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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The use of multiple models in case-based diagnosis

The work described in this paper has as its goal the integration of a number of reasoning techniques into a unified intelligent information system that will aid flight crews with malfunction diagnosis and prognostication. One of these approaches involves using the extensive archive of information contained in aircraft accident reports along with various models of the aircraft as the basis for case-based reasoning about malfunctions. Case-based reasoning draws conclusions on the basis of similarities between the present situation and prior experience. We maintain that the ability of a CBR program to reason about physical systems is significantly enhanced by the addition to the CBR program of various models. This paper describes the diagnostic concepts implemented in a prototypical case based reasoner that operates in the domain of in-flight fault diagnosis, the various models used in conjunction with the reasoner's CBR component, and results from a preliminary evaluation.

Karamouzis, Stamos T.↗
NASA NTRS1992

A study of mapping exogenous knowledge representations into CONFIG

Qualitative reasoning is reasoning with a small set of qualitative values that is an abstraction of a larger and perhaps infinite set of quantitative values. The use of qualitative and quantitative reasoning together holds great promise for performance improvement in applications that suffer from large and/or imprecise knowledge domains. Included among these applications are the modeling, simulation, analysis, and fault diagnosis of physical systems. Several research groups continue to discover and experiment with new qualitative representations and reasoning techniques. However, due to the diversity of these techniques, it is difficult for the programs produced to exchange system models easily. The availability of mappings to transform knowledge from the form used by one of these programs to that used by another would open the doors for comparative analysis of these programs in areas such as completeness, correctness, and performance. A group at the Johnson Space Center (JSC) is working to develop CONFIG, a prototype qualitative modeling, simulation, and analysis tool for fault diagnosis applications in the U.S. space program. The availability of knowledge mappings from the programs produced by other research groups to CONFIG may provide savings in CONFIG's development costs and time, and may improve CONFIG's performance. The study of such mappings is the purpose of the research described in this paper. Two other research groups that have worked with the JSC group in the past are the Northwest University Group and the University of Texas at Austin Group. The former has produced a qualitative reasoning tool named SIMGEN, and the latter has produced one named QSIM. Another program produced by the Austin group is CC, a preprocessor that permits users to develop input for eventual use by QSIM, but in a more natural format. CONFIG and CC are both based on a component-connection ontology, so a mapping from CC's knowledge representation to CONFIG's knowledge representation was chosen as the focus of this study. A mapping from CC to CONFIG was developed. Due to differences between the two programs, however, the mapping transforms some of the CC knowledge to CONFIG as documentation rather than as knowledge in a form useful to computation. The study suggests that it may be worthwhile to pursue the mappings further. By implementing the mapping as a program, actual comparisons of computational efficiency and quality of results can be made between the QSIM and CONFIG programs. A secondary study may reveal that the results of the two programs augment one another, contradict one another, or differ only slightly. If the latter, the qualitative reasoning techniques may be compared in other areas, such as computational efficiency.

Mayfield, Blayne E.↗
NASA NTRS2005

A novel tiered sensor fusion approach for terrain characterization and safe landing assessment

This paper presents a novel tiered sensor fusion methodology for real-time terrain safety assessment. A combination of active and passive sensors, specifically, radar, lidar, and camera, operate in three tiers according to their inherent ranges of operation. Low-level terrain features (e.g. slope, roughness) and high-level terrain features (e.g. hills, craters) are integrated using principles of reasoning under uncertainty. Three methodologies are used to infer landing safety: Fuzzy Reasoning, Probabilistic Reasoning, and Evidential Reasoning. The safe landing predictions from the three fusion engines are consolidated in a subsequent decision fusion stage aimed at combining the strengths of each fusion methodology. Results from simulated spacecraft descents are presented and discussed.

fuzzy reasoning↗
DOE OSTI2026

py-boomer v0.1.0

Py-BOOMER (Python Bayesian OWL Ontology MErgER in Python) is a probabilistic reasoning system for knowledge representation and ontological reasoning with uncertainty. Itnables reasoning over probabilistic facts and taxonomic relationships, finding the most likely consistent interpretation of potentially conflicting assertions. It uses a combination of graph-based reasoning and Bayesian probabilistic inference. Key features: Represent probabilistic ontological statements Reason over class subsumption hierarchies Evaluate class equivalence relationships Detect and resolve logical inconsistencies Calculate posterior probabilities for each assertion

Mungall, Chris [Lawrence Berkeley National Laborat↗
DOE OSTI2014

Guidelines for Beamline and Front-End Radiation Shielding Design at the Advanced Photon Source (Rev. 5)

Shielding for the APS will be such that the individual radiation worker dose will be as low as reasonably achievable (ALARA). The ALARA goals for the APS are to keep the total of the work-related radiation exposure (exposure coming from other than natural or medical sources) as far below 5 person mSv/yr (500 person-mrem/yr), collective total effective dose equivalent, as reasonably achievable. For an individual APS radiation worker, the goal is to keep the maximum occupational total effective dose equivalent of any one employee as far below 2 mSv/yr as reasonably achievable. The ALARA goal for APS beamline scientists is to keep the total of the work-related radiation exposure (exposure coming from other than natural or medical sources) as far below 1 person mSv/yr (100 person-mrem/yr), collective total effective dose equivalent, as reasonably achievable. For an individual APS beamline scientist, the goal is to keep the maximum occupational total effective dose equivalent of any one scientist as far below 0.5 mSv/yr (50 mrem/yr) as reasonably achievable. The dose is actively monitored by the radiation monitors on the storage ring wall in each sector and by the frequent area surveys performed by the health physics personnel. For cases in which surveys indicate elevated hourly dose rates that may impact worker exposure, additional local shielding is provided to reduce the radiation field to an acceptable level. Passive area monitors are used throughout the facility to integrate doses in various areas. The results are analyzed for trends of increased doses, and shielding in these areas is evaluated and improved, as appropriate. The APS policy for on-site nonradiation workers in the vicinity of the APS facilities requires that the average nonradiation worker dose be below 0.2 mSv/yr (20 mrem/yr). In addition, the dose at the site boundary from all pathways is required to be below 0.1 mSv/yr (10 mrem/yr). For future modifications of the facility, the doses shall be evaluated and additional shielding provided to meet the policy requirements.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1988

Diagnostics in the Extendable Integrated Support Environment (EISE)

Extendable Integrated Support Environment (EISE) is a real-time computer network consisting of commercially available hardware and software components to support systems level integration, modifications, and enhancement to weapons systems. The EISE approach offers substantial potential savings by eliminating unique support environments in favor of sharing common modules for the support of operational weapon systems. An expert system is being developed that will help support diagnosing faults in this network. This is a multi-level, multi-expert diagnostic system that uses experiential knowledge relating symptoms to faults and also reasons from structural and functional models of the underlying physical model when experiential reasoning is inadequate. The individual expert systems are orchestrated by a supervisory reasoning controller, a meta-level reasoner which plans the sequence of reasoning steps to solve the given specific problem. The overall system, termed the Diagnostic Executive, accesses systems level performance checks and error reports, and issues remote test procedures to formulate and confirm fault hypotheses.

Brink, James R.↗
NASA NTRS1993

An architecture for object-oriented intelligent control of power systems in space

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Holmquist, Sven G.↗
NASA NTRS2001

The Logic of Reachability

In recent years, Graphplan style reachability analysis and mutual exclusion reasoning have been used in many high performance planning systems. While numerous refinements and extensions have been developed, the basic plan graph structure and reasoning mechanisms used in these systems are tied to the very simple STRIPS model of action. In 1999, Smith and Weld generalized the Graphplan methods for reachability and mutex reasoning to allow actions to have differing durations. However, the representation of actions still has some severe limitations that prevent the use of these techniques for many real-world planning systems. In this paper, we 1) separate the logic of reachability from the particular representation and inference methods used in Graphplan, and 2) extend the notions of reachability and mutual exclusion to more general notions of time and action. As it turns out, the general rules for mutual exclusion reasoning take on a remarkably clean and simple form. However, practical instantiations of them turn out to be messy, and require that we make representation and reasoning choices.

Smith, David E.↗
NASA NTRS2006

Towards a Compositional SPIN

This paper discusses our initial experience with introducing automated assume-guarantee verification based on learning in the SPIN tool. We believe that compositional verification techniques such as assume-guarantee reasoning could complement the state-reduction techniques that SPIN already supports, thus increasing the size of systems that SPIN can handle. We present a "light-weight" approach to evaluating the benefits of learning-based assume-guarantee reasoning in the context of SPIN: we turn our previous implementation of learning for the LTSA tool into a main program that externally invokes SPIN to provide the model checking-related answers. Despite its performance overheads (which mandate a future implementation within SPIN itself), this approach provides accurate information about the savings in memory. We have experimented with several versions of learning-based assume guarantee reasoning, including a novel heuristic introduced here for generating component assumptions when their environment is unavailable. We illustrate the benefits of learning-based assume-guarantee reasoning in SPIN through the example of a resource arbiter for a spacecraft. Keywords: assume-guarantee reasoning, model checking, learning.

Pasareanu, Corina S.↗
NASA NTRS2012

Intelligent Data Visualization for Cross-Checking Spacecraft System Diagnosis

Any reasoning system is fallible, so crew members and flight controllers must be able to cross-check automated diagnoses of spacecraft or habitat problems by considering alternate diagnoses and analyzing related evidence. Cross-checking improves diagnostic accuracy because people can apply information processing heuristics, pattern recognition techniques, and reasoning methods that the automated diagnostic system may not possess. Over time, cross-checking also enables crew members to become comfortable with how the diagnostic reasoning system performs, so the system can earn the crew s trust. We developed intelligent data visualization software that helps users cross-check automated diagnoses of system faults more effectively. The user interface displays scrollable arrays of timelines and time-series graphs, which are tightly integrated with an interactive, color-coded system schematic to show important spatial-temporal data patterns. Signal processing and rule-based diagnostic reasoning automatically identify alternate hypotheses and data patterns that support or rebut the original and alternate diagnoses. A color-coded matrix display summarizes the supporting or rebutting evidence for each diagnosis, and a drill-down capability enables crew members to quickly view graphs and timelines of the underlying data. This system demonstrates that modest amounts of diagnostic reasoning, combined with interactive, information-dense data visualizations, can accelerate system diagnosis and cross-checking.

Ong, James C.↗
NASA NTRSDate not supplied

A Temporal Differential Dynamic Logic Formal Embedding

Differential dynamic logic is a formal framework to specify and reason about hybrid programs (HPs). The core of dL is a proof calculus that contains a collection of axioms and rules for the rigorous verification of properties of HPs. Recently, dL has been embedded within the theorem prover Prototype Verification System (PVS) resulting in the tool Plaidypvs2. The integration of dL into PVS expands its expressive power; user defined functions, such as trigonometric and other transcendental functions, can be used inside the dL framework, and meta-reasoning about HPs can be performed, including reasoning about entire classes of HPs, specified using dependent types in PVS. The differential temporal dynamic logic (dTL2) extends dL with temporal logic operators to reason about all the states reachable during the execution of an HP. This paper presents a work in progress focusing on embedding dTL2 in PVS as an extension of Plaidypvs. Plaidypvs is expanded with the formalization of a trace semantics for HPs, the definition of the LTL temporal operators eventually and globally, and the implementation of the proof calculus for dTL2. This new embedding has the same capabilties as Plaidypvs, which allows user defined functions and meta-reasoning of properties of HPs. To the best of the authors’ knowledge this is the first implementation of dTL2.

differential dynamic logic↗
DOE OSTI2019

Physical properties of RF magnetron sputtered GaN/n-Si thin film: impacts of RF power

GaN thin film was successfully produced on n-Si(100) substrate by RF magnetron sputter under different RF power. Experimental measurement techniques such as UV/Vis spectroscopy, field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), atomic force microscopy (AFM), and Micro-Raman Spectroscopy were used to research effects of Radio Frequency power on physical properties of produced thin film. It has been found that produced thin film was polycrystalline structure with (100) and (110) planes of hexagonal GaN from X-ray diffraction measurement result. It also proved that increasing RF power gives rise to deterioration in crystal quality of GaN thin film. Reason of this deterioration was discussed. It has been achieved that increasing RF power has resulted in decreasing optical band gap energy of GaN thin film. Reasons for these changes in optical band gap energy were explained. It was seen that some thin films were grown as layer-plus-island mode (Stranski–Krastanov growth mode) and others were grown as layer-by-layer growth mode (Frank van der Merwe mode) from AFM analysis. It has been found that increasing RF power has resulted in improvement of surface morphology of thin film from field emission scanning electron microscopy analysis. However, reaching RF power to 125 W leads to start to deteriorate of surface of GaN thin film. The reasons for this have been discussed. E{sub 1}(TO) transverse optical phonon mode of hexagonal GaN with different intensity was detected from Micro-Raman Spectroscopy measurement. The reasons for this difference have been discussed. It was concluded that RF power has played a significant role in growing high quality GaN thin film. Morphological, structural, and optical properties of GaN thin film were enhanced by controlling RF power, making them a potential candidate for LED, solar cell, diode application.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

On the applicability of the Redlich-Kister framework for viscosity estimation of molten halide salt mixtures

For molten halide salt mixtures already being utilized or under consideration for carbon-free energy production systems, it is crucial that their viscosity is well understood so that system thermal hydraulics can be reliably assessed. Because of the difficulty in accurately measuring molten halide viscosity and the sheer size of the matrix of possible higher order salt mixtures that may be of interest to the energy industry, there are several gaps in the quantified understanding of molten halide viscosity across this matrix. As such, both first-principles and semi-empirical modeling techniques may be crucial for rapidly assessing this broad, complex compositional domain. Herein, the Redlich-Kister framework is applied to assess the feasibility of broadly interpolating and estimating the viscosity of several pseudobinary and pseudoternary molten halide salt systems that may be of key interest to the energy industry. The framework is based on the assumption that an ideal component and a nonideal component collectively describe the viscosity as a function of composition and temperature for a given molten halide system. Three different ideal models were considered for the ideal component, including Grunburg-Nissan, Katti-Chaudhri, and Gambill methods. Regarding the pseudobinary interpolations, the Redlich-Kister models with either the Grunburg-Nissan or Katti-Chaudhri models as the ideal component resulted in either highly (average error less than 5%) or reasonably (average error less than 15%) accurate interpolations of pseudobinary halide viscosity; BeF 2 - or UF 4 -bearing salts tended to result in reasonably accurate interpolations, whereas other pseudobinary mixtures tended to show high accuracy. Regarding the pseudoternary extrapolations, the Redlich-Kister framework shows reasonable success at estimating the extent to which a pseudoternary system may indicate deviations from ideal Grunburg-Nissan mixing, where discrepancies with comparative experimental data generally stay within 30%. Finally, the primary reasons identified for such discrepancies are (1) inaccuracy in the underlying experimental data, (2) different complexation behavior in the higher order systems compared to the pseudobinary subsystems, and (3) extrapolation into temperatures too far out of the domain, which is valid for the underlying experimental data feeding the Redlich-Kister model.

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

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗
DOE OSTI2022

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Nuclear quantum effects in water exchange around lithium and fluoride ions

We employ classical and ring polymer molecular dynamics simulations to study the effect of nuclear quantum fluctuations on the structure and the water exchange dynamics of aqueous solutions of lithium and fluoride ions. While we obtain reasonably good agreement with experimental data for solutions of lithium by augmenting the Coulombic interactions between the ion and the water molecules with a standard Lennard-Jones ion-oxygen potential, the same is not true for solutions of fluoride, for which we find that a potential with a softer repulsive wall gives much better agreement. A small degree of destabilization of the first hydration shell is found in quantum simulations of both ions when compared with classical simulations, with the shell becoming less sharply defined and the mean residence time of the water molecules in the shell decreasing. In line with these modest differences, we find that the mechanisms of the exchange processes are unaffected by quantization, so a classical description of these reactions gives qualitatively correct and quantitatively reasonable results. We also find that the quantum effects in solutions of lithium are larger than in solutions of fluoride. This is partly due to the stronger interaction of lithium with water molecules, partly due to the lighter mass of lithium and partly due to competing quantum effects in the hydration of fluoride, which are absent in the hydration of lithium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

THREE-DIMENSIONAL FEATURES OF THE OUTER HELIOSPHERE DUE TO COUPLING BETWEEN THE INTERSTELLAR AND INTERPLANETARY MAGNETIC FIELDS. IV. SOLAR CYCLE MODEL BASED ON ULYSSES OBSERVATIONS

The solar cycle has a profound influence on the solar wind (SW) interaction with the local interstellar medium (LISM) on more than one timescales. Also, there are substantial differences in individual solar cycle lengths and SW behavior within them. The presence of a slow SW belt, with a variable latitudinal extent changing within each solar cycle from rather small angles to 90 Degree-Sign , separated from the fast wind that originates at coronal holes substantially affects plasma in the inner heliosheath (IHS)-the SW region between the termination shock (TS) and the heliopause (HP). The solar cycle may be the reason why the complicated flow structure is observed in the IHS by Voyager 1. In this paper, we show that a substantial decrease in the SW ram pressure observed by Ulysses between the TS crossings by Voyager 1 and 2 contributes significantly to the difference in the heliocentric distances at which these crossings occurred. The Ulysses spacecraft is the source of valuable information about the three-dimensional and time-dependent properties of the SW. Its unique fast latitudinal scans of the SW regions make it possible to create a solar cycle model based on the spacecraft in situ measurements. On the basis of our analysis of the Ulysses data over the entire life of the mission, we generated time-dependent boundary conditions at 10 AU from the Sun and applied our MHD-neutral model to perform a numerical simulation of the SW-LISM interaction. We analyzed the global variations in the interaction pattern, the excursions of the TS and the HP, and the details of the plasma and magnetic field distributions in the IHS. Numerical results are compared with Voyager data as functions of time in the spacecraft frame. We discuss solar cycle effects which may be reasons for the recent decrease in the TS particles (ions accelerated to anomalous cosmic-ray energies) flux observed by Voyager 1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Logical Model of Homology for Comparative Biology

There is a growing body of research on the evolution of anatomy in a wide variety of organisms. Discoveries in this field could be greatly accelerated by computational methods and resources that enable these findings to be compared across different studies and different organisms and linked with the genes responsible for anatomical modifications. Homology is a key concept in comparative anatomy; two important types are historical homology (the similarity of organisms due to common ancestry) and serial homology (the similarity of repeated structures within an organism). We explored how to most effectively represent historical and serial homology across anatomical structures to facilitate computational reasoning. We assembled a collection of homology assertions from the literature with a set of taxon phenotypes for the skeletal elements of vertebrate fins and limbs from the Phenoscape Knowledgebase. Using seven competency questions, we evaluated the reasoning ramifications of two logical models: the Reciprocal Existential Axioms (REA) homology model and the Ancestral Value Axioms (AVA) homology model. The AVA model returned all user-expected results in addition to the search term and any of its subclasses. The AVA model also returns any superclass of the query term in which a homology relationship has been asserted. The REA model returned the user-expected results for five out of seven queries. We identify some challenges of implementing complete homology queries due to limitations of OWL reasoning. This work lays the foundation for homology reasoning to be incorporated into other ontology-based tools, such as those that enable synthetic supermatrix construction and candidate gene discovery.

59 BASIC BIOLOGICAL SCIENCES↗