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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Unsteady Surface Pressure Characterization on Launch Vehicle in Liftoff Configuration

Acquisition of unsteady pressure using remote scanners can provide practical advantages over making the same measurements directly using flush-mounted pressure transducers. However, pneumatic distortion of the signal is introduced by the tubing between the sensing module and surface port. This typically limits the usefulness of such measurements to averaged, steady data only, restricting the application of pressure scanners for unsteady pressure measurements in the wind tunnel and flight-testing applications. In this work, unsteady pressure on the surface of a 1.75%-scale model of the NASA Space Launch System Block 1B Cargo vehicle was remotely measured at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using an ESP pressure scanner. Subsequent reconstruction using an empirically-tuned, Wiener-filtered inverse transfer function produced excellent agreement compared to nearby surface-mounted transducers within a usable bandwidth of approximately 500 Hz. Interactions between the launch vehicle and the support tower produced strong oscillations that were absent in the vehicle-alone configuration, and it is likely that the wake interaction leads to a resonant flow response when the launch tower is immediately downstream of the vehicle.

Unsteady pressure↗
DOE OSTI2025

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models

Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr −1 . We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
DOE OSTI2022

Elucidating the temperature dependence of TRIP in Q&P steels using synchrotron X-Ray diffraction, constituent phase properties, and strain-based kinetics models

Understanding the deformation-induced martensitic transformation (DIMT) is critical for interpreting the structure-property relationships that govern the performance of transformation-induced plasticity (TRIP) assisted steels. However, modern TRIP-assisted steels often exhibit DIMT kinetics that are not easily captured by existing empirical models based on bulk tensile strain. We address this challenge by combined bulk uniaxial tensile tests and in-situ high energy synchrotron X-ray diffraction, which resolved the phase volume fractions, stress-strain response, and microstructure evolution of each constituent phase. A modification of the Olson-Cohen model is implemented, which describes the martensitic transformation kinetics as a function of the estimated partitioned strain in austenite, rather than the bulk tensile strain. This DIMT kinetic model is used as a framework to clarify the root cause of an insufficiently understood toughness trough reported for TRIP-assisted steels during deformation at elevated temperatures. Here, the importance of the temperature-dependent toughness is discussed, based on the opportunity to modify deformation processes to tailor the DIMT kinetics and mechanical properties during forming and in service.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-Temperature Gas Sensor Materials with Properties Predicted via First-Principles Calculations with Machine Learning Modeling and Experimental Corroboration

Understanding the temperature dependence of functional properties of sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we first assess the temperature dependence of band gap renormalization in sensing materials by employing Allen-Heine-Cardona (AHC) theory with density functional theory (DFT) simulations corroborated with experimental observation. As the AHC calculations are impractical for high-throughput screening of materials, we employ data-driven Gaussian process regression to predict the parameters employed in the O’Donnell empirical model from a set of physical features. To mitigate the reliability issues arising from the small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as to quantify the uncertainty associated with theoretical predictions. These models capture well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions and, therefore, the variation of bandgap as a function of temperature for other novel materials. The predicted candidates from machine learning models are further validated by experiments and DFT calculations.

bandgap renormalization↗
NASA NTRS2000

Nonlinear Bulging Factors for Longitudinal and Circumferential Cracks in Cylindrical Shells Subjected to Combined Loads

Results of a geometrically nonlinear finite element parametric study to determine curvature correction factors or bulging factors that account for increased crack-tip stresses due to curvature for longitudinal and circumferential cracks in unstiffened cylindrical shells subjected to combined loads are presented. Nondimensional parameters varied in the study include the shell curvature parameter, l , which is a function of the shell radius, the shell wall thickness, and the crack length; a pressure loading parameter, h , which is a function of the shell geometry, material properties and the applied internal pressure; and a biaxial loading parameter, c , which is the ratio of the farfield axial stress to the farfield circumferential stress. The major results are presented in the form of contour plots of the bulging factor as a function of these three nondimensional parameters. These plots identify the ranges of the shell curvature and loading parameters for which the effects of geometric nonlinearity are significant, and show the effect of the biaxial loads on the value of the bulging factor. Simple empirical expressions for the bulging factor are then derived from the numerical results and are shown to predict accurately the nonlinear response of shells with longitudinal and circumferential cracks.

Young, Richard D.↗
NASA NTRS1976

A method of distortion pattern synthesis for high response data screening

An empirically derived method of estimating maximum levels of instantaneous inlet total pressure distortion from steady state measurements is presented. The estimation procedure uses steady state total pressure and root mean square turbulent pressure data measurements to synthesize instantaneous distortion patterns. The synthesis method is tailored to intensify distortion patterns in a manner consistent with the characteristics of the particular index to be used in evaluating inlet/engine compatability. The maximum expected value of distortion, a statistically determined function of the length of time of inlet operation, is used to constrain the amount of pattern intensification. Comparison with an independent set of data is presented for verification of the synthesis method.

King, R. W.↗
DOE OSTI2023

Graph-based quantum response theory and shadow Born–Oppenheimer molecular dynamics

Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations [A. M. N. Niklasson et al., J. Chem. Phys. 144, 234101 (2016)] is adapted to the most recent shadow potential formulations of extended Lagrangian Born–Oppenheimer molecular dynamics, including fractional molecular-orbital occupation numbers [A. M. N. Niklasson, J. Chem. Phys. 152, 104103 (2020) and A. M. N. Niklasson, Eur. Phys. J. B 94, 164 (2021)], which enables stable simulations of sensitive complex chemical systems with unsteady charge solutions. The proposed formulation includes a preconditioned Krylov subspace approximation for the integration of the extended electronic degrees of freedom, which requires quantum response calculations for electronic states with fractional occupation numbers. For the response calculations, we introduce a graph-based canonical quantum perturbation theory that can be performed with the same natural parallelism and linear scaling complexity as the graph-based electronic structure calculations for the unperturbed ground state. Further, the proposed techniques are particularly well-suited for semi-empirical electronic structure theory, and the methods are demonstrated using self-consistent charge density-functional tight-binding theory both for the acceleration of self-consistent field calculations and for quantum-mechanical molecular dynamics simulations. Graph-based techniques combined with the semi-empirical theory enable stable simulations of large, complex chemical systems, including tens-of-thousands of atoms.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1985

Two years of on-orbit gallium arsenide performance from the LIPS solar cell panel experiment

The LIPS on-orbit performance of the gallium arsenide panel experiment was analyzed from flight operation telemetry data. Algorithms were developed to calculate the daily maximum power and associated solar array parameters by two independent methods. The first technique utilizes a least mean square polynomial fit to the power curve obtained with intensity and temperature corrected currents and voltages; whereas, the second incorporates an empirical expression for fill factor based on an open circuit voltage and the calculated series resistance. Maximum power, fill factor, open circuit voltage, short circuit current and series resistance of the solar cell array are examined as a function of flight time. Trends are analyzed with respect to possible mechanisms which may affect successive periods of output power during 2 years of flight operation. Degradation factors responsible for the on-orbit performance characteristics of gallium arsenide are discussed in relation to the calculated solar cell parameters. Performance trends and the potential degradation mechanisms are correlated with existing laboratory and flight data on both gallium arsenide and silicon solar cells for similar environments.

Francis, R. W.↗
DOE OSTI2026

How does drought affect residential water demand and price elasticity?

Urban water scarcity is an important social and economic concern, particularly as the intensity, duration, and frequency of droughts is increasing in many regions. We consider whether drought induces changes to water demand and the price elasticity of demand for water that may last beyond a drought’s official end date. If drought shocks prompt long-term changes in water demand behavior, and these changes occur at broad geographic scale, they could have important implications for modeling adaptive responses to water scarcity. We assemble a novel dataset on residential water demand and pricing in the western United States to test empirically for effects of drought on water demand and price elasticity. We perform our analysis with aggregate quantity, price, and drought data, accounting for endogenous prices under increasing-block water tariffs and using both average and marginal water fees in estimating water demand functions. Results are consistent with the hypothesis that households may become less price-sensitive after exposure to drought. However, we find no systematic evidence of long-run, drought-related reductions in water demand, itself.

demand hardening↗
NASA NTRS1977

A multilevel approach for minimum weight structural design including local and system buckling constraints

A rational multilevel approach for minimum weight structural design of truss and wing structures including local and system buckling constraints is presented. Overall proportioning of the structure is achieved at the system level subject to strength, displacement and system buckling constraints, while the detailed component designs are carried out separately at the component level satisfying local buckling constraints. Total structural weight is taken to be the objective function at the system level while employing the change in the equivalent system stiffness of the component as the component level objective function. Finite element analysis is used to predict static response while system buckling behavior is handled by incorporating a geometric stiffness matrix capability. Buckling load factors and the corresponding mode shapes are obtained by solving the eigenvalue problem associated with the assembled elastic stiffness and geometric stiffness matrices for the structural system. At the component level various local buckling failure modes are guarded against using semi-empirical formulas. Mathematical programming techniques are employed at both the system and component level.

Schmit, L. A., Jr.↗
NASA NTRS1986

Safety hazards associated with the charging of lithium/sulfur dioxide cells

A continuing research program to assess the responses of spirally wound, lithium/sulfur dioxide cells to charging as functions of charging current, temperature, and cell condition prior to charging is described. Partially discharged cells that are charged at currents greater than one ampere explode with the time to explosion inversely proportional to the charging current. Cells charged at currents of less than one ampere may fail in one of several modes. The data allows an empirical prediction of when certain cells will fail given a constant charging current.

Frank, H.↗
NASA NTRS2010

Focal Plane Geometry Characterization of the Kepler Mission

The Kepler Mission focal plane contains 42 charge-coupled device (CCD) photodetectors. Each CCD is composed of 2.2 million square pixels, 27 micrometers on a side, arranged in a grid of 2,200 columns by 1,044 rows. The science goals of the Kepler Mission require that the position of each CCD be determined with an accuracy of 0.1 pixels, corresponding to 2.7 micrometers or 0.4 seconds of arc, a level which is not achievable through pre-flight metrology. We describe a technique for determining the CCD positioning using images of the Kepler field of view (FOV) obtained in flight. The technique uses the fitted centroid row and column positions of 400 pre-selected stars on each CCD to obtain empirical polynomials which relate sky coordinates (right ascension and declination) to chip coordinates (row and column). The polynomials are in turn evaluated to produce constraints for a nonlinear model fit which directly determines the model parameters describing the location and orientation of each CCD. The focal plane geometry characterization algorithm is itself embedded in an iterative process which determines the focal plane geometry and the Pixel Response Function for each CCD in a self-consistent manner. In addition to the fully automated calculation, a person-in-the-loop implementation was developed to allow an initial determination of the geometry in the event of large misalignments, achieving a much looser capture tolerance for more modest accuracy and reduced automation.

ccd↗
NASA NTRS2013

North Pacific Decadal Variability in the GEOS-5 Atmosphere-Ocean Model

This study examines the mechanisms of the Pacific decadal oscillation (PDO) in the GEOS-5 general circulation model. The model simulates a realistic PDO pattern that is resolved as the first empirical orthogonal function (EOF) of winter sea surface temperature (SST). The simulated PDO is primarily forced by Aleutian low through Ekman transport and surface fluxes, and shows a red spectrum without any preferred periodicity. This differs from the observations, which indicate a greater role of El Nino-Southern Oscillation (ENSO) forcing, and likely reflects the too short time scale of the simulated ENSO. The geostrophic transport in response to the Aleutian low is limited to the Kuroshio-Oyashio Extension, and is unlikely the main controlling factor in this model, although it reinforces the Ekman-induced SST anomalies. The delay between the Aleutian low and the PDO is relatively short (1 year) suggesting that the fast Ekman response (rather than Rossby wave propagation) sets the SST pattern immediately following an Aleutian low fluctuation. The atmospheric feedback (response to the SST) is only about 25 of the forcing and never evolves into an Aleutian low completely, instead projecting onto the North Pacific Oscillation (NPO), a meridional dipole in sea level pressure (SLP). The lack of preferred periodicity and weak atmospheric response bothindicate a coupled oscillation is an unlikely mechanism for the PDO in this model. In agreement with recent studies, the NPO is correlated with the North Pacific Gyre Oscillation (NPGO), which is another leading EOF of the North Pacific SST. A possible connection between the PDO and the NPGO is discussed.

Pacific Decadal Variability↗
NASA NTRS2018

Random Variables with Moment-Matching Staircase Density Functions

This paper proposes a family of random variables for uncertainty modeling. The variables of interest have a bounded support set, and prescribed values for the first four moments. We present the feasibility conditions for the existence of any of such variables, and propose a class of variables that conforms to such constraints. This class is called staircase because the density of its members is a piecewise constant function. Convex optimization is used to calculate their distributions according to several optimality criteria, including maximal entropy and maximal log-likelihood. The flexibility and efficiency of staircases enable modeling phenomena having a possibly skewed and/or multimodal response at a low computational cost. Furthermore, we provide a means to account for the uncertainty in the distribution caused by estimating staircases from data. These ideas are illustrated by generating empirical staircase predictor models. We consider the case in which the predictor matches the sample moments exactly (a setting applicable to large datasets), as well as the case in which the predictor accounts for the sampling error in such moments (a setting applicable to sparse datasets). A predictor model for the dynamics of an aeroelastic airfoil subject to flutter instability is used as an example. The resulting predictor not only describes the system's response accurately, but also enables carrying out a risk analysis for safe flight.

Luis G. Crespo↗
NASA NTRS1988

An empirical investigation of the InP shallow-homojunction solar cell

An experimental study of the performance of epitaxially grown InP shallow-homojunction solar cells as a function of the thickness and carrier concentration in the base and emitter layers is presented. Identification of improvements to cell design leading to higher performance is emphasized. As a result, using a near-optimum set of design parameters, cells with conversion efficiencies of 20.3 percent (global) and 17.6 percent (AM0) have been achieved. For such cells, it is shown that the internal response of the base layer is essentially perfect, whereas the emitter-layer properties can be improved substantially and warrant further investigation. Discrepancies between the results of the present study and those of earlier modeling efforts are discussed.

Wanlass, M. W.↗
NASA NTRS1994

Empirical Modeling of Plant Gas Fluxes in Controlled Environments

As humans extend their reach beyond the earth, bioregenerative life support systems must replace the resupply and physical/chemical systems now used. The Controlled Ecological Life Support System (CELSS) will utilize plants to recycle the carbon dioxide (CO2) and excrement produced by humans and return oxygen (O2), purified water and food. CELSS design requires knowledge of gas flux levels for net photosynthesis (PS(sub n)), dark respiration (R(sub d)) and evapotranspiration (ET). Full season gas flux data regarding these processes for wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) from published sources were used to develop empirical models. Univariate models relating crop age (days after planting) and gas flux were fit by simple regression. Models are either high order (5th to 8th) or more complex polynomials whose curves describe crop development characteristics. The models provide good estimates of gas flux maxima, but are of limited utility. To broaden the applicability, data were transformed to dimensionless or correlation formats and, again, fit by regression. Polynomials, similar to those in the initial effort, were selected as the most appropriate models. These models indicate that, within a cultivar, gas flux patterns appear remarkably similar prior to maximum flux, but exhibit considerable variation beyond this point. This suggests that more broadly applicable models of plant gas flux are feasible, but univariate models defining gas flux as a function of crop age are too simplistic. Multivariate models using CO2 and crop age were fit for PS(sub n), and R(sub d) by multiple regression. In each case, the selected model is a subset of a full third order model with all possible interactions. These models are improvements over the univariate models because they incorporate more than the single factor, crop age, as the primary variable governing gas flux. They are still limited, however, by their reliance on the other environmental conditions under which the original data were collected. Three-dimensional plots representing the response surface of each model are included. Suitability of using empirical models to generate engineering design estimates is discussed. Recommendations for the use of more complex multivariate models to increase versatility are included.

Cornett, Jessie David↗