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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 451 records · Page 25

Lockheed Martin Skunk Works Single Stage to Orbit/Reusable Launch Vehicle

Lockheed Martin Skunk Works has compiled an Annual Performance Report of the X-33/RLV Program. This report consists of individual reports from all industry team members, as well as NASA team centers. This portion of the report is comprised of a status report of Lockheed Martin's contribution to the program. The following is a summary of the Lockheed Martin Centers involved and work reviewed under their portion of the agreement: (1) Lockheed Martin Skunk Works - Vehicle Development, Operations Development, X-33 and RLV Systems Engineering, Manufacturing, Ground Operations, Reliability, Maintainability/Testability, Supportability, & Special Analysis Team, and X-33 Flight Assurance; (2) Lockheed Martin Technical Operations - Launch Support Systems, Ground Support Equipment, Flight Test Operations, and RLV Operations Development Support; (3) Lockheed Martin Space Operations - TAEM and A/L Guidance and Flight Control Design, Evaluation of Vehicle Configuration, TAEM and A/L Dispersion Analysis, Modeling and Simulations, Frequency Domain Analysis, Verification and Validation Activities, and Ancillary Support; (4) Lockheed Martin Astronautics-Denver - Systems Engineering, X-33 Development; (5) Sanders - A Lockheed Martin Company - Vehicle Health Management Subsystem Progress, GSS Progress; and (6) Lockheed Martin Michoud Space Systems - X-33 Liquid Oxygen (LOX) Tank, Key Challenges, Lessons Learned, X-33/RLV Composite Technology, Reusable Cyrogenic Insulation (RCI) and Vehicle Health Monitoring, Main Propulsion Systems (MPS), Structural Testing, X-33 System Integration and Analysis, and Cyrogenic Systems Operations.

Source record↗

Machine Intelligence to Detect, Characterise, and Defend against Influence Operations in the Information Environment

Social media has enabled a new era of manipulation in the information and cognitive domains. Deceptive content—misleading, falsified, and fabricated—is routinely created and spread in the modern social media environment with the intent to create confusion and widen political and social divides, and exploit the societal conflict exacerbated by these divides in the real-world (aka physical domain). Such disinformation campaigns demonstrate a threat to the integrity of economic, political, cultural, public health, and national security institutions around the world. In this work we overview our artificial intelligence (AI) capabilities to detect, describe, and defend against information operations on Twitter as an example social platform to understand the influence of misleading and falsified content diffusion and better enable those charged with defending against such manipulation to enable responsive parties to counter it. We first present novel linguistically-informed deep learning (DL) models for misinformation and disinformation detection, and present an in-depth linguistic analysis of psycho-linguistic markers across broad deception categories. We then demonstrate how our models perform in the multilingual and multimodal setting and categorize falsified and misleading content based on the intent to deceive. We also provide a large-scale analysis to describe user behavior and spread patterns while engaging with deceptive content and report novel findings about the immediate diffusion of deceptive content by characterizing the vulnerable sub-populations and their demographics, and explicitly measuring speed and scale of deception spread to uncover who shares deceptive content, how quickly, how much, and how evenly. In addition, we measure audience reactions to misinformation and disinformation at scale, distinguishing the reactions of users identified as bots versus humans. Finally, we take advantage of deep translation and generation models to create unique solutions for real-time defense against digital deception and discuss how to apply causal inference to prescribe and intervene into strategic communications jointly across information, cognitive, and physical domains.

artificial intelligence, deep learning, neural lan↗

Fracture mechanics approach to TRISO fuel particle failure analysis

Weibull stress-based methods for failure probability assessment have been developed and analyzed to assess the integrity of tristructural isotropic (TRISO) fuel particles during fuel life cycles and accident operating conditions. While simple, these methods entail a number of drawbacks when stress concentrates near crack tips, including finite element mesh size dependency when the Weibull stress is averaged over the finite element domain. Fracture mechanics approaches involving the use of interaction integrals eliminate this lack of mesh convergence and produce consistent fracture predictions. In this work, we use an interaction integral approach to computing stress intensity factors for a crack in the inner pyrolytic carbon layer perpendicular to the silicon carbide layer, which is simplified representation of a failure mode in TRISO particles. Further, the interface between these two TRISO layers has been shown to become porous, which we simulate by considering a transition of mechanical properties over such porous length, i.e. the layers are modeled as a functionally graded material. Aspects such as porosity and thermal and irradiation eigenstrains are considered in computing the stress intensity factor from a fracture mechanics approach and compared with the known Weibull stress failure approach. The methodology introduced in this paper enables a more general fracture probability assessment in TRISO particles and eliminates the need to identify best suited parameters when using local or averaged stress-based failure criterion. Finally, the numerical sensitivity studies show how parameters such as the porous transition zone length, the material stiffness, and creep affect the probability of TRISO fuel particle failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Famine Early Warning Systems and Remote Sensing Data

This book describes the interdisciplinary work of USAID's Famine Early Warning System Network (FEWS NET) and its influence on how food security crises are identified, documented and the kind of responses that result. The book describes FEWS NET's systems and methods for using satellite remote sensing to identify and describe how biophysical hazards impact the lives and livelihoods of the population where they occur. It presents several illustrative case studies that will demonstrate the integration of both physical and social science disciplines in its work. FEWS NET s operational needs have driven science in biophysical remote sensing applications through its collaboration with the US Geological Survey, the National Aeronautics and Space Administration, National Oceanographic and Atmospheric Administration, and US Department of Agriculture, as well as methodologies in the social science domain through its support of the US Agency for International Development, UNWorld Food Program and numerous international non-governmental organizations such as Save the Children, Oxfam and others. Because FEWS NET is an organization that must provide a global picture of food insecurity to decision makers, the information it relies on are by necessity observable and able to be documented. Thus many aspects of traditional livelihood analysis, for example, cannot be used by FEWS NET as they rely upon relationships, and ways of expressing power and knowledge at the local scale that cannot be easily scaled up to express variations in access to food at a community level. The book focuses on the ways that remote sensing information is transformed into an understanding of the actions that must be taken in order to ensure that lives and livelihoods are protected, including describing the remote sensing observations and models needed to identify hazards and the information gathering requirements and analytical frameworks needed to understand their impact. Its focus is primarily analysis conducted in Africa, but also touches upon FEWS NET s work in Central America, Haiti and Afghanistan. As an organization that seeks to integrate social and physical science methodologies and strategies into its work on a daily basis, it is a fascinating and rich example of interdisciplinary knowledge generation and innovation.

Brown, Molly E.↗

Tuning the structure and habit of iron oxide mesocrystals

A precise control over the meso- and microstructure of ordered and aligned nanoparticle assemblies, i.e., mesocrystals, is essential in the quest for exploiting the collective material properties for potential applications. In this work, we produced evaporation-induced self-assembled mesocrystals with different mesostructures and crystal habits based on iron oxide nanocubes by varying the nanocube size and shape and by applying magnetic fields. A full 3D characterization of the mesocrystals was performed using image analysis, high-resolution scanning electron microscopy and Grazing Incidence Small Angle X-ray Scattering (GISAXS). This enabled the structural determination of e.g. multi-domain mesocrystals with complex crystal habits and the quantification of interparticle distances with sub-nm precision. Mesocrystals of small nanocubes (l = 8.6 12.6 nm) are isostructural with a body centred tetragonal (bct ) lattice whereas assemblies of the largest nanocubes in this study (l = 13.6 nm) additionally form a simple cubic (sc) lattice. The mesocrystal habit can be tuned from a square, hexagonal to star-like and pillar shapes depending on the particle size and shape and the strength of the applied magnetic field. Finally, we outline a qualitative phase diagram of the evaporation-induced self-assembled superparamagnetic iron oxide nanocube mesocrystals based on nanocube edge length and magnetic field strength.

36 MATERIALS SCIENCE↗

Stochastic frequency fluctuation super-resolution imaging

The inherent non-linearity of intensity correlation functions can be used to spatially distinguish identical emitters beyond the diffraction limit, as achieved, for example, in super-resolution optical fluctuation imaging (SOFI). Here, we propose a complementary concept based on spectral correlation functions, termed spectral fluctuation super-resolution (SFSR) imaging. Through theoretical and computational analysis, we show that spatially resolving time-frequency correlation functions in the image plane can improve the imaging resolution by a factor of $\sqrt2$ in most cases and up to twofold for strictly two emitters. This improvement is achieved by quantifying the degree of correlation in spectral fluctuations across the spatial domain. Experimentally, SFSR can be implemented using a combination of interferometry and photon-correlation measurements. The method works for non-blinking emitters and stochastic spectral fluctuations with arbitrary temporal statistics. This suggests its utility in super-resolution microscopy of quantum emitters at low temperatures, where spectral diffusion is often more pronounced than emitter blinking.

47 OTHER INSTRUMENTATION↗

Computer technologies and institutional memory

NASA programs for manned space flight are in their 27th year. Scientists and engineers who worked continuously on the development of aerospace technology during that period are approaching retirement. The resulting loss to the organization will be considerable. Although this problem is general to the NASA community, the problem was explored in terms of the institutional memory and technical expertise of a single individual in the Man-Systems division. The main domain of the expert was spacecraft lighting, which became the subject area for analysis in these studies. The report starts with an analysis of the cumulative expertise and institutional memory of technical employees of organizations such as NASA. A set of solutions to this problem are examined and found inadequate. Two solutions were investigated at length: hypertext and expert systems. Illustrative examples were provided of hypertext and expert system representation of spacecraft lighting. These computer technologies can be used to ameliorate the problem of the loss of invaluable personnel.

Bell, Christopher↗

Theory for noise of propellers in angular inflow with parametric studies and experimental verification

This report presents the derivation of a frequency domain theory and working equations for radiation of propeller harmonic noise in the presence of angular inflow. In applying the acoustic analogy, integration over the tangential coordinate of the source region is performed numerically, permitting the equations to be solved without approximation for any degree of angular inflow. Inflow angle is specified in terms of yaw, pitch, and roll angles of the aircraft. Since these can be arbitrarily large, the analysis applies with equal accuracy to propellers and helicopter rotors. For thickness and loading, the derivation is given in complete detail with working equations for near and far field. However, the quadrupole derivation has been carried only far enough to show feasibility of the numerical approach. Explicit formulas are presented for computation of source elements, evaluation of Green's functions, and location of observer points in various visual and retarded coordinate systems. The resulting computer program, called WOBBLE has been written in FORTRAN and follows the notation of this report very closely. The new theory is explored to establish the effects of varying inflow angle on axial and circumferential directivity. Also, parametric studies were performed to evaluate various phenomena outside the capabilities of earlier theories, such as an unsteady thickness effect. Validity of the theory was established by comparison with test data from conventional propellers and Prop Fans in flight and in wind tunnels under a variety of operating conditions and inflow angles.

Propeller acoustics↗

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗

Application of Systems Engineering Principles and Techniques in Biological Big Data Analytics: A Review

In the past few decades, we have witnessed tremendous advancements in biology, life sciences and healthcare. These advancements are due in no small part to the big data made available by various high-throughput technologies, the ever-advancing computing power, and the algorithmic advancements in machine learning. Specifically, big data analytics such as statistical and machine learning has become an essential tool in these rapidly developing fields. As a result, the subject has drawn increased attention and many review papers have been published in just the past few years on the subject. Different from all existing reviews, this work focuses on the application of systems, engineering principles and techniques in addressing some of the common challenges in big data analytics for biological, biomedical and healthcare applications. Specifically, this review focuses on the following three key areas in biological big data analytics where systems engineering principles and techniques have been playing important roles: the principle of parsimony in addressing overfitting, the dynamic analysis of biological data, and the role of domain knowledge in biological data analytics.

dynamic analysis↗

Treatment of Launch Vehicle Flight Control Stability Margin Reductions for Crewed Missions with Emphasis on Slosh Dynamics

NESC’s perspective for crewed spaceflight: Acceptance of flight control gain/phase stability margin reductions from industry standards should be accompanied by an adequately extensive technical treatment, including: •Analyzing the fundamental physics involved, with applicable simulation tool verification (particularly if results are dissimilar among rules of thumb, linear tools, nonlinear analysis, and flight data) •Conducting sensitivity studies in time and frequency domains to analyze effects of possible parameter and system variations •Studying the effects of the consequence of instability associated with offending modes by running stressing cases in time domain •Assessing alternative flight control designs to demonstrate that present design appropriately balances overall vehicle risk (i.e., quantitatively delineate chosen tradeoffs between various stability margins and vehicle performance in the context of risk/consequence) Work presented here represents an example summary of expected engineering work to flight-certify crewed missions with unstable slosh modes and reduced stability margins

Launch Vehicle Flight Control↗

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Application of X-ray Technique to Study the Structure of Ultrafine-Grained Ferritic/Martensitic Steel

In this work, x-ray diffraction and transmission electron microscopy (TEM) analyses have been applied to study the structure of ultrafine-grained (UFG) ferritic/martensitic steel as compared to coarse-grained samples subjected to standard treatment. The x-ray phase analysis of diffraction patterns taken in the “transmission” mode allowed determining the volume fraction and phase composition of particles in the UFG samples. The lattice parameter, the size of coherent scattering domains, the averaged dislocation density, and the fraction of edge and screw dislocations of the ferritic phase in steel were determined according to the diffraction patterns taken in the “reflection” mode. The small-angle x-ray scattering (SAXS) technique was used to study the quantitative characteristics of the size, shape, and distribution of precipitates in the UFG samples. The TEM investigations were performed on the same foils to confirm the results of SAXS. The quantitative evaluations of dispersion and dislocation hardenings in ferritic/martensitic steel were conducted on the basis of the results obtained.

36 MATERIALS SCIENCE↗

A Tool for Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D has shown that HPF provides an efficient, concise way to express parallelism and to organize data traffic. The use of HPF, as noted in the papers, requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement, and data granularity. To simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and implemented ADAPT (Automatic Data Alignment and Placement Tool). ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT, and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level, or on the application interface level. ADAPT annotates an existing CFD FORTRAN application, performing computations on single or multiple grids. On each grid the application is considered as a sequence of operators, each applied to a set of variables defined in a particular grid domain. ADAPT automatically detects implicit operators (i.e., having data dependences) and explicit operators (without data dependences). For parallelization of an explicit operator ADAPT creates a template for the operator domain, aligns arrays used in the operator with the template, distributes the template, and declares the loops over the distributed dimensions as INDEPENDENT. For parallelization of an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if the compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator, then the loop which implements the operator can be declared as INDEPENDENT. ADAPT starts with an analysis of array index expressions of the loop nests. For each pair of arrays referenced in an assignment statement, it generates an arc in the alignment graph and annotates it with an affinity relation. The template, alignment, and distribution directives for a particular loop nest are then derived from a transitive closure of the affinity relation. A compromise of data distributions in different nests and subroutines is achieved by merging annotated alignment graphs for adjacent nests/stibroutine calls in the nest/call graph of the application in the process called distribution lifting. ADAPT has been implemented as a C++ program running in conjunction with a parallelization tool called CAPTools. ADAPT uses the parse tree, interprocedural analysis and application database generated by CAPTools. It also uses the Directed Graph class, initially implemented in p2d2 (parallel debugger oi distributed programs), and some other classes supporting symbolic computations. ADAPT uses data distribution techniques described. ADAPT was tested with ARC3D and the FT benchmark and has demonstrated a code performance within a factor of 1.5 of handwritten versions.

Frumkin, Michael↗

Symmetries of all lines in monolayer crystals

As `2D' materials (i.e. materials just a few atoms thick) continue to gain prominence, understanding their symmetries is critical for unlocking their full potential. In this work, we present comprehensive tables that tabulate the rod group symmetries of all crystallographic lines in all 80 layer groups, which describe the symmetries of 2D materials. These tables are analogous to the scanning tables for space groups found in Volume E of the International Tables for Crystallography, but are specifically tailored for layer groups and their applications to 2D materials. This resource will aid in the analysis of line defects, such as domain walls, which play a crucial role in determining the properties and functionality of 2D materials.

2D materials↗

Confidence Calibration Metrics

This technical report serves to summarize a literature search conducted that covered confidence calibration. This report is meant to serve as a solid starting reference for individuals interested in learning more about the confidence calibration domain as well as for individuals more familiar with this work – as a summarizing document for calibration metrics is notably lacking in the literature. This report is not meant to serve as a comprehensive review of everything that has been done in this field – in fact, the reader is encouraged to look further into this domain. We describe confidence and calibration and discuss properties of good calibration metrics. We detail various calibration and calibration-tangential metrics, presenting equations, algorithms, parameters, and an analysis of strengths and weaknesses. We apply a subset of these metrics to eight proxy confidence assessment datasets. We examine the various metrics in the context of model confidence. Finally, we discuss promising future directions and outstanding questions.

99 GENERAL AND MISCELLANEOUS↗