Results for “successive twinning” — Page 5

DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Twin Proliferation and Prolongation under Kinetic Control: Pd–Au Janus Icosahedra versus Pd@Au Core–Shell Starfishes

Heterogeneous bimetallic nanocrystals featuring explicit spatial configurations and abundant twin defects can simultaneously enable geometric and ligand effects to enhance catalytic and photonic applications. Herein, we report two growth patterns of Au atoms on penta-twinned Pd decahedra, involving twin proliferation to generate asymmetric Pd–Au Janus icosahedra and twin elongation to produce anisotropic Pd@Au core–shell starfishes, respectively. Mechanistic analysis indicates that the injection rate determines the lower-limit number (n low ) of Au(III) ions in the steady state and thus controls the growth pattern. When n low ≤ 5.5, the kinetic rate is slow enough to initiate asymmetrical one-side growth but fast enough to outpace surface diffusion; Au tetrahedral subunits are successively proliferated along the axial $\langle$110$\rangle$ direction of Pd decahedra to form Pd–Au Janus icosahedra. Composed of five Pd and 15 Au tetrahedral subunits, such a heterogeneous icosahedron supports high (2.2 GPa) tensile strain and high strain difference up to +21.9%. In contrast, when n low > 5.5, the fast reduction kinetics promotes symmetric growth with inadequate surface diffusion. As such, Au atoms are laterally deposited along five high-indexed $\langle$211$\rangle$ ridges of Pd decahedra to generate concave Pd@Au core–shell starfishes with tunable sizes (28–40 nm), twin elongation ratios (33.82–162.08%), and lattice expansion ratios (8.82–20.10%).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1983

A flight-test evaluation of a go-around control system for a twin engine powered-lift STOL airplane

An automatic go-around control system was evaluated on the Augmentor Wing Jet Short Takeoff and Landing (STOL) Research Airplane (AWJSRA) as part of a study of an automatic landing system for a powered-lift STOL airplane. The results of the evaluation indicate that the go-around control system can successfully transition the airplane to a climb configuration from any initiation point during the glide-slope track or the flare maneuver prior to touchdown.

Watson, D. M.↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of sub-critical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS2011

Designing the Balloon Experimental Twin Telescope for Infrared Interferometry

While infrared astronomy has revolutionized our understanding of galaxies, stars, and planets, further progress on major questions is stymied by the inescapable fact that the spatial resolution of single-aperture telescopes degrades at long wavelengths. The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII) is an 8-meter boom interferometer to operate in the FIR (30-90 micron) on a high altitude balloon. The long baseline will provide unprecedented angular resolution (approx. 5") in this band. In order for BETTII to be successful, the gondola must be designed carefully to provide a high level of stability with optics designed to send a collimated beam into the cryogenic instrument. We present results from the first 5 months of design effort for BETTII. Over this short period of time, we have made significant progress and are on track to complete the design of BETTII during this year.

Rinehart, Stephen↗

NASA NTRS2012

Ground Contact Model for Mars Science Laboratory Mission Simulations

The Program to Optimize Simulated Trajectories II (POST 2) has been successful in simulating the flight of launch vehicles and entry bodies on earth and other planets. POST 2 has been the primary simulation tool for the Entry Descent, and Landing (EDL) phase of numerous Mars lander missions such as Mars Pathfinder in 1997, the twin Mars Exploration Rovers (MER-A and MER-B) in 2004, Mars Phoenix lander in 2007, and it is now the main trajectory simulation tool for Mars Science Laboratory (MSL) in 2012. In all previous missions, the POST 2 simulation ended before ground impact, and a tool other than POST 2 simulated landing dynamics. It would be ideal for one tool to simulate the entire EDL sequence, thus avoiding errors that could be introduced by handing off position, velocity, or other fight parameters from one simulation to the other. The desire to have one continuous end-to-end simulation was the motivation for developing the ground interaction model in POST 2. Rover landing, including the detection of the postlanding state, is a very critical part of the MSL mission, as the EDL landing sequence continues for a few seconds after landing. The method explained in this paper illustrates how a simple ground force interaction model has been added to POST 2, which allows simulation of the entire EDL from atmospheric entry through touchdown.

Raiszadeh, Behzad↗

DOE OSTI2024

4th Big Data for Nuclear Power Plants Workshop 2023

The Ohio State University and Idaho National Laboratory organized the 4 th Big Data for Nuclear Power Plants Workshop in November, 2023 in Columbus, Ohio. Workshop topics were chosen to understand the challenges and gaps that need to be addressed to maximize the impact of data on the nuclear industry, as well as the associated applications and risks. Discussions were focused around six specific application areas: Operation and Maintenance; Machine Learning in Nuclear Materials and Advanced Manufacturing; Cybersecurity; High-Performance Computing and Massive Computation; Big Data and Digital Twins; and Nuclear Non-Proliferation. The opportunities, challenges, and risks identified in the six focus areas explored in this workshop are diverse, but some common themes emerge, such as the importance of data integrity, quality, coverage, privacy, and traceability. Big data and AI/ML tools can be leveraged to reduce costs, optimize human tasking, and reduce human error across various application areas. In order for the nuclear industry to benefit from big data and advanced analytic capabilities, it is essential to address challenges and risks, such as data privacy, model reliability, and computational resource availability. Learning from other industries that have successfully implemented big data and AI/ML technologies, like the aerospace industry, can help the nuclear industry successfully integrate these technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1986

The handling qualities and flight characteristics of the Grumman design 698 simulated twin-engine tilt Nacelle V/STOL aircraft

This paper describes three government-conducted, piloted flight simulations of the Grumman Design 698 vertical and short takeoff and landing (V/STOL) aircraft. Emphasis is placed on the aircraft's handling qualities as rated by various NASA, Navy, and Grumman Aerospace Corporating pilots with flight experience ranging from conventional takeoff and landing (CTOL) to V/STOL aircraft. Each successive simulation incorporated modifications to the aircraft in order to resolve the flight problems which were of most concern to the pilots in the previous simulation. The objective of the first simulation was to assess the basic handling qualities of the aircraft with the noncross-shafted propulsion system. The objective of the second simulation was to examine the effects of incorporating the cross-shafted propulsion system. The objective of the third simulation was to examine inoperative single-engine characteristics with and without cross-shafted engines.

Eskey, M. A.↗

DOE OSTI2025

PMDT: AI-Enabled Predictive Maintenance Digital Twins for Advanced Nuclear Reactors

Our team made substantial technical progress on various fronts during the course of the program. Multiple milestones were geared towards demonstrating the feasibility of machine learning based predictive maintenance digital twins towards reducing O&M costs, whereas some other milestones actually focused on identifying technical gaps and developing technologies such as humble AI to provide necessary robustness to the ML-based models. We were able to demonstrate in many cases that Machine learning-based methods can be successfully adapted for Nuclear plant environments especially for remote monitoring applications. Detailed analyses were carried out with plant and full scope simulation data along with capabilities of enhanced analytics to assess and set realistic expectations on cost reductions in O&M. These assessments are paving the way for investments towards reactor design improvements as well project planning for SMR projects as they develop and mature in the next few years. Technology developed under this program got direct visibility to GE Hitachi and their utility customers and resulted in positive intents to deploy some of the elements from design phase. The project additionally resulted in several reports, publications, software and data generation that will be useful in deployment and O&M services for BWRX300 fleets.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2021

GRACE Follow-On Early In-Flight Challenges

The Gravity Recovery and Climate Experiment (GRACE) Follow-On Mission is a successor to the highly successful GRACE Mission, which operated from 2002-2017. It is a partnership between the National Aeronautics and Space Administration (NASA) and the German Research Center for Geosciences, GeoForschungsZentrum Potsdam (GFZ). Under this partnership, the United States provides the project management, satellites and instruments, Germany provides the launch and mission operations. The partners share responsibilities for producing science data products. GRACE Follow-On, like its predecessor GRACE, consists of twin satellites which fly in a tandem formation at a near polar orbit separated by about 200 km along track. The mission continues the work of GRACE by tracking the movement of water, observing changes in ice sheets and sea level to provide a unique view of Earth’s changing climate. The satellites were launched May 22, 2018 from Vandenberg Air Force Base, in California, on a SpaceX Falcon 9 Rocket. Launch and Early Operations (LEOP) were completed within the first week and on-orbit commissioning proceeded for the next 8 months. The GRACE Follow-On mission is designed to last five years. The mission operations team has had to address several technical challenges early into the planned five-year mission life. The commissioning period was extended by 5 months to successfully address these issues, making it possible for the mission to meet key requirements for delivery and quality of the science data products. This paper will address the challenges faced by GRACE Follow-On and the actions taken by the mission operations team to continue to safely operate the mission.

Witkowski, M.M.↗

DOE OSTI2024

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

The Convolutional Multiple Whole Profile (CMWP) Fitting Method, a Global Optimization Procedure for Microstructure Determination

The analysis of line broadening in X-ray and neutron diffraction patterns using profile functions constructed on the basis of well-established physical principles and TEM observations of lattice defects has proven to be a powerful tool for characterizing microstructures in crystalline materials. These principles are applied in the convolutional multiple-whole-profile (CMWP) procedure to determine dislocation densities, crystallite size, stacking fault and twin boundary densities, and intergranular strains. The different lattice defect contributions to line broadening are separated by considering the hkl dependence of strain anisotropy, planar defect broadening and peak shifts, and the defect dependent profile shapes. The Levenberg–Marquardt (LM) peak fitting procedure can be used successfully to determine crystal defect types and densities as long as the diffraction patterns are relatively simple. However, in more complicated cases like hexagonal materials or multiple-phase patterns, using the LM procedure alone may cause uncertainties. Here, we extended the CMWP procedure by including a Monte Carlo statistical method where the LM and a Monte Carlo algorithm were combined in an alternating manner. The updated CMWP procedure eliminated uncertainties and provided global optimized parameters of the microstructure in good correlation with electron microscopy methods.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A lightweight Fe–Mn–Al–C austenitic steel with ultra-high strength and ductility fabricated via laser powder bed fusion

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (~9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, in this study, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Towards underwater additive manufacturing via additive friction stir deposition

Given the challenges in feed material supply and quality control, metal additive manufacturing has rarely been implemented in austere environments, especially underwater. This paper explores the underwater operation potential of an emerging solid-state additive technology: additive friction stir deposition, wherein material feeding and bonding are enabled by mechanical forces with minimal influences from water. It is demonstrated that additive friction stir deposition of 304 stainless steel can be successfully performed with the print head and substrate immersed in water. High temperature is reached in the deposition zone (>60% melting temperature); the material deposition behavior is similar to that in typical open-air operation. The as-deposited material is fully-dense, having fewer annealing twins and a substantially smaller grain size than the feed material (4.98 μm vs. 31.44 μm ). Such microstructural changes stem from dynamic recrystallization caused by the large strain and high temperature introduced during deposition. In addition to grain refinement, small equiaxed dispersoids (~2–3 μm or less) are formed and evenly distributed in the austenite steel matrix. Rich in Cr, Mn, and O, these particles likely result from the reaction between the elements in stainless steel and water at elevated temperatures.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Liquid Core Detection and Strand Condition Monitoring in a Continuous Caster Using Optical Fiber

Real-time monitoring of the liquid core position during the continuous casting of steel has been demonstrated using low-cost distributed optical-fiber-based strain sensors. These sensors were installed on the containment roll support structures in the segments of a production continuous caster to detect the position of the solid–liquid interface and monitor the strand condition during the continuous casting. Distributed Fiber Bragg Grating sensors (FBGs) were used in this work to monitor strain at six roll positions in the caster. The sensor performance was first validated by comparing optical strain measurements with conventional strain gauge measurements in the lab. Next, optical strain measurements were performed on an isolated caster segment in a segment maintenance facility using hydraulic jacks to simulate the presence of a liquid core under the roll. Finally, the sensors were evaluated during caster operation. The sensors successfully detected the load increase associated with the presence of a liquid core under each instrumented roll location. Incidents of bulging and roll eccentricity were also detected using frequency analysis of the optical strain signal. The liquid core position measurements were compared using predictions from computer models (digital twins) in use at the production site. The measurements were in good agreement with the model predictions, with a few exceptions. Under certain transient caster operating conditions, such as spraying practice changes and SEN exchanges, the model predictions deviated slightly from the liquid core position determined from strain measurements.

47 OTHER INSTRUMENTATION↗