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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Screening analysis of enhanced weathering of igneous rocks and industrial waste materials

Enhanced weathering (EW) is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. This manuscript reports on a screening level techno-economic analysis of EW. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The modeled EW process encompasses material purchase, comminution, transport, distribution of material on farmland, and measurement, reporting and verification of CO2 removal. Detailed sensitivities are performed to highlight promising scenarios for application. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured (less than $100 per total tonnes of CO2 captured from the atmosphere). NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

Leptinsky, Sarah [NETL Site Support Contractor, Na↗
DOE OSTI2021

Development of a reduced model for energetic particle transport by sawteeth in tokamaks

We report that the sawtooth instability is known for inducing transport and loss of energetic particles (EPs), and for generating seed magnetic islands that can trigger tearing modes. Both effects degrade the overall plasma performance. Several theories and numerical models have been previously developed to quantify the expected EP transport caused by sawteeth, with various degrees of sophistication to differentiate the response of EPs at different energies and on different orbits (e.g. passing vs. trapped), although the analysis is frequently limited to a single time slice during a tokamak discharge. This work describes the development and initial benchmark of a framework that enables a reduced model for EP transport by sawteeth retaining the full EP phase-space information. The model, implemented in the ORBIT hamiltonian particle-following code, can be used either as a standalone post-processor taking input data from codes such as TRANSP, or as a pre-processor to compute transport coefficients that can be fed back to TRANSP for time-dependent simulations including the effects of sawteeth on EPs. The advantage of the latter approach is that the evolution of the EP distribution can be simulated quantitatively for sawtoothing discharges, thus enabling a more accurate modeling of sources, sinks and overall transport properties of EP and thermal plasma species for comprehensive physics studies that require detailed information of the fast-ion distribution function and its evolution over time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Two-fluid and kinetic transport physics of Kelvin–Helmholtz instabilities in nonuniform low-beta plasmas

Hall-magnetohydrodynamic (Hall-MHD) theory, two-fluid simulations, and kinetic simulations are used in this work to investigate the cross-field transport properties of Kelvin–Helmholtz instabilities in nonuniform low-beta collisionless plasmas. Hall-MHD analysis shows how the linear properties of the instability are modified by density gradients and magnetization. High-order accurate two-fluid and kinetic simulations, with complete dynamics of finite-mass electrons and ions, are applied to a suite of parameter cases to systematically assess the effects of diamagnetic drift, magnetization, charge separation, and finite Larmor motion. Initialization of exact two-species kinetic equilibria facilitates the study of isolated physical effects and enables detailed cross-comparisons between two-fluid and kinetic simulations, including for cases where ion gyroradii are comparable to gradient scale lengths. For nonuniform plasmas with significant space charge, the results of two-fluid and kinetic simulations are found to disagree with Hall-MHD predictions. Kelvin–Helmholtz instability growth rates, per unit shear, are shown to be smaller when ion diamagnetic drift and $E \times B$ drift are parallel and larger when the two drifts are antiparallel. The effect is attributed to polarization drift in the shear layer, which leads to redistribution of charge, alters the electric field that drives plasma advection, and consequently modifies growth rates. Instability-induced mass transport for different parameters is characterized in terms of the flux across the shear layer and a simplified diffusion model. Distribution functions from kinetic simulations are shown to deviate substantially from Maxwellian reconstructions, indicating the importance of kinetic physics during the nonlinear phase of the instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Silver-mediated separations: A comprehensive review on advancements of argentation chromatography, facilitated transport membranes, and solid-phase extraction techniques and their applications

The use of silver(I) ions in chemical separations, also known as argentation separations, is a powerful approach for the selective separation and analysis of many natural and synthetic organic compounds. In this review, a comprehensive discussion of the most common argentation separation techniques, including argentation-liquid chromatography (Ag-LC), argentation-gas chromatography (Ag-GC), argentation-facilitated transport membranes (Ag-FTMs), and argentation-solid phase extraction (Ag-SPE) is provided. For each of these techniques, notable advancements, optimized separations, and innovative applications are discussed. The review begins with an explanation of the fundamental chemistry underlying argentation separations, mainly the reversible π-complexation between silver(I) ions and carbon-carbon double bonds. Within Ag-LC, the use of silver(I) ions in thin-layer chromatography, high-performance liquid chromatography, as well as preparative LC are explored. This discussion focuses on how silver(I) ions are employed in the stationary and mobile phase to separate unsaturated compounds. For Ag-GC and Ag-FTMs, different silver compounds and supporting media are discussed, often with relation to olefin-paraffin separations. Ag-SPE has been widely employed for the selective extraction of unsaturated compounds from complex matrices in sample preparation. This comprehensive review of Ag-LC, Ag-GC, Ag-FTMs, and Ag-SPE techniques emphasizes the immense potential of argentation separations in separations science and serves as a valuable resource for researchers seeking to learn, optimize, and utilize argentation separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evaluating the sustainability of the 2017 US biofuel industry with an integrated techno-economic analysis and life cycle assessment

The United States produced more than 66.2 billion Liters of biofuel, primarily in the form of corn ethanol (61 billion Liters) and soybean biodiesel (6 billion Liters), for the transportation industry in 2017. No work currently exists that evaluates both the economic and environmental outcomes of this industry with adequate geospatial resolution and national scope. In this study, a model framework is constructed to perform Techno-Economic Analysis and Life Cycle Assessment using high-resolution input datasets to provide a granular estimation of corn ethanol and soybean biodiesel sustainability performance in most counties in the United States in 2017 (the most recent year for which data is available). Results show a total life cycle, greenhouse gas emission volume of 99.5 million Mg CO 2-eq produced in 2017 by these two biofuels (94.8 million Mg from corn ethanol, and 4.7 million Mg from soybean biodiesel), excluding indirect land use change emissions. Further, this volume corresponds to a combined carbon intensity of 65.3 gCO 2-eq /MJ, which is a greenhouse gas improvement compared to petroleum-based gasoline (the carbon intensity of conventional gasoline is 93.0 gCO 2-eq /MJ). However, these biofuels are produced at an additional economic cost ($1.8 billion over the displaced gas/diesel). Additionally, these biofuels generate unfavorable impacts in other environmental categories when compared to petroleum-based fuels, particularly in areas of water, land, and nitrogen intensity. This work enables stakeholders to assess the specific value of biofuels as a means of emission reduction and determine if the attained improvements are worth the associated opportunity costs.

09 BIOMASS FUELS↗
DOE OSTI2023

Structure–Transport Relationships of Water–Organic Solvent Co-transport in Carbon Molecular Sieve (CMS) Membranes

We explore the effects of the carbon molecular sieve (CMS) microstructure on the separation performance and transport mechanism of water–organic mixtures. Specifically, we utilize PIM-1 dense films and integrally skinned asymmetric hollow fiber membranes as polymer precursors for the CMS materials. The PIM-1 membranes were pyrolyzed under several different pyrolysis atmospheres (argon, carbon dioxide, and diluted hydrogen gas) and at multiple pyrolysis temperatures. Detailed gas physisorption measurements reveal that membranes pyrolyzed under 4% H 2 and CO 2 had broadened ultramicropore distributions (pore diameter <7 Å) compared to Ar pyrolysis, and pyrolysis under CO 2 increased ultramicropore volume and broadened micropore distributions at increased pyrolysis temperatures. Gravimetric water and p-xylene sorption and diffusion measurements reveal that the PIM-1-derived CMS materials are more hydrophilic than other CMS materials that have been previously studied, which leads to sorption-diffusion estimations showing water-selective permeation. Water permeation in the vapor phase, pervaporation, and liquid-phase hydraulic permeation reveal that the isobaric permeation modes (vapor permeation and pervaporation) are reasonably well predicted by the sorption-diffusion model, whereas the hydraulic permeation mode is significantly underpredicted (>250×). Conversely, the permeation of p-xylene is well predicted by the sorption-diffusion model in all cases. The collection of pore size analysis, vapor sorption and diffusion, and permeation in different modalities creates a picture of a combined transport mechanism in which water–under high transmembrane pressures–permeates via a Poiseuille-style mechanism, whereas p-xylene solutes in the mixture permeate via sorption-diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility

Given the significance of selenium (Se) as a micronutrient, the radioactive nature of some of its isotopes, and its affinity to iron (Fe) minerals, extensive research has been conducted on the sorption mechanisms between Se and these minerals. Here, in this study, we employ sorption data sourced from the L-SCIE database and coprecipitation data from available literature to achieve the following objectives: i) establish coherence between adsorption and coprecipitation processes, ii) quantitatively evaluate the importance of these processes in nuclear waste repository science, and iii) propose a forward-looking approach for integrating coprecipitation into reactive transport models. Our findings indicate that a correlation between Se adsorption and coprecipitation can be established using the λ formalism. The comparable log(λ Se(IV) /λ Se(VI) ) ratios derived from adsorption and coprecipitation experiments suggest that these processes can be quantitatively compared and evaluated using our numerical approach. Across all iron oxide phases examined, coprecipitation leads to significantly greater immobilization of Se compared to adsorption. Specifically, for hydrous ferric oxide, hematite, and goethite, coprecipitation is predicted to result in 100–1000 times more Se immobilization compared to adsorption, irrespective of the Se oxidation state (Se(IV) or Se(VI)); notably stronger immobilization potential via coprecipitation was observed for magnetite. The modeling approach and quantitative analysis presented herein clearly highlight the importance of including coprecipitation processes when simulating Se (and other elements) transport, particularly under conditions where mineral compositions are transient or evolving with time. Neglecting coprecipitation in models is likely to lead to significant overestimates of migration.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Scaling CFB risers: Maintaining microstructure dynamics

Over the years there have been numerous approaches to develop a scaleup methodology for circulating fluidized beds. Many of these past approaches have relied on macroscopic definitions of similitude to define dimensionless groups such as Reynolds number, Froude number, density ratios, and dimensional ratios involving different length scales. These approaches have demonstrated various levels of success, but often fail when used outside the bounds of experimental datasets. The issue with these methods is that they rely on macroscopic similitude with the hopes that those conditions would provide microscopic similitude as it does in single phase systems where the Buckingham Pi techniques have given reasonable success. Two of the main reasons for failure are 1) changing fluidization regimes and 2) changing material properties that result in the material falling into a different Geldart group. Both are certain to change the microstructure (local instantaneous volume solids fraction) and changes to the microstructure affect the interphase transport properties of the reactor system, namely the mass transfer and heat transfer. Here, this work presents a new approach towards scaling based upon maintaining similitude at the microscale. It reviews a novel dimensionless flow regime map developed from analysis of the deterministic chaos parameters and higher order moments to ensure microstructure similitude. The work then examines four cases from the literature to assess the scaling approach used: (1) same particle-different scale risers for Geldart Group B particles, (2) Glicksman scaling of atmospheric circulating fluidized bed combustor, (3) same particle-different scale risers for Geldart Group A particles and (4) Glicksman scaling for pressurized gasification. General findings are that none of the scaling approaches produced directly applicable microstructure similar behavior based upon the chaotic and higher moment analysis. The positive take away is that the approach can define scale conditions that will provide similar microstructure that can be us to predict transport behavior.

42 ENGINEERING↗
DOE OSTI2020

Electrokinetic Analysis of Poorly Conductive Electrocatalytic Materials

While many factors can influence the activity of the electrochemical interface at atomic and molecular levels, the electron and ion transport have a big impact on the overall electrochemical performance. Here, we investigate how electrical resistance (conductivity) of the electrode affects the measured electrocatalytic activity using the hydrogen evolution reaction as a model reaction. We clearly demonstrate the effect of the poor electronic conductivity of MoS 2 on the electrochemical performance, as both values of the exchange current density as well as the Tafel slope depend on the level of utilization of the active material and the ohmic losses. A quantitative analysis using the composite electrode model is provided, showing the importance of the experimental conditions and good control of electrode/electrolyte system for the proper evaluation and comparison of electrocatalysts’ kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗
DOE OSTI2022

Enhancement of effective thermal conductivity of rGO/Mg nanocomposite packed beds

Engineering thermophysical properties of metal hydrides nanocomposites is crucial for effective thermal management during hydrogen storage reactions; however, the effect of microstructure on thermal transport mechanisms is still unclear. Here, we employed an integrated experiment-modeling approach to investigate microstructural factors that determine the effective thermal conductivity of individual reduced graphene oxide-magnesium (rGO/Mg) nanocomposites and their packed bed. Here the effective thermal conductivity of the rGO/Mg nanocomposite packed bed was measured by using guarded hot-plate method under various atmospheric conditions (i.e., vacuum, Ar and He). A microstructure-aware mesoscopic modeling revealed that anisotropy of the effective thermal conductivity of individual rGO/Mg nanocomposites plays an important role in determining the effective thermal conductivity of their packed bed. The validated mesoscopic model also disclosed a nontrivial interplay between the intrinsic rGO properties and the extrinsic composite structural features. Finally, quantitative sensitivity analysis based on the modeling framework is used to provide practical engineering guidance for controlling the thermal transport within nanocomposite packed beds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Explaining the lack of power degradation of energy confinement in wide pedestal quiescent H-modes via transport modeling

Wide pedestal quiescent H (WPQH)-mode is an attractive scenario for future burning plasmas as they operate without ELMs. WPQH is characterized by formation of a wider and higher pedestal (than quiescent H-mode), and broadband fluctuations in the pedestal. Unlike conventional H-modes, where the energy confinement time reduces with increasing heating power, the WPQH plasmas reported in this paper do not show power degradation of the energy confinement. As the injected neutral beam power was increased, reduced core (ρ ≤ 0.45) transport calculated by transp, as well as increased core temperatures, pressure gradient and diamagnetic E × B shear rate were observed. The reduction in the heat transport and rapid decrease in the ion temperature gradient scale length suggest the formation of an ion internal transport barrier (ITB) that was accompanied by increased stored energy in the core. Quasilinear turbulent transport modeling using the trapped gyro Landau fluid (tglf) code was used to predict the ITB and its turbulence stability properties. By using profiles and equilibria produced by matching the transp transport fluxes with the tglf transport model within the tgyro transport solver, the energy confinement time captures the experimentally observed insensitivity to the increased PNBI. Linear stability analysis reveals that drift-wave instabilities in the core are stabilized by E × B shear, T i /T e ratio and Shafranov shift; the latter was found to have the strongest effect on the turbulence suppression at the highest heating level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Uranium Single Particle Analysis for Simultaneous Fluorine and Uranium Isotopic Determinations via Laser-Induced Breakdown Spectroscopy/Laser Ablation–Multicollector–Inductively Coupled Plasma–Mass Spectrometry

Uranyl fluoride (UO 2 F 2 ) particles (<20 μm) were subjected to first-of-its-kind analysis via simultaneous laser-induced breakdown spectroscopy (LIBS) and laser ablation multi-collector inductively coupled plasma–mass spectrometry (LA–MC–ICP–MS). Briefly, a nanosecond pulsed high-energy laser was focused onto the sample (particle) surface. In a single laser pulse, the UO 2 F 2 particle was excited/ionized within the microplasma volume, and the emission of light was collected via fiber optics such that emission spectroscopy could be employed for the detection of uranium (U) and fluorine (F). The ablated particle was simultaneously transported into the MC–ICP–MS for high precision isotopic (i.e., 234 U, 235 U, and 238 U) analysis. This method, LIBS/LA–MC–ICP–MS was optimized and employed to rapidly measure 80+ UO 2 F 2 particles, which were subjected to different calcination processes, which results in varying degrees of F loss from the individual particles. In measuring the particles, the average F/U ratios for the populations treated at 100 and 500 °C were 2.78 ± 1.28 and 1.01 ± 0.50, respectively, confirming loss of F through the calcination process. The average 235 U/ 238 U on the particle populations for the 100 and 500 °C were 0.007262 (22) and 0.007231 (23), which was determined to be <0.2% from the expected value. The 234 U/ 238 U ratios on the same particles were 0.000053 (11) and 0.000050 (10) for the 100 and 500 °C, respectively, <10% from the expected value. Notably, each population was analyzed in under 5 min, demonstrating the truly rapid analysis technique presented here in this paper.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Structural Analysis Approach for the Defense Programs Package 3 (DPP-3)

The Pacific Northwest National Laboratory (PNNL) is the design authority for a new Type B hazardous materials transportation package designated as the Defense Programs Package 3 (DPP-3) for the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA). The DPP-3 has been developed using similar materials and fabrication methods employed in previous U.S. Nuclear Regulatory Commission (NRC), DOE, and NNSA certified packages. The DPP-3 design criteria are derived from the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), NNSA guidance and NRC regulatory guides in order to safely and securely transport a variety of payloads. Final regulatory approval by the NNSA will require physical testing to demonstrate that the containment vessel (CV) remains leaktight after enduring the entire regulatory testing sequence prescribed in Title 10 of the Code of Federal Regulations Part 71 (10 CFR 71). In order to gain confidence that the DPP-3 will remain leaktight after testing, the DPP-3 has been structurally analyzed using the Finite Element Analysis (FEA) software LS-DYNA. The FEA analyses serve two general purposes: first, they aid in design and development of the package, and second, they advise as to which drop orientations are expected to cause the most damage during regulatory testing. This paper will discuss how the design criteria are incorporated into analytical techniques needed to evaluate the FEA structural simulation results for 10 CFR 71 conditions to give confidence the DPP-3 testing campaign will be successful.

Sakalaukus Jr., Peter J.↗
DOE OSTI2023

Uncertainty analysis for techno-economic and life-cycle assessment of wet waste hydrothermal liquefaction with centralized upgrading to produce fuel blendstocks

Wet waste hydrothermal liquefaction is a promising technology for producing transportation fuels with much lower greenhouse gases emissions than petroleum-based fuels. However, its techno-economic and life cycle assessment are primarily based on laboratory scale testing data, subject to considerable uncertainties, and even bias, due to knowledge gaps. Here, a preliminary uncertainty analysis of key economic measures was conducted based on the 2019 state-of-technology model for biocrude production. Building on the preliminary analysis, this work presents a comprehensive uncertainty analysis in both economic and environmental measures of the entire supply chain of wet waste hydrothermal liquefaction to fuel blendstocks including biocrude upgrading based on the 2021 state-of-technology model. The analysis includes the most recent developments in hydrothermal liquefaction and biocrude upgrading technologies and Monte Carlo simulation based on an integrated model system including an improved reactor yield model, reduced-order process model, discounted cash flow economic model and simplified life-cycle assessment model. The estimated biocrude yield ranges from 42.2% to 52.4% with a median of 47.3%. The estimated fuel yield ranges from 34.7% to 42.7% with a median of 38.7%. The estimated minimum fuel selling price ranges from $\$ $2.28/gge to $\$ $3.45/gge with a median of $\$ $2.80/gge. Relative to petroleum-derived diesel, the estimated reduction in supply chain greenhouse gas emissions ranges from 73.4% to 81.8% with a median of 77.7%. Compared to the 2019 state-of-technology analysis, a significant improvement in biocrude selectivity and economic measures and reduction in uncertainties were achieved due to the incorporation of additional continuous experimental data sets, technology development and de-risking, and improvement in model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics ↗
DOE OSTI2026

Numerical Simulation of a Natural Convection–Driven Air-Cooled Reactor Cavity Cooling System Experiment

Ensuring the efficient removal of decay heat from the reactor vessel is essential for the safety of advanced reactor technologies. Several Generation-IV concepts incorporate variations in the reactor vessel cooling systems to achieve this objective. High-temperature gas-cooled reactors utilize a reactor cavity cooling system (RCCS), a passive ex-vessel system designed to operate without active components or external power during accident conditions. The RCCS removes decay heat primarily through radiative and convective heat transfer mechanisms. Here, this study presents a comprehensive validation of a computational fluid dynamics Reynolds-averaged Navier-Stokes model for the University of Wisconsin-Madison air-cooled RCCS facility. Validation was conducted for both high- and low-power natural convection cases under a uniform heating profile. Near-wall resolution was found to be critical for accurately modeling natural convection in the RCCS; employing an all-𝑦 + wall treatment resulted in wall temperature discrepancies exceeding 50 °⁢𝐶 compared to a wall-resolved mesh. Thermal-hydraulic behaviors under natural and forced convection conditions were compared within the heated cavity and RCCS. A turbulence model sensitivity analysis indicated that low-Reynolds number k-ɛ, k-ω shear stress transport (SST), and Reynolds stress transport models produce similar wall temperature predictions. A buoyancy modeling sensitivity study revealed that the Boussinesq approximation significantly underpredicted thermal-hydraulic behavior in the RCCS. Based on these findings, modeling recommendations are provided. The validated data set along with identified sensitivities refine the modeling of natural convection in the RCCS. The information produced by this study supports RCCS design, optimization, and safety evaluations, enabling the calibration and verification of reduced-order thermal-hydraulic models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗