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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Computational Fluid Dynamics Modeling to Facilitate Qualification of Stack Sampling Probe Location

Computational fluid dynamics (CFD) modeling was used to help evaluate modifications to a radiological effluent stack and assist with establishing a stack sampling location that met the mixing criteria for qualification. Requirements for stack sampling location are listed in the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-2021 standard. Modeling was performed to help develop a suitable design for increasing building ventilation for the radiological effluent stack. The ANSI/HPS N13.1-2021 criteria for the air monitoring probe location are that the coefficient of variation of velocity uniformity, gaseous tracer uniformity, and particulate tracer uniformity must be less than or equal to 20%. Furthermore, no point in the sampling location may have a gaseous tracer concentration that varies from the mean concentration by more than 30%. Additionally, the flow angle at the sampling location must not be more than 20 degrees. The ANSI/HPS N13.1-2021 standard allows for models (physical or computational) to be employed to perform the full suite of qualification tests, followed by a more limited set of verification tests on the actual stack to qualify the stack sampling location. Here, a series of computational model simulations were employed to evaluate the stack qualification criteria. Significant time and re-source savings are achieved using CFD modeling. CFD modeling demonstrated that the stack meets the criteria at the sample probe location. Verification tests were performed on the modified stack to measure the velocity uniformity and flow angle at the stack sampling location, and results demonstrated that the CFD model results may be used to support the qualification of the stack sampling location.

Air Monitoring↗
NASA NTRS1977

Wind-tunnel measurements in the wakes of structures

Detailed measurements of longitudinal mean velocity, turbulence intensity, space correlations, and spectra made in the wake of two rectangular scaled models in simulated atmospheric boundary-layer winds are presented. The model buildings were 1:50 scale models of two trailers. Results of a flow visualization study of the wake geometry are analyzed with some singular point theorems. Two hypothetical flow patterns of the detailed wake geometry are proposed. Some preliminary studies of the vortex wake, effects of the model size, model aspect ratios, and boundary layer characteristics on the decay rate and extent of the wake are also presented and discussed.

Woo, H. G. C.↗
DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗
NASA NTRS1982

Wind tunnel measurements of three-dimensional wakes of buildings

Measurements relevant to the effect of buildings on the low level atmospheric boundary layer are presented. A wind tunnel experiment was undertaken to determine the nature of the flow downstream from a gap between two transversely aligned, equal sized models of rectangular cross section. These building models were immersed in an equilibrium turbulent boundary layer which was developed on a smooth floor in a zero longitudinal pressure gradient. Measurements with an inclined (45 degree) hot-wire were made at key positions downstream of models arranged with a large, small, and no gap between them. Hot-wire theory is presented which enables computation of the three mean velocity components, U, V and W, as well as Reynolds stresses. These measurements permit understanding of the character of the wake downstream of laterally spaced buildings. Surface streamline patterns obtained by the oil film method were used to delineate the separation region to the rear of the buildings for a variety of spacings.

Logan, E., Jr.↗
NASA NTRS2006

Ferroelectric Material Application: Modeling Ferroelectric Field Effect Transistor Characteristics from Micro to Nano

All present ferroelectric transistors have been made on the micrometer scale. Existing models of these devices do not take into account effects of nanoscale ferroelectric transistors. Understanding the characteristics of these nanoscale devices is important in developing a strategy for building and using future devices. This paper takes an existing microscale ferroelectric field effect transistor (FFET) model and adds effects that become important at a nanoscale level, including electron velocity saturation and direct tunneling. The new model analyzed FFETs ranging in length from 40,000 nanometers to 4 nanometers and ferroelectric thickness form 200 nanometers to 1 nanometer. The results show that FFETs can operate on the nanoscale but have some undesirable characteristics at very small dimensions.

MacLeod, Todd, C.↗
DOE OSTI2022

Substructure at High Speed. II. The Local Escape Velocity and Milky Way Mass with Gaia eDR3

Abstract Measuring the escape velocity of the Milky Way is critical in obtaining the mass of the Milky Way, understanding the dark matter velocity distribution, and building the dark matter density profile. In Necib & Lin, we introduced a strategy to robustly measure the escape velocity. Our approach takes into account the presence of kinematic substructures by modeling the tail of the stellar distribution with multiple components, including the stellar halo and the debris flow called the Gaia Sausage (Enceladus). In doing so, we can test the robustness of the escape velocity measurement for different definitions of the “tail” of the velocity distribution and the consistency of the data with different underlying models. In this paper, we apply this method to the Gaia eDR3 data release and find that a model with two components is preferred, although results from a single-component fit are also consistent. Based on a fit to retrograde data with two bound components to account for the relaxed halo and the Gaia Sausage, we find the escape velocity of the Milky Way at the solar position to be v esc = 445 − 8 + 25 km s −1 . A fit with a single component to the same data gives v esc = 472 − 12 + 17 km s −1 . Assuming a Navarro−Frenck−White dark matter profile, we find a Milky Way concentration of c 200 = 19 − 7 + 11 and a mass of M 200 = 4.6 − 0.8 + 1.5 × 10 11 M ⊙ , which is considerably lighter than previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Urbanization-induced land and aerosol impacts on sea-breeze circulation and convective precipitation

Abstract. Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

A wind model for an elevated STOL-port configuration

Measurements of mean velocity magnitude and direction as well as three-dimensional turbulence intensity were made in the flow over a model of an elevated STOL-port. A 1:300 scale model was placed in a wind tunnel flow simulating the mean velocity profile and turbulence characteristics of atmospheric winds over a typical city environment excluding detailed wake structures of possible nearby buildings. Hot-wire anemometer measurements of velocity and turbulence were made along approach and departure paths of aircraft operating on the runway centerline and at specified lateral distances from the centerline. Approach flow directions simulated were 0 and 30 degrees to the runway centerline.

Peterka, J. A.↗
NASA NTRS1994

Computational analysis of high resolution unsteady airloads for rotor aeroacoustics

The study of helicopter aerodynamic loading for acoustics applications requires the application of efficient yet accurate simulations of the velocity field induced by the rotor's vortex wake. This report summarizes work to date on the development of such an analysis, which builds on the Constant Vorticity Contour (CVC) free wake model, previously implemented for the study of vibratory loading in the RotorCRAFT computer code. The present effort has focused on implementation of an airload reconstruction approach that computes high resolution airload solutions of rotor/rotor-wake interactions required for acoustics computations. Supplementary efforts on the development of improved vortex core modeling, unsteady aerodynamic effects, higher spatial resolution of rotor loading, and fast vortex wake implementations have substantially enhanced the capabilities of the resulting software, denoted RotorCRAFT/AA (AeroAcoustics). Results of validation calculations using recently acquired model rotor data show that by employing airload reconstruction it is possible to apply the CVC wake analysis with temporal and spatial resolution suitable for acoustics applications while reducing the computation time required by one to two orders of magnitude relative to that required by direct calculations. Promising correlation with this body of airload and noise data has been obtained for a variety of rotor configurations and operating conditions.

Quackenbush, Todd R.↗
DOE OSTI2022

Multi-fidelity information fusion with concatenated neural networks

Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.

42 ENGINEERING↗
DOE OSTI2023

TriWaSp: a multi-faceted visible spectroscopy diagnostic on the ST40 tokamak

Here, we present a new state-of-the-art Triple Wavelength Spectrometer (TriWaSp), recently deployed on ST40, a high field low aspect ratio spherical tokamak. The TriWaSp has a range of possible applications due to its flexible design; the current configuration focuses on charge exchange recombination spectroscopy from carbon and neon impurities in the ST40 plasma. This paper discusses the detailed setup of the system and presents initial charge exchange ion temperature measurements using a single line of sight, which show good agreement with other ion temperature diagnostics. Building on these commissioning results and forward modelling of the system, a new observation geometry has been implemented for the next experimental campaign which will considerably improve the localisation of ion temperature and velocity profile measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Tools for Assessing Performance Project: FY2021 Quarter 4 Report

The rotatable building located at Texas Tech’s Reese Technology Center is approximately 14 m wide (width being defined as more normal to the wind than parallel), 9 m long (aligned more with the wind than perpendicular), and 4 m tall. By placing 29 sonic anemometers downwind of the building, see Fig. 1, this facility provided a chance to collect data concerning both the wake velocity deficit distribution in the downstream and crosssteam directions (relative to the mean wind) behind an isolated building. A preliminary comparison between this data and the recently- developed fast-running diffusive wake model, which was developed based on wind tunnel and LES (performed with JOULES) simulations, for the purpose of either validating this model of understanding potential persistent differences between the idealized wind tunnel or LES conditions and those of full-scale real world phenomena. For this preliminary exploration, we utilized the diffusive wake model implemented in the QUIC model.

42 ENGINEERING↗
NASA NTRS2002

A Mechanistic Study of Nucleate Boiling Under Microgravity Conditions

The overall objective of this work is to study nucleate boiling heat transfer under microgravity conditions in such a way that while providing basic knowledge of the phenomena, it also leads to development of simulation models and correlations that can be used as design tools for a wide range of gravity levels. In the study a building block type of approach is used and both pool and low velocity flow boiling are investigated. Starting with experiments using a single bubble, the complexity of the experiments is increased to two or three inline bubbles, to five bubbles placed on a two-dimensional grid. Finally, experiments are conducted where a large number of prescribed cavities nucleate on the heater and when a commercial surface is used. So far experiments have been conducted at earth normal gravity and in the reduced gravity environment of the KC-135 aircraft whereas experiments on the space station are planned. Modeling/complete numerical simulation of the boiling process is an integral part of the total effort. Experiments conducted with single bubbles formed on a nucleation site microfabricated on a polished silicon wafer show that for gravity levels (g) varying from 1.5g(sub e) to 0.01g(sub e), the bubble diameter at departure varies approximately as (g(sub e)/g)(exp 1/2) and the growth period as (g(sub e)/g). When bubbles merge either inline or in a plane, the bubble diameter at departure is found to be smaller than that obtained for a single bubble and shows a weaker dependence on the level of gravity. The possible reason is that as the bubbles merge they create fluid circulation around the bubbles, which in turn induces a lift force that is responsible for the earlier departure of the bubbles. The verification of this proposition is being sought through numerical simulations. There is a merger of two inline, three inline, and several bubbles in a plane in the low gravity environment of the KC-135 aircraft. After merger and before departure, a mushroom type of bubble with several stems attached to the heater surface is clearly evident. Local heat fluxes during growth and departure of a single bubble were also measured. It was found that during most of the growth period of the bubble, generally the wall heat flux decreased with time because of the increased dry area under the bubble. However, the heat flux increased rapidly just prior to departure of the bubble because of the transient conduction into the cold liquid rushing to fill the space vacated by the bubble as the bubble base shrinks. The measured heat fluxes at various radial locations are found to be in qualitative agreement with the numerical predictions. Single bubble studies at earth normal gravity have also been performed on surfaces oriented at different angles to the gravitational acceleration with flow parallel to the surface. It is found that in all cases the bubbles slide along the surface before lift-off from the surface. The lift force generated as a result of the relative motion between the sliding bubbles and the imposed flow is found to play an important role when the normal force due to buoyancy is reduced. An experimental apparatus for the study of the bubble behavior with imposed flow under reduced gravity conditions has been developed and will soon be employed for experiments in the KC-135 aircraft.

Dhir, V. K.↗
DOE OSTI2023

Solving Seismic Wave Equations on Variable Velocity Models With Fourier Neural Operator

Here, in the study of subsurface seismic imaging, solving the acoustic wave equation is a pivotal component in existing models. The advancement of deep learning (DL) enables solving partial differential equations (PDEs), including wave equations, by applying neural networks to identify the mapping between the inputs and the solution. This approach can be faster than traditional numerical methods when numerous instances are to be solved. Previous works that concentrate on solving the wave equation by neural networks consider either a single velocity model or multiple simple velocity models, which is restricted in practice. Instead, inspired by the idea of operator learning, this work leverages the Fourier neural operator (FNO) to effectively learn the frequency domain seismic wavefields under the context of variable velocity models. We also propose a new framework paralleled FNO (PFNO) for efficiently training the FNO-based solver given multiple source locations and frequencies. Numerical experiments demonstrate the high accuracy of both FNO and PFNO with complicated velocity models in the OpenFWI datasets. Furthermore, the cross-dataset generalization test verifies that PFNO adapts to out-of-distribution velocity models. Finally, PFNO admits higher computational efficiency on large-scale testing datasets than the traditional finite-difference method. The aforementioned advantages endow the FNO-based solver with the potential to build powerful models for research on seismic waves.

58 GEOSCIENCES↗
DOE OSTI2025

Evaluating quenching in cosmological simulations of galaxy formation with spectral covariance in the optical window

ABSTRACT Cosmological hydrodynamical simulations provide valuable insights on galaxy evolution when coupled with observational data. Comparisons with real galaxies are typically performed via scaling relations of the observables. Here, we follow an alternative approach based on the spectral covariance in a model-independent way. We build upon previous work by Sharbaf et al. that studied the covariance of high-quality SDSS (Sloan Digital Sky Survey) continuum-subtracted spectra in a relatively narrow range of velocity dispersion ($\sigma \in [100,150]$ km s$^{-1}$). Here, the same analysis is applied to synthetic data from the eagle and IllustrisTNG100 simulations, to assess the ability of these runs to mimic real galaxies. The real and simulated spectra are consistent regarding spectral covariance, although with subtle differences that can inform the implementation of subgrid physics. Spectral fitting done a posteriori on stacks segregated with respect to latent space reveals that the first principal component (PC1) is predominantly influenced by the stellar age distribution, with an underlying age–metallicity degeneracy. Good agreement is found regarding star formation prescriptions but there is disagreement with active galactic nucleus (AGN) feedback, that also affects the subset of quiescent galaxies. We show a substantial difference in the implementation of the AGN subgrid prescriptions, regarding central black hole seeding, that could lead to the mismatch. Differences are manifest between these two simulations in the star formation histories stacked with respect to latent space. We emphasize that this methodology only relies on the spectral covariance to assess whether simulations provide a true representation of galaxy formation.

Sharbaf, Z. (ORCID:0009000450545946)↗
DOE OSTI2021

A general approach to seismic inversion with automatic differentiation

Imaging Earth structure or seismic sources from seismic data involves minimizing a target misfit function, and is commonly solved through gradient-based optimization. The adjoint-state method has been developed to compute the gradient efficiently; however, its implementation can be time-consuming and difficult. We develop a general seismic inversion framework to calculate gradients using reverse-mode automatic differentiation. The central idea is that adjoint-state methods and reverse-mode automatic differentiation are mathematically equivalent. Here, the mapping between numerical PDE simulation and deep learning allows us to build a seismic inverse modeling library, ADSeismic, based on deep learning frameworks, which supports high performance reverse-mode automatic differentiation on CPUs and GPUs. We demonstrate the performance of ADSeismic on inverse problems related to velocity model estimation, rupture imaging, earthquake location, and source time function retrieval. ADSeismic has the potential to solve a wide variety of inverse modeling applications within a unified framework.

58 GEOSCIENCES↗
DOE OSTI2022

Landmark-Warped Emulators for Models with Misaligned Functional Response

Many computer models output functional data, and in some cases, these functional data have similar, but misaligned, shape characteristics. In this paper, we introduce a general approach for building emulators for computer models that output misaligned functional data when key values in the functional response (landmarks) can be easily identified. This approach has two main parts: modeling the aligned (using the landmarks) functional data, and modeling the functions that map the misaligned data to the aligned space (warping functions). As the warping functions are required to be monotonic, we give special attention to modeling monotonic functional response data. We discuss how our approach can be easily applied for a variety of typical emulators, such as Gaussian processes, Bayesian multivariate adaptive regression splines, and Bayesian additive regression trees, and how sensitivity analysis can be performed. We demonstrate our approach by building emulators for two applications: (1) a high-energy-density physics computer model used to simulate inertial confinement fusion ignition experiments, where model outputs are highly misaligned, and (2) a multiphysics continuum hydrocode used to simulate high-velocity impact experiments, where model outputs are only slightly misaligned. In case (1) traditional methods cannot be applied, while in (2) they can be applied, but the proposed method performs significantly better.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Critical Progressive Damage Analysis Model Features for Low-Velocity Impact on Thermoset and Thermoplastic Panels

A previous verification and validation framework evaluated the ability of various progressive damage analysis (PDA) tools to predict the mechanical response and damage state in post-buckled stiffened aerospace structures composed of fiber-reinforced thermoset composite materials. Herein, the ability of PDA tools to predict damage in thermoplastic composite materials subject to low-velocity impact (LVI) loading has been assessed. LVI tests and analyses have been conducted for similar panels, comprising thermoset or thermoplastic composite materials. Preliminary test/analysis correlations revealed that using the same combination of PDA model features and finite element model-building guidelines for the thermoset and thermoplastic LVI specimens resulted in underprediction of matrix crack lengths and delaminated area in the thermoplastic analyses despite yielding good correlations for the thermoset specimens. In this paper, the quality of the test/analysis correlations for analyses of thermoplastic LVI specimens performed with different combinations of PDA model features using the NASA CompDam material model are presented. Model features that were assessed in terms of effect on the quality of the test/analysis correlation include the representation of damageable interfaces, residual thermal stresses, and fiber damage.

Frank Leone↗