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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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The main goal of the project was to develop a lab-scale manufacturing process to fabricate filaments with high carbon content for Fused Deposition Modeling (FDM) three-dimensional (3D) printing use. Graphene particles derived from domestic US coal waste was used as feedstock for filament development.
An extensive computer market survey was made to determine those available systems suitable for current and future flight simulation studies at Ames Research Center. The primary requirement is for the computation of relatively high frequency content (5 Hz) math models representing powered lift flight vehicles. The Rotor Systems Research Aircraft (RSRA) was used as a benchmark vehicle for computation comparison studies. The general nature of helicopter simulations and a description of the benchmark model are presented, and some of the sources of simulation difficulties are examined. A description of various applicable computer architectures is presented, along with detailed discussions of leading candidate systems and comparisons between them.
Many of the textures, morphologies, and mineral chemistries of the high-titanium mare basalts have been experimentally duplicated using single-stage cooling histories. Lunar high-titanium mare basalts are modeled in a 1 m thick gravitationally differentiating flow based on cooling rates, thermal models, and modal olivine contents. The low-pressure equilibrium phase relations of a synthetic high-titanium basalt composition were investigated as a function of oxygen fugacity, and petrographic criteria are developed for the recognition of phenocrysts which were present in the liquid at the time of eruption.
The 'OPSMODEL' operations-analysis and planning tool simulates on-orbit crew operations for the NASA Space Station, furnishing a quantitative measure of the effectiveness of crew activities in various alternative Station configurations while supporting engineering and cost analyses. OPSMODEL is entirely data-driven; the top-down modeling structure of the software allows the user to control both the content and the complexity level of model definition during data base population. Illustrative simulation samples are given.
Variations in abundance and isotopic composition of nitrogen in 79002/79001 drive tube samples result from mixing of two soil components: one mature, N-rich, and isotopically light, resembling breccia material in the core, and the other immature, N-poor, and isotopically heavy. That these materials are common to soil at each stratigraphic level in the core suggests widespread distribution in the local regolith. Preservation of mixing correlations involving nitrogen isotopic compositions and cosmogenic N-15 concentrations suggests relatively recent mixing, perhaps in association with emplacement of the core stratigraphy. Characteristics of nitrogen release from the endmember materials, relationships between their nitrogen contents and maturity, and contrasts in their cosmogenic N-15 contents are consistent with models involving secular increase of the N-15/N-14 ratio of the solar wind.
The coarsening behavior of the gamma-prime precipitate has been examined in high volume fraction nickel-base alloys aged at elevated temperatures for times of up to 5000 h. Although the cube rate law was observed during coarsening, none of the presently available coarsening theories showed complete agreement with the experimental particle size distributions (PSDs). These discrepancies were thought to be due to elastic coherency strains which were not considered by the available models. Increasing the Mo content significantly influenced the PSDs and decreased the coarsening rate of the gamma-prime cubes, as a result of increasing the magnitude of the lattice mismatch. After extended aging times, the gamma-prime cubes underwent massive coalescence into plates at a rate which was much faster than the cuboidal coarsening rate. Once the gamma-prime plates were formed, further coarsening was not observed, and this stabilization of the microstructure was attributed to the development of dislocation networks at the gamma-gamma-prime interfaces.
It is shown that for homogeneous areas soil moisture can be derived from synthetic aperture radar (SAR) measurements, so that the use of microwave remote sensing can given realistic estimates of energy fluxes if coupled to a simple two-layer model repesenting the soil. The model simulates volumetric water content (Wg) using classical meterological data, provided that some of the soil thermal and hydraulic properties are known. Only four parameters are necessary: mean water content, thermal conductivity and diffusitivity, and soil resistance to evaporation. They may be derived if a minimal number of measured values of Wg and surface layer temperature (Tg) are available together with independent measurements of energy flux to compare with the estimated values. The estimated evaporation is shown to be realistic and in good agreement with drying stage theory in which the transfer of water in the soil is in vapor form.
Infrared spectra of H2O, CH3OH, and NH3 condensed at T less than 20 K on amorphous silicate smokes reveal that predominantly crystalline phase ice forms directly on deposit. Spectra of these molecules condensed on aluminum substrates at T less than 20 K indicate that amorphous phase ice forms. On aluminum, crystalline phase H2O and CH3OH are formed by annealing amorphous deposits to 155 K and 130 K, respectively (or by direct deposit at these temperatures); crystalline NH3 is formed by direct deposit at 88 K. Silicate smokes are deposited onto aluminum substrates by evaporation of SiO solid or by combustion of SiH4 with O2 in flowing H2 followed by vapor phase nucleation and growth. Silicate smokes which are oxygen-deficient may contain active surface sites which facilitate the amorphous-to-crystalline phase transition during condensation. Detailed experiments to understand the mechanism are currently in progress. The assumption that amorphous phase ice forms routinely on grains at T less than 80 K is often used in models describing the volatile content of comets or in interpretations of interstellar cloud temperatures. This assumption needs to be reexamined in view of these results.
In this paper, an efficient numerical solution for the scattering problem of inhomogeneous dielectric rough surfaces is presented. The inhomogeneous dielectric random surface represents a bare soil surface and is considered to be comprised of a large number of randomly positioned dielectric humps of different sizes, shapes, and dielectric constants above an impedance surface. Clods with nonuniform moisture content and rocks are modeled by inhomogeneous dielectric humps and the underlying smooth wet soil surface is modeled by an impedance surface. In this technique, an efficient numerical solution for the constituent dielectric humps over an impedance surface is obtained using Green's function derived by the exact image theory in conjunction with the method of moments. The scattered field from a sample of the rough surface is obtained by summing the scattered fields from all the individual humps of the surface coherently ignoring the effect of multiple scattering between the humps. The statistical behavior of the scattering coefficient sigma(sup 0) is obtained from the calculation of scattered fields of many different realizations of the surface. Numerical results are presented for several different roughnesses and dielectric constants of the random surfaces. The numerical technique is verified by comparing the numerical solution with the solution based on the small perturbation method and the physical optics model for homogeneous rough surfaces. This technique can be used to study the behavior of scattering coefficient and phase difference statistics of rough soil surfaces for which no analytical solution exists.
A new parameter, cloud column susceptibility, is introduced to study the aerosol indirect effect. There are several advantages of this new parameter in comparison with the traditional cloud susceptibility. First, no assumptions about constant liquid water content and cloud layer thickness are required in calculations so that errors caused by these assumptions can be avoided. Second, no a priori knowledge of liquid water content is necessary in remote sensing, which makes global survey by satellite data possible even though liquid water content may change significantly. Third, this new parameter can deal with variations of cloud geometrical thickness during cloud-aerosol interactions, which are evidenced by Without assuming how cloud droplet size will respond to changes of number concentration, this new parameter describes the aerosol indirect effect more directly. It addresses the question of how cloud albedo changes with increasing column number concentrations of cloud droplets, which is resulted from cloud-aerosol interactions. In this study, two approaches are used to retrieve cloud column susceptibility by satellite data. The results of both approaches show a striking contrast of cloud column susceptibilities between continental and maritime. Between the two approaches, the one that uses no assumption of constant liquid water content leads to smaller, some times even negative, cloud column susceptibilities. This finding suggests that the aerosol indirect effect may be overestimated if the assumption of constant liquid water content is used in model studies.
Dr. France Cordova, NASA's Chief Scientist, chaired this, the fourth seminar in the NASA Administrator's Seminar Series. She introduced NASA Administrator, Daniel S. Goldin, who greeted the attendees, and in his opening remarks said that human beings have a need to understand the what and why of the forces of nature and of people, and the stresses on the planet Earth. The first speaker, Dr. Ellen Mosley-Thompson of Ohio State University discussed the many things that scientists have learned from ice cores obtained in Peru and the Antarctic. The next speaker, Dr. Michael McElroy of Harvard University, is active in environmental research. He noted that insurance companies need to know more about the physics and chemistry of weather in order to avoid bankruptcy; that the greenhouse effect, which is good because it reflects heat, is being changed, and we don't know the rules. In the discussion that followed, Goldin asked if the present technology for measuring circulation of air and water and contents of the atmosphere is worth the cost. Drs. McElroy and Mosley-Thompson noted that the historic record in an ice core is endangered by ice melts; that in the last 10 years we've learned that tropics change; that the water vapor in the tropics is critical right now; that clouds absorb short-wave radiation; and that there is a need to improve measurements of atmospheric contents, the development of models, and the understanding of basic physics. We also need to understand parameters for detecting climate change, water, water temperature, and be able to provide fundamental information. Additional information is included in the original extended abstract.
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The prediction of separation bubbles on NACA 65-213 and NACA 0012 using a modified Chen-Thyson transition model is presented. The contents include: 1) Background; 2) Analysis of NACA 65-213 separation bubble using cebeci's viscous-inviscid interaction method; 3) Analysis of NACA 0012 separation bubble using navier-stokes method; and 4) Comparison with experiment.
This viewgraph presentation describes the cost tradeoffs for large antenna arrays. The contents include: 1) Cost modeling for large arrays; 2) Antenna mechanical cost over a wide range of sizes; and 3) Cost of per-antenna electronics.
One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.
One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.
No abstract provided
Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.