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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Co-designing Spectral Transformation Oracles with Hybrid Oscillator-Qubit Quantum Processors: From Algorithms to Compilation

We co-design a family of quantum eigenvalue transformation oracles that can be efficiently implemented on hybrid discrete- or continuous-variable (qubit or qumode) hardware. To illustrate the oracle’s representation-theoretic power and near-term experimental accessibility, we encode a Gaussian imaginary time-evolution spectral filter. As a result, we define a continuous linear combination of unitaries block encoding. Due to the ancillary qumode’s infinite-dimensional nature, continuous-variable qumodes constitute a powerful compilation tool for encoding continuous spectral functions without discretization errors while minimizing resource requirements. We then focus on the ubiquitous task of preparing eigenstates in quantum spin models. For completeness, we provide an end-to-end compilation which expresses high-level oracles in terms of an experimentally realizable instruction set architecture in both 1D and 2D. Finally, we examine the leading-order effects of physical errors and highlight open research directions. Our algorithms scale linearly with the spatial extent of the target system and are applicable to both near-term and large-scale quantum processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis

This study aims to effectively analyze and visualize the concept to concept network derived from the COVID-19 Open Research Dataset (CORD-19) dataset, where we have more than 48,000 concepts with more than 300,000 relationships between concepts. In analyzing networks, we focus on finding relationship patterns between the coronavirus disease 2019 (COVID-19) concepts and other concepts. Given the node and edge datasets, we construct directional graphs and calculate all pair shortest paths based on multiple edge weight schemes. However, statistical metrics are not sufficient to identify specific relationships represented in the network. Therefore, we also propose a visual analytics approach to effectively understand the knowledge graph. Our highly interactive visual analytics allows users to effectively analyze the evolving graphs and (COVID-19) concept nodes and other nodes related to the COVID-19 nodes. We envision that this study will pave the path to develop strategies to provide more accurate and scalable predictive analysis on knowledge graphs related to CORD19 and other biomedical knowledge graphs.

Lim, Seung-Hwan↗
DOE OSTI2023

Scaling Automatic Vector Data Alignment to Satellite Imagery

Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly processing large-scale EO data using high performance computing resources. Accurate mapping of the built environment from remote sensing (RS) imagery has been one of the crucial components in GeoAI workflows for a wide spectrum of humanitarian applications. Derived vector data of built environment is often leveraged for disaster preparedness and response activities. However, factors such as differences in ortho-rectification, atmospheric conditions and human error, results in spatial misalignment between vector data and the timely available RS imagery. Model training for downstream tasks such as object detection, change analysis, etc., is negatively impacted due to such spatial misalignment. Although there has been progress towards automatic alignment of vector data, the lack of scalability remains an open research challenge. This paper proposes to leverage parallel computing to optimize an automatic vector data alignment workflow. It further employs CPU-level multi-core parallelism for improving the performance of the workflow for scalable built environment mapping. We report observations and discuss findings from the preliminary experiments performed on the Summit Supercomputer.

Potnis, Abhishek↗
DOE OSTI2021

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Galen View

This is software lets one explore the data released as part of the COVID-19 Open Research Dataset Challenge. It downloads and analyzes the natural language text of the data set and then creates a 2D visualization that can be used to explore it. SAND2020-12185 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Bauer, Travis↗
DOE OSTI2020

Towards scalable dataframe systems

Dataframes are a popular abstraction to represent, prepare, and analyze data. Despite the remarkable success of dataframe libraries in R and Python, dataframes face performance issues even on moderately large datasets. Moreover, there is significant ambiguity regarding dataframe semantics. In this paper we lay out a vision and roadmap for scalable dataframe systems. To demonstrate the potential in this area, we report on our experience building Modin, a scaled-up implementation of the most widely-used and complex dataframe API today, Python's pandas. With pandas as a reference, we propose a simple data model and algebra for dataframes to ground discussion in the field. Given this foundation, we lay out an agenda of open research opportunities where the distinct features of dataframes will require extending the state of the art in many dimensions of data management. We discuss the implications of signature dataframe features including flexible schemas, ordering, row/column equivalence, and data/metadata fluidity, as well as the piecemeal, trial-and-error-based approach to interacting with dataframes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spring 2023 Verification Presentation to Headquarters [Slides]

Testing codes is important, and more tests are needed. Verification testing is different than software-quality assurance, like regression suites. Tests should be simple, but not too simple, and tests should be code agnostic. Developing verification methods is still open research. Testing single-physics code pieces in isolation may lead to bad results when they are coupled. Good verification tests must include multiple physics models, multiple materials, and be performed in multiple dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

In Situ High-Pressure Synthesis of New Outstanding Light-Element Materials under Industrial P-T Range

High-pressure synthesis (which refers to pressure synthesis in the range of 1 to several GPa) adds a promising additional dimension for exploration of compounds that are inaccessible to traditional chemical methods and can lead to new industrially outstanding materials. It is nowadays a vast exciting field of industrial and academic research opening up new frontiers. In this context, an emerging and important methodology for the rapid exploration of composition-pressure-temperature-time space is the in situ method by synchrotron X-ray diffraction. This review introduces the latest advances of high-pressure devices that are adapted to X-ray diffraction in synchrotrons. It focuses particularly on the “large volume” presses (able to compress the volume above several mm3 to pressure higher than several GPa) designed for in situ exploration and that are suitable for discovering and scaling the stable or metastable compounds under “traditional” industrial pressure range (3–8 GPa). We illustrated the power of such methodology by (i) two classical examples of “reference” superhard high-pressure materials, diamond and cubic boron nitride c-BN; and (ii) recent successful in situ high-pressure syntheses of light-element compounds that allowed expanding the domain of possible application high-pressure materials toward solar optoelectronic and infra-red photonics. Finally, in the last section, we summarize some perspectives regarding the current challenges and future directions in which the field of in situ high-pressure synthesis in industrial pressure scale may have great breakthroughs in the next years.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Paradigms for machine learning

Five paradigms are described for machine learning: connectionist (neural network) methods, genetic algorithms and classifier systems, empirical methods for inducing rules and decision trees, analytic learning methods, and case-based approaches. Some dimensions are considered along with these paradigms vary in their approach to learning, and the basic methods are reviewed that are used within each framework, together with open research issues. It is argued that the similarities among the paradigms are more important than their differences, and that future work should attempt to bridge the existing boundaries. Finally, some recent developments in the field of machine learning are discussed, and their impact on both research and applications is examined.

Schlimmer, Jeffrey C.↗
NASA NTRS1992

The planning coordinator: A design architecture for autonomous error recovery and on-line planning of intelligent tasks

Developing a robust, task level, error recovery and on-line planning architecture is an open research area. There is previously published work on both error recovery and on-line planning; however, none incorporates error recovery and on-line planning into one integrated platform. The integration of these two functionalities requires an architecture that possesses the following characteristics. The architecture must provide for the inclusion of new information without the destruction of existing information. The architecture must provide for the relating of pieces of information, old and new, to one another in a non-trivial rather than trivial manner (e.g., object one is related to object two under the following constraints, versus, yes, they are related; no, they are not related). Finally, the architecture must be not only a stand alone architecture, but also one that can be easily integrated as a supplement to some existing architecture. This thesis proposal addresses architectural development. Its intent is to integrate error recovery and on-line planning onto a single, integrated, multi-processor platform. This intelligent x-autonomous platform, called the Planning Coordinator, will be used initially to supplement existing x-autonomous systems and eventually replace them.

Farah, Jeffrey J.↗
NASA NTRS1993

A survey of parametrized variational principles and applications to computational mechanics

This survey paper describes recent developments in the area of parametrized variational principles (PVP's) and selected applications to finite-element computational mechanics. A PVP is a variational principle containing free parameters that have no effect on the Euler-Lagrange equations. The theory of single-field PVP's based on gauge functions (also known as null Lagrangians) is a subset of the inverse problem of variational calculus that has limited value. On the other hand, multifield PVP's are more interesting from theoretical and practical standpoints. Following a tutorial introduction, the paper describes the recent construction of multifield PVP's in several areas of elasticity and electromagnetics. It then discusses three applications to finite-element computational mechanics: the derivation of high-performance finite elements, the development of element-level error indicators, and the constructions of finite element templates. The paper concludes with an overview of open research areas.

Felippa, Carlos A.↗
NASA NTRS2003

Technology Transfer Challenges for High-Assurance Software Engineering Tools

In this paper, we describe our experience with the challenges thar we are currently facing in our effort to develop advanced software verification and validation tools. We categorize these challenges into several areas: cost benefits modeling, tool usability, customer application domain, and organizational issues. We provide examples of challenges in each area and identrfj, open research issues in areas which limit our ability to transfer high-assurance software engineering tools into practice.

John Penix↗
NASA NTRS2012

Achievable Performance and Effective Interrogator Design for SAW RFID Sensor Tags

For many NASA missions, remote sensing is a critical application that supports activities such as environmental monitoring, planetary science, structural shape and health monitoring, non-destructive evaluation, etc. The utility of the remote sensing devices themselves is greatly increased if they are passive V that is, they do not require any on-board power supply such as batteries V and if they can be identified uniquely during the sensor interrogation process. Additional passive sensor characteristics that enable greater utilization in space applications are small size and weight, long read ranges with low interrogator power, ruggedness, and operability in extreme environments (vacuum, extreme high/low temperature, high radiation, etc.) In this paper, we consider one very promising passive sensor technology, called surface acoustic wave (SAW) radio-frequency identification (RFID), that satisfies all of these criteria. In general, RFID is a method of identifying items using radio waves to interrogate tags encoded with a unique identifier that are affixed to the items of interest. In the case of passive tags, only the interrogator, which transmits power to the tags in the form of radio-frequency electromagnetic radiation, requires access to a power supply. Passive RFID technologies are used today in many applications, including asset tracking and management, security and access control, and remote sensing. To date, most of the development and application in RFID technology has focused on either asset/inventory tracking and control or security and access control because these are the largest commercial application areas. Recently however, there has been growing interest in using passive RFID technology for remote sensing applications, and SAW devices are at the forefront of RFID sensing technology development. Although SAW RFID tags have great potential for use in numerous space-based remote sensing applications, the limited collision resolution capability of current generation tags limits the performance in a cluttered sensing environment. That is, as more SAW-based sensors are added to the environment, numerous tag responses are superimposed at the receiver and decoding all or even a subset of the telemetry becomes increasingly difficult. Background clutter generated by reflectors other than the sensors themselves is also a problem, as is multipath interference and signal distortion, but the limiting factor in many remote sensing applications can be expected to be tag mutual interference. This problem may be greatly mitigated by proper design of the SAW tag waveform, but that remains an open research problem, and in the meantime, several other related questions remain to be answered including: (1) What are the fundamental relationships between tag parameters such as bit-rate, time-bandwidth-product, SNR, and achievable collision resolution? (2) What are the differences in optimal or near-optimal interrogator designs between noise-limited environments and interference-limited environments? (3) What are the performance characteristics of different interrogator designs in term of parameters such as transmitter power level, range, and number of interfering tags? In this paper, we will present the results of a research effort aimed at providing at least partial answers to all of these questions.

Barton Richard J.↗
NASA NTRS2011

Achievable Performance and Effective Interrogator Design for SAW RFID Sensor Tags

For many NASA missions, remote sensing is a critical application that supports activities such as environmental monitoring, planetary science, structural shape and health monitoring, non-destructive evaluation, etc. The utility of the remote sensing devices themselves is greatly increased if they are passive that is, they do not require any on-board power supply such as batteries and if they can be identified uniquely during the sensor interrogation process. Additional passive sensor characteristics that enable greater utilization in space applications are small size and weight, long read ranges with low interrogator power, ruggedness, and operability in extreme environments (vacuum, extreme high/low temperature, high radiation, etc.) In this paper, we consider one very promising passive sensor technology, called surface acoustic wave (SAW) radio-frequency identification (RFID), that satisfies all of these criteria. Although SAW RFID tags have great potential for use in numerous space-based remote sensing applications, the limited collision resolution capability of current generation tags limits the performance in a cluttered sensing environment. That is, as more SAW-based sensors are added to the environment, numerous tag responses are superimposed at the receiver and decoding all or even a subset of the telemetry becomes increasingly difficult. Background clutter generated by reflectors other than the sensors themselves is also a problem, as is multipath interference and signal distortion, but the limiting factor in many remote sensing applications can be expected to be tag mutual interference. This problem may be greatly mitigated by proper design of the SAW tag waveform, but that remains an open research problem, and in the meantime, several other related questions remain to be answered including: What are the fundamental relationships between tag parameters such as bit-rate, time-bandwidth-product, SNR, and achievable collision resolution? What are the differences in optimal or near-optimal interrogator designs between noise-limited environments and interference-limited environments? What are the performance characteristics of different interrogator designs in term of parameters such as transmitter power level, range, and number of interfering tags? In this paper, we present the results of a research effort aimed at providing at least partial answers to all of these questions.

Barton, Richard J.↗
NASA NTRS2012

Prognostics for Microgrid Components

Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

Saxena, Abhinav↗
NASA NTRS2016

Titan as the Abode of Life

Titan is the only world we know other than Earth that has a liquid on its surface. It has a thick atmosphere composed of nitrogen and methane with a thick organic haze. There are lakes, rain, and clouds of methane and ethane. Here, we address the question of carbon-based life living in Titan liquids. Photochemically produced organics, particularly acetylene, in Titan's atmosphere could be a source of biological energy when reacted with atmospheric hydrogen. Light levels on the surface of Titan are more than adequate for photosynthesis but the biochemical limitations due to the few elements available in the environment may lead only to simple ecosystems that only consume atmospheric nutrients. Life on Titan may make use of the trace metals and other inorganic elements produced by meteorites as they ablate in the atmosphere. It is conceivable that H2O molecules on Titan could be used in a biochemistry that is rooted in hydrogen bonds in a way that metals are used in enzymes by life on Earth. Previous theoretical work has shown possible membrane structures in Titan liquids, azotosomes, composed of small organic nitrogen compounds, such as acrylonitrile. The search for a plausible information molecule for life in Titan liquids remains an open research topic - polyethers have been considered and shown to be insoluble at Titan temperatures. Possible search strategies for life on Titan include looking for unusual concentrations of certain molecules reflecting biological selection. Homochirality is a special and powerful example of such biology selection. Environmentally, a depletion of hydrogen in the lower atmosphere may be a sign of metabolism. A discovery of life in liquid methane and ethane would be our first compelling indication that the Universe is full of diverse and wondrous life forms.

H2O molecules on Titan↗
NASA NTRS2016

Modeling and Simulation Tools for Heavy Lift Airships

For conventional fixed wing and rotary wing aircraft a variety of modeling and simulation tools have been developed to provide designers the means to thoroughly investigate proposed designs and operational concepts. However, lighter-than-air (LTA) airships, hybrid air vehicles, and aerostats have some important aspects that are different from heavier-than-air (HTA) vehicles. In order to account for these differences, modifications are required to the standard design tools to fully characterize the LTA vehicle design and performance parameters.. To address these LTA design and operational factors, LTA development organizations have created unique proprietary modeling tools, often at their own expense. An expansion of this limited LTA tool set could be accomplished by leveraging existing modeling and simulation capabilities available in the National laboratories and public research centers. Development of an expanded set of publicly available LTA modeling and simulation tools for LTA developers would mitigate the reliance on proprietary LTA design tools in use today. A set of well researched, open source, high fidelity LTA design modeling and simulation tools would advance LTA vehicle development and also provide the analytical basis for accurate LTA operational cost assessments. This paper will present the modeling and analysis tool capabilities required for LTA vehicle design, analysis of operations, and full life-cycle support. A survey of the tools currently available will be assessed to identify the gaps between their capabilities and the LTA industry's needs. Options for development of new modeling and analysis capabilities to supplement contemporary tools will also be presented.

airship design and analysis↗