A hybrid measure-correlate-predict method for long-term wind condition assessment
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Zhang, Jie↗
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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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Early warning and crop condition assessment research
The Early Warning Crop Condition Assessment Project of AgRISTARS was a multiagency and multidisciplinary effort. Its mission and objectives were centered around development and testing of remote-sensing techniques that enhance operational methodologies for global crop-condition assessments. The project developed crop stress indicators models that provide data filter and alert capabilities for monitoring global agricultural conditions. The project developed a technique for using NOAA-n satellite advanced very-high-resolution radiometer (AVHRR) data for operational crop-condition assessments. This technology was transferred to the Foreign Agricultural Service of the USDA. The project developed a U.S. Great Plains data base that contains various meteorological parameters and vegetative index numbers (VIN) derived from AVHRR satellite data. It developed cloud screening techniques and scan angle correction models for AVHRR data. It also developed technology for using remotely acquired thermal data for crop water stress indicator modeling. The project provided basic technology including spectral characteristics of soils, water, stressed and nonstressed crop and range vegetation, solar zenith angle, and atmospheric and canopy structure effects.
Boatwright, G. O.↗
Overview and highlights of Early Warning and Crop Condition Assessment project
Work of the Early Warning and Crop Condition Assessment (EW/CCA) project, one of eight projects in the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS), is reviewed. Its mission, to develop and test remote sensing techniques that enhance operational methodologies for crop condition assessment, was in response to initiatives issued by the Secretary of Agriculture. Meteorologically driven crop stress indicator models have been developed or modified for wheat, maize, grain sorghum, and soybeans. These models provide early warning alerts of potential or actual crop stresses due to water deficits, adverse temperatures, and water excess that could delay planting or harvesting operations. Recommendations are given for future research involving vegetative index numbers and the NOAA and Landsat satellites.
Boatwright, G. O.↗
HAP [Hydropower Advancement Project] Condition Assessment Manual, Revision 1.1
This document is a compilation of condition assessment methodologies for hydropower facility component operation and maintenance. The component documents were originally authored primarily by hydropower engineering experts of Mesa and Associates under sub-contract to UT-Battelle as part of the Hydropower Advancement Project (HAP) funded by the Department of Energy Wind and Waterpower Technologies Office in 2012-2013. The component manuals were disseminated informally during that time and have been shared informally since that time but were never published by ORNL through its Resolution or Publication Tracking System processes because the HAP was terminated abruptly by DOE. This compilation represents a formal document and publication of the HAP Condition Assessment Manual. The information it contains was intended from the beginning of the project to be disseminated publicly for the benefit of U.S. and worldwide hydropower operation and maintenance practices.
13 HYDRO ENERGY↗
A Resilient Condition Assessment Monitoring System
An architecture and supporting methods are presented for the implementation of a resilient condition assessment monitoring system that can adaptively accommodate both cyber and physical anomalies to a monitored system under observation. In particular, the architecture includes three layers: information, assessment, and sensor selection. The information layer estimates probability distributions of process variables based on sensor measurements and assessments of the quality of sensor data. Based on these estimates, the assessment layer then employs probabilistic reasoning methods to assess the plant health. The sensor selection layer selects sensors so that assessments of the plant condition can be made within desired time periods. Resilient features of the developed system are then illustrated by simulations of a simplified power plant model, where a large portion of the sensors are under attack.
97 MATHEMATICS AND COMPUTING↗
Material condition assessment with eddy current sensors
Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges.
Goldfine, Neil J.↗
Methodology and Process for Condition Assessment at Existing Hydropower Plants
Hydropower Advancement Project was initiated by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy to develop and implement a systematic process with a standard methodology to identify the opportunities of performance improvement at existing hydropower facilities and to predict and trend the overall condition and improvement opportunity within the U.S. hydropower fleet. The concept of performance for the HAP focuses on water use efficiency how well a plant or individual unit converts potential energy to electrical energy over a long-term averaging period of a year or more. The performance improvement involves not only optimization of plant dispatch and scheduling but also enhancement of efficiency and availability through advanced technology and asset upgrades, and thus requires inspection and condition assessment for equipment, control system, and other generating assets. This paper discusses the standard methodology and process for condition assessment of approximately 50 nationwide facilities, including sampling techniques to ensure valid expansion of the 50 assessment results to the entire hydropower fleet. The application and refining process and the results from three demonstration assessments are also presented in this paper.
Zhang, Qin Fen↗
Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads
An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.
Parlos, Alexander G.↗
AgRISTARS: Soil moisture/early warning and crop condition assessment. Interface control document
The interactions and support functions required between the early warning/crop condition assessment (EW/CCA) project and soil moisture (SM) project are defined. The EW Project aims to develop, test and evaluate techniques and procedures for adapting remote sensing technology to provide early warning of events and the timely assessment of those factors which affect the quality and quantity of production of economically important crops. Those techniques to augment and reinforce the current assessment activities are to be developed to improve the definition of the relationship between the plant(s) and its environment. This assessment and evaluation will certainly include the need for soil moisture measurement and estimation. The SM Project aims to develop, test, and evaluate techniques and procedures to measure or predict soil moisture in the root zone using both contact and remote sensors.
Source record↗
Technical Needs for Enhancing Risk Monitors with Equipment Condition Assessment for Advanced Small Modular Reactors
Advanced small modular reactors (aSMRs) can provide the United States with a safe, sustainable, and carbon-neutral energy source. The controllable day-to-day costs of aSMRs are expected to be dominated by operation and maintenance costs. Health and condition assessment coupled with online risk monitors can potentially enhance affordability of aSMRs through optimized operational planning and maintenance scheduling.
Advanced Small Modular Reactor↗
NNP-LANL Utilities - Condition Assessment and Project Approach
This report is a presentation on LANL Utilities & Transportation Asset Management; Utility Assets Overview; Condition Assessment; Utilities Project Nominations & Ranking; and Utilities Project Execution.
99 GENERAL AND MISCELLANEOUS↗
Augmented Monitoring and Condition Assessment Program for SNF Wet Storage Life Extension - 20489
Approximately 27 MTHM of spent nuclear fuel (SNF) owned and managed by the U.S. Department of Energy, Office of Environmental Management is stored in the L Basin at the Savannah River Site (SRS). This 'DOE SNF' is comprised of approximately 12,000 aluminum-clad, aluminum-based fuel assemblies (∼7 MTHM), and approximately 2000 non-aluminum fuel assemblies (∼20 MTHM). A program is in progress to perform Non-Destructive Examination (NDE) of the fuel and their storage containers to characterize the materials' condition, and to evaluate the effects of service to enable continued safe wet storage of the SNF. The Augmented Monitoring and Condition Assessment Program (AMCAP), a two-part program to develop and implement remote underwater Non-Destructive Examination of the aluminum SNF, and of the containers of the non-aluminum SNF, respectively, is aimed at the characterization and evaluation of corrosion degradation of aluminum fuel and container materials. The predominant design of the aluminum SNF (ASNF) stored in L Basin is the Materials Test Reactor (MTR) equivalent design, a plate fuel design. These SNF are stored in 5'' diameter tubes or 5'' x 5'' squares (called bundles) that are nominally 12' or up to 14' long. The SNF is de-bundled and inspected using a custom-designed MTR Fuel Inspection Table. The inspection table provides for indexed fuel positioning for a video camera examination with controlled lighting. A total of 10 of the SNF originating from foreign research and test reactors were selected for examination based on burnup, enrichment, and prior damage caused by service/storage history. A special inspection campaign of these 10 assemblies is in progress. The observed corrosion damage included minor to moderate attack from general corrosion, pitting, crevice, end grain and galvanic corrosion. Example results from the completed inspections are shown and discussed. The focus is a comparison of the as-received condition versus the as-found current storage condition that will serve to validate Water Chemistry and Corrosion Monitoring Programs. The non-aluminum SNF (NASNF) stored in L Basin are of diverse design that includes various geometries with claddings of stainless steel, Zircaloy, and Hastelloy. The fuel core materials include uranium alloys, oxides/mixed oxides, and carbides. These SNF materials, originating from early experimental and test reactors, are in various physical forms including single fuel elements and cut pieces. The fuel is stored in L Basin in various configurations including in direct bundled storage in aluminum tubes and in isolation cans that are in the bundles or in a larger over-size storage container (OSC). Concern with inside-out corrosion and the potential loss of configuration control and ability to handle the storage containers prompted the development of remote NDE methods that include visual and UT technologies to assess the condition of the containers. Candidate stored materials were selected for a special inspection campaign; the development of the NDE methods for the inspection for galvanic, crevice and sediment-induced corrosion (inside-out) are discussed. A summary of the SNF storage in L Basin at the SRS, and an overview of the AMCAP to enable continued safe storage of DOE SNF are described. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning
Over the past decade, the use of artificial intelligence techniques in the field of health-monitoring has gained significant interest, especially for structures such as building and bridges. However, applications to industrial systems such as equipment-piping systems in nuclear plants have not been explored. Here, in this paper, it is shown that the existing techniques developed for buildings and bridges cannot be extended directly to equipment-piping systems as the response of such systems is governed by multiple localized modes unlike that in buildings and bridges. This paper proposes a new approach that consists of three key aspects: (i) a novel vector of degradation-sensitive features extracted from measured data, (ii) using a deep Artificial Neural Network (ANN) for diagnosis of degradation location and degradation severity, and (iii) consideration of uncertainty in degradation severity when training the ANN. Degradation in piping-equipment systems can occur due to flow-accelerated erosion and corrosion. These locations can potentially exhibit damage such as localized yielding or initiation of cracking due to an external event such as an earthquake. Moreover, such locations can at times go undetected by current inspection techniques. Therefore, a robust framework is needed for detection of degradation after a seismic event. This manuscript proposes a proof-of-concept framework, which utilizes data collected from sensors to generate a deep ANN database for predicting degraded locations and severity in a piping-equipment system. Degradation severity is classified as minor, moderate, and severe. In the suggested methodology, a novel vector of degradation-sensitive features is extracted from the sensor data to train the ANN. A simple piping-equipment system is selected to demonstrate feature extraction as a means to simplify pattern recognition, explore the design and parameters of an ANN, and develop a sensor placement strategy. The effectiveness of the proposed framework is demonstrated on a realistic primary safety system of a two-loop nuclear reactor. It is shown that the proposed post-hazard condition assessment framework is able to detect degraded locations along with the severity levels, including minor degradation, with considerably higher accuracy.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Using Facility Condition Assessments to Identify Actions Related to Infrastructure
To support cost effective, quality research it is essential that laboratory and testing facilities are maintained in a continuous and reliable state of availability at all times. NASA Langley Research Center (LaRC) and its maintenance contractor, Jacobs Technology, Inc. Research Operations, Maintenance, and Engineering (ROME) group, are in the process of implementing a combined Facility Condition Assessment (FCA) and Reliability Centered Maintenance (RCM) program to improve asset management and overall reliability of testing equipment in facilities such as wind tunnels. Specific areas are being identified for improvement, the deferred maintenance cost is being estimated, and priority is being assigned against facilities where conditions have been allowed to deteriorate. This assessment serves to assist in determining where to commit available funds on the Center. RCM methodologies are being reviewed and enhanced to assure that appropriate preventive, predictive, and facilities/equipment acceptance techniques are incorporated to prolong lifecycle availability and assure reliability at minimum cost. The results from the program have been favorable, better enabling LaRC to manage assets prudently.
Rubert, Kennedy F.↗
Augmented Monitoring and Condition Assessment Program (AMCAP) - Proof-of-Principle (POP) Mockup for Non-Aluminum Spent Nuclear Fuel Container In-Situ Examinations
A disciplined engineering approach is being followed to develop an engineered system of tooling and sensors, characterization techniques, and deployment subsystems for in-situ inspection of the several container types used for the storage of non-aluminum spent nuclear fuel (NASNF) in L Basin under the Augmented Monitoring and Condition Assessment Program (AMCAP). Inspecting the containers to provide information on their structural condition helps ensure the safe handling and storage of the NASNF containers pending final disposition. This report describes the work performed in the initial two phases of this developmental work, namely the bench scale and proof-of-principle (POP) scale, which focus on sensor selection and the tooling design and fabrication for two remote non-destructive examination (NDE) methods. These methods include visual testing (VT) for a visual examination of the container surfaces and ultrasonic testing (UT) for a n examination to characterize container wall material thickness and flaws.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
GeoXO Atmospheric Composition Instrument (AC) Measurements Conditions Assessment
NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecraft at GOES-Central position, that will carry an Atmospheric Composition Instrument (ACX) among its payloads; the requirement on the ACX is to scan its region of interest in one hour. An assessment of ACX observational conditions is presented, based on view geometry and solar angle range over the year. The availability for observations of each pixel is estimated per day of the year, as function of the geometric air mass factor (AMF), which can be related to signal to noise ratio using a model of the ACX instrument performance, and ultimately to expected column error for specific atmospheric species. In addition, cloud climatology – based on statistics derived from GOES-16 ABI cloud product data – is considered to determine typical fractions of cloud-free ACX observations and typical cloud optical depths, for each pixel as function of time of day and season. The results of such assessments can be used to prepare for GeoXO ACX data and further the understanding and development of the future instrument operations.
Boryana Efremova↗
AgRISTARS: Early warning and crop condition assessment. Plant cover, soil temperature, freeze, water stress, and evapotranspiration conditions
Emissive (10.5 to 12.5 microns) and reflective (0.55 to 1.1 microns) data for ten day scenes and infrared data for six night scenes of southern Texas were analyzed for plant cover, soil temperature, freeze, water stress, and evapotranspiration. Heat capacity mapping mission radiometric temperatures were: within 2 C of dewpoint temperatures, significantly correlated with variables important in evapotranspiration, and related to freeze severity and planting depth soil temperatures.
Wiegand, C. L.↗
An Updated Methodology for Enhancing Risk Monitors with Integrated Equipment Condition Assessment
Small modular reactors (SMRs) generally include reactors with electric output of ~350 MWe or less (this cutoff varies somewhat but is substantially less than full-size plant output of 700 MWe or more). Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. Enhancing affordability of AdvSMRs will be critical to ensuring wider deployment, as AdvSMRs suffer from loss of economies of scale inherent in small reactors when compared to large (~greater than 600 MWe output) reactors and the controllable day-to-day costs of AdvSMRs will be dominated by operation and maintenance (O&M) costs. Technologies that help characterize real-time risk are important for controlling O&M costs. Risk monitors are used in current nuclear power plants to provide a point-in-time estimate of the system risk given the current plant configuration (e.g., equipment availability, operational regime, and environmental conditions). However, current risk monitors are unable to support the capability requirements listed above as they do not take into account plant-specific normal, abnormal, and deteriorating states of active components and systems. This report documents technology developments towards enhancing risk monitors that, if integrated with supervisory plant control systems, can provide the capability requirements listed and meet the goals of controlling O&M costs. The report describes research results on augmenting an initial methodology for enhanced risk monitors that integrate real-time information about equipment condition and POF into risk monitors. Methods to propagate uncertainty through the enhanced risk monitor are evaluated. Available data to quantify the level of uncertainty and the POF of key components are examined for their relevance, and a status update of this data evaluation is described. Finally, we describe potential targets for developing new risk metrics that may be useful for studying trade-offs for economic operation while maintaining adequate safety margins.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗