Engineering Commons^™

Prediction Of Mooring System Characteristics Of The Floating Barge Using Deep Neural Networks, Janghoon Seo, Dong-Woo Park

Journal of Marine Science and Technology–Taiwan

The present study establishes deep learning models to predict the tensions and inclinations of mooring lines of a floating barge and verifies applicability of these models. Hydrodynamic and mooring analyses are conducted on the dataset used for the deep learning models. Three types of neural network models include a deep neural network (DNN) with input data representing the six degrees of freedom motions of a floating barge, convolutional neural network (CNN) with input images of the floating barge and mooring lines on a horizontal plane, and hybrid neural network (HNN) that consolidates the characteristics of DNN and CNN models. The …

Mapping Of The Potential To Substitute Plastic In Food Packaging In Finnish Supermarkets, Taina Lahtinen, Kirsi Kataja, Jari Viitanen, Vinay Kumar, Jussi Lahtinen, Ali Harlin

Journal of Applied Packaging Research

Single-use plastics (SUP), which are extensively utilized in food packaging, are one notable cause for the constantly growing littering issue. This novel study is one of the first attempts to systemically analyze food packaging data to reveal the potential for plastic packaging material reduction or substitution by utilizing a primary packaging material summary of single items sold in Finnish supermarkets. The outcome of the study indicates considerable dissimilarities among product groups concerning used packaging materials, weight, share of plastic, and sales volume. The analysis identified sweets and ready-to-eat meals as product groups for which there is a clear need, but …

High-Fidelity Machine Learning Techniques For Driver Drowsiness Detection, Yasser Ismail, Ebenezer Essel, Abeer Abdelhamid, Mahmoud Darwich, Fahmi Khalifa, Fred Lacy

Faculty Publications

It is devastating that daily, there is an ample number of car crashes that cause damage to automobiles, onboard passengers get injured, and others tend to lose their lives. Road crashes are fast rising across the globe and have drawn many road safety commissions and concerned individuals to discuss ways to reduce this menacing situation drastically. With the introduction of artificial intelligence and technological advancement, the government and state commissions have beckoned on the various universities and research institutions to develop methods to curb the rise of automobile crashes. Some causes of these crashes include drunk driving and drowsiness, the …

Glycerol-Free Biodiesel Via Catalytic Interesterification: A Pathway To A Netzero Biodiesel Industry, Nessren Farrag, Omar Youssef Youssef, Esraa Khaled, Omar Aboelazayem

Chemical Engineering

Conventional biodiesel manufacturing uses alcohol as an acyl acceptor, resulting in glycerol as a side product. The increased demand for biodiesel has led to the production of a substantial surplus of glycerol, exceeding the market need. Consequently, glycerol is now being regarded as a byproduct, and in some cases, even as waste. The present study aims to suggest an economically viable and ecologically friendly approach for maintaining the viability of the biodiesel sector. This involves generating an alternative byproduct of higher value, rather than glycerol. Triacetin is produced through the interesterification of triglycerides with methyl acetate, and is a beneficial …

Optimising Grid-Forming Inverters To Prevent Under-Frequency Load Shedding With Minimal Energy Storage, Indoopa Manamperi, Iftekhar Ahmad, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The increasing penetration of distributed photovoltaics decreases the available loads in distribution feeders. This makes the traditional under-frequency load shedding systems ineffective. As an alternative, large-scale energy storage systems (ESS) could be used to provide contingency frequency response. This study investigates the optimum sizing of the ESS to prevent under-frequency load shedding. The optimal size is determined for both droop and virtual synchronous generator control-based inverters, to maintain frequency within operating standards. The control parameters are treated as variables in the optimisation process, allowing the identification of the optimal set of control parameters that minimise the ESS size while preventing …

Use Of Pulsed Electric Fields And Hydrogen Peroxide For Pre And Postharvest Strategies To Reduce Microbial Loads On Fresh Produce, Zachary Rosenzweig

Theses and Dissertations

Several issues exist within the agricultural industry surrounding failure to prevent pathogen transfer to plants preharvest and failure to decontaminate foods postharvest. Fresh produce, like leafy greens, pose a large threat to public safety if contaminated because they are minimally processed and often eaten raw. Numerous outbreaks have been linked to fresh produce in recent decades, with irrigation water emerging as a potential source. These outbreaks have severe economic repercussions and can contribute to millions of hospitalizations and deaths each year, worldwide. This thesis focuses on the usage of pulsed electric fields (PEF) and hydrogen peroxide (H2O2) as a means …

Research On Development Status And Strategy Of Advanced Materials In Guangdong-Hong Kong-Macao Greater Bay Area, Ziwei Zhao, Can Wang, Weihua Wang, Qingli Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Advanced materials are an important source of new quality productivity. Guangdong-Hong Kong-Macao Greater Bay Area is now facing the internal and external pressure of manufacturing upgrading, and there is an urgent need to play the leading and supporting role of advanced materials in the construction of modernized industrial system. This study combs through the basic situation of the development of materials science and industry in Guangdong-Hong Kong-Macao Greater Bay Area, analyzes its advantages, characteristics and problems in depth, and puts forward a number of suggestions around how to develop materials science, technology, and industry in the Greater Bay Area.

A Global Model-Agnostic Rule-Based Xai Method Based On Parameterized Event Primitives For Time Series Classifiers, Ephrem T. Mekonnen, Luca Longo, Pierpaolo Dondio

Articles

Time series classification is a challenging research area where machine learning and deep learning techniques have shown remarkable performance. However, often, these are seen as black boxes due to their minimal interpretability. On the one hand, there is a plethora of eXplainable AI (XAI) methods designed to elucidate the functioning of models trained on image and tabular data. On the other hand, adapting these methods to explain deep learning-based time series classifiers may not be straightforward due to the temporal nature of time series data. This research proposes a novel global post-hoc explainable method for unearthing the key time steps …

Emerging Productivity And Advanced Equipment Manufacturing: Issues, Reflections, And Practices, Jianlin Cao

Bulletin of Chinese Academy of Sciences (Chinese Version)

An important aspect of developing new quality productivity is utilizing the latest scientific and technological advancements for industrial upgrading, which includes developing emerging industries (high-tech industries) and transforming traditional industries. The weakness in advanced equipment manufacturing is a key challenge in China’s current industrial upgrading. This study, based on the global distribution of manufacturing enterprises, proposes a classification of four types of enterprises. It explains the reasons behind China’s lack of the fourth type of enterprise (those capable of integrating the latest technological achievements into their produced equipment) and the difficulties in cultivating and developing such enterprises. The study also …

Cornerstone Of Digital Economy: Challenges And Opportunities Of Ic Technologies, Jiang Xu, Wei Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the cornerstone of the digital economy in the information age, the essence of integrated circuit (IC) chips is to represent and process information by using physical phenomena. The IC challenges faced by China are not only in the field of fabrication, but also in the fields of electronics design automation (EDA) and talent training. Based on a review of the background and current situations of IC technologies, this study analyzes advantages, issues that need attention, and potential areas of technological breakthrough in the Guangdong-Hong Kong-Macao Greater Bay Area.

Salicylhydroxamic Acid Containing Structural Adhesive, Md Saleh Akram Bhuiyan, Kan Wang, Seyedehfatemeh Razaviamri, Bruce Lee

Michigan Tech Publications

The feasibility of utilizing salicylhydroxamic acid (SHAM) as a new adhesive molecule for designing structural adhesives is investigated in this study. SHAM-containing polymers were prepared with a hydroxyethyl methacrylate (HEMA) or methoxyethyl acrylate (MEA) backbone and mixed with polyvinylidene fluoride (PVDF). PVDF was included to increase the cohesive property of the adhesive through hydrogen bond (H-bond) formation with the adhesive polymers. SHAM-containing adhesive demonstrated lap shear adhesion strength (S ) greater than 0.9 MPa to glass, metal, and polymeric surfaces. Adhesive formulations with elevated SHAM-content also demonstrated increased adhesive properties with S values reaching as high as 4.8 MPa. Due …

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.

Golf Club Selection With Ai-Based Game Planning, Mehdi Khazaeli, Leili Javadpour

Pacific Faculty Work

In the dynamic realm of golf, where every swing can make the difference between victory and defeat, the strategic selection of golf clubs has become a crucial factor in determining the outcome of a game. Advancements in artificial intelligence have opened new avenues for enhancing the decision-making process, empowering golfers to achieve optimal performance on the course. In this paper, we introduce an AI-based game planning system that assists players in selecting the best club for a given scenario. The system considers factors such as distance, terrain, wind strength and direction, and quality of lie. A rule-based model provides the …

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 …

A Limited-Preemption Scheduling Model Inspired By Security Considerations, Benjamin Standaert, Fatima Raadia, Marion Sudvarg, Sanjoy Baruah, Thidapat Chantem, Nathan Fisher, Christopher Gill

Computer Science and Engineering Faculty Research

Safety-critical embedded systems such as autonomous vehicles typically have only very limited computational capabilities on board that must be carefully managed to provide required enhanced functionalities. As these systems become more complex and inter-connected, some parts may need to be secured to prevent unauthorized access, or isolated to ensure correctness.

We propose the multi-phase secure (MPS) task model as a natural extension of the widely used sporadic task model for modeling both the timing and the security (and isolation) requirements for such systems. Under MPS, task phases reflect execution using different security mechanisms which each have associated execution time costs …

Experimental Investigations On Mechanical Wear And Corrosion Behaviour Of Sintered Atomet 4601 Based Hybrid Alloys, Palaksha Reddy K

Theses and Dissertations

Powder metallurgy enables the development of new materials to manufacture products for applications requiring unique properties. The present research initially investigates the mechanical and tribological behaviour of powder metallurgy alloys made from ATOMET 4601 prealloyed powder and varying amounts of elemental carbon (0, 0.5, and 1.0 wt%) as reinforcement. ATOMET 4601 is a high-strength, water-atomized prealloyed powder capable of being compressed to higher densities, with applications in producing near-net or net-shaped parts for the industrial field.

Mechanical behaviour studies on sinter-forged ATOMET 4601, ATOMET 4601+0.5C, and ATOMET 4601+1.0C alloy steels revealed increased hardness, tensile strength, and impact strength, with ATOMET …

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 …

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 …

Biomanufacturing Of High-Strength Concrete: Incorporation Of Hemp Fiber To Improve High-Temperature Performance, Srishti Banerji

Funded Research Records

No abstract provided.

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

Funded Research Records

No abstract provided.

Eager: Leveraging Disruptive Technologies To Promote Learner Agency In Engineering Education, Cassandra J. Mccall

Funded Research Records

No abstract provided.

Effects Of Biofilm Colonization On The Dynamics Of Microplastics In Turbulent Flow, Liyuan Joanna Hou

Funded Research Records

No abstract provided.

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 …