Characterizing soil water content variability across spatial scales from optimized high-resolution distributed temperature sensing technique
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54 ENVIRONMENTAL SCIENCES↗
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Results for “Distributed Temperature Sensing”
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Tower Distributed Temperature-Sensing (DTS) - channel 2
Tower Distributed Temperature-Sensing (DTS) - channel 2
54 ENVIRONMENTAL SCIENCES↗
Tower Distributed Temperature-Sensing (DTS) - channel 3 (b1-level)
Tower Distributed Temperature-Sensing (DTS) - channel 3
54 ENVIRONMENTAL SCIENCES↗
Tower Distributed Temperature-Sensing (DTS) - channel 1 (b1-level)
Tower Distributed Temperature-Sensing (DTS) - channel 1
54 ENVIRONMENTAL SCIENCES↗
Tower Distributed Temperature-Sensing (DTS) - channel 4 (b1-level)
Tower Distributed Temperature-Sensing (DTS) - channel 4
54 ENVIRONMENTAL SCIENCES↗
Optical monitoring to detect contamination of power grid components
A monitoring system includes an array of optical sensors disposed within a transformer tank. Each optical sensor is configured to have an optical output that changes in response to a temperature within the transformer tank. An analyzer is coupled to the array of optical sensors. The analyzer is configured to determine a sensed temperature distribution based on the sensed temperature. The sensed temperature distribution is compared to an expected distribution. Exterior contamination of the transformer tank is detected based on the comparison.
Mostafavi, Saman↗
Optical monitoring to detect contamination of power grid components
A monitoring system includes an array of optical sensors disposed within a transformer tank. Each optical sensor is configured to have an optical output that changes in response to a temperature within the transformer tank. An analyzer is coupled to the array of optical sensors. The analyzer is configured to determine a sensed temperature distribution based on the sensed temperature. The sensed temperature distribution is compared to an expected distribution. Exterior contamination of the transformer tank is detected based on the comparison.
Mostafavi, Saman↗
Characterization of Intrinsic Fiber Optic Temperature Sensors by In-core and Furnace Testing
Increased research and development in nuclear technology has raised the demand for novel sensors and instrumentation to meet data objectives, and survive in different conditions and environments, beyond conventional light water reactor (LWR) environments. Expediting the deployment of advanced nuclear technologies by developing, demonstrating, and qualifying advanced reactor fuel forms necessitates a deeper understanding of how irradiation affects fuels and materials' performance. To achieve a more comprehensive understanding of fuels and materials performance, researchers require more specialized experiments and measurements. The demand for innovative sensors to support nuclear fuel development arises from the complexity of materials' behavior under irradiation and the challenges of deploying instrumentation in Material Test Reactors (MTRs) for irradiation tests. Additionally, measurements of material properties require integrated measurement systems to characterize thermal properties, mechanical properties, chemistry, and microstructure [1]. Among the potential measurement techniques, optical fiber-based sensors have been identified as potential sensors to measure different physical phenomena such as temperature, strain, pressure, and fluid level. Optical fiber sensors have the capability to provide multi-sensing and multiplexing instrumentation, allowing the measurement of different physical parameters within a single sensor configuration, and transmitting data collected at multiple locations through a single fiber. They offer immunity to electromagnetic interference, electrical passivity, compatibility with various sensing methodologies, and cost-effectiveness. Beyond their widespread use in telecommunications, silica fiber-based instruments are utilized in industrial applications, even at temperatures reaching 300?400°C, such as distributed temperature sensing in oil and gas recovery. The Department of Energy (DOE) is interested in using fiber optics to support fuel cycle development [2]. Fiber optics are an excellent candidate for harsh environment sensing, including sensing at very high temperatures (1900oC for sapphire optical fibers). Distributed fiber optic sensing has been deployed in other harsh environments like coal gasification plants [3]. Distributed strain sensing, which operates similarly to distributed temperature sensing, has been deployed to monitor underground mines and fibers have been imbedded in soil to monitor sink-hole development [4][5]. The application of fiber optic sensors to advanced reactor development is a promising area of research.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Experimental study on the startup of the annular wick type heat pipe using fiber optical temperature measurement technique
This study used optical fiber-distributed temperature sensors to measure the internal and external temperature distributions of a water-cooled heat pipe. The sensor technology used in this study is fiber optical distributed temperature sensing, a distributed sensing technique based on the naturally occurring Rayleigh backscatter in optical fibers. This measurement technique provides maximum spatial resolution for static and semi-static applications. Using this sensor, the temperature distribution of the heat pipe's internal, external, vapor core, and the wick was measured with a spatial resolution of 0.65 mm, a sampling frequency of 40 Hz, and a temperature resolution of 0.1 °C. Through the measured temperature distribution database, the starting phenomenon, the effective length trend, and the limitation onset were observed. From the results, it is found that a high-temperature peak appears at the evaporator if a high initial power (75 W) is imposed on the heat pipe, even after the heat pipe approaches the normal operating status. The peak is not observed in a slower startup (30 W initial power then slowly increased to 75 W). It is also found that the temperature distributions and effective condenser length of the heat pipe highly depend on the cooling conditions. There are variations in the temperature according to the radial direction of the horizontal heat pipe due to gravity. In conclusion, lead and lag of the temperature evolution were observed at the onset of the operating limitations.
42 ENGINEERING↗
Distributed optical fibre sensing in physical oceanography: emergence and future prospects
Distributed optical fibre sensing (DOFS) is a technology that enables continuous, real-time measurements of a range of environmental parameters along the length of a fibre optic cable. In this article, we review the recently emerged applications of DOFS techniques in physical oceanography and offer a perspective on the technology's potential for future growth within the field. The introduction of DOFS to physical oceanography is contextualised with a brief history of the technology, which spun off primarily from the use of seafloor-laid optical fibres for telecommunications purposes. The key components and underpinning physics of a DOFS system are outlined and, on their basis, the suite of variables that are observable with DOFS are discussed. The implementation factors of DOFS, which include trade-offs between measurement accuracy and spatio-temporal resolutions and ranges, are also examined. The physical oceanographic applications of DOFS to date are then illustrated with case examples of four distinct DOFS techniques: distributed temperature sensing (DTS), which can provide ocean temperature observations; distributed static strain sensing (DSS) and distributed acoustic sensing (DAS), which are sensitive to temperature, cable strain and strain-associated variables, such as pressure and ocean velocity; and ultra-long-range observations of ocean currents with optical interferometry. The forthcoming prospects of DOFS in physical oceanography are considered, and are proposed to include new fibre optic-based approaches to sense ocean salinity and measure through the water column. We conclude with reflections on the future role of DOFS within the Global Ocean Observing System, and highlight the opportunities provided by the existing world-wide network of seafloor-laid optical fibres.
Naveira Garabato, Alberto C. [Univ. of Southampton↗
Utah FORGE: Well 16B(78)-32 DTS, RFS DSS Strain, and Absolute Strain Circulation Test Fiber Optic Data - August 2024
This dataset contains processed fiber optic measurements collected during the extended cross-well circulation test at the Utah FORGE site in August 2024. The data was acquired from the 16B(78)-32 well using distributed fiber optic sensing (DFOS) technology, including distributed temperature sensing (DTS) on multimode fiber and distributed strain sensing (DSS) measurements on single-mode fiber. The dataset includes Brillouin absolute strain, Rayleigh frequency shift (RFS) DSS strain change, RFS DSS strain change rate, and temperature (DTS) data, all stored in HDF5 format. Time coordinates are provided in UTC, and depth measurements are given in measured depth relative to the rotary kelly bushing (MD RKB) in feet. The spatial sampling on the RFS DSS strain data and the Brillouin Absolute Total Strain data is 20 cm and the spatial sampling on the DTS data is 1m. The dataset is accompanied by a report from Neubrex, which provides further documentation.
15 GEOTHERMAL ENERGY↗
Blue Canyon Dome: Development of a Small-Scale Testbed for Monitoring Underground Explosions
This report documents the development of the Blue Canyon Dome (BCD) testbed, including test site selection, development, instrumentation, and logistical considerations. The BCD testbed was designed for small-scale explosive tests (~5 kg TNT equivalence maximum) for the purpose of comparing diagnostic signals from different types of explosives, the assumption being that different chemical explosives would generate different signatures on geophysical and other monitoring tools. The BCD testbed is located at the Energetic Materials Research and Testing Center near Socorro, New Mexico. Instrumentation includes an electrical resistivity tomography array, geophones, distributed acoustic sensing, gas samplers, distributed temperature sensing, pressure transducers, and high-speed cameras. This SAND report is a reference for BCD testbed development that can be cited in future publications.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Complementary Subsurface Characterization Methods to Develop a Geologic Model for the EGS Collab Experiment, Sanford Underground Research Facility
The EGS (Enhanced Geothermal Systems) Collab project was performed within the Sanford Underground Research Facility (SURF) with a goal of understanding processes and evaluation of models related to hydraulic stimulation of rock at depth. The present work deals with the development of Testbed 2 where experiments were conducted at a depth of 1.25 km and were located within a well-characterized testbed in a metamorphic, amphibolite host rock. A total of eleven boreholes varying in length between 10.6 m and 81.2 m were continuously cored to develop the testbed. In addition to the continuous coring of the amphibolite host rock, geophysical instrumentation supporting electrical resistivity tomography (ERT), microearthquake (MEQ) detection, and optical fiber providing distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) were installed in the monitoring boreholes, all of which produced a comprehensive complementary suite of characterization and monitoring technologies. Pre-stimulation characterization of the groundwater conditions identified only two hydraulically significant fractures, neither of which transects the central portion of the testbed. Flow and pressure monitoring indicated low preexisting pore pressure conditions likely affected by the mine openings.
15 GEOTHERMAL ENERGY↗
Complementary Subsurface Characterization Methods to Develop a Geologic Model for the EGS Collab Experiment, Sanford Underground Research Facility
The EGS (Enhanced Geothermal Systems) Collab project was performed within the Sanford Underground Research Facility (SURF) with a goal of understanding processes and evaluation of models related to hydraulic simulation of rock at depth. The present work deals with the development of Testbed 2 where experiments were conducted at a depth of 1.25 km and were located within a well-characterized testbed in a metamorphic, amphibolite host rock. A total of eleven boreholes varying in length between 10.6 m and 81.2 m were continuously cored to develop the testbed. In addition to the continuous coring of the amphibolite host rock, geophysical instrumentation supporing electrical resisivity tomography (ERT), microearthquake (MEQ) detection, and optical fiber providing distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) were installed in the monitoring boreholes, all of which produced a comprehensive complementary suite of characterization and monitoring technologies.
15 GEOTHERMAL ENERGY↗
Utah FORGE: Neubrex Well 16B(78)-32 Circulation Test Fiber Optics Monitoring Data and Reports - July, 2023
This dataset features Distributed Acoustic Sensing (DAS) and fiber optics monitoring data acquired by Neubrex Energy Services during the Utah FORGE Well 16B(78)-32 circulation test in July 2023. DAS and fiber optic monitoring data include absolute strain, strain change, strain change rate, distributed temperature sensing (DTS), and frequency band extraction (FBE). Data processing was completed between September and October 2023. The dataset includes the fiber optic sensing data collected during these operations, along with a data collection report, descriptions of the data, and instructions for reading the data files.
15 GEOTHERMAL ENERGY↗
One-Step Ahead Prediction of Thermal Mixing Tee Sensors with Long Short Term Memory (LSTM) Neural Networks
High-temperature advanced reactors under development, such as sodium fast reactors (SFR) and molten salt cooled reactors (MSCR), are expected to offer lower levelized cost of energy (LCOE) compared to existing light water reactor (LWR’s). In the existing light water reactors (LWR’s), operation and maintenance (O&M) expenses constitute the largest fraction of the total operating cost. Some of the O&M costs are related maintenance of sensors which can fail due to exposure to harsh environment in a reactor. The O&M costs of Advanced Reactor (AR)’s are expected to constitute a significant fraction of the total cost as well, because of high temperature and radiation level in AR are likely to cause material fatigue and premature failure of sensors and components. The O&M costs in AR’s could be reduced through integration of advanced informatics of performance-related sensors into a digital twin designed for reactor monitoring. For example, machine learning (ML) could be employed for real-time validation and correction of performance-related sensors, and reducing the number of performance-related physical sensor units through virtual sensing. As part of the effort, we investigate real-time validation of thermal hydraulic sensors through one-step ahead forecasting of sensor values using long short-term memory (LSTM) recurrent neural networks (RNN). The sensors are installed in a flow loop containing a thermal mixing tee, which is a common experimental model to study thermal fatigue in a thermal hydraulic loop. In addition, nonlinear transients generated in a thermal mixing tee constitute a good challenge data set for training and validation of ML algorithms. Sensors in this study include thermocouples, flow meters, and optical fibers for distributed temperature sensing. In one experiment, measurement data sets were obtained for a loop was filled with water, and in another experiment, measurements were performed on a loop filled with liquid metal Galinstan. We have also conducted preliminary investigation of one-step ahead prediction of fiber optics-based distributed temperature sensing with LSTM networks. In predicting fiber-based temperature measurements, we treated each gauge pitch of the fiber as an independent sensor. Accuracy of one-step ahead forecasting was estimated by calculating root mean square error (RMSE) for the test segment of time series of each sensor. RMSE’s for temperature sensors in water loop were, for the most part, lower than for the same sensors in Galinstan loop. The RMSE’s for flow meters were similar for both loops. The RMSE’s for distributed temperature measured with the fiber optic sensor were similar to those of the point sensors. Results of this study demonstrated the capability of LSTM one-step ahead forecasting with RMSE comparable to uncertainty in sensor measurements.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Thermal Effects on Far-Field Distributed Acoustic Strain-Rate Sensors
Summary Fiber-optic cables cemented outside of the casing of an unconventional well measure crosswell strain changes during fracturing of neighboring wells with low-frequency distributed acoustic sensing (LF-DAS). As a hydraulic fracture intersects an observation well instrumented with fiber-optic cables, the fracture fluid injected at ambient temperatures can cool a section of the sensing fiber. Often, LF-DAS and distributed temperature sensing (DTS) cables are run in tandem, enabling the detection of such cooling events. The increasing use of LF-DAS for characterizing unconventional hydraulic fracture completions demands an investigation of the effects of temperature on the measured strain response by LF-DAS. Researchers have demonstrated that LF-DAS can be used to extract the temporal derivative of temperature for use as a differential-temperature-gradient sensor. However, differential-temperature-gradient sensing is predicated on the ability to filter strain components out of the optical signal. In this work, beginning with an equation for optical phase shift of LF-DAS signals, a model relating strain, temperature, and optical phase shift is explicitly developed. The formula provides insights into the relative strength of strain and temperature effects on the phase shift. The uncertainty in the strain-rate measurements due to thermal effects is estimated. The relationship can also be used to quantify uncertainties in differential-temperature-gradient sensors due to strain perturbations. Additionally, a workflow is presented to simulate the LF-DAS response accounting for both strain and temperature effects. Hydraulic fracture geometries are generated with a 3D fracture simulator for a multistage unconventional completion. The fracture width distributions are imported by a displacement discontinuity method (DDM) program to compute the strain rates along an observation well. An analytic model is used to approximate the temperature in the fracture. Using the derived formulae for optical phase shift, the model outputs are then used to compute the LF-DAS response at a fiber-optic cable, enabling the generation of waterfall plots including both strain and thermal effects. The model results suggest that before, during, and immediately following a fracture intersecting a well instrumented with fiber, the strain on the fiber drives the LF-DAS signal. However, at later times, as completion fluid cools the observation well, the temperature component of the LF-DAS signal can be equal to or exceed the strain component. The modeled results are compared to a published field case in an attempt to enhance the interpretation of LF-DAS waterfall plots. Finally, we propose a sensing configuration to identify the events when “wet fractures” (fractures with fluids) intersect the observation well.
Engineering↗
Real-time well integrity monitoring in underground gas storage wells using distributed temperature and strain sensing: a field demonstration
Here, this article presents the first successful field demonstration of a combined distributed temperature and strain sensing (DTSS) system installed directly on newly replaced tubing in a 5400-ft-deep operational underground gas storage well. The DTSS system uses a single optical fiber to monitor temperature and strain in real-time, providing a cost-effective solution for long-term well integrity assessment. In this study, the strain–stress correlation of the tubing—representative of material behavior analysis—is investigated as a potential method for monitoring tubing integrity throughout its lifetime. Moreover, the DTSS system’s capability to support both continuous and discrete monitoring is evaluated by comparing future data with historical records, enabling the early detection of issues such as material fatigue, corrosion, or deformation. Overall, the work examines the effectiveness and scalability of the DTSS system for real-time monitoring of well operations and integrity in a newly replaced well.
Distributed Strain Sensing↗