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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.

Morelli, Eugene A.↗
NASA NTRS2024

Improved Soil Moisture Estimation and Detection of Irrigation Signal By Incorporating SMAP Soil Moisture Into the Indian Land Data Assimilation System (ILDAS)

Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).

Soil Moisture↗
NASA NTRS1994

Cloud-radiation interactions and their parameterization in climate models

This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18-20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth's surface, and to refine the process models which are used to develop advanced cloud parameterizations.

Source record↗
DOE OSTI2013

Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Evaluation of cloudiness parameterizations using a cumulus ensemble model

Diagnostic cloudiness parameterizations in large-scale models are evaluated by using a two-dimensional numerical cumulus ensemble model. The model covers a large horizontal domain (512 km) but resolves individual clouds. This study explores the dependence of diagnostic relations (between cloud amount and a large-scale variable) on cloud regime, horizontal averaging distance, and cloud type for tropical convective cloud regimes. Large-scale variables, including relative humidity, cumulus mass flux, large-scale vertical velocity and surface precipitation rate, are examined. It is shown that the total cloud amount can be better estimated as the sum of separate estimates of stratiform and convective cloud amounts using different large-scale variables than by an estimate of the total cloud amount using any single large-scale variable. The stratiform cloud amount can best be estimated by using relative humidity. The convective cloud amount can be diagnosed by using cumulus mass flux. Neither set of diagnostic relations depends significantly on the stimulated cloud regime or horizontal averaging distance, but other diagnostic relations do show some such dependence. These results are interpreted and their implications for cloudiness parameterization are discussed.

Xu, Kuan-Man↗
NASA NTRS2005

Representation of Vegetation and Other Nonerodible Elements in Aeolian Shear Stress Partitioning Models for Predicting Transport Threshold

The presence of nonerodible elements is well understood to be a reducing factor for soil erosion by wind, but the limits of its protection of the surface and erosion threshold prediction are complicated by the varying geometry, spatial organization, and density of the elements. The predictive capabilities of the most recent models for estimating wind driven particle fluxes are reduced because of the poor representation of the effectiveness of vegetation to reduce wind erosion. Two approaches have been taken to account for roughness effects on sediment transport thresholds. Marticorena and Bergametti (1995) in their dust emission model parameterize the effect of roughness on threshold with the assumption that there is a relationship between roughness density and the aerodynamic roughness length of a surface. Raupach et al. (1993) offer a different approach based on physical modeling of wake development behind individual roughness elements and the partition of the surface stress and the total stress over a roughened surface. A comparison between the models shows the partitioning approach to be a good framework to explain the effect of roughness on entrainment of sediment by wind. Both models provided very good agreement for wind tunnel experiments using solid objects on a nonerodible surface. However, the Marticorena and Bergametti (1995) approach displays a scaling dependency when the difference between the roughness length of the surface and the overall roughness length is too great, while the Raupach et al. (1993) model's predictions perform better owing to the incorporation of the roughness geometry and the alterations to the flow they can cause.

King, James↗
NASA NTRS2018

Polarization Decomposition and Temperature Bias Resolution for SMAP Passive Soil Moisture Retrieval Using Time Series Brightness Temperature Observations

In passive microwave remote sensing of soil moisture, the tau-omega (τ-ω) model has often been used to provide soil moisture estimates at a spatial scale representative of the satellite footprint dimensions. For modeling simplicity, model parameters such as the single scattering albedo (ω) and vegetation opacity (τ) that go into the geophysical inversion process are often assumed to be independent of polarizations. Although this absence of polarization dependence can often be justified in special cases as in low-frequency remote sensing or under dense vegetation conditions, it is not a robust assumption in general. Additional model parameterization errors arising from this assumption are possible, leading to degradation in soil moisture estimation accuracy. In this paper, we propose a time series approach to try to resolve the polarization dependence of several τ-ω model parameters as well as the temperature bias arising from the ancillary temperature data. The Version 4 of the Soil Moisture Active Passive (SMAP) Level 1B brightness temperature time series observations were used to illustrate the mechanics of this approach, with an emphasis on a comparison between resulting satellite soil moisture retrievals and in situ data collected at several core validation sites. It was found that this time series approach resulted in significant reduction of the dry bias exhibited in the current SMAP passive soil moisture data products, while retaining the same performance in other metrics of the current baseline passive soil moisture retrieval algorithm.

time series↗
NASA NTRS1989

Physical retrieval of precipitation cell parameters using passive 118-GHz observations

Physical retrieval of precipitation parameters from 118-GHz spectra is investigated using an iterative planar-stratified numerical radiative-transfer model. Liquid and frozen hydrometeors are modeled as spherical Marshall-Palmer and Sekhon-Srivastava (SS) distributed Mie-scattering polydispersions, respectively, with Henyey-Greenstein phase functions. A comparison of 118-GHz rain-cell spectral perturbations observed during Cohmex with model calculations based on coincident radar data yields + or - 10 percent agreement over the convective core region, although a mean ice size 50 percent larger than that given by the SS distribution is required for agreement over the anvil region. A rain-cell model parameterized by top-altitude and total water density suggests that the dominant 118-GHz spectral modes can be used to retrieve top-layer altitude with rms errors of about 1-1.5 km, consistent with statistical retrieval results. Model calculations also suggest that cell density is not observable using 118-GHz spectra alone.

Gasiewski, A. J.↗
DOE OSTI2023

Number of sites-based solver for determining coverages from steady-state mean-field micro-kinetic models

Kinetic models parameterized by ab-initio calculations have led to significant improvements in understanding chemical reactions in heterogeneous catalysis. These studies have been facilitated by implementations which determine steady-state coverages and rates of mean-field micro-kinetic models. As implemented in the open-source kinetic modeling program, CatMAP, the conventional solution strategy is to use a root-finding algorithm to determine the coverage of all intermediates through the steady-state expressions, constraining all coverages to be non-negative and to properly sum to unity. Though intuitive, this root-finding strategy causes issues with convergence to solution due to these imposed constraints. In this work, we avoid explicitly imposing these constraints, solving the mean-field steady-state micro-kinetic model in the space of number of sites instead of solving it in the space of coverages. Here, we transform the constrained root-finding problem to an unconstrained least-squares minimization problem, leading to significantly improved convergence in solving micro-kinetic models and thus enabling the efficient study of more complex catalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Characterization of Exoplanet Atmospheres with the Optical Coronagraph on WFIRST

Wide-Field Infrared Survey Telescope (WFIRST)-CGI is a NASA technology demonstration mission that is charged with demonstrating key technologies for future exo-Earth imaging missions in space. In the process, it will obtain images and low-resolution spectra of a handful to a dozen extrasolar planets and possibly protoplanetary disks. Its unprecedented contrast levels in the optical will provide astronomers’ with their first direct look at mature, Jupiter-sized planets at moderate separations. This paper addresses the question: what science can be done with such data? An analytic noise model, which is informed by the ongoing engineering developments, is used to compute maximum achievable signal-to-noise ratios and scientifically viable integration times for hypothetical star–planet systems, as well as to investigate the constraining power of various combinations of WFIRST-CGI photometric and spectral observations. This work introduces two simple models for planetary geometric albedos, which are inspired largely by the solar system’s gas giants. The first planet model is a hybrid Jupiter–Neptune model, which separately treats the short and long wavelengths where chromophores and methane dominate absorption, respectively. The second planet model fixes cloud and haze properties in CoolTLusty to match Jupiter’s albedo spectrum, it then perturbs only the metallicity. MCMC retrievals performed on simulated observations are used to assess the precision with which planet model parameters can be measured subject to different exposure times and observing cases. Planet radius is recovered within ±15% for all observing cases with both the hybrid model and the CoolTLusty metallicity grid. Fit results for both models’ parameterizations of geometric albedo spectra demonstrate that a rough indication of the metallicity or methane content should be possible for some WFIRST-CGI targets. We conclude that real observations will likely be able to differentiate between extreme cases using these models, but will lack the precision necessary to uncover subtle trends.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization

Purpose: The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms. Methods: The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models. Results: Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve as a jumping point from which to create an unlimited number of 3D and 4D variations for imaging research. Conclusions: A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. The series of anatomically variable phantoms developed in this work provide a valuable resource for investigating 3D and 4D imaging devices and the effects of anatomy and motion in imaging. Combined with Monte Carlo simulation programs, the phantoms also provide a valuable tool to investigate patient-specific dose and image quality, and optimization for adults undergoing imaging procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

A set of 4D pediatric XCAT reference phantoms for multimodality research

Purpose: The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols. Methods: Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection. Results: The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities. Conclusions: The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗
DOE OSTI2020

Assimilating Scanning Radar Data into High-Resolution Models

This report documents the findings of a project aiming to improve the initial conditions of km-scale simulations of deep convective storms by assimilating cloud-scale weather radar observations. More accurate numerical analyses will increase the effectiveness of research efforts using LES cloud models as tool to better understand land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development. Work reported on herein includes: i) assessment of radar data sets for use in data assimilation (‘DA’) experiments, ii) quality control of the radar data set and format conversion to one acceptable to DA schemes utilized by the Weather Research and Forecasting (WRF) model, and iii) examination of the sensitivity of the numerical representation of cloud-scale wind and microphysical features to a variety of tunable DA parameters.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Comparison of cloud microphysical parameters derived from surface and satellite measurements during FIRE phase 2

Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.

Young, David F.↗
DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗
DOE OSTI2026

Radiation-induced segregation in dilute Fe–Cr: A rate-theory framework for the Cr enrichment–depletion transition at the grain boundary

Radiation-induced segregation (RIS) poses a significant challenge for ferritic Fe–Cr alloys under irradiation, as it can compromise mechanical integrity and increase susceptibility to intergranular corrosion. Yet, the mechanisms governing Cr segregation remain incompletely understood. Here, in this study, we present a physics-based rate-theory model parameterized using self-consistent mean field theory-based Onsager transport coefficients to investigate RIS at the grain boundary in dilute Fe-(0.1 at. %) Cr. Under equal production rates of vacancies and self-interstitial atoms (SIA), and their equal absorption rates by bulk dislocations, the model simulates the experimentally observed transition from Cr enrichment at low temperatures to depletion at higher temperatures. Under these unbiased conditions, systematic investigation reveals that while temperature-dependent transport properties dictate the segregation direction, dose rate, grain size, and dislocation density only influence the magnitude and spatial extent of Cr segregation. However, under more realistic conditions of preferential vacancy production within damage cascade and/or preferential SIA absorption by bulk dislocations, the enrichment-to-depletion transition shifts to lower temperatures. Our findings demonstrate that RIS predictions based solely on transport coefficients are valid only under symmetric point defect flux conditions, and that biases in defect production and absorption must be considered for accurate predictions. This work provides a mechanistic framework for understanding RIS in ferritic alloys and informs alloy design for advanced nuclear systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Evidence for Sub-Chandrasekhar Mass Type Ia Supernovae from an Extensive Survey of Radiative Transfer Models

There exists two classes of viable progenitors for normal Type Ia supernovae (SNe Ia): systems in which a white dwarf explodes at the Chandrasekhar mass (${M}_{\mathrm{ch}}$), and systems in which a white dwarf explodes below the Chandrasekhar mass (sub-${M}_{\mathrm{ch}}$). It is not clear which of these channels is dominant; observations and light-curve modeling have provided evidence for both. In this work we use an extensive grid of 4500 time-dependent, multiwavelength radiation transport simulations to show that the sub-${M}_{\mathrm{ch}}$ model can reproduce the entirety of the width–luminosity relation, while the ${M}_{\mathrm{ch}}$ model can only produce the brighter events $(0.8\lt {\rm{\Delta }}{M}_{15}(B)\lt 1.55)$, implying that fast-declining SNe Ia come from sub-${M}_{\mathrm{ch}}$ explosions. We do not assume a particular theoretical paradigm for the progenitor or explosion mechanism, but instead construct parameterized models that vary the mass, kinetic energy, and compositional structure of the ejecta, thereby realizing a broad range of possible outcomes of white dwarf explosions. We provide fitting functions based on our large grid of detailed simulations that map observable properties of SNe Ia, such as peak brightness and light-curve width, to physical parameters such as ${}^{56}\mathrm{Ni}$ and total ejected mass. These can be used to estimate the physical properties of observed SNe Ia.

79 ASTRONOMY AND ASTROPHYSICS↗