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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 OSTI2016

Fabrication of core-shell Fe{sub 3}O{sub 4}@MIL-100(Fe) magnetic microspheres for the removal of Cr(VI) in aqueous solution

Facile regeneration of an adsorbent is very important for commercial feasibility. One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) with diameter about of 350 nm were successfully synthesized. The growth of MIL-100(Fe) shell on the surface of Fe{sub 3}O{sub 4} was utilized precursor as crystal seed via in-situ step hydrothermal reaction. It is a simple way to obtain well organized core-shell MOF composites, compared to the step-by-step method. MMCs were firstly used to uptake of Cr(VI) anions in aqueous solution. Adsorption experiments were carried out in batch sorption mode investigating with the factors of contact time (0–1000 min), pH (from 2 to 12), dose of adsorbent (4–25 mg), and initial Cr(VI) concentration (range from 10 to 100 ppm). - Graphical abstract: One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) were successfully synthesized. Utilizing Fe{sub 3}O{sub 4} precursor as crystal seed to grow MIL-100(Fe) shell by in-situ step hydrothermal reaction. It is a simple way to obtain core-shell MOF composites. MMCs could effectively uptake of Cr(VI) anions in aqueous solution. - Highlights: • Fe{sub 3}O{sub 4}@MIL-100(Fe) composites with core-shell structure were successfully prepared through a simple method. • The influence factors on Cr(VI) adsorption by Fe{sub 3}O{sub 4}@MIL-100(Fe) were investigated. • Cr(VI) can efficiently adsorbed by Fe{sub 3}O{sub 4}@MIL-100(Fe) composites from aqueous solution.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Controls on Barite (BaSO 4 ) Precipitation in Unconventional Reservoirs

Barite (BaSO 4 ) precipitation is one of the most ubiquitous examples of secondary sulfate mineral scaling in shale oil and gas reservoirs. Often, a suite of chemical additives is used during fracturing operations to inhibit the accumulation of mineral scales, though their efficacy is widely varied and poorly understood. This study combines experimental data and multi-component numerical reactive transport modeling to offer a more comprehensive understanding of the geochemical behavior of barite accumulation in shale matrices under conditions typical of fracturing operations. A variety of additives and conditions are individually tested in batch reactor experiments to identify the factors controlling barite precipitation. Our experimental results demonstrate a pH dependence in the rate of barite precipitation, which we use to develop a predictive model including a pH-dependent term that satisfactorily reproduces our observations. Further, this model is then extended to consider the behavior of three major shale samples of highly variable mineralogy (Eagle Ford, Marcellus, and Barnett). This data-validated model offers a reliable tool to predict and ultimately mitigate against secondary mineral accumulation in unconventional shale reservoirs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Accelerating Radiation Computations for Dynamical Models With Targeted Machine Learning and Code Optimization

Abstract Atmospheric radiation is the main driver of weather and climate, yet due to a complicated absorption spectrum, the precise treatment of radiative transfer in numerical weather and climate models is computationally unfeasible. Radiation parameterizations need to maximize computational efficiency as well as accuracy, and for predicting the future climate many greenhouse gases need to be included. In this work, neural networks (NNs) were developed to replace the gas optics computations in a modern radiation scheme (RTE+RRTMGP) by using carefully constructed models and training data. The NNs, implemented in Fortran and utilizing BLAS for batched inference, are faster by a factor of 1–6, depending on the software and hardware platforms. We combined the accelerated gas optics with a refactored radiative transfer solver, resulting in clear‐sky longwave (shortwave) fluxes being 3.5 (1.8) faster to compute on an Intel platform. The accuracy, evaluated with benchmark line‐by‐line computations across a large range of atmospheric conditions, is very similar to the original scheme with errors in heating rates and top‐of‐atmosphere radiative forcings typically below 0.1 K day −1 and 0.5 W m −2 , respectively. These results show that targeted machine learning, code restructuring techniques, and the use of numerical libraries can yield material gains in efficiency while retaining accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling Thermal Interactions between Buildings in an Urban Context

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly consider this term in the surface heat balance calculations and developed an algorithm to batch calculating the surrounding surfaces’ view factors using a ray-tracing technique. We conducted a case study with a district in the Chicago downtown area to evaluate the longwave radiant heat exchange effects between urban buildings. Results show that the impact of the longwave radiant effects on annual energy use ranges from 0.1% to 3.3% increase for cooling and 0.3% to 3.6% decrease for heating, varying among individual buildings. At the district level, the total energy demand increases by 1.39% for cooling and decreases 0.45% for heating. We also observe the longwave radiation can increase the exterior surface temperature by up to 10 °C for certain exterior surfaces. These findings justify a detailed and accurate way to consider the thermal interactions between buildings in an urban context to inform urban planning and design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Monitoring of U(VI) Bioreduction after ARCADIS demonstration at Savannah River Site F-Area - 15699

The F/H Area Seepage Basins located in the center of Savannah River Site (SRS) received approximately 1.8 billion gallons of acidic waste solutions. The acidic nature of the basin waste solutions triggered the mobilization of metals and radionuclides including soluble uranium (VI). SRS F-Area sediments are acidic and composed predominantly of quartz sand with varying amounts of fine-grained minerals and iron-oxides. In 2010, ARCADIS implemented in-situ injections of a carbohydrate substrate to establish anaerobic reactive zones for metal and radionuclide remediation via the Enhanced Anaerobic Reductive Precipitation (EARP) process at the SRS F-Area (Figure 2). The addition of the molasses substrate solution to groundwater produces anaerobic conditions with redox values in the methanogenic or sulfate-reducing range conducive to the reductive precipitation of uranium. Objectives: Determine the mineral composition of SRS fine clay fractions and identify all iron-oxide phases. Establish if ferrous carbonate and ferrous sulfide compounds will be present in the sediment after the bioreduction process has occurred. The presence of these compounds will indicate that anaerobic reductive conditions were established. Determine the types of reactions that might occur in the anaerobic aquifer. Determine if conditions will return to the initial state once samples are returned to aerobic conditions. Microcosm studies were prepared with SRS sediments treated using a basal medium solution augmented with sulfate and molasses as well as a trace metal solution. To create anaerobic conditions necessary for the experiment, a vinyl anaerobic airlock chamber from COY Lab Products was used to ensure that no oxygen reached the samples. Half of the samples were augmented with sulfate in an attempt to create iron sulfide and stabilize reduced uranium. A pH evolution study was conducted to find the type of pH changes that occurred in the samples. Samples were sieved to 180 mm before X-ray Diffraction (XRD) analysis was conducted to identify any mineralogical changes in the samples. The experimental patterns were compared against known XRD patterns for siderite and pyrite. Liquid samples were filtered through 0.45 mm filters and were diluted by a factor of 200 in nitric acid (1%) for ICP-OES analysis to determine the ferrous iron concentration. XRD analysis indicated that the sediments contained quartz, kaolinite, montmorillonite, and goethite. All of the samples have followed a similar trend, with a decline in the pH values. It was noted that samples amended with sulfates had slightly higher pH than sulfate-free samples. The pH drop can be attributed to the fermentation process of molasses and the natural acidity of SRS soil used for the microcosm study. The low pH conditions are believed to have hindered the formation of bicarbonate/carbonate ions used to form the iron precipitates. XRD results confirmed the assumption that with low pH values no iron compounds would precipitate in the samples. The experimental patterns for each sample was compared with the patterns for siderite and pyrite; the results for these analyses were negative. ICP-OES analysis confirmed that there is ferrous iron present in the samples. The highest iron concentration being 13312.8 ppb for Batch 1, Sample 1-2, the lowest were in Batch 2 Samples 2,3, and 4 which may be below the calibration curve. This may also be an indication that the iron has precipitated in these samples. Future work: Conduct ICP analysis on the Batch 2 samples using a lower dilution factor. Determine the types of reactions that might occur in the anaerobic aquifer. Verify the continued sequestration of U(VI) in relation to the possible re-oxidation of minerals from the bioreduction zone. Sulfate concentrations will be examined using an ion analysis technique. Determine pH levels, sulfate concentrations, and iron concentrations after re-oxygenation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Importance of Depth and Artificial Structure as Predictors of Female Red Snapper Reproductive Parameters

Abstract The Red Snapper Lutjanus campechanus is a structure‐associated species occurring across a wide depth range in the northern Gulf of Mexico. We used the random forest machine learning algorithm to understand which habitat and individual fish characteristics could predict reproductive parameters of female Red Snapper. We evaluated fish captured from 2016 to 2018 on three artificial structure types with various structure heights at depths of 100 m or less. Overall, we found that depth and month were important predictors for most reproductive parameters, but the type of structure (artificial reefs, oil platforms, and rigs‐to‐reefs structures) was not important. Maturity was correctly classified in 88.9% of the cases when using the random forest ensemble model, with important predictors including FL, depth, structure height, and month of collection. Spawning seasonality (measured as gonadosomatic index [GSI]) was correctly classified in 59.5% of the cases when using histology reproductive phase, FL, month, and depth variables. Reproductively active or inactive females were correctly classified in 89.3% of the cases using GSI, month, FL, and depth, while females in the developing versus spawning capable phases were correctly classified in 82.2% of the cases using GSI, FL, month, and depth. Histological indicators that show potential spawning within a 36‐h period were correctly classified 61.5% of the time, with the best predictors being depth, FL, GSI, and month. Stepwise regression indicated that month was the only factor that significantly predicted contrasts in relative batch fecundity, with significantly greater values in August compared to all other months. Our findings suggest that female Red Snapper reproductive effort is not consistently or well predicted by artificial structure type or height but that a combination of fish FL, month, and depth can predict reproductive characteristics of female Red Snapper.

Brown‐Peterson, Nancy J.↗
DOE OSTI2014

Remote auditing of radiotherapy facilities using optically stimulated luminescence dosimeters

Purpose: On 1 July 2012, the Australian Clinical Dosimetry Service (ACDS) released its Optically Stimulated Luminescent Dosimeter (OSLD) Level I audit, replacing the previous TLD based audit. The aim of this work is to present the results from this new service and the complete uncertainty analysis on which the audit tolerances are based. Methods: The audit release was preceded by a rigorous evaluation of the InLight® nanoDot OSLD system from Landauer (Landauer, Inc., Glenwood, IL). Energy dependence, signal fading from multiple irradiations, batch variation, reader variation, and dose response factors were identified and quantified for each individual OSLD. The detectors are mailed to the facility in small PMMA blocks, based on the design of the existing Radiological Physics Centre audit. Modeling and measurement were used to determine a factor that could convert the dose measured in the PMMA block, to dose in water for the facility's reference conditions. This factor is dependent on the beam spectrum. The TPR{sub 20,10} was used as the beam quality index to determine the specific block factor for a beam being audited. The audit tolerance was defined using a rigorous uncertainty calculation. The audit outcome is then determined using a scientifically based two tiered action level approach. Audit outcomes within two standard deviations were defined as Pass (Optimal Level), within three standard deviations as Pass (Action Level), and outside of three standard deviations the outcome is Fail (Out of Tolerance). Results: To-date the ACDS has audited 108 photon beams with TLD and 162 photon beams with OSLD. The TLD audit results had an average deviation from ACDS of 0.0% and a standard deviation of 1.8%. The OSLD audit results had an average deviation of −0.2% and a standard deviation of 1.4%. The relative combined standard uncertainty was calculated to be 1.3% (1σ). Pass (Optimal Level) was reduced to ≤2.6% (2σ), and Fail (Out of Tolerance) was reduced to >3.9% (3σ) for the new OSLD audit. Previously with the TLD audit the Pass (Optimal Level) and Fail (Out of Tolerance) were set at ≤4.0% (2σ) and >6.0% (3σ). Conclusions: The calculated standard uncertainty of 1.3% at one standard deviation is consistent with the measured standard deviation of 1.4% from the audits and confirming the suitability of the uncertainty budget derived audit tolerances. The OSLD audit shows greater accuracy than the previous TLD audit, justifying the reduction in audit tolerances. In the TLD audit, all outcomes were Pass (Optimal Level) suggesting that the tolerances were too conservative. In the OSLD audit 94% of the audits have resulted in Pass (Optimal level) and 6% of the audits have resulted in Pass (Action Level). All Pass (Action level) results have been resolved with a repeat OSLD audit, or an on-site ion chamber measurement.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Reactive Transport Models with Geomechanics to Mitigate Risks of CO2 Utilization and Storage

Reactivity of carbon dioxide (CO 2 ), rocks and brine is important in a number of practical situations in carbon dioxide sequestration. Injectivity of CO 2 will be affected by near wellbore dissolution or precipitation. Natural fractures or faults containing specific minerals may reactivate leading to induced seismicity. In this project, we first examined if the reactions between CO 2 , brine and rocks affect the nature of the porous medium and properties including petrophysical properties in the timeframe of the injection operations. This was done by carrying out experiments at sequestration conditions (2000 psi for corefloods and 2400 psi for batch experiments, and 600°C) with three different types of rocks – sandstone, limestone and dolomite. Experiments were performed in batch mode and corefloods were conducted over a two-week period. Batch experiments were performed with samples of differing surface area to understand the impact of surface area on overall reaction rates. Toughreact, a reactive transport model was used to interpret and understand the experimental results. The role of iron in dissolution and precipitation reactions was observed to be significant. Iron containing minerals – siderite and ankerite dissolved resulting in changes in porosity and permeability. Corefloods and batch experiments revealed similar patterns. With the right cationic balance, there is a possibility of precipitation of iron bearing carbonates. The results indicate that during injection operations mineralogical changes may lead to injectivity enhancements near the wellbore and petrophysical changes elsewhere in the system. Limestone and dolomite cores showed consistent dissolution at the entrance of the core. The dissolution led to formation of wormholes and interconnected dissolution zones. Results indicate that near wellbore dissolution in these rock-types may lead to rock failure. Micro-CT images of the cores before and after the experiments revealed that an initial high-permeability pathway facilitated the formation of wormholes. The peak cation concentrations and general trends were matched using Toughreact. Batch reactor modeling showed that the geometric factors obtained using powder data that related effective surface area to the BET surface area had to be reduced for fractured samples and cores. This indicates that the available surface area in consolidated samples is lower than that deduced from powder experiments. Field-scale modeling of reactive transport and geomechanics was developed in parallel at Idaho National Laboratory. The model is able to take into account complex chemistry, and consider interactions of natural fractures and faults. Poroelastic geomechanical considerations are also included in the model.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Cholesky-based experimental design for Gaussian process and kernel-based emulation and calibration.

Gaussian processes and other kernel-based methods are used extensively to construct approximations of multivariate data sets. The accuracy of these approximations is dependent on the data used. This paper presents a computationally efficient algorithm to greedily select training samples that minimize the weighted L p error of kernel-based approximations for a given number of data. The method successively generates nested samples, with the goal of minimizing the error in high probability regions of densities specified by users. The algorithm presented is extremely simple and can be implemented using existing pivoted Cholesky factorization methods. Training samples are generated in batches which allows training data to be evaluated (labeled) in parallel. For smooth kernels, the algorithm performs comparably with the greedy integrated variance design but has significantly lower complexity. Numerical experiments demonstrate the efficacy of the approach for bounded, unbounded, multi-modal and non-tensor product densities. We also show how to use the proposed algorithm to efficiently generate surrogates for inferring unknown model parameters from data using Bayesian inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

malbacR: A Package for Standardized Implementation of Batch Correction Methods for Omics Data

Mass spectrometry is a powerful tool for identifying and analyzing small molecules, such as metabolites and lipids, in com-plex biological samples. Liquid chromatography and gas chromatography mass spectrometry studies quite commonly in-volve large numbers of samples, which can require significant time for sample preparation and analyses. To accommodate such studies, the samples are commonly split into batches. Inevitably, variations in sample handling, temperature fluctua-tion, imprecise timing, column degradation and other factors result in systematic errors or biases of the measured abundances between the batches. Numerous methods are available via R packages to assist with batch correction for small molecule om-ics data; however, since these methods were developed by different research teams, the algorithms are available in separate R packages, each with different data input and output formats. We introduce the malbacR package which consolidates eleven common batch effect correction methods for small molecule omics data into one place so users can easily implement and compare: pareto scaling, power scaling, range scaling, ComBat, EigenMS, NOMIS, RUV-random, QC-RLSC, WaveI-CA2.0, TIGER, and SERRF. The malbacR package standardizes data input and output formats across these batch correction methods. The package works in conjunction with the pmartR package, allowing users to seamlessly include batch effect cor-rection in a pmartR workflow without needing any additional data manipulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Effects of Blending and In-Tank Pretreatment on Direct Feed Hanford High Level Waste Vitrification - 18434

A direct feed high level waste (DFHLW) option is under consideration for early operations of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). In this option, the Pretreatment Facility would be bypassed in order to support an earlier start-up of the HLW Vitrification Facility. For HLW, this would mean that ultrafiltration and caustic leaching that would otherwise have been performed either would not be performed or would be replaced by interim pretreatment functions such as in-tank washings. These changes could result in higher aluminum contents, higher chromium contents, higher fractions of supernate, and lower solids contents in the HLW feed. As a result, glass formulations and downstream vitrification operations will be impacted. In the present work, we investigate the effects of various waste blending and in-tank pretreatment scenarios on DFHLW glass waste loadings, canister counts, and processing rates. Eleven source tanks and five waste groups were selected for the studies of waste blending. In addition, the five waste groups selected were the subjects of an in-tank pretreatment study. Glass property-composition models and melter test data were used to calculate waste loadings, canister counts, processing rates, and treatment durations for a range of DFHLW scenarios. The processing scenarios were defined by the types of waste blending and in-tank pretreatment that were assumed. Blending cases were evaluated that ranged between the 'No Blend' and 'Total Blend' extremes and included pairwise blending (blending of two source tanks, either completely or in various proportions) and macro-batches formed from various combinations of the source tanks. Over 36,000 possible pairwise blending scenarios were evaluated and an optimal retrieval/blending sequence was identified. The waste loading of this optimal sequence is within 0.03 wt% of the 'Total Blend' case. Further, a total of 38 retrieval sequences were identified that have waste loadings within 0.1 wt% of the 'Total Blend' case. To evaluate the effects of in-tank pretreatment, an in-tank wash/settle/decant process was assumed and tank-specific wash factors were employed. Washing of the macro-batch blends gave a general increase in HLW loading, decrease in canister count, and decrease in glass yield. Glass yields are towards the low end of the values expected for the WTP, which could lead to lower than nominal glass production rates. The waste loading increases and canister count reductions with washing were small for two of the wastes indicating that direct treatment of the unwashed waste may be practical. For wastes that are relatively low in sulfate and halides, excessive washing is counterproductive. The results highlight the importance of maintaining high solids content in the HLW feed to maintain glass production rates. The results also illustrate that the optimum washing strategy will need to be evaluated on a tank-to-tank basis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Isotopic insights into microbial sulfur cycling in oil reservoirs

Microbial sulfate reduction in oil reservoirs (biosouring) is often associated with secondary oil production where seawater containing high sulfate concentrations (~28 mM) is injected into a reservoir to maintain pressure and displace oil. The sulfide generated from biosouring can cause corrosion of infrastructure, health exposure risks, and higher production costs. Isotope monitoring is a promising approach for understanding microbial sulfur cycling in reservoirs, enabling early detection of biosouring, and understanding the impact of souring. Microbial sulfate reduction is known to result in large shifts in the sulfur and oxygen isotope compositions of the residual sulfate, which can be distinguished from other processes that may be occurring in oil reservoirs, such as precipitation of sulfate and sulfide minerals. Key to the success of this method is using the appropriate isotopic fractionation factors for the conditions and processes being monitored. For a set of batch incubation experiments using a mixed microbial culture with crude oil as the electron donor, we measured a sulfur fractionation factor for sulfate reduction of -30 . We have incorporated this result into a simplified 1D reservoir reactive transport model to highlight how isotopes can help discriminate between biotic and abiotic processes affecting sulfate and sulfide concentrations. Modeling results suggest that monitoring sulfate isotopes can provide an early indication of souring for reservoirs with reactive iron minerals that can remove the produced sulfide, especially when sulfate reduction occurs in the mixing zone between formation waters (FW) containing elevated concentrations of volatile fatty acids (VFAs) and injection water (IW) containing elevated sulfate. In addition, we examine the role of reservoir thermal, geochemical, hydrological, operational and microbiological conditions in determining microbial souring dynamics and hence the anticipated isotopic signatures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Performance and kinetic study of semi-dry thermophilic anaerobic digestion of organic fraction of municipal solid waste

Highlights: • Performance of the reactor was evaluated by the degradation of volatile solids. • Biogas yield at the end of the digestion was 52.9 L/kg VS. • Value of reaction rate constant, k, obtained was 0.0249 day{sup −1}. • During the digestion 66.7% of the volatile solid degradation was obtained. - Abstract: Anaerobic digestion (AD) of the organic fraction of municipal solid waste (OFMSW) is promoted as an energy source and waste disposal. In this study semi dry anaerobic digestion of organic solid wastes was conducted for 45 days in a lab-scale batch experiment for total solid concentration of 100 g/L for investigating the start-up performances under thermophilic condition (50 °C). The performance of the reactor was evaluated by measuring the daily biogas production and calculating the degradation of total solids and the total volatile solids. The biogas yield at the end of the digestion was 52.9 L/kg VS (volatile solid) for the total solid (TS) concentration of 100 g/L. About 66.7% of the volatile solid degradation was obtained during the digestion. A first order model based on the availability of substrate as the limiting factor was used to perform the kinetic studies of batch anaerobic digestion system. The value of reaction rate constant, k, obtained was 0.0249 day{sup −1}.

09 BIOMASS FUELS↗
DOE OSTI2017

An Integrated Approach to Parameter Learning in Infinite-Dimensional Space

The availability of sophisticated modern physics codes has greatly extended the ability of domain scientists to understand the processes underlying their observations of complicated processes, but it has also introduced the curse of dimensionality via the many user-set parameters available to tune. Many of these parameters are naturally expressed as functional data, such as initial temperature distributions, equations of state, and controls. Thus, when attempting to find parameters that match observed data, being able to navigate parameter-space becomes highly non-trivial, especially considering that accurate simulations can be expensive both in terms of time and money. Existing solutions include batch-parallel simulations, high-dimensional, derivative-free optimization, and expert guessing, all of which make some contribution to solving the problem but do not completely resolve the issue. In this work, we explore the possibility of coupling together all three of the techniques just described by designing user-guided, batch-parallel optimization schemes. Our motivating example is a neutron diffusion partial differential equation where the time-varying multiplication factor serves as the unknown control parameter to be learned. We find that a simple, batch-parallelizable, random-walk scheme is able to make some progress on the problem but does not by itself produce satisfactory results. After reducing the dimensionality of the problem using functional principal component analysis (fPCA), we are able to track the progress of the solver in a visually simple way as well as viewing the associated principle components. This allows a human to make reasonable guesses about which points in the state space the random walker should try next. Thus, by combining the random walker's ability to find descent directions with the human's understanding of the underlying physics, it is possible to use expensive simulations more efficiently and more quickly arrive at the desired parameter set.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Preliminary Neutronics Design and Analysis of the Fast Modular Reactor

General Atomics is developing a new 100-MW(thermal) fast modular reactor (FMR) that provides safe, carbon-free electricity and is capable of incremental capacity additions. The modular design allows it to be factory built and assembled onsite to keep the capital cost low, while the use of dry cooling facilitates siting to complement renewables in nearly any location. The FMR uses high-assay low-enriched uranium-dioxide fuel encapsulated by recognized irradiationresistant silicon carbide composite (SiGA®) cladding that is derisked in the current accident-tolerant fuel program. The FMR fuel assembly is a hexagonal fuel bundle of 120 fuel rods. The total length of the fuel assembly is less than 4 m, with an active fuel length of 1.8 m. The fuel assemblies are configured in an annular core that is located and supported by the reactor internals. The coolant material is helium at a normal operating pressure of 7 MPa. The core is surrounded by zirconium silicide (Zr 3 Si 2 ) and graphite reflector blocks. The fuel, coolant, internals, and reflectors are contained within a reactor pressure vessel. Here, the preliminary nuclear design and analysis established the arrangement of the active core and reflector blocks. The nuclear design analyses of the FMR defined the design parameters, such as fuel enrichments, excess reactivity, fueling scheme, fuel cycle, power distribution, and control rod worth. The preliminary conceptual design determined the three-batch fueling scheme with the allowable total power peaking factor of 1.5. The average discharge burnup is 100 GW days per ton of uranium.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Linear complexity

We present factorization and solution phases for a new linear complexity direct solver designed for concurrent batch operations on fine-grained parallel architectures, for matrices amenable to hierarchical representation. We focus on the strong-admissibility-based $\mathscr{H}^{2}$ format, where strong recursive skeletonization factorization compresses remote interactions. We build upon previous implementations of $\mathscr{H}^{2}$ matrix construction for efficient factorization and solution algorithm design, which are illustrated graphically in stepwise detail. The algorithms are ‘blackbox’ in the sense that the only inputs are the matrix and right-hand side, without analytical or geometrical information about the origin of the system. We demonstrate linear complexity scaling in both time and memory on four representative families of dense matrices up to one million in size. Parallel scaling up to 16 threads is enabled by a multi-level matrix graph coloring and avoidance of dynamic memory allocations thanks to prefix-sum memory management. An experimental backward error analysis is included. We break down the timings of different phases, identify phases that are memory-bandwidth limited, and discuss alternatives for phases that may be sensitive to the trend to employ lower precisions for performance.

Boukaram, Wajih↗
DOE OSTI2023

Mechanistic insights into Cr(VI) removal by a combination of zero-valent iron and pyrite

Recent studies have revealed that a combination of zero-valent iron (ZVI) and pyrite (FeS 2 ) can effectively remove (Cr(VI)) from water, but the reasons behind this synergistic effect are still unclear. Our batch experiments showed that dissolved oxygen (DO) is a critical factor in the improved removal of Cr(VI) by ZVI and pyrite. When 0.08 g/L pyrite was combined with 0.5 g/L ZVI in the presence of DO, total Cr was reduced from 10 mg/L to 0.02 mg/L within 6 h. Conversely, in the absence of DO, total Cr was only reduced to 5.6 mg/L. DO oxidation of pyrite produced protons that promote ZVI corrosion, and mixing pyrite with water creates dissolved sulfide, which also contributes to the improved removal of Cr(VI). Here, electron microscopy images and X-ray absorption near edge structure analyses revealed that the presence of dissolved sulfide led to the formation of ferrous sulfide precipitates on the ZVI surface, preventing the formation of a passivating layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

VERSE-LC TCCR Model Calibration using Batch 1A, Batch 2, and Batch 3 Column Data

The objective of this work is to utilize on-line gamma monitoring data collected during Tank Closure Cesium Removal (TCCR) Column Batch 3 operations to calibrate the parameters (essentially, the correction/dilution factors (CF or DF)) used in the VERSE-LC models for the prediction of cesium breakthrough while processing Savannah River Site (SRS) Tank 10H dissolved saltcake High-Level Waste through a packed cylindrical bed of Crystalline Silicotitanate (CST). Calibrated VERSE-LC models could be applied to aid in evaluating future TCCR operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗