SEARCH · Engineering Papers

Results for “parametric analysis”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Bayesian Calibration of Stochastic Agent Based Model via Random Forest

Agent-based models (ABM) provide an excellent framework for modeling outbreaks and interventions in epidemiology by explicitly accounting for diverse individual interactions and environments. However, these models are usually stochastic and highly parametrized, requiring precise calibration for predictive performance. When considering realistic numbers of agents and properly accounting for stochasticity, this high-dimensional calibration can be computationally prohibitive. This paper presents a random forest-based surrogate modeling technique to accelerate the evaluation of ABMs and demonstrates its use to calibrate an epidemiological ABM named CityCOVID via Markov chain Monte Carlo (MCMC). The technique is first outlined in the context of CityCOVID's quantities of interest, namely hospitalizations and deaths, by exploring dimensionality reduction via temporal decomposition with principal component analysis (PCA) and via sensitivity analysis. The calibration problem is then presented, and samples are generated to best match COVID-19 hospitalization and death numbers in Chicago from March to June in 2020. Further, these results are compared with previous approximate Bayesian calibration (IMABC) results, and their predictive performance is analyzed, showing improved performance with a reduction in computation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

HERO CarbonSAFE Phase 2 Project in the Columbia River Basalt Group

The Hermiston, Oregon Basalt CarbonSAFE Phase II project (HERO CarbonSAFE) seeks to accelerate the deployment of commercial carbon dioxide (CO2) storage projects in basaltic rocks. Basalt CO2 storage has several advantages to conventional saline storage reservoirs including 1. The potential for rapid mineralization of CO2, 2. Associated decreases in pressure and CO2 migration risks, 3. Reduced long-term monitoring requirements with respect to plume tracking, 4. Widespread geographic distribution and, 5. Large storage potential due to thickness, porosity, and CO2 interactions with basalt. And for locations such as the Pacific Northwest, Hawaii, Iceland, India and Japan, basalts may offer the only economically feasible option for local CO2 storage. However, there are limited field-scale assessments of CO2 storage in basalt, and current carbon capture utilization and storage (CCUS) permitting and regulatory frameworks were developed for conventional saline reservoirs. HERO CarbonSAFE is designed to address research gaps and uncertainties associated with basalt storage. Specifically, the project will assess the feasibility of CO2 injection in the deep layered basalts, long-term storage (mineralization), practical approaches for large-scale implementation (50+ million metric tons of CO2 over 30 years), lithology-specific risks, and the technoeconomic potential for CO2 storage in basalts. The HERO CarbonSAFE project will assess feasibility of developing a commercial-scale (50+ million metric tons of CO2) geological storage complex within the Columbia River Basalt Group (CRBG), a layered continental flood basalt complex that underlies Calpine’s natural gas-fired Hermiston Power Project (HPP) in Hermiston, OR (Figure 1). Under this 2-year CarbonSAFE Phase II project, the HERO team will conduct a data acquisition campaign that includes drilling a stratigraphic well to a total depth of ~1,500 m into the thick layered basalts proximal to HPP. A comprehensive well logging and hydrologic testing program will be augmented with new core collected from flow zones and sealing units, and comprehensive laboratory testing to help refine the kinetic rates of mineralization. The newly acquired information will be integrated with existing data from regional wells to correlate basalt injection zone properties to develop storage hub/commercial-scale models. Using these models, the project team will evaluate injection scenarios to define the technical and economic potential for storing a minimum of 50 million metric tons of CO2 over a 30-year period, along with a robust sensitivity analysis on key parameters governing reservoir viability for sustainable injection over a commercial project lifetime. Specific technical objectives of HERO are: (1) assessing the reservoir response of a series of stacked layered reservoir flowtop sequences occurring in this area of the CRBG to commercial-scale injection volumes; (2) extending prior efforts by the project team to characterize the deep layered basalts encountered in regional studies, to leverage prior investments by U.S. Department of Energy’s (DOE) Carbon Storage program; (3) leveraging DOE’s mineralization characterization efforts to advance model parametrization for commercial scale injection of CO2 in basalts; (4) conducting risk assessments associated with scaling up to commercial storage hub injection goals, while validating DOE’s National Risk Assessment Partnership (NRAP) tools, to identify potential constraints that would prevent the CRBG from serving as a commercial-scale storage complex; (5) developing mitigation plans to address identified risks; (6) developing a commercial-scale injection and monitoring, verification and accounting (MVA) strategy; (7) utilizing computational models to define and minimize, if possible, the Area of Review (AoR) under Class VI regulations; and (8) developing a robust CO2 management strategy for CRBG that also considers a regional source/sink approach that is responsive to stakeholder needs and industrial demand. Specific institutional objectives are: (1) identifying and developing plans to mitigate the nontechnical challenges associated with the build-out of a commercial-scale storage complex within the CRBG with integrated CO2 sources; (2) implementing the community outreach plan; (3) conducting regulatory research, including a survey of issues related to pore space ownership, MVA and long-term assurance of mineralization-based storage, to support an eventual application for a UIC Class VI permit; (4) advancing the project’s plan for CO2 liability management; and (5) continuing to refine and update the project’s economic model. The final objective is the preparation of a comprehensive Site Characterization Plan that draws upon the technical and institutional feasibility assessments to prepare the project for future commercialization efforts.

58 GEOSCIENCES↗

DOE OSTI2021

Assessing the Energy Resilience of Office Buildings: Development and Testing of a Simplified Metric for Real Estate Stakeholders

Increasing concern over higher frequency extreme weather events is driving a push towards a more resilient built environment. In recent years there has been growing interest in understanding how to evaluate, measure, and improve building energy resilience, i.e., the ability of a building to provide energy-related services in the event of a local or regional power outage. In addition to human health and safety, many stakeholders are keenly interested in the ability of a building to allow continuity of operations and minimize business disruption. Office buildings are subject to significant economic losses when building operations are disrupted due to a power outage. We propose “occupant hours lost” (OHL) as a means to measure the business productivity lost as the result of a power outage in office buildings. OHL is determined based on indoor conditions in each space for each hour during a power outage, and then aggregated spatially and temporally to determine the whole building OHL. We used quasi-Monte Carlo parametric energy simulations to demonstrate how the OHL metric varies due to different building characteristics across different climate zones and seasons. The simulation dataset was then used to develop simple regression models for assessing the impact of ten key building characteristics on OHL. The most impactful were window-to-wall ratio and window characteristics. The regression models show promise as a simple means to assess and screen for resilience using basic building characteristics, especially for non-critical facilities where it may not be viable to conduct detailed engineering analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Expansion-history preferences of DESI DR2 and external data

We explore the origin of the preference of Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) baryon acoustic oscillation measurements and external data from cosmic microwave background (CMB) and type Ia supernovae (SNIa) that dark energy behavior departs from that expected in the standard cosmological model with vacuum energy (Λ ⁢CDM). In our analysis, we allow a flexible scaling of the expansion rate with redshift that nevertheless allows reasonably tight constraints on the quantities of interest, and adopt and validate a simple yet accurate compression of the CMB data that allows us to constrain our phenomenological model of the expansion history. We find that data consistently show a preference for a 3%–4% increase in the expansion rate at 𝑧 ≃ 0.7 relative to that predicted by the standard Λ⁢ CDM model, in excellent agreement with results from the less flexible (𝑤 0 ,𝑤 𝑎 ) parametrization which was used in previous analyses. Even though our model allows a departure from the best-fit Λ⁢ CDM model at zero redshift, we find no evidence for such a signal. We also find no evidence (at greater than 1⁢𝜎 significance) for a departure of the expansion rate from the Λ ⁢CDM predictions at higher redshifts for any of the data combinations that we consider. Altogether, our results strengthen the robustness of the findings using the combination of DESI, CMB, and SNIa data to dark-energy modeling assumptions.

Cosmological parameters↗

DOE OSTI2025

Towards stabilization of pressurized oxy-coal diffusion flames

Designing an effective burner is vital for the development of pressurized oxy-fuel combustion technologies. Turbulent jet diffusion burners are adopted for the pressurized oxy-combustor in this research and a bluff-body is employed to create a recirculation zone to stabilize the flame in pressurized oxy-combustor. The objective of this numerical work is to perform a systematic analysis of the characteristics of this pressurized non-premixed flame. Specifically, a 15-bar POFC combustor of power 100 kWth is modeled employing the Ansys FLUENT commercial platform, using Reynolds-averaged Navier-Stokes (RANS) modeling. The present computational work focuses on identifying the aerothermodynamic features of the isothermal and reacting flow with a disk-shape bluff-body. Results show that fuel-oxidizer stream momentum ratio has great impacts on the temperature profile of the down-fired, co-axial, pressurized oxy-coal, diffusion flame. Parametric study of the width of the burner tip identifies an optimal range for this pressurized burner.

Li, Lei↗

DOE OSTI2020

A multi-dimensional dataset for two-phase instability in low pressure natural circulation based on direct transient local measurement

Thermal hydraulic instability can challenge the control and the safety of nuclear reactors. This experimental research captures and investigates the instability in a low-pressure (1–10 atmospheres) natural circulation loop with an adiabatic chimney installed above the heated section. Direct transient local measurement of two-phase flow is performed at multiple axial locations along the flow channel with thermocouples and conductivity probes traversed by customized high-precision mechanisms. Based on the periodicity of oscillations, a post-processing method is proposed to align the data captured non-simultaneously to reconstruct the instability behavior in one representative period. The averaging operation over multiple oscillation cycles is performed to reduce the random errors. Cyclic phenomena are clearly demonstrated by the post-processed data, and rapid void fraction change induced by the flashing is observed to be significant in the driving mechanism for low pressure oscillations. Parametric effects of inlet subcooling, heat flux, inlet flow restriction and system pressure are studied within the experiment range, and qualitative results are explained and compared with existing literature. The ratio between the oscillation period and the travelling time of the fluid particle through the test section is compared with the theoretical value for the density wave oscillation. The new dataset contains directly measured transient multi-dimensional two-phase data along the flow channel for natural circulation under density wave oscillations. The generated dataset is valuable for the validation of system analysis codes and CFD codes in the simulation of natural circulation phenomena and dynamic two-phase flow.

42 ENGINEERING↗

DOE OSTI2020

First Results on Dark Matter Substructure from Astrometric Weak Lensing

Low-mass structures of dark matter (DM) are expected to be entirely devoid of light-emitting regions and baryons. Precisely because of this lack of baryonic feedback, small-scale substructures of the Milky Way are a relatively pristine testing ground for discovering aspects of DM microphysics and primordial fluctuations on subgalactic scales. In this work, we report results from the first search for Galactic DM subhalos with time-domain astrometric weak gravitational lensing. The analysis is based on a matched-filter template of local lensing corrections to the proper motion of stars in the Magellanic Clouds. We describe a data analysis pipeline detailing sample selection, background subtraction, and handling outliers and other systematics. For tentative candidate lenses, we identify a signature based on an anomalous parallax template that can unequivocally confirm the presence of a DM lens, opening up prospects for robust discovery potential with full time-series data. We present our constraints on substructure fraction f l ≲5 at 90% CL (and f l ≲2 at 50% CL) for compact lenses with radii r l <1pc, with best sensitivity reached for lens masses M l around 10 7 -10 8 M ⊙ . Parametric improvements are expected with future astrometric data sets; by end of mission, Gaia could reach f l ≲10 -3 for these massive point-like objects, and be sensitive to lighter and/or more extended subhalos for O(1) substructure fractions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Performance Analysis of a Membrane-based Ionic Liquid Desiccant (ILD) Dehumidifier

Air dehumidification through cooling is an energy-intensive process, which consumes about 20-40% of the overall energy for air-conditioning. Liquid desiccant dehumidification can separate dehumidification from space cooling and has potential to improve the cooling efficiency and reduce the overall energy consumption for air-conditioning. However, the drawbacks such as liquid carryover and corrosion, membrane contamination and blocking, limit its application. To eliminate these problems, a new dehumidifier using nonporous membrane and ionic liquid desiccant (ILD) was developed. The dehumidification performance of the new dehumidifier was characterized through a series of lab tests. Test results indicate that the new dehumidifier can achieve a moisture removal rate up to 180.3 g/h and a dehumidification effectiveness up to 12.7%. A parametric study found that the dehumidification performance is sensitive to the flowrates of the air and the ILD solution. A higher mass flow ratio between the ILD solution and the air could result in better dehumidification performance.

Wang, Lingshi↗

DOE OSTI2022

Measures of illuminant-induced metameric mismatch: theory, comparative analysis, and implications for application

Illuminant-induced metameric mismatch is an important consideration in the specification of light sources for some architectural environments, yet there is currently no standardized performance measure. The goal of this work was to evaluate two recent research proposals: the metameric uncertainty index ( R t ) and the metamer mismatching color rendering index (MMCRI). To compare the relative performance of these two measures, 100,000 spectral power distributions were generated with 3, 4, 5, 6, and 7 Gaussian spectral components and spectral widths varying from 1 nm (monochromatic) to 100 nm. Both measures generally agree with the theory that broadband radiation should cause less metameric mismatch than narrowband radiation. The two measures have relatively better agreement for broadband SPDs and relatively worse agreement for narrower spectra. Despite some similarities, non-parametric statistical tests suggest that R t and MMCRI are significantly different quantifications of illuminant-induced metameric mismatch ( p < 0.0001 for all comparisons). Characteristics of the MMCRI computation that are potentially problematic for applied lighting were observed.

42 ENGINEERING↗

DOE OSTI2022

Anisotropic yield models for lattice unit cell structures exploiting orthotropic symmetry

We report numerical homogenization enables efficient computational analysis and design of multiscale structures made of micro-architected materials including lattice unit cells. However, predicting yield is nontrivial because it requires accurate and efficient predictions of the maximum stress inside the homogenized unit cells. To address this challenge, we develop a macroscale anisotropic yield function for micro-architected materials. The yield function depends on the three-dimensional macroscale stress state and the parameters describing a family of micro-architectures, such as the radii of the struts in a lattice unit cell. To ensure accuracy, we determine the maximum stress using three-dimensional continuum finite-element analysis. To ensure efficiency, we construct surrogate models from the aforementioned high-fidelity results for yield prediction. To reduce simulation costs and surrogate modeling complexity, we leverage orthotropic symmetry commonly found in lattice unit cells. In this paper, we provide a thorough presentation of group representations and the systematic procedure to exploit orthotropic domain symmetry in homogenization and surrogate modeling. We illustrate the use of linear homogenization results to predict yield in specific unit cells without further simulations. We furthermore show that surrogate modeling presents a viable option for anisotropic yield prediction in a continuously parametrized family of micro-architectures. More specifically, despite the dimensionality and degree of nonlinearity in the maximum micro von Mises stress within the unit cell, the surrogate models can predict it with less than 5% error at least 90% of the time. Moreover, the largest under-prediction error, which is more critical than the over-prediction error, is typically less than 10%.

42 ENGINEERING↗

DOE OSTI2024

Discoveries in Blast-Driven Turbulence of Astrophysical Relevance

The fluid mixing caused by variable-density instabilities is important in a wide variety of scenarios from ocean mixing and astrophysical phenomena to nuclear fusion techniques and atomic weapons. This thesis explores the mixing resulting from a specific instability known as the Blast Driven Instability (BDI). This work investigates the variable density mixing in an explosively driven environment due to the fluid instabilities at the material interfaces. Specifically, diverging Richtmyer-Meshkov (impulsive-acceleration environment) and Rayleigh-Taylor (variable-acceleration environment) instabilities (present in supernova and inertial confinement fusion) are studied using advanced high-speed diagnostics in carefully designed laboratory experiments. The BDI morphology is presented through a time development of Mie scattering images, and steps through the parameter space (varying density ratio and driver speed), highlighting the development of the structures that form during mixing. A scaling criterion is used to relate the two systems of vastly different spatiotemporal scales. Velocity fields in the BDI have been captured for the first time using the high temporal resolution PIV technique. Subsequent analysis of the dynamics of the instability from the velocity fields illustrates the distribution of kinetic energy, the transition to turbulence, and the characteristic growth of the instability are discussed. This study furthers understanding of how blast-driven instability pertains to supernova and inertial confinement fusion science. The morphology of the BDI has been characterized for the first time. This work steps through the parameter space covered in Mie scattering experiments, and how the different parameters contribute to development of structures and mixing. It also examines a scaling of the Atwood number for expanding predictive capabilities to other experimental conditions and simulations. The first collection of velocity fields acquired for the BDI are recorded, and subsequent analysis evaluating the distribution of kinetic energy throughout space and time for two density ratios from the overall parameter space, as well as the transition to turbulence, estimated from a Reynolds number calculated based on momentum mixing are all presented. This information is useful in advancing the development of models to predict physics of high energy density applications where experiments are not always readily available. This research has successfully demonstrated understanding for the time criteria defining regimes where the shock driven (Richtmyer-Meshkov instability) and the buoyancy driven (Rayleigh-Taylor instability) dominates through a parametric study of density variation (Atwood number) and driver speed (Mach number). All this furthers understanding of how the BDI pertains to SN and ICF.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Analysis of Frost Formation and Novel Defrost Techniques for Commercial Refrigeration Applications

The purpose of this Cooperative Research and Development Agreement (CRADA) was to test a heat exchanger defrosting approach using radiant energy, including ultraviolet-C, -B, and -A. A preliminary test conducted at Oak Ridge National Laboratory demonstrated the concept of ultraviolet-based defrosting, which melts frost on the fin surface of a heat exchanger without increasing its overall temperature, thereby offering a new defrosting method that does not interrupt heat exchanger operation. Building on this key finding, this CRADA outlines a plan for upgrading the test equipment and for further testing to bridge the gap between the concept and its feasibility for industrial applications. This report also provides a brief review of existing defrosting technologies, the current state of the experimental system, and future parametric experiment plans.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Conjugate Heat Transfer Modeling of Salt-Filled Fuel Pins for Stable Salt Reactor Safety Analysis

The Stable Salt Reactor (SSR) combines the proven structural design of light water reactor fuel assemblies with the inherent safety and fuel-cycle advantages of molten salt technology. In its fast reactor configuration, the SSR utilizes recycled nuclear waste as fuel, sealed within narrow salt-filled fuel pins and cooled by a surrounding liquid salt coolant. Reliable transfer of heat from the molten fuel salt through the cladding to the external coolant is essential for both reactor safety and performance. This work investigates conjugate heat transfer (CHT) in the SSR’s salt-filled fuel pins using NekRS, a high-fidelity spectral element computational fluid dynamics (CFD) solver. The analyses capture internal natural convection within the molten fuel salt and external forced convection in the coolant, under steady-state and transient operating conditions. Parametric studies evaluate how variations in reactor power and coolant flow rate influence heat transfer distributions and system response. The high-fidelity CFD results are time-averaged and post-processed for direct comparison with moderate-fidelity Reynolds-averaged Navier–Stokes (RANS) models, and for the development of reduced-order models within the SAM system code. These validated models support fast-running safety analyses of normal and off-normal transients, improving predictive capability for key safety margins. By integrating advanced CFD with system-level safety tools, this study strengthens the modeling framework for SSR design, reduces uncertainty in molten salt CHT simulations, and accelerates the engineering and licensing of next-generation nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Sol-gel derived silicate-phosphate glass SiO 2 –P 2 O 5 –CaO–TiO 2 : The effect of titanium isopropoxide on porosity and thermomechanical stability

Despite of several decades lasting extensive research of bioactive and bioresorbable glasses the systematic parametrization and determination of the key factors affecting porosity and thermomechanical characteristics still remains challenging. Here, we present silica-phosphate glasses, with the composition 70SiO 2 - 20P 2 O 5 - (10-x)CaO-xTiO 2 (mol%; x = 0, 2.5, 5, and 7.5), prepared by sol -gel method and reinforced by titanium dioxide via titanium isopropoxide (TTIP) incorporation which demonstrated tunable variation of porosity from micro-to macro -region and superb mechanical integrity during the calcination process. The presence of 7.5 mol% TiO 2 promotes dimensional stability up to 1000°C as investigated by thermomechanical analysis. The XRD showed the dominant presence of silicon phosphate [Si(P 2 O 7 )], titanium phosphate [Ti(P 2 O 7 )] and calcium phosphates [β-Ca(P 2 O 6 ) and γ- Ca 2 (P 2 O 7 )]. The effect of TiO 2 doping on the multiscale morphology and porosity was investigated by means of SEM, MIP, μCT, N 2 adsorption and USAXS/SAXS. Increasing TiO 2 content leads to the formation of open porosity up to 70vol% and drives the formation of a refined interconnected macroporosity of 2-30 μm. In contrast, mesoporosity with a dominance of 3-6nm pores decreases in all samples with increasing TiO 2 content. USAXS/SAXS revealed an increase in primary particle size with increasing TiO 2 content which is in good agreement with the nitrogen physisorption analysis showing that microporosity decreases with increasing TiO2 content.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗

DOE OSTI2024

Development of a neural network model for peeling–ballooning stability analysis in the KSTAR tokamak pedestals

The neural network model, MISHKA-NN is developed to mitigate the computational burden associated with the linear ideal magnetohydrodynamic (MHD) stability analysis of the pedestal based on the peeling–ballooning (P–B) model. By utilizing both 1D plasma profiles (current density, pressure gradient, and safety factor) and 0D parameters (plasma geometry, total current, and toroidal mode number), the model predicts linear growth rate of edge-localized ideal MHD instability in a given equilibrium state. By enabling the prediction of each instability within a second, the model reduces the time required for plotting a pedestal P–B stability diagram (j - α diagram) from approximately 100 CPU hours to a few CPU minutes. Notably, even with the utilization of parametric pressure and current profiles and plasma boundary shapes for the training dataset, the model shows a satisfactory level of performance in benchmarking the j - α diagram for the reconstructed equilibrium from a KSTAR tokamak experiment. We anticipate the model to serve as a versatile alternative to 2D linear MHD stability codes, alleviating numerical costs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Study of the f 0 ( 980 ) and f 0 ( 500 ) Scalar Mesons through the Decay D s + → π + π − e + ν e

Using e + e − collision data corresponding to an integrated luminosity of 7.33 fb − 1 recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D s + → π + π − e + ν e , where the D s + is produced via the process e + e − → D s * ± D s ∓ . We observe the f 0 ( 980 ) in the π + π − system and the branching fraction of the decay D s + → f 0 ( 980 ) e + ν e with f 0 ( 980 ) → π + π − measured to be ( 1.72 ± 0.1 3 stat ± 0.1 0 syst ) × 10 − 3 , where the uncertainties are statistical and systematic, respectively. The dynamics of the D s + → f 0 ( 980 ) e + ν e decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f 0 ( 980 ) in the differential decay rate, and the product of the form factor f + f 0 ( 0 ) and the c → s Cabibbo-Kobayashi-Maskawa matrix element | V c s | is determined for the first time to be f + f 0 ( 0 ) | V c s | = 0.504 ± 0.01 7 stat ± 0.03 5 syst . Furthermore, the decay D s + → f 0 ( 500 ) e + ν e is searched for the first time but no signal is found. The upper limit on the branching fraction of D s + → f 0 ( 500 ) e + ν e , f 0 ( 500 ) → π + π − decay is set to be 3.3 × 10 − 4 at 90% confidence level. Published by the American Physical Society 2024

Ablikim, M.↗

DOE OSTI2022

Aerodynamic Analysis of Wind Loading on Parabolic Trough Collectors Using High-Fidelity CFD Modeling

Wind loading on parabolic solar collector support structures is the key driver for material costs. As identified by NREL's CSP Best Practices project [1], ability to predict wind-loading in deep-arrays and the impact of edge effects has potential to decrease levelized cost of electricity (LCoE) by 15%. In this study, we present a high-fidelity computational model that can model the flow around deep arrays of parabolic troughs under varying turbulent inflow conditions. Ability to accurately reproduce atmospheric boundary layer (ABL) profiles is first demonstrated through Large Eddy Simulation (LES) simulations and compared against wind tunnel measurements. Thereafter, unsteady turbulent flow past single row and six row configurations is computed using hybrid RANS/LES simulations. Investigations of wind loading, through parametric tilt angle variations of single row and on waked collectors in six-row configuration, are used to highlight design considerations for parabolic troughs only possible through high-fidelity unsteady calculations.

aerodynamics↗