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At least 757 records · Page 42

All sources NASA NTRS DOE OSTI

DOE OSTI2020

A Performance analysis of the Claridge-Culp-Liu dehumidification process: A novel approach for drying moist air based on membrane separation, vacuum compression and sub-atmospheric condensation

This article covers a basic model for analyzing the performance of the Claridge-Culp-Liu dehumidification process. The fundamental process efficiency limit for dehumidification is close to COP Carnot , but for the eight dehumidification cases examined, the limiting or ideal energy use required is 26% to 56% that of a Carnot condensing system as shown in an earlier paper. The model presented in this paper is used to show the membrane system performance reduction caused by finite membrane area, finite water vapor permeance, non-zero air permeance, non-zero system air pressure drop, non-ideal compressors, vacuum pumps, and condensers. The performance of a “conservative” membrane system based on the use of existing components is computed for eight specific conditions along with that of a “target” system that assumes expected component performance after additional future component development. The “conservative” membrane system would use 36% to 66% as much energy as a system with a COP=7 chiller to produce the same dehumidification for the eight cases examined while the “target” system would use 15% to 40% the energy of a system with a COP=7 chiller. In addition to the significant energy reduction over conventional technology, the membrane system offers the advantages of: 1) no HFC refrigerant use; 2) direct isothermal control over humidity ratio setpoint; 3) maximum capacity occurs at design conditions; and 4) system generates pure water extracted from air as a by-product.

42 ENGINEERING↗

DOE OSTI2025

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

DOE OSTI2024

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

DOE OSTI2022

Preliminary Safety Analysis for a 400-kW Molten Salt Nuclear Battery

The Molten Salt Nuclear battery (MsNB) is a microreactor based on technology developed and operated at Oak Ridge National Laboratory in the 1960s [1]. But the MsNB has been simplified by removing pumps and valves for improved reliability and safety. The MsNB can safely provide up to 10 MWe of power for up to 10 years and potentially it can be transported by air, truck, and rail thanks due to to its small footprint. A computer model has been developed to represent a prototypical 400-kW MsNB using the ANL system code SAM [2]. The model has been used to produce a reactor thermal-hydraulic performance map and perform analysis of unprotected loss of heat sink accident scenario.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

BASS: An R Package for Fitting and Performing Sensitivity Analysis of Bayesian Adaptive Spline Surfaces

In this work, we present the R package BASS as a tool for nonparametric regression. The primary focus of the package is fitting fully Bayesian adaptive spline surface (BASS) models and performing global sensitivity analyses of these models. The BASS framework is similar to that of Bayesian multivariate adaptive regression splines (BMARS) from Denison, Mallick, and Smith (1998), but with many added features. The software is built to efficiently handle significant amounts of data with many continuous or categorical predictors and with functional response. Under our Bayesian framework, most priors are automatic but these can be modified by the user to focus on parsimony and the avoidance of overfitting. If directed to do so, the software uses parallel tempering to improve the reversible jump Markov chain Monte Carlo (RJMCMC) methods used to perform inference. We discuss the implementation of these features and present the performance of BASS in a number of analyses of simulated and real data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Effect of Internal Structure on Warpage in a Large-Scale Additive Manufacturing Process With Bio-Derived Composites

Extrusion-based large-format additive manufacturing (LFAM) often results in unintended deformation and failures due to thermal residual stress between layers. This LFAM involves a hot molten polymer deposited on a previously deposited and cooled layer, generating a temperature mismatch between the layers. The temperature discrepancy causes a thermal contraction mismatch, generating thermal residual stress. Due to the residual stress, printed structures experience warpage and delamination Therefore, understanding the heat distribution behavior is essential to preventing undesired deformation and failures. The goal of this study is to investigate the effect of infill patterns on heat distribution and deformation in an LFAM system. Wood fiber-reinforced polylactic acid was used as a sustainable and low-cost reinforcement material. A numerical model was developed to predict the temperature and deformation field with thermo-mechanical properties, which were measured by a dynamic mechanical analysis and a thermal expansion test. Simulations were performed on a box geometry with three different infill patterns. The simulation model was verified with temperature data gathered from an infrared camera. The results show good agreement between predicted and measured temperature profiles. The developed simulation model was applied to a roof tray with different infill patterns for a case study. We found that the different thermal mass distributions resulting from the various infill patterns affected the heat distribution and deformation. These findings contribute to a better understanding of the thermal and mechanical behavior of LFAM.

Jo, Eonyeon↗

DOE OSTI2025

The SAS4A/SASSYS-1 Version 5.8 Safety Analysis Code System

SAS4A/SASSYS-1 is a software simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced nuclear reactors. Detailed, mechanistic models of steady-state and transient thermal, hydraulic, kinetic, and mechanical phenomena are employed to describe the response of the reactor core, the reactor primary and secondary coolant loops, the reactor control and protection systems, and the balance-of-plant to accidents caused by changes in coolant flow, loss of heat rejection, or reactivity insertion. The consequences of single and double-fault accidents can be modeled, including fuel and coolant heating, fuel and cladding mechanical behavior, core reactivity feedbacks, coolant loop performance including natural circulation, and decay heat removal. Analyses are typically terminated upon demonstration of reactor and plant shutdown to permanently coolable conditions, or upon violation of design basis margins. The objective of the analysis is to quantify accident consequences as measured by the transient behavior of system performance parameters, such as fuel and cladding temperatures, reactivity, and cladding strain. Originally developed for analysis of sodium cooled reactors with oxide fuel clad by stainless steel, the models were subsequently extended and specialized to metallic fuel clad with advanced alloys and to several other coolant options, including lead, LBE, and water.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Stabilized Hyperfoam Modeling of the General Plastics EF4003 (3 PCF) Flexible Foam

Constitutive model parameterizations for the General Plastics EF4003 low density 3 pound per cubic foot are needed for design and qualification purposes in normal and abnormal mechanical simulations. The material is expected to be deformed in two ways: first during preloading, and second under impact conditions of the system (transient dynamic). All analyses are to be performed at room temperature. The goal is to provide the analysis community a robust constitutive model parameterization to represent the compression behavior of the EF4003 foam from small deformations up to massive compressive deformations when the foam is densifying. It is worth noting the EF4003 exhibits anisotropy in its stress-strain behavior between the rise and transverse directions (See figure 2.8c-d) as well as plateau behavior that is very likely to cause material stability issues, due to the buckling transition, (and has historically done so) when using Sandia’s current workhorse models for flexible foams, Hyperfoam and Flex Foam. A Stability-informed Hyperfoam parameterization procedure is developed and executed to calibrate a hyperfoam model for the EF4003 room temperature, transversely loaded data. A rise orientation parameterization was not attempted due to localization in the experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Machine learning for surrogate process models of bioproduction pathways

Technoeconomic analysis and life-cycle assessment are critical to guiding and prioritizing bench-scale experiments and to evaluating economic and environmental performance of biofuel or biochemical production processes at scale. Traditionally, commercial process simulation tools have been used to develop detailed models for these purposes. However, developing and running such models can be costly and computationally intensive, which limits the degree to which they can be shared and reproduced in the broader research community. This study evaluates the potential of an automated machine learning approach to develop surrogate models based on conventional process simulation models. The analysis focuses on several high-value biofuels and bioproducts for which pathways of production from biomass feedstocks have been well-established. The results demonstrate that surrogate models can be an accurate and effective tool for approximating the cost, mass and energy balance outputs of more complex process simulations at a fraction of the computational expense.

09 BIOMASS FUELS↗

DOE OSTI2021

Pilot Testing of a Modular Oxygen Production System Using Oxygen Binding Adsorbents (Final Report)

In this project, RTI and Air Liquide have focused on the development of innovative oxygen separation materials and technologies based on reversibly binding of oxygen to enable smaller and cheaper air separations. In alignment with that object the team has had multiple achievements to advance the technology including: Synthesized and characterized novel M-CoSalen (RTIO2Sorb-1) material which showed a dynamic oxygen adsorption capacity in excess of 1wt%. Developed synthesis routes for RTIO2Sorb-1 with commercially relevant techniques and produced batches of 0.25kg and over 4 kg of total synthesis. Synthesized and characterized extrudate forms of the RTIO2Sorb-1 with relevant crush strength and maintained dynamic oxygen adsorption capacity in near 1wt%. Developed techniques for forming structured beds in fiber shapes with conventional materials. Developed a model for O 2 sorption processes to analyze various bed configurations and cycle parameters. Studied classic O 2 solid sorbents reported in the literature to learn oxygen binding mechanisms. Design a 10 kg/day O 2 VPSA pilot system with 2 or 4-bed operation. Completed a techno-economic analysis based on the experimental results and modeling. The overall objective of the project was to design, fabricate, and test a modular O 2 production system and perform a techno-economic analysis (TEA) after testing to determine the cost-benefit of the advanced modular air separation system. The goals of this technology development project were to achieve a bed-size factor (BSF) of less than 600 lb-adsorbent/TPD O 2 (ton/day O 2 ) (as compared with the state-of-the-art BSF of 850), and O 2 -purity greater than 95% at a cost that is projected to be equivalent or lower than the current state of the art (SOTA), commercially available large-scale cryogenic air separation systems. To achieve these goals and objective, the project team executed on (1) oxygen binding adsorbent optimization and scale up, (2) adsorbent material formation process studies to form the adsorbent material into structured beds for rapid pressure swing adsorption (PSA) cycles with low pressure drop, fast mass transfer, and low attrition, (3) cycle development studies to optimize the PSA process, and (4) develop simulation tools for rapid cycle modeling and numerical evaluation/optimization.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Simulation of Inelastic Neutron Scattering Spectra Directly from Molecular Dynamics Trajectories

Inelastic neutron scattering (INS) is a widely used technique to study atomic and molecular vibrations. With the increasing complexity of materials and thus the INS spectra, being able to simulate the spectra from various atomistic models becomes an essential step and also a major bottleneck for INS data analysis. The conventional approach using density functional theory and lattice dynamics often falls short when the materials of interest are complex (e.g., defective, disordered, heterogeneous, amorphous, large-scale), for which molecular dynamics driven by an interatomic force field is a more common approach. In this paper, we demonstrate a method to directly convert molecular dynamics trajectories into simulated INS spectra, including not only fundamental but also higher order excitations. In this work, the results are compared with data collected on various representative samples from different neutron spectrometers. This development will open great opportunities by providing the key tool to perform in-depth analysis of INS data and to validate and optimize computer models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Technical and Regulatory Aspects of Integrating Safety and Security at Nuclear Power Plants

This paper provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. It describes how a user could integrate their plant-specific FOF models with safety mitigation actions in EMRALD, and with thermal-hydraulic tools, such as MAAP. The work performed in this paper is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are presented for dissemination. No plant’s sensitive information is included in this paper. The discussion shows examples of insights that can be obtained from the proposed methodology.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗

DOE OSTI2022

Combined Normal and Disruption, Electromagnetic Transient, Thermal, and Structural Analysis of COMPASS Upgrade

We report that COMPASS Upgrade is a replacement for the COMPASS device at the Institute of Plasma Physics (IPP) of the Czech Academy of Sciences. It is a cryogenic copper machine with a major radius of 0.89 m, with 5 T at the plasma centerline and 2-MA plasma current. It is intended to develop ITER relevant plasma densities and high power fluxes in the divertor region. The entire vacuum vessel is planned to reach 500 °C. The COMPASS-U TF coil is a bitter plate-like design with radial conductor plates that extend the width of the TF inner leg. Currents redistribute radially based on resistive and inductive effects. This necessitates an electromagnetic (EM) transient analysis of the coil current distribution. For copper coils like COMPASS Upgrade, the solution must be coupled with a thermal solution to properly include the temperature-dependent resistive effects. The EM transient solution includes the TF magnetic loads, and a stress pass on the results produces in-plane loads. The EM solution chosen requires inclusion of all the conducting and nonconducting regions surrounding the TF coil. With the TF current distribution solved, the addition of the poloidal coils and resulting background fields allows the determination of the out-of-plane loads. Integration of the Joule heating produced from the EM solution produces temperature distributions throughout the shot, which can be read in to a structural pass to include thermal stresses in the evaluation. This is true of both TF and PF temperature prediction with appropriate packing fractions. Currents in the PF coils, with computed background fields, produce Lorentz loads. Time transients of the PF currents produce startup eddy currents in the structures included in the model; inclusion of the vessel and other passive structures allows these to be included in a stress pass. The EM transient solution includes all the elements needed for a disruption analysis with prescribed motions and quench of the plasma. From a model originally intended to simulate current diffusion in the TF coil, the analysis can be refined to be used to predict the performance of most of the components of the tokamak or provide boundary conditions for more detailed submodels. In this article, the use of the current diffusion model for bounding assessments of the COMPASS Upgrade TF, PF, vessel, external structure, and disruption analyses will be presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

An analytic asymmetric-piston model for the impact of mode-1 shell asymmetry on ICF implosions

For many years, low mode asymmetry in inertially confined fusion (ICF) implosions has been recognized as a potential performance limiting factor, but analysis has been limited to using simulations and searching for data correlations. In this paper, an analytically solvable model based upon the simple picture of an asymmetric piston is presented. Asymmetry of the shell driving the implosion, as opposed to asymmetry in the hot-spot, is key to the model. The model provides a unifying framework for the action of mode-1 shell asymmetry and the resulting connections between various diagnostic signatures. A key variable in the model is the shell asymmetry fraction, f, which is related to the areal density variation of the shell surrounding the hot-spot. It is shown that f is simply related to the observed hot-spot mode-1 velocity and to the concept of residual energy in an implosion. The model presented in this paper yields explicit expressions for the hot-spot diameter, stagnation pressure, hot-spot energy, inertial confinement-time, Lawson parameter, hot-spot temperature, and fusion yield under the action of mode-1 asymmetry. Agreement is found between the theory scalings when compared to ICF implosion data from the National Ignition Facility and to large ensembles of detailed simulations, making the theory a useful tool for interpreting data. The theory provides a basis for setting tolerable limits on asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Cosmic shear in harmonic space from the Dark Energy Survey Year 1 Data: compatibility with configuration space results

ABSTRACT We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the metacalibration catalogue and perform a likelihood analysis within the framework of CosmoSIS. We set scale cuts based on baryonic effects contamination and model redshift and shear calibration uncertainties as well as intrinsic alignments. We adopt as fiducial covariance matrix an analytical computation accounting for the mask geometry in the Gaussian term, including non-Gaussian contributions. A suite of 1200 lognormal simulations is used to validate the harmonic space pipeline and the covariance matrix. We perform a series of stress tests to gauge the robustness of the harmonic space analysis. Finally, we use the DES-Y1 pipeline in configuration space to perform a similar likelihood analysis and compare both results, demonstrating their compatibility in estimating the cosmological parameters S8, σ8, and Ωm. We use the DES-Y1 metacalibration shape catalogue, with photometric redshifts estimates in the range of 0.2−1.3, divided in four tomographic bins finding σ8(Ωm/0.3)0.5 = 0.766 ± 0.033 at 68 per cent CL. The methods implemented and validated in this paper will allow us to perform a consistent harmonic space analysis in the upcoming DES data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides . High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.

09 BIOMASS FUELS↗

DOE OSTI2025

Quasisteady evolution of fast neutrino-flavor conversions

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions’ effects in the theoretical modeling of CCSN and BNSM. Some phenomenological schemes have shown good performance in approximating asymptotic states of fast neutrino-flavor conversions (FFCs), known as one of the collective neutrino oscillation modes induced by neutrino self-interactions. However, a recent study showed that they would yield qualitatively different asymptotic states of FFC if the neutrino number is forced to evolve. It is not yet fully understood why the canonical phenomenological models fail to predict asymptotic states. In this paper, we perform detailed investigations through numerical simulations and then provide an intuitive explanation with a quasihomogeneous analysis. Based on the analysis, we propose a new phenomenological model, in which the quasisteady evolution of FFCs is analytically determined. The model also allows us to express the convolution term of spatial wave number as a concise form, which corresponds to useful information on analyses for the nonlinear feedback from small-scale flavor conversions to large-scale ones. Furthermore, our model yields excellent agreement with numerical simulations, which lends support to our interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗