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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Characterization of Tank 51 Sludge Slurry Samples (HTF-51-17-67, -68, -69, -74, -75, and -76) in Support of Sludge Batch 10 Processing

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) Engineering (SRR-E) to provide sample characterization and analyses of Tank 51 sludge samples in support of Sludge Batch (SB) 10. The six Tank 51 sludge samples were sampled and delivered to SRNL in August of 2017. These six Tank 51 sludge samples, after undergoing physical characterizations which included rheology, weight percent total solid, dissolved solids and density measurements, were combined into one composite Tank 51 sample and analyzed for corrosion controls analytes, select radionuclides, chemical elements, density and weight percent total solids.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Characterization of Tank 51 Sludge Slurry Samples (HTF-51-17-44/ HTF-51-17-48) in Support of Sludge Batch 10 Processing

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) Engineering (SRR-E) to provide sample characterization and analyses of Tank 51 sludge samples in support of Sludge Batch (SB) 10. The two Tank 51 sludge samples were sampled and delivered to SRNL in May of 2017. These two Tank 51 sludge samples were combined into one composite sample and analyzed for corrosion controls analytes, select radionuclides, chemical elements, density and weight percent total solids and aluminum hydroxides (gibbsite and boehmite) by x-ray diffraction.

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

Microfluidic, One-Batch Synthesis of Pd Nanocrystals on N-Doped Carbon in Surfactant-Free Deep Eutectic Solvents for Formic Acid Electrochemical Oxidation

One of the grand challenges that impedes practical applications of nanomaterials is the lack of robust manufacturing methods that are scalable, cheap, and environmentally friendly. In this work, we address this challenge by developing a microfluidic approach that produces surfactant-free Pd nanocrystals (NCs) uniformly loaded on N-doped porous carbon in a one-batch process. The deep eutectic solvent (DES) prepared from choline chloride and ethylene glycol was employed as a novel synthesis solvent, and its extended hydrogen networks and abundant ionic species effectively stabilize Pd facets and confine nanocrystal sizes without using surfactants. The microreactors provide faster heat exchange and more uniform mass transport, which in combination with DES produced Pd NCs with better-defined shape and predominately exposed Pd (100) facet. Furthermore, we describe that the N-doped functional groups in porous carbon direct dense and uniform heterogeneous growth of Pd NCs in a one-batch process, thereby eliminating a separate catalyst deposition step that is often involved in conventional synthesis. The Pd NCs in the one-batch-produced Pd/C catalysts exhibited a size distribution of similar to ~13 ± 3.5 nm and a high ESCA of 46.0 m 2 /g and delivered 362 mA/mg for formic acid electrochemical oxidation with improved stability, demonstrating the unique potentials of microfluidic reactors and DES for the controllable and scalable synthesis of electrocatalyst materials for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Scalable continuous flow synthesis of ZnO nanorod arrays in 3-D ceramic honeycomb substrates for low-temperature desulfurization

Scalable and cost-effective synthesis and assembly of technologically important nanostructures in three-dimensional (3D) substrates hold keys to bridge the demonstrated nanotechnologies in academia with industrially relevant scalable manufacturing. In this paper, using ZnO nanorod arrays as an example, a hydrothermal-based continuous flow synthesis (CFS) method is successfully used to integrate the nano-arrays in multi-channeled monolithic cordierite. Compared to the batch process, CFS enhances the average growth rate of nano-arrays by 125%, with the average length increasing from 2 μm to 4.5 μm within the same growth time of 4 hours. The precursor utilization efficiency of CFS is enhanced by 9 times compared to that of batch process by preserving the majority of precursors in recyclable solution. Computational fluid dynamic simulation suggests a steady-state solution flow and mass transport inside the channels of honeycomb substrates, giving rise to steady and consecutive growth of ZnO nano-arrays with an average length of 10 μm in 12 h. The monolithic ZnO nano-array-integrated cordierite obtained through CFS shows enhanced low-temperature (200 °C) desulfurization capacity and recyclability in comparison to ZnO powder wash-coated cordierite. This can be attributed to exposed ZnO {101¯0} planes, better dispersion and stronger interactions between sorbent and reactant in the ZnO nanorod arrays, as well as the sintering-resistance of nano-array configurations during sulfidation–regeneration cycles. Finally, with the demonstrated scalable synthesis and desulfurization performance of ZnO nano-arrays, a promising, industrially relevant integration strategy is provided to fabricate metal oxide nano-array-based monolithic devices for various environmental and energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Continuous Water Quality Sensing for FGD Wastewater

The coal fired plant power industry requires new solutions for on-line monitoring of flue gas desulfurization (FGD) wastewaters for regulated trace metals to reduce recurring operating and off-site laboratory analysis costs and provide a high level of confidence of compliance with state and federal discharge guidelines. The University of Alabama at Birmingham (UAB) developed an integrated water sensor package for continuous water quality monitoring of flue gas desulfurization (FGD) wastewaters for concentration measurements of Selenium (Se). UAB utilized a diverse team of University Professors/Staff Members/Student(s) (Engineering and Innovative Technology Development Group), a University Affiliated Research Institution from the local area (Southern Research), and a cost sharing Industry Partner (Metrohm). The team developed and validated a proprietary wet chemistry batch process for water sample preparation; and implemented this process as a fully automated on-line monitor prototype system. This prototype system’s performance was evaluated in both the laboratory and during in-field deployment to a coal fired power plant. In both environments it was found that the prototype system was unable to recreate the batch process’s success at preparing FGD water samples for total Se measurements with a commercial-off-the-shelf (COTS) cyclic anodic stripping voltammetry (CSV) system. Through this experience, UAB has provided insight into a number of specific areas where improvements can be made with respect to the COTS systems used in this project to yield a more complete and competitive industry solution for on-line monitoring of total Se in industrial wastewater.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Continuous Water Quality Sensing for FGD Wastewater

The coal fired plant power industry requires new solutions for on-line monitoring of flue gas desulfurization (FGD) wastewaters for regulated trace metals to reduce recurring operating and off-site laboratory analysis costs and provide a high level of confidence of compliance with state and federal discharge guidelines. The University of Alabama at Birmingham (UAB) developed an integrated water sensor package for continuous water quality monitoring of flue gas desulfurization (FGD) wastewaters for concentration measurements of Selenium (Se). UAB utilized a diverse team of University Professors/Staff Members/Student(s) (Engineering and Innovative Technology Development Group), a University Affiliated Research Institution from the local area (Southern Research), and a cost sharing Industry Partner (Metrohm). The team developed and validated a proprietary wet chemistry batch process for water sample preparation; and implemented this process as a fully automated on-line monitor prototype system. This prototype system’s performance was evaluated in both the laboratory and during in-field deployment to a coal fired power plant. In both environments it was found that the prototype system was unable to recreate the batch process’s success at preparing FGD water samples for total Se measurements with a commercial-off-the-shelf (COTS) cyclic anodic stripping voltammetry (CSV) system. Through this experience, UAB has provided insight into a number of specific areas where improvements can be made with respect to the COTS systems used in this project to yield a more complete and competitive industry solution for on-line monitoring of total Se in industrial wastewater.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

Enabling opportunistic resources for CMS Computing Operations

With the increased pressure on computing brought by the higher energy and luminosity from the LHC in Run 2, CMS Computing Operations expects to require the ability to utilize opportunistic resources resources not owned by, or a priori configured for CMS to meet peak demands. In addition to our dedicated resources we look to add computing resources from non CMS grids, cloud resources, and national supercomputing centers. CMS uses the HTCondor/glideinWMS job submission infrastructure for all its batch processing, so such resources will need to be transparently integrated into its glideinWMS pool. Bosco and parrot wrappers are used to enable access and bring the CMS environment into these non CMS resources. Finally, we describe our strategy to supplement our native capabilities with opportunistic resources and our experience so far using them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Performance Portable, Fully Implicit Landau Collision Operator with Batched Linear Solvers

Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallelism in algorithms that have traditionally run on MPI processes or multiple threads within a single process. Opportunities for batching arise in, for example, kinetic discretizations of magnetized plasmas where collisions are advanced in velocity space at each spatial point independently. This paper builds on previous work on a high-performance, fully nonlinear, Landau collision operator by batching the linear solver, as well as batching the spatial point problems and adding new support for multiple grids for multiscale, multispecies problems. An anisotropic relaxation verification test that agrees well with previously published results and analytical models is presented. The performance results from NVIDIA A100 and AMD MI250X nodes are presented with hardware utilization analysis for each architecture. Finally, the entire implicit Landau operator time advance is implemented in Kokkos for performance portability, running entirely on the device and is available in the PETSc numerical library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Autonomous online optimization of a closed-circuit reverse osmosis system

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Dynamic Contingency Analysis Tool 2.0 User Manual with Test System Examples

This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images

Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. Here this approach is time-consuming and restricts the number of images that can be processed. Her in this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2014

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application’s throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based look-ahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from public and private IaaS clouds. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

XTL Converter

"XTL Converter" is a short Python script for electron microscopy simulation. The program takes an input crystal file in the VESTA *.XTL format and converts it to a text format readable by the multislice simulation program ìSTEM. The process of converting a crystal *.XTL file to the format used by the ìSTEM simulation program is quite tedious; it generally requires the user to select dozens or hundreds of atoms, rearranging and reformatting their position. Header information must also be reformatted to a specific style to be read by ìSTEM. "XTL Converter" simplifies this process, saving the user time and allowing for easy batch processing of crystals.

Spurgeon, StevenR↗
DOE OSTI2026

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗
DOE OSTI2015

XTL Converter

"XTL Converter" is a short Python script for electron microscopy simulation. The program takes an input crystal file in the VESTA *.XTL format and converts it to a text format readable by the multislice simulation program ìSTEM. The process of converting a crystal *.XTL file to the format used by the ìSTEM simulation program is quite tedious; it generally requires the user to select dozens or hundreds of atoms, rearranging and reformatting their position. Header information must also be reformatted to a specific style to be read by ìSTEM. "XTL Converter" simplifies this process, saving the user time and allowing for easy batch processing of crystals.

Spurgeon, Steven R↗