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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications

Abstract An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.

Donlan, Connor F. (ORCID:0000000223317882)↗
DOE OSTI2016

Time-resolved measurement of subchannel void distribution for boiling two-phase flow in 5 x 5 rod bundle at high-pressure and high-temperature

A subchannel void sensor (SCVS) was improved to acquire time-resolve boiling two-phase flow in a 5-by-5 heated rod bundle at high-pressure and high-temperature. The SCVS consists of 6-by-6 wire electrodes and 5-by-5 rod electrodes. The SCVS can acquire a time series data of local void fraction at 32 points of central subchannel region in addition to 100 points of rod surface regions between rods. The devised sensors are installed in the heated rod bundle at eight height levels to acquire two-phase flow dynamics and its development. The axial and radial power profile of the heated rod bundle are uniform, and eight pairs of sheath thermocouples are embedded on the heated rod to monitor its surface temperature distribution. The paper addresses the axial and cross-sectional distributions of void fraction at various pressure and rod bundle power conditions, which simulates an accidental condition in reactor core and in a spent fuel pool of a boiling water reactor (BWR). The experimental data are suitable to validate the computational multi-fluid dynamics (CMFD) and subchannel codes. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Fabrication and Testing of a Stainless Steel Quartz Coaxial Cable Structure for High Temperature Measurement

This paper presents a stainless-steel quartz coaxial cable structure for distributed sensing of high temperatures. The coaxial cable sensor uses stainless steel as the inner and outer conductors and quartz as the insulator in order to achieve mechanical strength and temperature resilience. Girdle-shaped reflectors are fabricated on the quartz tubing by CNC grinding and CO 2 laser resurfacing. The sensor operates by measuring the temperature dependent change in the effective electromagnetic length between the two adjacent reflectors on the quartz tubing. A retaining collar is fabricated at the tip of the quartz tubing by 3D printing and laser resurfacing to secure the connection between the sensor and the signal cable. The prototype sensor was tested for high temperature measurements up to 600°C, and the performance characteristics of the sensor such as sensitivity, resolution uncertainty, repeatability, and stability were estimated based on the test results.

Jiao, Xinyu↗
DOE OSTI2023

Distributed Coaxial Cable Sensors for In-Situ Condition Based Monitoring of Coal-Fired Boiler Tubes

The increasing contributions of renewable energy sources present new challenges to the operation and maintenance of the existing coal-fired power plants. One of the major operational risks is the unexpected failure of superheater boiler tubes, leading to the most unplanned power plant outrages. The boiler tube failure is difficult to predict due to the harsh operating environments. Therefore, condition-based monitoring (CBM) with a reliable high temperature sensor becomes necessary to produce a meaningful assessment of the health condition of boiler tubes and their remaining lifetime. In this work, the stainless-steel and quartz coaxial cable sensor (SSQ-CCS) is proposed for in-situ distributed monitoring of the boiler tube temperatures in existing coal-fired power plants. Comprehensive tests have been conducted with an in-house testing facility at Clemson University to study and evaluate the sensors’ performance in the temperature range of 100℃ to 600℃. The results indicated that the measurement resolution of the SSQ-CCS sensor is better than 1℃, and the drift is less than 2% over long-period testing. Meanwhile, multi-physics finite element analysis has been conducted to optimize the design and evaluate the safety of the SSQ-CCS temperature sensor under various operational conditions. Based on the performance obtained in the laboratory-scale testing, a field test has been implemented at a power plant. Four SSQ-CCS temperature sensors were installed for in-situ monitoring of the temperatures of a power plant’s superheat tube assembles. The data acquisition system has been successfully set up and collected sensing signals for more than three months. The sensing signals have been post-processed, and the monitored temperature history through the SSQ-CCS temperature sensor has been validated and compared with the conventional high temperature thermal couple data.

Jiao, Xinyu↗
DOE OSTI2018

Development of a Kalman filter estimator for simulation and control of particulate matter distribution of a diesel catalyzed particulate filter

The knowledge of the temperature and particulate matter mass distribution is essential for monitoring the performance and durability of a catalyzed particulate filter. A catalyzed particulate filter model was developed, and it showed capability to accurately predict temperature and particulate matter mass distribution and pressure drop across the catalyzed particulate filter. However, the high-fidelity model is computationally demanding. Therefore, a reduced order multi-zone particulate filter model was developed to reduce computational complexity with an acceptable level of accuracy. In order to develop a reduced order model, a parametric study was carried out to determine the number of zones necessary for aftertreatment control applications. The catalyzed particulate filter model was further reduced by carrying out a sensitivity study of the selected model assumptions. The reduced order multi-zone particulate filter model with 5 × 5 zones was selected to develop a catalyzed particulate filter state estimator considering its computational time and accuracy. Next, a Kalman filter–based catalyzed particulate filter estimator was developed to estimate unknown states of the catalyzed particulate filter such as temperature and particulate matter mass distribution and pressure drop (Δ P) using the sensor inputs to the engine electronic control unit and the reduced order multi-zone particulate filter model. A diesel oxidation catalyst estimator was also integrated with the catalyzed particulate filter estimator in order to provide estimates of diesel oxidation catalyst outlet concentrations of NO 2 and hydrocarbons and inlet temperature for the catalyzed particulate filter estimator. The combined diesel oxidation catalyst–catalyzed particulate filter estimator was validated for an active regeneration experiment. The validation results for catalyzed particulate filter temperature distribution showed that the root mean square temperature error by using the diesel oxidation catalyst–catalyzed particulate filter estimator is within 3.2 °C compared to the experimental data. Similarly, the Δ P estimator closely simulated the measured total Δ P and the estimated cake pressure drop error is within 0.2 kPa compared to the high-fidelity catalyzed particulate filter model.

Engineering↗
DOE OSTI2021

Power Plant Testing of Ultrasonic Measurements of Temperature Distributions and Heat Fluxes to Heat Exchange Surfaces

Extreme environmental conditions are common in energy conversion applications, in which the most hardened insertion sensors often do not perform reliably for long. On the other hand, ultrasonic measurements can be acquired noninvasively, with sensitive components kept away from the damaging environment. We have previously developed the ultrasonic method for measuring the spatial distribution of temperatures in solid materials applicable when large thermal gradients are present. In the developed approach, we use the echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features, to produce a train of echoes in response to an external pulse of ultrasonic excitation. This paper outlines the testing results of this approach applied to the temperature distribution measurements to a waterwall of a 500 MW power-plant utility boiler. The validation results obtained over the prolonged power plant test show that the estimated temperature profile is correctly captured, and the measurement accuracy can be comparable with traditional insertion sensors, such as thermocouples. Overall, the testing has confirmed that the developed approach has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term temperature measurements in extreme environments. Heat fluxes and thermal stresses in the structure can then be characterized noninvasively using the measured temperature distribution as the basis.

Walton, Kenneth↗
DOE OSTI2024

Distributed Sensors for Waste Plastics Gasification and Clean Hydrogen Productions

This project developed distributed fiber sensors for plastics gasification reactor for clean hydrogen production. These sensors can be directly inserted into gasification reactors to perform real-time, in-situ hydrogen and temperature profile measurements with 5-cm spatial resolution across the entire reactor chamber. Our research team will use this new sensor capability to study how feedstock mixtures, feedstock preparations, and air/steam flows impact feedstock consumption, hydrogen production, and harmful chemical production emissions.

08 HYDROGEN↗
DOE OSTI2019

Ultrasonic Measurements of Temperature Distribution and Heat Fluxes Across Containments of Extreme Environments

Extreme conditions are common in energy conversion, material processing, nuclear, airspace, and military applications. In such environments, the most hardened insertion sensors do not perform reliably for long. Ultrasonic measurements, on the other hand, can be acquired noninvasively, with sensitive components kept away from the damaging environment. We have previously developed the ultrasonic method for measuring the spatial distribution of temperatures in solid materials applicable in the cases when large thermal gradients are present. In the developed approach, we use the echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features, to produce a train of echoes in response to an external pulse of ultrasonic excitation. The delays between the echoes, which encode the information on the temperature distribution in the corresponding segments, is used to reconstruct unknown temperature profile. In this paper, we outline the results of pilot-scale testing of the developed approach and demonstrate its application to the measurements of the temperature distribution across the containment of a high-temperature combustion process. The validation results show that the estimated temperature profile is correctly captured, and the measurement accuracy can be comparable with traditional insertion sensors, such as thermocouples. Overall, the testing has confirmed that the developed approach has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term temperature measurements in extreme environments. Heat fluxes and thermal stresses in the structure can then be characterized noninvasively using the measured temperature distribution as the basis.

Jia, Yunlu↗
DOE OSTI2021

Embedded Sensors in Additively Manufactured Silicon Carbide

Silicon carbide (SiC) components are being considered for a wide range of nuclear applications due to their high-temperature strength retention, low neutron absorption, chemical inertness, and dimensional stability under neutron irradiation. However, machining and joining of SiC components have traditionally limited its application to relatively simple geometries. Recent work has demonstrated additive manufacturing of complex, high-purity, crystalline SiC components using a combination of binder jet printing and densification via chemical vapor infiltration (CVI). The process lends itself to embedding of fuel, absorbers, moderators, and sensors at strategic locations within a component. The latter could allow for enhanced in situ performance monitoring of limiting fuel temperatures, self-shielded neutron flux, and potentially spatially distributed strain within complex SiC components if sensors can be successfully embedded during CVI. This work describes (1) methods for embedding sensors; (2) thermodynamic analyses and material compatibility testing for identifying sensors capable of surviving high temperatures and exposure to hydrogen and hydrogen chloride during CVI; and (3) nuclear applications for embedded sensors, including potential failure modes during fabrication and during reactor operation. Molybdenum-sheathed thermocouples were successfully embedded in a complex SiC component, whereas niobium-sheathed high-temperature irradiation-resistant thermocouples started to drift as soon as the reactant gases were introduced and ultimately failed during CVI due to severe constrained expansion, potentially resulting from niobium hydride formation in the low-temperature region of the CVI system. Optical fibers were successfully embedded in SiC, but further work is needed to protect the fragile fiber leads after their protective coatings are removed during CVI.

thermocouples↗
DOE OSTI2020

Remote monitoring system

A remote monitoring system for monitoring parameters of an underground asset, such as an electric cable system, a pipeline serving as a conduit for water, gas, oil, sewage, or the like. Parameter detectors, such as sensors that measure temperature, voltage, current, moisture, etc., are distributed along the asset to provide electrical signals that represent respective monitored parameters of the asset. An underground hub disposed in an underground vault, or manhole, through which the asset passes is coupled to the parameter detectors to acquire the signals provided by the parameter detectors. The hub includes a controller to provide data derived from the acquired signals, the data being transmitted to a remote central location by a transceiver, or modem, via LP-WAN communication. Signals from the transceiver are transmitted directly from underground.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Investigation of the MTC noise estimation with a coupled neutronic/thermal-hydraulic dedicated model - 'Closing the loop'

This paper investigates the reliability of different noise estimators aimed at determining the Moderator Temperature Coefficient (MTC) of reactivity in Pressurized Water Reactors. By monitoring the inherent fluctuations in the neutron flux and moderator temperature, an on-line monitoring of the MTC without perturbing reactor operation is possible. In order to get an accurate estimation of the MTC by noise analysis, the point-kinetic component of the neutron noise and the core-averaged moderator temperature noise have to be used. Because of the scarcity of the in-core instrumentation, the determination of these quantities is difficult, and several possibilities thus exist for estimating the MTC by noise analysis. Furthermore, the effect of feedback has to be negligible at the frequency chosen for estimating the MTC in order to get a proper determination of the MTC. By using an integrated neutronic/thermal- hydraulic model specifically developed for estimating the three-dimensional distributions of the fluctuations in neutron flux, moderator properties, and fuel temperature, different approaches for estimating the MTC by noise analysis can be tested individually. It is demonstrated that a reliable MTC estimation can only be provided if the core is equipped with a sufficient number of both neutron detectors and temperature sensors, i.e. if the core contain in-core detectors monitoring both the axial and radial distributions of the fluctuations in neutron flux and moderator temperature. It is further proven that the effect of feedback is negligible for frequencies higher than 0.1 Hz, and thus the MTC noise estimations have to be performed at higher frequencies. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models

We benchmark performance of long-short term memory (LSTM) network machine learning model and autoregressive integrated moving average (ARIMA) statistical model in temporal forecasting of distributed temperature sensing (DTS). Data in this study consists of fluid temperature transient measured with two co-located Rayleigh scattering fiber optic sensors (FOS) in a forced convection mixing zone of a thermal tee. We treat each gauge of a FOS as an independent temperature sensor. We first study prediction of DTS time series using Vanilla LSTM and ARIMA models trained on prior history of the same FOS that is used for testing. The results yield maximum absolute percentage error (MaxAPE) and root mean squared percentage error (RMSPE) of 1.58% and 0.06% for ARIMA, and 3.14% and 0.44% for LSTM, respectively. Next, we investigate zero-shot forecasting (ZSF) with LSTM and ARIMA trained on history of the co-located FOS only, which is advantageous when limited training data is available. The ZSF MaxAPE and RMSPE values for ARIMA are comparable to those of the Vanilla use case, while the error values for LSTM increase. We show that in ZSF, performance of LSTM network can be improved by training on most correlated gauges between the two FOS, which are identified by calculating the Pearson correlation coefficient. The improved ZSF MaxAPE and RMSPE for LSTM are 4.4% and 0.33%, respectively. Performance of ZSF LSTM can be further enhanced through transfer learning (TL), where LSTM is re-trained on a subset of the FOS that is the target of forecasting. We show that LSTM pre-trained on correlated dataset and re-trained on 30% of testing target dataset achieves MaxAPE and RMSPE values of 2.32% and 0.28%, respectively.

ARIMA↗
DOE OSTI2016

A concept for non-invasive temperature measurement during injection moulding processes

Current models of the injection moulding process insufficiently consider the thermal interactions between melt, solidified material and the mould. A detailed description requires a deep understanding of the underlying processes and a precise observation of the temperature. Because todays measurement concepts do not allow a non-invasive analysis it is necessary to find new measurement techniques for temperature measurements during the manufacturing process. In this work we present the idea of a set up for a tomographic ultrasound measurement of the temperature field inside a plastics melt. The goal is to identify a concept that can be installed on a specialized mould for the injection moulding process. The challenges are discussed and the design of a prototype is shown. Special attention is given to the spatial arrangement of the sensors. Besides the design of a measurement set up a reconstruction strategy for the ultrasound signals is required. We present an approach in which an image processing algorithm can be used to calculate a temperature distribution from the ultrasound scans. We discuss a reconstruction strategy in which the ultrasound signals are converted into a spartial temperature distribution by using pvT curves that are obtained by dilatometer measurements.

42 ENGINEERING↗
DOE OSTI2022

Characterization of Losses in Superconducting Radio-Frequency Cavities by Combined Temperature and Magnetic Field Mapping

Superconducting radio-frequency (SRF) cavities are one of the fundamental building blocks of modern particle accelerators. To achieve the highest quality factors (10 10 -10 11 ), SRF cavities are operated at liquid helium temperatures. Magnetic flux trapped on the surface of SRF cavities during cool-down below the critical temperature is one of the leading sources of residual RF losses. Instruments capable of detecting the distribution of trapped flux on the cavity surface are in high demand in order to better understand its relation to the cavity material, surface treatments and environmental conditions. We have designed, developed, and commissioned two novel diagnostic tools to measure the distribution of trapped flux at the surface of SRF cavities. One is a magnetic field scanning system (MFSS) which uses cryogenic Hall probes and anisotropic magnetoresistance sensors that fit the contour of a 1.3 GHz cavity. The second setup is a stationary, combined magnetic and temperature mapping system which uses AMR sensors and carbon resistor temperature sensors, covering the surface of a 3 GHz SRF cavity. The MFSS system revealed a non-uniform distribution of trapped flux on the cavities' surface, dependent on the magnitude of the applied magnetic field during field-cooling below the critical temperature. The MFSS shows that magnetic field scanning as a function of the RF field indicates redistribution of trapped flux at some locations. About ~ 33% of hot-spots observed by temperature mapping during high power RF tests overlapped with the high B-field spots. Almost all high B-field spots observed after field-cool were found to be overlapped on grain boundaries. A clear correlation between the hot- spot formed after quench and local trapped flux was found, providing insight on the RF dissipation of trap vortices. The combined B&T map system showed that the T-map system is capable of detecting hot-spots and quench location on the surface of the 3 GHz SRF cavity. Different distribution of trapped flux was measured after different cool-down and residual B-field, but, no variation in magnetic field distribution was observed during quench, possibly due to magnetic sensors being far from the quench location.

Parajuli, Ishwari↗
DOE OSTI2023

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗
DOE OSTI2015

Development of metal-ceramic coaxial cable Fabry-Pérot interferometric sensors for high temperature monitoring

Metal-ceramic coaxial cable Fabry-Pérot interferometric (MCCC-FPI) sensors have been developed using a stainless steel tube and a stainless steel wire as the outer and inner conductors, respectively; a tubular α-alumina insulator; and a pair of air gaps created in the insulator along the cable to serve as weak reflectors for the transmitting microwave (MW) signal. The MCCC-FPI sensors have been demonstrated for high temperature measurements using MW signals in a frequency range of 2–8 GHz. The temperature measurement is achieved by monitoring the frequency shift (Δƒ) of the MW interferogram reflected from the pair of weak reflectors. The MW sensor exhibited excellent linear dependence of Δƒ on temperature; small measurement deviations (±2.7%); and fast response in a tested range of 200–500 °C. The MCCC has the potential for further developing multipoint FPI sensors in a single-cable to achieve in situ and continuous measurement of spatially distributed temperature in harsh environments.

47 OTHER INSTRUMENTATION↗