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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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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Proceedings of the First NASA Formal Methods Symposium

Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000.

Denney, Ewen↗
NASA NTRS2011

Flight Simulation of ARES in the Mars Environment

A report discusses using the Aerial Regional- scale Environmental Survey (ARES) light airplane as an observation platform on Mars in order to gather data. It would have to survive insertion into the atmosphere, fly long enough to meet science objectives, and provide a stable platform. The feasibility of such a platform was tested using the Langley Standard Real- Time Simulation in C++. The unique features of LaSRS++ are: full, six-degrees- of-freedom flight simulation that can be used to evaluate the performance of the aircraft in the Martian environment; capability of flight analysis from start to finish; support of Monte Carlo analysis of aircraft performance; and accepting initial conditions from POST results for the entry and deployment of the entry body. Starting with a general aviation model, the design was tweaked to maintain a stable aircraft under expected Martian conditions. Outer mold lines were adjusted based on experience with the Martian atmosphere. Flight control was modified from a vertical acceleration control law to an angle-of-attack control law. Navigation was modified from a vertical acceleration control system to an alpha control system. In general, a pattern of starting with simple models with well-understood behaviors was selected and modified during testing.

Kenney, P. Sean↗
NASA NTRS2019

Simulated Microgravity Affects Behavior and Cytokine Expression in the Hippocampus of Adult Mice: Influence of Mitochondrial Reactive Oxygen Species

The effects of microgravity, and social isolation on the CNS are poorly understood. We hypothesize that mitochondrial reactive oxygen species (ROS) play an important role in this process. Since mice are social animals, our lab developed a novel social model of hindlimb unloading (HU), enabling us to determine the effects of both social isolation and simulated microgravity. Responses to 30d of HU were compared in wildtype or transgenic MCAT mice who over-express human catalase in mitochondria. Abundance of 4-Hydroxynonenal, Park7 (a redox-sensitive chaperone and sensor of oxidative stress) and corticosterone were measured by ELISA. Cytokines related to inflammation in the hippocampus and in plasma were analyzed by a protein array. Behavioral data was collected over a 24-hour period.Socially housed HU mice were more active and conducted at least two times more exploratory activities, compared to normally loaded mice. Correlation analysis revealed that specific brain and plasma cytokines correspond with specific behaviors. Simulated microgravity and/or social isolation caused changes in cytokine patterns in the hippocampus and in plasma, with significant interaction effects of HU and genotype in expression levels of five cytokines (out of 35). Interestingly, elevation of these generally pro-inflammatory cytokines by HU in WT mice was mitigated in MCAT mice, suggesting a role for mitochondrial ROS signaling in inflammatory CNS responses to microgravity. Interestingly, socially housed mice had also lower level of 4HNE and higher level of Park7 in the hippocampus compared to singly housed animals. The cytokine responses to social isolation were more extensive in brain vs plasma. Further, there was no overlap in the cytokine repertoire regulated in response to microgravity versus, isolation suggesting divergent mechanisms or downstream signaling. These findings implicate a potentially important role for mitochondrial ROS in CNS responses to the challenges posed both by prolonged missions in space and bedrest on Earth

Guttmann, Linda↗
NASA NTRSDate not supplied

An Approach for Practical Grid-Resolved Roughness Aerothermodynamic Simulations for Woven Heatshield Surfaces

An approach for simulating the aerothermal environment over a patterned roughness surface within an otherwise axisymmetric flow is developed. The patterned roughness is simplified into a sinusoidal shape that captures the basic features of a charred 3MDCP ablator. Two orientations of this pattern, which are equally flight relevant due to the forming process, enable periodic boundary conditions along the edges of a grid spanning a single roughness element. This simplified three-dimensional grid represents the minimum problem size for a patterned roughness simulation, which enables computationally efficient grid-resolved roughness simulations. This approach is validated by simulating the Langley Mach 6 measurements made on a similar sinusoidal surface, which results in convective heating within 5% of the experimental data. Applying this approach to Mars Sample Return (MSR) Earth Entry System (EES) flight cases, considering simulations with both 11 species air and 30 species air with ablation products, results in heating augmentation that is slightly lower than the widely-used Dahm correlation approach, with the difference being dependent on pattern orientation. This result provides the only insight into the behavior of the roughness augmentation at the high temperature reacting flow conditions present for EES flight cases, which are not captured by available ground test measurements. For shear augmentation, the simulations revealed that the surface-parallel pressure component is dominant. For arc-jet tests targeted to flight values for shear, the higher arc-jet pressures required to match flight values for shear result in up to a 400% increase in the rough wall shear value, which is not captured by the Dahm correlation. This indicates that, to avoid significant over-testing, grid-resolved roughness simulations are required to determine arc-jet conditions that produce flight shear levels in rough-wall scenarios.

Christopher O Johnston↗
NASA NTRS2015

Environmental Effects on Long Term Displacement Data of Woven Fabric Webbings Under Constant Load for Inflatable Structures

An experimental study of the effects of environmental temperature and humidity conditions on long-term creep displacement data of high strength Kevlar and VectranTM woven fabric webbings under constant load for inflatable structures is presented. The restraint layer of an inflatable structure for long-duration space exploration missions is designed to bear load and consists of an assembly of high strength webbings. Long-term creep displacement data of webbings can be utilized by designers to validate service life parameters of restraint layers of inflatable structures. Five groups of high-strength webbings were researched over a two year period. Each group had a unique webbing length, load rating, applied load, and test period. The five groups consisted of 1.) 6K Vectran webbings loaded to 49% ultimate tensile strength (UTS), 2.) 6K Vectran webbings loaded to 55% UTS, 3.) 12.5K Vectran webbings loaded to 22% UTS, 4.) 6K Kevlar webbings loaded to 40% and 43% UTS, and 5.) 6K Kevlar webbings loaded to 48% UTS. Results show that all webbing groups exhibit the initial two stages of three of a typical creep curve of an elastic material. Results also show that webbings exhibit unique local wave patterns over the duration of the test period. Data indicate that the local pattern is primarily generated by daily variations in relative humidity values within the test facility. Data indicate that after a three to six month period, where webbings reach a steady-state creep condition, an annual sinusoidal displacement pattern is exhibited, primarily due to variations in annual mean temperature values. Data indicates that variations in daily temperature values and annual mean humidity values have limited secondary effects on creep displacement behavior. Results show that webbings in groups 2 and 5 do not exhibit well defined annual displacement patterns because the magnitude of the applied loads cause large deformations, and data indicate that material yielding within a webbing tends to neutralize the annual sinusoidal displacement pattern. Study indicates that applied load, environmental effects, mechanical strength, coefficient of thermal expansion, and hygroscopic properties of webbings are fundamental requirements for quantifying accurate creep displacements and behaviors over multiple year time periods. Results from a study of the environmental effects on long-term creep displacement data of Kevlar and Vectran woven webbings are presented to increase the knowledge base of webbing materials and to enhance designs of inflatable space structures for long-duration space missions.

Kenner, WInfred S.↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Quantifying Turbine-Level Risk to Golden Eagles Using a High-Fidelity Updraft Model and a Stochastic Behavioral Model

To minimize the effects of wind farms on Golden Eagle (Aquila chrysaetos) populations while enabling sustainable development of renewable energy resources, it is important to understand how eagles interact with atmospheric flows, terrain features, and anthropogenic structures. Models that predict migratory flight paths provide one tool that helps us grasp how the location of wind farms may influence interactions and impacts on migrating Golden Eagles. The current state-of-the-art in predicting migratory flight paths uses a deterministic fluid-flow analogy to predict eagle trajectory using only an orographic updraft potential computed from topographical features. This model does not take into account variables, such as thermal updrafts and time varying atmospheric conditions that are known to influence migratory behavior. In this work, we improve on the model with the objective of developing tools that advance our understanding of how atmospheric flows and terrain features affect migratory eagle behavior and their interactions with wind farms. Specifically, we 1) incorporate both orographic and thermal updraft information in simulating eagle flight paths; 2) incorporate stochasticity into eagle travel patterns to better capture the influence of exogenous factors on, and the inherent stochasticity of eagle behavior; 3) consider spatio-temporal atmospheric data at wind-farm-scale when computing updraft potential; and 4) account for how atmospheric conditions and the direction of migration change seasonally and how these changes affect eagle migratory flight behavior. We tested the model using a 50km by 50km region with 50 m resolution in the western United States. We simulated 900 independent, probabilistic eagle tracks during southerly and northerly migration, assuming eagles solely rely on orographic updrafts. The preliminary results indicate that the inclusion of finer resolution atmospheric data allows for the inclusion of realistic conditions that an eagle experiences. The stochasticity in eagle tracks provides a platform to include uncertainty in eagle decision making and help produce robust eagle presence maps. We will deploy updraft and downdraft velocities computed using a high-fidelity, wind farm scale, computational fluid dynamics solver under development at National Renewable Energy Laboratory. This work is a first step in the development of a predictive and generalizable eagle behavior model at the wind farm scale that does not rely on empirical data collection. Although the current model is intended for migratory eagles, we will extend and refine this model to inform the development of additional behavioral modes, including resident eagle behavior. This modeling approach improves our ability to understand eagle use of the landscape at a fine scale, and it is our hope that this work will ultimately help advance strategies that minimize the impact of wind development on Golden Eagle populations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2019

Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks

Here this paper proposes a self-taught anomaly detection framework for optical networks. The proposed framework makes use of a hybrid unsupervised and supervised machine learning scheme. First, it employs an unsupervised data clustering module (DCM) to analyze the patterns of monitoring data. The DCM enables a self-learning capability that eliminates the requirement of prior knowledge of abnormal network behaviors and therefore can potentially detect unforeseen anomalies. Second, we introduce a self-taught mechanism that transfers the patterns learned by the DCM to a supervised data regression and classification module (DRCM). The DRCM, whose complexity is mainly related to the scale of the applied supervised learning model, can potentially facilitate more scalable and time-efficient online anomaly detection by avoiding excessively traversing the original dataset. We designed the DCM and DRCM based on the density-based clustering algorithm and the deep neural network structure, respectively. Evaluations with experimental data from two use cases (i.e., single-point detection and end-to-end detection) demonstrate that up to 99% anomaly detection accuracy can be achieved with a false positive rate below 1%.

42 ENGINEERING↗
DOE OSTI2016

Interface Engineering of Domain Structures in BiFeO 3 Thin Films

A wealth of fascinating phenomena have been discovered at the BiFeO 3 domain walls, examples such as domain wall conductivity, photovoltaic effects, and magnetoelectric coupling. Thus, the ability to precisely control the domain structures and accurately study their switching behaviors is critical to realize the next generation of novel devices based on domain wall functionalities. In this work, the introduction of a dielectric layer leads to the tunability of the depolarization field both in the multilayers and superlattices, which provides a novel approach to control the domain patterns of BiFeO 3 films. Moreover, we are able to study the switching behavior of the first time obtained periodic 109° stripe domains with a thick bottom electrode. Besides, the precise controlling of pure 71° and 109° periodic stripe domain walls enable us to make a clear demonstration that the exchange bias in the ferromagnet/BiFeO 3 system originates from 109° domain walls. Lastly, our findings provide future directions to study the room temperature electric field control of exchange bias and open a new pathway to explore the room temperature multiferroic vortices in the BiFeO 3 system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Stochasticity in the Switching of Nanodisks for Probabilistic Computing

Stochasticity in magnetic nanodevices is an essential characteristic for harnessing these devices to computing based on population coding or the building blocks of probabilistic computing, p-bits. A magnetic tunneling junction (MTJ) consisting of a patterned magnetic element is considered a promising computing unit in the concept of artificial neurons and p-bits. A comprehensive understanding of the stochasticity in the switching of patterned magnetic elements is crucial for realizing MTJ-based probabilistic computing technology. In the present work, the stochastic behavior in the switching process of a perpendicularly magnetized Co/Pt disk within an array was directly observed utilizing full-field soft X-ray microscopy. Within 50 repeated hysteretic cycles, the stochastic magnetization switching of individual Co/Pt disks within disk arrays is identified. We found that the stochasticity in the magnetization switching of disks considerably depends on the disk size. The stochasticity initially decreases as the disk radius gets bigger from 125 to 375 nm (region I), then increases with further enlarging the disk size to 625 nm (region II). The variance of thermal fluctuation relevant to the disk size and the multilevel switching within a disk are severely involved in the observed size-dependent stochasticity. Furthermore, this work provides the way for controlling the stochasticity in the switching of nanopatterned elements, which is a key aspect of MTJ-based probabilistic computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗
NASA NTRS2022

Brief Communication: Preliminary ICESat-2 (Ice, Cloud and Land Elevation Satellite-2) Measurements of Outlet Glaciers Reveal Heterogeneous Patterns of Seasonal Dynamic Thickness Change

Dynamic changes of marine-terminating outlet glaciers are projected to be responsible for about half of future ice loss from the Greenland Ice Sheet. However, we lack a unified, process-based understanding that can explain the observed dynamic changes of all outlet glaciers. Many glaciers undergo seasonal dynamic thickness changes, and classifying the patterns of seasonal thickness change can improve our understanding of the processes that drive glacier behavior. The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) provides space-based, seasonally repeating altimetry measurements of the ice sheets, allowing us to quantify near-termini seasonal dynamic thickness patterns of 37 outlet glaciers around the Greenland Ice Sheet. We classify the glaciers into seven common patterns of seasonal thickness change over a 2-year period from 2019 to 2020. We find small groupings of neighboring glaciers with similar patterns of seasonal thickness change, but, within larger sectors of the ice sheet, patterns of seasonal thickness change are mostly heterogeneous. Future studies can build upon our results by extending these time series, comparing seasonal dynamic thickness changes with external forcings, such as ocean temperature and meltwater runoff, and with other dynamic variables such as seasonal glacier velocity and terminus position changes.

Christian J Taubenberger↗
DOE OSTI2019

Wear and Corrosion Resistances of Active Screen Plasma-Nitrided Duplex Stainless Steels

Two grades of duplex stainless steel, SAF 2205 and SAF 2507, were nitrided using an active screen plasma process carried out at 380 °C for 10 h and were characterized in terms of microstructure and hardness. Wear resistance was assessed by means of linear scratch tests, using loads below and above the critical load. Potentiodynamic polarization was used to analyze corrosion behavior in 0.6 M NaCl solution. X-ray diffractometry showed expanded austenite formation in all nitrided samples. The super duplex steel SAF 2507 showed much better scratch resistance, with low friction coefficient and greater toughness, as judged by the pattern of superficial cracks when it was tested above the critical load. The corrosion behavior of steels was also different, mainly in the active region, and nitriding had a more beneficial effect upon SAF 2507. The potential relative to the transpassive region was practically unaffected by the nitriding.

36 MATERIALS SCIENCE↗
DOE OSTI2026

1995 San Diego Region Travel Behavior Survey

The 1995 San Diego Region Travel Behavior Survey was conducted January-June of 1995 under the auspices of the San Diego Association of Governments. The survey was an essential element in the regional study of transportation activity and travel patterns. The survey was designed to examine the relationship between characteristics of households and travel behavior, as well as to provide information state and local decision makers require when considering future regional transportation needs and investments. In total, 2,375 households were recruited to participate in the study. Of these, 2,062 households completed travel diaries, and the information was retrieved from all household members older than age five. 2,049 were successfully geocoded to California state plane coordinates for home addresses. A total of 17,060 trips were profiled in the course of this survey during the assigned 24-hour weekday.

1Hz data↗
DOE OSTI2026

1998 North Front Range (NFR) MPO

The North Front Range Travel Survey was a comprehensive study of travel behavior throughout the north front range of Colorado. The primary purpose of the survey was to provide a picture of travel patterns and characteristics of travelers in the Denver region. The survey was part of four primary surveys under the Regional Travel Behavior Inventory—a collaborative effort among the Denver Regional Council of Governments in partnership with the Regional Transportation District, the Colorado Department of Transportation, and the Regional Air Quality Council. The survey, conducted from October to January, provided demographic and household-based trip information for household members age 16 and older from 13,348 households. A 24-hour travel diary was provided to respondents to record their travel.

1Hz data↗
DOE OSTI2024

Darshan for HEP applications

Modern HEP workflows must manage increasingly large and complex data collections. HPC facilities may be employed to help meet these workflows’ growing data processing needs. However, a better understanding of the I/O patterns and underlying bottlenecks of these workflows is necessary to meet the performance expectations of HPC systems.Darshan is a lightweight I/O characterization tool that captures concise views of HPC application I/O behavior. It intercepts application I/O calls at runtime, records file access statistics for each process, and generates log files detailing application I/O access patterns.Typical HEP workflows include event generation, detector simulation, event reconstruction, and subsequent analysis stages. A study of the I/O behavior of the ATLAS simulation and filtering stage, and the CMS simulation workflow using Darshan is presented, including insights into the I/O operations and data access size.

Wang, Rui↗
DOE OSTI2025

Analyzing Trip Chaining Behavior in New York State Using 2009 and 2017 National Household Travel Survey

Trip chaining, defined as the sequential linking of trips by individuals throughout a given day, provides critical insights into daily mobility patterns and activity sequencing. Understanding these patterns has significant implications for transportation demand forecasting, congestion management, and local economic activity. This analysis examines trip chaining behaviors in New York State (NYS) for the years 2009 and 2017 and compares the Middle Atlantic Census Division with other U.S. regions in 2022, utilizing data from the National Household Travel Survey (NHTS). Through demographic, geographic, and temporal analysis, this study characterizes how populations organize travel for work, personal errands, and social activities, providing empirical evidence of evolving trip chaining behaviors to inform transportation planning strategies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Exploring the Origins of Anti-Ambipolarity in BBL Polymer: Links to Redox Chemistry, Electronic Structure, and Structural Dynamics

We examine the intrinsic physical-chemical properties of the conjugated ladder-type polymer poly(benzimidazobenzophenanthroline) (BBL) in response to electron transfer. We aim at explaining the origin of the anti-ambipolar behavior behind the observed BBL nonlinear response associated with specific device architectures. To elucidate this point, we use theory and computation based on first principles, including density functional theory optimizations, ab initio molecular dynamics, time-dependent DFT, and Marcus-theory analysis. Our results reveal that this redox response is not simply monotonic but follows an alternating odd/even pattern in which gap narrowing and reopening occur sequentially before near-gapless behavior emerges at high charging. Converging theoretical evidence in this work demonstrates that bell shaped conductivity in BBL originates in its fundamental electronic structure and supramolecular organization.

FOS: Physical sciences↗