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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 1,639 records · Page 91
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NASA NTRS1989

The intrinsic luminosity and initial period of pulsars

The observed properties of pulsars are modeled on the assumption that they evolve by emitting magnetic dipole radiation and have exponentially decaying magnetic fields. The models are constructed by using Monte Carlo techniques to generate a Galactic sample of pulsars having particular distributions of initial periods, magnetic dipole moments, and positions. By choosing a relationship between the radio luminosity L(r), the period (P), and the P derivative, it is determined which pulsars of the generated sample could be detected by one of the major pulsar surveys. Detailed account is taken of known selection effects in these surveys. Models in which the size of the pulsar emission cone is dependent on the period are considered. The properties of the detectable pulsars are compared with the properties of the observed pulsars, and the initial distributions and luminosity relation of the model are adjusted until a satisfactory agreement is obtained. A crucial point is that the observed relation between L(r) and P, P derivative is affected by selection effects and does not apply to the actual pulsar population. It is found that the best fits are obtained with models in which the pulsars are injected with relatively long periods, about 0.5 sec.

Emmering, Robert T.↗
DOE OSTI2022

Estimating dermal contact soil exposure for amphibians

Abstract Chemical exposure estimation through the dermal route is an underemphasized area of ecological risk assessment for terrestrial animals. Currently, there are efforts to create exposure models to estimate doses from this pathway for use in ecological risk assessment. One significant limitation has been insufficient published data to characterize exposure and to support the selection and parameterization of appropriate models, particularly for amphibians in terrestrial habitats. Recent publications measuring pesticide doses to terrestrial‐phase amphibians have begun to rectify this situation. We collated and summarized available measurements of terrestrial amphibian dermal exposure to pesticides from 11 studies in which researchers measured tissue concentrations associated with known pesticide experimental application rates. This data set included tissue concentrations in 11 amphibian species and 14 different pesticides. We then compared the results of two screening exposure models that differed based on surface area scaling approaches as a function of body weight (one based on birds as surrogates for amphibians and another amphibian‐specific) to the measured tissue residue concentrations. We define a false‐negative rate for each screening model as the proportion of amphibians for which the predicted concentration is less than the observed concentration (i.e., underestimate), contrary to the intent of screening models, which are intended to have a bias for higher exposure concentrations. The screening model that uses birds as surrogates did not have any instances where estimated expected avian doses were less than measured amphibian body burdens. When using the amphibian‐specific exposure model that corrected for differences between avian and amphibian surface area, measured concentrations were greater than model estimates for 11.3% of the 1158 comparisons. The database of measured pesticide concentrations in terrestrial amphibians is provided for use in calculating bioconcentration factors and for future amphibian dermal exposure model development. Integr Environ Assess Manag 2023;19:9–16. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Environmental Sciences & Ecology↗
DOE OSTI2025

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as imaging systematics. In this paper, we present the imaging systematics mitigation applied to the DESI Data Release 1 (DR1) large-scale structure catalogs used in the DESI 2024 cosmological analyses. We also explore extensions of the fiducial treatment. This includes a combined approach, through forward image simulations (Obiwan) in conjunction with neural network-based regression, to obtain an angular selection function that mitigates the imaging systematics observed in the DESI DR1 ELGs target density. We further derive a line of sight selection function from the forward model that removes the strong redshift dependence between imaging systematics and low redshift ELGs. Combining both angular and redshift-dependent systematics, we construct a three-dimensional selection function and assess the impact of all selection functions on clustering statistics. We quantify differences between these extended treatments and the fiducial treatment in terms of the measured 2-point statistics. We find that the results are generally consistent with the fiducial treatment and conclude that the differences are far less than the imaging systematics uncertainty included in DESI 2024 full-shape measurements. We extend our investigation to the ELGs at 0.6 < z < 0.8, i.e., beyond the redshift range (0.8 < z < 1.6) adopted for the DESI clustering catalog, and demonstrate that determining the full three-dimensional selection function is necessary in this redshift range. Our tests showed that all changes are consistent with statistical noise for BAO analyses indicating they are robust to even severe imaging systematics. Specific tests for the full-shape analysis will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Bayesian Neural Network Ensemble Approach for Improving Large-Scale Streamflow Predictability

Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g.,AI driven model/component/parameterization selection). We propose a Bayesian neural network ensemble approach for improving large-scale streamflow predictability and understanding in a changing environment that combines multiple Earth system land model predictions by calculating spatiotemporally varying model weights and biases while accounting for various types of observations at multiple scales with uncertainty.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗
NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗
NASA NTRS1986

Solvability conditions for dendritic growth in the boundary-layer model with capillary anisotropy

This paper is concerned primarily with the development of an analytic approach to the theory of steady-state velocity selection in the boundary-layer model of dendritic solidification. The two-dimensional version of this model with a fourfold crystalline anisotropy alpha in the surface tension is considered. By extending a WKB method introduced in an earlier paper, the alpha dependence of the selected growth rate is determined in the limit of small alpha; and this rate is studied for large alphas in the limit in which the dimensionless undercooling approaches unity. Portions of the paper are devoted to a reinterpretation of the mathematical structure of the solvability condition in problems of this kind.

Langer, J. S.↗
DOE OSTI2024

Development of a Chemistry-Based Isotherm Model and Techno-Economic Optimization of a Moving Bed Process for CO2 Capture Using a Functionalized Metal-Organic Framework

Amine-appended metal-organic frameworks of the class Mg2(dobpdc) are promising candidates for efficient carbon capture in part due to their step-shaped CO2 adsorption behavior. However, the existing isotherm models are lacking as they are unable to capture the complicated chemisorption mechanisms which are still not well known for these materials. Here, a chemistry-based isotherm model is developed and fit to experimental CO2 adsorption data for dmpn-Mg2(dobpdc). Reactions for a cooperative adsorption mechanism are proposed, and the reaction pathway is optimally selected. The chemistry-based model shows an improvement in prediction by a factor of 6 when compared to a recent isotherm model in literature. A plant-wide model is developed for a moving bed based adsorber/desorber and techno-economic optimization is performed. For likely values of price and lifespan, the moving bed process gives a significant improvement in economics when compared to a fixed bed contactor process and a traditional MEA capture system.

carbon capture↗
DOE OSTI2026

System-of-systems optimization of hydrogen infrastructure for heavy-duty freight corridors: The interstate 10 case study

Medium and heavy-duty freight transportation requires hydrogen energy infrastructure that is cost-effective, operationally reliable, spatially coherent, and resilient to demand variability along major corridors. This paper presents an integrated hydrogen corridor planning framework using Oak Ridge National Laboratory's OR-AGENT that couples freight-driven, route-resolved hydrogen demand modeling with optimized station siting, sizing, and station-level techno-economic analysis. The framework is demonstrated for the Interstate 10 freight corridor and the Houston-to-Los-Angeles region. Hydrogen demand is derived from high-resolution origin–destination freight data, duty-cycle characterization, and physics-based energy consumption modeling. Candidate refueling sites are selected from existing heavy-duty diesel fueling locations and optimized subject to onboard storage and station capacity constraints. Resulting station throughputs are evaluated using established techno-economic models for electrolytic hydrogen production and dispensing infrastructure. Results show that a regional, portfolio-level aggregation, average dispensed electrolytic hydrogen cost of $6.87–$7.26/kg is currently feasible, and is strongly influenced by demand density and utilization.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗
DOE OSTI2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

Abstract. Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. Estimates of future land use and land cover differ significantly across economic models as a result of differences in drivers, model structure, and model parameters; however, these models often rely on heuristics to determine model parameters. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. Specifically, we generate a large set of model parameter perturbations for the selected parameters and run gcamland simulations with these parameter sets over the historical period in the United States to quantify land use and land cover, determine how well the model reproduces observations, and identify parameter combinations that best replicate observations, assuming other model parameters are fixed. We also test alternate methods for forming expectations about uncertain crop yields and prices, including adaptive, perfect, linear, and hybrid approaches. In particular, we estimate parameters for six parameters used in the formation of expectations and three of seven logit exponents for the USA only. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops, landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We examine the change in model parameters as the metric of model error changes, finding that the measure of model fitness affects the choice of parameter sets. Finally, we discuss how the methodology and results used in this study could be used for other regions or economic models to improve projections of future land use and land cover change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.

Dreher, Joseph G.↗
NASA NTRS2018

Marginal protein stability drives subcellular proteome isoelectric point

There exists a positive correlation between the pH of subcellular compartments and the median isoelectric point (pI) for the associated proteomes. Proteins in the human lysosome—a highly acidic compartment in the cell—have a median pI of ∼6.5, whereas proteins in the more basic mitochondria have a median pI of ∼8.0. Proposed mechanisms reflect potential adaptations to pH. For example, enzyme active site general acid/base residue pKs are likely evolved to match environmental pH. However, such effects would be limited to a few residues on specific proteins, and might not affect the proteome at large. A protein model that considers residue burial upon folding recapitulates the correlation between proteome pI and environmental pH. This correlation can be fully described by a neutral evolution process; no functional selection is included in the model. Proteins in acidic environments incur a lower energetic penalty for burying acidic residues than basic residues, resulting in a net accumulation of acidic residues in the protein core. The inverse is true under alkaline conditions. The pI distributions of subcellular proteomes are likely not a direct result of functional adaptations to pH, but a molecular spandrel stemming from marginal stability.

Kaiser Loell↗
NASA NTRS1984

Shuttle derived atmospheric density model. Part 2: STS atmospheric implications for AOTV trajectory analysis, a proposed GRAM perturbation density model

A perturbation model to the Marshall Space Flight Center (MSFC) Global Reference Atmosphere Model (GRAM) was developed for use in the Aeroassist Orbital Transfer Vehicle (AOTV) trajectory and analysis. The model reflects NASA Space Shuttle experience over the first twelve entry flights. The GRAM was selected over the Air Force 1978 Reference Model because of its more general formulation and wider use throughout NASA. The add-on model, a simple scaling with altitude to reflect density structure encountered by the Shuttle Orbiter was selected principally to simplify implementation. Perturbations, by season, can be utilized to minimize the number of required simulations, however, exact Shuttle flight history can be exercised using the same model if desired. Such a perturbation model, though not meteorologically motivated, enables inclusion of High Resolution Accelerometer Package (HiRAP) results in the thermosphere. Provision is made to incorporate differing perturbations during the AOTV entry and exit phases of the aero-asist maneuver to account for trajectory displacement (geographic) along the ground track.

Findlay, J. T.↗
NASA NTRS1974

Some after-dinner reflections on system identification

The growth of the field of system identification is discussed along with changes in methodology which have taken place in recent years. The similarity between pattern recognition and system identification is pointed out, involving the modelling in the latter and the feature selection problem in the former. It is stated that once a model is formulated, including the disturbances and measurement errors, the parameter finding can be formulated as a statistical estimation problem. The various techniques and their application are discussed.

Balakrishnan, A. V.↗
NASA NTRS1987

Non-linear identification of a squeeze-film damper

Described is an experimental study to identify the damping laws associated with a squeeze-film vibration damper. This is achieved by using a non-linear filtering algorithm to process displacement responses of the damper ring to synchronous excitation and thus to estimate the parameters in an nth-power velocity model. The experimental facility is described in detail and a representative selection of results is included. The identified models are validated through the prediction of damper-ring orbits and comparison with observed responses.

Stanway, Roger↗
NASA NTRS1987

Earth observing system instrument pointing control modeling for polar orbiting platforms

An approach to instrument pointing control performance assessment for large multi-instrument platforms is described. First, instrument pointing requirements and reference platform control systems for the Eos Polar Platforms are reviewed. Performance modeling tools including NASTRAN models of two large platforms, a modal selection procedure utilizing a balanced realization method, and reduced order platform models with core and instrument pointing control loops added are then described. Time history simulations of instrument pointing and stability performance in response to commanded slewing of adjacent instruments demonstrates the limits of tolerable slew activity. Simplified models of rigid body responses are also developed for comparison. Instrument pointing control methods required in addition to the core platform control system to meet instrument pointing requirements are considered.

Briggs, H. C.↗
DOE OSTI2025

Optimization Through Multi-Fidelity Modeling

We present a novel method for optimizing parameter selection for simulations with an evaluation budget. We start with an existing method for building a multi-fidelity model out of many low-fidelity simulations and few high-fidelity simulations. We propose a novel method to simplify parameter selection without sacrificing performance. We verify these results and compare with existing literature. Next, we propose a novel algorithm which uses this difference model to suggest new points in the parameter design space to simulate. We add each point we simulate to the model to improve its quality for the next iteration. The algorithm trades off reducing the uncertainty of the existing model with optimization of the objective. The first is more useful when a large fraction of the computation budget remains. The second is more useful when a small fraction of the computation budget remains. Our method converges to the optimum by using a high-fidelity evaluation for just 16 of the 427 points. Our method is general enough to work if there is no low-fidelity model. Furthermore, it is agnostic to the underlying physics of the problem. Therefore, both the low-fidelity and high-fidelity models can be generated by any arbitrary function, including simulations and physical experiments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Projection and assembly method for multibody component model reduction

The problem addressed is that of obtaining reduced-order component models for use in simulating the dynamics of a multibody system. In certain cases, nonlinear system models may be constructed using linear dynamic models for each component, but allowing large angle motion between components. Without some form of model reduction, system models constructed in this manner may be too large for use in control system design and simulation trades. This paper analyzes one method of component model reduction that allows systems level requirements (e.g., capturing the effect of body 1 reaction wheel noise on body 2 camera pointing) to aid in the selection of the reduced-order component models. Briefly stated, important modes are selected at the system level and projected onto the components, and reduced-order components are then assembled into a reduced-order system model that retains the projected modes.

Bernard, Douglas E.↗