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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Covalently-Bonded Laminar Assembly of Van der Waals Semiconductors with Polymers: Toward High-Performance Flexible Devices

Van der Waals semiconductors (vdWS) offer superior mechanical and electrical properties and are promising for flexible microelectronics when combined with polymer substrates. However, the self-passivated vdWS surfaces and their weak adhesion to polymers tend to cause interfacial sliding and wrinkling, and thus, are still challenging the reliability of vdWS-based flexible devices. Here, in this study, an effective covalent vdWS–polymer lamination method with high stretch tolerance and excellent electronic performance is reported. Using molybdenum disulfide (MoS 2 ) and polydimethylsiloxane (PDMS) as a case study, gold–chalcogen bonding and mercapto silane bridges are leveraged. The resulting composite structures exhibit more uniform and stronger interfacial adhesion. This enhanced coupling also enables the observation of a theoretically predicted tension-induced band structure transition in MoS 2 . Moreover, no obvious degradation in the devices’ structural and electrical properties is identified after numerous mechanical cycle tests. This high-quality lamination enhances the reliability of vdWS-based flexible microelectronics, accelerating their practical applications in biomedical research and consumer electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bilayer Electron Transport Layers for High–Performance Rigid and Flexible Perovskite Solar Cells

While great progress is being made in achieving high power conversion efficiency (PCE), durability, and reliability in rigid and flexible n–i–p perovskite solar cells (PSCs), there is still room for improvement. Among myriad ways this can be achieved, one way is to improve the processing and quality of electron transport layers (ETLs) used in PSCs. To that end, here we explore the use of SnO 2 /TiO 2 bilayer ETLs in both rigid and flexible PSCs. In the case of rigid PSCs, chemical bath deposition (CBD) is used where the bilayer architecture affords the CBD of high-quality ETL, which results in PSCs with up to 25.13% PCE and operational stability T 80 (80% of initial PCE retained) of 2220 h under 1-sun continuous illumination with maximum power-point tracking. In the case of flexible PSCs, once again, the bilayer architecture allows us to fabricate high-quality ETL using spin coating, which results in PSCs with up to 22.54% PCE and excellent mechanical durability, withstanding 20 000 bending cycles with ≈92% of the initial PCE retained. Mechanisms underlying the enhanced performance and stability/durability of rigid and flexible PSCs that use SnO 2 /TiO 2 bilayer ETLs are elucidated. Furthermore, this approach could be extended to other ETL systems for PSCs for further improvements in PCE, durability, and reliability.

14 SOLAR ENERGY↗
DOE OSTI2020

Protection Scheme for Multiterminal HVDC System Based on Wavelet Transform Modulus Maxima

Fault protection is a major issue in the development of multiterminal high‐voltage direct current (HVDC) system based on voltage‐source converter. Owing to the rapid increase in fault current under DC faults, protection requires a fast fault detection method to isolate the fault current. However, the selectivity and reliability of the fast protection scheme should be primarily guaranteed. Therefore, a new protection strategy based on modulus maximum under wavelet transform is proposed in this paper. Fault detection and discrimination are achieved using single‐end signals of fault current. The external and internal faults can be discriminated via local information. The reliability and robustness of the proposed scheme against potential factors are verified. Numerous simulation cases are performed in PSCAD/EMTDC under different fault scenarios, and signal data are analyzed in MATLAB to demonstrate the effectiveness of the proposed fault protection scheme. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Huai, Qing↗
DOE OSTI2023

A promising intersection of excited‐state‐specific methods from quantum chemistry and quantum Monte Carlo

Abstract We present a discussion of recent progress in excited‐state‐specific quantum chemistry and quantum Monte Carlo alongside a demonstration of how a combination of methods from these two fields can offer reliably accurate excited state predictions across singly excited, doubly excited, and charge transfer states. Both of these fields have seen important advances supporting excited state simulation in recent years, including the introduction of more effective excited‐state‐specific optimization methods, improved handling of complicated wave function forms, and ways of explicitly balancing the quality of wave functions for ground and excited states. To emphasize the promise that exists at this intersection, we provide demonstrations using a combination of excited‐state‐specific complete active space self‐consistent field theory, selected configuration interaction, and state‐specific variance minimization. These demonstrations show that combining excited‐state‐specific quantum chemistry and variational Monte Carlo can be more reliably accurate than either equation of motion coupled cluster theory or multi‐reference perturbation theory, and that it can offer new clarity in cases where existing high‐level methods do not agree. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry

Otis, Leon↗
DOE OSTI2024

OC6 Phase IV: Validation of CFD Models for Stiesdal TetraSpar Floating Offshore Wind Platform

ABSTRACT With only a few floating offshore wind turbine (FOWT) farms deployed anywhere in the world, FOWT technology is still in its infancy, building on a modicum of real‐world experience to advance the nascent industry. To support further development, engineers rely heavily on modeling tools to accurately portray the behavior of these complex systems under realistic environmental conditions. This reliance creates a need for verification and validation of such tools to improve reliability of load and dynamic response prediction and analysis capabilities of FOWT systems. The Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project was created under the framework of the International Energy Agency to address this need and considers a three‐sided verification and validation between engineering level models, computational fluid dynamics (CFD), and experimental results. In this paper, a novel floating offshore wind platform, the Stiesdal TetraSpar, is simulated using CFD under the load conditions defined by Phase IV of the OC6 project. The comparison of these CFD results against the experimental results demonstrated the ability to predict the platform response to waves when imposing the measured wave signals as input. Although validation versus experiment was largely successful, the damping behavior was impacted by uncertainties likely originating from the mooring system and sensor umbilical cable. This extensive comparison effort with multiple CFD practitioners offers insight into best practices to achieve reliable results.

17 WIND ENERGY↗
DOE OSTI2025

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗
DOE OSTI2020

Universality between vector-like and chiral quiver gauge theories: anomalies and domain walls

We study low-energy dynamics of [SU($\textit{N}$)]$^K$ chiral quiver gauge theories in connection with $\mathcal{N}$ = 1 super Yang-Mills (SYM) theory, and quantum chromodynamics with bi-fundamental fermions (QCD(BF)). These theories can be obtained by $\mathbb Z_K$ orbifold projections of $\mathcal{N}$ = 1 SU($\textit{N K}$) SYM theory, but the perturbative planar equivalence does not extend nonperturbatively for $\textit{K}$ ≥ 3. In order to study low-energy behaviors, we analyze these systems using ’t Hooft anomaly matching and reliable semiclassics on $\mathbb R^3 × S^1$. Thanks to ’t Hooft anomaly that involves 1-form center symmetry and discrete chiral symmetry, we predict that chiral symmetry must be spontaneously broken in the confinement phase, and there exist $\textit{N}$ vacua. Theories with even $\textit{K}$ possess a physical θ angle despite the presence of massless fermions, and we further predict the $\textit{N}$-branch structure associated with it; the number of vacua is enhanced to 2$\textit{N}$ at θ = π due to spontaneous $\textit{C P}$ breaking. Both of these predictions are explicitly confirmed by reliable semiclassics on $\mathbb R^3 × S^1$ with the double-trace deformation. Symmetry and anomaly of odd-$\textit{K}$ theories are the same as those of the $\mathcal{N}$ = 1 SYM, and the ones of even-$\textit{K}$ theories are same as those of QCD(BF). We unveil why there exists universality between vector-like and chiral quiver theories, and conjecture that their ground states can be continuously deformed without quantum phase transitions. We briefly discuss anomaly inflow on the domain walls connecting the vacua of the theory and possible anomaly matching scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Efficient use of quantum computers for collider physics

Most observables at particle colliders involve physics at a wide variety of distance scales. Due to asymptotic freedom of the strong interaction, the physics at short distances can be calculated reliably using perturbative techniques, while long distance physics is non-perturbative in nature. Factorization theorems separate the contributions from different scales, allowing to identify the pieces that can be determined perturbatively from those that require non-perturbative information, and if the non-perturbative pieces can be reliably determined, one can use experimental measurements to extract the short distance effects, sensitive to possible new physics. Without the ability to compute the non-perturbative ingredients from first principles one typically identifies observables for which the non-perturbative information is universal in the sense that it can be extracted from some experimental observables and then used to predict other observables. In this paper we argue that the future ability to use quantum computers to calculate non-perturbative matrix elements from first principles will allow to make predictions for observables with non-universal non-perturbative long-distance physics.

Algorithms and Theoretical Developments↗
DOE OSTI2024

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗
DOE OSTI2020

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. Here, this study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash–Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt 2 ) is lower than that of Landsat estimation (10.4 ppt 2 ) and numerical simulations (9.6 ppt 2 ). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Imputation of urban environmental sensor data using gated attention bidirectional long short-term memory (GA-BiLSTM): methods, performance, and implications

Urban environmental monitoring networks frequently encounter significant data gaps due to sensor malfunctions, environmental disturbances, and communication failures. Reliable approaches to address these gaps are essential for ensuring the continuity and quality of environmental data streams. In this study, we developed a gated attention bidirectional long short-term memory (GA-BiLSTM) model to impute missing data in a dense urban monitoring network. Using observations from the CROCUS network in Chicago, we evaluated GA-BiLSTM against widely used approaches (XGBoost and K-nearest neighbors) under scenarios of both short-term intermittent gaps and prolonged outages. GA-BiLSTM consistently outperformed comparative methods, particularly during extended outages of up to ten days, demonstrating its ability to capture spatiotemporal dependencies across sensor nodes. Beyond performance metrics, feature importance and spatial network analyses highlighted the unexpected but critical predictive role of peripheral rural nodes, underlining their strategic value for maintaining robust urban monitoring systems. These results emphasize that advanced imputation methods can substantially improve the reliability of environmental monitoring networks and support more resilient data infrastructures for urban sustainability.

Data imputation↗
DOE OSTI2022

Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)

First-mile last-mile (FMLM) mobility services that connect riders to public transit can lead to improved transit accessibility and network efficiency if such services are convenient and reliable. However, many current FMLM services are inefficient and costly because they are inflexible (e.g., fixed supply of shuttles) and do not leverage collected data for optimized decision making. At the same time, new forms of shared mobility can provide added flexibility and real-time analytics to FMLM systems when carefully integrated. This study evaluates performance and cost implications of public/private coordination between transit shuttles and transportation network companies (TNC) in the FMLM context. A real-time operations model was developed to simulate daily operations for an existing FMLM system using real-world demand data. Three supply strategies were tested with varying levels of flexibility: (1) Status Quo (two 23-passenger on-demand shuttles), (2) Hybrid (one 23-passenger on-demand shuttle + TNC), and (3) TNC Only (exclusively use TNC services). Results indicated that the added flexibility of the Hybrid service design (using shuttles and TNCs) improved service performance (a 7.7% improvement), reduced daily operating costs (– 6.0%), and improved service reliability (95th percentile travel times decreased by up to 40% during peak periods). In addition, the Hybrid service design was more robust to variations in demand. Here, the Hybrid service was significantly cheaper to operate (– 31.6%) at reduced demand levels (50% of normal), and improved service performance (a 10.2% improvement) when demand levels were increased (150% of normal). These findings emphasize the importance of flexibility in FMLM service designs, especially when demand is sparse and variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Comparative Analysis of Imaging and Measurements of Micrometer-Scale Fracture Aperture Fields Within a Heterogeneous Rock Using PET and X-ray CT

Knowledge of the spatial distribution of fracture apertures is essential for reliable characterization of flow and transport processes in fractured systems and for better understanding of physicochemical matrix–fracture interactions. Here, we propose and test two image-based methods, thereby extending the current experimental capabilities to characterize aperture size distribution in structurally heterogeneous geologic porous media noninvasively. The first approach utilizes an inversion method based on the dataset acquired from positron emission tomography (PET) and the second approach considers an extension of the classic missing attenuation technique that relies on clinical X-ray computed tomography (X-ray CT). Independent sets of imaging experiments are conducted on a fractured basalt core with heterogeneous matrix properties and aperture distributions to compare the two methodologies. A repeat of each experiment is conducted to verify the proposed workflows. The performance of these two imaging techniques is systematically evaluated through the analysis of signal-to-noise ratio, minimum fracture size detectability, and measurement errors. While both approaches provide a reliable estimation of fracture aperture distributions, PET yields a signal-to-noise ratio that is substantially higher than the corresponding X-ray CT measurements. Furthermore, uncertainties of the aperture values for PET are considerably lower ($\bar {\sigma}_{\text {d}} = 15\%$) compared to those obtained from X-ray CT ($\bar {\sigma}_{\text {d}} = 29\%$), allowing for the detection of minimum aperture sizes of 20 $\mu$m with 70% confidence level. Finally, these approaches provide key experimental tools for better understanding dynamic hydromechanical fracture properties in geologic systems.

58 GEOSCIENCES↗
DOE OSTI2021

NREL’s Wind Turbine Drivetrain Condition Monitoring and Wind Plant Operation and Maintenance Research During the 2010s: A US Land-Based Perspective

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

17 WIND ENERGY↗
DOE OSTI2020

Facile healing of cracks in organic–inorganic halide perovskite thin films

Organic-inorganic halide perovskite (OIHP) thin films at the heart of the burgeoning thin-film perovskite solar cells (PSCs) technology possess poor mechanical properties, which is likely to limit the long-term reliability of PSCs as they are poised for commercialization. In an effort to address this issue, in this work we demonstrate that through-thickness cracks induced by bending-tension in thin films of the two prototypical OlHPs, methylammonium lead triiodide (MAPbl(3)) and formamidinium lead triiodide (FAPbl(3)), can be healed easily. This is through the application of either a moderate compressive stress (bending-compression) at room temperature or a simple heat-treatment at modest temperatures. The crack-healing process is found to be time-dependent, which indicates that facile mass-transport in OlHPs plays a key role in this phenomenon. An explanation for this phenomenon is provided, one based on the fundamentals of brittle fracture. This discovery has broad implications for the prevention and/or restoration of the overall performance, environmental stability, and mechanical reliability of PSCs, and other devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine-learning enabled thermodynamic model for the design of new rare-earth compounds

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been sparse due to limited availability of reliable datasets. In this work, we developed an ‘in-house’ rare-earth database with more than 600 + compounds, each entry was populated with formation enthalpy and related atomic features using high-throughput density-functional theory (DFT). The SISSO (sure independence screening and sparsifying operator) based machine-learning method with meaningful atomic features was used for training and testing the formation enthalpies of rare earth compounds. The complex lattice function coupled with the machine-learning model was used to explore the effect of transition metal alloying on the energy stability of Ce based cubic Laves phases (MgCu 2 type). The SISSO predictions show good agreement with high-fidelity DFT calculations and X-ray powder diffraction measurements. Our study provides quantitative guidance for compositional considerations within a machine-learning model and discovering new metastable materials. The electronic-structure of Ce-Fe-Cu based compound was also analyzed to get an in-depth understanding of the electronic origin of phase stability. The interpretable analytical models in combination with density-functional theory and experiments provide a fast and reliable design guide for discovering technologically useful materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of a new control rod drive mechanism design for the ISU AGN-201M reactor

The Aerojet General Nucleonics (AGN) model 201-Modified, known as the AGN-201M reactor, plays an essential role in the educational and research activities at Idaho State University (ISU). The ISU AGN-201M's original Control Rod Drive Mechanism (CRDM) has been in operation for more than fifty years with no large-scale redesigns. The CRDM is required to eject the fuel rods within one second during a SCRAM event (also known as a 'reactor trip') and adjust the control rods' insertion speed, and keeps the rod insertion sequence correct. The existing control rod drive mechanisms meet these criteria but experience a few concerns due to aging. Concerns include complex maintenance and costly repairs for old electromechanical components, rod position feedback errors, and the impediment of the plate during a SCRAM due to binding of the lead screws of the existing mechanism. During a binding event, the drive mechanism becomes locked, preventing the control rod's magnetic plate from moving in or out under the reactor's normal and emergency operating conditions. Although, the binding has no effect on the ability of the rod to exit the core during the SCRAM. To counteract the concerns and issues with the current CRDM, a new design has been proposed using newer components and a simplified design. The new design utilizes more advanced electric and mechanical components that are commercially available. The new CRDM system is divided into four main aspects: (1) control rod movement design (motor, lead screw, guide rods), (2) control rod ejection (springs, electromagnet), (3) control rod position and feedback (position transducer, microswitches), and (4) material selection and structural analysis. The new design aims to reduce the overall complexity and probability of failure to improve the reactor's overall reliability. With proper material selection and improved structural design, the new drives are lighter with little to no change in structural integrity. The new control rod drive mechanism eliminates binding scenarios by using a single lead screw and implementing additional guide rods. An advanced linear position sensor and microswitches replace the existing and aging synchro system for accurate rod position feedback resulting in better reactivity control. The new design meets the reactor's operational limits by having an average reactivity insertion of 0.065% Δk/k per second, which corresponds to a total control rod insertion time of 19.23 s, while the control rod's ejection time remains less than one second during a SCRAM event. The new design ensures the reactor's long-term viability for educational and research activities by increasing the reliability and safety of operation for years to come.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗