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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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This paper describes a glove with which users enter input by tapping fingertips with the thumb or by rubbing the thumb over the palmar surfaces of the middle and index fingers. The glove has been informally tested as the controller for two semi-autonomous robots in a a 3D simulation environment. A preliminary evaluation of the glove s performance is presented.
A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.
Using JSC-developed and other industry-standard off-the-shelf 3D modeling, animation, and rendering software packages, the Image Science Analysis Group (ISAG) supports Orion Project imagery planning efforts through dynamic 3D simulation and realistic previsualization of ground-, vehicle-, and air-based camera output.
Time lag analysis shows very long time lags between all channel pairs. Impulsive heating cannot address these long time lags. 3D Simulations of footpoint heating shows a similar pattern of time lags (magnitude and distribution) to observations. Time lags and relative peak intensities may be able to differentiate between TNE and impulsive heating solutions. Adding a high temperature channel (like XRT Be-thin) may improve diagnostics.
A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.
Development and optimization of composite materials designed for thermal protection of NASA’s spacecraft requires the understanding of their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the micro-scale on realistic representations of these composites. The digital micro-structures are generated either synthetically or through X-ray micro-tomography reconstructions. One of the main challenges in the prediction of heatshield material structural response is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the micro-scale. These are driven by the fiber layout within the micro-structure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled through the use of a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme. The MPSA, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA), was discussed in a previous presentation at the 15th USCCN and in reference. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.
In this study, we compare the SDO/HMI line-of-sight observables (magnetic field, velocity, continuum intensity, and line depth) with the related physical properties for several dynamo simulation runs performed using the "StellarBox" 3D Radiative MHD code. The modeling of the Fe I 6173 A Stokes profiles is performed using the SPINOR radiative transfer code in the LTE approximation. The reproduced SDO/HMI line-of-sight pipeline is applied to the modeled spectra, and the observables are synthesized with high (numerical) and SDO/HMI (instrumental) resolutions. Correlations between the observables and the physical properties at various heights in the atmosphere are studied for a set of view angles (0, 30, 45, 60, 70, and 80 degrees away from the solar disk center). It is found that the SDO/HMI magnetic field and velocity measurements are unambiguously correlated with physical parameters at certain heights of the solar atmosphere. These heights increase from about 100 km above the photosphere for the disk center case to 300-600 km above the photosphere for the 80-degree case. The heights are found to be slightly lower in regions where stronger magnetic fields are found. The comparison of the photospheric magnetic flux and integrated continuum intensity derived from the SDO/HMI observables and high-resolution observations and spectra is discussed. The results of our study improve physics-based interpretations of the SDO/HMI observables and provide a better understanding of the physical properties of the solar atmosphere.
The development and optimization of composite materials designed for thermal protection of NASA’s spacecraft require understanding their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the microscale on realistic representations of these composites. The digital microstructures are generated either synthetically or through X-ray micro-computed tomography reconstructions. One of the main challenges in the prediction of the structural response of heatshield materials is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the microscale. These are driven by the fiber layout within the microstructure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled using a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA) that was presented at the 10th Ablation Workshop. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases, and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.
The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.
The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.
Reconnection is studied as an explanation for high-energy flares from the Crab Nebula. The production of synchrotron emission >100 MeV challenges classical models of acceleration. 3D simulation shows that reconnection, converting magnetic energy to kinetic energy, can accelerate beyond γ rad . The power-law index and high-energy cutoff are important for understanding the radiation spectrum dN/dγ = f(γ) ∝ γ -α . α and cutoff were measured vs. L and σ, where L is system (simulation) size and σ is upstream magnetization (σ = B 2 /4πnmc 2 ). α can affect the high-energy cutoff. In conclusion, for collisionless relativistic reconnection in electron-positron plasma, without guide field, n b /n d =0.1: (1) relativistic magnetic reconnection yields power-law particle spectra, (2) the power law index decreases as σ increases, approaching ≈1.2. (3) the power law is cut off at an energy related to acceleration within a single current layer, which is proportional to the current layer length (for small systems, that length is the system length, yielding γ c2 ≈ 0.1 L/ρ 0 ; for large systems, the layer length is limited by secondary tearing instability, yielding γ c1 ≈ 4σ; the transition from small to large is around L/ρ 0 = 40σ.). (4) although the large-system energy cutoff is proportional to the average energy per particle, it is significantly higher than the average energy per particle.
This study demonstrates the potential for flow focusing due to overpressuring in marine sedimentary environments to act as a significant methane transport mechanism from which methane hydrate can precipitate in large quantities in dipping sandstone bodies. Traditionally, gas hydrate accumulations in nature are discussed as resulting from either short-range diffusive methane migration or from long-range advective fluid transport sourced from depth. However, 3D simulations performed in this study demonstrate that a third migration mechanism, short-range advective transport, can provide a significant methane source that is unencumbered by limitations of the other two end-member mechanisms. Short-range advective sourcing is advantageous over diffusion because it can convey greater amounts of methane to sands over shorter timespans, yet it is not necessarily limited by down-dip pore blocking in sands as is typical of updip advection from a deep source. These results are novel because they integrate pore size impacts on spatial solubility gradients, grid block properties that evolve through time, and methane sourcing through microbial methanogenesis into a holistic characterization of environments exposed to multiple methane hydrate sourcing mechanisms. We show that flow focusing toward sand bodies transports large quantities of methane, the magnitude of which are determined by the sand-clay solubility contrast, and generates larger quantities of hydrate in sands than a solely diffusive system; after depositing methane as hydrate, fluid exiting a sand body is depleted in methane and leaves a hydrate free region in its wake above the sand. Additionally, we demonstrate that in overpressured environments, hydrate growth is initially diffusively dominated before transitioning to an advection-dominated regime. The timescale and depth at which this transition takes place depends primarily on the rate of microbial metabolism and the sedimentation rate but only depends loosely on the degree of overpressuring.
The Mu2e experiment at Fermilab is designed to explore charged lepton flavor violation by searching for muon-to-electron conversion. The magnetic field generated by a system of solenoids is crucial for Mu2e and requires accurate characterization to detect any flaws and to produce a detailed field map. Stringent physics goals are driving magnetic field specifications for the Mu2e solenoids. A field mapper is being designed, which will produce detailed magnetic field maps. The uniform field region of the spectrometer volume requires the highest level of precision (1 Gauss per 1 Tesla). During commissioning, multiple magnetic field maps will be generated to verify proper alignment of all magnet coils, and to create the final magnetic field map. In order to design and build a precise field mapping system consisting of Hall and NRM probes, tolerances and precision for such a system need to be evaluated. In this paper we present a design for the Mu2e field mapping hardware, and discuss results from OPERA-3D simulations to specify parameters for Hall and NMR probes. We also present a fitting procedure for the analytical treatment of our expected magnetic measurements.
We measured 2D electric eld in quasi-hemispheric CdZnTeSe detector. The method is based on rotating by the crossed polarizers and finding the conditions at which the transmittance at each separate pixel has maximum. Space charge distribution can be calculated using by the Gauss's law. 3D Pockels by this method? Not directly (sum of effects along optical path), but in combination of 3D simulations possible. Othfier materials: Beside zinc-blende crystals, the method could be possibly generalized also to other Pockels materials
3D simulations have been performed for a variety of SRF cavities which incorporate Higher Order Mode dampers, either in form of coaxial couplers or waveguide dampers. Instead of utilizing the rather standard approach of matching the output port of the dampers with a broadband coaxial or waveguide port, dissipative materials are modelled for RF field absorption. This for instance not only avoids the otherwise required definition of the number of modes considered for damping, which has an impact on the computational time, but also allows tailoring the load material to conform with experimental data of e.g. non-perfect absorbers. The new calculation scheme is presented. Findings are partially compared with those achieved with the standard waveguide port approach by means of external quality factors. CPU speeds are briefly discussed for both approaches.
Structural alloys under irradiation develop radiation-induced segregation (RIS) at point defect sinks, which lead to undesired changes in the alloy's properties. Additively manufactured austenitic stainless steels are expected to yield a distinct response to irradiation damage owing to their unique as-printed dislocation cell structure. In this talk, we present the development of a mesoscale model for dislocation cell structure evolution coupled with RIS using the MOOSE framework. The evolution of network dislocations within spatially distinct cells and cell walls are modeled using climb-mediated edge annihilation and generation processes. Starting with initial microstructures of as-printed non-equilibrium segregations at dislocation cell walls, our 2D and 3D simulations explore the effects of irradiation temperature, dose rate, dislocation sink bias, and specimen thickness on microstructure evolution. The results will be compared against experimental characterizations of in-situ and ex-situ ion-irradiated samples, and the implications of evolving cell structure on irradiation damage response will be discussed.
We are interested in simulating a variety of problems in 3 dimensions (3D) featuring large electric currents. While 2D simulations have been quite informative, cylindrical symmetry may interfere with a problem’s relevant physics. Specifically, all objects in the domain behave as if they are extruded 360°—turning particles into hoops. In dealing with electrical current, this can have serious ramifications on the current pathways. In 3D (r, φ, z) currents can adjust their pathways anywhere along those 360 degrees given the right conditions; however, in 2D (r, z) those pathways can be completely choked off because an insulating hoop, rather than a particle, is present.
Three-dimensional (3D) Monte Carlo simulation was used to study the variation of backscattered electron (BSE) signal across pore-solid boundaries in cement-based materials in order to enhance quantitative analysis of pore structure. The effects of pore size, depth and boundary inclination angle were investigated. It is found that pores down to 1 nm can generate sufficient contrast to be detected. Visibility improves with larger pore size, smaller beam probe size and lower acceleration voltage. However, pixels in shallow pores or near pore boundaries display higher grey values (brightness) than expected due to sampling sub-surface or neighbouring solid material. Thus, cement-based materials may appear less porous or the pores appear smaller than they actually are in BSE images. Simulated BSE images were used to test the accuracy of the Overflow pore segmentation method. Results show the method is generally valid and gives low errors for pores that are 1 μm and greater.