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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance Assessment for the Environmental Restoration Disposal Facility (Annual Status Report FY 2022)

DOE O 435.1 and DOE M 435.1-1 require that a determination of continued adequacy of the performance assessment (PA) (CP-60089), composite analysis (CA), and disposal authorization statement (DAS) be made on an annual basis, and that the determination must consider the results of data collection and analysis from research, field studies, and monitoring as well as the need to update any Radioactive Waste Management Basis (RWMB) documents. Beginning in 1996, the Environmental Restoration Disposal Facility (ERDF) started accepting low-level radioactive, hazardous, and mixed wastes that were generated during cleanup activities at the Hanford Site. ERDF is composed of a series of cells or disposal areas and can accommodate future design expansions as needed. Currently, there are eight cells and two supercells in ERDF. Each supercell is the equivalent of two cells. During this reporting period (fiscal year 2022, extending from October 1, 2021, through September 30, 2022), approximately 8.52E+04 metric tons (9.39E+04 U.S. tons) of waste was disposed at ERDF. From ERDF inception through September 30, 2022, approximately 17.0 million metric tons (18.7 million U.S. tons) of waste has been disposed at ERDF, which equates to consumption of approximately 89.1% of the currently constructed disposal volume. According to the design of ERDF, the facility has the ability to be expanded as needed. As a condition of the DAS, disposal operations within ERDF must be in accordance with the waste acceptance criteria (ERDF-00011) that provide specific radionuclide disposal limits, waste form restrictions, and descriptions of acceptable waste packages in compliance with the requirements of DOE M 435-1.1. The ERDF waste acceptance criteria stipulate that waste destined for disposal at ERDF be controlled based on source, physical form, and contaminant concentration and activity levels. There have been no changes to the physical configuration of ERDF or to the waste forms (source, physical form, etc.). No new unreviewed disposal question screenings or evaluations have been generated in this reporting period. Therefore, there are no noted impacts to the PA, CA, DAS, or RWMB resulting from the evaluations and screenings. Sum-of-fractions analysis shows that the disposed inventory meets both the concentration and inventory threshold requirements. A sum-of-fractions value is computed for ERDF sensitive radionuclides contributing to the groundwater pathways and the air pathway inventory limits. Computed values were 5.50E-04 and 3.30E-03, respectively. The disposed waste inventory remained well under the PA imposed limits, as shown in Table 4 and Table 5 in the main text of this report. Required monitoring was satisfactorily completed during the fiscal year reporting period. Compliance with performance objectives were met as each of the reported values were well below the established limit. Overall, there are no substantive changes to primary PA assumptions or changes to the PA analysis conclusion; therefore, compliance with DOE O 435.1 and the DAS is maintained.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗
DOE OSTI2025

Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators

Abstract Real-time monitoring is a foundation of nuclear digital twin technology, crucial for detecting material degradation and maintaining nuclear system integrity. Traditional physical sensor systems face limitations, particularly in measuring critical parameters in hard-to-reach or harsh environments, often resulting in incomplete data coverage. Machine learning-driven virtual sensors offer a transformative solution by complementing physical sensors in monitoring critical degradation indicators. This paper introduces the use of Deep Operator Networks (DeepONet) to predict key thermal-hydraulic parameters in the hot leg of pressurized water reactor. DeepONet acts as a virtual sensor, mapping operational inputs to spatially distributed system behaviors without requiring frequent retraining. Our results show that DeepONet achieves low mean squared and Relative L2 error, making predictions 1400 times faster than traditional CFD simulations . These characteristics enable DeepONet to function as a real-time virtual sensor, synchronizing with the physical system to track degradation conditions and provide insights within the digital twin framework for nuclear systems.

Hossain, Raisa↗
DOE OSTI2026

Machine Protection Studies of Fast Instability-Driven Beam Losses in the EIC Electron Storage Ring

Fast transverse beam instabilities represent one of the most challenging protection scenarios for the Electron-Ion Collider (EIC) electron storage ring (ESR). Coherent betatron oscillations driven by collective effects can grow rapidly and lead to substantial beam losses within only a few tens of turns, posing a threat to collimators, superconducting (SC) magnets, cryogenic systems, and detector components. A dedicated simulation framework based on distributed transverse excitations was developed to evaluate instability-driven beam losses in the ESR. A conservative instability rise time on the order of 10 turns was used to define a bounding protection scenario. Simulations show that the original two-collimator configuration is insufficient to localize losses under all operating conditions, whereas an optimized four-collimator configuration reduces loss leakage into protected regions by more than two orders of magnitude. Nevertheless, the most severe instability scenarios produce catastrophic beam impacts, with nearly half of the stored beam being intercepted by the collimators within a single turn, exceeding the preliminary estimated survivability limits of the baseline collimator design. The results demonstrate that collimation alone is insufficient to guarantee safe ESR operation and must be complemented by a fast machine-protection system. Dedicated turn-by-turn beam-position monitors and fast beam-loss monitors provide sufficient advance warning to detect instability growth and initiate a beam abort before equipment-damaging loss levels are reached. These findings establish quantitative requirements for the ESR machine-protection architecture and support the implementation of a multilayer protection strategy for both accelerator and detector systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Intersubband Relaxation in CdSe Colloidal Quantum Wells

The dynamics of intersubband relaxation are critical to quantum well technologies such as quantum cascade lasers and quantum well infrared photodetectors. In this work, intersubband relaxation in CdSe colloidal quantum wells, or nanoplatelets, is studied via pump-push-probe transient spectroscopy. An initial interband pump pulse is followed by a secondary infrared push excitation, resonant with intersubband absorption, which promotes electrons from the first conduction band of the quantum well to the second conduction band. A probe pulse monitors subsequent electron cooling to the band edge of the quantum well. Using this technique, intersubband relaxation is studied as a function of critical variables such as colloidal quantum well size and thickness, surface ligand chemistry, temperature, and excitation pulse intensity. Larger quantum well sizes, judicious selection of surface ligand chemistry (e.g., thiolates), low temperatures, and elevated push pulse fluences slow intersubband relaxation. However, compared to resonant intraband relaxation in colloidal quantum dots (up to hundreds of picoseconds), intersubband relaxation in colloidal quantum wells is rapid (<1 ps) under all examined conditions. These experiments indicate that rapid relaxation is driven by both LO phonon and surface scattering. The short time scale of relaxation observed in these materials may hinder intersubband technologies such as mid-infrared detectors, although such rapid relaxation may prove valuable in optical switching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Novel Deep Learning Transformer Model for Short to Sub‐Seasonal Streamflow Forecast

Accurate short-to-subseasonal streamflow forecasts are becoming crucial for effective water management in an increasingly variable climate. However, streamflow forecast remains challenging over extended lead times, uncertainty in meteorological inputs, and increased frequency and variability in extreme weather and climate events. We implemented a Future Time Series Transformer (FutureTST) model for streamflow forecasting that separately integrates past meteorological and streamflow data while incorporating future weather conditions. FutureTST achieves a mean Nash-Sutcliffe Efficiency (NSE) of 0.82 to 0.67 for 1- to 30-day streamflow forecasts. Incorporating upstream streamflow information improved forecast accuracy by up to 10%. During real-time forecast, FutureTST maintains higher forecast skills of 9.03 for 1-day and 5.74 for 14-day forecasts. In contrast, calibrated process-based hydrological model forecasts become unreliable beyond a 4-day lead time. Our findings demonstrate the potential of FutureTST as a reliable streamflow forecasting tool that offers a valuable addition to operational flood monitoring systems and climate-resilient decision-making.

Ambika, Anukesh Krishnankutty [Oak Ridge National ↗
DOE OSTI2023

Unlocking the potential of DNA-based tagging: current market solutions and expanding horizons

The commercialization of DNA tagging is a growing trend that demonstrates the increasing practicality of this novel approach. This interdisciplinary technology is based on the distinctive characteristics of DNA as a molecule that can remain stable in varying environmental conditions and store data following appropriate preparation. Moreover, newly developed technologies could simplify DNA synthesis and the encoding of data within DNA. The implementation of DNA tagging presents distinctive benefits in comparison to conventional labelling techniques, including universal product code (UPC) barcoding, radio-frequency identification (RFID), quick response (QR) codes, and Bluetooth technologies, by surmounting the limitations encountered by these systems. The discourse pertains to extant DNA-tagging mechanisms along with prospective implementations in a wide range of domains, including but not limited to art, the metaverse, forensics, wildlife monitoring, and the military. The potential of DNA labelling in various contexts underscores the importance of continued research and development in this rapidly evolving field.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Health monitoring device

Example aspects of a volatile organic compound detection device, a wearable health monitoring device, and a method of monitoring a user's health are disclosed. The volatile organic compound detection device can comprise a collector comprising a collector material configured to collect volatile organic compounds given off from a user's skin; a separator comprising a gas chromatography column configured to separate mixtures of the volatile organic compounds into their constituent chemicals; and an identifier comprising a detector and a processor, the detector configured to transduce the constituent chemicals into a signal, the processor configured to process the signal to identify specific volatile organic compounds indicative of a health condition.

42 ENGINEERING↗
DOE OSTI2023

Assessment of InSAR Seasonal Movements at Bayou Choctaw SPR Site

Ground deformation is important to monitor for the ongoing safety and stability of underground caverns. Implementing InSAR technology to monitor site-wide surface deformation at the Strategic Petroleum Reserve has revealed seasonal ground movements at Bayou Choctaw in Louisiana. The cyclic, seasonal pattern shows soil shrinkage during the spring and summer months and soil expansion during the fall and winter months. Prior to this report, no in-depth investigation was conducted to explain this seasonal phenomenon. However, the ground movement is believed to be near-surface and not geological due to the relatively insignificant movement between years. To better understand seasonality movements, soil properties, land cover, and climatic conditions are assessed to relate near-surface water and soil interactions. The soil, land, and climatic properties all contribute to seasonal ground movement, and vegetation cover and the soil's water capacity contribute to the spatial variability of InSAR seasonal measurements at Bayou Choctaw.

02 PETROLEUM↗
DOE OSTI2025

In Situ Spectroscopic Monitoring of MSR Molten Salt and Off-Gas Systems

A significant challenge that must be overcome before commercialization of molten salt reactors is tracking special nuclear material (SNM) through the reactor and subsystems such as fuel chemical processing and off-gas systems. In recent years, several approaches have been explored to track SNM, fission products, and corrosion products in these different subsystems. One such approach is to employ laser and optical spectroscopy to measure the atomic and molecular signals of MSR salts. The advantages of these approaches are that they typically are non-intrusive and offer the capability of process monitoring while still providing low uncertainties. At the Idaho National Laboratory, spectroscopy approaches such as laser-induced breakdown spectroscopy (LIBS) and ultraviolet-visible (UV-Vis) spectroscopy have been utilized to investigate molten salts in an aerosol (LiCl, KCl, RbCl2, NdCl3, and PrCl3) and vapor phases (MgCl5, NdCl5, and ZrCl4) with success. Testing to date has yielded qualitative information on all the above species and quantitative data and analytical figures of merit for species in the vapor phases. These findings, including results from ongoing testing, as well as the experimental conditions and potential applications will be presented.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2024

Dynamic changes in evapotranspiration, canopy photosynthesis and expansive growth in open field under rapid fluctuating radiation

Abstract In open fields, plants experience dynamic changes in environment, particularly radiation, temperature, wind, and humidity but their short-term responses have not been adequately characterized under natural conditions. In this study, we assessed causal effects of rapid radiation fluctuation on seven plant parameters in open fields of cotton and sweet corn canopies. The parameters are evapotranspiration ( ET ), canopy photosynthesis indicated by CO2 flux from air to canopy ( FCO2 ), sensible heat energy flux ( H ), canopy conductance for water vapor ( gcw ), canopy surface temperature ( Ts ), shoot and leaf elongation rate, and stem diameter change. The energy and CO2 fluxes were measured with Bowen ratio/energy balance/CO2 gradient (BREB+) technique, using averaging time of 5 min. Shoot + leaf elongation and stem diameter change were monitored with position transducers using averaging time of 1 min. All parameters were all found to respond to change in radiation and transpiration within minutes or sooner. While radiation effects on canopy gas exchanges are expected, illuminating are the indirect but immediate effects on shoot + leaf growth and stem diameter change through radiation effects on transpiration and plant water status. A novel finding is that gcw also responded within minutes or sooner to radiation fluctuations and that FCO2 was related almost linearly to gcw . Results are discussed in terms of soil-plant-atmosphere continuum, and interpreted in terms of dynamic interactions between transpiration and plant water status. The clear inverse relationship between ET and elongation rate or stem diameter changes provides additional evidence supporting the validity of 5-min averaging for the BREB + technique.

Hsiao, Theodore C.↗
DOE OSTI2022

All-Inorganic Open-Framework Chalcogenides, A 3 Ga 5 S 9 · x H 2 O ( A = Rb and Cs), Exhibiting Ultrafast Uranyl Remediation and Illustrating a Novel Post-Synthetic Preparation of Open-Framework Oxychalcogenides

Fast and effective uranyl sequestration is of interest to the nuclear industry. Recently layered chalcogenide materials have demonstrated fast, selective, and efficient sorption properties towards uranyl cations and the development and investigation of new types of chalcogenide materials continues to be of interest and represents an intriguing option for uranyl remediation. Three new all-inorganic A 3 Ga 5 S 9 ·xH 2 O (A = Rb, Rb/Cs, and Cs) open-framework chalcogenides were obtained via an in-situ alkali carbonate to alkali sulfide conversion process achieved under mild hydrothermal conditions. The structures of the all-inorganic open framework chalcogenides consist of a 2-fold interpenetrated diamond-like 3D framework containing pseudo-T 3 [Ga 10 S 20 ] 10– supertetrahedra. 48% of the structural volume is occupied by A + cations and water species, as established by single-crystal X-ray diffraction (SCXRD), infrared (IR) and energy-dispersive (EDS) spectroscopies. The dynamic nature of the A + cations and water molecules within the pores was investigated via single crystal X-ray diffraction as well as by IR spectroscopy monitored H 2 O to D 2 O exchange experiments. Framework stability was probed with post-synthetic treatment of A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples in acidic solutions that resulted in the formation of the oxysulfide (A/H) 3 Ga 5 S 9–y O y ·xH 2 O (A = Rb and Cs; y = 0–1), as shown by SCXRD and IR. Ion-exchange studies on A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples were carried out utilizing a uranyl acetate solution. The presence of the UO 2 2+ species in the ion-exchanged product was supported by IR and EDS spectroscopies. Batch method ion-exchange experiments on Cs 3 Ga 5 S 9 ·xH 2 O powder demonstrated fast kinetics with 95% uranyl removal from the uranyl acetate solution during the first minute, a maximum uranyl uptake capacity of 15mg/g, and the subsequent elution of uranyl species with KCl solution. Furthermore, the porous and dynamic nature of the A 3 Ga 5 S 9 ·xH 2 O framework coupled with effective UO 2 2+ ···S 2– bonding interactions makes it a good potential sorbent for uranyl remediation from aqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH 4 + ) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Solving k –SAT problems with generalized quantum measurement

We generalize the projection–based quantum measurement–driven k –SAT algorithm of Benjamin, Zhao, and Fitzsimons to arbitrary strength quantum measurements, including the limit of continuous monitoring. In doing so, we clarify that this algorithm is a particular case of the measurement–driven quantum control strategy elsewhere referred to as “Zeno dragging”. We argue that the algorithm is most efficient with finite time and measurement resources in the continuum limit, where measurements have an infinitesimal strength and duration. Moreover, for solvable k -SAT problems, the dynamics generated by the algorithm converge deterministically towards target dynamics in the long–time (Zeno) limit, implying that the algorithm can successfully operate autonomously via Lindblad dissipation, without detection. We subsequently study both the conditional and unconditional dynamics of the algorithm implemented via generalized measurements, quantifying the advantages of detection for heralding errors. These strategies are investigated first in a computationally–trivial 2-qubit 2-SAT problem to build intuition, and then we consider the scaling of the algorithm on 3-SAT problems encoded with 4–10 qubits. We numerically investigate the scaling of 3-SAT with respect to algorithmic runtime and find that the optimized time to solution scales with qubit number n as λ n , where λ is slightly larger than $\sqrt{2}$ for unconditional dynamics and less than $\sqrt{2}$ for conditional dynamics. We assess the implications for using this analog measurement–driven approach to quantum computing in practice.

quantum information↗
DOE OSTI2024

Benchmarking the Suitability of Novec$^{\mathrm{TM}}$ 4710 for Application in Flux Compression Generators

Here, an experimental study evaluated the feasibility of replacing traditional insulating gases such as SF 6 with C 4 F 7 N (3M TM , Novec 4710) in flux compression generator (FCG) applications. Currently available data indicate that Novec 4710 could offer certain performance benefits over SF 6 . However, the available literature is focused on low frequency (50–60 Hz) and dc at static pressures. To evaluate the performance of Novec 4710 under the pulsed dynamic pressure and temperature conditions found in an FCG, we report a performance comparison between three sets of identical FCGs using air, SF 6 , and Novec 4710 as the insulating gas. The generators used in this study had a single stage, directly seeded design with an armature diameter of 25 mm and a stator diameter of 46 mm. To highlight the performance of the different gases rather than any wire insulation, the stator was constructed with uninsulated wire. Furthermore, the generators were seeded aggressively, making the performance difference between the different gases more apparent. The performance was monitored with a pair of differential Rogowski coils that captured the generators’ di / dt while also using high-speed videography to capture possible gaseous breakdown signatures. The data gathered during this study indicate that Novec 4710 performs at least as well as SF 6 in FCG applications, if not significantly better.

42 ENGINEERING↗
DOE OSTI2025

Hardware-Based Demonstration of Temperature Control Functions for Reactor Systems

Establishing autonomy in reactor control systems has become essential for the expansion of nuclear technologies. Thermal regulation in particular remains crucial for maintaining stable operation and ensuring the integrity of fuel. To alleviate public skepticism of the safety of nuclear reactors, demonstrating control over this key factor is pivotal. Utilizing electric heat pads to simulate the heat released in a reactor core, thermocouples for temperature monitoring, and an Arduino micro programmable logic controller (PLC) for control, a hardware-based demonstration of a reactor heating system validates the efficacy of reactor control over this key parameter. To improve precision, a proportional-integral-derivative (PID) algorithm was implemented in the heating control loop to ensure meticulous control of reactor functions. In addition, the integration of this physical system with a digital simulator tool such as RELAP5-3D establishes a foundation for a comprehensive testing environment. This allows for a refinement of temperature control under various simulated reactor conditions, bringing another layer of reliability to the operation of the system. By facilitating a physical demonstration of reactor thermal management and control strategies, this project provides a foundation for expanded testing and educational outreach. Ultimately, this system advances the broader goal of demonstrating the safety and viability of autonomous reactor operations, contributing to public trust and future reactor deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Stochastic Thermo-Hydro Modeling and Neural Network Surrogate Development for Thermal Resource Assessment of the Galleries-to-Calories Geobattery

The Galleries-to-Calories Geobattery concept explores the use of abandoned coal mine workings for large-scale thermal energy transport and storage. The system involves injecting waste heat from a supercomputing facility into flooded mine galleries, where groundwater flow can store and transport thermal energy for potential recovery in downgradient district heating and cooling applications. To evaluate the feasibility and performance of the Geobattery under geological and operational uncertainty, we developed a suite of stochastic thermo-hydrological (TH) simulations using Monte Carlo sampling of key uncertain parameters (e.g., permeability, porosity, thermal conductivity, specific heat capacity) and operating conditions (e.g., injection rate, injection temperature). Results identified injection rate and temperature as the most influential parameters governing thermal front propagation, while the geometry of the room-and-pillar structure played a critical role in directing the extent and orientation of thermal advancement. Optimal combinations of material properties for maximizing heat recovery were also determined. To address the high computational cost of coupled-process stochastic modeling, we trained a neural network surrogate model on 24,000 physics-based realizations, achieving an R² > 0.99 and MAE < 0.1 for temperature predictions at monitoring locations. This surrogate enabled an additional 100,000 realizations for global sensitivity analysis and probabilistic thermal resource assessment. The integrated stochastic physics–surrogate modeling framework offers a computationally efficient tool for quantifying uncertainty, identifying key drivers, and informing early-stage design decisions for Geobattery systems.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2023

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Abstract Predicting failure in solids has broad applications including earthquake prediction which remains an unattainable goal. However, recent machine learning work shows that laboratory earthquakes can be predicted using micro-failure events and temporal evolution of fault zone elastic properties. Remarkably, these results come from purely data-driven models trained with large datasets. Such data are equivalent to centuries of fault motion rendering application to tectonic faulting unclear. In addition, the underlying physics of such predictions is poorly understood. Here, we address scalability using a novel Physics-Informed Neural Network (PINN). Our model encodes fault physics in the deep learning loss function using time-lapse ultrasonic data. PINN models outperform data-driven models and significantly improve transfer learning for small training datasets and conditions outside those used in training. Our work suggests that PINN offers a promising path for machine learning-based failure prediction and, ultimately for improving our understanding of earthquake physics and prediction.

42 ENGINEERING↗