Physical Sciences and Mathematics Commons^™

Numerical Study Of Owls’ Leading-Edge Serrations, Asif Shahriar Nafi

Electronic Theses and Dissertations

The silent flight ability of owls is often attributed to their unique wing morphology and its interaction with their wingbeat kinematics. Among these distinctive morphological features, leading-edge serrations stand out – these are rigid, miniature, hook-like patterns located at the leading edge of the primary feathers of their wings. It had been hypothesized that these leading-edge serrations serve as a passive flow control mechanism, influencing the aerodynamic performance and potentially affecting the boundary layer development over the wing, subsequently influencing wake flow dynamics. Despite being the subject of research spanning multiple decades, a consensus regarding the aerodynamic mechanisms underpinning owls’ …

Artificial Intelligence-Enabled Exploratory Cyber-Physical Safety Analyzer Framework For Civilian Urban Air Mobility, Md. Shirajum Munir, Sumit Howlader Dipro, Kamrul Hasan, Tariqul Islam, Sachin Shetty

VMASC Publications

Urban air mobility (UAM) has become a potential candidate for civilization for serving smart citizens, such as through delivery, surveillance, and air taxis. However, safety concerns have grown since commercial UAM uses a publicly available communication infrastructure that enhances the risk of jamming and spoofing attacks to steal or crash crafts in UAM. To protect commercial UAM from cyberattacks and theft, this work proposes an artificial intelligence (AI)-enabled exploratory cyber-physical safety analyzer framework. The proposed framework devises supervised learning-based AI schemes such as decision tree, random forests, logistic regression, K-nearest neighbors (KNN), and long short-term memory (LSTM) for predicting and …

Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

This paper expands the authors’ prior work[1], which focuses on developing a convolutional neural network (CNN) model capable of mapping time-averaged, unsteady Reynold’s-averaged Navier-Stokes (URANS) simulations to higher resolution results informed by time-averaged detached eddy simulations (DES). The authors present improvements over the prior CNN autoencoder model that result from hyperparameter optimization, increased data set augmentation through the adoption of a patch-wise training approach, and the predictions of primitive variables rather than vorticity magnitude. The training of the CNN model developed in this study uses the same URANS and DES simulations of a transonic flow around several NACA 4-digit airfoils …

Convolutional-Neural-Network-Based Des-Level Aerodynamic Flow Field Generation From Urans Data, John P. Romano, Oktay Baysal, Alec C. Brodeur

Mechanical & Aerospace Engineering Faculty Publications

The present paper culminates several investigations into the use of convolutional neural networks (CNNs) as a post-processing step to improve the accuracy of unsteady Reynolds-averaged Navier–Stokes (URANS) simulations for subsonic flows over airfoils at low angles of attack. Time-averaged detached eddy simulation (DES)-generated flow fields serve as the target data for creating and training CNN models. CNN post-processing generates flow-field data comparable to DES resolution, but after using only URANS-level resources and properly training CNN models. This document outlines the underlying theory and progress toward the goal of improving URANS simulations by looking at flow predictions for a class of …

Optimization Of Ported Cfd Kernels On Intel Data Center Gpu Max 1550 Using Oneapi Esimd, Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Christoph Bauinger, Xiao Zhu

Computer Science Faculty Publications

We describe our experience porting FUN3D’s CUDA-optimized kernels to Intel oneAPI SYCL.We faced several challenges, including foremost the suboptimal performance of the oneAPI code on Intel’s new data center GPU. Suboptimal performance of the oneAPI code was due primarily to high register spills, memory latency, and poor vectorization. We addressed these issues by implementing the kernels using Intel oneAPI’s Explicit SIMD SYCL extension (ESIMD) API. The ESIMD API enables the writing of explicitly vectorized kernel code, gives more precise control over register usage and prefetching, and better handles thread divergence compared to SYCL. The ESIMD code outperforms the optimized SYCL …

Underwater Communication Acoustic Transducers: A Technology Review, Laila Shams, Tian-Bing Xu, Zhongqing Su (Ed.), Branko Glisic (Ed.), Maria Pina Limongelli (Ed.)

Mechanical & Aerospace Engineering Faculty Publications

This paper provides a comprehensive review on transducer technologies for underwater communications. The popularly used communication transducers, such as piezoelectric acoustic transducers, electromagnetic acoustic transducers, and acousto-optic devices are reviewed in detail. The reasons that common air communication technologies are invalid die to the differences between the media of air and water are addresses. Because of the abilities to overcome challenges the complexity of marine environments, piezoelectric acoustic transducers are playing the major underwater communication roles for science, surveillance, and Naval missions. The configuration and material properties of piezoelectric transducers effects on signal output power, beamwidth, amplitude, and other properties …

Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi

Mechanical & Aerospace Engineering Faculty Publications

The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to …

Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo

Student Works

Aircraft taxiing operations in the aerodrome were identified to consume the most jet fuel apart from the cruise phase of the flight. This was also well supported by various research associating taxi operations at large, congested airports, with high jet fuel consumption, high carbon emissions, and noise pollution. Existing literature recognised the potential to address the environmental issues of aerodrome taxi operations by operating External or Onboard Aircraft Ground Propulsion Systems (AGPS). Designed to power aircraft with sources other than their main engines, external Aircraft Ground Power Systems (AGPS) have shown the potential to significantly cut jet fuel consumption and …

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Molecular Dynamics Modeling Of Polymers For Aerospace Composites, Swapnil Sambhaji Bamane

Dissertations, Master's Theses and Master's Reports

Polymer matrix composite materials are widely used as structural materials in aerospace and aeronautical vehicles. Resin/reinforcement wetting and the effect of polymerization on the thermo-mechanical properties of the resin are key parameters in the manufacturing of aerospace composite materials. Determining the contact angle between combinations of liquid resin and reinforcement surfaces is a common method for quantifying wettability. It is challenging to determine contact angle values experimentally of high-performance resins on CNT materials such as CNT, graphene, bundles or yarns, and BNNT surfaces. It is also experimentally difficult to determine the effect of polymerization reaction on material properties of a …

Nasa Student Launch - Payload, Eli Kirk

All Undergraduate Projects

A team of mechanical engineering, physics, and computer science students from Central Washington University have constructed a fully functional subscale model rocket to be flown at the NASA Student Launch competition. The rocket’s payload was designed to open the nose cone and take a photo of the rocket’s surroundings after descending from the launch. Smaller parts were constructed through machining and 3D printing that will be added to the purchased major component, the linear actuator, in order to perform the required tasks. These tasks are signaled by an attached electronics board, which will receive an RF command remotely, execute code, …

Probabilistic Short Term Solar Driver Forecasting With Neural Network Ensembles, Joshua Daniell

Graduate Theses, Dissertations, and Problem Reports

Commonly utilized space weather indices and proxies drive predictive models for thermosphere density, directly impacting objects in low-Earth orbit (LEO) by influencing atmospheric drag forces. A set of solar proxies and indices (drivers), F_10.7, S_10.7, M_10.7, and Y_10.7, are created from a mixture of ground based radio observations and satellite instrument data. These solar drivers represent heating in various levels of the thermosphere and are used as inputs by the JB2008 empirical thermosphere density model. The United States Air Force (USAF) operational High Accuracy Satellite Drag Model (HASDM) relies on JB2008, and …

Accuracy Assessment Of The Ebee Using Rtk And Ppk Corrections Methods As A Function Of Distance To A Gnss Base Station, Joseph Cerreta, David Thirtyacre, Peter Miller, Scott S. Burgess, William J. Austin

International Journal of Aviation, Aeronautics, and Aerospace

The use of unmanned aircraft systems to collect data for photogrammetry models has grown significantly in recent years. The accuracy of a photogrammetric model can depend on image georeferencing. The distance from a reference base station can affect the accuracy of the results. Positioning corrections data relies on precise timing measurements of satellite signals. The signals travel through the Earth's atmosphere, which introduces errors due to ionospheric and tropospheric delays. The aim of this research was to examine the eBee X and its global GNSS accuracy by comparing the RTK and PPK methods at different base station distances in photogrammetry …

Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal

International Journal of Aviation, Aeronautics, and Aerospace

Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.

We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …

A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu Phd, Irene Moulitsas Phd

Journal of Aviation/Aerospace Education & Research

This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Stratospheric Glider Measurements Of Atmospheric Parameters, Anisa Haghighi

Theses and Dissertations--Mechanical Engineering

In June 2021 a series of high altitude flights were conducted in Spaceport America, NM, using a balloon launched Uncrewed Aircraft System (UAS) to assess its capability to conduct measurements of various atmospheric properties and study turbulence in the troposphere and lower stratosphere. This UAS descends using an automated flight trajectory. The instruments aboard included a NASA-developed infrasonic microphone to evaluate its remote turbulence detection capabilities and a five-hole probe capable of measuring the in situ wind vector. Also on board were temperature, humidity and wind profile sensors. This document focuses on the atmospheric properties measured at high altitudes, the …

Impact Of Spallation And Internal Radiation On Fibrous Ablative Materials, Raghava Sai Chaitanya Davuluri

Theses and Dissertations--Mechanical Engineering

Space vehicles are equipped with Thermal Protection Systems (TPS) that encounter high heat rates and protect the payload while entering a planetary atmosphere. For most missions that interest NASA, ablative materials are used as TPS. These materials undergo several mass and energy transfer mechanisms to absorb intense heat. The size and construction of the TPS are based on the composition of the planetary atmosphere and the impact of various ablative mechanisms on the flow field and the material. Therefore, it is essential to quantify the rates of different ablative phenomena to model TPS accurately. In this work, the impact of …

Jet Noise Reduction: A Fresh Start, Christopher K. Tam, Fang Q. Hu

Mathematics & Statistics Faculty Publications

Attempts to reduce jet noise began some 70 years ago. In the literature, there have been many publications written on this topic. By now, it is common knowledge that jet noise consists of a number of components. They possess different spectral and radiation characteristics and are generated by different mechanisms. It appears then that one may aim at the suppression of the noise of a single component instead of trying to reduce jet noise overall. The objective of the present project is to reduce large turbulence structures noise. It is the most dominant noise component radiating in the downstream direction. …

Actively Guided Cansats For Assisting Localization And Mapping In Unstructured And Unknown Environments, Cary Chun, M. Hassan Tanveer

Symposium of Student Scholars

When navigating in unknown and unstructured environments, Unmanned Arial Vehicles (UAVs) can struggle when attempting to preform Simultaneous Localization and Mapping (SLAM) operations. Particularly challenging circumstance arise when an UAV may need to land or otherwise navigate through treacherous environments. As the primary UAV may be too large and unwieldly to safely investigate in these types of situations, this research effort proposes the use of actively guided CanSats for assisting in localization and mapping of unstructured environments. A complex UAV could carry multiple of these SLAM capable CanSats, and when additional mapping and localization capabilities where required, the CanSat would …

Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky

Doctoral Dissertations

The adoption of mathematically formal simulation-based optimization approaches within aerodynamic design depends upon a delicate balance of affordability and accessibility. Techniques are needed to accelerate the simulation-based optimization process, but they must remain approachable enough for the implementation time to not eliminate the cost savings or act as a barrier to adoption.

This dissertation introduces a reduced-order model technique for accelerating fixed-point iterative solvers (e.g. such as those employed to solve primal equations, sensitivity equations, design equations, and their combination). The reduced-order model-based acceleration technique collects snapshots of early iteration (pre-convergent) solutions and residuals and then uses them to project …

Manufacturability And Analysis Of Topologically Optimized Continuous Fiber Reinforced Composites, Jesus A. Ferrand

Doctoral Dissertations and Master's Theses

Researchers are unlocking the potential of Continuous Fiber Reinforced Composites for producing components with greater strength-to-weight ratios than state of the art metal alloys and unidirectional composites. The key is the emerging technology of topology optimization and advances in additive manufacturing. Topology optimization can fine tune component geometry and fiber placement all while satisfying stress constraints. However, the technology cannot yet robustly guarantee manufacturability. For this reason, substantial post-processing of an optimized design consisting of manual fiber replacement and subsequent Finite Element Analysis (FEA) is still required.

To automate this post-processing in two dimensions, two (2) algorithms were developed. The …

Aircraft Engine Particulate Matter Emissions From Sustainable Aviation Fuels: Results From Ground-Based Measurements During The Nasa/Dlr Campaign Eclif2/Nd-Max, Tobias Schripp, Bruce E. Anderson, Uwe Bauder, Bastian Rauch, Joel C. Corbin, Greg J. Smallwood, Prem Lobo, Ewan C. Crosbie, Michael A. Shook, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Philip D. Whitefield, Claire E. Robinson

Chemistry Faculty Research & Creative Works

The use of alternative jet fuels by commercial aviation has increased substantially in recent years. Beside the reduction of carbon dioxide emission, the use of sustainable aviation fuels (SAF) may have a positive impact on the reduction of particulate emissions. This study summarizes the results from a ground-based measurement activity conducted in January 2018 as part of the ECLIF2/ND-MAX campaign in Ramstein, Germany. Two fossil reference kerosenes and three different blends with the renewable fuel component HEFA-SPK (Hydroprocessed Esters and Fatty Acids Synthetic Paraffinic Kerosene) were burned in an A320 with V2527-A5 engines to investigate the effect of fuel naphthalene/aromatic …

Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen

Doctoral Dissertations and Master's Theses

Accurate characterization of fragment fly-out properties from high-speed warhead detonations is essential for estimation of collateral damage and lethality for a given weapon. Real warhead dynamic detonation tests are rare, costly, and often unrealizable with current technology, leaving fragmentation experiments limited to static arena tests and numerical simulations. Stereoscopic imaging techniques can now provide static arena tests with time-dependent tracks of individual fragments, each with characteristics such as fragment IDs and their respective position vector. Simulation methods can account for the dynamic case but can exclude relevant dynamics experienced in real-life warhead detonations. This research leverages machine learning methodologies to …

A Data Driven Modeling Approach For Store Distributed Load And Trajectory Prediction, Nicholas Peters

Doctoral Dissertations and Master's Theses

The task of achieving successful store separation from aircraft and spacecraft has historically been and continues to be, a critical issue for the aerospace industry. Whether it be from store-on-store wake interactions, store-parent body interactions or free stream turbulence, a failed case of store separation poses a serious risk to aircraft operators. Cases of failed store separation do not simply imply missing an intended target, but also bring the risk of collision with, and destruction of, the parent body vehicle. Given this risk, numerous well-tested procedures have been developed to help analyze store separation within the safe confines of wind …

A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail

Theses and Dissertations

Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Rocket Measurements Of Electron Energy Spectra From Earth’S Photoelectron Production Layer, Glyn A. Collinson, Alex Glocer, Dennis Chornay, Robert Mitchell, Rob Pfaff, Tim Cameron, Nasa Goddard Space Flight Center, Rudy A. Frahm, Traci Rosnack, Chris Pirner, Ted Gass, Jim Clemmons, Aroh Barjatya, Steven Martin, Hassanali Akbari, Shantanab Debchoudhury, Rachel Conway, Francis Eparvier, Eftyhia Zesta, Nikolaos Paschalidis

Publications

Photoelectrons are crucial to atmospheric physics. They heat the atmosphere, strengthen 28 planetary ambipolar electric fields, and enhance the outflow of ions to space. However, 29 there exist only a handful of measurements of their energy spectrum near the peak of 30 photoproduction. We present calibrated energy spectra of pristine photoelectrons at their 31 source by a prototype Dual Electrostatic Analyzer (DESA) instrument flown on July 11 32 2021 aboard the Dynamo-2 sounding rocket (NASA № 36.357). Photopeaks arising from 33 30.4nm He-II spectral line were observed throughout the flight above 120km. DESA also 34 successfully resolved the rarely observed …

Review On 11 Years Of Implementation Of Strategic Priority Program (Spp) On Space Science And Its Prospect, Ji Wu, Chi Wang, Quanlin Fan

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Strategic Priority Program (SPP) on space science is a series scientific satellites program implemented by Chinese Academy of Science (CAS) since 2011. Since then, it has become the only and systematic space science satellite series of China. The article reviews the major scientific outcomes and technological breakthroughs in its first phase (2011-2016), the ongoing mission developments of its second phase (2017-2024), and the selected mission proposals for future space science program up to 2030. In 2016, President Xi has addressed:"to promote full developments of space science, space technology and space application," where he put space science in the first …

Thoughts On Space Science Development, Yidong Gu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Space science is a large-scale activity by using space vehicles to explore the universe and natural laws and carry out special experiments, which has made great contributions to the development of contemporary science. This paper outlines the major breakthroughs in international space science, analyzes the context and new trends of space science and manned exploration activities, reviews the development achievements of space science in China in the past 20 years, puts forward existing problems and gaps, and emphasizes the strategic position of space science and its importance to China's science and technology, aerospace and the national long-term development. It is …