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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Photoinduced Electron-Transfer Distance Is Controlled by the Driving Force in Solid-State Organic Donor-Acceptor Systems

Understanding how short-range electron transfer generates photocurrent in organic solar cells and what photochemical driving force is needed to maximize efficiencies has been an immensely difficult problem. Here we show how these questions are intertwined: the driving force controls the average charge-transfer distance, skipping the shortest-range states in the optimal case. Using photoinduced absorption-detected magnetic resonance, we measure average charge-separation distances in dilute donor–acceptor blends as a function of driving force, and compare these with free charge yields measured by time-resolved microwave conductivity. We find that the largest driving forces show the shortest charge-separation distances, explaining their suppressed free-carrier generation. These results support a long-range electron-transfer model, wherein the driving force controls the initial delocalization of the electron–hole pair. The minimum driving force required for efficient charge separation (and minimal voltage losses) is ultimately set by the dielectric constant of the material.

14 SOLAR ENERGY↗
DOE OSTI2025

Design Report on the MiniFuel Instrumented Test Apparatus for Understanding Radiation Effects

Most nuclear fuels irradiations at Oak Ridge National Laboratory (ORNL) over the past decade have been conducted using MiniFuel—a static capsule design employing subscale fuel specimens to collect separate-effects irradiated fuel performance data. Irradiation conditions for MiniFuel experiments are predicted pre-test using reactor physics, and thermal models are verified post-irradiation via SiC dilatometry and various spectrometry methods. Relevant fuel performance parameters are also observed post-irradiation in a hot cell, thereby providing a single data point for each parameter representing the cumulative effects of the irradiation conditions. Substantially more data can be harvested from a single test and within a shorter duration by instrumenting irradiation vehicles and measuring desired quantities in situ. This report presents the design and analysis of the MiniFuel INstrumented Irradiation Test Apparatus for Understanding Radiation Effects (MINITAURE)—an instrumented test rig based on the separate-effects MiniFuel concept that aims to capture fission gas release (FGR) and thermal conductivity degradation of fuel specimens during irradiation in the High Flux Isotope Reactor (HFIR). MINITAURE will be integrated with the Materials Irradiation Facility (MIF) located in the HFIR building outside the reactor containment. The MIF will act as the instrumentation and control center for the experiment, enabling real-time feedback from in situ sensors and control of irradiation temperatures via a gas delivery system. Two unique capsule designs were developed to capture each phenomenon: the thermal conductivity capsule, which uses a thermopile method to estimate fuel specimen thermal conductivity, and the fission gas release capsule, which will have continuous flowing gas communication to high-purity germanium detectors that are housed in the MIF for monitoring FGR. This report details the reactor physics and heat transfer modeling activities that were used to inform the experiment design and predict capsule performance. It also describes out-of-pile activities conducted to stand up this new capability and verify the measurement techniques. Modeling efforts to date have demonstrated the feasibility of the in situ measurement techniques and supported the development of the MINITAURE assembly configuration. Out-of-pile testing of the thermal conductivity measurement shows promise in capturing relative changes in thermal conductivity. However, significant errors exist in the measured absolute value, posing a need for further refinement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Coupled heat and mass transfer in internally cooled silica gel-coated aluminum foam heat exchangers for dehumidification

Solid desiccant dehumidifiers offer significant potential to improve humidity control in buildings due to their ability to independently regulate latent (humidity) and sensible (temperature) loads. However, adsorption of water vapor by desiccants is an exothermic process; the resulting heat of adsorption increases both the desiccant bed temperature and the temperature of the air flowing over the bed, thereby limiting the performance of desiccant dehumidifiers. To address this problem, desiccant-coated heat exchanger prototypes were developed by coating silica gel onto aluminum foam substrates and integrated with chilled water circulation for effective removal of the heat of adsorption. Prototype heat exchangers with two different pore densities (10 and 20 pores per inch (PPI)) and two different desiccant loadings (∼10.36% and ∼17.80%) were fabricated. Experiments were conducted by varying the inlet air face velocity, chilled water inlet temperature, and chilled water flow rate to investigate the coupled heat and mass transfer characteristics of the prototype heat exchangers over a wide range of operating conditions. The underlying transport mechanisms were analyzed using transient desiccant bed temperature, outlet air temperature, and outlet humidity profiles. The results demonstrate that internal cooling significantly enhances dehumidification performance by maintaining more favorable thermodynamic conditions for water vapor adsorption. Under identical operating conditions, a 20 PPI heat exchanger coated with 25.05 g of silica gel achieved 98.98% higher cumulative water uptake and 97.75% higher moisture removal capacity than the corresponding non-cooled case after 5 min of adsorption. This substantial enhancement was further supported by a validated one-dimensional coupled heat and mass transfer model developed in the present study. To date, this is one of the first experimental studies to systematically investigate the combined effects of internal cooling, foam pore density, and desiccant loading on the performance of silica-gel-coated metal foam heat exchangers under HVAC-relevant operating conditions.

42 ENGINEERING↗
DOE OSTI2026

Ultrafast (1‐5 sec) Lamination of Perovskite Solar Cells With Self‐Encapsulation Using Rapid Joule Heating

Perovskite solar cells (PSCs) are traditionally fabricated using sequential layer‐by‐layer deposition, in which each layer of the device is processed on top of the preceding layer. This constrains the processing techniques and selection of transport layer materials that can be used in the solar cell. To overcome these challenges, two half‐cells can be processed independently and then diffusion‐bonded through a lamination process. However, current lamination processes for perovskite solar cells suffer from relatively long process times, which can limit throughput when moving toward high‐volume manufacturing. In this study, a custom platform was designed for rapid‐joule heating of perovskite materials and devices. This enabled more than a 99% reduction in lamination time from 26 min to 1 s. Perovskite samples that were laminated in 1 s exhibited comparable values of percent bonded area, interfacial toughness, grain domain size, and X‐ray diffraction spectra to those laminated in greater than 10 min. As a proof‐of‐concept, 18.3% efficient devices were successfully laminated in 5 s. A transient heat transfer model was developed to describe the relationship between the perovskite temperature and the electrical power supplied to the heaters, establishing a baseline for predicting processing conditions in large‐scale manufacturing systems. Ultra‐fast lamination provides a pathway toward scalable roll‐to‐roll or sheet‐to‐sheet manufacturing of PSCs.

heat transfer↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2025

Molecular level insight into non-bilayer structure formation in thylakoid membranes: a molecular dynamics study

In oxygenic photosynthetic organisms, the light reactions are performed by protein complexes embedded in the lipid bilayer of thylakoid membranes (TMs). The organization of the bulk lipid molecules into bilayer structures provide optimal conditions for the build-up of the proton motive force (pmf) and its utilization for ATP synthesis. However, the lipid composition of TMs is dominated by the non-bilayer lipid species monogalactosyl diacylglycerol (MGDG), and functional plant TMs, besides the bilayer, contain large amounts of non-bilayer lipid phases. Bulk lipids have been shown to be associated with lumenal, stromal-side and marginal-region proteins and proposed to play roles in the self-assembly and photoprotection of the photosynthetic machinery. Furthermore, it has recently been pointed out that the generation and utilization of pmf for ATP synthesis according to the ‘protet’ or protonic charge transfer model Kell (Biochim Biophys Acta Bioenerg 1865(4):149504, 2024), requires high MGDG content Garab (Physiol Plant 177(2):e70230, 2025). In this study, to gain better insight into the structural and functional roles of MGDG, we employed all atom and coarse-grained molecular dynamics simulations to explore how temperature, hydration levels and varying MGDG concentrations affect the structural and dynamic properties of bilayer membranes constituted of plant thylakoid lipids. Our findings reveal that MGDG promotes increased membrane fluidity and dynamic fluctuations in membrane thickness. MGDG-rich stacked bilayers spontaneously formed inverted hexagonal phases; these transitions were enhanced at low hydration levels and at elevated but physiologically relevant temperatures. It can thus be inferred that MGDG plays important roles in heat and drought stress mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Clumping index estimation with 30°-tilted cameras in row crops: Evaluation of methods and segment size effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Furthermore, applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

30°-tilted camera↗
DOE OSTI2026

Pu(IV) quantification via visible–near-infrared absorption spectroscopy: tackling interferences using D-optimal design and partial least squares

Here, this study presents a novel analytical approach for quantifying Pu(IV) in glove box environments using fiber-optic-based visible–near-infrared absorption spectroscopy in combination with partial least squares regression (PLSR) and design of experiments. The method addresses significant challenges posed by overlapping spectral features arising from Nd(III), which is a common fission product impurity, and the speciation variability of Pu(IV) nitrato complexes in HNO 3 concentrations ranging from 2.5 to 11 M. A curated training set consisting of data from 20 samples was developed via D-optimal design to enable robust PLSR model calibration for Pu(IV) using the near-infrared band near 1050 nm. The training set was acquired from samples in cuvettes with a 1-cm path length and was used to build the PLSR model. The robustness of the model was validated with data collected using a dip probe with a 1-cm path length and varying Pu(IV) concentrations. The strong performance of the model indicates good model transfer from cuvette to dip probe and highlights the potential for in situ measurements and online monitoring of reactions in a crystallization reactor vessel. The results demonstrate that this combined spectroscopic and chemometric approach can accurately and simultaneously quantify Pu(IV) and HNO 3 , thereby offering a promising tool for real-time monitoring in process environments.

Actinide↗
DOE OSTI2026

Real-Space Constrained Density Functional Theory Investigation of Site-Specific, Interfacial Charge Recombination Dynamics Across the Au Nanoparticle/TiO 2 Heterojunction

Au nanoparticle (NP)/TiO 2 heterojunction is a representative system to study interfacial charge transfer in photocatalysis and photovoltaics, where suppressing recombination from TiO 2 to Au can enhance hot carrier extraction. We apply real-space constrained density functional theory (CDFT) with Marcus theory to quantify charge recombination time scales across Au/TiO 2 . This approach enables direct control and visualization of charge-separated states, aligning with site-specific probes like time-resolved X-ray photoelectron spectroscopy (trXPS). We find that the charge-separated state features a bipolaron, with recombination dominated by TiO 2 LUMO to Au HOMO transitions, primarily at interfacial Au sites. Marcus rate predictions are benchmarked with surface hopping methods, quantifying differences in time scales and computational efficiency. Lastly, we examine how the Au cluster size affects the free energy change (ΔG) and reorganization energy (λ), explaining trends in closed-shell systems and highlighting challenges for open-shell extrapolations. Overall, CDFT + Marcus theory provides efficient, mechanistically transparent interfacial charge transfer modeling, and we clearly defined its applicability and limitation.

Glenna, Drew M. [Univ. of Idaho, Idaho Falls, ID (↗
DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗
DOE OSTI2025

Modeling cross-beam energy transfer with sector ray tracing

Ray-based cross-beam energy transfer (CBET) models are an essential feature of the radiation-hydrodynamic codes used to simulate inertial confinement fusion implosions, but full 3D ray-based CBET calculations can have a prohibitively high computational cost. Sector ray tracing can be used to reduce the cost by orders of magnitude in cases where the coronal plasma and laser drive can be approximated as spherically symmetric. An extension of sector ray tracing (section ray tracing) can be used to relax the assumption of a spherically symmetric drive while still retaining most of the computational savings of a sector ray trace. We discuss the foundations of sector and section ray tracing and compare them to full ray tracing.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A Fast and Accurate Reduced-Order Model for High-Intensity Transferred Arc Discharges

Arc discharges are widely used in welding, plasma smelting, and other industrial processes, where variations in operating conditions strongly affect arc stability, temperature distribution, and energy transfer. Accurate modeling of these phenomena typically requires computationally expensive high-fidelity simulations. This study presents a hierarchy of three arc discharge models with progressively reduced physical fidelity. The high-fidelity model provides a fully physics-resolved reference, the reduced-order model reproduces the dominant thermal and flow characteristics of the arc with reasonable accuracy, and the Elenbaas-Heller model captures key trends in a simplified, rapid formulation. This hierarchy demonstrates that reduced-order model can effectively balance predictive fidelity and computational efficiency, providing practical tools for arc simulation and parametric studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Uncovering the truth about M101, NGC 3938, and their significant others through radiative transfer

ABSTRACT Solving the inverse problem in spiral galaxies, that allows the derivation of the spatial distribution of dust, gas, and stars, together with their associated physical properties, directly from panchromatic imaging observations, is one of the main goals of this work. To this end, we used radiative transfer models to decode the spatial and spectral distributions of the nearby face-on galaxies M101 and NGC 3938. In both cases, we provide excellent fits to the surface-brightness distributions derived from GALEX, SDSS, 2MASS, Spitzer, and Herschel imaging observations. Together with previous results from M33, NGC 628, M51, and the Milky Way, we obtain a small statistical sample of modelled nearby galaxies that we analyse in this work. We find that in all cases Milky Way-type dust with Draine-like optical properties provide consistent and successful solutions. We do not find any ‘submm excess’, and no need for modified dust-grain properties. Intrinsic fundamental quantities like star-formation rates (SFR), specific SFR (sSFR), dust opacities, and attenuations are derived as a function of position in the galaxy and overall trends are discussed. In the SFR surface density versus stellar mass surface density space, we find a structurally resolved relation (SRR) for the morphological components of our galaxies, that is steeper than the main sequence (MS). Exception to this is for NGC 628, where the SRR is parallel to the MS.

Pricopi, D.↗
DOE OSTI2025

Thermal Conductivity Measurement of Extrusion-Printed Silver Using Modulated Photothermal Radiometry

Flexible printed electronics is a rapidly growing field with applications in conformal and flexible devices. However, the physical properties of the films created by many state-of-the-art printing methods become highly dependent on printing parameters, resulting in varying thermal properties often differing significantly from their bulk ink components. To understand the influence of the printing process, we build upon our previous work, where a noncontact optical technique, known as modulated photothermal radiometry (MPTR), was used to measure the thermal conductivity of aerosol-jet-printed thin films. In this work, we use the method to study the thermal properties of extrusion-printed silver on glass and alumina substrates. A noise-resistant data analysis fitting technique is applied using a 2-D heat transfer model. Here, the thermal conductivity measurement is validated using the Weidemann-Franz (WF) relationship from measured electrical conductivity values.

42 ENGINEERING↗
DOE OSTI2026

An Acid-Free, Temperature-Based Cation Contamination Removal Strategy for PEM Water Electrolysis

It is widely understood that the durability and reliability of polymer electrolyte membrane (PEM) water electrolyzers are heavily dependent on feedwater purity, with cation contaminants that originate from incomplete water purification and balance of plant materials significantly harming electrolyzer performance. However, contamination remains a challenge and a common cause of failure at the stack level, indicating the need for strategies to recover the performance of contaminated cells. In this study, we investigate the effects of temperature on the uptake, electrochemical impacts, and removal of contaminant calcium and iron cations. Lower operating temperatures increase the sensitivity of the cell performance to contaminant cations, while also decreasing cation uptake and promoting contaminant removal. Computational charge transfer modelling shows that lower temperature increases the concentration of contaminant at the cathode and facilitates their removal from the cell. By testing single cells under scenarios designed to mimic stack temperature dynamics, we investigate low-temperature operation as an approach to stack-relevant contaminant recovery. Together, these results demonstrate that the low-temperature recovery approach is a promising approach for acid-free contamination recovery for PEM water electrolysis to promote stack reliability and durability.

08 HYDROGEN↗
DOE OSTI2025

Gas Hydrate Film Growth in Microfluidic Channels for Carbon Dioxide Capture and Sequestration Applications

Gas or clathrate hydrates are a solid, crystalline compound composed of water and guest molecules that typically form at high pressure and low temperature conditions. Carbon dioxide (CO2) hydrates may be involved in several carbon dioxide capture and sequestration (CCS) applications, including CO2 pipeline transportation and CO2 offshore sequestration. Within these applications, the formation mechanism and kinetics must be well understood to manage the CCS processes, either by preventing or promoting hydrate formation. In this work, a high-pressure glass microfluidic reactor is used in tandem with visual microscopy and in-situ Raman spectroscopy to study both the morphological and kinetic behavior of gas hydrate crystals. Subcooling, pressure, and CO2 flow rate are investigated for their impact on the thickening behavior of pure CO2 hydrates, with flow rate being the only parameter to have a significant effect. Visual and Raman spectroscopy evidence show that both a dense hydrate layer and a porous hydrate layer form, and the latter may provide a path for mass transfer to continue hydrate crystallization. A first principles mass transfer model is developed to describe CO2 hydrate crystal thickening at the interface between gas and water. The impacts of gas impurities and channel wettability are also studied. This method is further applied to investigate the conversion of methane hydrate to CO2 hydrate for combined energy recovery and methane hydrate formation. The authors acknowledge the US Department of Energy Basic Energy Science award # DE-SC0022162.

Wadsworth, Lindsey [Colorado School of Mines, Gold↗
DOE OSTI2026

Deflagration to Detonation Transition Update: XDDT Code Modularization

A legacy FORTRAN 77 implementation of the Baer–Nunziato two-phase mixture theory for deflagration-to-detonation transition (DDT) in reactive granular materials—hereafter the XDDT (eXplosive DDT) code—has been modularized to Fortran 90 with modular structure, external input files, and adaptive mesh capability. During validation, two code defects were identified and corrected: an inconsistency in the nodal solid pressure evaluation and a nonphysical burn-front tracking criterion. The ignition criterion was also corrected to use the granular surface temperature from the interface heat transfer model, matching the original Baer implementation. An initial attempt to validate against Figure 3 of the original Baer and Nunziato (1986) paper revealed that the code’s detonation velocity on a 201-node mesh (5.5 km/s) was approximately 21% below the expected Chapman–Jouguet value for 70% TMD HMX (∼7 km/s). Validation was redirected to the piston-driven DDT experiments of McAfee et al. (1989), Shot B-9036, for which well-characterized ionization-pin data are available. With the compaction-burn coefficient calibrated to 𝐶 𝛼 = 75, the XDDT code reproduces the DDT transition time to within 0.4% and produces a steady-state detonation velocity within 4% of the McAfee experimental value of 6.36 km/s. The burn model was generalized to support pressure-dependent exponents, enabling application to nitrocellulose-based ball propellants (TS3659) with a cube-root pressure dependence. Validation against the Sandusky/Baer PDC82 piston-impact experiment yielded a reactive wave velocity of 2.3–2.8 km/s, in good agreement with the experimental value of ∼2.2 km/s, and wave coalescence within 5% of the experimental timing. The mathematical model, input parameter requirements, and a roadmap for extending XDDT to PETN with an autocatalytic burn model are presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗