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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 307 records · Page 17

Convergent Protocols for Computing Protein–Ligand Interaction Energies Using Fragment-Based Quantum Chemistry

Fragment-based quantum chemistry methods offer a way to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation to compute protein–ligand interaction energies in systems with several thousand atoms, using a new software platform for managing fragment-based calculations that implements a screened many-body expansion. Convergence tests using a minimal-basis semiempirical method (HF-3c) indicate that two-body calculations, with single-residue fragments and simple hydrogen caps, are sufficient to reproduce interaction energies obtained using conventional supramolecular electronic structure calculations, to within 1 kcal/mol at about 1% of the computational cost. We also demonstrate that the HF-3c results are illustrative of trends obtained with density functional theory in basis sets up to augmented quadruple-ζ quality. Strategic deployment of fragmentation facilitates the use of converged biomolecular model systems alongside high-quality electronic structure methods and basis sets, bringing ab initio quantum chemistry to systems of hitherto unimaginable size. This will be useful for generation of high-quality training data for machine learning applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composite pressure cell for pulsed magnets

We report that extreme pressures and high magnetic fields can affect materials in profound and fascinating ways. However, large pressures and fields are often mutually incompatible; the rapidly changing fields provided by pulsed magnets induce eddy currents in the metallic components used in conventional pressure cells, causing serious heating, forces, and vibration. Here, we report a diamond-anvil-cell made mainly out of insulating composites that minimizes inductive heating while retaining sufficient strength to apply pressures of up to 8 GPa. Any residual metallic component is made of low-conductivity metals and patterned to reduce eddy currents. The simple design enables rapid sample or pressure changes, desired by pulsed-magnetic-field-facility users. The pressure cell has been used in pulsed magnetic fields of up to 65 T with no noticeable heating at cryogenic temperatures. Several measurement techniques are possible inside the cell at temperatures as low as 500 mK.

47 OTHER INSTRUMENTATION↗

Challenges in Training PINNs: A Loss Landscape Perspective

This paper explores challenges in training Physics Informed Neural Networks (PINNs), emphasizing the role of the loss landscape in the training process. We examine difficulties in minimizing the PINN loss function, particularly due to ill conditioning caused by differential operators in the residual term. We compare gradient-based optimizers Adam, L-BFGS, and their combination Adam+L-FGS, showing the superiority of Adam+L-BFGS, and introduce a novel secondorder optimizer, NysNewton-CG (NNCG), which significantly improves PINN performance. Theoretically, our work elucidates the connection between ill-conditioned differential operators and ill-conditioning in the PINN loss and shows the benefits of combining first- and second-order optimization methods. Our work presents valuable insights and more powerful optimization strategies for training PINNs, which could improve the utility of PINNs for solving difficult partial differential equations.

Rathore, Pratik↗

Systems analysis of a low-acceleration research facility

The Low-Acceleration Research Facility (LARF), an unmanned free-flier that is boosted from low-earth orbit to a desired altitude using an orbital transfer vehicle is discussed. Design techniques used to minimize acceleration-causing disturbances and to create an ultra-quiet workshop are discussed, focusing on residual acceleration induced by the environment, the spacecraft and experiments. The selection and integration of critical subsystems, such as electrical power and thermal control, that enable the LARf to accomodate sub-microgravity levels for extended periods of time are presented, including a discussion of the Low-Acceleration Module, which will supply the payload with 25.0 kW of power, and up to 11.8 kW in the low-power mode. Also, the data management, communications, guidance, navigation and control, and structural features of supporting subsystems are examined.

Martin, Gary L.↗

Aerodynamic characteristics and pressure distributions for an executive-jet baseline airfoil section

A wind tunnel test of an executive-jet baseline airfoil model was conducted in the adaptive-wall test section of the NASA Langley 0.3-Meter Transonic Cryogenic Tunnel. The primary goal of the test was to measure airfoil aerodynamic characteristics over a wide range of flow conditions that encompass two design points. The two design Mach numbers were 0.654 and 0.735 with corresponding Reynolds numbers of 4.5 x 10(exp 6) and 8.9 x 10(exp 6) based on chord, respectively, and normal-force coefficients of 0.98 and 0.51, respectively. The tests were conducted over a Mach number range from 0.250 to 0.780 and a chord Reynolds number range from 3 x 10(exp 6) to 18 x 10(exp 6). The angle of attack was varied from -2 deg to a maximum below 10 deg with one exception in which the maximum was 14 deg for a Mach number of 0.250 at a chord Reynolds number of 4.5 x 10(exp 6). Boundary-layer transition was fixed at 5 percent of chord on both the upper and lower surfaces of the model for most of the test. The adaptive-wall test section had flexible top and bottom walls and rigid sidewalls. Wall interference was minimized by the movement of the adaptive walls, and the airfoil aerodynamic characteristics were corrected for any residual top and bottom wall interference.

Allison, Dennis O.↗

Dimensional Reduction: A Method for Retrieving Lightning Charge

A method is introduced for retrieving the locations and magnitudes of charges deposited by a lightning flash using multiple ground-based electric field change measurements. The method, called Dimensional Reduction, reduces the number of unknowns in a discrete 2-charge model from the standard of eight (x, y, z, Q, x' , y' , z' , Q') to just four (x, y, z, Q). This reduction is accomplished by analyzing "residual measurements" that are formed by subtracting from each ground-based electric field change the contribution due to the source (x, y, z, Q). Using an improved analytic solution to the four-parameter point charge model (or "Q-model") the residual measurements are inverted to find the associated "residual source." For flash charge depositions that look approximately like two arbitrary charges, the residual source will be modeled accurately when (x, y, z, Q) is accurate. Hence, one need only minimize a chi-squared goodness-of-fit that is a function of the four variables (x, y, z, Q), rather than one that is a function of the eight variables (x, y, z, Q, x , y , z , Q ). The accuracy of the method is assessed by inverting computer-simulated electric field changes produced from known charge sources. The method is also applied to analyze real lightning electric field change data derived from the NASA Kennedy Space Center (KSC) and United States Air Force (USAF) Eastern Range (ER) ground-based field mill network It is shown that the charge retrievals compare favorably with associated ancillary ground- and satellite- based lightning measurements.

Koshak, William↗

Virtual Fit Assessment: Validation using Historical Spacesuit Fit Data

Virtual fit tests using 3D body scans have provided a cost-effective means to predictively assess spacesuit fit for the current and future astronaut population. However, fit is a complex issue influenced by physical interferences, subjective preference, and many other factors. Fit can substantially differ between the type of hardware, environmental conditions, and tasks being performed. Namely, fit changes across different contexts, such as 3D printed mockup evaluations, pressurized one-g suited test events, neutral buoyancy and other training events, and flight extravehicular activities (EVA). These challenges make it difficult to validate virtual fit frameworks to physical suit sizing. This study proposes a new method of validation using the wealth of historically archived suit fit data. Physically Assessed Fit (PAF) data was assessed from astronauts and test volunteers who wore the legacy Extravehicular Mobility Unit (EMU). The data was collected during the past decades at NASA and considered to be most reliable and dependable. Each participant was 3D scanned for body shape and spacesuit-critical dimensions were measured per NASA guidelines. The participants’ size preference for hard upper torso (HUT) assembly was retrieved from their pressurized suit fit check records. Fit assessments were also updated after one-g EVA training, neutral buoyancy training, and EVA flights. Virtually Assessed Fit (VAF) was done by overlaying the CAD model of a HUT with the 3D body scans of the PAF participants. Each body scan was iteratively adjusted for the position inside the HUT to minimize the suit-to-body contact interference while satisfying a set of prescribed requirements. Then the residual contact area, depth, and volume were quantified as VAF metrics. This process was repeated for the different HUT sizes, including medium, large, and extra-large. Statistical modeling is currently in progress and will be presented at the conference. A statistical classifier will be developed to predict a fit probability for different HUT sizes as a function of the corresponding person’s VAF metrics. The HUT size with the highest fit probability will constitute the most likely size selection for the person, and the prediction will be compared against the corresponding PAF data. The participant data will be randomly pre-grouped into either a model development or validation subset. While the model development subset will be used to build the probability model, the validation subset will be used to assess the model accuracy. Also, the locations and magnitudes of suit-body-contacts will be estimated from VAF. This information can identify the critical suit geometry and body shape features that influence suit fit. The variations found in PAF size selections by subjects with similar VAF metrics will allow for investigations into subjective preferences, for example, tight versus loose fit. Overall, this study is expected to provide a structured validation of a virtual suit fit framework, which has not been possible in the past. The outcome can also provide useful insights and potential limitations for interpreting virtual fit tests for future spacesuit designs and population accommodation.

Han Kim↗

Organic Products of Fatty Acid and Magnesium Sulfate Mixtures after Gamma Radiolysis: Implications for Missions to Europa

If ocean-derived materials are present at Europa’s surface, they would represent accessible records of ocean chemistry and habitability, but such materials would be further processed by the moon’s harsh radiation environment. In this study, saturated fatty acids were precipitated onto a Europa-relevant hydrated magnesium sulfate and exposed to gamma radiation doses up to 2 MGy at -196° C. Alkane chains, with carbon numbers one less than those of the starting fatty acids, were the most abundant radiolysis products in solvent and thermal extracts analyzed by gas chromatography mass spectrometry. Detections of monounsaturated fatty acids and combined radiolysis products were attributed to the experiment’s Europa-like parameters. Additionally, elevated concentrations of shorter-chain saturated fatty acids suggest that gamma radiation induced charge remote fragmentation of the alkyl chains of some starting fatty acids under these experimental conditions. Quantitation of fatty acid concentrations in the irradiated samples enabled the calculation of a radiolysis constant that indicated exposure to a 5 MGy dose of gamma radiation would have resulted in a ~90% loss of the initial fatty acid population. The samples were further studied by Raman spectroscopy and laser desorption and ionization mass spectrometry, which characterized the distribution of fatty acids and their radiolysis products on sulfate surfaces. The substantial loss of starting fatty acids typically seen with increasing radiation dose, along with the remarkable diversity of radiolysis products identified, suggest that the detection of fatty acids in irradiated sulfate deposits on Europa will be challenged by rapid destruction of any initial fatty acid populations and scrambling of their residual signals by a myriad of organic radiolysis products. If missions to Europa encounter sulfate deposits, targeting minimally irradiated units may still enable the detection of surviving fatty acid signatures that could inform about Europa’s subsurface chemistry and habitability.

James M T Lewis↗

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

B. D. Loomis↗

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

Loomis, B. D.↗

Generative Framework Approach to Match Landsat and Sentinel-2 Data

Linear regression and histogram matching based techniques have been widely used to minimize the surface reflectance difference between two similar satellite observations such as Landsat-8/9 and Sentinel-2A/B products [1]. However, regionally or globally derived conversion factors may not be suitable for all land cover types and locations, resulting in noticeable residual differences between the sensors. Generative Adversarial Network (GAN) has shown promise in the field of image processing for domain or style transfer[2]. In this work we aim to minimize the surface reflectance difference between Landsat and Sentinel-2 products based on GAN.

Sujit Roy↗

Online Adaptive Algorithm for Constraint Energy Minimizing Generalized Multiscale Discontinuous Galerkin Method

Here in this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method. Combining the technique of oversampling, one makes use of the information of the current residuals to adaptively construct basis functions in the online stage to reduce the error of multiscale approximation. A complete analysis of the method is presented, which shows the proposed online enrichment leads to a fast convergence from multiscale approximation to the fine-scale solution. The error reduction can be made sufficiently large by suitably selecting oversampling regions and the number of oversampling layers. Further, the convergence rate of the enrichment algorithm depends on a factor of exponential decay regarding the number of oversampling layers and a user-defined parameter. Numerical results are provided to demonstrate the effectiveness and efficiency of the proposed online adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗

Inhibiting multiple mode vibration in controlled flexible systems

Prior research has led to the development of input command pre-shapers that can significantly reduce residual vibration. These shapers exhibit marked insensitivity to errors in natural frequency estimates and can be used to minimize vibration at more than one frequency. A method is outlined for the development of multiple mode input shapers. An examination is made of the results of shaper performance tests conducted on linear and non-linear computer models of MACE, an MIT/NASA experimental flexible structure.

Hyde, James M.↗

Using input command pre-shaping to suppress multiple mode vibration

Spacecraft, space-borne robotic systems, and manufacturing equipment often utilize lightweight materials and configurations that give rise to vibration problems. Prior research has led to the development of input command pre-shapers that can significantly reduce residual vibration. These shapers exhibit marked insensitivity to errors in natural frequency estimates and can be combined to minimize vibration at more than one frequency. This paper presents a method for the development of multiple mode input shapers which are simpler to implement than previous designs and produce smaller system response delays. The new technique involves the solution of a group of simultaneous non-linear impulse constraint equations. The resulting shapers were tested on a model of MACE, an MIT/NASA experimental flexible structure.

Hyde, James M.↗

Measuring attitude with a gradiometer

This paper explores using a gravity gradiometer to measure the attitude of a satellite, given that the gravity field is accurately known. Since gradiometers actually measure a combination of the gradient and attitude rate and acceleration terms, the answer is far from obvious. The paper demonstrates that it can be done and at microradian accuracy. The technique employed is dynamic estimation, based on the momentum biased Euler equations. The satellite is assumed nominally planet pointed, and subject to control, gravity gradient, and partly radom drag torques. The attitude estimator is unusual. While the standard method of feeding back measurement residuals is used, the feedback gain matrix isn't derived from Kalman theory. instead, it's chosen to minimize a measure of the terminal covariance of the error in the estimate. This depends on the gain matrix and the power spectra of all the process and measurement noises. An integration is required over multiple solutions of Lyapunov equations.

Sonnabend, David↗

Decision time on orbital debris

The problem of orbital debris, especially in LEO is discussed, stressing ways to minimize hazards caused by debris. There are over 7,000 objects making up 2.4 X 10 to the 6th kg of debris in LEO with velocities up to 7 km/sec. The least costly way of minimizing hazards from debris is to make spent rocket stages inert, to preclude failures after their useful life, by insuring that all residual propellants and pressurant gases are vented while the stage is still subject to command. A more costly option is the actively controlled deorbit of spent stages and spacecraft at the end of their useful mission life. The removal of inert stages or spacecraft is too costly to be practical. The least expensive methods of removal are deorbit for altitudes below 25,000 km and placing the object in earth-escape trajectory for objects at higher altitudes. NASA is developing a special radar to measure the existing small-particle debris and its changes over time, and international agreements are expected to set standards of operational practices to minimize debris.

Loftus, Joseph P.↗

Effects of SRPPF ARS Effluent Variations on Magnesium Oxysulfate Solidification

A magnesium oxysulfate (MOS) grout formulation has been identified to solidify the liquid effluent from the Savannah River Plutonium Processing Facility (SRPPF) Aqueous Recovery System (ARS). The formulation uses reactive, light burnt MgO (28 wt%), anhydrous MgSO 4 (10 wt%), and dead burnt MgO (62 wt%), resulting in a grout with good mixability, acceptable density, acceptable setting times, and a leachate pH around 9.4, within the assumed Waste Isolation Pilot Plant (WIPP) brine pH range. A series of tests were then designed to observe how this formula reacted to variations in the liquid effluent. Liquid effluent temperature, the caustic pH level, concentration of NaNO 3 , and the presence of neutralization products, trace metals, and/or sodium sulfate (all potential residuals found in the effluent from upstream processing), were evaluated to see how each impacts the grout mixing time, peak temperature, setting time, presence of bleed water, leachate pH, and density. The standard mix has an average mixing time of 18 minutes, peak temperature of 100.5 °C, and set time of 60 minutes. Increasing the temperature of the liquid effluent increased the reaction rate of the mix and reduced mixing and setting times. Between 30 and 40°C the change was relatively small, raising no more than 6 °C compared to the standard mix maximum temperature. Increasing the pH of the liquid effluent had no significant impact on the mix. The addition of neutralization products and trace metals had an overall impact of decreasing the reactivity of the mix. The addition of more ions in the liquid effluent, such as an increase in the concentration of NaNO 3 and the addition of Na 2 SO 4 , generally decreased the reactivity of the mix. None of the variations to the liquid effluent hindered solidification as indicated by the lack of bleed water found on all the samples. The leachate pH values for all mixes tested did not significantly vary from the expected pH of 9.4 and none of the density values fell below 1.8 g/cm 3 . Overall, changes to the liquid effluent were found to have a minimal impact on the formulation suggesting the grout's ability to properly form despite increased temperatures and the presence of residuals typically found in the liquid effluent from the ARS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗