SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A domain-aware generative framework that takes 3D coordinates of the molecule and scaffold as an input and generates 3D coordinates of novel therapeutic candidates as an output while preserving the desired scaffolds. We show that our model generates predominantly valid, unique, novel, and experimentally synthesizable molecules that have drug-like properties similar to the molecules in the training set
Advancements in aircraft electric propulsion may enable an expanded operational envelope for electrically powered vehicles compared to their internal combustion engine counterparts. High aspect ratio wings provide additional lift and drag reduction for a proposed multi-propulsor design, however, the challenge is to reduce the weight of wing structures while maintaining adequate structural and aeroelastic margins. Design exploration using a conventional design-and-build philosophy coupled with a finite element method (FEM)-based design of experiments (DOE) strategy are presented to examine high aspect ratio wing structures that have spanwise distributed electric motors. Multiple leading-edge-mounted engine masses presented a challenge to design a wing within acceptable limits for dynamic and aeroelastic stability. Because the first four primary bending eigenmodes of the proposed wing structure are very sensitive to outboard motor placement, safety-of-flight requirements drove the need for multiple spars, rib attachments, and outboard structural reinforcements in the design. Global aeroelasticity became an increasingly important design constraint during the on-going design process, with outboard motor pod flutter ultimately becoming a primary design constraint. Designers successively generated models to examine stress, dynamics, and aeroelasticity concurrently. This research specifically addressed satisfying multi-disciplinary design criteria to generate fluid-structure interaction solution sets, and produced high aspect ratio primary structure designs for the NASA Scalable Convergent Electric Propulsion Technology and Operations Research (SCEPTOR) project in the Aeronautic Research Mission Directorate at NASA. In this paper, a dynamics-driven, quasi-inverse design methodology is presented to address aerodynamic performance goals and structural challenges encountered for the SCEPTOR demonstrator vehicle. These results are compared with a traditional computer aided design based approach.
The past ten years have seen steady progress in surface modeling procedures, and wholesale changes in grid generation technology. Today, it seems fair to state that a satisfactory grid can be developed to model nearly any configuration of interest. The issues at present focus on operational concerns such as cost and quality. Continuing evolution of the engineering process is placing new demands on the technologies of surface modeling and grid generation. In the evolution toward a multidisciplinary analysis-bascd design environment, methods developed for Computational Fluid Dynamics are finding acceptance in many additional applications. These two trends, the normal evolution of the process and a watershed shift toward concurrent and multidisciplinary analysis, will be considered in assessing current capabilities and needed technological improvements.
Given here is a summary of the paper sessions and panel discussions of the NASA Workshop on Future Directions in Surface Modeling and Grid Generation held a NASA Ames Research Center, Moffett Field, California, December 5-7, 1989. The purpose was to assess U.S. capabilities in surface modeling and grid generation and take steps to improve the focus and pace of these disciplines within NASA. The organization of the workshop centered around overviews from NASA centers and expert presentations from U.S. corporations and universities. Small discussion groups were held and summarized by group leaders. Brief overviews and a panel discussion by representatives from the DoD were held, and a NASA-only session concluded the meeting. In the NASA Program Planning Session summary there are five recommended steps for NASA to take to improve the development and application of surface modeling and grid generation.
An agent to analyze electroweak phase transition. LeWRON turns a BSM model description or a reproduction target into a structured run: symbolic setup, effective-potential artifacts, finite-temperature machinery, generated model code, a scientific report, and an interactive exploration session. It keeps both machine-readable artifacts and human-readable notes, so a run can be resumed, audited, revised, and shared.
Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.
We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.
In an earlier paper, we proposed that Jupiter's alternating wind bands are a manifestation of the global interaction between rotation and convection in a shallow layer. The model, however, was obtained from linearization of the 2D equations of motions. At HKUST/Hong Kong, we are now trying to study this problem by rigorous numerical simulation. Using a three-dimensional spectral numerical code, we compute models for the outermost layer of Jupiter's convective envelope. Two cases have been studied. In one the atmospheric pressure varies from 1 to 23 bar, and in the other from 1 to 115 bar. The physical parameters (internal energy flux, rotation rate) are chosen to be close to those expected, but solar heating, chemistry, as well as dynamical influences from deeper layers are ignored. The models generate wind field patterns that contain alternating jet streams with resemblance to the Jovian bands. Instantaneous values of the mean zonal flow at the equator reach 80 m/sec. Yet the mean meridional flows are less than 1% of such value. The meridional temperature profile at the cloud top level also shows a double hump structure of a few degrees (as observed) in the subtropics. Though there is not complete quantitative agreement (caused perhaps by neglected effects like solar radiation), these models demonstrate, in principle, the feasibility of generating a Jovian type wind pattern through the interaction of fast rotation and convection in a thin shell.
Optical diffraction and wavefront sensing and control (WFSC) models validated against the high-fidelity Roman Space Telescope Coronagraph Instrument (CGI) testbed play a key role in mask design selection and the verification of many requirements that cannot be accomplished until the observatory is in orbit. We have been steadily improving our model fidelity for the as-built CGI testbed system, demonstrating recently good agreement between measurements and model predictions while validating the Hybrid Lyot Coronagraph’s (HLC) performance using the in-orbit high order wavefront sensing and control (HOWFSC) operational scenario. We present modeling and testbed validation results that explain the reason many testbed WFSC iterations were needed for HLC in the past. A new, direct application of model-generated deformable mirror (DM) solutions has since been successfully demonstrated on the testbed with significant speed and performance improvement. The benefit of using such a solution opens up new model-based WFSC approaches for CGI. This can greatly reduce flight risk from potentially insufficient ground solution generation due to schedule or cost constraints or from unexpected post-delivery changes.
Previous work has examined the evidence for a gadolinium bias within SCALE. This work extends the previous work to include benchmark models with hafnium experiments from the ICSBEP Handbook. VALID contains only one experiment with hafnium: MIX-COMP-THERM-008. Newly generated models provide an opportunity to assess the potential presence of a hafnium bias.
This project developed a scalable, high-resolution model to simulate medium- and heavy-duty (MHD) electric truck charging demand and assess its impact on grid infrastructure. Using generative modeling, simulation, and cost optimization, the project delivered an end-to-end software pipeline and a library of 96 real-world scenarios for the Dallas–Houston megaregion. We demonstrated a modular architecture for transportation and grid modeling, implemented cost-optimized infrastructure planning methods, and quantified grid capital, operational, and environmental costs across a wide range of truck electrification scenarios. The results have been adopted by major utility stakeholders and contributed to regional planning efforts.
We present new results obtained with our model based on the track structure and chromatin geometry that predicts the DSB spatial and genomic distributions in a cell nucleus with the full genome represented. The model generates stochastic patterns of DSBs in the physical space of the nucleus filled with the realistic configuration of human chromosomes. The model was re-used to find the distribution of DSBs in a physical volume corresponding to a visible phosphorylation focus believed to be associated with a DSB. The data shows whether there must more than one DSB per foci due to finite size of the visible focus, even if a single DSB is radiochemically responsible for the phosphorylation of DNA in its vicinity. The same model can predict patterns of closely located DSBs in a given gene, or in a DNA loop, one of the large-scale chromatin structures. We demonstrated for the example of the HPRT gene, how different sorts of radiation lead to proximity effect in DSB locations, which is important for modeling gene deletions. The spectrum of intron deletions and total gene deletions was simulated for the HPRT gene. The same proximity effect of DSBs in a loop can hinder DSB restitutions, as parts of the loop between DSBs is deleted with a higher likelihood. The distributions of DSBs and deletions of DNA in a loop are presented.
Liquid sloshing within spacecraft propellant tanks causes rapid energy dissipation at resonant modes, which can result in attitude destabilization of the vehicle. Identifying resonant slosh modes currently requires experimental testing and mechanical pendulum analogs to characterize the slosh dynamics. Computational Fluid Dynamics (CFD) techniques have recently been validated as an effective tool for simulating fuel slosh within free-surface propellant tanks. Propellant tanks often incorporate an internal flexible diaphragm to separate ullage and propellant which increases modeling complexity. A coupled fluid-structure CFD model is required to capture the damping effects of a flexible diaphragm on the propellant. ANSYS multidisciplinary engineering software employs a coupled solver for analyzing two-way Fluid Structure Interaction (FSI) cases such as the diaphragm propellant tank system. Slosh models generated by ANSYS software are validated by experimental lateral slosh test results. Accurate data correlation would produce an innovative technique for modeling fuel slosh within diaphragm tanks and provide an accurate and efficient tool for identifying resonant modes and the slosh dynamic response.
Two new models for the design and performance analysis of RTG's are outlined in this paper. The first model assumes a small-signal transient-type calculational sequence that permits the separation of steady-state operation of the generator from its dynamic behavior. The second model uses a numerical (finite difference) solution of the performance equations of the RTG. Both models enable the investigation of transient and steady-state performance of RTG's. Simplifying assumptions have been kept to a minimum in the new RTG models and these models enable the inclusion of generator end losses, axial temperature gradients and heat interchange between thermoelements and thermal insulation in RTG performance calculations in a self-consistent manner.
The goal was to quantify the extent to which a sea surface temperature (SST) front can influence cyclogenesis. The approach was to use the Drexel Limited-Area Mesoscale Prediction System (LAMPS) dynamical model to simulate cyclogenesis over various SST fields. Research during the past year focused on the development and testing of a four dimensional data assimilation (FDDA) technique within LAMPS. The technique is a continuous dynamical assimilation where forcing terms are added to the governing model equations to gradually nudge the model solution toward a gridded analysis. Here, the nudging is used as a dynamic initialization tool during a 12 hour preforecast to generate model balanced initial conditions for a subsequent 24 hour numerical prediction. Tests were performed to determine which variables to nudge and how to specify the four dimensional weighting function used to scale the nudging terms. To date, optimal results were obtained by nudging the u and v components of the wind along with the potential temperature. The weighting function ranged from 0 to 1 and varies in time as a quadratic polynomial. It was initialized at 0, reached its maximum at 9 hours into the preforecast, and fell back at 0 to 12 hours. The nudging terms are included in the model equations for all grid points except those within the model predicted oceanic boundary layer. This design attempts to confine changes imposed by the specified SST field to the oceanic boundary layer during the preforecast period.
The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.
Features of the DEGRA 2 computer code for simulating the operations of a spacecraft thermoelectric generator are described. The code models the physical processes occurring during operation. Input variables include the thermoelectric couple geometry and composition, the thermoelectric materials' properties, interfaces and insulation in the thermopile, the heat source characteristics, mission trajectory, and generator electrical requirements. Time steps can be specified and sublimation of the leg and hot shoe is accounted for, as are shorts between legs. Calculations are performed for conduction, Peltier, Thomson, and Joule heating, the cold junction can be adjusted for solar radition, and the legs of the thermoelectric couple are segmented to enhance the approximation accuracy. A trial run covering 18 couple modules yielded data with 0.3% accuracy with regard to test data. The model has been successful with selenide materials, SiGe, and SiN4, with output of all critical operational variables.
A review of the theory for the electromagnetic functional used to date to determine the lunar conductivity profile from spectral analyses of lunar magnetometer data. The 'hard' boundary condition used by Sonett et al. (1971) and others appears to be a good approximation for the sunlit lunar hemisphere. The use of the spectral data in conjunction with the functional to find a least squares conductivity profile is examined from the point of view of the nonuniqueness of nonlinear estimation. An unsuccessful search was carried out to find models that were both geophysically reasonable and consistent with the data. It is asserted that the failure to find these models is due to the inadequacy of the functional. Of the models generated, those that best fit the data all have a conductivity peak at a depth of 240 km similar to that of the model discussed by Sonett et al. However, all of these models are quite distinct elsewhere in the profile. It is shown how such models are dependent on both the nature of the functional as well as the initial guess in the least squares procedure. A correlation analysis shows that the only resolvable features from this type of model are a low conductivity crust, a high conductivity peak of limited radial extent, and a low conductivity zone beneath the peak.