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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Web-Based Computational Model Builder For Nuclear Energy Advanced Modeling and Simulation (Final Report)

According to the World Nuclear Association, the U.S. is the largest producer of nuclear power worldwide. In fact, the U.S. provides over 30 percent of the world's nuclear generation of electricity. Although few new reactors have been built in the past 30 years, the association anticipates that four to six reactors may be built by 2020. The first of the reactors will be built in response to 16 license applications, which have been completed since 2007, to build 24 additional nuclear reactors. Currently, both government and industry are working to accelerate approval for the construction and design of new nuclear energy plants. The U.S. nuclear industry has already achieved significant developments in the implementation of nuclear power plants due to advancements in refueling, maintenance, and safety systems at current power plants. Meanwhile, changes in government policy, which have occurred since the late 1990s, have provided for noteworthy expansion in nuclear capacity. For example, the Energy Policy Act of 2005 evoked investment in electricity infrastructure such as nuclear power. To design future systems and continue operational improvements at existing U.S. plants, advanced modeling and simulation of nuclear reactors are crucial. We developed a Cloud/Web-based tool, HPCCloud, that enables nuclear energy firms, or other manufacturing and engineering companies, to innovate using advanced modeling and simulation. Through the Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling and Simulation grant, we develop HPCCloud to simplify and democratize advanced modeling and simulation in the nuclear energy industry on a range of nuclear engineering applications. It leverages millions of investment dollars from the Department of Energy's Consortium for Advanced Simulation of Light Water Reactors (CASL) and the Office of Nuclear Energy's research and development in Nuclear Energy Advanced Modeling and Simulation (NEAMS). Our approach simplifies the workflow, alleviates the need for in-house computational science and engineering experts, and lowers the capital investments required for advanced modeling and simulation. The Cloud/Web-based simulation environment guides end-users and developers through the advanced modeling and simulation lifecycle. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where one can save, share, and even publish the full path of data from input to final analyzed results. HPCCloud addresses identified challenges to the nuclear energy industry's use of advanced modeling and simulation. With this unique Cloud/Web-based environment, we enable an ecosystem of synergistic activities, fueling new research and development for nuclear energy. HPCCloud lays the groundwork for commercialization, through customization, technology integration, and advanced research and development services.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Assessment of radiation dose in nuclear cardiovascular imaging using realistic computational models

Purpose: Nuclear cardiology plays an important role in clinical assessment and has enormous impact on the management of a variety of cardiovascular diseases. Pediatric patients at different age groups are exposed to a spectrum of radiation dose levels and associated cancer risks different from those of adults in diagnostic nuclear medicine procedures. Therefore, comprehensive radiation dosimetry evaluations for commonly used myocardial perfusion imaging (MPI) and viability radiotracers in target population (children and adults) at different age groups are highly desired. Methods: Using Monte Carlo calculations and biological effects of ionizing radiation VII model, we calculate the S-values for a number of radionuclides (Tl-201, Tc-99m, I-123, C-11, N-13, O-15, F-18, and Rb-82) and estimate the absorbed dose and effective dose for 12 MPI radiotracers in computational models including the newborn, 1-, 5-, 10-, 15-yr-old, and adult male and female computational phantoms. Results: For most organs, {sup 201}Tl produces the highest absorbed dose whereas {sup 82}Rb and {sup 15}O-water produce the lowest absorbed dose. For the newborn baby and adult patient, the effective dose of {sup 82}Rb is 48% and 77% lower than that of {sup 99m}Tc-tetrofosmin (rest), respectively. Conclusions: {sup 82}Rb results in lower effective dose in adults compared to {sup 99m}Tc-labeled tracers. However, this advantage is less apparent in children. The produced dosimetric databases for various radiotracers used in cardiovascular imaging, using new generation of computational models, can be used for risk-benefit assessment of a spectrum of patient population in clinical nuclear cardiology practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

FY-24 Progress on Computational Modeling of the Water Based NSTF

This report summarizes the computational modeling of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) completed in FY24. This year’s modeling campaign focuses on the continual testing of the RELAP5 model against experimental data. Several fault cases were simulated with the RELAP5 model in FY23 to study the accuracy of the model under complex flow conditions. Similarly, in FY24, a case is simulated where the chimney outlet is throttled with a valve while the flow is undergoing two-phase oscillations. The purpose of this case is to study the effects of increasing pressure drop in the two-phase region on the system behavior. Even though the model is able to capture the experimental data qualitatively, it overpredicts the pressure drops experienced by the flow in the two-phase regime. Nevertheless, the model and the experiment show that oscillations are stabilized with increased pressure drop in the two-phase region.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Computational modeling of proton acceleration with multi-picosecond and high energy, kilojoule, lasers

Here, we use computational modeling to investigate proton beam generation from kilojoule, multi-picosecond laser pulses pertinent to several recently commissioned, large-scale laser facilities. The dependencies of proton acceleration on electron source parameters including pulse duration, temperature, and flux are independently and systematically evaluated. Proton acceleration is found to depend not only on the source size and peak temperature of the injected electrons but also on the rate of increase for a more physical time-varying temperature. Simulations of a 10 ps, sub-relativistic intensity (8 × 10 17 W/cm 2 ) at 1 μm wavelength laser pulse show that energetic electrons generated within the expanding under-dense laser-produced plasma sustain the proton acceleration for ~20 ps. This results in 15 MeV energy gain of the protons, well above what would be predicted based on conventional intensity scalings or what has been observed with shorter pulses. Using this prolonged acceleration, a scheme consisting of a 1 ps and 10 ps double pulse is shown to further boost proton maximum energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Multi-scale computational modeling of residual stress in selective laser melting with uncertainty quantification

Selective laser melting (SLM) is a powder-based additive manufacturing technique which creates parts by fusing together successive layers of powder with a laser. The quality of produced parts is highly dependent on the proper selection of processing parameters, requiring significant testing and experimentation to determine parameters for a given machine and material. Computational modeling could potentially be used to shorten this process by identifying parameters through simulation. However, simulating complete SLM builds is challenging due to the difference in scale between the size of the particles and laser used in the build and the size of the part produced. Often, continuum models are employed which approximate the powder as a continuous medium to avoid the need to model powder particles individually. While computationally expedient, continuum models require as inputs effective material properties for the powder which are often difficult to obtain experimentally. Building on previous works which have developed methods for estimating these effective properties along with their uncertainties through the use of detailed models, this work presents a part scale continuum model capable of predicting residual thermal stresses in an SLM build with uncertainty estimates. Model predictions are compared to experimental measurements from the literature.

42 ENGINEERING↗
DOE OSTI2022

People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Mechanistic insights into metal, nitrogen doped carbon catalysts for oxygen reduction: progress in computational modeling

We report metal and nitrogen doped carbon materials (denoted as M–N–C) synthesized through high-temperature pyrolysis have been found to exhibit activity for oxygen reduction reaction (ORR) approaching that of Pt and electrochemical stability higher than previous MN 4 -containing macrocyclic molecular catalysts. Tremendous efforts have thus been devoted to the advancement of M–N–C catalysts as an economical alternative to Pt-based catalysts for proton exchange membrane fuel cell cathodes with a focus on simultaneously improving activity and stability. To this end, novel computational modeling techniques have been developed and applied to acquire knowledge crucial for accelerating the pace of M–N–C catalyst development. In this review, recent progress in computational method development, as well as the predictions of chemical structure of active sites, reaction pathways, ORR kinetics, and catalyst stability in electrochemical environments, are critically surveyed. Moreover, the crucial role of computational modeling to elucidate the functional mechanism of M–N–C catalysts for ORR in acid media and enable rational design of M–N–C catalysts is discussed with a visionary outlook for the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Computational modeling of nanoscale and microscale particle deposition, retention and dosimetry in the mouse respiratory tract

Comparing effects of inhaled particles across rodent test systems and between rodent test systems and humans is a key obstacle to the interpretation of common toxicological test systems for human risk assessment. These comparisons, correlation with effects and prediction of effects, are best conducted using measures of tissue dose in the respiratory tract. Differences in lung geometry, physiology and the characteristics of ventilation can give rise to differences in the regional deposition of particles in the lung in these species. Differences in regional lung tissue doses cannot currently be measured experimentally. Regional lung tissue dosimetry can however be predicted using models developed for rats, monkeys, and humans. A computational model of particle respiratory tract deposition and clearance was developed for BALB/c and B6C3F1 mice, creating a cross-species suite of available models for particle dosimetry in the lung. Airflow and particle transport equations were solved throughout the respiratory tract of these mice strains to obtain temporal and spatial concentration of inhaled particles from which deposition fractions were determined. Particle inhalability (Inhalable fraction, IF) and upper respiratory tract (URT) deposition were directly related to particle diffusive and inertial properties. Measurements of the retained mass at several post-exposure times following exposure to iron oxide nanoparticles, micro- and nanoscale C60 fullerene, and nanoscale silver particles were used to calibrate and verify model predictions of total lung dose. Interstrain (mice) and interspecies (mouse, rat and human) differences in particle inhalability, fractional deposition and tissue dosimetry are described for ultrafine, fine and coarse particles.

Lung deposition, nanosized particles, particle↗
DOE OSTI2019

A computational model for exploring particle acceleration during reconnection in macroscale systems

A new computational model suitable for exploring the self-consistent production of energetic electrons during magnetic reconnection in macroscale systems is presented. The equations are based on the recent discovery that parallel electric fields are ineffective drivers of energetic particles during reconnection so that the kinetic scales which control the development of such fields can be ordered out of the equations. The resulting equations consist of a magnetohydrodynamic (MHD) backbone with the energetic component represented by macro-particles described by the guiding center equations. Crucially, the energetic component feeds back on the MHD equations so that the total energy of the MHD fluid and the energetic particles is conserved. The equations correctly describe the firehose instability, whose dynamics plays a key role in throttling reconnection and in controlling the spectra of energetic particles. The results of early tests of the model, including the propagation of Alfvén waves in a system with pressure anisotropy and the growth of firehose modes, establish that the basic algorithm is stable and produces reliable physics results in preparation for further benchmarking with particle-in-cell models of reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Review of Computational Models for the Flow of Milled Biomass Part I: Discrete-Particle Models

Biomass is a renewable and sustainable energy resource. Current design of biomass handling and feeding equipment leverage both experiments and numerical modeling. This paper reviews the state-of-the-art discrete element methods (DEM) for the flow of milled biomass (Part I), accompanied by a comprehensive review on continuum-based computational models (Part II). The present review on DEM is primarily focused on the features and suitability of various particle shape models for different types of milled biomass because particle shape is the predominant attribute controlling the flow behavior of complex-shaped granular material. The general strengths and weaknesses in the applicability of those models for the milled biomass modeling are summarized. In particular, comments are provided to balance the numerical model capabilities and the computational cost for the development of DEM models. To our best knowledge, this is the first-of-its-kind review on DEM specifically for biomass. Our study indicates that the current DEM models require further development, calibration, and validation based on a deep understanding of biomass particle contact mechanics and experimental data support before they can be reliably used for predictive simulations in handling and feeding systems.

42 ENGINEERING↗
DOE OSTI2022

Computational Modeling of Battery Materials

This chapter provides a broad overview of the various computational modeling techniques used to gain fundamental insights into coupled electrochemical processes that occur in battery materials at electronic-to-mesoscopic scales. Furthermore, representative successes of these techniques in modeling electrodes, electrolytes, and electrode-electrolyte interfaces are highlighted to establish the current state-of-the-art in the field.

25 ENERGY STORAGE↗
DOE OSTI2019

Developing High-Performance Computing Model of Vapor Transition Through Advanced Membranes for Applications in 7AC Liquid Desiccant Air Conditioners

This poster for the 2019 Advanced Manufacturing Office Peer Review covers the high-performance computing model development for applications in Liquid Desiccant Air Conditioners. Conventional compressor-based cooling has undergone incremental changes over the past 100 years. Further improvements in efficiency require evermore complex systems, especially under humid conditions. Microporous membranes offer unique opportunities for efficient humidity control in buildings using an absorbent desiccant solution, but membranes are not designed for this purpose. This project used molecular dynamic (MD) simulations to determine the effect of membrane properties on important metrics for these air-conditioning applications, focusing on the membrane properties at the membrane/liquid/air interface. Improved membranes can enable smaller, more durable, and less costly designs for these membrane air conditioning systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Computing model independent perturbations in dark energy and modified gravity

We present a methodology for computing model independent perturbations in dark energy and modified gravity. This is done from the Lagrangian for perturbations, by showing how field content, symmetries, and physical principles are often sufficient ingredients for closing the set of perturbed fluid equations. The fluid equations close once ''equations of state for perturbations'' are identified: these are linear combinations of fluid and metric perturbations which construct gauge invariant entropy and anisotropic stress perturbations for broad classes of theories. Our main results are the proof of the equation of state for perturbations presented in a previous paper, and the development of the required calculational tools.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite

Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.

Computational Modeling of Molten Salt Infiltration↗
DOE OSTI2018

Formulation and validation of a computational model for a dilute biomass slurry undergoing rotational mixing

In this paper we develop a computational model for the mixing and transport of a dilute biomass slurry. The objective was to create a sufficiently simple and efficient model for biomass transport that can be coupled with reaction models for the study of conversion of cellulosic biomass into fermentable sugars. Our target system is 5%-by-mass ..alpha..-cellulose, which is our proxy for more complex lignocellulosic biomass. In the authors' previous work, an experimental investigation with ..alpha..-cellulose under two vane-mixer configurations showed a bifurcation between a settling regime, for which settling effects dominate, and a suspended regime, for which solids are mostly suspended. Here, a mixed-fluid model was chosen, for which the model for the mixture-velocity field is the incompressible Navier-Stokes equations under the Boussinesq approximation for buoyancy. Solids transport includes solids motion due to diffusion, settling, advection, and shear. Comparison of simulated and experimental results show good agreement in the suspended regime, and in capturing the bifurcation rate. While the model captured well the distribution of solids in the settling regime, the model was incapable of capturing the high torque values seen in experiments with vanishing mixer rotation rate.

09 BIOMASS FUELS↗
DOE OSTI2021

Computational Modeling of Photovoltaic Mini-Modules Undergoing Accelerated Stress Testing

A finite element model of a four-cell photovoltaic mini-module was developed and compared to experimental results from an accelerated stress test protocol in order to validate that computational models can accurately represent their physical counterparts when subjected to mechanical loading and to assess mini-module representativeness against full scale photovoltaic modules. Deflected shapes across the simulated mini-modules were compared to measured mini-module shapes when subjected to various pressure loads. Displaced mini-module shape results constrained to the experimental protocols of 0.4 mm and 1.1 mm of displacement at the mini-module center were compared to experimental results of full-size modules subjected to module qualification test load levels of 1.0 kPa and 2.4 kPa, to assess if the bending of mini-modules was representative of full-sized modules under the load. Temperature cycling was incorporated into the model to simulate the impacts of stress due to thermal expansion of the backsheet and cells. A preliminary uncertainty analysis was performed to show how variations in material properties and geometric parameters change the simulation results.

computational modeling↗