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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Block-Structured Operator Inference for Coupled Multiphysics Model Reduction

This work presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the governing equation structure for each physics component and the structure of the coupling terms. Once the multiphysics structure is specified, the reduced-order model is learned from snapshot data following the nonintrusive Operator Inference methodology. In addition to preserving physical system structure, which in turn permits preservation of system properties such as stability and second-order structure, the block-structured approach has the advantages of reducing the overall dimensionality of the learning problem and admitting tailored regularization for each physics component. The numerical advantages of the block-structured formulation over a monolithic Operator Inference formulation are demonstrated for aeroelastic analysis, which couples aerodynamic and structural models. For the benchmark test case of the AGARD 445.6 wing, block-structured Operator Inference provides an average 20% online prediction speedup over monolithic Operator Inference across subsonic and supersonic flow conditions in both the stable and fluttering parameter regimes while preserving the accuracy achieved with monolithic Operator Inference.

42 ENGINEERING↗
DOE OSTI2018

Quantifying the agreement between observed and simulated extratropical modes of interannual variability

Using historical simulations of the Coupled Model Intercomparison Project-5 (CMIP5) and multiple observationally-based datasets, we employ skill metrics to analyze the fidelity of the simulated Northern Annular Mode, the North Atlantic Oscillation, the Pacific North America pattern, the Southern Annular Mode, the Pacific Decadal Oscillation, the North Pacific Oscillation, and the North Pacific Gyre Oscillation. We assess the benefits of a unified approach to evaluate these modes of variability, which we call the common basis function (CBF) approach, based on projecting model anomalies onto observed empirical orthogonal functions (EOFs). The CBF approach circumvents issues with conventional EOF analysis, eliminating, for example, corrections of arbitrarily assigned, but inconsistent, signs of the EOF’s/PC’s being compared. It also avoids the problem that sometimes the first observed EOF is more similar to a higher order model EOF, particularly if the simulated EOFs are not well separated. Compared to conventional EOF analysis of models, the CBF approach indicates that models compare significantly better with observations in terms of pattern correlation and root-mean-squared-error (RMSE) than heretofore suggested. In many cases, models are doing a credible job at capturing the observationally-based estimates of patterns; however, errors in simulated amplitudes can be large and more egregious than pattern errors. In the context of the broad distribution of errors in the CMIP5 ensemble, sensitivity tests demonstrate that our results are relatively insensitive to methodological considerations (CBF vs. conventional approach), observational uncertainties in pattern (as determined by using multiple datasets), and internal variability (when multiple realizations from the same model are compared). The skill metrics proposed in this study can provide a useful summary of the ability of models to reproduce the observed EOF patterns and amplitudes. Additionally, the skill metrics can be used as a tool to objectively highlight where potential model improvements might be made. Finally, we advocate more systematic and objective testing of simulated extratropical variability, especially during the non-dominant seasons of each mode, when many models are performing relatively poorly.

58 GEOSCIENCES↗
DOE OSTI2016

The effect of interacting dark energy on local measurements of the Hubble constant

In the current state of cosmology, where cosmological parameters are being measured to percent accuracy, it is essential to understand all sources of error to high precision. In this paper we present the results of a study of the local variations in the Hubble constant measured at the distance scale of the Coma Cluster, and test the validity of correcting for the peculiar velocities predicted by gravitational instability theory. The study is based on N-body simulations, and includes models featuring a coupling between dark energy and dark matter, as well as two ΛCDM simulations with different values of σ{sub 8}. It is found that the variance in the local flows is significantly larger in the coupled models, which increases the uncertainty in the local measurements of the Hubble constant in these scenarios. By comparing the results from the different simulations, it is found that most of the effect is caused by the higher value of σ{sub 8} in the coupled cosmologies, though this cannot account for all of the additional variance. Given the discrepancy between different estimates of the Hubble constant in the universe today, cosmological models causing a greater cosmic variance is something that we should be aware of.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Multiple-amplifier sensing charged-coupled device: model and improvement of the node removal efficiency

The multiple-amplifier sensing charge-coupled device (MAS-CCD) has emerged as a promising technology for astronomical observation, quantum imaging, and low-energy particle detection due to its ability to reduce the readout time for the same readout noise level compared with its predecessor, the skipper-CCD, by reading out the same charge packet through multiple inline amplifiers. Previous works identified a new parameter in this sensor, called node removal inefficiency (NRI), related to inefficiencies in charge transfer and residual charge removal from the sense node of each amplifier after readout. These inefficiencies can lead to distortions in the measured signals similar to those produced by the charge transfer inefficiencies in standard CCDs. We introduce more details in the mathematical model of the NRI mechanism and provide techniques to quantify its magnitude from the measured data. It also proposes a new operation strategy that significantly reduces its effect with minimal alterations of the timing sequences or voltage settings for the other signals of the sensor. The proposed technique is demonstrated experimentally on a 16-amplifier MAS-CCD. At the same time, the experimental data demonstrate that this approach minimizes the NRI effect to levels comparable with other sources of distortion such as the charge transfer inefficiency in scientific devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Coupled Multiphysics Modeling of Lithium-Ion Batteries for Automotive Crashworthiness Applications

Considerable advances have been made in battery safety models, but achieving predictive accuracy across a wide range of conditions continues to be challenging. Interactions between dynamically evolving mechanical, electrical, and thermal state variables make model prediction difficult during mechanical abuse scenarios. In this study, we develop a physics-based modeling approach that allows for choosing between different mechanical and electrochemical models depending on the required level of analysis. We demonstrate the use of this approach to connect cell-level abuse response to electrode-level and particle-level transport phenomena. A pseudo-two-dimensional model and simplified single-particle models are calibrated to electrical-thermal cycling data and applied to mechanically induced short-circuit scenarios to understand how the choice of electrochemical model affects the model prediction under abuse scenarios. These models are implemented using user-defined subroutines on ls-dyna finite element software and can be coupled with existing automotive crash safety models.

analysis and design of components↗
DOE OSTI2016

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. Here, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. Furthermore, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. In order to serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Debiasing Watermarks for Large Language Models via Maximal Coupling

Watermarking language models is essential for distinguishing between human and machine-generated text and thus maintaining the integrity and trustworthiness of digital communication. Here, we present a novel green/red list watermarking approach that partitions the token set into “green” and “red” lists, subtly increasing the generation probability for green tokens. To correct token distribution bias, our method employs maximal coupling, using a uniform coin flip to decide whether to apply bias correction, with the result embedded as a pseudorandom watermark signal. Theoretical analysis confirms this approach’s unbiased nature and robust detection capabilities. Experimental results show that it outperforms prior techniques by preserving text quality while maintaining high detectability, and it demonstrates resilience to targeted modifications aimed at improving text quality. This research provides a promising watermarking solution for language models, balancing effective detection with minimal impact on text quality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Ion Energy and Angular Distribution in Biased Inductively Coupled Ar/O 2 Discharges by Using a Hybrid Model

In this work, a global bulk plasma model coupled bi‐directionally with a Monte‐Carlo/fluid sheath model was developed for electronegative inductive discharges, to explore the ion energy function (IEDF) and angular distributions function (IADF) bombarding an rf‐biased electrode. At low bias voltage, the IEDF of shows a single energy peak that transforms into a bimodal distribution with increasing bias voltage. The IEDFs of and are always bimodal. The ion energy peak separation width largely depends on the ion masses. The IADFs are affected by the bias voltage, pressures and coil powers. The results at different coil powers indicate the importance of considering the collisions induced by atoms, especially in a a molecular gas.

Wen, De‐Qi↗
DOE OSTI2016

Carbon cost of plant nitrogen acquisition: global carbon cycle impact from an improved plant nitrogen cycle in the Community Land Model

Abstract Plants typically expend a significant portion of their available carbon ( C ) on nutrient acquisition – C that could otherwise support growth. However, given that most global terrestrial biosphere models ( TBM s) do not include the C cost of nutrient acquisition, these models fail to represent current and future constraints to the land C sink. Here, we integrated a plant productivity‐optimized nutrient acquisition model – the Fixation and Uptake of Nitrogen Model – into one of the most widely used TBM s, the Community Land Model. Global plant nitrogen ( N ) uptake is dynamically simulated in the coupled model based on the C costs of N acquisition from mycorrhizal roots, nonmycorrhizal roots, N‐fixing microbes, and retranslocation (from senescing leaves). We find that at the global scale, plants spend 2.4 Pg C yr −1 to acquire 1.0 Pg N yr −1 , and that the C cost of N acquisition leads to a downregulation of global net primary production ( NPP ) by 13%. Mycorrhizal uptake represented the dominant pathway by which N is acquired, accounting for ~66% of the N uptake by plants. Notably, roots associating with arbuscular mycorrhizal ( AM ) fungi – generally considered for their role in phosphorus (P) acquisition – are estimated to be the primary source of global plant N uptake owing to the dominance of AM ‐associated plants in mid‐ and low‐latitude biomes. Overall, our coupled model improves the representations of NPP downregulation globally and generates spatially explicit patterns of belowground C allocation, soil N uptake, and N retranslocation at the global scale. Such model improvements are critical for predicting how plant responses to altered N availability (owing to N deposition, rising atmospheric CO 2 , and warming temperatures) may impact the land C sink.

Shi, Mingjie↗
DOE OSTI2013

Fully Coupled Well Models for Fluid Injection and Production

Wells are the primary engineered component of geologic sequestration systems with deep subsurface reservoirs. Wells provide a conduit for injecting greenhouse gases and producing reservoirs fluids, such as brines, natural gas, and crude oil, depending on the target reservoir. Well trajectories, well pressures, and fluid flow rates are parameters over which well engineers and operators have control during the geologic sequestration process. Current drilling practices provided well engineers flexibility in designing well trajectories and controlling screened intervals. Injection pressures and fluids can be used to purposely fracture the reservoir formation or to purposely prevent fracturing. Numerical simulation of geologic sequestration processes involves the solution of multifluid transport equations within heterogeneous geologic media. These equations that mathematically describe the flow of fluid through the reservoir formation are nonlinear in form, requiring linearization techniques to resolve. In actual geologic settings fluid exchange between a well and reservoir is a function of local pressure gradients, fluid saturations, and formation characteristics. In numerical simulators fluid exchange between a well and reservoir can be specified using a spectrum of approaches that vary from totally ignoring the reservoir conditions to fully considering reservoir conditions and well processes. Well models are a numerical simulation approach that account for local conditions and gradients in the exchange of fluids between the well and reservoir. As with the mathematical equations that describe fluid flow in the reservoir, variation in fluid properties with temperature and pressure yield nonlinearities in the mathematical equations that describe fluid flow within the well. To numerically simulate the fluid exchange between a well and reservoir the two systems of nonlinear multifluid flow equations must be resolved. The spectrum of numerical approaches for resolving these equations varies from zero coupling to full coupling. In this paper we describe a fully coupled solution approach for well model that allows for a flexible well trajectory and screened interval within a structured hexahedral computational grid. In this scheme the nonlinear well equations have been fully integrated into the Jacobian matrix for the reservoir conservation equations, minimizing the matrix bandwidth.

coupled well model↗
DOE OSTI2015

Rethinking the Default Construction of Multimodel Climate Ensembles

Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process. If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Coupling the Modeled Structural Transmissibility of a Used Nuclear Fuel Conveyance to Over the Road Data - 16215

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Fuel Cycle Technology, has established the Used Fuel Disposition Campaign (UFDC) to conduct research and development activities related to storage, transportation, and disposal of used nuclear fuel (UNF) and high-level radioactive waste (HLW). The mission of the UFDC is to identify alternatives and conduct scientific research and technology development to enable storage, transportation and disposal of used nuclear fuel and HLW generated by existing and future nuclear fuel cycles. The Storage and Transportation staff within the UFDC is responsible for addressing issues regarding the long-term or extended storage (ES) of UNF and its subsequent transportation. Current information is insufficient to determine the ability of UNF, including high-burnup fuel, to withstand shock and vibration loads that could occur when UNF is shipped by rail from nuclear power plant sites to a storage or disposal facility after extended storage. In order to make this determination, the magnitude of the transportation loads transmitted to the UNF must be quantified. Previous preliminary modeling work has shown how the structural transmissibility of the transport system can affect the magnitude of these loads and the importance of modeling all aspects of the transport system (i.e. rail car, transport cradle, cask, canister, and fuel). The work presented herein proposes a methodology for determining the structural transmissibility of a hypothetical transport system, and conditions existing over the road test (OTR) data to predict the performance of the hypothetical system. This method utilizes the modeled frequency response of the hypothetical system to scale the existing OTR acceleration data. This work will be relevant in creating models of a UNF conveyance during transport. As such, preliminary work in coupling the rail vehicle dynamics code NUCARS{sup C}, a general purpose multi-body rail vehicle dynamics simulation package developed by Transportation Technology Center Inc. (TTCI), to existing models of UNF during transport are also discussed herein. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Stevenson, Samantha↗
DOE OSTI2021

Multiphysics and Multiscale Modeling of Coupled Transport of Chloride Ions in Concrete

Chloride ions (Cl−)-induced corrosion is one of the main degradation mechanisms in reinforced concrete (RC) structures. In most situations, the degradation initiates with the transport of Cl− from the surface of the concrete towards the reinforcing steel. The accumulation of Cl− at the steel-concrete interface could initiate reinforcement corrosion once a threshold Cl− concentration is achieved. An accurate numerical model of the Cl− transport in concrete is required to predict the corrosion initiation in RC structures. However, existing numerical models lack a representation of the heterogenous concrete microstructure resulting from the varying environmental conditions and the indirect effect of time dependent temperature and relative humidity (RH) on the water adsorption and Cl− binding isotherms. In this study, a numerical model is developed to study the coupled transport of Cl− with heat, RH and oxygen (O2) into the concrete. The modeling of the concrete microstructure is performed using the Virtual Cement and Concrete Testing Laboratory (VCCTL) code developed by the U.S. National Institute of Standards and Technology (NIST). The concept of equivalent maturation time is utilized to eliminate the limitation of simulating concrete microstructure using VCCTL in specific environmental conditions such as adiabatic. Thus, a time-dependent concrete microstructure, which depends on the hydration reactions coupled with the temperature and RH of the environment, is achieved to study the Cl− transport. Additionally, Cl− binding isotherms, which are a function of the pH of the concrete pore solution, Cl− concentration, and weight fraction of mono-sulfate aluminate (AFm) and calcium-silicate-hydrate (C-S-H), obtained from an experimental study by the same authors are utilized to account for the Cl− binding of cement hydration products. The temperature dependent RH diffusion was considered to account for the transport of Cl− with moisture transport. The temperature and RH diffusion in the concrete domain, composite theory, and Cl− binding and water adsorption isotherms are used in combination, to estimate the ensuing Cl− diffusion field within the concrete. The coupled transport process of heat, RH, Cl−, and O2 is implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE) developed by the U.S. Idaho National Laboratory (INL). The model was verified and validated using data from multiple experimental studies with different concrete mixture proportions, curing durations, and environmental conditions. Additionally, a sensitivity analysis was performed to identify that the water-to-cement (w/c) ratio, the exposure duration, the boundary conditions: temperature, RH, surface Cl− concentration, Cl− diffusion coefficient in the capillary water, and the critical RH are the important parameters that govern the Cl− transport in RC structures. In a case study, the capabilities of the developed numerical model are demonstrated by studying the complex 2D diffusion of Cl− in a RC beam located in two different climatic regions: warm and humid weather in Galveston, Texas, and cold and dry weather in North Minnesota, Minnesota, subjected to time varying temperature, RH, and surface Cl− concentrations.

composite theory↗
NASA NTRS2008

A Stable Clock Error Model Using Coupled First and Second Order Gauss-Markov Processes

Long data outages may occur in applications of global navigation satellite system technology to orbit determination for missions that spend significant fractions of their orbits above the navigation satellite constellation(s). Current clock error models based on the random walk idealization may not be suitable in these circumstances, since the covariance of the clock errors may become large enough to overflow flight computer arithmetic. A model that is stable, but which approximates the existing models over short time horizons is desirable. A coupled first- and second-order Gauss-Markov process is such a model.

Carpenter, Russell↗
DOE OSTI2016

A meridional dipole in premonsoon Bay of Bengal tropical cyclone activity induced by ENSO

Analysis of Bay of Bengal tropical cyclone (TC) track data for the months of May–June during 1979–2014 reveals a meridional dipole in TC intensification: TC intensification rates increased significantly in the northern region and decreased in the southern region. The dipole is consistent with changes in the large–scale TC environment estimated using the Genesis Potential Index (GPI) for the same period. While an increase in lower troposphere cyclonic vorticity and midtroposphere humidity in the northern Bay of Bengal made the environment more favorable for TC intensification, enhanced vertical wind shear in the southern Bay of Bengal tended to reduce TC development. Furthermore, these environmental changes were associated with a strengthening of the monsoon circulation for the months of May–June, driven by a La Niña–like shift in tropical Pacific SSTs and associated tropical wave dynamics. Finally, analysis of a suite of climate models from the Coupled Model Intercomparison Project Phase 5 archive shows that most models correctly reproduce the link between ENSO and premonsoon Bay of Bengal TC activity at interannual timescales, demonstrating the robustness of our main conclusions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Emergent Behavior of Arctic Precipitation in Response to Enhanced Arctic Warming: Enhanced Arctic Precipitation

Amplified warming of the high latitudes in response to human-induced emissions of greenhouse gases has already been observed in the historical record and is a robust feature evident across a hierarchy of model systems, including the models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The main aims of this analysis are to quantify intermodel differences in the Arctic amplification (AA) of the global warming signal in CMIP5 RCP8.5 (Representative Concentration Pathway 8.5) simulations and to diagnose these differences in the context of the energy and water cycles of the region. This diagnosis reveals an emergent behavior between the energetic and hydrometeorological responses of the Arctic to warming: in particular, enhanced AA and its associated reduction in dry static energy convergence is balanced to first order by latent heating via enhanced precipitation. This balance necessitates increasing Arctic precipitation with increasing AA while at the same time constraining the magnitude of that precipitation increase. The sensitivity of the increase, ~1.25 (W/m 2 )/K (~240 (km 3 /yr)/K), is evident across a broad range of historical and projected AA values. Accounting for the energetic constraint on Arctic precipitation, as a function of AA, in turn informs understanding of both the sign and magnitude of hydrologic cycle changes that the Arctic may experience.

54 ENVIRONMENTAL SCIENCES↗