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DOE OSTI2014

Sci—Fri PM: Dosimetry—06: Commissioning of a 3D patient specific QA system for hypofractionated prostate treatments

The objective of this work is to commission the 6MV-SRS beam model in COMPASS (v2.1, IBA-Dosimetry) and validate its use for patient specific QA of hypofractionated prostate treatments. The COMPASS system consists of a 2D ion chamber array (MatriXX{sup Evolution}), an independent gantry angle sensor and associated software. The system can either directly calculate or reconstruct (using measured detector responses) a 3D dose distribution on the patient CT dataset for plan verification. Beam models are developed and commissioned in the same manner as a beam model is commissioned in a standard treatment planning system. Model validation was initially performed by comparing both COMPASS calculations and reconstructions to measured open field beam data. Next, 10 hypofractionated prostate RapidArc plans were delivered to both the COMPASS system and a phantom with ion chamber and film inserted. COMPASS dose distributions calculated and reconstructed on the phantom CT dataset were compared to the chamber and film measurements. The mean (± standard deviation) difference between COMPASS reconstructed dose and ion chamber measurement was 1.4 ± 1.0%. The maximum discrepancy was 2.6%. Corresponding values for COMPASS calculation were 0.9 ± 0.9% and 2.6%, respectively. The average gamma agreement index (3%/3mm) for COMPAS reconstruction and film was 96.7% and 95.3% when using 70% and 20% dose thresholds, respectively. The corresponding values for COMPASS calculation were 97.1% and 97.1%, respectively. Based on our results, COMPASS can be used for the patient specific QA of hypofractionated prostate treatments delivered with the 6MV-SRS beam.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Novel, Low-Cost, Light-Weight High Efficiency (H*10 Capable) Neutron Detector-Dosimeter

The goal of this project was to design, develop and validate a novel, spectroscopy enabled H*(10) neutron dosimetry system based on the tensioned metastable fluid detector (TMFD) sensor technology. The project team consisted of staff from Oak Ridge National Laboratory (ORNL), Purdue University (PU) and Sagamore Adams Laboratories, LLC (SAL). PU-SAL staff were tasked with the design, development, construction and testing of the H*TMFD hardware and software, along with developing the control and data acquisition software for comparison of predictions from H*TMFD against a commonly accepted and widely used industry standard system; for this project, the Li-I detector coupled to bonner spheres (LiI-BSS) system manufactured by Ludlum, Inc. was utilized as the reference (“gold”) standard – similar in terms of neutron spectroscopy enablement to another industry recognized, albeit, significantly higher cost (est. $300K) system referred to as “ROSPEC” (from BTI, Inc., which was not available for this project). ORNL staff were tasked with providing field-relevant guidance, apparatus and facilities for acquiring data against calibrated neutron sources, and comparing results of H*TMFD against LiI-BSS system predictions in a series of blind-tests conducted at ORNL. Over the course of 12 months, the PU-SAL-ORNL staff successfully accomplished the proposed technical and administrative tasks, inclusive of engaging in outreach to potential users of this technology in the DOE-wide infrastructure. The proposed tasks were successfully accomplished in timely manner; the follow-up type tasks pertaining to SBIR type Phases 2-3 were discussed and are initiated, inclusive of filing for intellectual property (IP) disclosures and possible patent filings by PU’s Office of Technology Commercialization (OTC). Two H*TMFD system architectures (see Exhibits 1 & 2 in the report) were developed and constructed for hand-portability by health-physicists (HPs) – the HP-H*TMFD, and the H*TMFD system which consists of a side-by-side mounted array of 4 TMFDs of 3 different sizes in sensitive volume (including one with borated fluid) that now simultaneously enables neutron energy spectroscopy: single bin for < 0.1 MeV, and 152 energy bins in the 0.1-15.2 MeV range; H*(10) dosimetry from ~5 μRem/h towards 10 R/h ranges. Several experiments were conducted using neutron sources in various configurations (shielded and unshielded). In direct comparison against the LiI-BSS industry standard (acquiring data for 26h each source), the H*TMFD system (acquiring data for ~6h for each source) offered H*(10) dose predictions for the most part accurate to within +/-10% for dose rates in the 100-300 μRem/h range. The LiI-BSS was impractical to use under ultra-low (~10 μRem/h) dose rate space, as also another metering device used at ORNL (Ludlum 4241L non-spectroscopy enabled) for which the lower limit is set by the manufacturer at 100 μRem/h. The enablement for efficient use in timely manner at the 10 μRem/h levels is deemed to be a strong enabling factor for H*TMFD for use in the DOE-nuclear laboratory arena. In terms of weight, the HP-H*TMFD weighs under ~5-7 lb.; the H*TMFD system weighs ~35-lb. As such, it is ~1/4 the weight of an LiI-BSS system weighing ~120 lb (LiI detector with 6 bonner spheres) and, ~1/2 the weight of ROSPEC. As a result of this activity, two involved post-doctoral student staff have now transitioned their knowledge and experiences to DOE’s Pacific Northwest National Laboratory (PNNL). A PU graduate student has also benefited from this project work which formed a principal basis for his Ph.D. dissertation work (in progress).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Introducing “ The Integrator ”: A novel technique to monitor environmental flow systems

Abstract We introduce “ The Integrator ,” a novel technique to quantify transport and reaction metrics commonly used to characterize flow systems. This development consists of two products: (1) The Integrator sampling device and (2) its supporting mathematical framework, which is compatible with semi‐continuous sensor data. The use of The Integrator device simplifies the logistics of sample collection and greatly reduces the number of samples needed, making it ideal to characterize systems that are: (1) difficult to access, (2) large and thus intractable or highly heterogeneous, and (3) highly instrumented otherwise but where a more holistic, mechanistic understanding may be gained by monitoring one or more currently untracked elements. We tested and validated The Integrator technique using experimental data collected from a heart rate monitor (high‐quality, high‐frequency data in response to known excitation events) and solute tracer experiments conducted in two contrasting (fourth and seventh order) rivers. In the Supporting Information , we provide details concerning the design of The Integrator device used in our field case studies and provide insight into potential improvements. Despite our case studies focus on the analysis of conservative and reactive transport of solutes in rivers, the principles behind The Integrator technique can be used to monitor water quality in hyporheic zones, aquifers, wetlands, swamps, karsts, oceans, wastewater treatment plants, pipe networks, and air quality. Furthermore, special arrangements of Integrator devices can be used to gather data at spatial and temporal resolutions that are currently unattainable due to high transportation and/or personnel costs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

TEAMER: Performance mapping of Re Vision's Persistance PTO

Contains datasets from experimental measurements that were used to validate Re Vision's Persistence PTO's efficiency and performance. These measurements were obtained using a dynamometer test bench setup. The data includes open-circuit voltage and loss measurements to validate machine characteristics, efficiency mapping tests to determine the generator's performance mapping, and efficiency mapping tests to determine the converter's efficiency over the feasible operating range. This data was collected between June 2023 and September 2023. The data was collected at the National Renewable Energy Laboratory's Flatirons Campus, Colorado, United States. The data was collected using NREL's 5-kW dynamometer test bench, equipped with a torque sensor and various voltage and current sensors fed to a dedicated data acquisition system. Units for the data are included in the data file headers for each data series. A text editor or spreadsheet software such as Excel is required to view the *.csv data. The data are also provided in *.mat files. To view data plots, a Matlab script with *.mat files are provided.

16 TIDAL AND WAVE POWER↗

DOE OSTI2016

Fiber Optic Instrumentation in High Temperature Irradiation Environments

The extremely harsh conditions of advanced reactor designs pose serious challenges for nuclear fuels and materials. Traditional instrumentation (thermocouples, strain gauges, etc.) are not well suited for extended operation in such a harsh environment. This work discusses the potential for using fiber optic-based instrumentation in high temperature irradiation experiments. The primary limitation of fiber optic instrumentation in irradiation experiments is signal darkening due to attenuation in the fiber material. A computational model has been developed to predict broadband optical attenuation in fused silica fiber materials as a function of time, temperature, and dose. Preliminary results obtained using this model are shown for one cycle of irradiation in the high flux isotope reactor at various temperatures. An irradiation campaign has been initiated to provide temperature-dependent optical attenuation data at high dose in order to validate the predictive model. Demonstration of the safety and reliability of new and enhanced nuclear fuels and materials is essential for improving the safety and reliability of existing nuclear power plants and for the licensing and operation of advanced nuclear reactor technologies. Experimental validation of fuel performance codes requires high fidelity measurements during instrumented irradiation experiments. Therefore, a clear need exists for sensors of unprecedented accuracy, resolution, time/space/energy spectrum dependence, reduced size, and, perhaps most importantly, performance in harsh environments. The harsh environment during accelerated irradiation testing could include temperatures from 300 deg. C up to 2600 deg. C, and radiation damage levels ranging from 1 to greater than 100 dpa. Optical fiber-based sensors are a promising candidate for instrumentation in high temperature irradiation environments. Optical fibers are small, inexpensive, chemically inert, immune to electromagnetic interference, and made of high temperature radiation-hard materials. The ability to make distributed measurements of temperature or strain using a single inexpensive optical fiber currently exists for non-extreme environments as commercially available technology. Other advanced sensing technologies such as laser ultrasound, borescopes, and laser-induced breakdown spectroscopy use fiber optic light delivery as a critical component of the sensor design. Some potential applications for optical fiber-based sensors in instrumented irradiation experiments include in-situ measurements of thermal conductivity, ultrasonic measurement of elastic constants (with fiber optic delivery of signal for generation and detection of ultrasonic wave), and distributed measurements of temperature and/or strain (i.e., swelling). The primary limitation for the use of optical technologies for harsh environment (e.g., high neutron flux reactor environments) instrumentation is the attenuation of the light signal due to the effects of temperature and/or irradiation. This work summarizes initial efforts towards developing a predictive model of temperature-dependent radiation-induced attenuation in fused silica optical fibers at high dose. If there is adequate transmission in the fibers, fiber optic-based instrumentation could provide highly accurate distributed measurements during instrumented fuel/material irradiation experiments. Preliminary results show attenuation on the order of 5- 10 dB/m in the wavelength range of 750-900 nm at temperatures of 300 deg. C and below after one HFIR cycle (24 days). At higher temperatures (600 and 900 deg. C), the attenuation is reduced below 5 dB/m in the same wavelength range. This amount of attenuation is acceptable for most fiber optic based sensor systems with a dynamic range on the order of 20-50 dB for a reasonable length (1-2 meters) of fiber in the high flux region. Many optical components use a wavelength of 850 nm, which lies in the low attenuation window. In order to refine and ultimately validate the predictive model of optical fiber attenuation, a reactor irradiation campaign has been initiated. Rabbit irradiation capsules have been designed to irradiate optical fiber material (low and high OH fused silica, as well as single crystal sapphire) specimens in the HFIR at temperatures ranging from 100 to 1200 deg. C. (authors)

42 ENGINEERING↗

DOE OSTI2023

Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor

Abstract Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control.

Li, Jingxi (ORCID:0000000165958680)↗

DOE OSTI2023

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

System architecture and method of processing data therein

A system architecture encoded on a non-transitory computer readable medium, the system architecture includes a first protocol. The first protocol is configured to receive a plurality of outputs from an ICS used in controlling an industrial system. The first protocol is configured to receive a plurality of inputs from a physical module. The physical module includes at least one of a component, a sensor, or the ICS. Additionally, the system architecture includes a second protocol, wherein the second protocol is configured to validate the plurality of inputs from the first protocol. Moreover, the system architectures includes a third protocol, wherein the third protocol is configured to validate the plurality of outputs from the first protocol. Further, the system architecture includes a fourth protocol, wherein the fourth protocol is configured to manage the ICS based on the second protocol and the third protocol.

Abdel-Khalik, Hany S.↗

DOE OSTI2024

System architecture and method of processing data therein

Abdel-Khalik, Hany S.↗

DOE OSTI2026

Design optimization of MAPS-based detectors using a data-driven fast simulation approach

A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

Abstract We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or “drone” to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

42 ENGINEERING↗

DOE OSTI2016

International Collaboration Activities on Engineered Barrier Systems

The Used Fuel Disposition Campaign (UFDC) within the DOE Fuel Cycle Technologies (FCT) program has been engaging in international collaborations between repository R&D programs for high-level waste (HLW) disposal to leverage on gathered knowledge and laboratory/field data of near- and far-field processes from experiments at underground research laboratories (URL). Heater test experiments at URLs provide a unique opportunity to mimetically study the thermal effects of heat-generating nuclear waste in subsurface repository environments. Various configurations of these experiments have been carried out at various URLs according to the disposal design concepts of the hosting country repository program. The FEBEX (Full-scale Engineered Barrier Experiment in Crystalline Host Rock) project is a large-scale heater test experiment originated by the Spanish radioactive waste management agency (Empresa Nacional de Residuos Radiactivos S.A. – ENRESA) at the Grimsel Test Site (GTS) URL in Switzerland. The project was subsequently managed by CIEMAT. FEBEX-DP is a concerted effort of various international partners working on the evaluation of sensor data and characterization of samples obtained during the course of this field test and subsequent dismantling. The main purpose of these field-scale experiments is to evaluate feasibility for creation of an engineered barrier system (EBS) with a horizontal configuration according to the Spanish concept of deep geological disposal of high-level radioactive waste in crystalline rock. Another key aspect of this project is to improve the knowledge of coupled processes such as thermal-hydro-mechanical (THM) and thermal-hydro-chemical (THC) operating in the near-field environment. The focus of these is on model development and validation of predictions through model implementation in computational tools to simulate coupled THM and THC processes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Measurement of free chlorine levels in water using potentiometric responses of biofilms and applications for monitoring and managing the quality of potable water

We report residual free chlorine is not monitored continuously at scale in drinking water distribution systems because existing real-time sensor technologies require frequent maintenance, cleaning, and calibration, which makes these products too costly to be used throughout a distribution system. As a result, current measurement approaches require manual sampling, which is not feasible for the consistent monitoring of free chlorine because chlorine concentrations vary significantly throughout pipeline distribution and over time and space. This research presents an alternative and cost-effective method of predicting free chlorine levels in drinking water using graphite electrodes coated with naturally grown microbial biofilms. This Microbial Potentiometric Sensor (MPS) array was installed in a Continuously Mixed Batch Reactor (CMBR), and drinking water containing variable free chlorine concentrations. The chlorine concentrations were introduced in a controlled manner, and the MPS signals were monitored over time. MPS signals were measured from the change in Open Circuit Potential (OCP) across the MPS array in real-time. An empirically derived relationship between the normalized change in OCP and free chlorine was established by fitting individual and average MPS data to a decaying exponential growth function in order to predict free chlorine levels. The results show that free chlorine can be predicted with reasonable accuracy, with model validation showing an average absolute error of ±0.09 ppm below 1.1 ppm and ±0.30 ppm between 1.1 and 2.7 ppm. However, the accuracy of predictions was reduced at higher free chlorine levels. The researchers conclude that MPS systems may benefit drinking water distribution systems by measuring free chlorine. These advantages of the MPS are especially pronounced in the developing world because this system is inexpensive and does not require routine maintenance or cleaning. The system relies on a naturally forming and regenerating biofilm and an inexpensive potentiometric meter to produce stable measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

(U) Physics Validation of the RMI-Based Ejecta Source Model Implementation in FLAG: L2 Milestone #6035 Report

The Los Alamos Physics and Engineering Models (PEM) program has developed a model for Richtmyer-Meshkov instability (RMI) based ejecta production from shock-melted surfaces, along with a prescription for a self-similar velocity distribution (SSVD) of the resulting ejecta particles. We have undertaken an effort to validate this source model using data from explosively driven tin coupon experiments. The model’s current formulation lacks a crucial piece of physics: a method for determining the duration of the ejecta production interval. Without a mechanism for terminating ejecta production, the model is not predictive. Furthermore, when the production interval is hand-tuned to match time-integrated mass data, the predicted time-dependent mass accumulation on a downstream sensor rises too sharply at early times and too slowly at late times because the SSVD overestimates the amount of mass stored in the fastest particles and underestimates the mass stored in the slowest particles. The functional form of the resulting m(t) is inconsistent with the available time-dependent data; numerical simulations and analytic studies agree on this point. Simulated mass tallies are highly sensitive to radial expansion of the ejecta cloud. It is not clear if the same effect is present in the experimental data but if so, depending on the degree, this may challenge the model’s compatibility with tin coupon data. The current implementation of the model in FLAG is sensitive to the detailed interaction between kinematics (hydrodynamic methods) and thermodynamics (material models); this sensitivity prohibits certain physics modeling choices. The appendices contain an extensive analytic study of piezoelectric ejecta mass measurements, along with test problems, excerpted from a longer work (LA-UR-17-21218).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants

This report describes the status of ongoing research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants

This report describes research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Retro-Commissioning Sensor Suitcase for Energy Efficiency (CRADA Final Report)

The Sensor Suitcase project aimed to enable cost-effective, data-driven retro-commissioning (RCx) in small commercial buildings through a self-installable toolkit consisting of portable sensors and diagnostic software. Results showed that the Sensor Suitcase could identify common operational faults leading to 5–15% energy savings opportunities, with automated reports requiring minimal user interpretation. The project adhered closely to its Statement of Work (SOW) but evolved the reporting interface and sensor logging duration based on field feedback. The development and validation of diagnostics are documented in PNNL technical reports and internal analysis summaries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Inception Based Deep Convolutional Neural Network for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available and physical modeling is often not feasible. In this paper, a deep convolutional neural network (CNN) architecture is investigated for its ability to estimate the RUL of turbofan engines. The input to the model is a window of time series data collected from the engine under test. Inputting raw sensor data allows features to be learned instead of manually determined. To incorporate the ability to detect features of differing lengths, inception modules are used in the neural network architecture. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set and high prognosis accuracy was achieved. The developed model was used in the 2021 PHM Society Data Challenge and received second place, further validating its ability to accurately estimate RUL.

DeVol, Nathaniel↗