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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 Astrobee preliminary design documents include subsystem design overview slides and a 3D model of the preliminary design of the Astrobee system including: mechanical, electrical, flight software, network, and ground subsystems.
Abstract Predicting the structure of multi‐protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage predefined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any precomputed physics‐inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end‐to‐end learning from molecular structures containing tens of thousands of atoms: a point‐based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems.
Titanium alloys are processed to develop a wide range of microstructure configurations and therefore material properties. While these properties are typically measured experimentally, a framework for property prediction could greatly enhance alloy design and manufacturing. In this work, a microstructure-sensitive framework is presented for the prediction of strength and ductility as well as estimates of the bounds in variability for these properties. The framework explicitly considers distributions of microstructure via new approaches for instantiation of structure in synthetic samples. The parametric evaluation strategy, including the finite element simulation package FEpX, is used to create and test virtual polycrystalline samples to evaluate the variability bounds of mechanical properties in Ti-6Al-4V. Critical parameters for the property evaluation framework are provided by measurements of single crystal properties and advanced characterization of microstructure and slip system strengths in 2D and 3D. Property distributions for yield strength and ductility are presented, along with the validation and verification steps undertaken. Comparisons between strain localization and slip activity in virtual samples and in experimental grain-scale strain measurements are also discussed.
Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.
A composite HDPE/PCM filament for 3D printing thermal energy storage systems is naturally hydrophobic.
We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.
The Pacific Northwest National Laboratory (PNNL) has recently developed an active 3D microwave/millimeter-wave shoe scanner. This system is designed to detect threats concealed within the soles of common footwear. The system operates over the 10-40 GHz frequency range for excellent penetration of common materials. The system presents several challenges for efficient image reconstruction, including the thick dielectric window, multi-row linear arrays, and focusing close to the antenna elements. In this paper, an efficient back-projection reconstruction algorithm is presented that overcomes these challenges. Experimental imaging results are shown that demonstrate high-resolution imaging performance for this new scanner.
The software is used to control an Associated Particle Imaging (API) imaging system that can measure the 3d carbon distribution in soil. Furthermore, the software is used to analyze the data from the instrument.
The coupled electronic states in two-dimensional (2D) and three-dimensional (3D) double quantum dot (DQD) systems are investigated using a phenomenological model applied to InAs/GaAs heterostructures. The single-band k • p effective potential approach previously proposed by our group is employed to numerically calculate the energy spectrum and spatial localization of a single electron, serving as an indicator of the coupling strength within the binary system. For identical quantum dots (QDs) in a DQD, the electronic states exhibit ideal coherence. We systematically vary the DQD geometry and the strength of the confinement potential (via an applied electric field) to examine the effects of symmetry breaking and the sensitivity of electron localization in both identical and nearly identical DQDs. Our results show that coherence in DQDs is highly sensitive to these subtle variations. This sensitivity can be harnessed to detect changes in the surrounding environment, such as fluctuations in chemical or electrical properties that affect the DQD system.
The determination of optimal trajectories for the aeroassisted flight experiment (AFE) is discussed. The intent of this experiment is to simulate a GEO-to-LEO transfer, where GEO denotes a geosynchronous earth orbit and LEO denotes a low earth orbit. The trajectories of an AFE spacecraft are analyzed in a 3D-space, employing the full system of 6 ordinary differential equations (ODEs) describing the atmospheric pass. The atmospheric entry conditions are given, and the atmospheric exit conditions are adjusted. Two possible transfers are considered: (1) indirect ascent to a 178 NM perigee via a 197 NM apogee; and (2) direct ascent to a 178 NM apogee.
The determination of optimal trajectories for the aero-assisted flight experiment (AFE) is investigated. The intent of this experiment is to simulate a GEO-to-LEO transfer, where GEO denotes a geosynchronous Earth orbit and LEO denotes a low Earth orbit. The trajectories of an AFE spacecraft are analyzed in a 3D-space, employing the full system of 6 ODEs describing the atmospheric pass. The atmospheric entry conditions are given, and the atmospheric exit conditions are adjusted in such a way that the following conditions are satisfied: (1) the atmospheric velocity depletion is such that, after exiting, the AFE spacecraft first ascends to a specified apogee and then descends to a specified perigee; and (2) the exit orbital plane is identical with the entry orbital plane. The final maneuver, not analyzed here, includes the rendezvous with and the capture by the space shuttle.
The use of pulsed laser holography in analyzing the atomization of impinging jets is evaluated using a holographic camera system capable of recording a 3D image of the atomization process in 3 x 10 exp -8 seconds. The holocamera and the experimental configuration and procedure are described in detail. Two nozzles were fabricated to produce 1-mm diameter liquid water jets that impinged at 60 and 90 deg. Holograms were obtained for each nozzle at liquid velocities of 20 and 40 m/s. Analysis of the holograms revealed the evolution of the jets from the plane of emergence through the region of droplet formation. Features of interest included the growth of disturbances prior to the breakup region and the effect of these disturbances on the formation of ligaments and liquid globules. Preliminary analyses show that waves of atomized liquid formed after impingement are closely correlated to waves measured on the jets, leading to the possibility of controlling the atomization process at the nozzle.
We have combined new radial velocities of both components of Capella, obtained at McDonald and Kitt Peak, with those recently published by Batten et al. (1991), and with interferometric observations, to derive a new 3D orbit of the Capella system. Our results agree well with those of Bagnuolo and Hartkopf (1989), and yield masses accurate to +/- 3 percent. The cooler component, which is the fainter star visually but the more luminous one bolometrically, is the more massive. The mass ratio differs from unity by more than four times its uncertainty, and this lends strong support to the hypothesis that the cool component has begun to consume its core helium. If so, it may be possible to reconcile, qualitatively at least, the orbit's circularity and the stars' rotational velocities with theories of synchronization and circularization, such as that of the Tassouls (1992).
Pickup ions in the solar wind are initially are born in ring-beam distributions, i.e. f(v) varies as delta(v(sub perpendicular) - V(sub sw)sin(Theta)) delta(v(sub parallel) - V(sub sw)cos(Theta)), where Theta is the angle between the solar wind velocity and the IMF(Interplanetary Magnetic Field), and V(sub sw) is the solar wind speed. Often the distribution has been presumed to relax to a distribution that is isotropic in Theta and essentially mono-energetic, a shell or a 'bi-spherical distribution.' However solar wind turbulence is capable of heating the ring distribution on the timescale of a few tens of gyroperiods, a timescale not greatly distinct from that required for pitch angle scattering to a shell. To describe this effect, we have performed test-particle studies of the heating/scattering of the ring beam distribution by MHD turbulence, adopting various models for the MHD fluctuations, including slab and fully dynamic 2D and 3D incompressible turbulence. Furthermore, a system composed of a cold ion ring and a background plasma is unstable to several kinetic plasma instabilities. We carried out kinetic simulations of the ring beam distribution, showing that plasma instabilities also rapidly energize and scatter particles. Results will be presented comparing relaxation and heating rates of the ring-beam distribution by the various mechanisms.
Pointwise Inc.'s, Gridgen Software is a system for the generation of 3D (three dimensional) multiple block, structured grids. Gridgen is a visually-oriented, graphics-based interactive code used to decompose a 3D domain into blocks, distribute grid points on curves, initialize and refine grid points on surfaces and initialize volume grid points. Gridgen is available to U.S. citizens and American-owned companies by license.
Assessing the biological risks associated with exposure to the high-energy charged particles encountered in space is essential for the success of long-term space exploration. Although prokaryotic and eukaryotic cell models developed in our laboratory and others have advanced our understanding of many aspects of genotoxicity, in vitro models are needed to assess the risk to humans from space radiation insults. Such models must be representative of the cellular interactions present in tissues and capable of quantifying I genotoxic damage. Toward this overall goal, the objectives of this study were to examine the effect of the localized microenvironment of cells, cultured as either 2-dimensional (2D) monolayers or 3-dimensional (3D) aggregates, on the rate and type of genotoxic damage resulting from exposure to iron charged particles, a significant portion of space radiation. We used rodent transgenic cell lines containing 50-70 copies of a LacI transgene to provide the enhanced sensitivity required to quantify mutational frequency and type in the 1,100-bp LacI target as well as assessment of DNA,damage to the entire 45-kbp construct. Cultured cells were exposed to high-ener~ir on charged particles at Brookhaven National Laboratory s Alternating Gradient Synchrotron facility for a total dose of 0, 0.1, 0.25,0.5, 1.0, or 2.0 Gy and allowed to recover for 0, 1, or 7 days, after which mutational type and frequency were evaluated. The mutational frequency was found to be higher in 3D samples than in 2D samples at all radiation doses. Mutational frequency also was higher at 7 days after irradiation than immediately after exposure. DNA sequencing of the mutant targets revealed that deletional mutations contributed an increasingly high percentage (up to 27%) of all mutations in cells as the dose was increased from 0.5 to 2 Gy. Several mutants also showed large and complex deletions in multiple locations within the Lac1 target. However, no differences in mutational type were found between the 2D and the 3D samples. These 3D tissue-like model systems can reduce the uncertainty involved in extrapolating risk between in vitro cellular and in vivo models.
A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.
Crew exercise is important during long-duration space flight not only for maintaining health and fitness but also for preventing adverse health problems, such as losses in muscle strength and bone density. Monitoring crew exercise via motion capture and kinematic analysis aids understanding of the effects of microgravity on exercise and helps ensure that exercise prescriptions are effective. Intelligent Automation, Inc., has developed ESPRIT to monitor exercise activities, detect body markers, extract image features, and recover three-dimensional (3D) kinematic body poses. The system relies on prior knowledge and modeling of the human body and on advanced statistical inference techniques to achieve robust and accurate motion capture. In Phase I, the company demonstrated motion capture of several exercises, including walking, curling, and dead lifting. Phase II efforts focused on enhancing algorithms and delivering an ESPRIT prototype for testing and demonstration.