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At least 1,369 records · Page 76

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NASA NTRS1988

An adaptive identification and control scheme for large space structures

A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive controllers to LSS problems has been the requirement for accurate models. We feel that MPC coupled with the CVA identification scheme will resolve this limitation. The results are based on research performed under an SBIR grant, administered by the Air Force Office of Scientific Research.

Carroll, J. V.↗

NASA NTRS1999

Exploiting the Temperature/Concentration Dependence of Magnetic Susceptibility to Control Convection in Fundamental Studies of Solidification Phenomena

The objective of this new research project is to demonstrate by experiment, supplemented by mathematical modeling and physical property measurement, that the effects of buoyancy driven convection can be largely eliminated in ground-based experiments, and further reduced in flight, by applying a new technique. That technique exploits the dependence of magnetic susceptibility on composition or temperature. It is emphasized at the outset that the phenomenon to be exploited is fundamentally and practically different from the magnetic damping of convection in conducting liquids that has been the subject of much prior research. The concept suggesting this research is that all materials, even non-conductors, when placed in a magnetic field gradient, experience a force. Of particular interest here are paramagnetic and diamagnetic materials, classes which embrace the "model alloys", such as succinonitrile-acetone, that have been used by others investigating the fundamentals of solidification. Such alloys will exhibit a dependence of susceptibility on composition. The consequence is that, with a properly oriented field (gradient) a force will arise that can be made to be equal to, but opposite, the buoyancy force arising from concentration (or temperature) gradients. In this way convection can be stilled. The role of convection in determining the microstructure, and thereby properties, of materials is well known. Elimination of that convection has both scientific and technological consequences. Our knowledge of diffusive phenomena in solidification, phenomena normally hidden by the dominance of convection, is enhanced if we can study solidification of quiescent liquids. Furthermore, the microstructure, microchemistry and properties of materials (thereby practical value) are affected by the convection occurring during their solidification. Hitherto the method of choice for elimination of convection has been experimentation in microgravity. However, even in low Earth orbit, residual convection has effects. That residual convection arises from acceleration (drag on the spacecraft), displacement from the center of mass or transients in the gravitational field (g-jitter). There is therefore a need for both further reducing buoyancy driven flow in flight and allowing the simulation of microgravity during ground based experiments. Previous investigations, the research project description, theory behind the study and experimental methods as well as plots of magnetic fields and forces are presented.

Evans, J. W.↗

NASA NTRS1997

Light microscopic image analysis system to quantify immunoreactive terminal area apposed to nerve cells

The present report describes a desktop computer-based method for the quantitative assessment of the area occupied by immunoreactive terminals in close apposition to nerve cells in relation to the perimeter of the cell soma. This method is based on Fast Fourier Transform (FFT) routines incorporated in NIH-Image public domain software. Pyramidal cells of layer V of the somatosensory cortex outlined by GABA immunolabeled terminals were chosen for our analysis. A Leitz Diaplan light microscope was employed for the visualization of the sections. A Sierra Scientific Model 4030 CCD camera was used to capture the images into a Macintosh Centris 650 computer. After preprocessing, filtering was performed on the power spectrum in the frequency domain produced by the FFT operation. An inverse FFT with filter procedure was employed to restore the images to the spatial domain. Pasting of the original image to the transformed one using a Boolean logic operation called 'AND'ing produced an image with the terminals enhanced. This procedure allowed the creation of a binary image using a well-defined threshold of 128. Thus, the terminal area appears in black against a white background. This methodology provides an objective means of measurement of area by counting the total number of pixels occupied by immunoreactive terminals in light microscopic sections in which the difficulties of labeling intensity, size, shape and numerical density of terminals are avoided.

Non-NASA Center↗

NASA NTRS2000

Modeling a Wireless Network for International Space Station

This paper describes the application of wireless local area network (LAN) simulation modeling methods to the hybrid LAN architecture designed for supporting crew-computing tools aboard the International Space Station (ISS). These crew-computing tools, such as wearable computers and portable advisory systems, will provide crew members with real-time vehicle and payload status information and access to digital technical and scientific libraries, significantly enhancing human capabilities in space. A wireless network, therefore, will provide wearable computer and remote instruments with the high performance computational power needed by next-generation 'intelligent' software applications. Wireless network performance in such simulated environments is characterized by the sustainable throughput of data under different traffic conditions. This data will be used to help plan the addition of more access points supporting new modules and more nodes for increased network capacity as the ISS grows.

Alena, Richard↗

NASA NTRS2011

Crosscutting Development- EVA Tools and Geology Sample Acquisition

Exploration to all destinations has at one time or another involved the acquisition and return of samples and context data. Gathered at the summit of the highest mountain, the floor of the deepest sea, or the ice of a polar surface, samples and their value (both scientific and symbolic) have been a mainstay of Earthly exploration. In manned spaceflight exploration, the gathering of samples and their contextual information has continued. With the extension of collecting activities to spaceflight destinations comes the need for geology tools and equipment uniquely designed for use by suited crew members in radically different environments from conventional field geology. Beginning with the first Apollo Lunar Surface Extravehicular Activity (EVA), EVA Geology Tools were successfully used to enable the exploration and scientific sample gathering objectives of the lunar crew members. These early designs were a step in the evolution of Field Geology equipment, and the evolution continues today. Contemporary efforts seek to build upon and extend the knowledge gained in not only the Apollo program but a wealth of terrestrial field geology methods and hardware that have continued to evolve since the last lunar surface EVA. This paper is presented with intentional focus on documenting the continuing evolution and growing body of knowledge for both engineering and science team members seeking to further the development of EVA Geology. Recent engineering development and field testing efforts of EVA Geology equipment for surface EVA applications are presented, including the 2010 Desert Research and Technology Studies (Desert RATs) field trial. An executive summary of findings will also be presented, detailing efforts recommended for exotic sample acquisition and pre-return curation development regardless of planetary or microgravity destination.

Source record↗

NASA NTRS2004

Program Analyzes Radar Altimeter Data

A computer program has been written to perform several analyses of radar altimeter data. The program was designed to improve on previous methods of analysis of altimeter engineering data by (1) facilitating and accelerating the analysis of large amounts of data in a more direct manner and (2) improving the ability to estimate performance of radar-altimeter instrumentation and provide data corrections. The data in question are openly available to the international scientific community and can be downloaded from anonymous file-transfer- protocol (FTP) locations that are accessible via links from altimetry Web sites. The software estimates noise in range measurements, estimates corrections for electromagnetic bias, and performs statistical analyses on various parameters for comparison of different altimeters. Whereas prior techniques used to perform similar analyses of altimeter range noise require comparison of data from repetitions of satellite ground tracks, the present software uses a high-pass filtering technique to obtain similar results from single satellite passes. Elimination of the requirement for repeat-track analysis facilitates the analysis of large amounts of satellite data to assess subtle variations in range noise.

Vandemark, Doug↗

NASA NTRS2015

AgMIP's Transdisciplinary Agricultural Systems Approach to Regional Integrated Assessment of Climate Impacts, Vulnerability, and Adaptation

This chapter describes methods developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to implement a transdisciplinary, systems-based approach for regional-scale (local to national) integrated assessment of agricultural systems under future climate, biophysical, and socio-economic conditions. These methods were used by the AgMIP regional research teams in Sub-Saharan Africa and South Asia to implement the analyses reported in their respective chapters of this book. Additional technical details are provided in Appendix 1.The principal goal that motivates AgMIP's regional integrated assessment (RIA) methodology is to provide scientifically rigorous information needed to support improved decision-making by various stakeholders, ranging from local to national and international non-governmental and governmental organizations.

agriculture↗

NASA NTRS2018

Landslide Mapping Along the Karnali Highway, Nepal using High-Resolution Imagery

The Karnali highway (Figure 1) is the only major transportation link that connects the remote Karnali region to the provincial capital in Province 6 of Nepal. This area becomes inaccessible by roads during every rainy season due to landslides. Despite the known landslide frequency, there have been no systematic landslide inventories conducted along this highway to date. Recent advancements in remote-sensing technologies have significantly increased our ability to map landslides of various sizes rapidly with less in situ surveys or human interaction. Landslide susceptibility, hazard and risk studies require a complete landslide inventory, which might only be possible from very high-resolution (VHR) and high-resolution (HR) imagery. Recent launch of Sentinel-2 in 2015 has provided free access to HR imagery enabling landslide detection at finer scales then what was possible with previous open source satellite imagery obtained from Landsat and ASTER. Satellites providing VHR imagery are commercially owned, expensive and not freely available expect for when disasters charter is activated. NextView licensing agreement, a partnership between the US government and US commercial vendors provides access to VHR imagery to federal agencies in support of scientific research [1]. This partnership provides access to VHR imagery obtained from the DigitalGlobe (DG) constellation which enables mapping of small landslides (< 100 m2). In this study, VHR imagery from DG and HR imagery from Sentinel-2 will be used to map landslides along the Karnali highway using a semi automatic method based on object-oriented analysis (OOA) to create most recent and up-to-date landslide inventory. The effectiveness of this remote sensing based landslide inventory to produce a susceptibility map and its predictive capacity will be tested.

landslide↗

NASA NTRS2020

NASA’s Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) Social Network and Community of Practice

The NASA Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) have been planned and funded by the NASA Earth Science Division. Both programs have a focus on engaging stakeholders and developing science useful for decision making. The resulting programs have funded significant scientific output and advancements in understanding how satellite remote sensing observations can be used to not just study how the Earth is changing, but also create data products that are of high utility to stakeholders and decisions makers. In this paper we focus on documenting thematic diversity of research themes and methods used, and how the CMS and ABoVE themes are related. We do this through developing a Correlated Topic Model on the 521 papers produced by the two programs and plotting the results in a network diagram. Through analysis of the themes in these papers, we document the relationships between researchers and institutions participating in CMS and ABoVE programs and the benefits from sustained engagement with stakeholders due to recurring funding. We note an absence of policy engagement in the papers and conclude that funded researchers need to be more ambitious and explicit in drawing the connection between their research and carbon policy implications in order to meet the stated goals of the CMS and ABoVE programs.

Molly E Brown↗

NASA NTRSDate not supplied

Artemis Internal Science Team Update: Deployed Payloads

Artemis will reestablish human presence on the Moon and lead to a new era of scientific discovery and exploration. Led by the National Aeronautics and Space Administration (NASA), the Artemis effort includes a collaboration of space agencies and companies from around the world [1]. In support of Artemis, a cross-disciplinary effort of science, engineering, operations, and human factors personnel is currently developing the best methods, facilities, and field locations to test hardware, train astronauts, and evaluate concepts of operations. This abstract, as part of the Artemis Internal Science Team (AIST) [2], provides an update to NASA’s plans for the solicitation, development, and operations of deployed surface payloads. In calendar year 2023, NASA’s Science Mission Directorate will solicit proposals for instruments to be deployed by crew on the surface of the Moon (Fig. 1), beginning with Artemis III [3]. The Artemis III mission will land in the south polar region of the Moon, within 6º of latitude from the south pole, in the vicinity of both persistently illuminated and permanently shadowed areas of the Moon, with potential access to surface-accessible volatile deposits [4]. Several of the proposed landing regions are located among some of the oldest parts of the Moon, and together with the permanently shadowed regions, provide the opportunity to learn about the history of the Moon through previously unexplored lunar regions [5]. Deployed payloads will be a critical part of a notional program that captures the highest-priority science for Artemis III and provides the greatest feedforward to follow-on missions and the build-up to the Artemis Base Camp

R. C. Weber↗

DOE OSTI2026

Higher-order LaSDI: Reduced order modeling with multiple time derivatives

Solving complex partial differential equations (PDEs) is essential across scientific disciplines but often requires numerical models that can be prohibitively expensive in time-sensitive applications. Reduced-order models (ROMs) address this challenge by exploiting low-dimensional structure to create fast approximations. The Latent Space Dynamics Identification (LaSDI) framework has demonstrated success in learning ROMs for parameterized PDE families, but remains limited to first-order systems. Here, in this paper, we propose Higher-Order LaSDI (HLaSDI), which extends the LaSDI framework to PDEs with arbitrary order of time derivatives. This generalization significantly expands the applicability of LaSDI-based methods to systems previously outside their scope, including hyperbolic PDEs. We demonstrate HLaSDI’s accuracy and efficiency on several linear and nonlinear benchmark problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A Review of the Lawrence Livermore Nuclear Accident Dosimeter 1980s-present

A Nuclear Accident Dosimetry program is a federal requirement for all facilities that have the potential to have a criticality accident. Personnel Nuclear Accident Dosimeter (PNAD) theory and analytical procedures are driven by various scientific needs and interacting regulations. A brief history of the status of USA Department of Energy (DOE) nuclear accident dosimetry regulations, recommendations, and performance testing criteria are given. Then, the history of the Lawrence Livermore National Laboratory (LLNL) PNAD is explored, including changes in the physical dosimeter and adjustments of the analysis method through the last four decades. Finally, the performance of LLNL’s PNAD at criticality accident intercomparison training exercises since 2009 is explored. In general, reported neutron doses have been within or close to DOE-STD-1098 performance criteria while reported gamma doses have been outside of DOE-STD-1098 performance criteria. Reported total absorbed doses have varied in meeting ANSI/HPS N13.3 and ANSI/HPS N13.3 (R2019) performance criteria. Dosimetry staff retirement and turnover have left historical knowledge gaps, yet provided opportunities within the NAD program at LLNL. This review paper serves as an overview of the history and status of the NAD program. Brief technical, procedural and programmatic recommendations to improve LLNL’s NAD program are given. Technical recommendations include investigating orientation factors through modeling or empirical experimentation, investigating gamma dosimetry methods for high-dose scenarios, and exploring other dosimetric methods for simpler, quicker NAD analysis. Procedural recommendations include better documentation of conversion factor (activity-to-fluence and fluence-to-dose) derivations and spectrum uses, and updated analysis spreadsheets or simple Graphic User Interfaces for dose calculations. In conclusion, programmatic recommendations include formalized training for NAD analysts, and having multiple SMEs trained on the NAD program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

On the effectiveness of neural operators at zero-shot weather downscaling

Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

17 WIND ENERGY↗

DOE OSTI2020

A Shift Selection Strategy for Parallel Shift-invert Spectrum Slicing in Symmetric Self-consistent Eigenvalue Computation

The central importance of large-scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world’s largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing massive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions that will be explored in future work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement

Alamo is a high-performance scientific code that uses block-structured adaptive mesh refinement to solve such problems as: the ignition and burn of solid rocket propellant, plasticity, damage and fracture in materials undergoing loading, and the interaction of compressible flow with eroding solid materials. Alamo is powered by AMReX, and provides a set of unique methods, models, and algorithms that enable it to solve solid-mechanics problems (coupled to other physical behavior such as fluid flow or thermal diffusion) using the power of block-structured adaptive mesh refinement.

36 MATERIALS SCIENCE↗

DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Energy: A continuing bibliography with indexes, February 1975

Reports, articles, and other documents introduced into the NASA scientific and technical information system from July 1, 1974 through September 30, 1974 are cited. Regional, national, and international energy systems; research and development on fuels and other sources of energy; energy conversion, transport, transmission, distribution, and storage, with emphasis on the use of hydrogen and solar energy are included along with methods of locating or using new energy resources. Emphasis is placed on energy for heating, lighting, and powering aircraft, surface vehicles, or other machinery.

Source record↗

NASA NTRS1978

Energy. A continuing bibliography with indexes, issue 18

This issue of Energy lists 1038 reports, journal articles, and other documents announced between April 1, 1978 and June 30, 1978 in Scientific and Technical Aerospace Reports (STAR) or in International Aerospace Abstracts (IAA). The coverage includes regional, national and international energy systems; research and development on fuels and other sources of energy; energy conversion, transport, transmission, distribution and storage, with special emphasis on use of hydrogen and of solar energy. Also included are methods of locating or using new energy resources. Of special interest is energy for heating, lighting, for powering aircraft, surface vehicles, or other machinery.

Source record↗