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Articles 61 - 90 of 3445
Full-Text Articles in Engineering
Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi
Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi
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Graph Neural Networks (GNNs) have increasingly gained popularity as tools for analyzing graph data in areas like biology, knowledge-graphs, social networks, biology, and recommendation systems. However, their vulnerability to adversarial attacks - small, targeted manipulations of graph structures or node features - raises serious concerns about their reliability in real-world applications. Existing defense strategies, such as adversarial training, edge filtering, low-rank approximations, and randomization-based methods, often suffer from high computational costs, scalability issues, or reduced clean-data performance. Unlike these methods, the proposed approach integrates multi-hop relationships, applies adaptive regularization, and maintains a balance between feature-based and structural embeddings, ensuring improved …
Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram
Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram
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In today's technological landscape, hardware devices are integral to critical applications such as industrial automation, autonomous vehicles, and medical equipment, relying on advanced platforms like FPGAs for core functionalities. However, the multi-stage manufacturing process, often distributed across various foundries, introduces substantial security risks, notably the potential for hardware Trojan insertion. These malicious modifications compromise the reliability and safety of hardware systems. This research addresses the detection of hardware Trojans through side-channel analysis, utilizing power and electromagnetic signal data, combined with meta-learning techniques, specifically model stacking. By employing diverse base models and a meta-model to consolidate predictions, this non-invasive approach effectively …
Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore
Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore
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Zinc sulfide has an infrared cutoff in the LWIR, but its low hardness makes it susceptible to rain erosion and abrasion. A composite of cerium oxide and zinc sulfide that retains an infrared cutoff in the LWIR, and with hardness higher than pure zinc sulfide is a potential solution to the rain erosion and abrasion issue. Several different processes were undertaken in this project to produce such a composite. The different reactions between ZnS and CeO2 were researched, along with the effects of different processing parameters. Composite samples were made that had a better hardness than zinc sulfide but did …
Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi
Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi
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Swift Heavy Ions (SHI) irradiation, characterized by high kinetic energy ions, induces significant material/structural modification, e.g., latent track. However, the intricate interaction among various physics, i.e., mechanical stress, phase transition, and heat transfer, has been ignored in the continuum-based approaches in favor of simplicity. Here, we developed a two-dimensional coupled phase-field inelastic-thermal spike (PF-iTS) model to investigate the effect of thermal crosstalk, elastic energy, and irradiation flux on latent track formation. A particular focus is placed on investigating the influence of internal mechanical stress on latent track formation. Simulation results reveal a shift in critical stopping energy and a reduction …
Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii
Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii
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An approach for the architecture optimization of emulator embedded neural networks is proposed. While the emulator embedded neural network has been shown to provide accurate predictions with suitable emulators, there is still a challenge regarding how to select the optimal hyperparameters of network architectures, such as, the number of neurons, layers, types of activation functions, etc. The selection of hyperparameters greatly affects the performance of the neural network model training both in terms of accuracy and efficiency. To address this challenge, this study proposes an algorithm that tests a range of hyperparameters and selects the best performing set. The algorithm …
Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes
Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes
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It is generally accepted that there exist two types of laminar separation bubbles (LSBs): short and long. The process by which a short LSB transitions to a long LSB is known as bursting. In this research, large eddy simulations (LES) are used to study the evolution of an LSB that develops along the suction surface of the L3FHW-LS at low Reynolds numbers. The L3FHW-LS is a new high-lift, high-work low-pressure turbine (LPT) blade designed at the Air Force Research Laboratory. The LSB is shown to burst over a critical range of Reynolds numbers. Bursting is discussed at length and its …
Deep Learning Based Optical Flow Analysis Of High-Speed Flows, Daniel H. Zhang, Zifeng Yang
Deep Learning Based Optical Flow Analysis Of High-Speed Flows, Daniel H. Zhang, Zifeng Yang
Mechanical and Materials Engineering Faculty Publications
Two-dimensional Rayleigh scattering imaging is utilized to quantify the high-speed flow velocity by employing deep learning based optical flow analysis, along with density fields from Rayleigh scattering intensity profiles.
Generating Blood Analog For Laser Induced Fluorescent Particle Image Velocimetry, Chungyiu Ma, Jared Chong, Hang Yi, Zifeng Yang, Luke Bramlage, Bryan Ludwig
Generating Blood Analog For Laser Induced Fluorescent Particle Image Velocimetry, Chungyiu Ma, Jared Chong, Hang Yi, Zifeng Yang, Luke Bramlage, Bryan Ludwig
Mechanical and Materials Engineering Faculty Publications
To mimic blood non-Newtonian viscosity features under designated temperatures from 305 to 315 K, transparent blood analogs were generated by the mixture of xanthan gum and deionized water with fluorescent particles for laser induced fluorescent particle image velocimetry.
3d Flow Field Quantification In An Artery Model Using Optical Flow Method Based On Simulated Multi-Angle Angiography, Zifeng Yang, Hang Yi, Luke Bramlage, Bryan Ludwig
3d Flow Field Quantification In An Artery Model Using Optical Flow Method Based On Simulated Multi-Angle Angiography, Zifeng Yang, Hang Yi, Luke Bramlage, Bryan Ludwig
Mechanical and Materials Engineering Faculty Publications
3D flow field in a numerically simulated arterial model is quantified using the three-dimensional optical flow method based on simulated simultaneous multi-angle X-ray angiography of the blood flow with contrast agent perfusions.
A Pade-Eno Flux Reconstruction For High-Speed Flows, Blake Martin
A Pade-Eno Flux Reconstruction For High-Speed Flows, Blake Martin
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The development of high order numerical schemes has been instrumental in advancing computational fluid dynamics (CFD), particularly for applications requiring high resolution of discontinuities and complex flow phenomena prevalent in high-speed flows. This thesis introduces the Pade-ENO scheme, a high-order method that integrates Essentially Non-Oscillatory (ENO) techniques with compact Pade stencils to achieve superior accuracy, up to 7th order, while maintaining stability in harsh environments. The scheme’s performance is evaluated through benchmark tests, including the advection equation, Burgers’ equation, and the Euler equations. For high Mach number flows, such as the sod shock tube the Pade-ENO method demonstrates its ability …
Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama
Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama
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In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key …
Fabricating And Analyzing Liquid And Polymer Electrolytes For Sodium Ion Batteries, Kekule Augustine
Fabricating And Analyzing Liquid And Polymer Electrolytes For Sodium Ion Batteries, Kekule Augustine
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The abundance and the cost-effectiveness of sodium resources have made sodium-ion batteries (SIBs) viable alternatives to lithium-ion batteries. Developing low-cost and high-performance electrolytes is one of the key areas for the advancement of SIB technology. The highly conductive liquid or solid electrolytes have the potential for practical sodium-ion battery applications. Long-term stability, alternative polymers, and full-cell integrations are other avenues that need further research to improve scalability and performance for SIBs. This research covers preparing and evaluating liquid and polymer electrolytes, with a focus on ionic conductivities. Liquid electrolytes were prepared by the dissolution of different sodium salts including NaCl, …
An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma
An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma
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Occupationally-acquired infections impact thousands of healthcare workers (HCWs) in the U.S., with many cases preventable through proper use of personal protective equipment (PPE). This study seeks to develop a robust system to enhance PPE compliance and reduce infection risks among HCWs. The objectives of this thesis are twofold: (1) to create a hybrid machine learning model that combines object detection and keypoint detection to ensure correct donning and doffing of PPE, and (2) to design a real-time feedback system using LED indicators and a display interface to offer actionable guidance to HCWs during PPE usage. The goal is to optimize …
An Enhanced Real-Time Object Detection Of Helmets And License Plates Using A Lightweight Yolov8 Deep Learning Model, Mounika Thatikonda
An Enhanced Real-Time Object Detection Of Helmets And License Plates Using A Lightweight Yolov8 Deep Learning Model, Mounika Thatikonda
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Traffic surveillance and enforcement heavily depend on the real-time detection of helmets and license plates, particularly in high-density urban environments. This study presents a dynamic and optimized lightweight model, the proposed G-YOLOv8n, designed for resource constrained edge devices like the Raspberry Pi. By integrating the GhostNet module into the YOLOv8n architecture, this research achieves a nearly 50% reduction in model size and computational load, while maintaining comparable detection accuracy to the original YOLOv8n. These enhancements enable real-time processing capabilities crucial for traffic monitoring operations. The growing demand for real-time, low-power solutions in intelligent transportation systems necessitates lightweight, efficient detection models. …
A Systematic Study Of Freezing Behavior In Earthworms In Response To Auditory And Vibratory Stimuli, Navjot Singh, A. Burton, Dragana Ivkovich Claflin
A Systematic Study Of Freezing Behavior In Earthworms In Response To Auditory And Vibratory Stimuli, Navjot Singh, A. Burton, Dragana Ivkovich Claflin
Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials
This study examined the parameters needed to reliably induce a freezing fear response to a predator-like auditory stimulus in the earthworm species Eisenia Fetida. Previous work from our lab found that a grunting noise was more reliable in causing freezing compared to a mole sound, i.e. artificial versus natural predators of E. Fetida (Worthen et al., 2024). In the present study, 8 amplitude levels of grunting sound were presented in either serial or random order. The speaker location was varied so that it either did or did not touch the apparatus, thus producing a mechanical vibration in addition to the …
Dual Airfoil Testing System, Zifeng Yang, Collin Charvat, Jack Stafford, Kyle Mathews, Logan Kelly
Dual Airfoil Testing System, Zifeng Yang, Collin Charvat, Jack Stafford, Kyle Mathews, Logan Kelly
Mechanical and Materials Engineering Faculty Publications
A dual airfoil testing system includes a platform including a frame defining a chamber that is configured to receive a horizontal flow of air for testing a first airfoil and a second airfoil contained in the chamber and a control system including a controller to control a first attack angle stepper motor, a second attack angle stepper motor, at least one gap stepper motor, and at least one stagger stepper motor. The controller is configured to automatically control and adjust the stepper motors to control and adjust the attack angle of the first airfoil, the attack angle of the second …
Void Fraction And Quality Correlation Analysis Using The Separated Flow Model For Pulsed-Power Heat Loads, Zachary Joseph Carner
Void Fraction And Quality Correlation Analysis Using The Separated Flow Model For Pulsed-Power Heat Loads, Zachary Joseph Carner
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Aircraft platforms are continually upgraded with increasingly high quantities of high-powered electronics. As such, efficient thermal management systems are crucially important to overcome system instabilities and support pulsed power profiles. To create effective thermal control systems, it is imperative to thoroughly examine and account for a variety of potential system behaviors caused by transient changes in the flow regime. If left unconstrained, these changes will create thermal instabilities, which can severely damage electronics and hurt the overall reliability of the aircraft. These instabilities can be described by both void fraction and quality. Electrical Capacitance Tomography (ECT) allows for the collection …
Mechanical Reliability Of Aerosol Jet Printed Sensors And Interconnects, Lemuel A. Duncan
Mechanical Reliability Of Aerosol Jet Printed Sensors And Interconnects, Lemuel A. Duncan
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Heterogeneous integration (HI) is currently being investigated to maintain the pace of technological progress in the electronics industry. With the recent acceleration witnessed in additive manufacturing (AM) technology, interest has been expressed in introducing aerosol jet (AJ) printing to the fabrication process for sensors and electronic packages. Integrating AM technology in these areas promises design flexibility and minimal material waste. Three AJ printed applications investigated in this work include strain sensors, electrical interconnects, and metal embedded chip assemblies. Before moving forward with the use of AJ printing in these applications, it is necessary to evaluate their performance under standard mechanical …
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
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This research explores the integration of knowledge graphs with large language models that have already been trained on a vast pool of unstructured text data. Large language models trained on this type of data have a tendency to hallucinate and produce factually inaccurate results. This behavior is primarily due to the data being trained is unstructured and huge text corpus, and large language model uses predictive text analysis methods to obtain a response. These issues can be addressed by applying Retrieval Augmented Generation and Fine-tuning to large language models, employing an underlying domainspecific knowledge graph. Integrating knowledge graph and large …
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
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Chronic Kidney Disease (CKD) poses significant health and financial threat to millions of patients all around the world. The irreversible nature of this disease not just leads to comorbid diseases like Diabetes Mellitus, Hypertension, Anemia, Bone Disease, Neurological Implants etc. It can permanently damage the kidney by progressing to Acute Kidney Injury (AKI) or End Stage Renal Diseases (ESRD). The risk factors of CKD become more dangerous as patients suffering from it have little to no idea about the presence of CKD in their body until it takes the shape of AKI or ESRD. There are severe economic burdens for …
Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih
Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih
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Implantable leads used in pacemakers, defibrillators, and cardiac resynchronization therapy are designed for in-vivo applications, yet their longevity is inevitably shaped by the conditions within the human body. The mechanical behavior of these leads can be affected over time, necessitating the evaluation of their residual properties. Two main insulators, silicone, and polyurethane are commonly used for the outer insulation of cardiac leads. Understanding the long-term performance of these insulators is crucial for ensuring the reliability and safety of cardiac implantable devices. The research aims to assess the long-term mechanical properties and performance of implantable leads utilized in cardiovascular implantable electronic …
Potential Role Of Ttt Complex In Regulating Dna Replication Checkpoint In The Fission Yeast Schizosaccharomyces Pombe, Sankhadip Bhadra
Potential Role Of Ttt Complex In Regulating Dna Replication Checkpoint In The Fission Yeast Schizosaccharomyces Pombe, Sankhadip Bhadra
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DNA replication can be perturbed by various agents that slow or stall the replication forks, causing replication stress. If undetected, stressed forks may collapse, causing mutagenic DNA damage or cell death. In response to replication stress and DNA damage, the eukaryotic cell activates the DNA replication checkpoint (DRC) and DNA damage checkpoint (DDC) pathways to promote DNA synthesis, repair, and cell survival. The two cell cycle checkpoint pathways are controlled by the protein sensor kinases Rad3 (hATR/scMec1) and Tel1 (hATM/scTel1) in fission yeast, although Tel1 plays a minimal role in checkpoint functions. Rad3 and Tel1 belong to a family of …
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
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Hardware Trojans are malicious circuits, hidden in integrated circuits (ICs) which pose a significant threat to security. Detection of hardware Trojans is important to build trust, verify, and make the semiconductor ICs process secure. The existing hardware Trojan detection methods are generally destructive, require intricate comparisons, or require a long time for reverse engineering. In the initial phase of this study, the substitution of supervised hardware Trojan detection methods in ASICs chips is explored with unsupervised approaches, thereby eliminating the dependence on golden references. The Trojan detection uses a ring oscillator (RO) based on NAND as the power monitor. Frequency …
Investigation Of Spalart-Allmaras Turbulence Model For Vortex Flows, Abigail Rayna Kerestes
Investigation Of Spalart-Allmaras Turbulence Model For Vortex Flows, Abigail Rayna Kerestes
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Conventional turbulence models often predict behaviors opposite as to what is observed in flows subject to rotation. In this type of flow scenario, rotation typically induces turbulence suppression. To address this limitation, a modification to the Spalart Allmaras Model with Rotation Correction (SA-R) was proposed to enhance the original Spalart Allmaras Model’s sensitivity to rotation and curvature. To test the validity and accuracy of this modification, two cases were investigated. The first case involved an axisymmetric rotating pipe. A Reynolds Number of 37,000 was implemented and the initial and boundary conditions established by Zaets et. al. were utilized. Initially non-rotating, …
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
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The effectiveness of a deployed knowledge graph is commonly evaluated with defined use-cases from domain experts. This poses challenges during the development cycle in determining how to represent data. Developers of a knowledge graph can optionally include semantics into a knowledge graph by abstracting the data representation in such a way that mirrors information as it exists in the real world. Consequently, the abstraction is represented by additional layers, resulting in performant differences in knowledge graph embedding; such as, the embedded model's ability to infer facts between entities through link predictions. This thesis presents a comprehensive analysis of the performance …
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
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Semiconductor microelectronics integrated circuits (ICs) are increasingly integrated into modern life-critical applications, from intelligent infrastructure and consumer electronics to the Internet of Things (IoT) and advanced military and medical systems. Unfortunately, these applications are vulnerable to new hardware security attacks, including microelectronics counterfeits and hardware modification attacks. Physical Unclonable Functions (PUFs) are state-of-the-art hardware security solutions that utilize process variations of integrated circuits for device authentication, secret key generation, and microelectronics counterfeit detection. The negative impact of aging on Static Random Access Memory Physical Unclonable Functions (SRAM PUFs) has significant consequences for microelectronics authentication, security, and reliability. This research thoroughly …
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
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Hardware components are becoming prone to threats with increasing technological advances. Malicious modifications to such components are increasing and are known as hardware Trojans. Traditional approaches rely on functional assessments and are not sufficient to detect such malicious actions of Trojans. Machine learning (ML) assisted techniques play a vital role in the overall detection and improvement of Trojan. Our novel approach using various ML models brings an improvement in hardware Trojan identification with power signal side channel analysis. This study brings a paradigm shift in the improvement of Trojan detection in integrated circuits (ICs). In addition to this, our further …
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
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This research illustrates a high-security wireless communication method using a joint radar/communication waveform, addressing the vulnerability of traditional low probability of detection (LPD) waveforms to hostile receiver detection via cyclostationary processing (CSP). To mitigate this risk, RF steganography is used, concealing communication signals within linear frequency modulation (LFM) radar signals. The method integrates reduced phase-shift keying (RPSK) modulation and variable symbol duration, ensuring secure transmission while evading detection. Implementation is validated through software-defined radios (SDRs), demonstrating effectiveness in covert communication scenarios. Results include analysis of message reception and cyclostationary features, highlighting the method's ability to conceal messages from hostile receivers. …
Experimental Validation Of Two Highly Loaded Low Pressure Turbine Blades At High Speed Low Reynolds Number Conditions, Ryan Sauder
Experimental Validation Of Two Highly Loaded Low Pressure Turbine Blades At High Speed Low Reynolds Number Conditions, Ryan Sauder
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In the constant search for more efficient engines, one approach to gain performance is to reduce the weight of the low pressure turbine (LPT) module. This module can account for up to 30% of the total engine weight [1], and a reduction in LPT weight results in clear gains to engine performance and a reduction in engine cost. High lift airfoils accomplish this weight reduction by each blade extracting a larger amount of work from the flow and thus requiring fewer blades to drive the compressor when compared to conventional blades. However, high lift LPT blades, quantified by a high …
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
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Performing automatic target recognition (ATR) on full-size aircraft targets using inverse synthetic aperture radar (ISAR) data is challenging and expensive. The use of scale models and radar systems of such large targets saves time and reduces facility requirements. This study examines the feasibility of performing ATR on 1:144 scale model airplanes at Ka-band. The scale model and Ka-band radar simulate the collection of full-scale targets at VHF-band. The phase history measurement collections were completed in the Sensors and Signals Exploitation Laboratory (SSEL) at Wright State University. To ensure sufficient data for training and testing, the phase history data was augmented …