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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Near-field supersonic flow predictions by an adaptive unstructured tetrahedral grid solver

Applicability of a three-dimensional solution adaptive unstructured tetrahedral Euler flow solver about generic models for near-field sonic boom pressure signature predictions is evaluated. Comparisons of computational and experimental data demonstrates the capability of the method for predicting inviscid solutions useful for high speed calculations about simple 3-D geometries. The approach has promising features and results indicate potential for application to more complex configurations. The mesh generation is based on the advancing front technique, and steady state solutions of the Euler equations are achieved by explicit time integration. Spatial discretization uses the Taylor-Galerkin approach; an alternate time integration, based on the Runge-Kutta method, is also included. The solution-adaptive grid procedure is based on either remeshing or mesh refinement techniques. An alternative geometry-adaptive grid procedure has also been incorporated.

Djomehri, M. J.↗
NASA NTRS2024

New Cryogenic Method for Combining Lunar Regolith Simulant and Frozen Volatiles to Generate Icy Lunar Simulated Regolith

There is a requirement within the lunar science and exploration communities to develop lunar simulants containing volatiles that are solids at the cryogenic temperatures found in the permanently shadowed regions (PSRs), such as those found near the Lunar South Pole. Icy regolith simulants would be used for curation training, as well as for various research activities. One of the most critical aspects of developing a regolith simulant that is more physically and chemically like icy lunar regolith is minimizing any form of modification driven by elevated temperatures. Here we document our ongoing efforts to combine materials at ultralow temperatures, designed to minimize any chemical reactions or other physical changes during the production of the icy regolith. Our goal is to document how one can create an essentially “unreacted” icy regolith that can serve as an effective “time zero” start point from which advanced curation research will proceed. This is done using commercial off-the-shelf equipment as much as possible, along with creating a custom spray plate that can be adapted to a wide variety of methods, all for the planetary simulant community. This method creates crystals of various volatiles such as water, methanol, along with CO 2 ice and these components are combined with lunar regolith that is at -196°C temperature to avoid chemical reactions, and/or phase changes thus creating a more chemically relevant icy lunar regolith. The rules of chemistry stay the same regardless of location whether it’s in the lab, or directly on the lunar surface, and therefore we aim for creating a more authentic icy lunar simulant in the laboratory by operating at ultralow temperatures. It is also envisioned that this method will lead to advanced materials testing in the future. In addition, this method is directly applicable to prior missions such as LCROSS.

Cryogenic Lunar Simulant and Icy Volatile Producti↗
NASA NTRS2024

New Cryogenic Method for Combining Lunar Regolith Simulant and Frozen Volatiles to Generate Icy Lunar Simulated Regolith

There is a requirement within the lunar science and exploration communities to develop lunar simulants containing volatiles that are solids at the cryogenic temperatures found in the permanently shadowed regions (PSRs), such as those found near the Lunar South Pole. Icy regolith simulants would be used for curation training, as well as for various research activities. One of the most critical aspects of developing a regolith simulant that is more physically and chemically like icy lunar regolith is minimizing any form of modification driven by elevated temperatures. Here we document our ongoing efforts to combine materials at ultralow temperatures, designed to minimize any chemical reactions or other physical changes during the production of the icy regolith. Our goal is to document how one can create an essentially “unreacted” icy regolith that can serve as an effective “time zero” start point from which advanced curation research will proceed. This is done using commercial off-the-shelf equipment as much as possible, along with creating a custom spray plate that can be adapted to a wide variety of methods, all for the planetary simulant community. This method creates crystals of various volatiles such as water, methanol, along with CO 2 ice and these components are combined with lunar regolith that is at -196°C temperature to avoid chemical reactions, and/or phase changes thus creating a more chemically relevant icy lunar regolith. The rules of chemistry stay the same regardless of location whether it’s in the lab, or directly on the lunar surface, and therefore we aim for creating a more authentic icy lunar simulant in the laboratory by operating at ultralow temperatures. It is also envisioned that this method will lead to advanced materials testing in the future. In addition, this method is directly applicable to prior missions such as LCROSS.

Cryogenic Lunar Simulant and Icy Volatile Producti↗
DOE OSTI2023

KEBLM: Knowledge-Enhanced Biomedical Language Models

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Adaptive time scaling for accelerating explicit finite element analysis

A method for accelerating an explicit finite element analysis (FEA) simulation of a modeled system or process includes performing an initial iteration of the FEA simulation according to a baseline time interval via an FEA computing network, and calculating a criteria ratio of a predetermined set of scaling criteria for the modeled system or process. The method includes determining a time-scaling factor using the criteria ratio via the FEA computing network as a function of the criteria ratio, and then applying the time-scaling factor to the baseline time interval to generate a scaled time interval. The scaled time interval accelerates simulation time of the FEA simulation. The method includes performing a subsequent iteration of the explicit FEA simulation at the scaled time interval using the FEA computing network. The process continues for subsequent iterations, with the time-scaling factor adapting with each iteration.

Chen, Jian↗
NASA NTRS1992

Learning and tuning fuzzy logic controllers through reinforcements

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Berenji, Hamid R.↗
DOE OSTI2020

Mercury Speciation of Hanford 241-AP-107 Tank Waste Samples - 20384

The concentration of key mercury species in the Hanford tank waste has not been previously measured. Based on process knowledge, an estimated inventory of 2,100 kg of mercury is assumed and was distributed in varied amounts across 149 single-shell tanks (SSTs) and 28 double-shell tanks (DSTs). Limited analyses of individual SSTs and DSTs for total mercury were all below detection, yielding upper limits in concentration estimates based solely on instrument detection limits, resulting in an uncertain mercury inventory for Hanford tanks. Accurate and reliable chemical speciation and quantification is desired to anticipate, predict, and abate the mass movements of various mercury species through the Hanford waste processing flowsheet. Highly sensitive separation and quantification methods for total, elemental, and monomethyl mercury species, in tank waste, have been developed at the Pacific Northwest National Laboratory's (PNNL) Radiochemical Processing Laboratory (RPL). A non-radiological environmental method to quantify mercury species has been adapted for application to Hanford tank 241-AP-107 raw supernatant feed, filtered feed, and cesium-decontaminated samples. These samples represent feed inventory and pretreatment process effluents prior to immobilization by vitrification. This method separates and preconcentrates total, elemental, and monomethyl mercury onto selective solid substrates with little-to-no radioactive background. The solid samples can then be released from strict radiological control, allowing for analytical work to be conducted in low-level radiological facilities. Separation of mercury species was demonstrated at PNNL's RPL in Richland, Washington before transport and analytical quantification using cold vapor atomic fluorescence spectrometry (CVAFS) at PNNL's Marine Science Laboratory (MSL) in Sequim, Washington. Additional studies were conducted to assess the stability of monomethyl mercury in distilled matrices and preconcentrated onto the Carbotrap{sup R} solid substrate to assess sample degradation over time during transport. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2005

Displacing Unpredictable Nulls in Antenna Radiation Patterns

A method of maintaining radio communication despite the emergence of unpredictable fades and nulls in the radiation pattern of an antenna has been proposed. The method was originally intended to be applied in the design and operation of a radio antenna aboard a robotic exploratory vehicle on a remote planet during communication with a spacecraft in orbit around the planet. The method could also be applied in similar terrestrial situations for example, radio communication between two ground vehicles or between a ground vehicle and an aircraft or spacecraft. The method is conceptually simple, is readily adaptable to diverse situations, and can be implemented without adding greatly to the weight, cost, power demand, or complexity of a system to which it may be applied. The unpredictable fades and nulls in an antenna radiation pattern arise because of electromagnetic interactions between the antenna and other objects within the near field of the antenna (basically, objects within a distance of a few wavelengths). These objects can include general vehicle components, masts, robotic arms, other antennas, the ground, and nearby terrain features. Figure 1 presents representative plots of signal strength versus time during a typical pass of a spacecraft or aircraft through the far field of such an antenna, showing typical nulls and fades caused by nearby objects. The traditional approach to ensuring reliability of communication in the presence of deep fades calls for increasing the effective transmitter power and/or reducing the receiver noise figure at the affected ground vehicle, possibly in combination with appropriate redesign of the equipment at the spacecraft or aircraft end of the communication link. These solutions can be expensive and/or risky and, depending on the application, can add significantly to weight, cost, and power demand. The proposed method entails none of these disadvantages.

Lux, James↗
DOE OSTI2022

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗
DOE OSTI2020

Efficient and Flexible Sensitivity Matrix Computation for Adaptive Electrical Capacitance Volume Tomography

Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive Electrical Capacitance Volume Tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imaging and an improved resolution. Construction of the sensitivity matrix is a necessary step to obtain flow images. This step requires computation of the electric field inside the sensing domain, which is done via a typical field solver such as the finite element method. In this work, we present an efficient and flexible method to construct the sensitivity matrix for Adaptive Electrical Capacitance Volume Tomography (AECVT) based on individual electrode segment excitations and their judicious combination to form desired matrix elements. We illustrate how the proposed method yields the same sensitivity matrix as the traditional method but at a much lower computational cost. Once all segment contributions are obtained, we also indicate how the proposed method, unlike the traditional approach, can generate the sensitivity matrix on demand for an arbitrary combination of synthetic electrodes and obviating the need for any additional field computations. Finally, we present image reconstruction results for two different experimental scenarios where the mutual capacitance data and the corresponding sensitivity vectors are obtained through the proposed measurement combination scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1972

Utilization of FSK communications for time

The method of time control at a radio station for time signal transmission using frequency shift keying, is discussed. Methods for extracting a recovered clock at the receiver are described. Results of a test involving the methods of processing time signals are presented. The requirements for adapting Precise Time and Time Interval control to a communications system are analyzed. A method for reducing the time required for synchronization or identification of messages and the fallout from the communication system to passive timekeeping users are reported.

Stone, R. R., Jr.↗
NASA NTRS1992

A wall interference assessment/correction system

A Wall Signature method originally developed by Hackett has been selected to be adapted for the Ames 12-ft Wind Tunnel WIAC system in the project. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating blockage wall interference. The lifting interference will be treated separately by representing in a horseshoe vortex system for the model's lifting effects. The development and implementation of a working prototype will be completed, delivered and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method--Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected data with those of the free-air simulation.

Lo, Ching F.↗
NASA NTRS1992

Learning and tuning fuzzy logic controllers through reinforcements

This paper presents a new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system. In particular, our generalized approximate reasoning-based intelligent control (GARIC) architecture (1) learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward neural network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto et al. (1983) to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Berenji, Hamid R.↗
NASA NTRS1994

A wall interference assessment/correction system

A Wall Signature method originally developed by Hackett has been selected to be adapted for the Ames 12-ft Wind Tunnel WIAC system in the project. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating wall interference at the model location. The development and implementation of a working prototype will be completed, delivered and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method--Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected parameters with those for the free-air simulation. The following two additional tasks are included: (1) On-line wall interference calculation: The developed wall signature method (modified Hackett's method) for Ames 12-ft Tunnel will be the pre-computed coefficients which facilitate the on-line calculation of wall interference, and (2) Support system effects estimation: The effects on the wall pressure measurements due to the presence of the model support systems will be evaluated.

Lo, C. F.↗
NASA NTRS1995

Numerical solution of differential equations by artificial neural networks

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks (ANN's) are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed by the author to mate the adaptability of the ANN with the speed and precision of the digital computer. This method has been successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Meade, Andrew J., Jr.↗
NASA NTRS1992

Procedure for Adapting Direct Simulation Monte Carlo Meshes

A technique is presented for adapting computational meshes used in the G2 version of the direct simulation Monte Carlo method. The physical ideas underlying the technique are discussed, and adaptation formulas are developed for use on solutions generated from an initial mesh. The effect of statistical scatter on adaptation is addressed, and results demonstrate the ability of this technique to achieve more accurate results without increasing necessary computational resources.

Woronowicz, Michael S.↗
DOE OSTI2023

Optimization Stability in Excited-State-Specific Variational Monte Carlo

Here, we investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

A wall interference assessment/correction system

A Wall Signature method originally developed by Hackett was selected to be adapted for the Ames 12-ft Wind Tunnel Wall Interference Assessment/Correction (WIAC) System in the project. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating wall interference at the model location. The lifting interference will be treated separately by representing in a horseshoe vortex system for the model's lifting effects. The development and implementation of a working prototype will be completed, delivered, and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method - Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected parameters with those for the free-air simulation. The following two additional tasks are included in the supplement No. 1 to the basic Grant. On-line wall interference calculation: The developed wall signature method (modified Hackett's method) for Ames 12-ft Tunnel will be the pre-computed coefficients which facilitate the on-line calculation of wall interference; and support system effects estimation: The effects on the wall pressure measurements due to the presence of the model support systems will be evaluated.

Lo, Ching F.↗