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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pyridine Polyaminocarboxylate Ligands for Use as Actinide-selective Holdback Reagents in Simplified TALSPEAK-like Extraction Systems

Three pyridine-based aqueous complexants have been synthesized and used in an unbuffered TALSPEAK (Trivalent Actinide Lanthanide Separation by Phosphorus-reagent from Aqueous Komplexes) separation system as minor actinide-selective holdback reagents. The selectivity was established based on distribution studies using radiotracer 152/154Eu, 241Am, stable Ln, Y and Th. In this system, these ligands selectively sequester Am from the lanthanides without the need for a secondary pH buffer. Am-lanthanide separation factors for Eu were found to be > 70 for all three ligands and > 15 for Nd. Aqueous pyridine based ligands represent viable alternatives for traditional actinide-selective holdback reagents in TALSPEAK-based systems.

TALSPEAK Process, pyridine, Aminopolycarboxylate, ↗
DOE OSTI2023

Dynamic model-based feature extraction for fault detection and diagnosis of a supermarket refrigeration system

With the increasing concerns over climate change and carbon emissions, fault detection and diagnostics (FDD) of low–global warming potential (GWP) refrigerant supermarket refrigeration systems has gained great attention from academic and industrial sectors. Various FDD approaches have been developed to detect, identify, and diagnose faults to save energy, improve food quality, and protect the environment. Here, to mitigate the difficulty of collecting high-quality steady-state operational data in field operations faced by most model-based FDD methods, this study developed dynamic models of a low–GWP refrigerant (CO 2 ) supermarket refrigeration system. The model accuracy was validated using manufacturer data and experimental data. Simulations were conducted to predict the system dynamic response under two common operational faults—evaporator air path blockage fault and the display case door open fault—to identify fault patterns and define key dynamic behavior indexes for supporting FDD algorithm development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Acoustic Signatures of Solvent Extraction Processes [Poster and Paper]

Data from four low-frequency acoustic sensors were used to investigate potential acoustic characteristics of centrifugal contactor, aqueous pump, and organic pump activity during the experiment. Three of the four sensors were Gem Infrasound Loggers (Anderson, et al. 2018) with serial numbers 190, 189, and 188. They will hereafter be referred to as GEM190, GEM189, and GEM188, respectively. The fourth acoustic sensor was a Raspberry Shake & Boom (Raspberry Shake 2017), which will hereafter be referred to as the RS&B. All four sensors record audio at a sampling rate of 100 Hz, allowing analysis of signals with characteristic frequencies up to 50 Hz.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Nuclear Reactor Heat Extraction for Synthetic Fuel Plants

This report looks at the viability and best approach when producing synthetic fuels using heat and power supplied by advanced nuclear energy systems. The report looks at a low temperature integration pathway with four types of advanced reactors: a pressurized water reactor (PWR), an advanced light water reactor (A-LWR), a sodium fast reactor (SFR), and a high-temperature gas-cooled reactor (HTGR). A failure modes and effects analysis (FMEA) of the coupling system between the nuclear plant and the synthetic fuel systems is performed with the goal of identifying the reliability of such a thermal delivery system. Furthermore, a high temperature pathway is investigated for synfuel coupling to determine if this is more efficient and more cost effective as a coupling approach.

10 - SYNTHETIC FUELS↗
NASA NTRS2004

Real time on-chip sequential adaptive principal component analysis for data feature extraction and image compression

In this paper, we present a new, simple, and optimized hardware architecture sequential learning technique for adaptive Principle Component Analysis (PCA) which will help optimize the hardware implementation in VLSI and to overcome the difficulties of the traditional gradient descent in learning convergence and hardware implementation.

PCA feature extraction image compression real time↗
NASA NTRSDate not supplied

Overview of Extractive and Optical PM Measurements from the NASA SE-5 High Pressure Flame Diagnostics Laboratory

Soot emissions measurements of multiphase non-premixed flames are sparse in the literature due to the complexities of sampling in such environments. We present an overview from on-going work at the NASA SE-5 High Pressure Flame Diagnostics laboratory focusing on soot and gaseous emissions at elevated pressures. SE-5 is a gaseous and liquid fueled high pressure flame tube facility capable of operating at pressures up to 880 psia, cooling capacity of 4,000,000 BTU/hr, liquid fuel flow rates up to 2 GPH, and an equivalence ratio range of 0.2 (fuel lean) to 4 (fuel rich). SE-5 provides optical access via four UV-grade fused silica optical windows of the primary reaction zone enabling non-intrusive optical diagnostics of the flame.

Soot↗
DOE OSTI2022

Use of Machine Learning for Signature Development in a Multi-Sensor Environment for Safeguard Applications of Solvent Extraction Processes

Idaho National Laboratory is constructing the Special Nuclear Material test bed (Beartooth) for research and development pertaining to nuclear fuel processing operations using centrifugal contactors. Beartooth will enable give researchers the opportunity to study the dissolution, separation, and conversion of special nuclear materials (e.g., plutonium, enriched uranium, and thorium). As a lead-in to Beartooth, this project constructed a test bed to study the process and equipment behavior with real time series data collection using a variety of non-traditional sensors, in order to identify process failures and label them as either accidental or purposeful, thus enhancing nuclear nonproliferation stewardship. The measurement sources in this test bed include vibration, acoustic, current, flow, colorimetric, and thermal data. These measurements vary in terms of magnitude, frequency, and location. This information will be combined and used within data-driven machine-learning methods to detect operation condition changes that are either intentional (i.e., changes in operating set points) or malicious (i.e., flow diversion) in nature. This presentation covers the data processing and signature development activities necessary for utilizing this heterogeneous dataset to classify process anomalies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Radiolytic Studies of Single-Cycle Extraction Systems

Presentation reporting the INL Center for Radiation Chemistry Research's activities supporting the development of advanced used nuclear reprocessing technologies through evaluating the radiation robustness of ligands.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗