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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Breakthrough Hybrid CTL Process Integrating Advanced Technologies for Coal Gasification, Natural Gas Partial Oxidation, Warm Syngas Cleanup and Syngas-to-Jet Fuel

The objective of this research and development effort was to develop a breakthrough hybrid CTL process integrating advanced coal gasification (R-Gas) and natural gas partial oxidation technologies from Gas Technology Institute (GTI) (previously developed by Aerojet Rocketdyne (AR)) with advanced warm syngas cleanup (WDP) and advanced syngas-to-liquids (STL) technologies from RTI International to produce cost-competitive jet fuel compared to conventional refining routes and having a greenhouse gas emissions footprint that meets EISA 2007 §526 requirements.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

DPC Cement Filler Development (Progress Report)

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The following cement filler compositions were selected for experimental development work and accelerated testing in FY20: Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with H 3 PO 4 ; Calcium phosphate cements (CPCs); more specifically composed of pure or nearly pure hydroxyapatite or HAP (Ca 5 (PO 4 ) 3 (OH)); Wollastonite phosphate cements (WPC), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material and the phosphate serves as the binder. The FY20 effort focused on the optimization of compositions and subsequent processing of these three materials to achieve dense and well-consolidated monolithic samples with 30 to 40% porosity and permeabilities of 1 millidarcy. At the close of this progress report the aluminum phosphate cements (APCs) and the wollastonite phosphate cements (WPCs) appear to show the most promise for continued development. Less progress has been made with the calcium phosphate cements (CPCs); their slurry viscosities are high (and difficult to measure) and they exhibit relatively short cure times of 2 to 3 hours with concomitant and excessive volatile (e.g. CO 2 ) generation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development and Advanced Testing of DPC Cement Fillers

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The research presented here is focused Sandia’s efforts for the development of phosphate-based cement fillers. Molten metal filler research is an ongoing activity at Oak Ridge National Laboratories and is not discussed herein. After the completion of the FY20 research effort the following cement filler compositions were selected for further experimental development work and advanced testing in FY21: 1. Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with various phosphate sources; 2. Wollastonite phosphate cements (WPCs), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material bound by a calcium phosphate that serves as the binder; and 3. Calcium aluminate phosphate cements (CAPCs) specifically grossite (CaAl 4 O 7 ) and hibonite (CaAl 11 O 18 ) fillers bound by an aluminum phosphate that serves as the binder. This effort focused on the optimization and subsequent processing of these three cements to achieve dense and well-consolidated monolithic samples. Upon completion of the FY21 effort the aluminum phosphate cements (APCs) and the calcium aluminate phosphate cements (CAPCs) show the most promise for advanced testing and scale up. We will begin the work in FY22 focused on testing the performance of these two cements in small scale DPCs as well as advanced materials testing to evaluate cement performance under expected radiation doses and representative post-closure geochemical environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Safety Analysis for the Versatile Test Reactor Conceptual Design

Safety analysis simulations have been carried out using the SAS4A/SASSYS-1 safety analysis code system to update the baseline set of results for the Versatile Test Reactor conceptual design. Results from a previous revision of this work provided input for the Conceptual Safety Design Report summarizing the overall safety basis for the VTR. This work will also support future analyses that will be required for Chapter 13, “Accident Analysis,” of a preliminary safety analysis report. A number of transients have been evaluated based on categories of postulated accident sequences suggested for consideration in NUREG-1537. Ultimately, the full spectrum of event initiators and subsequent accident sequences will be defined through a probabilistic risk assessment of the plant design following the implementation of the Licensing Modernization Project guidelines as described in the VTR Safety Design Strategy. Since that process is ongoing, the present analysis addresses several transients that are expected to be bounding accident scenarios that represent the three key ways to perturb a reactor: through changes to the core inlet temperature, mass flow rate, or reactivity. These correspond to a loss of heat sink (LOHS), loss of flow (LOF) or station blackout (SBO), and transient overpower (TOP), respectively. Both Protected and Unprotected versions of these transients have been evaluated, along with additional transients that include transient overpower with one stuck rod, pump coast-down failures, seismic events, and overcooling events. At the current stage of design, transient simulation results for the Versatile Test Reactor indicate that large safety margins exist for many event initiators. However, several “enabling” assumptions have been made, in terms of both design features and design limits, in order to perform the analyses; and these assumptions will need to be revised as the design matures. In addition, a larger spectrum of events needs to be evaluated as part of the on-going probabilistic risk assessment process.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors

This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Leveraging design of experiments to build chemometric models for the quantification of uranium (VI) and HNO3 by Raman spectroscopy

Partial least squares regression (PLSR) and support vector regression (SVR) models were optimized for the quantification of U(VI) (10–320 g L −1 ) and HNO 3 (0.6–6 M) by Raman spectroscopy with optimized calibration sets chosen by optimal design of experiments. The designed approach effectively minimized the number of samples in the calibration set for PLSR and SVR by selecting sample concentrations with a quadratic process model, despite complex confounding and covarying spectral features in the spectra. The top PLS2 model resulted in percent root mean square errors of prediction for U(VI), HNO 3 , and NO 3 − of 3.7%, 3.6%, and 2.9%, respectively. PLS1 models performed similarly despite modeling an analyte with a majority linear response (i.e., uranyl symmetric stretch) and another with more covarying vibrational modes (i.e., HNO 3 ). Partial least squares (PLS) model loadings and regression coefficients were evaluated to better understand the relationship between weaker Raman bands and covarying spectral features. Support vector machine models outperformed PLS1 models, resulting in percent root mean square error of prediction values for U(VI) and HNO 3 of 1.5% and 3.1%, respectively. The optimal nonlinear SVR model was trained using a similar number of samples (11) compared with the PLSR model, even though PLS is a linear modeling approach. The generic D-optimal design presented in this work provides a robust statistical framework for selecting training set samples in disparate two-factor systems. This approach reinforces Raman spectroscopy for the quantification of species relevant to the nuclear fuel cycle and provides a robust chemometric modeling approach to bolster online monitoring in challenging process environments.

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

Laser-Plasma Spectroscopy of Hydroxyl with Applications

This article discusses laser-induced laboratory-air plasma measurements and analysis of hydroxyl (OH) ultraviolet spectra. The computations of the OH spectra utilize line strength data that were developed previously and that are now communicated for the first time. The line strengths have been utilized extensively in interpretation of recorded molecular emission spectra and have been well-tested in laser-induced fluorescence applications for the purpose of temperature inferences from recorded data. Moreover, new experiments with Q-switched laser pulses illustrate occurrence of molecular recombination spectra for time delays of the order of several dozen of microseconds after plasma initiation. The OH signals occur due to the natural humidity in laboratory air. Centrifugal stretching of the Franck-Condon factors and r-centroids are included in the process of determining the line strengths that are communicated as a Supplementary File. Laser spectroscopy applications of detailed OH computations include laser-induced plasma and combustion analyses, to name but two applications. This work also includes literature references that address various diagnosis applications.

47 OTHER INSTRUMENTATION↗