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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗
NASA NTRS1982

Analytical modeling of operating characteristics of premixing-prevaporizing fuel-air mixing passages. Volume 1: Analysis and results

A model for predicting the distribution of liquid fuel droplets and fuel vapor in premixing-prevaporizing fuel-air mixing passages of the direct injection type is reported. This model consists of three computer programs; a calculation of the two dimensional or axisymmetric air flow field neglecting the effects of fuel; a calculation of the three dimensional fuel droplet trajectories and evaporation rates in a known, moving air flow; a calculation of fuel vapor diffusing into a moving three dimensional air flow with source terms dependent on the droplet evaporation rates. The fuel droplets are treated as individual particle classes each satisfying Newton's law, a heat transfer, and a mass transfer equation. This fuel droplet model treats multicomponent fuels and incorporates the physics required for the treatment of elastic droplet collisions, droplet shattering, droplet coalescence and droplet wall interactions. The vapor diffusion calculation treats three dimensional, gas phase, turbulent diffusion processes. The analysis includes a model for the autoignition of the fuel air mixture based upon the rate of formation of an important intermediate chemical species during the preignition period.

Anderson, O. L.↗
NASA NTRS1983

Analytical Modeling of Operating Characteristics of Premixing-prevaporizing Fuel-air Mixing Passages

A model for predicting the distribution of liquid fuel droplets and fuel vapor in premixing-prevaporizing fuel-air mixing passages of the direct injection type is described. This model consists of three computer programs: a calculation of the two dimensional or axisymmetric air flow field neglecting the effects of fuel; a calculation of the three dimensional fuel droplet trajectories and evaporation rates in a known, moving air flow; and a calculation of fuel vapor diffusing into a moving three dimensional air flow with source terms dependent on the droplet evaporation rates. The air flow calculation can treat compressible swirling flows in arbitrary ducts with arbitrary distributions of temperature and velocity as initial conditions. The fuel droplets are treated as initial conditions. The fuel droplets are treated as individual particle classes each satisfying Newton's law, a heat transfer, and a mass transfer equation. The vapor diffusion calculation treats three dimensional, gas phase, turbulent diffusion processes with the turbulence level determined by the air flow calculations and the source terms determined by the droplet evaporation rates.

Anderson, O. L.↗
NASA NTRS1989

An investigation of the diffraction of an acoustic plane wave by a curved surface of finite impedance

Phenomena associated with long range propagation of sound over irregular topography motivated this work, which was to analyze the diffraction effects which would occur near the tops of hills and ridges. The diffraction of a high frequency plane wave due to its grazing of a two-dimensional curved surface of finite impedance was also studied. Laboratory scale models were constructed and measurements were made of the field on, above, and behind either of two curved surfaces possessing distinctly different impedances; that is, one was soft while the other was hard. The experimental technique consisted of simultaneously measuring the pressure at a reference point and at a field point due to a transient pulse generated by an electric spark. The pressure waveforms were digitized and processed. The ratio of the discrete Fourier transforms of the two waveforms provided an estimate of the insertion loss between them. The results of the measurements were compared with the predictions of a theory which was derived by Pierce using the method of Matched Asymptotic Expansions (MAE). The predictions relied upon the experimental evaluation of the impedance of each surface at grazing angles of incidence. This evaluation was achieved by a fairly standard technique involving empirical models of various generic types of surfaces. An example was shown of the important role that the structural intricacies of a surface play in the determination of an appropriate model. The comparison between the measurements and predictions indicated that the theory gives an excellent description of the field anywhere near a curved surface. Further, with a simple modification, the theory was also shown to give nearly as good of a description of the field surrounding a curved surface even at distances far behind the surface yet near the line of sight.

Kearns, James A.↗
NASA NTRS1992

A VLA 3.6 centimeter survey of N-type carbon stars

The results are presented of a VLA-continuum survey of 7 N-type carbon stars at 3.6 cm. Evidence exists for hot plasma around such stars; the IUE satellite detected emission lines of singly ionized metals in the optically brightest carbon stars, which in solar-type stars indicate the existence of a chromosphere. In the past, these emission lines were used to constrain the lower portion of the archetypical chromospheric model of N-type carbon stars, that of TX Psc. Five of the survey stars are semiregular (1 SRa and 4 SRb) variables and two are irregular (Lb) variables. Upper limits of about 0.07 mJy are set of the SRb and Lb variables and the lone SRa (V Hya) was detected with a flux of 0.22 mJy. The upper limits for the six stars that are not detected indicate that the temperature in their winds is less than 10,000 K. Various scenarios for the emission from V Hya are proposed, and it is suggested that the radio continuum is shock-related (either due to pulsation or the suspected bipolar jet) and not due to a supposed accretion disk around an unseen companion.

Luttermoser, Donald G.↗
NASA NTRS2005

Modeling of Triangular Lattice Space Structures with Curved Battens

Techniques for simulating an assembly process of lattice structures with curved battens were developed. The shape of the curved battens, the tension in the diagonals, and the compression in the battens were predicted for the assembled model. To be able to perform the assembly simulation, a cable-pulley element was implemented, and geometrically nonlinear finite element analyses were performed. Three types of finite element models were created from assembled lattice structures for studying the effects of design and modeling variations on the load carrying capability. Discrepancies in the predictions from these models were discussed. The effects of diagonal constraint failure were also studied.

Chen, Tzikang↗
DOE OSTI2023

Efficient Reliability Analysis using Generalized Multifidelity Modeling and Explainable Active Learning

To assess the reliability of critical technologies like nuclear plants and infrastructure systems and improve the robustness of design, engineers have to quantify the uncertainties surrounding the system behavior accurately. However, the complexity of the problem can make standard reliability analysis algorithms prohibitively expensive, primarily due to the high computational cost of estimating the system response at each iteration. This cost can be greatly reduced by using multi-fidelity modeling and machine learning to build a surrogate model to replace the expensive response function. We propose a general and robust method for building surrogates from multiple Low Fidelity (LF) models coupled with machine learning to retain accuracy. Our framework first constructs “Corrected Low Fidelity models” (CLFs) by coupling a High Fidelity (HF) model inferred Gaussian Process correction term with each of the LF models. It then uses the correction terms to assign model probabilities to each of these CLFs in an explainable way before using them to assemble the final surrogate. No assumptions are made about the type of the LF models or their correlation with the HF model. The proposed surrogate modeling framework is used within the subset simulation algorithm (a variance-reduced MCMC-based reliability analysis algorithm) for enhanced efficiency. Additionally, an active learning step is added to the algorithm to adaptively decide when the surrogate is not sufficiently accurate, at which point the HF model is called and used to refine the surrogate. Through a frame buckling example, our method is shown to be highly efficient at reducing the expensive HF model calls while accurately estimating the failure probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1995

Spectral and Temporal Characteristics of X-Ray-Bright Stars in the Pleiades

We follow up our deep ROSAT imaging survey of the Pleiades (Stauffer et al. 1994) with an analysis of the spectral and temporal characteristics of the X-ray-bright stars in the Pleiades. Raymond & Smith (1977) one and two-temperature models have been used to fit the position-sensitive proportional counter (PSPC) pulse-height spectra of the dozen or so brightest sources associated with late-type Pleiades members. The best-fit temperatures suggest hot coronal temperatures for K, M, and rapidly rotating G stars, and cooler temperatures for F and slowly rotating G stars. In order to probe the many less X-ray-luminous stars, we have generated composite spectra by combining net counts from all Pleiades members according to spectral type and rotational velocity. Model fits to the composite spectra confirm the trend seen in the individual spectral fits. Particularly interesting is the apparent dependence of coronal temperature on L(sub x)/L(sub bol). A hardness-ratio analysis also confirms some of these trends. The PSPC data have also revealed a dozen or so strong X-ray flares with peak X-ray luminosities in excess of approx. 10(exp 30) ergs/sec. We have modeled the brightest of these flares with a simple quasi-static cooling loop model. The peak temperature and emission measure and the inferred electron density and plasma volume suggest a very large scale flaring event. The PSPC data were collected over a period of approx. 18 months, allowing us to search for source variability on timescales ranging from less than a day (in the case of flares) to more than a year between individual exposures. On approximately year-long timescales, roughly 25% of the late-type stars are variable. Since the Pleiades was also intensively monitored by the imaging instruments on the Einstein Observatory, we have examined X-ray luminosity variations on the 10 yr timescale between Einstein and ROSAT and find that up to 40% of the late-type stars are X-ray variable. Since there is only marginal evidence for increased variability on decade-long timescales, the variability observed on long and short timescales may have a common physical origin.

Gagne, Marc↗
DOE OSTI2021

Modeling and simulation of vascular tumors embedded in evolving capillary networks

Here in this work, we present a coupled 3D–1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionally, the model includes erosion of the extracellular matrix, interstitial flow, and coupled flow in blood vessels and tissue. We employ continuum mixture theory with stochastic Cahn–Hilliard type phase-field models of tumor growth. The interstitial flow is governed by a mesoscale version of Darcy’s law. The flow in the blood vessels is controlled by Poiseuille flow, and Starling’s law is applied to model the mass transfer in and out of blood vessels. The evolution of the network of blood vessels is orchestrated by the concentration of the tumor angiogenesis factors (TAFs); blood vessels grow towards the increasing TAFs concentrations. This process is not deterministic, allowing random growth of blood vessels and, therefore, due to the coupling of nutrients in tissue and vessels, makes the growth of tumors stochastic. We demonstrate the performance of the model by applying it to a variety of scenarios. Numerical experiments illustrate the flexibility of the model and its ability to generate satellite tumors. Simulations of the effects of angiogenesis on tumor growth are presented as well as sample-independent features of cancer.

3D–1D coupled blood flow models↗
NASA NTRS1988

Time domain identification of element matrices

Accurate mathematical models are clearly an important part of the design, modification, control, and damage assessment of large space structures. A critical part of model determination of any type of structure is the use of system identification (SI), a process for using measured excitation and response data to improve the form of a mathematical model or the values of the parameters in it. The reasons for using SI are manifold, but most of them involve uncertainties in either the form of or the parameters in the mathematical model. Some of the more common uncertainties are the following: the nature of the damping, the characteristics of sloppy or sticky joints, inelastic material properties, and parameters in a reduced Degree-of-Freedom (DOF) model. This paper contains a description of the SI algorithm followed by two illustrations: one in which all parameters in a shear building model are determined using pull back and quick release data, and another in which an equivalent reduced DOF model is obtained for a two story frame.

Matzen, Vernon C.↗
NASA NTRS2010

Identification of a New Spinel-Rich Lunar Rock Type by the Moon Mineralogy Mapper (M (sup 3))

The canonical characterization of the lunar crust is based principally on available Apollo, Luna, and meteorite samples. The crust is described as an anorthosite-rich cumulate produced by the lunar magma ocean that has been infused with a mix of Mgsuite components. These have been mixed and redistributed during the late heavy bombardment and basin forming events. We report a new rock-type detected on the farside of the Moon by the Moon Mineralogy Mapper (M3) on Chandrayaan-1 that does not easily fit with current crustal evolution models. The rock-type is dominated by Mg-spinel with no detectible pyroxene or olivine present (<5%). It occurs along the western inner ring of Moscoviense Basin as one of several discrete areas that exhibit unusual compositions relative to their surroundings but without morphological evidence for separate processes leading to exposure.

Pieters, C. M.↗
NASA NTRS1991

Methods for evaluating the predictive accuracy of structural dynamic models

Modeling uncertainty is defined in terms of the difference between predicted and measured eigenvalues and eigenvectors. Data compiled from 22 sets of analysis/test results was used to create statistical databases for large truss-type space structures and both pretest and posttest models of conventional satellite-type space structures. Modeling uncertainty is propagated through the model to produce intervals of uncertainty on frequency response functions, both amplitude and phase. This methodology was used successfully to evaluate the predictive accuracy of several structures, including the NASA CSI Evolutionary Structure tested at Langley Research Center. Test measurements for this structure were within + one-sigma intervals of predicted accuracy for the most part, demonstrating the validity of the methodology and computer code.

Hasselman, Timothy K.↗
DOE OSTI2026

Differential Privacy in Grid Kitchen: Implementation & Software Documentation

Sharing of power grid feeder models faces significant challenges due to the potential risk of exposing sensitive operational information. Traditional anonymization techniques have shown notable limitations in other sensitive domains, as evidenced by documented re-identification attacks that combine supposedly anonymized datasets with auxiliary information, raising concerns that similar vulnerabilities could affect power grid data. Consequently, there is a pressing need for a more rigorous privacy protection strategy that not only delivers formal mathematical guarantees but also preserves the analytical value of the shared models. To address this challenge, we have enhanced the Grid Kitchen framework by implementing differential privacy mechanisms within the distribution model dehydration pipeline. This implementation carefully calibrates and applies noise to sensitive attributes in feeder models according to configurable privacy levels—low, moderate, and high—each offering different balances between data utility and privacy protection. Our approach uses established noise functions (Gaussian for continuous data and Discrete Laplace for integer values) with parameters carefully calibrated so that the impact of individual data points is effectively masked in the final output. The integration leverages our Noise Catalog, which we developed to categorize feeder model properties by component type, data type, and sensitivity. This catalog guides the application of appropriate noise functions and privacy parameters ($\varepsilon$ and $\delta$) to each attribute, ensuring consistent privacy protection across the model while maintaining its structural integrity and analytical usefulness. This implementation also includes evaluation tools that allow model owners to assess the impact of privacy-preserving transformations before sharing data with external parties. This report provides documentation for the differential privacy capabilities added to the Grid Kitchen project. It includes a primer on differential privacy concepts and their importance in modern data sharing, details the architecture of our implementation, explains the privacy modes and parameter configurations, and offers practical guidance on using the code for applying differential privacy to grid feeder models. Through examples and code snippets, we demonstrate the effective application of these privacy-enhancing technologies, enabling utility operators and researchers to confidently share grid data while protecting sensitive information.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗