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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

H2 Sensing with an Optical Fiber Sensor in the Subsurface H2 Storage Conditions

The concentration of hydrogen is subject to change due to biological reactions in the underground hydrogen storage reservoirs. Thus, monitoring hydrogen concentration in the subsurface gas deposits is vital to ensure the integrity and safety of the storage facilities. In this study, the optical fiber hydrogen sensor was developed and validated in relevant subsurface storage environments. Specifically, the sensor has demonstrated successful sensing performance at high temperatures (~80 °C) and high pressures (~1,000 psi) under very humid conditions (~100% RH). In addition, the sensor was exposed to real subsurface microbial samples to monitor microbially induced changes in hydrogen concentration. The sensor has shown stable H2 sensing responses in the replicated underground hydrogen storage conditions without deterioration or loss of H2 sensitivity. The biotic subsurface sample with hydrogen gas resulted in higher transmission intensity change than the abiotic sample due to the possible hydrogen consumption with microbes.

Kim, Daejin↗
DOE OSTI2017

Method, system, and computer-readable medium for determining performance characteristics of an object undergoing one or more arbitrary aging conditions

A method, system, and computer-readable medium are described for characterizing performance loss of an object undergoing an arbitrary aging condition. Baseline aging data may be collected from the object for at least one known baseline aging condition over time, determining baseline multiple sigmoid model parameters from the baseline data, and performance loss of the object may be determined over time through multiple sigmoid model parameters associated with the object undergoing the arbitrary aging condition using a differential deviation-from-baseline approach from the baseline multiple sigmoid model parameters. The system may include an object, monitoring hardware configured to sample performance characteristics of the object, and a processor coupled to the monitoring hardware. The processor is configured to determine performance loss for the arbitrary aging condition from a comparison of the performance characteristics of the object deviating from baseline performance characteristics associated with a baseline aging condition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Long-Term Monitoring of Utility-Scale Solar Energy Development and Application of Remote Sensing Technologies: Summary Report

In anticipation of increased utility-scale solar energy development over the next 20 to 50 years, federal agencies and other organizations have identified a need to develop comprehensive long-term monitoring programs specific to solar energy development. Increasingly, stakeholders are requesting that federal agencies, such as the U.S. Department of the Interior Bureau of Land Management (BLM), develop rigorous and comprehensive long-term monitoring programs. Argonne National Laboratory (Argonne) is assisting the BLM in developing an effective long-term monitoring plan as required by the BLM Solar Energy Program to study the environmental effects of solar energy development. The monitoring data can be used to protect land resources from harmful development practices while at the same time reducing restrictions on utility-scale solar energy development that are determined to be unnecessary. The development of a long-term monitoring plan that incorporates regional datasets, prioritizes requirements in the context of landscape-scale conditions and trends, and integrates cost-effective data collection methods (such as remote sensing technologies) will translate into lower monitoring costs and increased certainty for solar developers regarding requirements for developing projects on public lands. This outcome will support U.S. Department of Energy (DOE) Sunshot Program goals. For this reason, the DOE provided funding for the work presented in this report.

14 SOLAR ENERGY↗
NASA NTRS2006

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Dempsey, Paula J.↗
DOE OSTI2017

Sensor Placement Optimization using Chama

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low - cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy. Chama is an open source Python package which includes mixed - integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama is currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .

47 OTHER INSTRUMENTATION↗
NASA NTRS1974

Study of recreational land and open space using Skylab imagery

The author has identified the following significant results. Despite almost uniform surface temperature conditions in the study area, the thermal imagery did illustrate the following possible uses: (1) Surface temperatures relative to 0 C reveal whether the snow and ice cover is wet and the melt pattern. This information is useful in hydrologic monitoring of runoff timing and rate, as well as indicating trafficability conditions on the snow. (2) When the surface temperature of snow and ice is below freezing, it may serve as an indicator of spatial variation of air temperatures. This information may be used in calculating the spatial variation of surface radiation budgets, or in observing synoptic weather condition changes or local microclimatic effects. (3) Frozen inland lakes with less than about three or four inches of snow over the ice may be differentiated from surrounding snow covered land areas; this is not always feasible in visible wavelength imagery. The feasibility of this application decreases as the ice thickness increases.

Sattinger, I. J.↗
NASA NTRS2006

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Dempsey, Paula J.↗
NASA NTRS2003

Electrical-Impedance-Based Ice-Thickness Gauges

Langley Research Center has developed electrical-impedance-based ice-thickness gauges and is seeking partners and collaborators to commercialize them. When used as parts of active monitoring and diagnostic systems, these gauges make it possible to begin deicing or to take other protective measures before ice accretes to dangerous levels. These gauges are inexpensive, small, and simple to produce. They can be adapted to use on a variety of stationary and moving structures that are subject to accumulation of ice. Examples of such structures include aircraft, cars, trucks, ships, buildings, towers, power lines (see figure), power-generating equipment, water pipes, freezer compartments, and cooling coils. A gauge of this type includes a temperature sensor and two or more pairs of electrically insulated conductors embedded in a surface on which ice could accumulate. The electrical impedances of the pairs of conductors vary with the thickness of any ice that may be present. Somewhat more specifically, when the pairs of conductors are spaced appropriately, the ratio between their impedances is indicative of the thickness of the ice. Therefore, the gauge includes embedded electronic circuits that measure the electrical impedances, plus circuits that process the combination of temperature and impedance measurements to determine whether ice is present and, if so, how thick it is. Of course, in the processing of the impedance measurements, the temperature measurements help the circuitry to distinguish between liquid water and ice. The basic design of a gauge of this type can be adapted to local conditions. For example, if there is a need to monitor ice over a wide range of thickness, then the gauge can include more than two sets of conductors having various spacings.

Weinstein, Leonard↗
DOE OSTI2015

A Simple Demonstration of Concrete Structural Health Monitoring Framework

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This ongoing research project is seeking to develop a probabilistic framework for health diagnosis and prognosis of aging concrete structures in a nuclear power plant subjected to physical, chemical, environment, and mechanical degradation. The proposed framework consists of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report describes a proof-of-concept example on a small concrete slab subjected to a freeze-thaw experiment that explores techniques in each of the four elements of the framework and their integration. An experimental set-up at Vanderbilt University’s Laboratory for Systems Integrity and Reliability is used to research effective combination of full-field techniques that include infrared thermography, digital image correlation, and ultrasonic measurement. The measured data are linked to the probabilistic framework: the thermography, digital image correlation data, and ultrasonic measurement data are used for Bayesian calibration of model parameters, for diagnosis of damage, and for prognosis of future damage. The proof-of-concept demonstration presented in this report highlights the significance of each element of the framework and their integration.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A Demonstration of Concrete Structural Health Monitoring Framework for Degradation due to Alkali-Silica Reaction

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high-confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This ongoing research project is seeking to develop a probabilistic framework for health diagnosis and prognosis of aging concrete structures in a nuclear power plant that is subjected to physical, chemical, environment, and mechanical degradation. The proposed framework consists of four elements: monitoring, data analytics, uncertainty quantification and prognosis. This report focuses on degradation caused by ASR (alkali-silica reaction). Controlled specimens were prepared to develop accelerated ASR degradation. Different monitoring techniques – thermography, digital image correlation (DIC), mechanical deformation measurements, nonlinear impact resonance acoustic spectroscopy (NIRAS), and vibro-acoustic modulation (VAM) -- were used to detect the damage caused by ASR. Heterogeneous data from the multiple techniques was used for damage diagnosis and prognosis, and quantification of the associated uncertainty using a Bayesian network approach. Additionally, MapReduce technique has been demonstrated with synthetic data. This technique can be used in future to handle large amounts of observation data obtained from the online monitoring of realistic structures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Feasibility Study of Non-Destructive Techniques to Measure Corrosion in SAVY Containers

Stainless Steel SAVY containers are used to transport and store nuclear material. They are prone to interior corrosion in the presence of certain chemicals and a low-oxygen environment. SAVY containers also have relatively thin walls to reduce their weight, making their structural integrity more vulnerable to the effects of corrosion. A nondestructive evaluation system that finds and monitors corrosion within containers in use would improve safety conditions and preclude hazards. Non-destructive testing can determine whether oxidation or corrosion is occurring inside the SAVY containers, and there are a variety of non-destructive testing methods that may be viable. The feasibility study described will objectively decide which method best fits the requirements of the facility and the problem. To improve efficiency, the containers cannot be opened during the non-destructive examination. The chosen technique should also be user-friendly and relatively quick to apply. It must also meet facility requirements regarding wireless technology and maintenance. A feasibility study is an objective search for a new technology or product to solve a particular problem. First, the design, technical, and facility feasibility requirements are chosen and ranked in order of importance. Then each technology considered is given a score based upon a standard ranking system. The technology with the highest total score is deemed the best fit for a certain application.

42 ENGINEERING↗
DOE OSTI2011

The cloud monitor by an infrared camera at the Telescope Array experiment

The mesurement of the extensive air shower using the fluorescence detectors (FDs) is affected by the condition of the atmosphere. In particular, FD aperture is limited by cloudiness. If cloud exists on the light path from extensive air shower to FDs, fluorescence photons will be absorbed drastically. Therefore cloudiness of FD's field of view (FOV) is one of important quality cut condition in FD analysis. In the Telescope Array (TA), an infrared (IR) camera with 320x236 pixels and a filed of view of 25.8 deg. x19.5 deg. has been installed at an observation site for cloud monitoring during FD observations. This IR camera measures temperature of the sky every 30 min during FD observation. IR camera is mounted on steering table, which can be changed in elevation and azimuthal direction. Clouds can be seen at a higher temperature than areas of cloudless sky from these temperature maps. In this paper, we discuss the quality of the cloud monitoring data, the analysis method, and current quality cut condition of cloudiness in FD analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Impact of Synthesis and Aging on Titanium Carbide MXenes for Printed Microsystems

This work investigates the long-term electrical stability of Ti3C2Tx MXene Inks under accelerated aging conditions. Inks were synthesized from commercial MAX-Phase precursors, drop-cast onto custom PCB’s and monitored automated in-situ measurements. Samples aged at 85°C/85% RH, 85°C/0% RH and ambient conditions revealed distinct degradation trends. Wet aged inks showed rapid resistance increased while etched formulations exhibited long term stability. These findings highlight the influence of synthesis stage and environmental exposure on MXene Inks reliability, offering critical insights for printed MEMS and sensor applications. Ongoing measurements extend the aging timeline beyond prior studies, marking the longest evaluation under accelerated aging conditions to date.

Aging↗
NASA NTRS2020

Groundwater Drought: Environmental Controls and Monitoring

Arising from a long-term deficit of precipitation, groundwater drought often lags meteorological drought by months to years, depending on climate and subsurface hydrogeological conditions. Due to the paucity of in situ groundwater data in many parts of the world, global monitoring of groundwater storage variations and drought may be best achieved using satellite observations and/or groundwater time series simulated by hydrological models. The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions have greatly benefitted the modeling and monitoring of groundwater storage changes and drought at the global scale. In this chapter, we first review environmental controls on the temporal variability of groundwater using in situ data. We then describe an approach that infuses GRACE and GRACE-FO observations into a land surface model for assessing groundwater storage changes and drought globally. We also discuss characteristics of simulated groundwater drought and the limitations of current groundwater drought monitoring approaches.

Bailing Li↗
NASA NTRS1986

The role of space borne imaging radars in environmental monitoring: Some shuttle imaging radar results in Asia

The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. How synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather is discussed. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agricultural land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems are discussed.

Imhoff, Marc L.↗
DOE OSTI2020

In situ laser reflectivity to monitor and control the nucleation and growth of atomically thin 2D materials*

The growth of atomically thin two-dimensional (2D) layered and other quantum materials is typically performed without in situ monitoring or control. Here, a simple laser reflectivity approach is demonstrated to provide in situ control over sub-monolayer thickness and growth kinetics during pulsed laser deposition (PLD) of MoSe 2 layers. First, the general technique is presented with emphasis on designing the maximum sensitivity of the optical contrast through consideration of Fresnel's equations with proper choice of layer thickness, substrate, and laser monitoring wavelength, incidence angle, and laser polarization. Then the 632.8 nm optical reflectivity of MoSe 2 layers on SiO 2 /Si substrates was predicted and compared with in situ monitoring of MoSe 2 growth by PLD under actual growth conditions using a probe HeNe laser beam. The measurements showed high sensitivity and excellent agreement with MoSe 2 surface coverages calculated from atomic resolution STEM analysis of 2D layers deposited in arrested growth experiments. Finally, growth kinetics revealed by these measurements showed sigmoidal nucleation and growth stages in the formation of the 2D MoSe 2 layers that are described by a simple model, indicating the promise of the laser reflectivity technique for in situ monitoring and control of 2D materials deposition.

2D materials↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗
DOE OSTI2016

Fault detection and analysis in nuclear research facility using artificial intelligence methods

In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.

42 ENGINEERING↗