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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Towards an open model intercomparison platform for integrated assessment models scenarios

The majority of scenarios in the IPCC database are generated by integrated assessment models (IAMs) and come from model intercomparison projects. However, the way in which the current model intercomparison projects are organized is not open to all IAM teams worldwide. Here we propose a transparent and inclusive platform that is open to anyone with an IAM regarding protocols development, scenario submissions and results evaluation. We discuss the challenges of this approach, particularly human resources and financial support. Here, we identify diversity in the level of model capability and quality of model output as possibly critical issues. Despite such challenges, the IAM community and its scientific activities can improve and benefit from the proposed platform, ultimately contributing to better climate policymaking.

IAM↗
DOE OSTI2025

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗
DOE OSTI2015

Two-dimensional hybrid Monte Carlo–fluid modelling of dc glow discharges: Comparison with fluid models, reliability, and accuracy

Two-dimensional hybrid Monte Carlo–fluid numerical code is developed and applied to model the dc glow discharge. The model is based on the separation of electrons into two parts: the low energetic (slow) and high energetic (fast) electron groups. Ions and slow electrons are described within the fluid model using the drift-diffusion approximation for particle fluxes. Fast electrons, represented by suitable number of super particles emitted from the cathode, are responsible for ionization processes in the discharge volume, which are simulated by the Monte Carlo collision method. Electrostatic field is obtained from the solution of Poisson equation. The test calculations were carried out for an argon plasma. Main properties of the glow discharge are considered. Current-voltage curves, electric field reversal phenomenon, and the vortex current formation are developed and discussed. The results are compared to those obtained from the simple and extended fluid models. Contrary to reports in the literature, the analysis does not reveal significant advantages of existing hybrid methods over the extended fluid model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Demonstration of the Advanced Dynamic System Modeling Tool TRANSFORM in a Molten Salt Reactor Application via a Model of the Molten Salt Demonstration Reactor

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. Here, this paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations

Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ the Monte Carlo N-Particle (MCNP) code to provide high- delity simulations of radiation transport within an urban domain. The model is constructed to employ a source location (x, y, z) as input and return the estimated count rate for a set of speci ed detector locations. Because MCNP simulations are computationally expensive, we develop e cient and accurate surrogate models of the detector responses. We construct surrogate models using Gaussian processes (GP) and neural networks (NN) that we train and verify using the MCNP simulations. The trained surrogate models provide an e cient framework for Bayesian inference and experimental design. We employ Delayed Rejection Adaptive Metropolis (DRAM), a Markov Chain Monte Carlo (MCMC) algorithm, to infer the location and intensity of an unknown source. The DRAM results yield a posterior probability distribution for the source's location conditioned on the observed detector count rates. The posterior distribution exhibits regions of high and low probability within the simulated environment identifying potential source locations. In this manner, we can quantify the source location to within at least one of these regions of high probability in the considered cases. Employing these methods, we are able to reduce the space of potential source locations by at least 60%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Chelation Modeling: The Use of Ad Hoc Models and Approaches to Overcome a Dose Assessment Challenge

Here, chelating agents are administered to treat significant intakes of radioactive elements such as plutonium, americium, and curium. These drugs may be used as a medical countermeasure after radiological accidents and terrorist acts. The administration of a chelating agent, such as Ca-DTPA or Zn-DTPA, affects the actinide's normal biokinetics. It enhances the actinide's rate of excretion, posing a dose assessment challenge. Thus, the standard biokinetic models cannot be directly applied to the chelation-affected bioassay data in order to assess the radiation dose. The present study reviews the scientific literature, from the early 1970s until the present, on the different studies that focused on developing new chelation models and/or modeling of bioassay data affected by chelation treatment. Although scientific progress has been achieved, there is currently no consensus chelation model available, even after almost 50 y of research. This review acknowledges the efforts made by different research groups, highlighting the different methodology used in some of these studies. Finally, this study puts into perspective where we were, where we are, and where we are heading in regards to chelation modeling.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Comparison of Load Models for Estimating Electrical Efficiency in DC Microgrids: Preprint

This paper compares several electrical load models for estimating the efficiency of DC vs. AC distribution in microgrids. Candidate models include energy balance, harmonic power flow, and time-domain modeling. Model results are compared with numerical studies and validated with experimental measurements. Based on quantitative and qualitative considerations, the most appropriate load modeling approach for larger-scale DC distribution efficiency studies is proposed.

DC distribution↗
DOE OSTI2016

Modeling of Protection in Dynamic Simulation Using Generic Relay Models and Settings

This paper shows how generic protection relay models available in planning tools can be augmented with settings that are based on NERC standards or best engineering practice. Selected generic relay models in Siemens PSS®E have been used in dynamic simulations in the proposed approach. Undervoltage, overvoltage, underfrequency, and overfrequency relays have been modeled for each generating unit. Distance-relay protection was modeled for transmission system protection. Two types of load-shedding schemes were modeled: underfrequency (frequency-responsive non-firm load shedding) and underfrequency and undervoltage firm load shedding. Several case studies are given to show the impact of protection devices on dynamic simulations. This is useful for simulating cascading outages.

cascading failures↗
DOE OSTI2012

Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions and a new approach for estimating net ecosystem exchange from inventory-based data

While fossil fuel emissions are calculated with relatively high precision, understanding the fate of those emissions with respect to sequestration in terrestrial ecosystems requires data and methods that can reduce uncertainties in the diagnosis of land-based CO2 sinks. The wide range in the land surface flux estimates is related to a number of factors, but most generally because of the different methodologies used to develop estimates of carbon stocks and flux, and the uncertainties inherent in each approach. The alternative approaches to estimating continental scale carbon fluxes that we explored here can be broadly classified as applying a top-down or bottom-up perspective. Top-down approaches calculate land-atmosphere carbon fluxes based on atmospheric budgets and inverse modeling. Bottom-up approaches rely primarily on measurements of carbon stock changes (the inventory approach) or on spatially distributed simulations of carbon stocks and/or fluxes using process-based modeling (the forward modelapproach).

Hayes, D J↗
DOE OSTI2021

Theoretical Control-Centric Modeling for Precision Model-Based Sliding Mode Control of a Hydraulic Artificial Muscle Actuator

Artificial muscles (AMs) typically rely on pneumatic sources of fluid power. The use of hydraulics can increase the power and force to weight and volume ratios of AM actuators. This paper develops a control-centric third-order single-input single-output (SISO) lumped-parameter dynamic model and sliding mode position controller based on Filippov's principle of equivalent dynamics for a braided hydraulic artificial muscle (HAM) actuator. The model predicts the nonlinear behavior of the HAM free contraction and captures the fluid and actuator nonlinear dynamic interactions in addition to the braid deformation. Model simulations are compared to experimental results for quasi-static pressurization, isometric pressurization, and open-loop square wave commands at 0.25, 0.5, and 1 Hz. Experiments of sine wave tracking at 0.25, 0.5, and 1 Hz and continuous square wave tracking at 0.067 Hz are conducted using a sliding mode controller (SMC) derived from the model. The SMC achieves a steady-state error of 6 μm at multiple setpoints within the actuator's 17 mm stroke. Compared to a proportional-integral-derivative (PID) controller, the SMC root-mean-square (RMS) error, mean error, and absolute maximum error are reduced on average by 53%, 61%, and 44%, respectively, demonstrating the benefit of model-based approaches for controlling HAMs.

42 ENGINEERING↗
DOE OSTI2013

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

We use observations of robust scaling behavior in clouds and precipitation to derive constraints on how partitioning of precipitation should change with model resolution. Our analysis indicates that 90-99% of stratiform precipitation should occur in clouds that are resolvable by contemporary climate models (e.g., with 200 km or finer grid spacing). Furthermore, this resolved fraction of stratiform precipitation should increase sharply with resolution, such that effectively all stratiform precipitation should be resolvable above scales of ~50 km. We show that the Community Atmosphere Model (CAM) and the Weather Research and Forecasting (WRF) model also exhibit the robust cloud and precipitation scaling behavior that is present in observations, yet the resolved fraction of stratiform precipitation actually decreases with increasing model resolution. A suite of experiments with multiple dynamical cores provides strong evidence that this `scale-incognizant' behavior originates in one of the CAM4 parameterizations. An additional set of sensitivity experiments rules out both convection parameterizations, and by a process of elimination these results implicate the stratiform cloud and precipitation parameterization. Tests with the CAM5 physics package show improvements in the resolution-dependence of resolved cloud fraction and resolved stratiform precipitation fraction.

atmospheric↗
DOE OSTI2012

CRADA NFE-07-00912: Development of Model Fuels Experimental Engine Data Base & Kinetic Modeling Parameter Sets (Final Report)

The automotive and engine industries are in a period of very rapid change being driven by new emission standards, new types of after treatment, new combustion strategies, the introduction of new fuels, and drive for increased fuel economy and efficiency. The rapid pace of these changes has put more pressure on the need for modeling of engine combustion and performance, in order to shorten product design and introduction cycles. New combustion strategies include homogeneous charge compression ignition (HCCI), partial-premixed combustion compression ignition (PCCI), and dilute low temperature combustion which are being developed for lower emissions and improved fuel economy. New fuels include bio-fuels such as ethanol or bio-diesel, drop-in bio-derived fuels and those derived from new crude oil sources such as gas-to-liquids, coal-to-liquids, oil sands, oil shale, and wet natural gas. Kinetic modeling of the combustion process for these new combustion regimes and fuels is necessary in order to allow modeling and performance assessment for engine design purposes. In this research covered by this CRADA, ORNL developed and supplied experimental data related to engine performance with new fuels and new combustion strategies along with interpretation and analysis of such data and consulting to Reaction Design, Inc. (RD). RD performed additional analysis of this data in order to extract important parameters and to confirm engine and kinetic models. The data generated was generally published to make it available to the engine and automotive design communities and also to the Reaction Design Model Fuels Consortium (MFC).

computational fluid dynamics↗
DOE OSTI2013

Molten Salt Power Tower Cost Model for the System Advisor Model (SAM)

This report describes a component-based cost model developed for molten-salt power tower solar power plants. The cost model was developed by the National Renewable Energy Laboratory (NREL), using data from several prior studies, including a contracted analysis from WorleyParsons Group, which is included herein as an Appendix. The WorleyParsons' analysis also estimated material composition and mass for the plant to facilitate a life cycle analysis of the molten salt power tower technology. Details of the life cycle assessment have been published elsewhere. The cost model provides a reference plant that interfaces with NREL's System Advisor Model or SAM. The reference plant assumes a nominal 100-MWe (net) power tower running with a nitrate salt heat transfer fluid (HTF). Thermal energy storage is provided by direct storage of the HTF in a two-tank system. The design assumes dry-cooling. The model includes a spreadsheet that interfaces with SAM via the Excel Exchange option in SAM. The spreadsheet allows users to estimate the costs of different-size plants and to take into account changes in commodity prices. This report and the accompanying Excel spreadsheet can be downloaded at https://sam.nrel.gov/cost.

14 SOLAR ENERGY↗
DOE OSTI2016

Improving representation of drought stress and fire emissions in climate carbon models: measurements and modeling with a focus on the western USA

The objective of the proposed research was to collect data and develop models to improve our understanding of the role of drought and fire impacts on the terrestrial carbon cycle in the western US, including impacts associated with urban systems as they impacted regional carbon cycles. Using data we collected and a synthesis of other measurements, we developed new ways (a) to evaluate the representation of drought stress and fire emissions in the Community Land Model, (b) to model net ecosystem exchange combining ground level atmospheric observations with boundary layer theory, (c) to model upstream impacts of fire and fossil fuel emissions on atmospheric carbon dioxide observations, and (d) to model carbon dioxide observations within urban systems and at the urban-wildland interfaces of forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A dynamic growth model of vegetative soya bean plants: model structure and behaviour under varying root temperature and nitrogen concentration

A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.

Non-NASA Center↗
NASA NTRS2013

Evaluation of Aerosol Mixing State Classes in the GISS Modele-matrix Climate Model Using Single-particle Mass Spectrometry Measurements

Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 micron, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 micron contain large fractions of organic material, internally-mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.

climate models↗