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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 sources NASA NTRS DOE OSTI

DOE OSTI2022

Characterization of Tank 9H Salt Dissolution Batch 2B in Support of Tank Closure Cesium Removal (TCCR) 1A Batch 2 Preparations

Savannah River Mission Completion (SRMC) is currently preparing the second batch of material to be processed through the Tank Closure Cesium Removal (TCCR) 1A system. The feed for TCCR 1A consists of dissolved saltcake from Tank 9H. The second batch of salt to make up processing Batch 2 (Batch 2B) has recently been dissolved in Tank 9H and transferred to Tank 10H where it was composited with the first part of the batch (Batch 2A) in preparation for processing through the TCCR 1A unit. Savannah River National Laboratory (SRNL) received samples from the recent batch (2B) of dissolved salt for characterization. Two samples from Batch 2B were received for characterization, a surface sample and a variable depth sample (VDS). Neither sample contained significant solids, although the VDS appeared slightly cloudy as compared to the surface sample. The sodium concentrations of both the surface and VDS filtrate samples were approximately 5.8 M, and the 137 Cs activity was 9.8E+07 dpm/mL in the surface sample and 9.5E+07 dpm/mL in the VDS. The total Cs concentrations were 2.5 mg/L and 2.4 mg/L in the surface sample and VDS, respectively, using the gamma activity and the Cs isotopic ratios determined by ICP-MS. The alpha activity was below the detection limit in both samples. Nitrate was the dominant anion present, and the samples were primarily concentrated sodium nitrate solutions with hydroxide, nitrite, and carbonate present at 0.1 – 0.2 M. In general, the Batch 2B samples were more dilute than the previously characterized Batch 2A samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Characterization of Tank 9h Salt Dissolution Batch 2C In Support of Tank Closure Cesium Removal (TCCR) 1A Batch 2 Preparations

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Characterization of Tank 9H Salt Dissolution Batch 2A in Support of Tank Closure Cesium Removal (TCCR) 1A Batch 2 Preparations

Savannah River Remediation (SRR) is currently preparing the second batch of material to be processed through the Tank Closure Cesium Removal (TCCR) 1A system. The feed for TCCR 1A consists of dissolved saltcake from Tank 9H. The first batch of salt to make up Batch 2 (Batch 2A) has been dissolved in Tank 9H and will later be transferred to Tank 10H. Savannah River National Laboratory (SRNL) received samples from the batch of dissolved salt for characterization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Enhancement of oxidative dehydrogenation over cerium-doped nickel niobium catalysts and analysis of batch-to-batch variability

Nickel based catalysts are inexpensive and efficient for use in the oxidative dehydrogenation of ethane. NiO doped with niobium and cerium shows increased ethylene production. Small amounts of Ce doped onto a NiNb catalyst led to increased Ni activity. The catalyst that had the highest ethylene production rate per g of catalyst had 1 atom% Ce, 86 at% Ni, and 13 at% Nb (1CeNiNb) while, if surface area is incorporated into the calculation, the catalyst that had the highest ethylene production rate per m 2 was the 0.5CeNiNb catalyst. The ethylene production rates of these Ce-containing catalysts are 27 %-127 % higher than those with NiNb alone previously reported in the literature. Here, to fully understand how cerium affects the NiNb catalyst, the Ce content and effect on active sites has been fully characterized over multiple batches. In doing this, light has been shed on batch-to-batch variability. Characterization techniques such as powder X-ray diffraction, hydrogen temperature programmed reduction, X-ray photoelectron spectroscopy, synchrotron X-ray absorption spectroscopy, and methanol adsorption were used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Benzo[d]thiazole Based Wide Bandgap Donor Polymers Enable 19.54% Efficiency Organic Solar Cells Along with Desirable Batch-to-Batch Reproducibility and General Applicability

The limited selection pool of high-performance wide bandgap (WBG) polymer donors is a bottleneck problem of the nonfullerene acceptor (NFA) based organic solar cells (OSCs) that impedes the further improvement of their photovoltaic performances. In this work, a series of new WBG polymers, namely PH-BTz, PS-BTz, PF-BTz, and PCl-BTz, are developed by using the bicyclic difluoro-benzo[d]thiazole (BTz) as the acceptor block and benzo[1,2-b:4,5-b']dithiophene (BDT) derivatives as the donor units. By introducing S, F, and Cl atoms to the alkylthienyl sidechains on BDT, the resulting polymers exhibit lowered energy levels and enhanced aggregation properties. The fluorinated PBTz-F not only exhibits a low-lying HOMO level, but also has stronger face-on packing order and results in more uniform fibril-like interpenetrating networks in the related PF-BTz:L8-BO blend. A high-power conversion efficiency (PCE) of 18.57% is achieved. Moreover, PBTz-F also exhibits a good batch-to-batch reproducibility and general applicability. In addition, ternary blend OSCs based on the host PBTz-F:L8-BO blend and PM6 guest donor exhibits a further enhanced PCE of 19.54%, which is among the highest values of OSCs.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Tolerance of engineered Rhodosporidium toruloides to sorghum hydrolysates during batch and fed-batch lipid production

Abstract Background Oleaginous yeasts are a promising candidate for the sustainable conversion of lignocellulosic feedstocks into fuels and chemicals, but their growth on these substrates can be inhibited as a result of upstream pretreatment and enzymatic hydrolysis conditions. Previous studies indicate a high citrate buffer concentration during hydrolysis inhibits downstream cell growth and ethanol fermentation in Saccharomyces cerevisiae . In this study, an engineered Rhodosporidium toruloides strain with enhanced lipid accumulation was grown on sorghum hydrolysate with high and low citrate buffer concentrations. Results Both hydrolysis conditions resulted in similar sugar recovery rates and concentrations. No significant differences in cell growth, sugar utilization rates, or lipid production rates were observed between the two citrate buffer conditions during batch fermentation of R. toruloides . Under fed-batch growth on low-citrate hydrolysate a lipid titer of 16.7 g/L was obtained. Conclusions Citrate buffer was not found to inhibit growth or lipid production in this engineered R. toruloides strain, nor did reducing the citrate buffer concentration negatively affect sugar yields in the hydrolysate. As this process is scaled-up, $131 per ton of hydrothermally pretreated biomass can be saved by use of the lower citrate buffer concentration during enzymatic hydrolysis. Graphical Abstract

09 BIOMASS FUELS↗

DOE OSTI2023

Data for Tolerance of Engineered Rhodosporidium toruloides to Sorghum Hydrolysates During Batch and Fed-Batch Lipid Production

Oleaginous yeasts are a promising candidate for the sustainable conversion of lignocellulosic feedstocks into fuels and chemicals, but their growth on these substrates can be inhibited as a result of upstream pretreatment and enzymatic hydrolysis conditions. Previous studies indicate a high citrate buffer concentration during hydrolysis inhibits downstream cell growth and ethanol fermentation in Saccharomyces cerevisiae . In this study, an engineered Rhodosporidium toruloides strain with enhanced lipid accumulation was grown on sorghum hydrolysate with high and low citrate buffer concentrations. Both hydrolysis conditions resulted in similar sugar recovery rates and concentrations. No significant differences in cell growth, sugar utilization rates, or lipid production rates were observed between the two citrate buffer conditions during batch fermentation of R. toruloides . Under fed-batch growth on low-citrate hydrolysate a lipid titer of 16.7 g/L was obtained. Citrate buffer was not found to inhibit growth or lipid production in this engineered R. toruloides strain, nor did reducing the citrate buffer concentration negatively affect sugar yields in the hydrolysate. As this process is scaled-up, $131 per ton of hydrothermally pretreated biomass can be saved by use of the lower citrate buffer concentration during enzymatic hydrolysis.

Conversion↗

NASA NTRS1992

A high-fidelity batch simulation environment for integrated batch and piloted air combat simulation analysis

A batch air combat simulation environment known as the Tactical Maneuvering Simulator (TMS) is presented. The TMS serves as a tool for developing and evaluating tactical maneuvering logics and to evaluate the tactical implications of perturbations to aircraft performance or supporting systems. The TMS is capable of simulating air combat between any number of engagement participants, with practical limits imposed by computer memory and processing power. Aircraft are modeled using equations of motion, control laws, aerodynamics and propulsive characteristics, and databases representative of a modern high-performance aircraft with and without thrust-vectoring capability are included. A Tactical Autopilot is implemented in the aircraft simulation model to convert guidance commands issued by computerized maneuvering logics in the form of desired angle-of-attack and wind axis-bank angle into inputs to the inner-loop control augmentation system of the aircraft.

Goodrich, Kenneth H.↗

NASA NTRS1992

A High-Fidelity Batch Simulation Environment for Integrated Batch and Piloted Air Combat Simulation Analysis

A batch air combat simulation environment known as the Tactical Maneuvering Simulator (TMS) is presented. The TMS serves as a tool for developing and evaluating tactical maneuvering logics. The environment can also be used to evaluate the tactical implications of perturbations to aircraft performance or supporting systems. The TMS is capable of simulating air combat between any number of engagement participants, with practical limits imposed by computer memory and processing power. Aircraft are modeled using equations of motion, control laws, aerodynamics and propulsive characteristics equivalent to those used in high-fidelity piloted simulation. Databases representative of a modern high-performance aircraft with and without thrust-vectoring capability are included. To simplify the task of developing and implementing maneuvering logics in the TMS, an outer-loop control system known as the Tactical Autopilot (TA) is implemented in the aircraft simulation model. The TA converts guidance commands issued by computerized maneuvering logics in the form of desired angle-of-attack and wind axis-bank angle into inputs to the inner-loop control augmentation system of the aircraft. This report describes the capabilities and operation of the TMS.

Goodrich, Kenneth H.↗

DOE OSTI2023

xSDK-batched Subcontract - Ginkgo Batched Iterative Solver Development (Final Report)

Iterative solvers are fundamentally different from direct solvers in terms of execution as they generally do not execute a pre-defined sequence of operations or steps, but adapt the number of iterations to the specific problem and the preset solution quality. Generally, the adaptation of the iteration count to the problem is realized by monitoring the solver convergence and stopping the iteration process once the monitored metric, e.g., the residual norm, hits a pre-defined threshold. When addressing a set of problems with different properties, it is necessary to monitor the threshold for each problem individually and break up the SIMD execution style to avoid excess iterations for “easier” problems. Ginkgo integrates a simple but customizable stopping criterion for the residual norm and generally uses a pre-defined (relative or absolute) residual norm as the stopping criterion. In order to avoid the overhead of launching a kernel at every iteration, the iteration convergence and iteration control is part of the solver kernel. Each thread maintains its own copy of the iteration count.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Batched Sparse Linear Algebra (Final Report for Subcontract B648960)

This report finalizes design specifications for developing batched kernels for small tensor operations for unassembled matrix-free iterative solvers, batched solvers for partially assembled operators, and batched solvers with support for various sparse formats. The outcome of the project milestones is a set of interfaces to Batched Sparse LA solvers running on hardware accelerators for use in ECP Libraries and Applications. It is part of the development of sparse batched kernels, solvers/preconditioners as well as creating interoperability in xSDK libraries with sparse and dense batched functions to benefit ECP applications. The participants included representatives from ECP libraries (not limited to the xSDK project), applications, and vendors (AMD, Intel, and NVIDIA). Batched sparse linear algebra solvers form the new frontier for algorithmic development and performance engineering. Many applications (ECP and non-ECP alike) require simultaneous solutions of small linear systems of equations that are structurally sparse. To move towards high hardware utilization, it is important to provide these applications with appropriate interfaces to efficient batched sparse solvers running on modern hardware accelerators. We present interface designs in use by HPC software libraries supporting batched sparse linear algebra and the development of sparse batched kernel codes for solvers and preconditioners. We also address the potential interoperability opportunities to keep the software portable between the major hardware accelerators from AMD, Intel, and NVIDIA. The presented interface specifications includes batched band, sparse iterative, and sparse direct solvers. This report summarizes progress in Kokkos Kernels and the xSDK libraries MAGMA, Ginkgo, hypre, SUNDIALS, and SuperLU_dist.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 44 and 49 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS). Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 44 and 49, which correspond to material from the processing of Salt Batches (StB) 12 and 11, respectively, are reported herein. The unwashed dried solids of the PRFT Batches 44 and 49 are predominately MST, ~63-59% MST. The two batches have a much higher amount of Fe, Mn, and Ni compared to all previous batches. For Batch 44 this appears to be due to the use of a sludge simulant filter aid during processing of StB 12 and for Batch 49, it is possibly due to the larger amount of insoluble solids for StB 11 in comparison to all previous salt batches. Like previous PRFT batches, a significant amount of the unwashed dried solids are alkaline earth metals. The total sulfate, in mg/kg of slurry, for PRFT Batches 44 and 49 is 119 and 139, respectively, which is well below the current sulfate concentration used in Material Tracking Program calculations and is in agreement with DWPF laboratory sulfate measurements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Tula: Optimizing Time, Cost, and Generalization in Distributed Large-Batch Training

Distributed training increases the number of batches processed per iteration either by scaling-out (adding more nodes) or scaling-up (increasing the batch-size). However, the largest configuration does not necessarily yield the best performance. Horizontal scaling introduces additional communication overhead, while vertical scaling is constrained by computation cost and device memory limits. Thus, simply increasing the batch-size leads to diminishing returns: training time and cost decrease initially but eventually plateaus, creating a knee-point in the time/cost vs. batch-size pareto curve. The optimal batch-size therefore depends on the underlying model, data and available compute resources. Large batches also suffer from worse model quality due to the well-known “generalization gap”. In this paper, we present Tula, an online service that automatically optimizes time, cost, and convergence quality for large-batch training of convolutional models. It combines parallel-systems modeling with statistical performance prediction to identify the optimal batchsize. Tula predicts training time and cost within 7.5−14% error across multiple models, and achieves up to 20× overall speedup and improves test accuracy by ≈9% on average over standard large-batch training on various vision tasks, thus successfully mitigating the generalization gap and accelerating training at the same time.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗

DOE OSTI2024

Batched sparse direct solver design and evaluation in SuperLU_DIST

Over the course of interactions with various application teams, the need for batched sparse linear algebra functions has emerged in order to make more efficient use of the GPUs for many small and sparse linear algebra problems. In this paper, we present our recent work on a batched sparse direct solver for GPUs. The sparse LU factorization is computed by the levels of the elimination tree, leveraging the batched dense operations at each level and a new batched Scatter GPU kernel. The sparse triangular solve is computed by the level sets of the directed acyclic graph (DAG) of the triangular matrix. Batched operations overcome the large overhead associated with launching many small kernels. For medium sized matrix batches with not-so-small bandwidth, using an NVIDIA A100 GPU, our new batched sparse direct solver is orders of magnitude faster than a batched banded solver and uses less than one-tenth of the memory.

Boukaram, Wajih↗

NASA NTRSDate not supplied

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗

DOE OSTI2021

In-situ X-ray and visual observation of foam morphology and behavior at the batch-melt interface during melting of simulated waste glass

We report to attain a basic understanding of the primary foam structure and behavior, which affects the heat and mass transfer and the efficiency of the glass melting process, we investigated the primary foam layer under the glass batch floating on molten glass. The primary foam affects mass transfer during batch melting, in turn affecting the melting process. The recently performed direct in-situ three-dimensional X-ray computed tomography of the batch melting in a laboratory-scale melter vessel allowed us to visualize the features of the reacting batch layer and the foam that develops at its bottom, though with an insufficient resolution of images. In this study, we obtained better temporal and spatial resolution using the two-dimensional X-ray radiography and visual observation of the structure and behavior of transient primary foam as it formed and decayed. As soon as the batch was charged onto the melt surface, foam bubbles began to evolve, grow, and coalesce, forming a primary foam layer, 5-10 mm thick, within tens of seconds. This foam layer was sustained by ongoing gas evolving reactions counterbalanced by bubble coalescence into cavities that moved sideways and escaped to the atmosphere. Eventually, the entire remaining batch turned into foam that gradually decayed at the melt surface. The decay rate agreed with literature observations of surface foam produced by secondary foaming.

36 MATERIALS SCIENCE↗

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↗