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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Finite-Strain Fractional-Order Viscoelastic (FOV) Material Models and Numerical Methods for Solving Them

Fraction-order viscoelastic (FOV) material models have been proposed and studied in 1D since the 1930's, and were extended into three dimensions in the 1970's under the assumption of infinitesimal straining. It was not until 1997 that Drozdov introduced the first finite-strain FOV constitutive equations. In our presentation, we shall continue in this tradition by extending the standard, FOV, fluid and solid, material models introduced in 1971 by Caputo and Mainardi into 3D constitutive formula applicable for finite-strain analyses. To achieve this, we generalize both the convected and co-rotational derivatives of tensor fields to fractional order. This is accomplished by defining them first as body tensor fields and then mapping them into space as objective Cartesian tensor fields. Constitutive equations are constructed using both variants for fractional rate, and their responses are contrasted in simple shear. After five years of research and development, we now possess a basic suite of numerical tools necessary to study finite-strain FOV constitutive equations and their iterative refinement into a mature collection of material models. Numerical methods still need to be developed for efficiently solving fraction al-order integrals, derivatives, and differential equations in a finite element setting where such constitutive formulae would need to be solved at each Gauss point in each element of a finite model, which can number into the millions in today's analysis.

Freed, Alan D.↗
NASA NTRS1987

Reynolds stress closure in jet flows using wave models

Numerical methods were developed that will form the computational part of the turbulence closure scheme. A wave model was developed for the two-dimensional shear layer. This configuration is being used as a test case for the closure schemes. Various numerical schemes were examined to give efficient solutions of the Rayleigh equation for this geometry. These include both spectral and finite difference methods. Secondly, numerical methods are under development to solve the non-separable Rayleigh equation. This solution is required for the closure scheme in more complex geometries. A model problem was used to assist in the algorithm development. Two-dimensional spectral methods and a hybrid spectral/finite difference technique were developed. An analytic solution of the Rayleigh equation for a basic elliptic flow was obtained. This will be used to verify the stability codes developed for arbitrary geometries. Other numerical methods for solving the Rayleigh equation based on the boundary element technique were also examined. These solutions are forming the basis of a model for the shock structure in jets of arbitrary geometry.

Morris, P. J.↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗
NASA NTRS1994

Impact of land-surface moisture variability on local shallow convective cumulus and precipitation in large-scale models

Numerical experiments using state-of-the-art high-resolution mesoscale cloud model showed that land-surface moisture significantly affects the timing of onset of clouds and the intensity and distribution of precipitation. In general, landscape discontinuity enhances shallow convective precipitation. Two mechanisms that are strongly modulated by land-surface moisture-namely, random turbulent thermal cells and organized sea-breeze-like mesoscale circulations-also determine the horizontal distribution of maximum precipitation. However, interactions between shallow cumulus and land-surface moisture are highly nonlinear and complicated by different factors, such as atmospheric thermodynamic structure and large-scale background wind. This analysis also showed that land-surface moisture discontinuities seem to play a more important role in a relatively dry atmsophere, and that the strongest precipitation is produced by a wavelength of land-surface forcing equivalent to the local Rossby radius of deformation. A general trend between the maximum precipitation and the normalized maximum latent heat flux was identified. In general, large values of mesoscale latent heat flux imply strongly developed mesoscale circulations and intense cloud activity, accompanied by large surface latent heat fluxes that transport more water vapor into the atmosphere.

Chen, Fei↗
DOE OSTI2021

Lattice Boltzmann simulation of the dissolution of slag in alkaline solution using real-shape particles

Highlights: • A dissolution numerical model was proposed to capture the real dissolution kinetics of slag in alkaline solution. • The log forward dissolution rate of Si was described as a function of NBO/T and solution pH. • A threshold solid volume fraction of 0.688 was found for a voxel in 3D, 63.8% larger than that for a pixel in 2D. • The proposed dissolution numerical model provides a reliable alternative to study the dissolution kinetics of slag. A dissolution numerical model was proposed in this study to capture the real dissolution kinetics of slag in alkaline solution. It consists of three modules, i.e. (i) simulation of the initial particle parking structure of slag in alkaline solution using real-shape particles of slag, (ii) simulation of the chemical reactions between slag and solution based on the transition state theory, and (iii) simulation of the physical transport of aqueous ions using the lattice Boltzmann method. This dissolution numerical model was verified using experimental results, showing reasonable accuracy. After verification, the dissolution numerical model was implemented to study the influences of temperature and particle shape using a proper recipe of slag in alkaline solution. This recipe was designed to avoid solid phase precipitation or gel formation via thermodynamic analysis. The simulation results showed faster dissolution kinetics of slag when using higher temperatures and more irregular particle shapes.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Numerical turbulence modeling

The underlying bases and developments in two techniques of detailed turbulence modeling are described where the flow is treated in the Eulerian sense, and one technique where the Lagrangian motions of vortices are followed. First, a technique is described for solving the single-point statistically averaged conservation equations. The Reynolds stresses that appear in these equations are evaluated by solving supplemental differential equations which contain terms that are modeled. A sequence of increasingly complex, but also increasingly general, modeling equations is described and computations based on these equations are compared with experimental data. The hierarchy of models described terminates with equations for the individual components of the Reynolds stress tensor. The second Eulerian technique approach to turbulence modeling is the direct numerical simulation of turbulent fields. In this approach, all three dimensional eddies between a predetermined range of sizes are computed in time within a specified volume of flow. Present day computers require a tradeoff between the size of the volume that can be considered and the degree of resolution of the turbulent eddies. Techniques of modeling the smallest eddies are described that permit enlarging the volume, or Reynolds number, that can be considered.

Rubesin, M. W.↗
DOE OSTI2025

Techno-economic feasibility of borehole thermal energy storage system connected to geothermal heat pumps for seasonal heating load of two buildings in Fairbanks, Alaska

Borehole thermal energy storage (BTES) is an effective solution for managing imbalanced heating and cooling loads in cold regions. This study evaluated the long-term feasibility of a BTES system in the Fairbanks area, Alaska, through building energy modeling, resource characterization, and numerical modeling. The system was designed to store waste heat from a nearby coal power plant during summer and provide thermal energy during winter to geothermal heat pumps supplying heating loads in two buildings. Heating load profiles were modeled for the buildings using EnergyPlus, and the results indicated the annual heating load was 5.6 times greater than the cooling load. 40 borehole heat exchangers were pre-designed approximately 100 m away from the two buildings in terms of land availability and regulatorily optimized depth. The 20-year performance of the designed BTES system under two operational scenarios—one with a 5-year preheating period and one without—was numerically modeled using subsurface temperature and properties characterized through the literature review and thermal response tests. Both scenarios demonstrated that the BTES has the capacity to fully cover the heating loads in the two buildings throughout the 20-year lifetime. Production temperatures at central wells were 33 % higher on average than at outer wells in both scenarios. The 5-year preheating period increased subsurface and extraction temperatures, and correspondingly annual average and total thermal energy production was higher for 8 years than in the scenario without the preheating period. These results highlight the long-term reliability and sustainability of the BTES system in meeting heating demands over its lifetime, with the preheating period offering potential performance improvements. Implementing the BTES system in cold regions with high heating demand, such as Fairbanks, Alaska, could provide a long-term, sustainable energy solution for managing imbalanced heating and cooling loads.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI↗
DOE OSTI2020

Using numerical methods to screen magnetocaloric materials in an active magnetic regenerative cycle

A 2-dimensional numerical model of a room temperature operating Active Magnetic Regenerator (AMR) that comprises of a regenerator, hot and cold heat exchangers, heat transfer fluid is developed. The regenerator is made of a magnetocaloric material (MCM) which heats up upon applying a magnetic field, H, and cools down when the field is removed; thus, making it the most essential part of an AMR. The model takes experimentally measured ΔT ad (H,T) and the C p (H,T) data as input and provides quantitative performance metrics of the magnetic cooling system, such as ΔT span and the cooling load, as output. With this model, it is possible to assess a wide range of MCMs in an AMR. 4 different MCMs were investigated using this model in terms of their ΔT span and the cooling loads—LaFe 10.96 Co 0.97 Si 1.07 , MnFeP (1-x) As (x) and AlFe 2 B 2 and Gd. During the screening of MCMs, all the important operating conditions of the device were fixed such as the fluid flow rate, ambient temperature, cycle duration, magnetic field strength. Our results indicate that Gd exhibits the maximum ΔT span with respectable cooling load, while AlFe 2 B 2 generates the lowest ΔT span . Even though LaFeCoSi compound did not perform as well as Gd, it could be the MCM choice for the realization of magnetic refrigeration on a global scale due to its much lower cost.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A two-fluid solar-wind model with intermittent Alfvénic turbulence

In one of the leading theories for the origin of the solar wind, photospheric motions launch Alfvén waves (AWs) that propagate along open magnetic-field lines through the solar atmosphere and into the solar wind. The radial variation in the Alfvén speed causes some of the AWs to reflect, and counter-propagating AWs subsequently interact to produce Alfveńic turbulence, in which AW energy cascades from long wavelengths to short wavelengths and dissipates, heating the plasma. In this paper we develop a one-dimensional two-fluid solar-wind model that includes Alfvénic turbulence, proton temperature anisotropy and a novel method for apportioning the turbulent heating rate between parallel proton heating, perpendicular proton heating and electron heating. We employ a turbulence model that accounts for recent observations from NASA’s Parker Solar Probe, which find that AW fluctuations in the near-Sun solar wind are intermittent and less anisotropic than in previous models of anisotropic magnetohydrodynamic turbulence. Our solar-wind model reproduces a wide range of remote observations of the corona and in-situ measurements of the solar wind, and our turbulent heating model consists of analytic equations that could be usefully incorporated into other solar-wind models and numerical models of more distant astrophysical plasmas.

astrophysical plasmas↗
DOE OSTI2021

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Assessing the Impact of a Forest Canopy on Near-Surface Wind Statistics

Representing the forest canopy in atmospheric numerical models should improve simulated winds within and above the canopy up to a few hundred meters above the ground. Here, in this study, we implement a forest canopy parameterization into the Weather Research and Forecasting (WRF) Model in a large-eddy simulation (LES) mode by applying drag forces across multiple layers within the canopy height. We use unique observations from the Lidar Experiments for Assessing Flow over Forests (LEAFF) field campaign at the Wind River Experimental Forest (WREF) in the U.S. Pacific Northwest to evaluate model performance. In a 2-day case study, the canopy parameterization improved wind predictions both within and above the canopy, particularly during the daytime and at finer grid resolution. Without it, winds were frequently overpredicted above the canopy. Similarly, derived quantities such as the wind shear index also yielded estimates closer to observations with the canopy parameterization implemented. These findings suggest that representing the canopy using drag forces alone can improve simulated mean winds up to 200 m above the surface. Furthermore, second-order statistical moments of wind were more sensitive to canopy density than first-order moments, especially during the daytime. This increased sensitivity and the improved daytime performance in wind speed—evidenced by the lowest bias from observations (3% compared to 20% over diurnal cycle)—imply that winds above the canopy layer are strongly influenced by how well turbulence above the canopy is modeled. The results of this study can serve as a foundation for parameterizing forest canopy effects in coarser weather forecast models.

Energy - Wind↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
NASA NTRS1985

Diagnostics of severe convection and subsynoptic scale ageostrophic circulations

Diagnostics of severe convection and subsynoptic scale ageostrophic circulations are reported. Mesoscale circulations through forcing of ageostrophic motion by adiabatic, diabatic and frictional processes were studied. The development and application of a hybrid isentropic sigma coordinate numerical model was examined. The numerical model simulates mesoscale ageostrophic circulations associated with propagating jet streaks and severe convection. A complete list of publications and these completed through support of the NASA severe storms research project is included.

Source record↗
NASA NTRS1989

Low level remote sensing: Orographic winds

The orographic flow data set was obtained from a flight program to measure the influence of orographic features on turbulence momentum, heat, and moisture fluxes. The NASA B-57 aircraft instrumented with probes for measuring the three fluctuating wind speed components, temperature, and humidity was the primary measuring vehicle. Ancillary measurements were made with several ground-based sensors. These include the NOAA radar wind profilers, the Boulder wind network, the PROFS mesoscale surface network, the Boulder Atmospheric Observatory 300 m tower, special rawinsonde observations, and the NOAA/WPL Doppler lidar. The major objective of the flight program was to provide planetary boundary layer parameter information for new and current general circulation computer models. A numerical code, WINDER, based on a discrete element technique was run to numerically model the water tunnel simulated flow. Comparison of the analytical model with the experimental results is very good. Physical fluid dynamic principles embedded in the computational model and visual and hot wire anemometer measurements from the simulation are being rationalized to develop a physical understanding of the vortex flow. The results will be interpreted as they pertain to full scale atmospheric flows.

Frost, Walter↗
NASA NTRS1993

The 24 GHz measurements of 2.2 lambda conical horn antennas illuminating a conducting sheet

Monostatic reflection-coefficient magnitude, absolute value of Gamma, measurements occurring between a radiating horn and a metal reflecting plate are presented for a family of three 2.2 lambda diameter conical horn antennas. The three horns have different aperture phase deviations: 6 deg, 22.5 deg, and 125 deg. Measurements of the magnitude of absolute value of Gamma as a function of horn-plate separation (d) extend from an effective antenna aperture short (d = O) to beyond the far-field boundary (d = 2D(sup 2)/lambda, where D is the antenna diameter). Measurement data are presented with various physical environments for each of the horns. Measured scalar data are compared with theoretical data from two models, a numerical model for a circular waveguide aperture in a ground plane and a scalar diffraction theory model. This work was conducted in support of the development effort for a spaceborne multifrequency microwave reflectometer designed to accurately determine the distance from a space vehicle's surface to a reflecting plasma boundary. The metal reflecting plate was used to simulate the RF reflectivity of a critically dense plasma. The resulting configuration, a ground plane mounted aperture facing a reflecting plane in close proximity, produces a strong interaction between the ground plane and the reflecting plate, especially at integral half-wavelength separations. The transition coefficient is characterized by large amplitude variations.

Cross, A. E.↗
NASA NTRS1993

Research on Earth's rotation and the effect of atmospheric pressure on vertical deformation and sea level variability

The work done under NASA grant NAG5-485 included modelling the deformation of the earth caused by variations in atmospheric pressure. The amount of deformation near coasts is sensitive to the nature of the oceanic response to the pressure. The PSMSL (Permanent Service for Mean Sea Level) data suggest the response is inverted barometer at periods greater than a couple months. Green's functions were constructed to describe the perturbation of the geoid caused by atmospheric and oceanic loading and by the accompanying load-induced deformation. It was found that perturbation of up to 2 cm are possible. Ice mass balance data was used for continental glaciers to look at the glacial contributions to time-dependent changes in polar motion, the lod, the earth's gravitational field, the position of the earth's center-of-mass, and global sea level. It was found that there can be lateral, non-hydrostatic structure inside the fluid core caused by gravitational forcing from the mantle, from the inner core, or from topography at the core/mantle or inner core/outer core boundaries. The nutational and tidal response of a non-hydrostatic earth with a solid inner core was modeled. Monthly, global tide gauge data from PSMSL was used to look at the 18.6-year ocean tide, the 14-month pole tide, the oceanic response to pressure, the linear trend and inter-annual variability in the earth's gravity field, the global sea level rise, and the effects of post glacial rebound. The effects of mantle anelasticity on nutations, earth tides, and tidal variation in the lod was modeled. Results of this model can be used with Crustal Dynamics observations to look at the anelastic dissipation and dispersion at tidal periods. The effects of surface topography on various components of crustal deformation was also modeled, and numerical models were developed of post glacial rebound.

Wahr, John↗
NASA NTRS1999

Solidification of II-VI Compounds in a Rotating Magnetic Field

This project is aimed at using a rotating magnetic field (RMF) to control fluid flow and transport during directional solidification of elemental and compound melts. Microgravity experiments have demonstrated that small amounts of residual acceleration of less than a micro-g can initiate and prolong fluid flow, particularly when there is a static component of the field perpendicular to the liquid solid interface. Thus a true diffusion boundary layer is not formed, and it becomes difficult to verify theories of solidification or to achieve diffusion controlled solidification. The RMF superimposes a stirring effect on an electrically conducting liquid, and with appropriate field strengths and frequencies, controlled transport of material through a liquid column can be obtained. As diffusion conditions are precluded and complete mixing conditions prevail, the technique is appropriate for traveling solvent zone or float zone growth methods in which the overall composition of the liquid can be maintained throughout the growth experiment. Crystals grown by RMF techniques in microgravity in previous, unrelated missions have shown exceptional properties. The objective of the project is two-fold, namely (1) using numerical modeling to simulate the behavior of a solvent zone with applied thermal boundary conditions and demonstrate the effects of decreasing gravity levels, or an increasing applied RMF, or both, and (2) to grow elements and II-VI compounds from traveling solvent zones both with and without applied RMFs, and to determine objectively how well the modeling predicts solidification parameters. Numerical modeling has demonstrated that, in the growth of CdTe from a tellurium solution, a rotating magnetic field can advantageously modify the shape of the liquid solid interface such that the interface is convex as seen from the liquid. Under such circumstances, the defect structure is reduced as any defects which are formed tend to grow out and not propagate. The flow of liquid, however, is complex due to the competing flow induced by the rotating magnetic field and the buoyancy driven convection. When the acceleration forces are reduced to one thousandth of gravity, the flow pattern is much simplified and well controlled material transport through the solvent zone can be readily achieved. Triple axis diffractometry and x-ray synchrotron topography have demonstrated that there is no significant improvement in crystal quality for HgCdTe grown on earth from a tellurium solution when a rotating magnetic field is applied. However, modeling shows that the flow in microgravity with a rotating magnetic field would produce a superior product.

Gillies, D. C.↗