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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗
DOE OSTI2021

Design and Optimization of a Gas-Cooled, Airfoil Fin Microchannel Heat Exchanger

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, was analyzed and optimized using a design of experiments with artificial intelligence and machine learning techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin PCHEs has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure was developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. STAR-CCM+ was used to analyze a simplified two-channel configuration where five parameters were varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods were compared for generating surrogate models – a 5D polynomial and a regression neural network. A response surface approximation was created from the surrogate models and input to a genetic algorithm. The genetic algorithm identified a set of optimal points on the Pareto front. The optimal geometry was found across six channel Reynolds numbers ranging from 1000 to 5000 to analyze how varying inlet conditions affects the optimal design. A set of optimal designs that maximizes heat transfer and minimizes pressure drop was identified, and a thermal stress analysis was performed on the optimal design. This work has developed a digital framework for the expedient topology design and evaluation of PCHE designs for gas-cooled microreactor applications. Correlations for the Nusselt number and Darcy friction factor were developed that can be useful for thermal hydraulic analyses using system codes. A thermal stress analysis was conducted and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2021

Prediction of PbLi fluid flow and temperature field in a thermal convection loop for qualification of fusion materials

Two modeling tools, a thermohydraulics code and a computational model in COMSOL Multiphysics, have been developed, tested and then applied to the analysis of fluid flow and heat transfer in a thermal convection loop (TCL). Such a device has recently been used to experimentally evaluate corrosion compatibility of APMT (Fe–21Cr–5Al–3Mo) steel with high-temperature molten eutectic lead-lithium (PbLi) alloy at Oak Ridge National Lab, TN, USA. Here, the 1-D thermohydraulics code allows for rapid calculations of the loop parameters as a function of the applied heat flux. The supplemental COMSOL finite-element computations provide detailed 3-D velocity and temperature field data but are much more time consuming. Both modelling tools demonstrate an excellent agreement in the computed circulation velocity as well as maximum and minimum temperatures. The performed TCL analysis focuses on flow development in the “hot” and “cold” legs, formation of Dean vortices in corner regions, blocking effect of the immersed samples, and radiative and convective cooling effects under the experiment-relevant conditions for Prandtl number Pr = 0.015, Grashof numbers Gr ~10 7 , and Reynolds numbers Re ~10 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

First-Principles Cost Estimation of a Sodium Fast Reactor Nuclear Plant

A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Sex Differences in Vagus Nerve Stimulation Effects on Rat Cardiovascular and Immune Systems

Background: Investigations into the benefits of vagus nerve stimulation (VNS) through pre-clinical and clinical research have led to promising findings for treating several disorders. Despite proven effectiveness of VNS on conditions such as epilepsy and depression, understanding of off-target effects and contributing factors such as sex differences can be beneficial to optimize therapy design. New Methods: In this article, we assessed longitudinal effects of VNS on cardiovascular and immune systems, and studied potential sex differences using a rat model of longterm VNS. Rats were implanted with cuff electrodes around the left cervical vagus nerve for VNS, and wireless physiological monitoring devices for continuous monitoring of cardiovascular system using electrocardiogram (ECG) signals. ECG morphology and heart rate variability (HRV) features were extracted to assess cardiovascular changes resulting from VNS in short-term and long-term timescales. We also assessed VNS effects on expression of inflammatory cytokines in blood during the course of the experiment. Statistical analysis was performed to compare results between Treatment and Sham groups, and between male and female animals from Treatment and Sham groups. Results: Considerable differences between male and female rats in cardiovascular effects of VNS were observed in multiple cardiovascular features. However, the effects seemed to be transient with approximately 1-h recovery after VNS. While short-term cardiovascular effects were mainly observed in male rats, females in general showed more significant long-term effects even after VNS stopped. We did not observe notable changes or sex differences in systemic cytokine levels resulting from VNS. Comparison With Existing Methods: Compared to existing methods, our study design incorporated wireless physiological monitoring and systemic blood cytokine level analysis, along with long-term VNS experiments in unanesthetized rats to study sex differences. Conclusion: The contribution of sex differences for long-term VNS off-target effects on cardiovascular and immune systems was assessed using awake behaving rats. Although VNS did not change the concentration of inflammatory biomarkers in systemic circulation for male and female rats, we observed significant differences in cardiovascular effects of VNS characterized using ECG morphology and HRV analyses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Maximising the investment returns of a grid‐connected battery considering degradation cost

Energy storage systems (ESSs) are being deployed widely due to numerous benefits including operational flexibility, high ramping capability, and decreasing costs. This study investigates the economic benefits provided by battery ESSs when they are deployed for market‐related applications, considering the battery degradation cost. A comprehensive investment planning framework is presented, which estimates the maximum revenue that the ESS can generate over its lifetime and provides the necessary tools to investors for aiding the decision making process regarding an ESS project. The applications chosen for this study are energy arbitrage and frequency regulation. Lithium‐ion batteries are considered due to their wide popularity arising from high efficiency, high energy density, and declining costs. A new degradation cost model based on energy throughput and cycle count is developed for Lithium‐ion batteries participating in electricity markets. The lifetime revenue of ESS is calculated considering battery degradation and a cost–benefit analysis is performed to provide investors with an estimate of the net present value, return on investment and payback period. The effect of considering the degradation cost on the estimated revenue is also studied. The proposed approach is demonstrated on the IEEE Reliability Test System and historical data from PJM Interconnection.

25 ENERGY STORAGE↗
DOE OSTI2024

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Low-Temperature Plasma Treatment for Enhanced Recovery of Highly Valued Critical REEs from Coal (Final Technical Report)

The principle objective of this project was to develop a novel process flowsheet using low-temperature plasma treatment (LTP) integrated with conventional hydrometallurgical processes to recover rare earth elements (REEs), especially highly valued REEs (i.e. scandium and critical REEs), from coal and coal byproducts. LTP treatment was used to pretreat the solid feed material prior to leaching in an effort to improve the leaching characteristics of the REEs and potentially reduce acid consumption. Initially, a detailed experimental program was performed on a laboratory LTP furnace to identify a set of process parameter values to be used for assessing the enhanced leaching performance achieved on four specific gravity fractions of West Kentucky No. 13 and Fire Clay coarse coal refuse materials. High-temperature oxidation (HTO)) was also evaluated as a means for improving REE leachability on the same fractions of both coal sources. The lixiviants used to assess leachability improvements included i) untreated water, ii) 0.1 M ammonium sulfate solution and iii) 1.2 M sulfuric acid solution at a temperature of 75°C. The laboratory data was used to develop multiple process flow sheets using HTO only to produce a rare earth oxide mix concentrate or utilizing both LTP and HTO treatment processes to generate a high purity heavy REO mix concentrate and a light REO mix concentrate. A techno-economic analysis was performed on each circuit.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cited Reference Analysis in a National Laboratory to Assess Journal Usage

Librarians at a large, federally funded, multidisciplinary research organization sought to assess the value provided by the library’s collections. One method for capturing this value includes determining how well their library’s collections meet researcher needs, as expressed by the materials those researchers choose to cite in the production of new scholarly communications. A cited reference analysis was performed on the publications originating from the institution to provide the necessary data for the assessment, as well as to aid in the creation of a core list of journals which will inform future collection development efforts. Overall, this paper fills a gap in the library and information science literature by addressing the citation behaviors of researchers at a large multidisciplinary government research facility, a setting that has not been examined previously.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Angular systematics-free cosmological analysis of galaxy clustering in configuration space

ABSTRACT Galaxy redshift surveys are subject to incompleteness and inhomogeneous sampling due to the various constraints inherent to spectroscopic observations. This can introduce systematic errors on the summary statistics of interest, which need to be mitigated in cosmological analysis to achieve high accuracy. Standard practices involve applying weighting schemes based on completeness estimates across the survey footprint, possibly supplemented with additional weighting schemes accounting for density-dependent effects. In this work, we concentrate on pure angular systematics and describe an alternative approach consisting in analysing the galaxy two-point correlation function where angular modes are nulled. By construction, this procedure removes all possible known and unknown sources of angular observational systematics, but also part of the cosmological signal. We use a modified Landy–Szalay estimator for the two-point correlation function that relies on an additional random catalogue where angular positions are randomly drawn from the galaxy catalogue, and provide an analytical model to describe this modified statistic. We test the model by performing an analysis of the full anisotropic clustering in mock catalogues of luminous red and emission-line galaxies at 0.43 < z < 1.1. We find that the model fully accounts for the modified correlation function in redshift space, without introducing new nuisance parameters. The derived cosmological parameters from the analysis of baryon acoustic oscillations and redshift-space distortions display slightly larger statistical uncertainties, mostly for the growth rate of structure parameter fσ8 that exhibits a $50{{\ \rm per\ cent}}$ statistical error increase, but free from angular systematic error.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Lattice determination of 𝐼=0 and 2 𝜋⁢𝜋 scattering phase shifts with a physical pion mass

Phase shifts for 𝑠-wave 𝜋⁢𝜋 scattering in both the 𝐼 =0 and 𝐼 =2 channels are determined from a lattice QCD calculation performed on 741 gauge configurations obeying G-parity boundary conditions with a physical pion mass and lattice size of 32 3 ×64. These results support our recent 2021 study of direct 𝐶⁢𝑃 violation in 𝐾 → 𝜋⁢𝜋 decay, improving our earlier 2015 calculation. The phase shifts are determined for both stationary and moving 𝜋⁢𝜋 systems, at three (𝐼 = 0) and four (𝐼 = 2) different total momenta. We implement several 𝜋⁢𝜋 interpolating operators including a scalar bilinear “𝜎” operator and paired single-pion bilinear operators with the constituent pions carrying various relative momenta. Several techniques, including correlated fitting and a bootstrap determination of p-values have been used to refine the results and a comparison with the generalized eigenvalue problem method is given. A detailed systematic error analysis is performed which allows phase shift results to be presented at a fixed energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Constraining primordial non-Gaussianity from DESI DR1 quasars and Planck PR4 CMB lensing

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between 1.2 million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering 0.8 < z < 3.5, covering a sky fraction of ∼20%. We adopt a catalog-based pseudo-C ℓ estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter f NL and the linear bias amplitude in each redshift bin, we obtain f NL = 2 +28 -34 for a response parameter p = 1.6, and f NL = 6 +20 -24 for p = 1.0. These results improve the constraints on f NL by ∼35% compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming p = 1.6, we obtain f NL = 19 +25 -31 . Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

cosmological parameters from CMBR↗
DOE OSTI2025

Characterization and Damping Control of Mechanical Connections to Improve Performance of Horn Stripline

Magnetic focusing horns are critical components for creating a stable beam of neutrinos for neutrino facilities, such as the Long Baseline Neutrino Facility (LBNF) and the Neutrinos and Main Injector (NuMI) beam lines at Fermilab. The pulsed magnetic horns are powered by high current electricity through long striplines. In addition to requirements for low inductance and voltage standoff, the striplines must survive in a harsh radiation environment for the operational life of the component, specified as the 100 million pulses requirement for LBNF. Each stripline assembly consists of four (eight layers that splits off to 2 pairs of four layers at the horn interface) layers of Al 6101-T6. As an electromechanical system, the stripline layers are bolted together with ceramic isolators for electrical insulation and connections must facilitate passive cooling and mechanical stability. The striplines experience vibrational force in addition to clamping force, repetitive thermal and electro-magnetic loading. The holes of stripline plates for ceramic joints represent one of the weak links for potential failure [1,2]. By characterizing the contact behavior of these joints and optimizing their damping properties through finite element analysis and experimental modal analysis, stripline performance and longevity can be improved. This study not only helps predict the behavior of the striplines but also improves their performance to meet the required operational lifetime.

Liu, Zunping [Fermilab]↗
DOE OSTI2023

Evaluation of thermostat location for multizone commercial building performance

In multi-zone buildings, it is often found that a single shared thermostat controls more than one conditioned zones. Although these shared zones are supposed to have similar thermal needs (e.g., cooling and heating load), in reality, they are not mainly due to different orientations, sizes of windows, occupancy, space types, etc. This can cause unnecessary energy waste or thermal discomfort for the occupants. How to quantify this impact in multizone buildings remains a research gap. Therefore, this study aims to evaluate the impact of different sensor (i.e., thermostat) locations for multizone commercial buildings through a comprehensive modeling study. Here, two different scenarios for the sensor locations were selected to evaluate the impact in terms of energy and thermal comfort. The scenario (1) is that one to five sensors distributed among the five zones, but the sensor readings from selected zones will be used for no-sensor zones, which is no-mean sensor scenario. The scenario (2) is that one to five sensors distributed among the five zones, but the average temperature from the shared zones will be used for each of the shared zones, which is a mean sensor scenario. The uncertainty analysis was performed for different sensor location scenarios.(a)The major findings from an energy perspective, for scenario (1), the differences of cooling energy go as high as 17% more or 12% less, compared with the baseline. For heating energy consumption, the discrepancies go as high as 51% more or 52% less, compared with baseline. For site energy consumption, the discrepancies go as high as 3.2% more or 3.2% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.2% more or as low as 1.0% less, compared with baseline. For scenario (2), the discrepancies of cooling energy go as high as 3% more, or 0.5% less, compared with the baseline. For heating energy consumption, the discrepancies, are go as high as 10.1% more or as low as 3.0% less, compared with baseline. For site energy consumption, the discrepancies go as high as 1.3% more or 0.3% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.1% more or as low as 1.0% less, compared with baseline.(b) In terms of the indoor thermal comfort, for the no-mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 1,200 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 740 h, compared with the baseline. For the mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 750 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 50 h, compared with the baseline.

42 ENGINEERING↗
DOE OSTI2022

Co-optimized machine-learned manifold models for large eddy simulation of turbulent combustion

Many modeling approaches in large eddy simulation (LES) of turbulent combustion employ a projection of the thermochemical state onto a low-dimensional manifold within state space to reduce the number of transported variables and hence computational cost. Flamelet-generated manifolds (FGM) is an example of a well-established, physics-based approach, but increasingly, principal component analysis (PCA) is being used as a data-driven method for generating manifold models. For both approaches, the nonlinear relationship between the location on the predefined manifold and the outputs of interest, such as reaction rates, can be tabulated or encoded in a neural network. This work proposes a new approach for manifold modeling that extends these existing approaches. A modified neural network structure simultaneously encodes the definition of the manifold variables, the nonlinear mapping, and the subfilter closure for LES. This allows all three of these aspects of the model to be co-optimized, generating a model from any source of combustion thermochemical state data. The manifold parameterizing variables are constrained to be linear combinations of species, as in FGM and PCA-based models, to aid in interpretability and implementation. For LES, subfilter variances of the manifold variables are also included as inputs. Two types of a priori analysis are performed to evaluate the new approach. In the first, the model is trained on data from one-dimensional premixed flames. In this case, the approach recovers the behavior of flamelet-based manifold approaches, and in fact slightly improves performance by identifying an optimized progress variable. The approach is also applied to data from direct numerical simulations of spherical ignition kernels in isotropic turbulence. For any specified manifold dimensionality, the new approach provides substantially lower prediction errors than a PCA-based model developed from the same data set. Additionally, the LES formulation of the new approach can provide accurate predictions for filtered reaction rates across a variety of filter widths.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Constraints on directionality effect of nuclear recoils in a liquid argon time projection chamber

The direct search for dark matter in the form of weakly interacting massive particles (WIMP) is performed by detecting nuclear recoils produced in a target material from the WIMP elastic scattering. The experimental identification of the direction of the WIMP-induced nuclear recoils is a crucial asset in this field, as it enables unmistakable modulation signatures for dark matter. The Recoil Directionality (ReD) experiment was designed to probe for such directional sensitivity in argon dual-phase time projection chambers (TPC), that are widely considered for current and future direct dark matter searches. The TPC of ReD was irradiated with neutrons at the INFN Laboratori Nazionali del Sud. Data were taken with nuclear recoils of known directions and kinetic energy of 72 keV, which is within the range of interest for WIMP-induced signals in argon. The direction-dependent liquid argon charge recombination model by Cataudella et al. was adopted and a likelihood statistical analysis was performed, which gave no indications of significant dependence of the detector response to the recoil direction. The aspect ratio R of the initial ionization cloud is $R < 1.072$ with 90 % confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Thermo-Mechanical Modeling and Evaluation of the Cracking Response of Additively Manufactured Monolithic SiC Lattice Structures Subjected to Laser Heating

Increasing operating temperatures of solar receivers is paramount to the efficiency of concentrated solar thermal (CST) and solar power (CSP) systems. Owing to its high temperature stability combined with excellent thermal and optical properties, SiC has been the material of choice for application in high-temperature solar receivers. The state-of-the-art SiC volumetric concentrating solar air receivers such as honeycomb design have been demonstrated in field tests to achieve exit air temperatures approaching 800oC. However, successful application of CST systems for decarbonization requires significant increase in temperature capability of SiC receiver technology. Supported by an award from the Solar Technology Office (SETO), US Department of Energy (DOE), GE Research in collaboration with Heliogen Holdings Inc, is engaged in the development of ultra-High Operating Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR) enabled by additive manufacturing. The program objective is to design and to demonstrate a techno-economically viable SiC air receiver technology to achieve exit air temperature of 1100oC for CST applications. This report summarizes the learnings of a computational study on additively manufactured SiC lattice structures subjected to laser heating. The results from this study aim to help guide the design of a SiC receiver through a better understanding of lattice structure geometric parameters and their implications on the cracking response of the structure. In the study, a heat flux was applied to the surface of a 2”-diameter cylindrical lattice structure to simulate a 4kW CO2 laser. The resulting temperature distribution was applied to a structural model to approximate the stress distribution within the lattice structure and a Weibull analysis was performed to gain insight into the probability of failure and to evaluate the cracking response of the structure. With this approach, the influence of lattice density on temperature, stress, and probability of failure was explored for two different lattice beam spacings. A discussion on modeling assumptions, a comparison with experimental results, and an evaluation of the lattice cracking response is provided.

14 SOLAR ENERGY↗