Aerospace Engineering Commons^™

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 …

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, Et. Al.

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 …

Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang

Information Technology & Decision Sciences Faculty Publications

(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …

Optimization Of Orbital Trajectories Using Neuroevolution Of Augmenting Topologies, Nathan Wetherell

University Scholar Projects

This project aims to determine the feasibility of using NeuroEvolution of Augmenting Topologies (NEAT), an advanced neural network evolution scheme, to optimize orbital transfer trajectories. More specifically, this project compares a genetically evolved neural network to a standard Hohmann transfer between Earth and Mars. To test these two methods, an N-body simulation environment was created to accurately determine the result of gravitational interactions on a theoretical spacecraft when combined with planned engine burns. Once created, this simulation environment was used to train the neural networks created using the NEAT Python module. A genetic algorithm was used to modify the topology …

Characterizing And Predicting Human Visual Perception Of Unmanned Aerial Vehicle Gestures, Paul Fletcher

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Unmanned Aerial Vehicles (UAVs) are being used in public domains and hazardous environments where effective communication strategies are critical. UAV gesture techniques have been shown to communicate meaning to human observers and may be ideal in contexts that require lightweight systems such as unmanned aerial flight, however, this work may be limited to an idealized range of viewer perspectives. As gesture is a visual communication technique it is necessary to consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This thesis presents the results of three online user-studies that examine participants’ ability …

An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park

Electrical and Computer Engineering Faculty Research & Creative Works

The Industry Demand for Accurate and Fast Algorithms that Model Vital Battery Parameters, E.g., State-Of-Health, State-Of-Charge, Pulse-Power Capability, is Substantial. One of the Most Critical Models is Battery Capacity Fade. the Key Challenge with Physics-Based Battery Capacity Fade Modeling is the High Numerical Cost in Solving Complex Models. in This Study, an Efficient and Fast Model is Presented to Capture Capacity Fade in Lithium-Ion Batteries. Here, the High-Order Chebyshev Spectral Method is Employed to Address the Associated Complexity with Physics-Based Capacity Fade Models. its Many Advantages, Such as Low Computational Memory, High Accuracy, Exponential Convergence, and Ease of Implementation, Allow …

Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor

Faculty Publications

This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …

On The Use Of High-Frequency Surface Wave Oceanographic Research Radars As Bistatic Single-Frequency Oblique Ionospheric Sounders, Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, Teresa Updyke

CCPO Publications

We demonstrate that bistatic reception of high-frequency oceanographic radars can be used as single-frequency oblique ionospheric sounders. We develop methods that are agnostic of the software-defined radio system to estimate the group range from the bistatic observations. The group range observations are used to estimate the virtual height and equivalent vertical frequency at the midpoint of the oblique propagation path. Uncertainty estimates of the virtual height and equivalent vertical frequency are presented. We apply this analysis to observations collected from two experiments run at two locations in different years, but utilizing similar software-defined radio data collection systems. In the first …

Uas Obstacle Database For University Traffic Management System, Casey Calamaio

Summer Community of Scholars (RCEU and HCR) Project Proposals

No abstract provided.

Editorial For The Special Issue On Micromachines For Non-Newtonian Microfluidics, Lanju Mei, Shizhi Qian

Mechanical & Aerospace Engineering Faculty Publications

In lieu of an abstract, this is an excerpt from the first page.

Microfluidics has seen a remarkable growth over the past few decades, with its extensive applications in engineering, medicine, biology, chemistry, etc [...]

On The Implementation And Further Validation Of A Time Domain Boundary Element Method Broadband Impedance Boundary Condition, Fang Q. Hu, Douglas M. Nark

Mathematics & Statistics Faculty Publications

A time domain boundary integral equation with Burton-Miller reformulation is presented for acoustic scattering by surfaces with liners in a uniform mean flow. The Ingard-Myers impedance boundary condition is implemented using a broadband multipole impedance model and converted into time domain differential equations to augment the boundary integral equation. The coupled integral-differential equations are solved numerically by a March-On-in-Time (MOT) scheme. While the Ingard-Myers condition is known to support Kelvin-Helmholtz instability due to its use of a vortex sheet interface between the flow and the liner surface, it is found that by neglecting a second derivative term in the current …

Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future's uncertainty since multiple action sequences may come from or be followed by …

The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …

Recent Analytic Development Of The Dynamic Q-Tensor Theory For Nematic Liquid Crystals, Xiang Xu

Mathematics & Statistics Faculty Publications

Liquid crystals are a typical type of soft matter that are intermediate between conventional crystalline solids and isotropic fluids. The nematic phase is the simplest liquid crystal phase, and has been studied the most in the mathematical community. There are various continuum models to describe liquid crystals of nematic type, and Q-tensor theory is one among them. The aim of this paper is to give a brief review of recent PDE results regarding the Q-tensor theory in dynamic configurations.