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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Performance evaluation of fault tolerant systems represented by Markov models

A method to evaluate the performance of fault tolerant systems whose configuration can be represented by time-invariant, discrete-time, discrete-state Markov models is introduced. Each state is assumed to be associated with a constant qualitative measure of the system's performance. The method first computes the moments of the performance probability mass function (PMF) and then finds an approximating function that has the same moments. The form of this function is a maximum entropy solution of the moment matching problem. A simple algorithm for calculating the necessary moments is derived and a method for finding the approximate performance PMF is suggested. After some modification, the method is applied to an example, the Inertial Upper Stage navigation system.

Missana, Jean-Olivier A. A.↗
NASA NTRS1990

Computerized tomographic imaging for space plasma physics

The measurement of plasma electron velocity distribution functions as a problem in imaging and image reconstruction is considered. A model instrument that measures the integral of the distribution function along lines in velocity space is presented. This allows the use of the powerful mathematical and numerical methods that have recently been so successful in other areas of imaging. It is found that this approach leads to classes of instruments that are qualitatively different from contemporary designs. An investigation of different methods of reconstruction of the distribution function from integral measurements reveals that the mathematical tools appropriate to one particular imaging problem may be very different from those required to deal with another.

Zhang, Yuhong↗
DOE OSTI2021

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

The Transition of RGB Imagery Applied to Fog and Low Clouds from NASA Capabilities within the GOES Proving Ground to the Present Era

A wide range of RGB Imagery products are now available from the GOES ABI instrument, but less than a decade earlier, these false-color imagery products were only seen over Europe and Africa within the suite of the EUMETSAT SEVIRI geostationary instrument. The issue of fog and low clouds as applied to aviation and ground transportation hazards has been a long-standing challenge where satellite imagery provides notable value to visually inspect large spatial areas vs relying on in situ point observations. A legacy channel difference product was the standard satellite imagery tool, but the Nighttime Microphysics RGB would soon be introduced with GOES-R and -S where users had no interpretation experience. As part of the GOES Proving Ground efforts, the SPoRT program utilized existing NASA LEO satellites to demonstrate the future ABI capabilities. Operational users were able to test and adopt the RGBs from NASA LEO instruments prior to the GOES-R launch in order to be ready for the wealth of new channels available from ABI. The transition experience and methods from these proxy RGBs to the start of the GOES-R ABI era to the present day provides insights to the value of these new qualitative products in operations and to how the transition method of such products can be successfully implemented as well as future needs in the RGB Imagery area.

Kevin Fuell↗
NASA NTRS1989

Error analysis for semi-analytic displacement derivatives with respect to shape and sizing variables

Sensitivity analysis is fundamental to the solution of structural optimization problems. Consequently, much research has focused on the efficient computation of static displacement derivatives. As originally developed, these methods relied on analytical representations for the derivatives of the structural stiffness matrix (K) with respect to the design variables (b sub i). To extend these methods for use with complex finite element formulations and facilitate their implementation into structural optimization programs using the general finite element method analysis codes, the semi-analytic method was developed. In this method the matrix the derivative of K/the derivative b sub i is approximated by finite difference. Although it is well known that the accuracy of the semi-analytic method is dependent on the finite difference parameter, recent work has suggested that more fundamental inaccuracies exist in the method when used for shape optimization. Another study has argued qualitatively that these errors are related to nonuniform errors in the stiffness matrix derivatives. The accuracy of the semi-analytic method is investigated. A general framework was developed for the error analysis and then it is shown analytically that the errors in the method are entirely accounted for by errors in delta K/delta b sub i. Furthermore, it is demonstrated that acceptable accuracy in the derivatives can be obtained through careful selection of the finite difference parameter.

Fenyes, Peter A.↗
DOE OSTI2022

Organic Evaporation and Oxidation Testing in Support of Hanford Sample-and-Send

The Hanford site has approximately 56 million gallons of radioactive mixed waste stored in 177 underground storage tanks. The Hanford Waste Treatment and Immobilization Plant (WTP) is being built to treat and immobilize the tank waste. The baseline method for immobilization of Low Activity Waste (LAW) through the WTP is vitrification, but additional immobilization capacity is needed to supplement the initial LAW melters. An alternative cementitious waste form is being investigated for that future immobilization method to supplement vitrification. However, one impediment to a cementitious waste form is the presence of Land Disposal Restricted (LDR) organic chemicals in tank waste. This work evaluates potential avenues to eliminate that impediment to permit possible use of a cementitious waste form and work towards a decision whether additional LDR organic pretreatment would be required. Savannah River National Laboratory (SRNL) performed testing using simulants to examine evaporation as a method to remove some prevalent organics from LAW. Spiking the caustic LAW simulant with selected regulated organic chemicals found one that clearly decomposes because of caustic instability. Oxidation testing of other organic chemicals found some LDR organics degrade as desired and others are stable in the presence of peroxide and permanganate. In addition to studies with simulants, a literature review was performed to evaluate radiological stability of LDR organics. Descriptions of the experimental details, equipment, and results are included in this report. Evaporation testing consisted of preparing the LAW simulant, spiking that simulant with organic chemicals, and evaporating the mixture via differential distillation. The apparatus was a laboratory-scale vacuum evaporator operated at 60 ±5 torr absolute (vacuum evaporation) and also at atmospheric pressure. The LAW simulant represented the liquid expected to be retrieved from the Hanford tank farms at approximately 4.0 M [Na + ] total sodium ion concentration. The concentration of the organic chemicals added was significantly higher than typically found in the tank waste samples since the higher levels were necessary to assist in analytical measurement and tracking of the spiked species. Organic chemicals were chosen for the work with a consideration of how their volatility compares with that of methanol. This was done by comparing the ratio of the pure water Henry’s law coefficient (K h ) of methanol to that of the compound in question (hereafter termed the K h ratio), where ratios above unity indicated less volatility than methanol. Methanol was chosen because it is a common regulated chemical with relatively low volatility but which has been removed by evaporation in previous laboratory work. While organic separation results depend on evaporator design, laboratory experiments verified that organic partitioning to the overhead condensate stream by evaporation is a practical process. The work reported here found difficulties in quantitative analysis of the organic chemicals in aqueous samples. Most of the time there was insufficient analysis to close a mass balance for evaporator runs, but qualitative evidence of carryover was obtained. The methods were also able to show whether organic chemicals were susceptible or resistant to solution oxidation in permanganate or hydrogen peroxide tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

General, Rigorous Approach for the Treatment of Interfragment Covalent Bonds

Here, a generalized, projection-based transformation of the method-agnostic Fock operator in various ab initio fragment-based quantum chemistry methods has been developed for the treatment of interfragment covalent bonds. This transformation freezes the relevant localized molecular orbital associated with each interfragment bond, thereby restricting the variational subspace of the fragment wave functions, in order to maintain the proper physical characteristics of the involved covalent bonds. In addition, sets of orbitals that would lead to multiple occupancy of certain orbitals are explicitly removed from the variational space. The transformation is developed for the specific case of mutually orthonormal frozen and unfrozen orbitals within each fragment. The newly developed approach is then used to study model systems with two popular ab initio fragment-based methods, and the results of these calculations are compared to those obtained by existing methodologies. Analysis is focused on both quantitative and qualitative accuracy as well as computational scalability and stability. Other methods for which the developed formalisms are appropriate are outlined, and future extensions of the methods are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Capsule network-based semantic segmentation model for thermal anomaly identification on building envelopes

Thermography technology is widely used to inspect thermal anomalies in building façade systems. Computer vision-based techniques provide opportunities to autonomously detect such heat anomalies to significantly improve the efficiency of decision-making for building envelope retrofitting and maintenance. Here, in this work, we propose a novel Capsule Network-based deep learning model – CapsLab – that detects and identifies thermal anomalies by semantic segmentation. CapsLab is built based on our proposed prediction-tuning capsule (PT-Capsule) layer. Different from a traditional capsule layer, which consists of part-whole transformation and capsule-routing process, the proposed layer is composed of a prediction and tuning process, which helps decreasing the number of model parameters significantly. While the applicability of traditional Capsule Networks (CapsNets) has been limited to simpler tasks and smaller datasets due to their scalability issue, we can leverage the lightweight of the proposed PT-Capsule layer, and apply it to the semantic segmentation task. In this work, we also employ our previously presented performance metric, referred to as the Anomaly Identification Metric (AIM) (Kakillioglua et al. 2021), to evaluate the segmentation outputs. Traditional performance metrics do not accurately reflect the true performance of the segmentation models in thermal anomaly identification due to the high subjectivity in the annotation process and higher overlap ratio sensitivity of the standard metrics. AIM, on the other hand, is robust to these drawbacks. Experimental results show, both qualitatively and quantitatively, that our proposed segmentation method can effectively segment the thermal anomalies. Specifically, our model provides 9.38% and 13.53% improvements over the baseline model – DeepLabV3+ – based on traditional mIoU score and the AIM score, respectively, while requiring less model parameters and less computation at the same time. In addition, the scores that the AIM metric generates better align with the scores provided by building performance experts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗
DOE OSTI2025

A Design for Remanufacturing Framework Incorporating Identification, Evaluation, and Validation: A Case Study of Hydraulic Manifold

In recent years, academic researchers and engineers in the industry have widely recognized the necessity of integrating remanufacturing considerations into product design iterations to advance sustainability objectives. Acknowledging the importance of design for remanufacturing (DfRem), efforts were made to develop tools and guidelines that could be implemented in practice. However, such methods largely rely upon experiential insights and qualitative assessments, leaving a gap in the ability to quantitatively assess the economic and environmental impacts of design choices. To bridge this gap, we investigate existing efforts and present a framework for DfRem that integrates established design and remanufacturing practices into a cohesive workflow with quantitative assessments. To demonstrate its efficacy for making practical design changes for remanufacturing, we apply the framework to a hydraulic manifold in a transmission system for heavy-duty tractors. Through this industry-relevant case study, we focus on showcasing the practical utility of our framework. Based on the identified design modifications from remanufacturability analysis, we estimate the reductions in life cycle costs, energy consumption, and emissions. Afterward, the modifications are tested using physical experiments with plans for integration into future iterations of the hydraulic manifold design and production. Here, we anticipate this framework can illustrate the process of remanufacturing that ensures improvements in sustainability while maintaining performance and reliability standards.

design for X↗
DOE OSTI2021

Crossover from hydrogen to chemical bonding

Hydrogen bonds (H-bonds) can be interpreted as a classical electrostatic interaction or as a covalent chemical bond if the interaction is strong enough. As a result, short strong H-bonds exist at an intersection between qualitatively different bonding descriptions, with few experimental methods to understand this dichotomy. The [F-H-F] − ion represents a bare short H-bond, whose distinctive vibrational potential in water is revealed with femtosecond two-dimensional infrared spectroscopy. It shows the superharmonic behavior of the proton motion, which is strongly coupled to the donor-acceptor stretching and disappears on H-bond bending. In combination with high-level quantum-chemical calculations, we demonstrate a distinct crossover in spectroscopic properties from conventional to short strong H-bonds, which identify where hydrogen bonding ends and chemical bonding begins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Effect of Material Properties on Oxygen Evolution Activity and Assessing Half-Cell Screening as a Predictive Tool in Electrolysis

Iridium-based oxygen evolution catalysts are screened in this study for activity and stability with rotating disk electrode (RDE) half-cells. This study focuses on the electrochemical and materials approaches needed to characterize oxygen evolution catalysts, and include testing for activity, stability, composition, oxide content, and structure. Findings also discuss recommendations for data interpretation and detail the difficulties of comparing catalysts across materials sets with different elemental and oxide compositions, and linking RDE activity to device-level performance. The materials evaluated are a mixture of oxides and metals, and several methods are used to quantify metal content, qualitatively assess oxide content, and determine total surface area. Oxygen evolution activities and stabilities are compared, where a wide range of results are reported. In general, higher RDE performances are found for catalysts that contained larger amounts of ruthenium and metals. Higher durability, however, is found for catalysts that only contained iridium and a higher proportion of oxides. Additionally, catalysts are evaluated for performance in membrane electrode assemblies to assess RDE as a predictive tool in electrolysis. While activity trends within individual material sets generally held between ex- and in-situ testing, RDE tends to overestimate the activity of more metallic catalysts when compared to device-level performance. These results stress the need for multiple metal/oxide baselines for mixed catalysts, to better project in-situ kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microgrids in Emerging Markets - Private Sector Perspectives

This quick read assesses the barriers and opportunities for private sector entry into microgrid development. Information presented in this paper is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment in emerging markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Scaling Up Energy Efficiency Investment in Emerging Markets - Private Sector Perspectives

Since 2000, electricity demand has flattened and decoupled from Gross Domestic Product (GDP) growth in the Organization for Economic Cooperation and Development (OECD) countries. This trend is anticipated to continue for the next several decades and is largely attributed to the implementation of energy efficiency measures. However, non-OECD countries (emerging markets) have experienced, and are projected to continue experiencing, increasing electricity demands. If the world is to meet the requirements of the Paris Agreement, annual investments in clean energy and energy efficiency need to increase by a factor of six by 2050, compared to 2015. Information presented in this paper is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment including microgrid development, energy efficiency, smart grid development, and utility-scale wind and solar in emerging markets. Through literature review, a survey, and a series of webinar dialogues, USAID and the U.S. Department of Energy National Renewable Energy Laboratory (NREL) solicited input from private sector actors, including developers, project financiers, manufacturers and technical assistance service providers, on the challenges they face to market entry in emerging markets, and their suggestions for improving market competitiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Smart Grids in Emerging Markets - Private Sector Perspectives

Information presented in this report is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment in emerging markets as it relates to smart grids. Through literature review, a survey, and a series of webinar dialogues, the U.S. Agency for International Development (USAID) and the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) solicited input from private sector actors, including developers, project financiers, manufacturers, and technical assistance service providers on the challenges they face to market entry in developing and emerging markets, and their suggestions for improving market competitiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Position Papers for the ASCR Workshop on the Science of Scientific-Software Development and Use

Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.

42 ENGINEERING↗
NASA NTRS1972

Experimental and theoretical investigation of stress wave attenuation in fiber reinforced composites.

The propagation of an initialrcidrical pressure pulse through a linear elastic fiber reinforced composite medium is analysed, both experimentally and analytically. In the experiment, tests were performed on plates with single and multiple circular inclusions embedded in a matrix of lower characteristic impedance. Sharp compression pulses were generated at an edge of the plate. Strain gages were mounted on various positions of the plate to determine the attenuation of the transient stress in the fiber reinforced composite. The qualitative analytical treatment is based on the methods of propagating stress discontinuities. Computer programs were written to numerically determine the changes in the shape of the leading wave front and the stresses immediately behind it. Experimental results for the attenuation of stress wave on steel-aluminum and steel-brass fiber-matrix composites compared very well with the computed analytical results when the applied pressure is generated by small explosive charges. The results did not compare well when the applied pressure is generated by projectile impact.

Yang, J. C. S.↗
NASA NTRS1976

Rotational excitation of symmetric top molecules by collisions with atoms: Close coupling, coupled states, and effective potential calculations for NH3-He

The formalism for describing rotational excitation in collisions between symmetric top rigid rotors and spherical atoms is presented both within the accurate quantum close coupling framework and also the coupled states approximation of McGuire and Kouri and the effective potential approximation of Rabitz. Calculations are reported for thermal energy NH3-He collisions, treating NH3 as a rigid rotor and employing a uniform electron gas (Gordon-Kim) approximation for the intermolecular potential. Coupled states are found to be in nearly quantitative agreement with close coupling results while the effective potential method is found to be at least qualitatively correct. Modifications necessary to treat the inversion motion in NH3 are discussed.

Green, S.↗