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Full-Text Articles in Engineering

Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson Jan 2023

Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson

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In fluid flow experiments, there have been numerous techniques developed over the years to measure velocity. Most popular techniques are non-intrusive such as particle image velocimetry (PIV), but these techniques are not suitable for all applications. For instance, PIV cannot be used in examining in-vivo measurements since the laser is not able to penetrate through the patient, which is why medical applications typically use X-rays. However, the images obtained from X-rays, in particular digital subtraction angiography, are projective images which compress 3D flow features onto a 2D image. Therefore, when intensity techniques, such as optical flow method (OFM), are applied …

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A Machine Learning Framework For Hypersonic Vehicle Design Exploration, Atticus Beachy Jan 2023

A Machine Learning Framework For Hypersonic Vehicle Design Exploration, Atticus Beachy

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The design of Hypersonic Vehicles (HVs) requires meeting multiple unconventional and often conflicting design requirements in a hostile, high-energy environment. The most fundamental difference between ordinary aerospace design and hypersonic flight is that the extreme conditions of hypersonic flight require parts to perform multiple functions and be tightly integrated, resulting in significant coupled effects. Critical couplings among the disciplines of aerodynamics, structures, propulsion, and thermodynamics must be investigated in the early stages of design exploration to reduce the risk of requiring major design changes and cost overruns later. In addition, due to a lack of validated test data within the …

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Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green Jan 2023

Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green

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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …

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Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward Jan 2023

Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward

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In the present work, the variation in through-thickness residual stress profiles driven by elastic anisotropy is investigated using the incremental hole-drilling method. The standardized hole-drilling technique allows for the calculation of in-plane stresses based on measured surface strains, however, these calculations assume elastic isotropy. The assumption of elastic isotropy allows for the material constants to be reduced down to two values, however, this assumption is invalid for many materials used in aerospace design. These materials are often times elastically anisotropic, which leads to inaccuracy and uncertainty in measured stress profiles. An interference fit ring and plug sample was designed, using …

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Identifying A Novel Ferrocene Derivative As A K-Ras Inhibitor, Kristen Marie Rehl Jan 2023

Identifying A Novel Ferrocene Derivative As A K-Ras Inhibitor, Kristen Marie Rehl

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Ras proteins are small GTPases that regulate cell proliferation, differentiation and survival at the plasma membrane (PM). There are three Ras isoforms ubiquitously expressed in mammalian cells: H-, N- and K-Ras. Constitutively active Ras mutations are found in ~19% of all human cancers, with ~75% of those being in K-Ras. There are K-Ras inhibitors in clinic but they only target the oncogenic K-RasG12C mutant, which only makes up a small sub-set of K-Ras-driven cancers. Thus, there still exists a need for a pan anti-K-Ras drug. Ferrocene derivatives are a class of compounds that have been shown to inhibit the growth …

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Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo Jan 2023

Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo

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Alzheimer’s disease (AD) is the seventh leading cause of death globally with an estimated 6.5 million Americans aged 65 and above living with Alzheimer’s dementia in 2022 and at a projected national cost of $321 billion. AD is characterized by a progressive and irreversible neurodegenerative dysfunction with clinical symptoms such as deterioration in cognition and memory loss. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-site, public-private global research initiative that supports both investigation and development of treatments that slow or terminate AD progression. The study included 60 participants, comprising 30 AD and 30 control cohorts respectively. All participants were …

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Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee Jan 2023

Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee

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This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …

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Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers Jan 2023

Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers

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Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …

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Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan Jan 2023

Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan

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Additive Manufacturing (AM) methods are promising in applications where complex part geometries, exotic materials and small lot sizes are required. Aerospace manufacturing stands to use AM methods extensively in the future, and frequently requires temperature- and corrosion-resistant alloy materials such as Inconel 718. However, the microstructural evolution of Inconel 718 during additive manufacturing is poorly understood and depends on part size and shape. We studied the microstructure of Inconel 718 parts manufactured by Laser Powder Bed Fusion in order to further elucidate these dependencies. Microstructural analysis, SEM imaging, EBSD scans and Microhardness testing were performed.

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Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy Jan 2023

Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy

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High concentrations of phosphate are known to adversely affect the environment. Excess phosphate can lead to eutrophication that eventually fosters uncontrollable growth of aquatic plants and algae. This can result in depletion of oxygen content which adversely impacts underwater organism’s survival rates. Metal organic frameworks (MOFs) consist of organic linkers in conjunction with metal ions or clusters arranged within a crystalline structure. They are highly porous and have larger surface area due to their ability to possess extensive void spaces while remaining bulky in nature. MOFs can absorb phosphate from aqueous solutions. We have investigated the use of commercially available …

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Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball Jan 2023

Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball

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A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated …

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Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark Jan 2023

Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark

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This work is investigating a dual mode Rankine cycle for aircraft applications, specifically meeting vehicle thermal and power requirements. This multiconfigurational approach allows the Thermal Management System (TMS) to be controlled based on aircraft needs. In this design, waste heat is removed from critical areas of the aircraft (e.g., propulsion, structure, subsystems) using the fuel as a heat sink. Hot fuel is then forced through a heat exchanger actively boiling water. The vapor byproduct is fed to a turbine coupled to a generator, providing power. The low-pressure steam is then condensed using cold fuel drawn from its tank; however, when …

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Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh Jan 2023

Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh

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The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …

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Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman Jan 2023

Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman

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Insider threats to information security have become a burden for organizations. Understanding insider activities leads to an effective improvement in identifying insider attacks and limits their threats. This dissertation presents three systems to detect insider threats effectively. The aim is to reduce the false negative rate (FNR), provide better dataset use, and reduce dimensionality and zero padding effects. The systems developed utilize deep learning techniques and are evaluated using the CERT 4.2 dataset. The dataset is analyzed and reformed so that each row represents a variable length sample of user activities. Two data representations are implemented to model extracted features …

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Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner Jan 2023

Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner

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Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, …

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A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham Jan 2023

A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham

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The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …

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Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore Jan 2023

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

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In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

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Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson Jan 2023

Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson

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Automated vehicles pose challenges in various research domains, including robotics, machine learning, computer vision, public safety, system certification, and beyond. These vehicles autonomously handle navigation and locomotion, often requiring minimal user interaction, and can operate on land, in water, or in the air. In the context of aircraft, one specific application is Automated Aerial Refueling (AAR). Traditional aerial refueling involves a "tanker" aircraft using a mechanism, such as a rigid boom arm or a flexible hose, to transfer fuel to another aircraft designated as the "receiver". For AAR, the boom arm may be maneuvered automatically, or in certain instances the …

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Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management System, Danielle D. Hollon Jan 2023

Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management System, Danielle D. Hollon

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Icing, or the formation of ice from water via freezing or water vapor via desublimation, is a phenomenon that commonly occurs within air cycle-based refrigeration systems and requires thermal control that limits system performance. In aircraft applications icing frequently occurs in the heat exchangers and turbine(s) that are part of the air cycle machine, the refrigeration unit of the environmental control system. Traditionally, water vapor is removed from an air cycle machine via condensing in a heat exchanger and subsequent high-pressure water separation. This approach is not capable of removing all of the vapor present at low altitude conditions, corresponding …

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Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams Jan 2023

Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams

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Obtaining accurate inferences from deep neural networks is difficult when models are trained on instances with conflicting labels. Algorithmic recognition of online hate speech illustrates this. No human annotator is perfectly reliable, so multiple annotators evaluate and label online posts in a corpus. Labeling scheme limitations, differences in annotators' beliefs, and limits to annotators' honesty and carefulness cause some labels to disagree. Consequently, decisive and accurate inferences become less likely. Some practical applications such as social research can tolerate some indecisiveness. However, an online platform using an indecisive classifier for automated content moderation could create more problems than it solves. …

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Hierarchical Structure And Properties Of The Bone At Nano Level, Farah Hamandi, Tarun Goswami Nov 2022

Hierarchical Structure And Properties Of The Bone At Nano Level, Farah Hamandi, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Bone is a highly hierarchical complex structure that consists of organic and mineral components represented by collagen molecules (CM) and hydroxyapatite crystals (HAC), respectively. The nanostructure of bone can significantly affect its mechanical properties. There is a lack of understanding how collagen fibrils (CF) in different orientations may affect the mechanical properties of the bone. The objective of this study is to investigate the effect of interaction, orientation, and hydration on atomic models of the bone composed of collagen helix (CH) and HAC, using molecular dynamics simulations and therefrom bone-related disease origins. The results demonstrate that the mechanical properties of …

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Residual Properties Of Silicone (Med-4719) Lead With Leads From Retrieved Devices, Anmar Salih, Tarun Goswami Nov 2022

Residual Properties Of Silicone (Med-4719) Lead With Leads From Retrieved Devices, Anmar Salih, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Leads are designed for in vivo applications, however, for a definite period of time. In-vivo environment affects the mechanical behavior of implantable devices, therefore, there is a need to evaluate the residual properties of implantable leads used with pacemakers, defibrillator and neuro-stimulators. Silicone (MED-4719) lead is widely used in cardiac implantable electronic devices made by different manufacturers. . We collected 150 devices (with or without leads) from Anatomical Gift Program of the Wright State University. The objective of this study was to investigate the residual properties of Silicone (MED-4719) lead with different in vivo exposure time and compare the properties …

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Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang Nov 2022

Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang

Computer Science and Engineering Faculty Publications

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …

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Machine Learning For Aiding Blood Flow Velocity Estimation Based On Angiography, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang Oct 2022

Machine Learning For Aiding Blood Flow Velocity Estimation Based On Angiography, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang

Computer Science and Engineering Faculty Publications

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …

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Traumatic Brain Injury Biomarkers, Simulations And Kinetics, Celeste Hicks, Akshima Dhiman, Chauntel Barrymore, Tarun Goswami Oct 2022

Traumatic Brain Injury Biomarkers, Simulations And Kinetics, Celeste Hicks, Akshima Dhiman, Chauntel Barrymore, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

This paper reviews the predictive capabilities of blood-based biomarkers to quantify traumatic brain injury (TBI). Biomarkers for concussive conditions also known as mild, to moderate and severe TBI identified along with post-traumatic stress disorder (PTSD) and chronic traumatic encephalopathy (CTE) that occur due to repeated blows to the head during one’s lifetime. Since the pathways of these biomarkers into the blood are not fully understood whether there is disruption in the blood–brain barrier (BBB) and the time it takes after injury for the expression of the biomarkers to be able to predict the injury effectively, there is a need to …

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Therapeutic Efficacies Of Nano Carriers In Delivering Drugs, Bailey Krueger, Taylor Frazier, Sheila Galbreath, Tarun Goswami Oct 2022

Therapeutic Efficacies Of Nano Carriers In Delivering Drugs, Bailey Krueger, Taylor Frazier, Sheila Galbreath, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

The drug release rates of poorly soluble medications such as doxorubicin has been investigated in this paper. Since the drug was fixed, different carriers used to deliver it and their release rates compiled from literature were evaluated in this paper. Even though targeting of drugs is very important in drug delivery, it is not within the scope of this paper. However, functionalization of the carrier may provide this benefit, those constructs are included for comparison in terms of hybrid constructs. Dendrimer, micelles and hybrid constructs used in the delivery of doxorubicin compared in this paper with respect to carrier size …

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Therapeutic Efficacies Of Nano Carriers In Delivering Drugs, Bailey Krueger, Taylor Frazier, Sheila Galbreath, Tarun Goswami Oct 2022

Therapeutic Efficacies Of Nano Carriers In Delivering Drugs, Bailey Krueger, Taylor Frazier, Sheila Galbreath, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

The drug release rates of poorly soluble medications such as doxorubicin has been investigated in this paper. Since the drug was fixed, different carriers used to deliver it and their release rates compiled from literature were evaluated in this paper. Even though targeting of drugs is very important in drug delivery, it is not within the scope of this paper. However, functionalization of the carrier may provide this benefit, those constructs are included for comparison in terms of hybrid constructs. Dendrimer, micelles and hybrid constructs used in the delivery of doxorubicin compared in this paper with respect to carrier size …

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Safe Zones In Hip-Implant Designs To Resist Dislocation, Himanshu Bhatt, Tarun Goswami Oct 2022

Safe Zones In Hip-Implant Designs To Resist Dislocation, Himanshu Bhatt, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Major contributing parameters to hip implant dislocation include preoperative, intra-operative and post-operative factors. Implant geometry are design as well as non-design related. Femoral and acetabular component design features causing dislocation and/or resisting it are elucidated. Twelve implants were designed during this investigation were analyzed for dislocation resistance. A safe zone, establishes combinations of implant dimensions, was analyzed for all the 12 implants where implants were dislocation resistant. Head diameters between 26 mm to 32 mm, neck diameters closer to 14 mm, and neck angle between 25 to 35º were examined to be the safest ranges for hip implant designs.

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Toward Mental Effort Measurement Using Electrodermal Activity Features, William Romine, Noah Schroeder, Tanvi Banerjee, Josephine Graft Sep 2022

Toward Mental Effort Measurement Using Electrodermal Activity Features, William Romine, Noah Schroeder, Tanvi Banerjee, Josephine Graft

Computer Science and Engineering Faculty Publications

The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analysis of over 92 h of data collected with the Empatica E4 on a single participant across 91 different activities, we report on the efficacy of using EDA features getting at signal intensity, signal dispersion, and peak intensity for prediction of the participant's self-reported mental effort. We implemented the logistic regression algorithm as an interpretable machine learning approach and found …

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Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee Sep 2022

Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee

Computer Science and Engineering Faculty Publications

Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalization. Patients with heart failure can have both cardiovascular as well as non-cardiovascular comorbidities. Clinical notes of patients with heart failure can be analyzed to gain insight into the topics discussed in these notes and the major comorbidities in these patients. In this regard, we apply machine learning techniques, such as topic modeling, to identify the major themes found in the clinical notes specific to the procedures performed on 1,200 patients …

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