Engineering Commons^™

A Lab-Scale Mold Simulator Employing An Optical-Fiber-Instrumented Mold To Characterize Initial Steel Shell Growth Phenomena, Muhammad A. Nazim, Rony K. Saha, Mario F. Buchely, Ronald J. O'Malley, Jie Huang, Arezoo Emdadi

PSMRC Faculty Research

A mold simulator was developed to replicate the mold oscillation and casting speed conditions of a continuous caster on the lab scale. A mold was designed incorporating fiber optics to capture internal temperature gradients and transient heat transfer phenomena during the initial solidification of steel. Casting parameters (casting speed, oscillation stroke and oscillation frequency) were investigated using the mold simulator. Solidified steel shells and mold thermal data were collected and characterized after initial solidification to investigate the impacts of mold oscillation on shell growth and mold heat transfer.

Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: Enabling Distributed High- Temperature Measurements And Strain Monitoring In Steelmaking And Foundry Applications, Ogbole Collins Inalegwu, Yeshwanth Reddy Mekala, Rony Kumer Saha, Farhan Mumtaz, Dinesh Reddy Alla, Deva Prasaad Neelakandan, Jeffrey D. Smith, Ronald J. O'Malley, Rex Gerald, Jie Huang

PSMRC Faculty Research

This study demonstrates the use of fiber Bragg grating (FBG) sensors for distributed temperature and strain monitoring in steelmaking and foundry applications. Integrated into inexpensive optical fibers, FBGs offer accurate and real-time remote sensing, detecting shifts in wavelength due to temperature (up to 1,800 °C), strain, or structural wear and tear. Furthermore, the intrinsic features of FBG sensors: compact size, immunity to electromagnetic interference and corrosion, robustness to vibration, ease of integration into existing composite structures, and non-intrusive measurement capacity in harsh environments make them ideal for steelmaking. FBGs optimize production, ensure quality, and enhance safety within the steel industry.

Enhanced Bottom Anode Monitoring In Dc Electric Arc Furnaces Using Fiber Optic Sensors, Yeshwanth Reddy Mekala, Rony Kumer Saha, Ogbole Collins Inalegwu, Muhammad Roman, Farhan Mumtaz, Rex Gerald, Jeffrey D. Smith, Jie Huang, Ronald J. O'Malley

PSMRC Faculty Research

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom …

Fiber-Optic Raman Probe For On-Line Eaf Slag Analysis, Bohong Zhang, Hanok Tekle, Jeffrey D. Smith, Todd Sander, Ronald J. O'Malley, Jie Huang

PSMRC Faculty Research

In Electric Arc Furnace (EAF) steelmaking, the push for improved efficiency requires accurate analysis of the chemical composition of its slag system to control slag foaming, provide refractory protection, and maintain high furnace iron yield. Therefore, the ability to obtain real-time slag chemistry data would provide a useful tool to improve the control and efficiency of the process. The work reported here aims to assess the structure and chemistry of EAF slags at high temperatures using a portable fiber-optic Raman probe. The ability to relate Raman spectra peaks to chemistry and structure is demonstrated in experimental result with EAF slags …

The Melting Behavior Of Hydrogen Direct Reduced Iron In Molten Steel And Slag: An Integrated Computational And Experimental Study, Fabian Andres Calderon Hurtado, Joseph Govro, Arezoo Emdadi, Ronald J. O'Malley

PSMRC Faculty Research

Direct reduced iron (DRI) and hot briquetted iron (HBI) are essential feedstocks for tramp element control in the electric arc furnace (EAF). Due to greenhouse gas (GHG) concerns related to CO₂ emissions, hydrogen as a substitute for natural gas and a reductant in DRI production is being widely explored to reduce GHG emissions in ironmaking. This study examines the melting behavior of hydrogen DRI (H-DRI) pellets in the EAF containing low-carbon (0.1 wt.%) molten steel and molten slag. A computational heat transfer model was developed to predict the melting behavior of H-DRI pellets. To validate the model, a set …

Methylene Blue-Mediated Photodynamic Therapy In Combination With Doxorubicin: A Novel Approach In The Treatment Of Ht-29 Colon Cancer Cells, Nima Rastegar-Pouyani, Jaber Zafari, Alireza Nasirpour, Hossein Vazini, Nabbaa Najjar, Seyedeh Zohreh Azarshin, Fatemeh Javani Jouni

Electrical & Computer Engineering Faculty Publications

Introduction: With an alarmingly growing number of patients diagnosed with colorectal cancer, adopting innovative anti-cancer approaches has recently garnered great attention. One interesting concept is the co-administration of cytotoxic agents and safer modalities such as photodynamic therapy (PDT), which can subsequently improve therapeutic efficacy and potentially reduce the risks of severe adverse effects and drug resistance. In the course of PDT, a locally injected photosensitizer (PS) is irradiated with a light source, which subsequently generates reactive oxygen species (ROS) and induces programmed cell death in tumor cells.

Methods: In this study, to evaluate the potential anti-cancer effects of chemotherapy combined …

Energy And Empowerment In The High Arctic, Alyssa Pantaleo

Dartmouth College Ph.D Dissertations

National governments continue to depend on fossil fuels for electricity and heat generation in Arctic communities. This dependence threatens the economic, environmental, and cultural sustainability of Arctic communities and subjects them to future volatility and uncertainty. In Greenland, the centralized government structure creates additional challenges for northern communities by limiting the inclusion of local knowledge and priorities in favor of national, standardized solutions. This research identifies pathways towards fossil fuel reduction in northern Greenlandic communities via 1.) analyzing the potential for renewable energy inclusion in grid-scale or residential energy generation and 2.) analysis of the potential for energy reduction in …

Accelerating Cavity Fault Prediction Using Deep Learning At Jefferson Laboratory, Md M. Rahman, A. Carpenter, K. Iftekharuddin, C. Tennant

Electrical & Computer Engineering Faculty Publications

Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive …

Integrated Energy-Efficient Distributed Link Stability Algorithm For Uav Networks, Altaf Hussain, Shuaiyong Li, Tariq Hussain, Razaz Waheeb Attar, Farman Ali, Ahmed Alhomoud, Babar Shah

All Works

Ad hoc networks offer promising applications due to their ease of use, installation, and deployment, as they do not require a centralized control entity. In these networks, nodes function as senders, receivers, and routers. One such network is the Flying Ad hoc Network (FANET), where nodes operate in three dimensions (3D) using Unmanned Aerial Vehicles (UAVs) that are remotely controlled. With the integration of the Internet of Things (IoT), these nodes form an IoT-enabled network called the Internet of UAVs (IoU). However, the airborne nodes in FANET consume high energy due to their payloads and low-power batteries. An optimal routing …

Desirable Candidates For High-Performance Lead-Free Organic–Inorganic Halide Perovskite Solar Cells, Sajid Sajid, Salem Alzahmi, Imen Ben Salem, Nouar Tabet, Yousef Haik, Ihab M. Obaidat

All Works

Perovskite solar cells (PSCs) are currently demonstrating tremendous potential in terms of straightforward processing, a plentiful supply of materials, and easy architectural integration, as well as high power conversion efficiency (PCE). However, the elemental composition of the widely utilized organic–inorganic halide perovskites (OIHPs) contains the hazardous lead (Pb). The presence of Pb in the PSCs is problematic because of its toxicity which may slow down or even impede the pace of commercialization. As a backup option, the scientific community has been looking for non-toxic/less-toxic elements that can replace Pb in OIHPs. Despite not yet matching the impressive results of Pb-containing …

An Enhanced Deep Autoencoder For Flight Delay Prediction, Desmond B. Bisandu, Dan Andrei Soviani-Sitoiu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

Accurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless, there has not been a universal solution to the problem, as more intelligent flight decision systems are required for the aviation industry's future growth. Existing flight delay classification and prediction approaches are mainly shallow traffic models and do not satisfy many applications in the real world. Our motivation to rethink the deep architecture model for predicting flight delays emanates from the problem. In this research, we proposed a technique that modified stacked autoencoder architecture …

Computational Cognitive Modeling Of Pilot Performance In Pre-Flight And Take-Off Procedures, Rongbing Xu, Shi Cao, Suzanne K. Kearns, Ewa Niechwiej-Szwedo, Elizabeth Irving

Journal of Aviation/Aerospace Education & Research

While the current practice of pilot training relies on flight instructors’ subjective assessment, computational cognitive modeling may be used to support future objective assessment and diagnosis of pilot performance. We built two models in a cognitive architecture to simulate pilot flight performance during pre-flight and take-off tasks. Modeling results were compared with human results collected from the same tasks using X-Plane 11 flight simulator. The models were able to capture human pilot performance and workload results from both tasks with good levels of fitness (percentage errors ranging from 0.8% to 13.2%). This work demonstrated the capability and advantage of this …

Increasing Initial Cfi Capacity Within Collegiate Flight Programs, Andrew Leonard, Cody Christensen

International Journal of Aviation, Aeronautics, and Aerospace

According to the Government Accountability Office (2018), collegiate aviation schools face two primary challenges: flight instructor retention and the high cost of pilot training. In a study of collegiate aviation programs, 16 of the 18 schools reported difficulty in recruiting and retaining certified flight instructors (CFI), leading to the inability to accept all students who applied to the programs. Furthermore, these programs attributed the high instructor turnover to the increased demand for commercial pilots at the airlines, a challenge that is not expected to decrease in the near future (Boeing, 2023). While the lack of flight instructor retention impacts flight …

Leveraging Artificial Intelligence To Improve Data Configuration & Accuracy In Modern Flight Management Systems, Sreeram Chittayil

International Journal of Aviation, Aeronautics, and Aerospace

AI (Artificial intelligence) can automate the process of generating optimized flight routes using real-time data, such as AIRAC (Aeronautical Information Regulation and Control), significantly reducing the time needed for flight management tasks. While AIRAC data typically takes up to 28 days to refresh, AI could condense this process to just minutes, enhancing operational efficiency and ensuring pilots have timely and accurate flight information. The research includes practical experiments, prototype code, and visual case studies to demonstrate AI's role in optimizing FMS functions while addressing issues related to data input errors and human intervention. Key findings from trials show the algorithm's …

Automatic Detection Of Birds In Images Acquired With Remotely Piloted Aircraft For Managing Wildlife Strikes To Civil Aircraft, Maurycio Rodrigues Oviedo, Flavio A. C. Mendonca Ph.D., Jose Cabrera, Cole A. Mcnall, Raymond Ayres, Ricardo Luís Barbosa, Rodrigo Gallis

International Journal of Aviation, Aeronautics, and Aerospace

Wildlife strikes represent a significant threat to aviation safety and economics, as evidenced by notable incidents such as the emergency landing of US Airways Flight 1549 in 2009. The Federal Aviation Administration (FAA) acknowledges this growing concern, as evidenced by its report on Wildlife Strikes to Civil Aircraft in the United States from 1990 to 2019.To address the need for improved risk management, airports conduct Wildlife Hazard Assessments (WHA), a laborious process typically relying on visual identification by Qualified Airport Wildlife Biologists (QAWB). However, technological advancements, such as Remotely Piloted Aircraft (RPA) and machine learning (ML), offer promising solutions to …

Performance Prism: A Comprehensive Framework For Performance Measurement In Aircraft Maintenance, Mohammed Timjerdine, Saoudi Taibi, Younes Moubachir

International Journal of Aviation, Aeronautics, and Aerospace

Aircraft maintenance is governed by rigorous safety requirements and high operational complexity, demanding robust performance measurement frameworks to ensure optimal maintenance practices. This paper investigates existing performance measurement methodologies within the sector, highlighting their limitations and the need for a more structured evaluation system. Through this critical analysis of current literature, the paper proposes the Performance Prism (PP) framework as a novel and potentially robust solution for assessing and enhancing aircraft maintenance performance. Because the PP framework integrates multiple dimensions of evaluation, it provides a holistic assessment of aircraft maintenance performance, thereby enhancing reliability, efficiency, and overall effectiveness. Using examples …

Prioritization Of Voluntary Silence Criteria In Military Aviation For The Sustainability Or Safety Superiority, Vildan Durmaz, Cüneyt Ceyran, Ebru Yazgan

International Journal of Aviation, Aeronautics, and Aerospace

Since aviation is one of the sectors involving high levels of risk in today’s world, the presence of a safe working environment is crucial for both flight operations and aircraft maintenance services. Thus, it is vital for aviation workers to be aware of unsafe situations as well as dangers and potential risks in order to create a safe environment and establish an organizational safety culture. One of the fundamental components of such awareness is information, and voluntary reporting of this information as well as unsafe situations by aviation employees is one of the most important ways for managers to access …

Airspace Saturation And Midair Collision Risk: A Case Study At A Class D Airport, Luigi Raphael I. Dy, John H. Mott

International Journal of Aviation, Aeronautics, and Aerospace

Near midair collisions are precursor events to actual collisions and may be an indicator of risk. While previous studies have used reports of near midair collisions to relate factors such as airspace saturation to near midair collisions, the reports relied upon were generally subjective in nature. With the adoption of automatic dependent surveillance-broadcast (ADS-B), the approximate position of every equipped aircraft can be recorded. A six-month case study was performed at the Purdue University airport to relate the number of 1000-foot proximity events to airspace saturation, and whether the Class D airspace affected this relationship. Through a logistic regression analysis, …

De-Risking Pretreatment Of Microalgae To Produce Fuels And Chemical Co-Products, Jacob S. Kruger, Skylar Schutter, Eric P. Knoshaug, Bonnie Panczak, Hannah Alt, Alicia Sowell, Stafanie Van Wychen, Matthew Fowler, Kyoko Hirayama, Anuj Thakkar, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Conversion of microalgae to renewable fuels and chemical co-products by pretreating and fractionation holds promise as an algal biorefinery concept, but a better understanding of the pretreatment performance as a function of algae strain and composition is necessary to de-risk algae conversion operations. Similarly, there are few examples of algae pretreatment at scales larger than the bench scale. This work aims to de-risk algal biorefinery operations by evaluating the pretreatment performance across nine different microalgae samples and five different pretreatment methods at small (5 mL) scale and further de-risk the operation by scaling pretreatment for one species to the 80 …

Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu

Civil & Environmental Engineering Faculty Publications

The curved tidal channel, Luotou Deep-water Navigational Channel, is the main channel of the Ningbo Zhoushan Port, which is ranked first in the world. Tidal dynamics in the channel are spatially and temporally asymmetric. In this study, the three-dimensional tidal dynamics in the channel were analyzed using field data and simulated using FVCOM. The results show that the tides in the channel flood/ebb along the northern/southern bank near the bottom/surface layer and these asymmetries are due to the imbalanced Coriolis force, centrifugal force, sea-level gradient, and density gradient. Residual current velocity peaks (0.7 m/s) in the middle of the channel …

Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas

Civil & Environmental Engineering Faculty Publications

Site response describes the alterations of seismic energy due to its interaction with subsurface geological interfaces and structures, which is usually estimated by one dimensional (1D) ground response analysis (GRA). However, 1D GRA requires subsurface information (e.g., shear wave velocity profile), which makes it not widely applicable, particularly for the sites where subsurface information is unavailable. Alternatively, the microtremor horizontal-to-vertical spectral ratio (mHVSR) from three-component recordings of ambient noise on the ground surface is easily measured and is believed to have the potential for site response prediction (the peaks in mHVSR are strongly associated with the site resonant frequencies). However,the …

Exposure To Low (10 Cgy) Doses Of ⁴He Ions Leads To An Apparent Increase In Risk Taking Propensity In Female Rats, Nina Li, Simran Phuyal, Elliot Smits, Faith E. Reid, Ella N. Tamgue, Paola Alvarado Arriaga, Richard A. Britten

Department of Medicine Faculty Publications

The planned missions to the Moon and Mars will present more significant health challenges to astronauts compared to low earth orbit missions. During deep space missions, astronauts will be constantly exposed to Space radiation (SR). Multiple rodent studies suggest that < 25 cGy of SR impairs performance in executive functions, which play a key role in advanced cognitive processes, but also regulate response inhibition and impulse control. There is the possibility that SR exposure may exacerbate aberrant behaviors evoked by psychological stress related to exposure to isolated and confined (ICE) hostile environment or independently induce additional aberrant behaviors. This study has determined that female Wistar rats exposed to 10 cGy of 250 MeV/n He had an increased risk taking propensity (RTP)\compared to shams. The increased RTP of the He-exposed rats was associated with significantly increased reaction times during the trials, suggesting a SR-induced loss of processing speed. The response times of the He-exposed rats were even further reduced in trials that immediately followed a loss, raising the possibility that conflict and interference avoidance may be impaired after SR exposure. Whether these findings occur following other types of SR exposure, and/or in male rats remains to be determined.

Near Infrared Upconversion Nanoparticles Modified With Semiconducting Polymers For Anti-Counterfeiting, Abraham Chibuikem Ikeji

Dissertations and Theses

Lanthanide doped up-conversion nanoparticles (UCNPs) are excellent luminescent materials due to their ability to perform photon up-conversion from low energy to high energy using their triplet energy metastable states and because of their long-lived excited state. These properties enable multiple applications with the near infrared upconversion emission. They have been incorporated in developing technologies to help curb counterfeiting activities and other areas of research. However, they still have some limitations such as the hydrophobic nature of the UCNPs, and the absence of functional groups that can also help impact other desired features. Thus, in this work we have coated up-conversion …

Impact Of Traffic Congestion On Transportation System: Challenges And Remediations - A Review, Hamdy B. Faheem, Amira M. El Shorbagy, Mohamed Elsayed Gabr

Mansoura Engineering Journal

Traffic congestion is a growing problem in urban transportation networks around the world, having major consequences for the economy and the environment. As metropolitan populations rise and more people rely on autos for mobility, traffic congestion is becoming more common and severe. This review paper presents an overview of the economic and environmental issues caused by traffic congestion in urban areas, as well as proposed ways to reduce its negative effects. It discusses potential traditional transportation solutions such as traffic management infrastructure development, improving public transportation, and intelligent transportation solutions to address traffic congestion problems such as smart parking systems, …

Application Of Machine Learning Models In The Capacity Prediction Of Ccfst Columns, Khaled Megahed, Nabil Said Mahmoud, Saad Elden Mostafa Abd-Rabou

Mansoura Engineering Journal

Circular concrete-filled steel tubular (CCFST) columns are widely utilized in structural engineering due to their impressive load-bearing capabilities and ductility. Existing design standards often yield disparate outcomes when applied to structural columns with identical properties, introducing uncertainty for engineering designers. This study introduces an innovative technique to address these challenges using two machine learning (ML) models: Gaussian process regression (GPR) and extreme gradient boosting (XGBoost). These models consider various input variables, including the geometric and material properties of CCFST columns, to estimate the compressive strength. The models undergo training and evaluation using two datasets comprising 1004 axially loaded CCFST columns …

Numerical And Analytical Solution For Nonlinear Free Vibration Of Tapered Beams, Zain Abu Shaeer Abu Shaeer, Ramy I. Shahin, Galal I. El-Baghdady, Saad A. Yehia

Mansoura Engineering Journal

This study introduces a computational approach that combines numerical and semi-analytical methods to solve tapered beams' nonlinear free vibration equation. The study employs a numerical approach that relies on the cubic B-spline collocation method and an approximation technique known as the Homotopy perturbation method to approximate the solution to the equation governing nonlinear large-amplitude free vibrations of tapered beams. The effect of vibration amplitude on the frequency of nonlinear vibrations is investigated. The next step is to look at different ways to get close to exact solutions across the whole range of oscillation amplitude. This will show how useful and …

Enhancing Network Security In Iot Applications Through Ddos Attack Detection Using Ml, Ahmed Mohamed Salama, Mohamed Abdelazim Mohamed, Eman Abdelhalim

Mansoura Engineering Journal

A significant issue that affects contemporary network infrastructures is the Distributed Denial of Service (DDoS) attack, which presents serious dangers to organizations, people, and even governments. By flooding a target server, network, or website with deceptive traffic, this kind of cyberattack seeks to prevent it from providing services to legitimate users. For those in charge of maintaining network security, the prevalence and sophistication of these attacks have both grown significantly. DDoS attacks have the potential to lead to significant financial losses and service interruptions. Anomaly-based systems, traffic filtering, and Machine Learning (ML) algorithms are employed to spot them and lessen …

Effect Of The Shape And Volume Of Capsulated Phase Change Materialon The Melting Process And Exergy Efficiency, Ahmed Saad Soliman, Ahmed A. Sultan, Mohamed A. Sultan

Mansoura Engineering Journal

Due to the lack of solar energy continuity throughout the day, researchers tended to store this energy in phase change materials (PCM). The goal is to store a big amount of energy in a small PCM mass. In this study, the effect of the capsule shape (circular and elliptical cross-section), number of capsules with the same volume (1, 2, 3, 4, and 5 capsules), and one capsule with increasing its initial volume (multiplying of volume ratio 1 (Vr = 2, 3, 4, and 5)) on the PCM melting process was studied. The results of the numerical model for both circular …

Machine Learning-Based Prediction Of International Roughness Index For Continuous Reinforced Concrete Pavements, Ragaa T. Abd El-Hakim, Ahmed N. Awaad, Sherif M. El-Badawy

Mansoura Engineering Journal

The International Roughness Index (IRI) serves as a crucial indicator for ride quality and user comfort. As road roughness escalates, road serviceability diminishes, resulting in reduced vehicle speed and increased travel time, and consequently higher carbon dioxide emissions. Predicting the IRI is of utmost importance for Pavement Management Systems and sustainable development overall. While numerous studies have forecasted the IRI of flexible pavements, there is a notable scarcity of research focusing on rigid pavement performance prediction. This study addresses the gap in predicting IRI for Continuous Reinforced Concrete Pavements (CRCP), an understudied aspect of pavement engineering. Leveraging the Long-Term Pavement …

Influence Of Macro-Synthetic Fibers On The Flexural Behavior Of High Strength Concrete Beams Reinforced With Gfrp Bars, Maryam M. Koura, Ahmed M. Tahwia, Mohamed H. Matthana

Mansoura Engineering Journal

Rusting of steel reinforcement in marine environments causes the overall destruction of reinforced concrete constructions; steel rebars in concrete members have been replaced with fiber-reinforced polymer (FRP) bars in recent years. To enhance the shear behavior of glass (GFRP) bars reinforced concrete (RC), macro-synthetic polyolefin (PO) fiber was added. These materials have a low modulus of elasticity, a high tensile strength, and a linear stress-strain response to full failure. This study investigates the effect of macro synthetic structural fibers on the post-cracking and deformability properties of high strength concrete reinforced with FRP bars without transverse reinforcement. Eight full-scale RC beams …