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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗
NASA NTRS2010

Acoustic-Modal Testing of the Ares I Launch Abort System Attitude Control Motor Valve

The Attitude Control Motor (ACM) is being developed for use in the Launch Abort System (LAS) of NASA's Ares I launch vehicle. The ACM consists of a small solid rocket motor and eight actuated pintle valves that directionally allocate.thrust_- 1t.has-been- predicted-that significant unsteady. pressure.fluctuations.will.exist. inside the-valves during operation. The dominant frequencies of these oscillations correspond to the lowest several acoustic natural frequencies of the individual valves. An acoustic finite element model of the fluid volume inside the valve has been critical to the prediction of these frequencies and their associated mode shapes. This work describes an effort to experimentally validate the acoustic finite model of the valve with an acoustic modal test. The modal test involved instrumenting a flight-like valve with six microphones and then exciting the enclosed air with a loudspeaker. The loudspeaker was configured to deliver broadband noise at relatively high sound pressure levels. The aquired microphone signals were post-processed and compared to results generated from the acoustic finite element model. Initial comparisons between the test data and the model results revealed that additional model refinement was necessary. Specifically, the model was updated to implement a complex impedance boundary condition at the entrance to the valve supply tube. This boundary condition models the frequency-dependent impedance that an acoustic wave will encounter as it reaches the end of the supply tube. Upon invoking this boundary condition, significantly improved agreement between the test data and the model was realized.

Davis, R. Benjamin↗
NASA NTRS2002

Analysis and Design of Crew Sleep Station for ISS

This paper details the analysis and design of the Temporary Sleep Station (TeSS) environmental control system for International Space Station (ISS). The TeSS will provide crewmembers with a private and personal space, to accommodate sleeping, donning and doffing of clothing, personal communication and performance of recreational activities. The need for privacy to accommodate these activities requires adequate ventilation inside the TeSS. This study considers whether temperature, carbon dioxide, and humidity within the TeSS remain within crew comfort and safety levels for various expected operating scenarios. Evaluation of these scenarios required the use and integration of various simulation codes. An approach was adapted for this study, whereby results from a particular code were integrated with other codes when necessary. Computational Fluid Dynamics (CFD) methods were used to evaluate the flow field inside the TeSS, from which local gradients for temperature, velocity, and species concentration such as CO (sub 2) could be determined. A model of the TeSS, containing a human, as well as equipment such as a laptop computer, was developed in FLUENT, a finite-volume code. Other factors, such as detailed analysis of the heat transfer through the structure, radiation, and air circulation from the TeSS to the US Laboratory Aisle, where the TeSS is housed, were considered in the model. A complementary model was developed in G189A, a code which has been used by NASA/JSC for environmental control systems analyses since the Apollo program. Boundary conditions were exchanged between the FLUENT and G189A TeSS models. G189A provides human respiration rates to the FLUENT model, while the FLUENT model provides local convective heat transfer coefficients to G189A model. An additional benefit from using an approach with both a systems simulation and CFD model, is the capability to verify the results of each model by comparison to the results of the other model. The G189A and FLUENT models were used to evaluate various ventilation designs for the TeSS over a range of operating conditions with varying crew metabolic load, equipment operating modes, ventilation flow rates, and with the TeSS doors open and closed. Results from the study were instrumental in the optimization of a design for the TeSS ventilation hardware. A special case was considered where failure of the TeSS ventilation system occurred. In this case, a study was conducted in order to determine the time required for the CO (sub 2) concentration inside the TeSS to increase to ISS limit values under transient conditions. A lumped-capacitance code, SINDA-FLUINT was used in this case to provide accurate predictions of the human reaction to the TeSS cabin conditions including core and skin temperatures and body heat storage. A simple two-dimensional CFD model of a crewmember inside the TeSS was developed in FLUENT in order to determine the volume envelope of the respired air from the human, which maintained a minimum velocity profile. This volume was then used in the SINDA-FLUINT model to facilitate the calculations of CO (sub 2) concentrations, dry bulb temperatures and humidity levels inside the TeSS.

Keener, John F.↗
NASA NTRSDate not supplied

Investigation of Longitudinal Aero-Propulsive Interactions of a Small Quadrotor Unmanned Aircraft System

Aerodynamic propulsive and airframe interactions significantly influence the forces and moments of multirotor vehicles. This paper presents recent results studying the influence of these effects on a small quadrotor vehicle in hover and forward flight. Aerodynamic interaction model development was explored utilizing system identification tools and incorporated into a previously developed NASA quadrotor flight dynamic simulation. The aerodynamic interaction model improved accuracy of the simulation in comparison to free-flight and static wind tunnel results. Comparisons between models of different fidelity were completed to demonstrate the effects of aerodynamic interaction on model accuracy and provide recommendations for modelling requirements.

George Altamirano↗
NASA NTRS1995

Status of LDEF radiation modeling

The current status of model prediction and comparison with LDEF radiation dosimetry measurements is summarized with emphasis on major results obtained in evaluating the uncertainties of present radiation environment model. The consistency of results and conclusions obtained from model comparison with different sets of LDEF radiation data (dose, activation, fluence, LET spectra) is discussed. Examples where LDEF radiation data and modeling results can be utilized to provide improved radiation assessments for planned LEO missions (e.g., Space Station) are given.

Watts, John W.↗
DOE OSTI2020

Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016

The southeast Atlantic is home to well-defined smoke outflow from Africa coinciding vertically with extensive marine boundary-layer cloud decks, both reaching their climatological maxima in spatial extent around September. A framework is put forth for evaluating the performance of a range of global and regional aerosol models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. The sparse airborne observations are first aggregated into 2o grid boxes and into three vertical layers: the cloud-topped marine boundary layer (MBL), the layer from cloud top to 3 km, and the 3-6 km layer. Aerosol extensive properties simulated for the entire study region for all September suggest that the 2016 ORACLES observations are reasonably representative of the regional monthly average, with systematic deviations of 30% or less. All six models typically place the bottom of the smoke layer at lower altitudes than do the airborne lidar observations by 300-1400 m, whereas model aerosol top heights are within 0-500 m of the observations. All but one of the models that report carbonaceous aerosol masses underestimate the ratio of particulate extinction to the masses, a proxy for mass extinction efficiency, in 3-6 km. Notable findings on individual models include that WRF-CAM5 predicts the mass of black carbon and organic aerosols with minor (~10% or less) biases. GEOS-5 overestimates the carbonaceous particle masses in the MBL by a factor of 3-6. Extinction coefficients in the free troposphere (FT) and above-cloud aerosol optical depth (ACAOD) are 10-30% lower in WRF-CAM5, 30-50% lower in GEOS-5, 10-40% higher in GEOS-Chem, 10-20% higher in EAM-E3SM except for the practically unbiased 3-6 km extinction, and 20-70% lower in the Unified Model, than the airborne in situ, lidar and sunphotometer measurements. ALADIN-Climate also underestimates the ACAOD, by 30%. GEOS-5 and GEOS-Chem predict carbon monoxide in the MBL with small (10% or less) negative biases, despite their overestimates of carbonaceous aerosol masses. Overall, this study highlights a new approach to utilizing airborne aerosol measurements for model diagnosis.

Shinozuka, Yohei↗
DOE OSTI2024

Super-X and conventional divertor configurations in MAST-U ohmic L-mode; a comparison facilitated by interpretative modelling

Measurements are presented, alongside corresponding interpretative SOLPS-ITER simulations, of the first MAST-U experiments comparing ohmically heated L-mode fuelling scans in Conventional divertor (CD) and Super-X divertor (SXD) configurations. In experiment, at comparable outer mid-plane separatrix electron density, $n_{e,\textrm{sep,OMP}}$, the maximum lower outer target heat load was found to be a factor 16 $\,\pm\,7$ lower in SXD compared to CD. In simulation, a factor 26.8 reduction was found (slightly higher than the experimental range), suggesting an additional reduction in SXD compared to the factor 9.3 expected from geometric considerations alone. According to the simulations, this additional reduction in the SXD is due to a net radial transport of the energy remaining downstream of the $T_e = 5$ eV location. This energy is carried out of the critical (highest heat load) flux tube by deuterium atoms, demonstrating the importance of a longer legged divertor which provides space for this to occur. Importantly, in both simulation and experiment, the SXD has minimal impact on the upstream n e and T e profiles. Spectral inferences of detachment front movement in SXD compare well between simulation and experiment. In regions of high magnetic field gradient, the parallel movement of the front towards the X-point becomes less sensitive to increasing $n_{e,\textrm{sep,OMP}}$, in qualitative agreement with simplified models and previous predictive simulations. Additional aspects, regarding the target ion flux rollover, upstream separatrix temperature and drift effects, are also presented and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Evolving Electricity Supply and Demand to Achieve Net-Zero Emissions: Insights from the EMF-37 Study

This paper explores the role of electricity in achieving economy-wide net-zero CO2 emissions by 2050 in the United States based on results from 17 models as part of the 37th Stanford Energy Modeling Forum (EMF-37). In the study's Net-Zero scenario, the models use diverse pathways to achieve net-zero emissions by 2050, with gross energy-related residual emissions ranging from 17.2 to 66.6 % of 2020 levels. Electricity consistently emerges as central to achieving net-zero, with models projecting rapid electrification of end-uses and rapidly declining CO2 intensity of electricity. However, the extent of electrification and the technology mix to decarbonize the power sector vary considerably across models. In the Net-Zero scenario, electricity is projected to evolve from ~20 % of final energy in 2020 to 17-63 % in 2050 across the models driven by electrification in all sectors-buildings, industry, and transportation-and, to a lesser extent by direct air capture. By 2050, total electricity consumption increases by 24-176 % (relative to 2020), accompanied by significant expansion in renewable electricity production. Together, solar and wind generation grows by 175-834 %, supplying 45-90 % of total electricity in 2050, with wind achieving slightly higher shares than solar. Electricity storage technologies are deployed at scale to support wind and solar generation. The electricity generation mix varies across models: some project almost complete reliance on renewables, while others see a substantial role for natural gas, often with carbon capture and storage. This paper synthesizes the rich diversity of modeling approaches and results, highlighting differing views on how key drivers of electricity demand and supply might evolve.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Simulating Observations of Southern Ocean Clouds and Implications for Climate

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Analytical study of twin-jet shielding

Development of jet noise source model, and comparison to experiments with a point noise source are summarized. The refinement of the noise source is expected to resolve discrepancies noted between previous analytical results with a point noise source model and experimental results for twin-jet shielding. Comparison of the analytical model with experimental program which include shielding of a point noise source by a jet and twin jet shielding are also made. The comparisons should serve to define more completely the mechanisms of shielding

Gerhold, C. H.↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2025

A comparison of surrogate constitutive models for viscoplastic creep simulation of HT-9 steel

Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models become increasingly more complex – often involving coupled differential equations describing the effect of specific deformation modes – their associated computational costs can become prohibitive, particularly in optimization or uncertainty quantification tasks that require numerous model evaluations. To address this challenge, surrogate constitutive models that balance accuracy and computational efficiency are highly desirable. Data-driven surrogate models, that learn the constitutive relation directly from data, have emerged as a promising solution. In this work, we develop two local surrogate models for the viscoplastic response of a steel: a piecewise response surface method and a mixture of experts model. These surrogates are designed to adapt to complex material behavior, which may vary with material parameters or operating conditions. The surrogate constitutive models are applied to creep simulations of HT-9 steel, an alloy of considerable interest to the nuclear energy sector due to its high tolerance to radiation damage, using training data generated from viscoplastic self-consistent (VPSC) simulations. In conclusion, we define a set of test metrics to numerically assess the accuracy of our surrogate models for predicting viscoplastic material behavior, and show that the mixture of experts model outperforms the piecewise response surface method in terms of accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparison of interlaminar damage modeling strategies for hybrid composite/aluminum laminates subjected to low-velocity impact

Low-velocity impact of hybrid metal-composite structures was investigated experimentally and computationally. Composite laminates consisting of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) were joined with a 6061-T6 aluminum plate using an epoxy adhesive. Two variations of the structure were studied; one consisting of all plies oriented at 0° and one consisting of all plies oriented at 45°. A drop tower was used to impact structures at a range of energies, including energies above and below the threshold at which the aluminum layer was perforated. Numerical simulations were implemented using Sierra/SM, an in-house transient dynamics finite element code developed at Sandia National Laboratories. A Hosford plasticity model was used to describe the response of the aluminum layer. A newly implemented orthotropic continuum damage mechanics (CDM) constitutive model was used to represent the composite laminate. This 3D-CDM model was compared to a cohesive zone model (2D-CDM/CZM) to investigate efficacy of aluminum perforation energy prediction, delamination prediction, and computational cost. Accuracy of each model was evaluated using the experimental results. Each showed good agreement with the tests for both the force and velocity histories, as well as the observed damage mechanisms. The 2D-CDM/CZM model was marginally more accurate in capturing both the composite and aluminum behavior — this model averaged error percentages of -11.2% and 10.8% for residual velocity and peak force, respectively. Meanwhile, the 3D-CDM model predictions yielded average error percentages of -35.5% (velocity) and 22.6% (force). However, the 3D-CDM model generally resulted in a decreased computational cost; the average run time was 14% shorter than the 2D-CDM/CZM model and 3x as many timesteps per hour were computed using the same computational resources. In conclusion, new experimental data on the impact and perforation resistance of metal-composite laminates is presented in addition to numerical predictions of the impact behavior.

Carbon fiber↗
DOE OSTI2025

Demonstrating the impact of ro-vibrationally excited H 2 on divertor detachment via population modelling

EDGE2D-EIRENE profiles characteristic for low recycling, high recycling and detached plasmas are postprocessed applying a vibrationally resolved collisional radiative (CR) model based on the Yacora solver to predict excited state densities and thus the molecular Lyman-, Werner- and Fulcher band emission intensities. These emission intensities are compared to predictions from the AMJUEL database standardly used in EIRENE. Lower Fulcher band and higher Lyman- and Werner band emission is predicted by the Yacora model in comparison to AMJUEL suggesting that inconsistent results from model based evaluation of measured spectra are expected depending on which model and molecular emission band is considered. The implications on detachment rate predictions are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Comparison of PV Resource Modeling for Sizing Microgrid Components

Microgrid systems are being deployed with increased frequency to meet critical building loads during unplanned power outages. Determining the appropriate type and size of components that make up a microgrid can greatly affect its ability to meet this need. This paper presents a new tool to appropriately size PV, battery, and generator capacities to meet all site loads, given a resilience goal. It uses a statistical model to simulate microgrid behavior under a large range of solar resource conditions, providing resilience planners with confidence that critical loads will be met even under extreme weather conditions. We compare this model with one that uses typical weather data for sizing microgrids, and quantify the resilience effects of using these different methods. Our method produces more conservative generator capacities and fuel requirements in an outage, predicting up to 30% more fuel required in the most extreme case. Microgrid systems that are designed using more conservative estimates are more likely to continue to serve load during emergency outages under a large range of conditions.

Newman, Sarah F.↗
DOE OSTI2021

Quantification of Raman-Interfering Polyoxoanions for Process Analysis: Comparison of Different Chemometric Models and a Demonstration on Real Hanford Waste

The Hanford site represents a complicated environmental remediation challenge, remaining from the production of nuclear weapons. Over 100 million gallons of liquid radioactive waste of unknown composition will be chemically processed and vitrified, but the varying chemical composition and highly radioactive nature of the waste preclude the implementation of more developed, offline technologies to determine the composition. The only practical approach to waste treatment will require the significant utilization of real-time, chemometric modeling approaches. Although chemometric approaches have been applied to the analysis of Hanford waste, the models developed were highly tank-specialized, and limited discussion was provided on how models fared with interfering signals. As the tank waste is largely composed of oxoanions, which tend to have interfering Raman spectra, the general question was posed as to what chemometric approach is best suited to accurately quantify analytes in the presence of interfering signals. This was carried out by examining the ability of classical least square (CLS), principal component regression (PCR), partial least square (PLS), and locally weighted regression (LWR) to quantify NO 3 – and CO 3 2– using their bands around 1050 cm –1 . Finally, for all samples, the PLS-based model was found to be the most efficient approach from a model building and application perspective.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Comparison of plasma response models for RMP effects on the divertor and scrape-off layer in KSTAR

Resonant magnetic perturbations (RMPs) are beneficial for control of edge localized modes (ELMs) in tokamaks. Nevertheless, a side effect of RMPs is the appearance of helical striations in the particle and heat loads onto divertor targets. The extent and field line connection of these striations is significantly altered by the plasma response to external perturbations. For an ELM suppressed high confinement (H-mode) plasma at KSTAR, magnetic footprints are computed by FLARE based on plasma response from GPEC, MARS-F, M3D-C1 and JOREK with substantial differences in the resulting footprints (from 2 cm to 14 cm). This is reflected in EMC3-EIRENE simulations of the resulting heat loads: it is found that either the peak value or the extent of the striations appears to be overestimated compared to infrared camera measurements. Reasonable agreement can only be achieved for the smallest footprint for lower input power and lower cross-field transport, or for higher upstream density and radiative power losses.

Frerichs, H. [Univ. of Wisconsin, Madison, WI (Uni↗
DOE OSTI2020

Wind farm blockage effects: comparison of different engineering models

The work presents four engineering methods to estimate the induction zone in front of a wind turbine and account for the wind farm blockage effect. The methods comprise the vortex cylinder model, vortex dipole model, self-similar model, and wake projection model. The majority of the models presented account for yaw misalignments and ground effect. Actuator disk simulations are used to verify the individual models. The performance of each model is evaluated both in terms of precision and computational time. The induction models are coupled to wake models within the FLOw Redirection and Induction in Steady State framework to provide the full velocity field within a wind farm. Sample wind farm computations are presented, and the impact of including induction effects into wind farm performance predictions is reported. The different codes are publicly available online.

17 WIND ENERGY↗