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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Color constancy - A method for recovering surface spectral reflectance

An algorithm has been developed for estimating the surface reflectance functions of objects in a scene with incomplete knowledge of the spectral power distribution of the ambient light. An image processing system employing this algorithm can assign colors that are constant despite changes in the lighting of the scene; this capability is essential to correct color rendering in photography, TV, and in the construction of artificial visual systems for robotics. Attention is given to the way in which constraints on lights and surfaces in the environment make color-constancy possible for a visual system, and the algorithm's implications for human color vision are discussed.

Maloney, L. T.↗
DOE OSTI2022

graphenv: a Python library for reinforcement learning on graph search spaces

Many important and challenging problems in combinatorial optimization (CO) can be expressed as graph search problems, in which graph vertices represent full or partial solutions and edges represent decisions that connect them. Graph structure not only introduces strong relational inductive biases for learning (Battaglia et al., 2018) - in this context, by providing a way to explicitly model the value of transitioning (along edges) between one search state (vertex) and the next - but lends itself to problems both with and without clearly defined algebraic structure. For example, classic CO problems on graphs such as the Traveling Salesman Problem (TSP) can be expressed as either pure graph search or integer programs. Other problems, however, such as molecular optimization, do no have concise algebraic formulations and yet are readily implemented as a graph search (V. et al., 2022; Zhou et al., 2019). Such "model-free" problems constitute a large fraction of modern reinforcement learning (RL) research owing to the fact that it is often much easier to write a forward simulation that expresses all of the state transitions and rewards, than to write down the precise mathematical expression of the full optimization problem. In the case of molecular optimization, for example, one can use domain knowledge alongside existing software libraries to model the effect of adding a single bond or atom to an existing but incomplete molecule, and let the RL algorithm build a model of how good a given decision is by "experiencing" the simulated environment many times through. In contrast, a model-based mathematical formulation that fully expresses all the chemical and physical constraints is intractable. In recent years, RL has emerged as an effective paradigm for optimizing searches over graphs and led to state-of-the-art heuristics for games like Go and chess, as well as for classical CO problems such as the TSP. This combination of graph search and RL, while powerful, requires non-trivial software to execute, especially when combining advanced state representations such as Graph Neural Networks (GNN) with scalable RL algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Shape Optimization for Control and Isolation of Structural Vibrations in Aerospace and Defense Applications

Among the main challenges in shape optimization is the coupling of Finite Element Method (FEM) codes in a way that facilitates efficient computation of shape derivatives. This is particularly difficult with multi-physics problems involving legacy codes, where the costs of implementing and maintaining shape derivative capabilities are prohibitive. There are two mathematically equivalent approaches to computing the shape derivative: the volume method, and the boundary method. Each has a major drawback: the boundary method is less accurate, while the volume method is more invasive to the FEM code. Prior implementations of shape derivatives at Sandia have been based on the volume method. We introduce the strip method, which computes shape derivatives on a strip adjacent to the boundary. The strip method makes code coupling simple. Like the boundary method, it queries the state and adjoint solutions at quadrature nodes, but requires no knowledge of the FEM code implementations. At the same time, it exhibits the higher accuracy of the volume method. The development of the strip method also offers us the opportunity to share some lessons learned about implementing the volume method and boundary method, to show shape optimization results on problems of interest, and to begin addressing the other main challenges at hand: constraints on optimized shapes, and their interplay with optimization algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Joint Inversion of Surface Electrical Resistivity Tomography and Seismic Refraction Data between the 200 Areas

Geologic stratigraphy on the Hanford Site influences groundwater and contaminant migration through the aquifer system and the vadose zone. The current geologic framework model (GFM) relies heavily on a sparse distribution of borehole data in some locations to map geologic contacts and hydrologic properties in the subsurface. Non-invasive geophysical methods such as electrical resistivity tomography (ERT), transient electromagnetic surveying, and seismic imaging are being used at Hanford to map subsurface structure in areas with limited well observations. This is to develop and mature the capability of geophysical methods to aid in GFM refinement, to identify regions of subsurface complexity, and for optimal well siting. A joint inversion of co-located seismic refraction and ERT data was carried out for data collected on a ~2.3-km profile between the 200 Areas on the Hanford Site. While ERT and seismic refraction images have sensitivity to overlapping physical properties (porosity, moisture content, lithology), the resolution and physics used to acquire each of these datasets are different and therefore information can be different or mutually complementary. Performing a joint inversion provides a reasonable option for a coherent, coupled interpretation for mutually complementary datasets. Between the 200 Areas, there are few boreholes to interpret the geologic framework model, and these data sets were obtained to provide a first line of evidence toward identifying stratigraphic structure. The seismic refraction and ERT data were independently inverted during fiscal year 2022 and broadly showed a two-layer structure with a trough-like feature that is ~1 km wide and upwards of 150 m deep. The depth of the trough feature was greater in the ERT image compared to the seismic image, which indicated a maximum depth of approximately 110 m. The objective of the joint inversion described in this report was to invert the seismic refraction and ERT data together while constraining the ERT image to be structurally similar to the seismic refraction image. The approach was applied using the geophysical inverse modeling program E4D, which has the capability to invert first-arrival times from seismic refraction data and ERT resistances using a “cross-gradient” constraint. The application of cross-gradient constraints with different weights produces ERT models that show a high degree of similarity within the upper 100 m (above ~120 m elevation). None of the ERT models show an improved structural similarity to the seismic result; therefore, it is recommended that further attempts to jointly interpret these models focus on petrophysics and image resolution. Petrophysical measurements of core samples would improve knowledge of what drives the ERT response in this region and, along with downhole geophysical measurements, could be used to “ground truth” the surface-based geophysical results. Image resolution studies would provide insight into which regions of the inverted images are reliable and which regions are poorly constrained.

58 GEOSCIENCES↗
DOE OSTI2021

Machine Learning Predictions of Transition Probabilities in Atomic Spectra

Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Kinetics Modeling and Reactor Design Study of Glucose-to-Terpenes Cell-Free Conversion

Cell-free systems offer many advantages over traditional biological conversion by eliminating biological growth constraints. It also offers easy manipulation and finetuning of the reaction conditions for each individual enzyme. The conversion of cellulosic glucose to Limonene, a terpene, is a promising pathway for producing fuels and chemicals. Recent advances in developing cell-free systems focuses on bench scale optimization of terpene yield and to demonstrate its feasibility towards commercialization [1,2]. There is significant knowledge gap regarding reaction kinetics of these cell-free systems to further study how it will perform at larger scale. We present here, our studies on reaction kinetics and reactor design implications of cell-free glucose to Limonene conversion to facilitate the further development and commercialization of this process. We developed a novel kinetic model based on the metabolic-network structure of the cell-free system with multi-substrate reversible Michaelis-Menten rate law. To estimate kinetic parameters for this system of rate equations, we employed Bayesian optimization to perform global search with the assistance of gaussian processes to balance exploration and exploitation. The model parameters estimated showed good results compared with experimental data. The estimated parameters were used to perform sensitivity analysis. We found that Hexokinase is one of the most critical enzymes that affect the conversion of the glucose. We also observed that abundance of co-factors is also critical to the conversion of glucose to limonene. We investigated packed bed reactors with enzymes immobilized on the surface of particles to convert glucose stream into Limonene for larger scale production. The reactor design such as particle size, enzyme loading, and flow rate are found to be critical for improving yields. [1] Dudley, Q.M., Nash, C.J. and Jewett, M.C., 2019. Synthetic Biology, 4(1), p.ysz003. [2] Korman, T.P., Opgenorth, P.H. and Bowie, J.U., 2017. Nature communications, 8(1), p.15526.

09 BIOMASS FUELS↗
NASA NTRS1989

Global models: Robot sensing, control, and sensory-motor skills

Robotics research has begun to address the modeling and implementation of a wide variety of unstructured tasks. Examples include automated navigation, platform servicing, custom fabrication and repair, deployment and recovery, and science exploration. Such tasks are poorly described at onset; the workspace layout is partially unfamiliar, and the task control sequence is only qualitatively characterized. The robot must model the workspace, plan detailed physical actions from qualitative goals, and adapt its instantaneous control regimes to unpredicted events. Developing robust representations and computational approaches for these sensing, planning, and control functions is a major challenge. The underlying domain constraints are very general, and seem to offer little guidance for well-bounded approximation of object shape and motion, manipulation postures and trajectories, and the like. This generalized modeling problem is discussed, with an emphasis on the role of sensing. It is also discussed that unstructured tasks often have, in fact, a high degree of underlying physical symmetry, and such implicit knowledge should be drawn on to model task performance strategies in a methodological fashion. A group-theoretic decomposition of the workspace organization, task goals, and their admissible interactions are proposed. This group-mechanical approach to task representation helps to clarify the functional interplay of perception and control, in essence, describing what perception is specifically for, versus how it is generically modeled. One also gains insight how perception might logically evolve in response to needs of more complex motor skills. It is discussed why, of the many solutions that are often mathematically admissible to a given sensory motor-coordination problem, one may be preferred over others.

Schenker, Paul S.↗
NASA NTRS1991

Guidance, navigation, and control subsystem equipment selection algorithm using expert system methods

Enhanced engineering tools can be obtained through the integration of expert system methodologies and existing design software. The application of these methodologies to the spacecraft design and cost model (SDCM) software provides an improved technique for the selection of hardware for unmanned spacecraft subsystem design. The knowledge engineering system (KES) expert system development tool was used to implement a smarter equipment section algorithm than that which is currently achievable through the use of a standard data base system. The guidance, navigation, and control subsystems of the SDCM software was chosen as the initial subsystem for implementation. The portions of the SDCM code which compute the selection criteria and constraints remain intact, and the expert system equipment selection algorithm is embedded within this existing code. The architecture of this new methodology is described and its implementation is reported. The project background and a brief overview of the expert system is described, and once the details of the design are characterized, an example of its implementation is demonstrated.

Allen, Cheryl L.↗
NASA NTRS1998

Challenges to Laser-Based Imaging Techniques in Gas Turbine Combustor Systems for Aerospace Applications

Increasingly severe constraints on emissions, noise and fuel efficiency must be met by the next generation of commercial aircraft powerplants. At NASA Lewis Research Center (LeRC) a cooperative research effort with industry is underway to design and test combustors that will meet these requirements. To accomplish these tasks, it is necessary to gain both a detailed understanding of the combustion processes and a precise knowledge of combustor and combustor sub-component performance at close to actual conditions. To that end, researchers at LeRC are engaged in a comprehensive diagnostic investigation of high pressure reacting flowfields that duplicate conditions expected within the actual engine combustors. Unique, optically accessible flame-tubes and sector rig combustors, designed especially for these tests. afford the opportunity to probe these flowfields with the most advanced, laser-based optical diagnostic techniques. However, these same techniques, tested and proven on comparatively simple bench-top gaseous flame burners, encounter numerous restrictions and challenges when applied in these facilities. These include high pressures and temperatures, large flow rates, liquid fuels, remote testing, and carbon or other material deposits on combustor windows. Results are shown that document the success and versatility of these nonintrusive optical diagnostics despite the challenges to their implementation in realistic systems.

Locke, Randy J.↗
NASA NTRS2011

Optimal Asteroid Mass Determination from Planetary Range Observations: A Study of a Simplified Test Model

Mars ranging observations are available over the past 10 years with an accuracy of a few meters. Such precise measurements of the Earth-Mars distance provide valuable constraints on the masses of the asteroids perturbing both planets. Today more than 30 asteroid masses have thus been estimated from planetary ranging data (see [1] and [2]). Obtaining unbiased mass estimations is nevertheless difficult. Various systematic errors can be introduced by imperfect reduction of spacecraft tracking observations to planetary ranging data. The large number of asteroids and the limited a priori knowledge of their masses is also an obstacle for parameter selection. Fitting in a model a mass of a negligible perturber, or on the contrary omitting a significant perturber, will induce important bias in determined asteroid masses. In this communication, we investigate a simplified version of the mass determination problem. Instead of planetary ranging observations from spacecraft or radar data, we consider synthetic ranging observations generated with the INPOP [2] ephemeris for a test model containing ~25000 asteroids. We then suggest a method for optimal parameter selection and estimation in this simplified framework.

asteroids↗
NASA NTRS1992

Ureilites - A critical review

The paper discusses the current state of understanding of the petrogenesis of ureilites (which are ultramafic rocks considered to be products of a common planetary differentiation process), identifies areas in which basic knowledge is lacking, and suggests directions for future work on these rocks. The petrographic, chemical, and isotopic characteristics of ureilites are summarized, and petrogenetic implications of these characteristics are discussed. Particular attention is given to the apparent contradiction between the igneous and primitive features of ureilites. Several recently proposed models for ureilite petrogenesis are evaluated in terms of how well they satisfy these constraints and how they attempt to resolve the conflict between the igneous and primitive features. It is concluded that none of the proposed models satisfy all constraints satisfactorily.

Goodrich, Cyrena A.↗
NASA NTRS2004

Execution of the Spitzer In-orbit Checkout and Science Verification Plan

The Spitzer Space Telescope is an 85-cm telescope with three cryogenically cooled instruments. Following launch, the observatory was initialized and commissioned for science operations during the in-orbit checkout (IOC) and science verification (SV) phases, carried out over a total of 98.3 days. The execution of the IOC/SV mission plan progressively established Spitzer capabilities taking into consideration thermal, cryogenic, optical, pointing, communications, and operational designs and constraints. The plan was carried out with high efficiency, making effective use of cryogen-limited flight time. One key component to the success of the plan was the pre-launch allocation of schedule reserve in the timeline of IOC/SV activities, and how it was used in flight both to cover activity redesign and growth due to continually improving spacecraft and instrument knowledge, and to recover from anomalies. This paper describes the adaptive system design and evolution, implementation, and lessons learned from IOC/SV operations. It is hoped that this information will provide guidance to future missions with similar engineering challenges

operations↗
NASA NTRS2010

Constraints on Mercury's Na Exosphere: Combined MESSENGER and Ground-Based Data

We have used observations of sodium emission obtained with the McMath-Pierce solar telescope and MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer (MASCS) to constrain models of Mercury's sodium exosphere, The distribution of sodium in Mercury's exosphere during the period January 12-15. 2008. was mapped using the McMath-Pierce solar telescope with the 5" X 5" image slicer to observe the D-line emission. On January 14, 2008, the Ultraviolet and Visible Spectrometer (UVVS) channel on MASCS sampled the sodium in Mercury's anti-sunward tail region. We find that the bound exosphere has an equivalent temperature of 900-1200 K, and that this temperature can be achieved if the sodium is ejected either by photon-stimulated desorption (PSD) with a 1200 K Maxwellian velocity distribution, or by thermal accommodation of a hotter source. We were not able to discriminate between the two assumed velocity distributions of the ejected particles for the PSD. but the velocity distributions require different values of the thermal accommodation coefficient and result in different upper limits on impact vaporization, We were able to place a strong constraint on the impact vaporization rate that results in the release of neutral Na atoms with an upper limit of 2.1 x 10(exp 6) sq cm/s, The variability of the week-long ground-based observations can be explained by variations in the sources, including both PSD and ion-enhanced PSD, as well as possible temporal enhancements in meteoroid vaporization. Knowledge of both dayside and anti-sunward tail morphologies and radiances are necessary to correctly deduce the exospheric source rates, processes, velocity distribution, and surface interaction.

Mouawad, Nelly↗
NASA NTRS2015

Lunar Magma Ocean Crystallization: Constraints from Fractional Crystallization Experiments

The currently accepted paradigm of lunar formation is that of accretion from the ejecta of a giant impact, followed by crystallization of a global scale magma ocean. This model accounts for the formation of the anorthosite highlands crust, which is globally distributed and old, and the formation of the younger mare basalts which are derived from a source region that has experienced plagioclase extraction. Several attempts at modelling the crystallization of such a lunar magma ocean (LMO) have been made, but our ever-increasing knowledge of the lunar samples and surface have raised as many questions as these models have answered. Geodynamic models of lunar accretion suggest that shortly following accretion the bulk of the lunar mass was hot, likely at least above the solidus]. Models of LMO crystallization that assume a deep magma ocean are therefore geodynamically favorable, but they have been difficult to reconcile with a thick plagioclase-rich crust. A refractory element enriched bulk composition, a shallow magma ocean, or a combination of the two have been suggested as a way to produce enough plagioclase to account for the assumed thickness of the crust. Recently however, geophysical data from the GRAIL mission have indicated that the lunar anorthositic crust is not as thick as was initially estimated, which allows for both a deeper magma ocean and a bulk composition more similar to the terrestrial upper mantle. We report on experimental simulations of the fractional crystallization of a deep (approximately 100km) LMO with a terrestrial upper mantle-like (LPUM) bulk composition. Our experimental results will help to define the composition of the lunar crust and mantle cumulates, and allow us to consider important questions such as source regions of the mare basalts and Mg-suite, the role of mantle overturn after magma ocean crystallization and the nature of KREEP

Rapp, J. F.↗
DOE OSTI2024

The Science, Engineering, and Validation of Marine Carbon Dioxide Removal and Storage

Scenarios to stabilize global climate and meet international climate agreements require rapid reductions in human carbon dioxide (CO 2 ) emissions, often augmented by substantial carbon dioxide removal (CDR) from the atmosphere. While some ocean-based removal techniques show potential promise as part of a broader CDR and decarbonization portfolio, no marine approach is ready yet for deployment at scale because of gaps in both scientific and engineering knowledge. Marine CDR spans a wide range of biotic and abiotic methods, with both common and technique-specific limitations. Further targeted research is needed on CDR efficacy, permanence, and additionality as well as on robust validation methods—measurement, monitoring, reporting, and verification—that are essential to demonstrate the safe removal and long-term storage of CO 2 . Engineering studies are needed on constraints including scalability, costs, resource inputs, energy demands, and technical readiness. Research on possible co-benefits, ocean acidification effects, environmental and social impacts, and governance is also required.

climate mitigation↗
NASA NTRS1983

Bringing AI up to the space challenge

The state of the art in automated systems for working in environments hostile to humans is assessed, together with the technological advancements necessary to meet NASA goals. Since completely automated operations are not possible with the current level of artificial intelligence (AI), the operator must have access to remote television access and interactive computerized controls. A proximal system exists when the teleoperated mechanism is close enough so that negligible time passes between operator and servocontrolled activation and feedback. An additional constraint is the complexity of the signal. Further development areas have been identified as limiting the necessary communication, compensating for technical limitations of communication with remote systems, such as bandwidth, error rate, and equipment response time, and to build-in fault tolerance, self-diagnosis, and self-maintenance capabilities. An AI expert system is being developed at JPL to provide an expert knowledge base and a decision-making capability. It is suggested that only thorough questioning of mission and spacecraft experts, as well as searching the large volume of project documentations, will provide the necessary data for establishing an expert data base for AI implementation.

Heer, E.↗
NASA NTRS1992

Dynamics of the atmosphere of Mars

The current understanding of the Martian atmospheric circulation and boundary layer is described. The available meteorological data and the first-order constraints that can be derived from them are reviewed. Pertinent aspects of atmospheric radiation on Mars are briefly presented; their main features are the short radiative time constraints on Mars, as compared to earth, and the important role of suspended dust in providing a potent thermal drive for the atmosphere. The current understanding of the Martian atmospheric circulation and its various components - the zonal-mean, zonal, and meridional flows, stationary and traveling planetary waves, atmospheric thermal tides, topographic wind systems, free modes, and gravity waves - is examined. Present-day knowledge of the PBL on Mars is reviewed, with particular attention given to the Viking Orbiter and Lander observations relating to the winds required for raising dust from the surface. The theory of the origin and decay of great dust storms on Mars is reviewed.

Zurek, Richard W.↗
NASA NTRS2006

Innovative Trajectory Designs to meet Exploration Challenges

This document is a viewgraph presentation of the conference paper. Missions incorporated into NASA's Vision for Space Exploration include many different destinations and regions; are challenging to plan; and need new and innovative trajectory design methods to enable them. By combining proven methods with chaos dynamics, exploration goals that require maximum payload mass or minimum duration can be achieved. The implementation of these innovative methods, such as weak stability boundaries, has altered NASA's approach to meet exploration challenges and is described to show how exploration goals may be met in the next decade. With knowledge that various perturbations play a significant role, the mission designer must rely on both traditional design strategies as well as these innovative methods. Over the past decades, improvements have been made that would at first glance seem dramatic. This paper provides a brief narrative on how a fundamental shift has occurred and how chaos dynamics improve the design of exploration missions with complex constraints.

Folta, David C.↗