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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The ABCs of On-Demand Transit (ODT)

On-demand mobility - also referred to as on-demand transit (ODT) - is a form of public mobility that is flexible with respect to where and when service is provided, and ODT deployments have increased significantly in recent years. Transit agencies are becoming increasingly interested in ODT, and due to differing definitions and various service design and business model options, it can be difficult to learn about the emerging industry. This work provides an overview of the definitions of ODT, recent trends internationally and in the U.S., ODT's benefits and challenges (particularly compared to fixed-route transit), three primary service design options, system costs and funding considerations, and a metrics framework for evaluating ODT systems to ensure continued successful performance. Identified benefits include increased service areas, short ride and wait times, increased user flexibility, potential to reduce energy consumption and emissions through shared trips and smaller, right-sized vehicles, increased safety and comfort through door-to-door service, and rich data streams including granular spatio-temporal data that can be analyzed to continuously improve the service. Challenges include scaling ODT service up as small increases in ridership require additional supply to keep service quality high, serving peak times including keeping low wait times, the lack of fixed schedule being challenging for commuters, integrating ODT services with nearby transit systems, and equity for riders without smartphones who cannot track the vehicle in a mobile app. Finally, an overview of seven ODT case studies (in Texas, Missouri, New York, and Ontario, Canada) performed by NREL and related analysis of travel time, energy and emissions, costs, and equity are presented. Initial key findings include: ODT can be cost- and energy-effective compared to fixed-route transit, ODT serves more people than other transit options, and ODT system deployments can be followed by rapid growth.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2000

Neural network recognition of chemical class information in mobility spectra obtained at high temperatures

A minimal neural network was applied to a large library of high-temperature mobility spectra drawn from 16 chemical classes including 154 substances with 2000 spectra at various concentrations. A genetic algorithm was used to create a representative subset of points from the mobility spectrum as input to a cascade-type back-propagation network. This network demonstrated that significant information specific to chemical class was located in the spectral region near the reactant ions. This network failed to generalize the solution to unfamiliar compounds necessitating the use of complete spectra in network processing. An extended back-propagation network classified unfamiliar chemicals by functional group with a mean for average values of 0.83 without sulfides and 0.79 with sulfides. Further experiments confirmed that chemical class information was resident in the spectral region near the reactant ions. Deconvolution of spectra demonstrated the presence of ions, merged with the reactant ion peaks that originated from introduced samples. The ability of the neural network to generalize the solution to unfamiliar compounds suggests that these ions are distinct and class specific.

NASA Discipline Environmental Health↗
DOE OSTI2018

The structural and dynamical role of water in natural organic matter: A 2H NMR and XRD study

Natural organic matter (NOM) is an important component in many near-surface geochemical environments, and its properties are greatly affected by the incorporation of water. Because of its importance, the macroscopic behavior and effects of water in NOM and soil organic matter (SOM) have been extensively studied using a wide range of experimental and computational methods. The molecular scale structural and dynamical behavior of water in these materials, however, is less well understood. This paper presents a variable temperature 2 H NMR and XRD study of water in Suwannee River NOM and its fulvic acid (FA) and humic acid (HA) fractions that provides new insight into the dynamical behavior of structurally different types of water and exchangeable hydrogen environments in NOM. The results provide a basis for future studies of more complex natural organic materials and the interaction of organic materials with mineral surfaces. Room temperature 2 H NMR spectra of samples hydrated in 2 H 2 O and then dehydrated, distinguish 2 H 2 O molecules that are in rapid reorientational motion (correlation times, ν c, > 10 5 Hz), 2 H exchanged onto carboxylic sites of the NOM that do not undergo rapid reorientation at frequencies >~10 3 Hz, and 2 H exchanged onto phenolic and possibly other alcohol sites of the NOM that undergoes rapid, but anisotropic, dynamical reorientation. For samples exposed to water and not dried, the XRD results collected at temperatures from 173 to 298 K show the formation of ice-1h in samples exposed to 100% relative humidity (R.H.) but not in samples exposed to 43% R.H. 2 H NMR of those samples collected at temperatures from 313 K to 173 K show the presence of multiple sites. Near room temperature, the spectra contain a narrow resonance for mobile water undergoing rapid isotropic motion, and a broader symmetrical resonance probably due to a combination of more dynamically restricted water molecules and 2 H exchanged onto phenolic and alcohol functional groups undergoing rapid anisotropic motion. The 43% R.H. samples also yield a broader, quadrupole-dominated, resonance for 2 H exchanged onto functional groups of the NOM. With decreasing temperature the resonances for dynamically restricted water molecules and 2 H exchanged onto phenolic and alcohol functional groups become broader, reflecting a decreasing rate of exchange between the water molecules and functional groups and a decreasing rate of reorientation of the 2 H 2 O molecules. The formation of ice-1h is directly reflected in the 2 H spectra of the 100% R.H. samples as a resonance with a quadrupole coupling constant (QCC) of ~180 kHz. For the 43% R.H. samples, there is also a broad, poorly resolved resonance with typical QCCs of ~180 kHz for which the relative signal intensity increases with decreasing temperature. This signal represents 2 H 2 O molecules that are not crystallized in ice-1h but have greatly reduced reorientation frequencies at low temperature and a hydrogen bonding network with hydrogen bond strengths similar to, but somewhat weaker than, ice-1h. Such molecules are also likely to be present in the 100% R.H. samples. At both R.H.s, some of the 2 H 2 O molecules do not freeze and retain their isotropic motion down to 173 K, the lowest temperature investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

I Know I'm Right, But Does My Phone?

Transportation is the largest source of green-house gas emissions in the United States. Reducing transportation emissions depends on human travel behavior, which relies on local land use and planning. Travel diaries, consisting of sequences of trips between places for a particular individual, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of GPS tracking surveys. Mode inference algorithms in particular have been well represented in literature. However, these algorithms have typically been validated using prompted recall of pre-segmented trips, which doesn't account for segmentation error, thus disregarding the continuity of mode inference. Furthermore, phone operating systems and applications have adopted battery-conserving techniques, but we are not aware of prior work that has characterized the resulting data collection errors or evaluated procedures to mitigate them. We introduce a framework to evaluate accuracy of trip length computations and mode inference. We develop a temporal alignment procedure in analyzing continuous mode-segmented trajectories for groups of trips. We then apply our framework to evaluate an example set of travel diary algorithms from the open-source OpenPATH travel diary platform against MobilityNet, a public dataset containing information from three artificial timelines that cover 15 different travel modes. Our results show that inference based on an integration with map features results in weighted F_1 scores of 0.60 (iOS) and 0.74 (android). We also show that OpenPATH tends to under count trip length, with mean of signed relative error of -0.0438 on android and -0.0704 on iOS. We hope that other travel diary algorithms will be evaluated using this standardized process, and that the results used to understand and improve the state-of-the-art in this field.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2018

CO 2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths

We report that CO 2 water-alternating-gas (WAG) injection is an enhanced oil recovery method designed to improve sweep efficiency during CO 2 injection with the injected water to control the mobility of CO 2 and to stabilize the gas front. Optimization of CO 2 -WAG injection is widely regarded as a viable technique for controlling the CO 2 and oil miscible process. Poor recovery from CO 2 -WAG injection can be caused by inappropriately designed WAG parameters. In previous study (Chen and Reynolds, 2016), we proposed an algorithm to optimize the well controls which maximize the life-cycle net-present-value (NPV). However, the effect of injection half-cycle lengths for each injector on oil recovery or NPV has not been well investigated. In this paper, an optimization framework based on augmented Lagrangian method and the newly developed stochastic-simplex-approximate-gradient (StoSAG) algorithm is proposed to explore the possibility of simultaneous optimization of the WAG half-cycle lengths together with the well controls. Finally, the proposed framework is demonstrated with three reservoir examples.

42 ENGINEERING↗
DOE OSTI2022

Phonon thermal Hall effect in a metallic spin ice

It has become common knowledge that phonons can generate thermal Hall effect in a wide variety of materials, although the underlying mechanism is still controversial. We study longitudinal κ xx and transverse κ xy thermal conductivity in Pr 2 Ir 2 O 7 , which is a metallic analog of spin ice. Despite the presence of mobile charge carriers, we find that both κ xx and κ xy are dominated by phonons. A T/H scaling of κ xx unambiguously reveals that longitudinal heat current is substantially impeded by resonant scattering of phonons on paramagnetic spins. Upon cooling, the resonant scattering is strongly affected by a development of spin ice correlation and κ xx deviates from the scaling in an anisotropic way with respect to field directions. Strikingly, a set of the κ xx and κ xy data clearly shows that κ xy correlates with κ xx in its response to magnetic field including a success of the T/H scaling and its failure at low temperature. This remarkable correlation provides solid evidence that an indispensable role is played by spin-phonon scattering not only for hindering the longitudinal heat conduction, but also for generating the transverse response.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms​ ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗
DOE OSTI2026

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms​ ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗
DOE OSTI2020

Hole Polaron Transport in Bismuth Vanadate BiVO 4 from Hybrid Density Functional Theory

In this paper, we address the chemical character and the mobility of hole polarons in BiVO 4 (BVO). Two distinct structures for hole polarons in BVO have been reported in the literature to date. “Standard” hybrid density functional theory (DFT) calculations have predicted hole polarons to be (BiO 8 ) dodecahedron-centered polarons, while Hubbard U-DFT (DFT + U) calculations have predicted single oxygen atom-centered polarons. Resolving these contrasting findings is critical to validate theory in materials research. We investigated the structure of hole polarons in BVO using hybrid DFT with varying fractions (α) of the exact exchange interaction that enters hybrid functionals. For values of the fraction α, from α = 0.25 to α = 0.45, we obtained both structures, the h + (BiO 8 ) hole structure and the h + (O) hole structure. For the smaller values of α, the h + (BiO 8 ) structure is lower in energy, while for the larger values of α, the h+(O) structure is more stable. The piece-wise linearity of DFT energies E(q) with respect to a point defect charge q is maintained satisfactorily in all cases, although the deviation is the smallest for hybrid DFT with a small exact exchange fraction. For α = 0.25, we determined the diffusivity of h + (BiO 8 ) holes from the Marcus/Holstein two-state model. The activation barrier for Bi-to-Bi hops (ΔG # ~76 meV) and mobility (μ ~0.029 cm2 V –1 s –1 ) are found to be in close agreement with the published THz experimental data (ΔG # ~90 meV and μ exp ~0.02 cm2 V –1 s –1 , respectively). In h + (BiO 8 ) structures, nearly 25% of the hole charge and unpaired spin reside on the Bi atom and the rest is divided among the eight O atoms. The hole is best described as a Bi-centered hole, rather than a Bi 6s hole. In contrast, in h + (O) structures, about 75% of the unpaired spin population resides on the O atom. These findings suggest that if one wishes to resolve this theoretical dichotomy, there remains a need for further experimental characterization of hole polarons in BVO with techniques that could identify the oxidation state of Bi and O atoms in operando conditions and help validate theoretical results of structure and transport.

14 SOLAR ENERGY↗
NASA NTRS2011

Development of the ISS EMU SPEEDR

The Self Powered EVA EMU Data Recorder (SPEEDR) is an FPGA (Field-programmable gate array) based device designed to collect high-rate EMU (Extravehicular Mobility Unit) PLSS (Primary Life Support Subsystem) data for download at a later time. The existing EMU PLSS data down-link capability during EVA is one data packet every 2 minutes and is subject to bad packets or loss of signal. High-rate PLSS data is generated by the ECWS (Enhanced Caution and Warning System) but is not normally captured or distributed. Access to high-rate data will increase the capability of EMU anomaly resolution team to pinpoint issues remotely, saving crew time by reducing required call-down Q&A and on-orbit diagnostic activities. With no Shuttle flights post FY11, and potentially limited down-mass capability, the ISS crew and ground support personnel will have to be capable of on-orbit operations to maintain, diagnose, repair, and return to service EMU hardware, possibly through 2028. Collecting high-rate EMU PLSS data during both IVA (Intravehicular Activity) and EVA (Extravehicular Activity) operations will provide trending analysis for life extension and/or predictive performance. The SPEEDR concept has generated interest as a tool/technology that could be used for other ISS subsystems or future exploration-class space suits where hardware reliability/availability is critical and low/variable bandwidth may require "store then forward" methodology. Preliminary work in FY11 produced a functional prototype consisting of an FPGA evaluation board, custom memory/interface circuit board, and custom software. The SPEEDR concept includes a stand-alone battery that is recharged by a computer USB (Universal Serial Bus) port while data is being downloaded.

Bernard. Craig↗
DOE OSTI2022

Advancing Nuclear Energy to Support Economy-wide Net-zero Solutions: Challenges and Opportunities

Governments and private industry around the world have established aggressive goals to achieve net-zero emissions for the power, industrial, and transportation sectors by 2050. These aggressive goals demand immediate action if we are to be successful, and they require us to think more holistically about our clean energy options. Programs within the U.S. Department of Energy (DOE) are addressing these holistic solutions. Traditionally, electricity generation and management and meeting energy demands for industry and transportation are considered independently. As we seek to achieve net-zero, we need to reassess energy demands. When we consider overall energy use, only one-third is in the form of electricity. Additional energy demands are in the form of heat or steam for industrial processes, as well as transportation. These sectors are much harder to abate, and electrification may not be the best option. Reducing environmental emissions at an affordable cost, while maintaining grid reliability and resilience, will require us to use all of the clean energy resources that we have available. That means coordinating the use of nuclear, renewables, and fossil fuels with carbon capture to meet growing demands for electricity, industrial applications, and mobility. The DOE Office of Nuclear Energy (DOE-NE) program on Integrated Energy Systems (IES) is led by researchers at Idaho National Laboratory (INL) and work is conducted in partnership with an array of other DOE laboratories, industry, and academia. The primary focus of IES research is to assess the technical and economic potential of IES to enhance the flexibility and utilization of nuclear reactors working alongside renewable generators to meet an array of energy demands—thereby maximizing the utilization of clean energy resources across all energy sectors. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and chemicals. The DOE-NE program additionally partners with the Hydrogen and Fuel Cell Technologies Office under the DOE Office of Energy Efficiency and Renewable Energy to jointly fund the development of analysis tools, technologies, and nuclear-integrated hydrogen demonstration projects. This presentation highlights the wide array of R&D being conducted across multiple DOE-funded programs to develop and deploy nuclear-based IES that will be key to achieving our net-zero goals. By working with key collaborators in the nuclear industry, analytical studies are now becoming a reality in demonstration projects. The presentation specifically focuses on motivations for the paradigm shift in how nuclear energy is deployed and used, opportunities for nuclear energy to support an array of non-electric application, integration options, computational tools and experimental systems to support evaluation and to accelerate deployment, and industry partnerships.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Degradation of Anion Exchange Membranes by Cation Elimination: Impact on Water Uptake, Nanostructure, and Ionic Mobility

Anion exchange membranes (AEMs) are an attractive platform for fuel cell and electrolysis technologies since they enable the use of cheaper, nonplatinum group metal electrodes and components. However, the widespread adoption of AEM-based devices is limited by chemical degradation of the AEM in the highly alkaline medium of operation. Experimental studies report three major pathways of degradation, including substitution (S N 2), elimination (E2), and backbone cleavage. The decline in membrane performance is likely due to a cumulative effect of several pathways, which has proven to be difficult to disentangle through experiments. Here we use coarse-grained molecular simulations to isolate the impact of E2 degradation, where cationic sites are replaced by an alkene group, on AEM water uptake, nanoscale morphology, structure of the ion-conducting channels, water mobility, and ionic conductivity. Our studies focus on the well-studied model AEM polyphenylene oxide with tetraalkylammonium cationic sites (PPO-TMA). We find that about half of the hydrophobic groups resulting from the degradation retract into the hydrophobic domains of the membrane. The reduction in ion exchange capacity (IEC) and the hydrophobicity of the alkene groups decrease both the equilibrium water uptake (%WU) and the number of water molecules per cation (λ) of the membrane. Interestingly, the evolution of λ with the IEC seems to follow that of undegraded PPO-TMA membranes. Additionally, we ascribe this to the similarity between the structure of the degraded monomer and the neutral one in the polymer. We conclude that most of the performance losses originate in the lower hydration of the degraded membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tandem bulk oxygen diffusion and surface reactions in reducible metal oxides control redox cycle dynamics

The interplay between bulk oxygen diffusion and surface reactions in reducible metal oxides is key in heterogeneous catalysts, but direct measurements of oxygen mobility, transient kinetics, and in situ spectroscopies have been lacking. Here, we reveal complex dynamic behavior of ceria-zirconia by H 2 using transient kinetics via mass spectrometry and in situ Raman and near-ambient pressure x-ray photoelectron spectroscopies. Molecular dynamics simulations with a machine learning potential delineate competitive oxygen diffusion mechanisms, with an optimal mobility at intermediate reductions. We expose a compensation between vacancy availability and lattice distortion at intermediate to high reductions and Frenkel defects at low reductions, underscoring a potential deficiency of 16 O/ 18 O exchange experiments in deducing oxygen mobility. Vacancies in proximity require electron localization on Ce atoms further away. The continuous replenishment of surface oxygen results in a varying reduction rate, with H 2 dissociation being the rate-limiting step. Multiscale transient simulations, consistent with experiments, indicate catalysts of potentially spatially varying oxidation states. The approach is broadly applicable to reducible oxide materials.

36 MATERIALS SCIENCE↗
NASA NTRS2019

A Summary of NASA Rotary Wing Research: Circa 2008–2018

The general public may not know that the first “A” in NASA stands for Aeronautics. If they do know, they will very likely be surprised that in addition to airplanes, the “A” includes research in helicopters, tiltrotors, and other vehicles adorned with rotors. There is, arguably, no subsonic air vehicle more difficult to accurately analyze than a vehicle with lift-producing rotors. No wonder that NASA has conducted rotary wing research since the days of the NACA and has partnered, since 1965, with the U.S. Army in order to overcome some of the most challenging obstacles to understanding the behavior of these vehicles. Since 2006, NASA rotary wing research has been performed under several different project names [Gorton et al., 2015]: Subsonic Rotary Wing (SRW) (2006–2012), Rotary Wing (RW) (2012–2014), and Revolutionary Vertical Lift Technology (RVLT) (2014–present). In 2009, the SRW Project published a report that assessed the status of NASA rotorcraft research; in particular, the predictive capability of NASA rotorcraft tools was addressed for a number of technical disciplines. A brief history of NASA rotorcraft research through 2009 was also provided [Yamauchi and Young, 2009]. Gorton et al. [2015] describes the system studies during 2009–2011 that informed the SRW/RW/RVLT project investment prioritization and organization. The authors also provided the status of research in the RW Project in engines, drive systems, aeromechanics, and impact dynamics as related to structural dynamics of vertical lift vehicles. Since 2009, the focus of research has shifted from large civil VTOL transports, to environmentally clean aircraft, to electrified VTOL aircraft for the urban air mobility (UAM) market. The changing focus of rotorcraft research has been a reflection of the evolving strategic direction of the NASA Aeronautics Research Mission Directorate (ARMD). By 2014, the project had been renamed the Revolutionary Vertical Lift Technology Project. In response to the 2014 NASA Strategic Plan, ARMD developed six Strategic Thrusts. Strategic Thrust 3B was defined as the “Ultra-Efficient Commercial Vehicles—Vertical Lift Aircraft.” Hochstetler et al. [2017] uses Thrust 3B as an example for developing metrics usable by ARMD to measure the effectiveness of each of the Strategic Thrusts. The authors provide near-, mid-, and long-term outcomes for Thrust 3B with corresponding benefits and capabilities. The importance of VTOL research, especially with the rapidly expanding UAM market, eventually resulted in a new Strategic Thrust (to begin in 2020): Thrust 4—Safe, Quiet, and Affordable Vertical Lift Air Vehicles. The underlying rotary wing analysis tools used by NASA are still applicable to traditional rotorcraft and have been expanded in capability to accommodate the growing number of VTOL configurations designed for UAM. The top-level goal of the RVLT Project remains unchanged since 2006: Develop and validate tools, technologies and concepts to overcome key barriers for vertical lift vehicles. In 2019, NASA rotary wing/VTOL research has never been more important for supporting new aircraft and advancements in technology. 2 A decade is a reasonable interval to pause and take stock of progress and accomplishments. In 10 years, digital technology has propelled progress in computational efficiency by orders of magnitude and expanded capabilities in measurement techniques. The purpose of this report is to provide a compilation of the NASA rotary wing research from ~2008 to ~2018. Brief summaries of publications from NASA, NASA-funded, and NASA-supported research are provided in 12 chapters: Acoustics, Aeromechanics, Computational Fluid Dynamics (External Flow), Experimental Methods, Flight Dynamics and Control, Drive Systems, Engines, Crashworthiness, Icing, Structures and Materials, Conceptual Design and System Analysis, and Mars Helicopter. We hope this report serves as a useful reference for future NASA vertical lift researchers.

Yamauchi, Gloria K.↗
NASA NTRS2016

Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Allen, B. Danette↗
DOE OSTI2024

ReLU, Sparseness, and the Encoding of Optic Flow in Neural Networks

Accurate self-motion estimation is critical for various navigational tasks in mobile robotics. Optic flow provides a means to estimate self-motion using a camera sensor and is particularly valuable in GPS- and radio-denied environments. The present study investigates the influence of different activation functions—ReLU, leaky ReLU, GELU, and Mish—on the accuracy, robustness, and encoding properties of convolutional neural networks (CNNs) and multi-layer perceptrons (MLPs) trained to estimate self-motion from optic flow. Our results demonstrate that networks with ReLU and leaky ReLU activation functions not only achieved superior accuracy in self-motion estimation from novel optic flow patterns but also exhibited greater robustness under challenging conditions. The advantages offered by ReLU and leaky ReLU may stem from their ability to induce sparser representations than GELU and Mish do. Our work characterizes the encoding of optic flow in neural networks and highlights how the sparseness induced by ReLU may enhance robust and accurate self-motion estimation from optic flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants

Maintenance activities in the United States nuclear power industry are mainly centered on preventive and corrective maintenance. Predictive maintenance, which is a variable time basis maintenance strategy that is dependent on the condition of the equipment, is less utilized but potentially more effective. In the current maintenance practices, the nuclear power plants rely on manual processes to supply information to a human decision making process. The plants have several processes that generate information that is not typically used beyond the intended target for collecting that information. This information is a source of data that is manually collected by labor intensive tasks. The data is therefore expensive to collect, yet limited in use. The industry has realized the opportunity present in reducing the labor intensive tasks by automating them and increasing the uses of the data collected by either developing advanced predictive maintenance methods using data-driven decision making that could span from trending to machine learning and artificial intelligence. This shift in maintenance strategy may result in high cost saving impact. In addition to reducing labor requirements and frequency of maintenance activities, this shift in strategy will reduce the materials portion of the operations and maintenance cost as well. The aim of this specific effort is to focus on the automation of data collection process. It is part of a series of planned efforts to target multiple elements of migrating the current preventive maintenance approach in nuclear power plants to a data-driven approach. These elements include data collection, management, analysis, visualization, in addition to value analysis and change enabling. The other five elements of migration were not considered because they are planned to be explicitly studied in multiple parallel efforts. Challenges including regulations requirements or limitations are planned in a future effort that focuses on change enabling. The risk and benefit/cost of the approach shift is planned in another effort targeted towards value. The storage, communication, computational power, data architecture, and protection are part of the information infrastructure and are planned in dedicated data management effort. The best means to present the data for assisted human decision making is planned in a data visualization effort. The data interpretation and patterns recognition for machine decision making is planned through multiple efforts in data analytics over the following years. This work identified seventeen data sources collection methods in nuclear power plants that could be automated for an integrated data platform that enables comprehensive and informed decision making. For each of the identified seventeen data sources, the base, modern, and state of the art states were described. The current state of data collection used by most utilities was identified as the "base state". The current achievable state was identified as the "modern state", a state that has either been achieved by at least some US utilities or in other industries. The future state that requires research and development to reach was identified as the "state of the art" state. The described states used an out-of-the-box thinking approach. This effort found that there is a hug potential for task automation and data fidelity improvements by evolving the current industry data collection methods. The majority of the processes analyzed were found to be manual and labor intensive and fell in the base state. As a result, the modern state often targeted reducing the manual logging efforts by using electronic and semi-intelligent means or complementing the work with sensors and mobile or fixed technologies that can reduce the demand of labor activities. The state of the art state involved applications advanced methods of data correlation, data mining, and machine learning along with increasing the spatial distribution and fidelity of data, coupling multiple data sources, and enabling the use of sophisticated mobile devices and machine comprehension methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting

Many popular vetting tools for Android applications use static code analysis techniques. In particular, Interprocedural Data-Flow Graph (IDFG) construction is the computation at the core of Android static data-flow analysis and consumes most of the analysis time. Many analysis tools use a worklist algorithm, an iterative fixed-point approach, to construct the IDFG. In this paper, we observe that a straightforward GPU parallelization of the worklist algorithm leads to significant underutilization of the GPU resources. We identify four performance bottlenecks, namely, frequent dynamic memory allocations, high branch divergence, workload imbalance, and irregular memory access patterns. Accordingly, we propose GDroid, a GPU-based worklist algorithm implementation with multiple fine-grained optimizations tailored to common characteristics of Android applications. The optimizations considered are: matrix-based data structure, memory access-based node grouping, and worklist merging. Our experimental evaluation, performed on 1000 Android applications, shows that the proposed optimizations are beneficial to performance, and GDroid can achieve up to 128X speedups against a plain GPU implementation.

Android security↗