeneration, Jacob Lee Carter

Theses and Dissertations

Nerve graft conduits (NGCs) are a rapidly advancing field for treating peripheral nerve injuries that aim to guide the growth of regenerating axons across damaged gaps. A more effective NGC can be manufactured by combining the use of nanofibers to act as guidewires within a 3-D hydrogel that imitates the extracellular matrix of nerve tissue. Several methods have been developed to embed aligned nanofibers in an ordered architecture within a hydrogel matrix. The first method involves layer-by-layer additive manufacturing to create NGCs with rows of polycaprolactone (PCL) nanofibers surrounded by a gelatin methacrylate (GelMe) hydrogel in a 3-D structure. A …

The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe

Faculty Publications

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset …

Government Construction Projects Stumbling In Saudi Arabia Case Study: Municipal Sector Projects, Nawaf Saleh Altayash Eng, Abdurahman Ibrahim Ammar Dr

Emirates Journal for Engineering Research

Governmental construction projects receive a large proportion of the annual Kingdom budgets. The Kingdom’s government has been interested in addressing the problem of stumbling projects by establishing and launching several programs, initiatives, and projects. Despite this interest, the problem of stumbling government projects still exists.

This study aims to reach recommendations that lead to practical solutions to solve the problem of stumbling municipal sector construction projects in the Kingdom, by identifying the reasons for government construction projects stumbling in general and construction municipal sector projects in particular, classifying the reasons for stumbling of municipal sector construction projects, and arranging them …

Development Of Message Passing-Based Graph Convolutional Networks For Classifying Cancer Pathology Reports, Hong Jun Yoon, Hilda B. Klasky, Andrew E Blanchard, J. Blair Christian, Eric B Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Linda Coyle, Lynne Penberthy, Georgia D Tourassi

School of Public Health Faculty Publications

Background: Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language texts. However, the text classification models based on the TextGCN possess weaknesses in terms of memory consumption and model dissemination and distribution. In this paper, we present a fast message passing network (FastMPN), implementing a GCN with message passing architecture that provides versatility and flexibility by allowing trainable node embedding and edge weights, helping the GCN model find the better solution. We applied the FastMPN model to …

Design Considerations For Self-Management Technologies For People Living With Dementia And Informal Carers – Perspectives Of Healthcare Professionals And Charity Workers, Dympna O'Sullivan

Conference papers

Dementia is a neurodegenerative disorder that leads to decline in memory, language, reasoning, and the ability to perform daily activities. It is linked to poorer quality of life for the person with dementia and their informal (unpaid) carers. While early intervention and access to adequate care are critical in slowing dementia's progression and better managing associated symptoms, dementia is frequently only diagnosed at an advanced stage and care is often fragmented. To better understand how to meet the complex needs of persons living with dementia and their informal carers, 10 healthcare professionals and 10 charity workers from relevant community and …

Design Considerations For Self-Management Technologies For People Living With Dementia And Informal Carers - Perspectives Of Healthcare Professionals And Charity Workers, Dympna O'Sullivan, Julie Doyle, Orla Moran, Michael Wilson, Siobhan Oneill, Jonathan Turner, Suzanne Smith

Conference papers

Dementia is a neurodegenerative disorder that leads to decline in memory, language, reasoning, and the ability to perform daily activities. It is linked to poorer quality of life for the person with dementia and their informal (unpaid) carers. While early intervention and access to adequate care are critical in slowing dementia's progression and better managing associated symptoms, dementia is frequently only diagnosed at an advanced stage and care is often fragmented. To better understand how to meet the complex needs of persons living with dementia and their informal carers, 10 healthcare professionals and 10 charity workers from relevant community and …

09.16.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Human Research with AI workshop

External Funding Opportunities for Students

Evaluating Llm Generative A.I. Responses To Engineering Design Questions, Dominik Steinhauer

AI Assignment Library

Students will utilize different Large Language Model Generative A.I. Software to ask an Engineering Design Question relevant to their Sr. Design Project. The students will then assess the A.I. responses on usability, relevance, & accuracy. Finally, the students will reflect on the results of the assessments and their thoughts on LLM Generative A.I. This is an In Class Discussion assignment intended to build off of previous lectures on Information/Digital Literacy, Assessment of Sources, Large Language Model Generative A.I., and Prompt Engineering.

Electrochemical Investigation Of Moisture Byproducts In Molten Calcium Chloride, Rankin Shum, Marah Gragun, Tyler Williams, Devin Rappleye

Faculty Publications

Residual water in molten CaCl₂ reacts to form different byproducts, such as HCl, which can impact the corrosivity of the salt and efficiency of electrochemical operations, such as electrolytic oxide reduction and electrorefining. The ability to detect and quantify these byproducts electrochemically can provide feedback on the efficacy of vacuum drying and other purification methods, as well as the impact of these byproducts on process operations. An electrochemical signal’s association with the production of H₂ is verified and characterized using cyclic voltammetry (CV) and residual gas analysis. CV estimated a 2-electron exchange process associated with H2 production. CV …

A Review Of The Dry Methods Available For Coal Beneficiation, Nikki Hughes, Marco Le Roux, Quentin Peter Campbell, Fardis Nakhaei

Mining Engineering Faculty Research & Creative Works

Water is a precious global resource that is important in most currently employed coal beneficiation practices. These widely accepted processes deliver consistent and precise separation efficiencies at desired product yields and throughputs. Although favored, the water usage related to wet processing may be impractical and unsustainable in certain regions. Consequently, present-day practices used in coal processing may soon have to adapt, irrespective of any improved technical and economic feasibility offered. Therefore, the development of efficacious dry beneficiation methods has become an appealing research topic. This review assembles information pertaining to the principle and success of commercially available and experimental phase …

Research On Digital Twin System Of Rockshaft Hoist, Baiting Zhao, Jianguo Shi, Xiaofen Jia

Journal of System Simulation

Abstract: In order to solve the problem of low intelligence and digitization of the current mine hoisting system, a method based on DT for digital modeling, 3D visualization, and virtual real interaction of shaft hoisting machines is proposed. Aiming at the rockshaft hoist system, based on the digital twin five dimensional model framework, we analyze the operating mechanism of the equipment, and model the fully physical digital system of the rockshaft hoist. By constructing multidimensional multi-scale models and multidimensional heterogeneous data models, twin digital scenes are constructed, and virtual real mapping technology is combined to achieve dynamic mapping and virtual …

A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification, Yecai Guo, Shuang Tong

Journal of System Simulation

Abstract: Highly accurate sleep staging plays a crucial role in correctly assessing sleep conditions. Aiming at the problem that the existing convolutional network cannot obtain the topological characteristics of physiological signals, a sleep staging algorithm based on multi-modal residual spatio-temporal fusion is proposed. Time-frequency images and spatio-temporal images are obtained using short-time Fourier transform and adaptive map convolution, which are converted into high-dimensional feature vectors; lightweight interaction of feature information flow is realized through time-frequency feature and spatiotemporal feature extraction modules; the feature enhancement fusion module fuses feature information to outputs sleep staging results. The results show that the model …

Research On Simulation Resource Management Based On Graph Association Organization, Zewei Liu, Yishan Ding, Tingyu Lin, Mingxing Ke, Liqing Guo, Yingying Xiao, Zhilong Zhao, Yan Li, Xuan Lü

Journal of System Simulation

Abstract: The simulation test and evaluation of intelligent system of systems, systems and single equipment is a complex system engineering, which requires effective management of multi-source, heterogeneous and distributed massive simulation resources scattered in cloud test centers and test sites of various units; and good control of dynamically generated tasks, assumptions, configurations, results, evaluations and other data and files. The traditional way of managing and querying simulation resources by category is inefficient and difficult to meet the requirements of large-scale intelligent simulation test and evaluation activities. An overall framework for simulation resource management based on graph association organization, defines a …

Indicator Transfer Learning Based On Cloud Model And Maximum Mean Discrepancy, Lixia Xu, Jilong Zhong, Shaoshi Wu, Yishan Ding, Xiaoyu Zhai, Shizhao Chen, Yizhe Wang, Xue Wen, Juanfang Zeng, Xinwen Hou

Journal of System Simulation

Abstract: In response to the problem of rare data samples in application experiment scenarios, this paper proposes an indicator transfer learning method based on cloud models and Maximum Mean Discrepancy (MMD), which transfers the indicator calculation model from typical simulation experiment scenarios to application experiment scenarios to meet the needs across platform and domain simulation evaluation. Using the maximum mean difference method to align the indicator distribution in the typical simulation experiment scenario to the indicator distribution in the application experiment scenario, thereby achieves indicator transfer, and by using cloud models based on a small number of examples for modeling …

Adversarial Simulation Testing Algorithm For Svm Based On Multi-Objective Evolutionary Optimization, Feixing Li, Lining Xing, Yu Zhou

Journal of System Simulation

Abstract: Machine learning typically mines underlying patterns and rules from data, making it susceptible to phenomena such as overfitting and underfitting, which in turn affects the generalization and robustness of learning models. This paper explores the potential fragility and instability of SVM from the perspective of adversarial simulation testing. The adversarial simulation strategy employed involves selectively contaminating training sample labels to simulate an attack on the SVM classifier, thereby degrading its performance and testing its dependency on training samples. To explore the ceiling of performance degradation of an SVM classifier under the combination attack of different samples, the contradictory objectives …

Simulation Study Of Personnel Evacuation In Fire Scenarios Of Old School Buildings, Qiankun Zhu, Jiwu Li, Yongfeng Du

Journal of System Simulation

Abstract: In order to improve the emergency evacuation capability of an old school building under fire scenarios, a fire evacuation model of an old school building is developed. The PyroSim software is used to build a fire dispersion model to simulate and analyse the changes of smoke visibility, temperature and CO at the safety exit of the fire floor in the school building under the condition of mechanical smoke exhaust, automatic sprinkler and whether the windows of the fire room are open or not. The simulation of the exit status and evacuation of people has been carried out in conjunction …

Research On Orb-Slam Algorithm Based On Windowed Matching Estimation, Wanye Yao, Zewei Pang, Peijie Sun, Zhu Wang

Journal of System Simulation

Abstract: To address unstability of location accuracy of ORB-SLAM system caused by randomness of camera pose solution method, an improved pose solution method based on feature point windowed matching and analytical ICP is proposed, and the mobile robot ORB-SLAM system is constructed. The extracted feature points are windowed to improve matching efficiency while ensuring good feature point matching, the analytical ICP algorithm is used to solve the camera pose for avoiding iteration, and the windowed pose solution with the smallest error is selected for bundle adjustment to reduce the pose errors caused by local information loss or mismatching. The results …

Edge Surveillance Task Offloading And Resource Allocation Algorithm Based On Drl, Chao Li, Jiabao Li, Caichang Ding, Zhiwei Ye, Fangwei Zuo

Journal of System Simulation

Abstract: For the resource limitation of intensive surveillance tasks in edge computing, a surveillance task offloading and resource allocation algorithm based on DRL is proposed. With the optimization objectives of surveillance task delay and recognition accuracy, the joint decision objective optimization solution of task offloading, wireless channel allocation, and image compression rate was modeled as a Markov decision process. To address the problem of slow and unstable algorithm convergence due to the high volatility of training samples caused by the dynamic nature of wireless channels and the randomness of surveillance tasks, an attention mechanism is used to jointly encode channel …

Modeling And Simulation Of Pipeline Cable Inspection Robot Based On Omnidirectional Wheel, Chao Yuan, Yao Zhang, Yadong Zhao, Dawei Xu, Jing Yuan, Yongjie Zhai

Journal of System Simulation

Abstract: Aiming at the problem that the inner space of underground pipeline cable is narrow and closed, which cannot be inspected by humans, and the existing pipeline robot cannot adapt to the special environment of pipeline cable, a miniaturized, compact pipeline cable inspection robot is designed. This robot is capable of operating within the underground pipeline where cables have already been laid to inspect the inner wall of the pipeline and the working condition of the cables. According to the requirements of the working conditions, the whole three-dimensional model of the robot has been established. The mapping relationship between the …

A New Model Predictive Current Controller Forac-Dc Matrix Converter In Unbalanced Grids, Wenlang Deng, Minghai Wu, Haipeng Xie, Yingjie Hu

Journal of System Simulation

Abstract: To reduce the fluctuation of active power on the grid side of AC-DC matrix converters under unbalanced input conditions and to address the issue of variable switching frequency in discrete model predictive control, this paper proposes a novel model predictive control method. This method selects effective vectors based on the phase angle of the grid current, thus avoiding the computational burden of evaluating the value function in traditional model predictive control. Additionally, a second-order extended complex Kalman filter is introduced, which achieves the computation accuracy of the secondorder term of the Taylor series expansion and enables the application of …