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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

WE-E-18A-01: Large Area Avalanche Amorphous Selenium Sensors for Low Dose X-Ray Imaging

Purpose: A large area indirect flat panel imager (FPI) with avalanche gain is being developed to achieve x-ray quantum noise limited low dose imaging. It uses a thin optical sensing layer of amorphous selenium (a-Se), known as High-Gain Avalanche Rushing Photoconductor (HARP), to detect optical photons generated from a high resolution x-ray scintillator. We will report initial results in the fabrication of a solid-state HARP structure suitable for a large area FPI. Our objective is to establish the blocking layer structures and defect suppression mechanisms that provide stable and uniform avalanche gain. Methods: Samples were fabricated as follows: (1) ITO signal electrode. (2) Electron blocking layer. (3) A 15 micron layer of intrinsic a-Se. (4) Transparent hole blocking layer. (5) Multiple semitransparent bias electrodes to investigate avalanche gain uniformity over a large area. The sample was exposed to 50ps optical excitation pulses through the bias electrode. Transient time of flight (TOF) and integrated charge was measured. A charge transport simulation was developed to investigate the effects of varying blocking layer charge carrier mobility on defect suppression, avalanche gain and temporal performance. Results: Avalanche gain of ∼200 was achieved experimentally with our multi-layer HARP samples. Simulations using the experimental sensor structure produced the same magnitude of gain as a function of electric field. The simulation predicted that the high dark current at a point defect can be reduced by two orders of magnitude by blocking layer optimization which can prevent irreversible damage while normal operation remained unaffected. Conclusion: We presented the first solid state HARP structure directly scalable to a large area FPI. We have shown reproducible and uniform avalanche gain of 200. By reducing mobility of the blocking layers we can suppress defects and maintain stable avalanche. Future work will optimize the blocking layers to prevent lag and ghosting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Deployment of Advanced Electroanalytical Sensors in the Kairos Power Engineering Test Unit (ETU) (Final CRADA Report)

This document serves as a summary report for the work conducted under CRADA 2022-22119 between Argonne National Laboratory and Kairos Power LLC. As part of this project, Argonne and Kairos worked to develop an advanced electrochemical system and testing protocol for the Kairos Power Enineering Test Unit (ETU), an industrial scale 14 ton molten FLiBe salt system. The main goals were (1) measurements of fundamental properties for key salt species, (2) the deployment and operations of sensors in the ETU, and (3) the development of automated approaches to analyze the measurements.

42 ENGINEERING↗
DOE OSTI2020

Combustion Performance and Emissions Optimization Through Integration of a Miniaturized High-Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2016

Solar variability datalogger

To address the lack of knowledge of local solar variability, we have developed and deployed a low-cost solar variability datalogger (SVD). While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we present evaluation of various low-cost irradiance sensor types, describe the SVD, and present validation and comparison of the SVD collected data. In conclusion, the low cost and ease of use of the SVD will enable a greater understanding of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic (PV) installations and thus will encourage greater penetrations of solar energy.

14 SOLAR ENERGY↗
DOE OSTI2016

SU-F-T-525: Monitordeep-Inspiratory Breathhold with a Laser Sensor for Radiation Therapy of Left Breast Cancer

Purpose: Radiation therapy (RT) of left sided breast cancers with deep-inspiratory breathhold (DIBH) can reduce the dose to heart. The purpose of this study is to develop and test a new laser-based tool to improve ease of RT delivery using DIBH. Methods: A laser sensor together with breathing monitor device (Anzai Inc., Japan) was used to record the surface breathing motion of phantom/volunteers. The device projects a laser beam to the chestwall and the reflected light creates a focal spot on a light detecting element. The position change of the focal spot correlates with the patient’s breathing motion and is measured through the change of current in the light detecting element. The signal is amplified and displayed on a computer screen, which is used to trigger radiation gating. The laser sensor can be easily mounted to the simulation/treatment couch with a fixing plate and a magnet base, and has a sensitivity range of 10 to 40 cm from the patient. The correlation of breathing signals detected by laser sensor and visionRT is also investigated. Results: It is found that the measured breathing signal from the laser sensor is stable and reproducible and has no noticeable delay. It correlates well with the VisionRT surface imaging system. The DIBH reference level does not change with movement of the couch because the laser sensor and couch move together. Conclusion: The Anzai laser sensor provides a cost-effective way to improve beam gating with DIBH for treating left breast cancer. It can be used alone or together with VisionRT to determine the correct DIBH level during the radiation treatment of left breast cancer with DIBH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Urea Sensor Final Report CRADA No. TSB-987-94

The purpose of this CIWDA project was to develop the ratiomde for an electrochemically-based biosensor for urea to integrate with NCM electronics for hemodialysis patient care.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

High Spatial Resolution Distributed Fiber-Optic Sensor Networks for Reactors and Fuel Cycle Systems

Objective of this NEET research program is to develop distributed fiber sensing solution to perform high spatial resolution measurements of physical and chemical parameters in radiation environments. These additional sensing capabilities will improve safety margins and efficient operation of nuclear energy system and various fuel cycle processes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

RadMAP: The Radiological Multi-sensor Analysis Platform

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. Here we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Development of a High-Intensity Heat Flux Gauge and Characterization Facility (Final Report)

Sandia National Laboratories (SNL) and Hukseflux Thermal Sensors (HTS) collaborated to advance the design and calibration of high-intensity heat flux gauges capable of measuring 2500 kW/m². An industry trade study was first conducted and highlighted the need for enhanced gauge designs and calibration methodology & services suited for high-intensities and broadband flux. We then developed, tested, and evaluated three prototype gauge designs along with four distinct coating types, each designed to extend the measurable flux range of existing HTS products to higher intensity levels. Following a down selection process, the project team refined the focus to a final product design, incorporating updated features to enhance its robustness during high flux exposure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Highly multiplexible thermal kinetic inductance detectors for x-ray imaging spectroscopy

For X-ray imaging spectroscopy, high spatial resolution over a large field of view is often as important as high energy resolution, but current X-ray detectors do not provide both in the same device. Thermal Kinetic Inductance Detectors (TKIDs) are being developed as they offer a feasible way to combine the energy resolution of transition edge sensors with pixel counts approaching CCDs and thus promise significant improvements for many X-ray spectroscopy applications. TKIDs are a variation of Microwave Kinetic Inductance Detectors (MKIDs) and share their multiplexibility: working MKID arrays with 2024 pixels have recently been demonstrated and much bigger arrays are under development. In this work, we present a TKID prototype, which is able to achieve an energy resolution of 75 eV at 5.9 keV, even though its general design still has to be optimized. We further describe TKID fabrication, characterization, multiplexing, and working principle and demonstrate the necessity of a data fitting algorithm in order to extract photon energies. With further design optimizations, we expect to be able to improve our TKID energy resolution to less than 10 eV at 5.9 keV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2018

Liquid level sensing for harsh environment applications using distributed fiber optic temperature measurements

This work demonstrates the measurement of liquid level from spatially distributed temperature measurements using optical frequency domain reflectometry. The goal of this work is to provide initial evidence for a liquid level sensor concept that could be applied in harsh environments such as those with: conductive, flammable, or other chemically aggressive media; electromagnetic interference; high temperatures (up to ~1000 °C); and neutron/gamma radiation. The sensor concept includes fiber optic sensors, along with an insulated heater wire assembled inside a protective Inconel 600 sheath. When the heater is not powered, the sensor provides spatially distributed temperature measurements along the length of the fiber. When the heater is powered, the difference in heat transfer in the liquid vs. vapor sections leads to a higher fiber temperature at locations above the liquid/vapor interface. The initial demonstration described in this work tested the sensor in a tank of water that was drained in increments of 2.5 cm. A model for determining liquid level from the distributed temperature measurements was developed that resulted in an accuracy of ±0.5 cm. Finally, the paper addresses potential effects of axial conduction through the sensor sheath, as well as ways to limit these effects to avoid “smearing” of what would otherwise be a step change in temperature at the liquid/vapor interface.

42 ENGINEERING↗
DOE OSTI2014

Non destructive technique for cracks detection by an eddy current in differential mode for steel frames

In this paper, a nondestructive technique is used as a tool to control cracks and microcracks in materials. A simulation by a numerical approach such as the finite element method is employed to detect cracks and eventually; to study their propagation using a crucial parameter such as the stress intensity factor. This approach has been used in the aircraft industry to control cracks. Besides, it makes it possible to highlight the defects of parts while preserving the integrity of the controlled products. On the other side, it is proven that the reliability of the control of defects gives convincing results for the improvement of the quality and the safety of the material. Eddy current testing (ECT) is a standard technique in industry for the detection of surface breaking flaws in magnetic materials such as steels. In this context, simulation tools can be used to improve the understanding of experimental signals, optimize the design of sensors or evaluate the performance of ECT procedures. CEA-LIST has developed for many years semi-analytical models embedded into the simulation platform CIVA dedicated to non-destructive testing. The developments presented herein address the case of flaws located inside a planar and magnetic medium. Simulation results are obtained through the application of the Volume Integral Method (VIM). When considering the ECT of a single flaw, a system of two differential equations is derived from Maxwell equations. The numerical resolution of the system is carried out using the classical Galerkin variant of the Method of Moments. Besides, a probe response is calculated by application of the Lorentz reciprocity theorem. Finally, the approach itself as well as comparisons between simulation results and measured data are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗
DOE OSTI2019

Comparative performance analysis of relative humidity sensor based on intermodal interference using tapered square no-core optical fiber and tapered cylindrical optical fiber

This work presents the computational evaluation of a new model for relative humidity sensor based on the principle of intermodal interference using a square-section no-core tapered optical fiber compared to a classical cylindrical tapered optical fiber sensor. Attempting at a new application of this type of sensor, simulations were carried out in the range of up to 60% of relative humidity, the main interest range of the pharmaceutical industry. Several materials were used in its modeling and an analysis was developed in its constructive dimensions, in order to verify the influence of each of them on the sensor performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Biocompatible surface functionalization architecture for a diamond quantum sensor

Significance Diamond-based quantum sensing enables nanoscale measurements of biological systems with unprecedented sensitivity. Potential applications of this emerging technology range from the investigation of fundamental biological processes to the development of next-generation medical diagnostics devices. One of the main challenges faced by bioquantum sensing is the need to interface quantum sensors with biological target systems. Specifically, such an interface needs to maintain the highly fragile quantum states of our sensor and at the same time be able to fish intact biomolecules out of solution and immobilize them on our quantum sensor surface. Our work overcomes these challenges by combining tools from quantum engineering, single-molecule biophysics, and material processing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

NWTC Researchers Field-Test Advanced Control Turbine Systems to Increase Performance, Decrease Structural Loading of Wind Turbines and Plants

Researchers at the National Renewable Energy Laboratory's (NREL's) National Wind Technology Center (NWTC) are studying component controls, including new advanced actuators and sensors, for both conventional turbines as well as wind plants. This research will help develop innovative control strategies that reduce aerodynamic structural loads and improve performance. Structural loads can cause damage that increase maintenance costs and shorten the life of a turbine or wind plant.

17 WIND ENERGY↗
DOE OSTI2019

REALIZATION OF A AUTOMATED T-WAY COMBINATORIAL TESTING APPROACH FOR A SOFTWARE BASED EMBEDDED DIGITAL DEVICE

Under the Department of Energy’s Light Water Reactor Sustainability Program, within the Plant Modernization research pathway, the Digital I&C Qualification Project is identifying new methods that would be beneficial in qualifying digital I&C systems and devices for safety-related usage. One such method that would be useful in qualifying field components such as sensors and actuators is the concept of testability. The Nuclear Regulatory Commission (NRC) considers testability to be one of two design attributes sufficient to eliminate consideration of software-based or software logic-based common cause failure (the other being diversity). The NRC defines acceptable “testability” as follows: Testability – A system is sufficiently simple such that every possible combination of inputs and every possible sequence of device states are tested and all outputs are verified for every case (100% tested). [NUREG 0800, Chapter 7, Branch Technical Position (BTP) 7-19] This qualification method has never proven to be practical in view of the very large number of combinations of inputs and sequences of device states for a typical I&C device. However, many of these combinations are not unique in the sense that they represent the same state space or in that that they represent state space that would not affect the critical design basis functions of the device. Therefore, the state space of interest might possibly be reduced to a manageable dimension through such analysis. This project will focus on a representative I&C device similar in design, function, and complexity to the types of devices that would likely be deployed in nuclear power plants as digital or software based sensors and actuators (e.g. Smart Sensors). Analysis will be conducted to determine the feasibility of testing this device in a manner consistent with the NRC definition. This report describes the development of test process for Bounded Exhaustive Testing with respect to Combinatorial Test (CT) methods. The report describes the candidate Device Under Test SW – the VCU smart sensor, conceptual experimental methods for stated test objectives, description of the process, tools, resources, and computing. This information will be used to fully develop a detailed test plan (based on statistical measure needs) and test environment for conducting an I&C device testability demonstration study. The future planed experimental study of this project is to demonstrate digital qualification via Bounded Exhaustive Testability with respect to Common Cause Failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗