Development of a Single Crystal Probe for Raman Distributed Temperature Sensing above 1000°C
SPIE Photonics West On Demand, Virtual, February 21-27, 2022
Engineering topics
Publications and source records attributed to Buric, Michael.
SPIE Photonics West On Demand, Virtual, February 21-27, 2022
DOE Office of Electricity TRAC Peer Review, Virtual, February 1-3, 2022
The continued development of molten salt reactors requires highly efficient and stable instruments that can efficiently track monitor conditions of the molten salt during long-term application operation in both the fuel and coolant/heat transfer fluid loops. Sapphire (Al 2 O 3 ) fibers have shown tremendous potential by enabling radiation resistance and a broader operational range of temperature . Thermodynamic modeling using the ThermoCalc and the SGTE Molten Salts (SALT1) and Pure Substances (Pure5) database is done performed to understand the compatibility of Al 2 O 3 fibers with NaCl-MgCl 2 eutectic molten salt in the temperature range of 600 to 1000°C. The thermodynamic calculations show that sapphire fibers are not expected to be compatible with long term exposure to molten chloride salts within this temperature range. Furthermore, various pure metallic elements were evaluated as potential cladding materials for part of the Al 2 O 3 fibers. Based on the thermodynamic analysis, molybdenum (Mo) and nickel (Ni) could be effective cladding materials to enhance the stability of Al 2 O 3 in NaCl and MgCl 2 chloride salt molten bath in the desired temperature range. The presence of a metallic cladding leads to the suppression of aluminum dissolution from Al 2 O 3 , thus improving its stability in chloride salts. Additionally, it is also shown that Al 2 O 3 remains stable up to 2300 K in the presence of pre-existing Al 2 MgO 4 and Al 2 NiO 4 in the eutectic molten chloride bath environment.
2021 MRS Fall Meeting and Exhibit, Virtual, December 6-8, 2021.
2021 AIChE Annual Meeting, Virtual, November 15-19, 2021.
The goal of this work is to investigate the performance of sapphire optical fiber temperature sensors and develop clad sapphire optical fibers for in-pile instrumentation. This work tests the distributed sensing performance of sapphire sensors by using optical backscatter reflectometry methods under combined radiation/temperature effects and high fluence. A series of irradiations will be completed to evaluate the effect of irradiation on sapphire optical fiber temperature sensors and to determine an operational limit for the sensors.
Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.
IEEE Ultrasonic Symposium 2021, Virtual, September 11-16, 2021
2021 Carbon Management and Oil and Gas Research Project Review Meeting, Virtual, August 23-27, 2021
Distributed acoustic sensors (DAS) have shown remarkable success in monitoring critical civil, energy and transportation assets over long distances and under harsh environmental conditions. Integration of artificial intelligence (AI) technologies with DAS can extend their operational capabilities from conventional tasks (e.g., vibration frequency detection) to more advanced intelligent tasks like anomaly detection. However, these AI technologies often require large labeled/ annotated DAS measurements datasets of the assets in both normal and anomalous operating conditions. This data acquisition task can be both time consuming and costly. This work develops a generative adversarial network based unsupervised domain adaptation framework to build intelligent DAS operational capabilities.
ECS 239th Meeting, Virtual, May 30-June 3, 2021
Overview of the NETL RIC Advanced Sensors & Controls FWP. Progress from EY2020 and looking ahead to EY2021. Introduces several other presentations by project PIs at the Crosscutting Research Sensors & Controls Annual Review meeting, May 2021.
Corrosion 2021 (Conference), Virtual, April 19-30, 2021
SPIE Defense + Commercial Sensing Digital Forum 2021, Virtual, April 12-16, 2021
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
Temperature gradients resulting from local electrochemical reactions, current distribution and geometry of gas flow channels in solid oxide fuel cells (SOFCs) create thermal stresses, localized thermophysical property gradients and uneven property evolution, contributing to SOFC degradation. This paper presents a new method to perform temperature measurements (up to 800°C) at high spatial resolutions to monitor the operation of SOFCs. Using femtosecond laser irradiation, distributed fiber sensors were hardened for high temperature environment applications. Distributed fiber sensors were embedded in interconnected plates using an additive manufacturing method to perform temperature measurements with 4-mm spatial resolution during the operation of a planar fuel cell. The measurement revealed the impact of various H 2 fuel concentrations and current loads have on temperature profiles of the SOFC tested. Temperature variation on the anode side was found to be less than 5°C, and 3°C on the cathode side. The measurements were compared to results from a multiphysics fuel cell performance model simulating similar conditions. These simulations predicted similar temperature gradients, indicating the experimental data obtained is reasonable. The model also predicts that the effect of the embedded sensor has on the local temperature will be minimal and that the gradient of temperature in the gas channels will be captured despite the separation between the sensor and the gas flow. Finally, the high spatial resolution data harnessed by these distributed fiber sensors provides experimental support for model-based design and optimization to improve the operational efficiency and longevity of solid oxide fuel cells and fuel cell assemblies.