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Development of Thermoacoustic Sensors for Sodium-cooled Fast Reactors

This Final Report refers to the project “Development of Thermoacoustic Sensors for Sodium-cooled Fast Reactor Systems”, which was led by Westinghouse Electric Company (Westinghouse) and carried out in collaboration with Argonne National Laboratory (ANL) and University of Pittsburgh. Thermo-acoustic Power Sensors (TAPS) are self-powered, wireless sensors envisioned for measuring key parameters, such as local temperature and neutron flux, in a nuclear reactor core. This project was intended to specifically investigate their applicability to Sodium-cooled Fast Reactors (SFR). TAPS are non-invasive (wireless) and passive (self-powered) devices. The passivity derives from their ability to use conditions that “naturally” exist in a nuclear reactor, such as gamma and neutron flux, as power sources. They generate oscillating pressure waves (i.e., sound waves) which, with a frequency and amplitude dependent upon these conditions, can travel through the core and associated structures, and reach the outside of the reactor vessel where a properly designed network of receivers can detect and interpret them. These receivers require a very small amount of power which, during loss of power events, can be provided for example by harvesting gamma radiation energy, thus resulting in a monitoring system that can function both during normal operation and during loss of power events. The project aimed at TAPS development through a series of tasks which are listed and briefly discussed as follows. TASK 1 – Sensor hardware design Subtask 1a: Assessment of sensor applications to SFRs Subtask 1b: Development of sensor functional requirements Subtask 1c: Definition of sensor hardware design specifications Task description: TAPS design was informed by considerations on their application (Subtask 1a), both the ultimate one in an SFR and the actual one in the ANL testing facilities that was intended to be used in support of the project. Considerations were made to identify optimum sensor design features that optimize the sensor size, materials, and output signal, for installation inside an SFR core. These considerations led to the development of Functional Requirements (Subtask 1b) and Design Requirements (Subtask 1c). TASK 2 – Sensor Hardware Manufacture Subtask 2a: Sensor hardware construction drawing development Subtask 2b: Sensor manufacture and assembly Task description: TAPS technical drawings were developed (Subtask 2a) using the Design Requirements established under Task 1. Subsequently, in spite of some problems which ultimately caused the program to be delayed, TAPS manufacturing was completed based on drawings (Subtask 2b). TASK 3 – Development of TAPS Signal Measurement System and TAPS Testing in Water Subtask 3a: Design, assembly and testing of signal measurement system, and TAPS testing in water Subtask 3b: Signal prediction-correction methodology development Task description: An assessment was performed on the techniques that can potentially be used to detect the signals emitted by the TAPS, e.g. a fiber-optic based acoustic signal measurement system, a laser vibrometer system, or an accelerometer-based system. The most suited technology, i.e. the accelerometer-based system, was developed further, and tested in water (Subtask 3a). Moreover, efforts were made to develop the methodology required to determine the actual system temperature and neutron flux distribution using differences between the measured and predicted TAPS responses (Subtask 3b). TASK 4 – Sensor System Testing in Sodium Subtask 4a: Test plan development Subtask 4b: Design, assembly and testing in small-scale sodium facility Subtask 4c: Design, assembly and testing in large-scale sodium and structures facility Task description: Upon proper test plan development (Subtask 4a), the fabricated TAPS was planned to be tested in sodium, by using two sodium facilities at ANL having different size and different purpose. The Under Sodium Viewing (USV) small-scale facility was intended to be used to investigate the effect of sodium on the sensor and its performance (Subtask 4b). The Mechanism Engineering Test Loop (METL) large-scale facility was instead intended to be used to assess the additional effect of prototypical SFR structures, such as fuel assembly mockup or parts of the core restrain structure, on sensor performance (Subtask 4c). As discussed in Section 3.2.2.7, unexpected issues during the TAPS manufacturing process resulted in some activities being delayed, with the TAPS and USV facility developed to the point to be ready for testing in sodium, however without the possibility to actually perform such testing (including the testing in METL) due to the end of the program’s performance period. Overall, through the development and testing (in water only) of two TAPS devices (a First-Generation TAPS followed by an optimized Second-Generation TAPS), the project confirmed the capability of this technology to generate acoustic signals proportional to temperature, which can be detected through a network of accelerometers identified as the best-suited type of receivers for acoustic signal detection. Moreover, the project also developed a computational model to predict the characteristics of the acoustic signals being generated, which combines thermal analysis of the TAPS with Finite Element Modeling (FEM)-aided acoustic characterization of the system. This model was benchmarked against experimental data collected during the project and, although general agreement was obtained, some limitations of the modeling methods were identified, which require additional development. Additional testing is needed in order to assess the effect, on TAPS operation and performance, of environmental changes resulting from the transition from water to liquid sodium. Such testing, which is suggested to be performed in the future, should look specifically at 1) both the effect resulting from the different thermoacoustic behavior of sodium (relative to water) and the effects of higher temperature on TAPS performance, and 2) the performance of the sensor-receiver system when multiple TAPS are used simultaneously and prototypical reactor structures are positioned in the testing environment. The latter testing is needed to assess the effects that potential signal attenuation/ distortion phenomena, as well as potential interference between signals emitted simultaneously, have on the performance of the technology for ultimate application in a nuclear reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

AREVA NP's industrial CFD single-phase methodology and applications for nuclear fuel

During the course of the last decade, AREVA NP has developed Computational Fluid Dynamics (CFD) methods capable of accurately predicting flow fields and thermal mixing within fuel bundles, as well as pressure losses and hydrodynamic forces on fuel assembly components such as spacer grids, lower and upper nozzles. The present work summarizes the evolution of AREVA NP's single-phase CFD methodology and the extensive validation efforts, with focus on improving confidence level in CFD results. Currently, it is possible to produce models for large sections of a fuel assembly and produce CFD simulation results with an uncertainty proven to be similar to the corresponding measurement uncertainty. Extensive validation has been conducted against in-house data obtained for a wide range of geometries representative of actual hardware, in multiple test facilities, with various measurement techniques. In addition to in-house validation data, AREVA NP has also exercised its best-practices against international benchmarks; blind test results were in very good agreement with the data. The current high level of confidence in single-phase CFD predictions allows investigating a wide variety of physics in Pressurized Water Reactor (PWR) as well as Boiling Water Reactor (BWR) fuel assemblies. CFD is used as a design and optimization tool as well as a supplement to regular testing to improve the quality of tests and optimize hardware design features for specific targets. CFD played a major role in the design of AREVA NP's latest fuel assembly designs (ATRIUM{sup TM1} 11 and GAIA). In this paper we first illustrate AREVA NP's comprehensive validation database for single-phase CFD (pressure drop, flow field), then provide several examples of applications: virtual testing for parts optimization and support of core operation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Deep learning model to detect various synchrophasor data anomalies

High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Additionally, four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.

42 ENGINEERING↗

Qubit Assignment Using Time Reversal

As quantum computers with large numbers of qubits become increasingly available, experiments executed on a given device may not utilize all available qubits. In this case, the outcome of executing a quantum program will depend on the ability to efficiently select a subset of high-performing physical qubits. For any given quantum program and device there are many ways to assign physical qubits for execution of the program, and assignments will differ in performance due to the variability in quality across qubits and entangling operations on a single device. Evaluating the performance of each assignment using fidelity estimation introduces significant experimental overhead and will be infeasible for many applications, while relying on standard device benchmarks provides incomplete information about the performance of any specific program. Furthermore, the number of possible assignments grows combinatorially in the number of qubits on the device and in the program, motivating the use of heuristic optimization techniques. We demonstrate a practical solution to the problem of qubit assignment by using simulated annealing with a cost function based on the Loschmidt echo, a diagnostic that measures the reversibility of a quantum process. We provide theoretical justification for this choice of cost function by demonstrating that the optimal qubit assignment coincides with the optimal qubit assignment based on state fidelity in the weak error limit, and we provide experimental justification using diagnostics performed on Google’s superconducting qubit devices. We then establish the performance of simulated annealing for qubit assignment using classical simulations of noisy devices as well as optimization experiments performed on a quantum processor. Our results demonstrate that the use of Loschmidt echoes and simulated annealing provides a scalable and flexible approach to optimizing qubit assignment on near-term hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Resilience of the surface code to error bursts

Quantum error correction works effectively only if the error rate of gate operations is sufficiently low. However, some rare physical mechanisms can cause a temporary increase in the error rate that affects many qubits; examples include ionizing radiation in superconducting hardware and large deviations in the global control of atomic systems. We refer to such rare transient spikes in the gate error rate as error bursts. In this work, we investigate the resilience of the rotated surface code to generic error bursts. We assume that, after appropriate mitigation strategies, the spike in the error rate lasts for only a single syndrome-extraction cycle; we also assume that the enhanced error rate is uniform across the code block. Under these assumptions, and for a circuit-level depolarizing noise model, we perform Monte Carlo simulations to determine the regime in burst error rate and background error rate for which the memory time becomes arbitrarily long as the code block size grows. Our results indicate that suitable hardware mitigation methods combined with standard decoding methods may suffice to protect against transient error bursts in the rotated surface code.

Quantum error correction↗

Classification of dynamical Lie algebras generated by spin interactions on undirected graphs

Dynamical Lie algebras (DLAs) are a versatile tool for various topics that span from the expressibility-trainability of variational quantum algorithms (VQAs), to simulation of many body Hamiltonians. Quantum gates and most of the Hamiltonians of interest consist of local interactions; therefore, the analysis of all possible DLAs generated by 1- and 2-local operators is crucial for quantum simulation and VQAs on current hardware. Previously in [R. Wiersema et al ., npj Quantum Inf. 10 , 110 (2024)], we analyzed the DLAs on linear, circular and all-to-all topologies, and obtained results about their dimensions and algebraic structure. Here, in this work, we extend our analysis into any possible hardware topology and provide a classification of all DLAs generated by Pauli strings on any undirected interaction graph. Our results indicate that the DLAs depend solely on whether the connectivity or interaction graph is bipartite or not. In addition, we find that the non-trivial polynomially scaling DLAs appear only on 1D line or circle topologies, and all other DLAs have dimensions scaling exponentially with the system size. Together with the current VQA literature, our results imply that either the majority of VQAs are non-trainable, or we are yet to understand the role of DLAs on the trainability of VQAs.

Algebraic structures↗

A Systems Engineering Analysis of National Ignition Facility Industrial Controls Systems and Safety Interlock Systems Remote Input/Output Networking Migration from ControlNet to EtherNet/IP

The ControlNet industrial communications protocol and modules used in the Industrial Control System (ICS) and Safety Interlock System (SIS) at the National Ignition Facility (NIF) are no longer necessary and the ICS and SIS would be better served by migrating the communications structure to use EtherNet/Industrial Protocol (IP) and EtherNet bridge modules instead. By the admission of the vendor of ControlNet hardware, Rockwell Automation, in literature by Bill Petro [1], “Moving forward, customers will be able to optimize their asset utilization better using EtherNet/IP protocol than with ControlNet.” The NIF is one of the key elements of the Inertial Confinement Fusion (ICF) program at Lawrence Livermore National Laboratory (LLNL), a federally funded research and development center (FFRDC). The NIF contains the systems and provides the operational capacity to perform ICF, high energy density (HED), and discovery science experiments utilizing 192 individual beamlines, a host of diagnostics, and all the industrial systems required to facilitate these beamlines and diagnostics. The industrial systems are governed by the ICS and SIS, with the ICS providing control and the SIS providing monitoring and permissives. Construction on the NIF began in 1997 and was certified complete in 2009 and, as a result, the ICS and SIS were developed during this time using the tools that were available then. This includes the communications structure and protocols for these systems, much of which was, and still is, ControlNet. ControlNet, particularly during the time that the ICS and SIS were being built, has several attractive features. ControlNet hardware is exclusive to Rockwell Automation, which was the automation hardware chosen for the ICS and SIS. One feature that could be considered an advantage or a disadvantage depending on the communication needs of the system is that ControlNet also utilizes no active network components, excluding repeaters which are not always necessary. According to the architect of the ICS system at the NIF, Gordon Lau, one of the most attractive features of the ControlNet protocol during development of the ICS and SIS was that it is deterministic, providing timing of data transfer that is executed exactly as it is defined by the developer.

42 ENGINEERING↗

MO-AB-206-00: Nuclear Medicine Physics and Testing

This education session will cover the physics and operation principles of gamma cameras and PET scanners. The first talk will focus on PET imaging. An overview of the principles of PET imaging will be provided, including positron decay physics, and the transition from 2D to 3D imaging. More recent advances in hardware and software will be discussed, such as time-of-flight imaging, and improvements in reconstruction algorithms that provide for options such as depth-of-interaction corrections. Quantitative applications of PET will be discussed, as well as the requirements for doing accurate quantitation. Relevant performance tests will also be described. Learning Objectives: Be able to describe basic physics principles of PET and operation of PET scanners. Learn about recent advances in PET scanner hardware technology. Be able to describe advances in reconstruction techniques and improvements Be able to list relevant performance tests. The second talk will focus on gamma cameras. The Nuclear Medicine subcommittee has charged a task group (TG177) to develop a report on the current state of physics testing of gamma cameras, SPECT, and SPECT/CT systems. The report makes recommendations for performance tests to be done for routine quality assurance, annual physics testing, and acceptance tests, and identifies those needed satisfy the ACR accreditation program and The Joint Commission imaging standards. The report is also intended to be used as a manual with detailed instructions on how to perform tests under widely varying conditions. Learning Objectives: At the end of the presentation members of the audience will: Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of gamma cameras for planar imaging. Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of SPECT systems. Be familiar with the tests of a SPECT/CT system that include the CT images for SPECT reconstructions. Become knowledgeable of items to be included in annual acceptance testing reports including CT dosimetry and PACS monitor measurements. T. Turkington, GE Healthcare.

61 RADIATION PROTECTION AND DOSIMETRY↗

Milestone 49 Report: Batched Sparse LA Phase 5 Implementation

Batched sparse linear algebra operations in general, and solvers in particular, have become the major algorithmic development activity and foremost performance engineering effort in the numerical software libraries work on modern hardware with accelerators such as GPUs. Many applications, ECP and non-ECP alike, require simultaneous solutions of many small linear systems of equations that are structurally sparse in one form or another. In order to move towards high hardware utilization levels, it is important to provide these applications with appropriate interface designs to be both functionally efficient and performance portable and give full access to the appropriate batched sparse solvers running on modern hardware accelerators prevalent across DOE supercomputing sites since the inception of ECP. To this end, we present here a summary of recent advances on the interface designs in use by HPC software libraries supporting batched sparse linear algebra and the development of sparse batched kernel codes for solvers and preconditioners. We also address the potential interoperability opportunities to keep the corresponding software portable between the major hardware accelerators from AMD, Intel, and NVIDIA, while maintaining the appropriate disclosure levels conforming to the active NDA agreements. The presented interface specifications include a mix of batched band, sparse iterative, and sparse direct solvers with their accompanying functionality that is already required by the application codes or we anticipated to be needed in the near future. This report summarizes progress in Kokkos Kernels and the xSDK libraries MAGMA, Ginkgo, hypre, PETSc, and SuperLU.

97 MATHEMATICS AND COMPUTING↗

MO-AB-206-02: Testing Gamma Cameras Based On TG177 WG Report

This education session will cover the physics and operation principles of gamma cameras and PET scanners. The first talk will focus on PET imaging. An overview of the principles of PET imaging will be provided, including positron decay physics, and the transition from 2D to 3D imaging. More recent advances in hardware and software will be discussed, such as time-of-flight imaging, and improvements in reconstruction algorithms that provide for options such as depth-of-interaction corrections. Quantitative applications of PET will be discussed, as well as the requirements for doing accurate quantitation. Relevant performance tests will also be described. Learning Objectives: Be able to describe basic physics principles of PET and operation of PET scanners. Learn about recent advances in PET scanner hardware technology. Be able to describe advances in reconstruction techniques and improvements Be able to list relevant performance tests. The second talk will focus on gamma cameras. The Nuclear Medicine subcommittee has charged a task group (TG177) to develop a report on the current state of physics testing of gamma cameras, SPECT, and SPECT/CT systems. The report makes recommendations for performance tests to be done for routine quality assurance, annual physics testing, and acceptance tests, and identifies those needed satisfy the ACR accreditation program and The Joint Commission imaging standards. The report is also intended to be used as a manual with detailed instructions on how to perform tests under widely varying conditions. Learning Objectives: At the end of the presentation members of the audience will: Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of gamma cameras for planar imaging. Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of SPECT systems. Be familiar with the tests of a SPECT/CT system that include the CT images for SPECT reconstructions. Become knowledgeable of items to be included in annual acceptance testing reports including CT dosimetry and PACS monitor measurements. T. Turkington, GE Healthcare.

61 RADIATION PROTECTION AND DOSIMETRY↗

MO-AB-206-01: PET Physics

This education session will cover the physics and operation principles of gamma cameras and PET scanners. The first talk will focus on PET imaging. An overview of the principles of PET imaging will be provided, including positron decay physics, and the transition from 2D to 3D imaging. More recent advances in hardware and software will be discussed, such as time-of-flight imaging, and improvements in reconstruction algorithms that provide for options such as depth-of-interaction corrections. Quantitative applications of PET will be discussed, as well as the requirements for doing accurate quantitation. Relevant performance tests will also be described. Learning Objectives: Be able to describe basic physics principles of PET and operation of PET scanners. Learn about recent advances in PET scanner hardware technology. Be able to describe advances in reconstruction techniques and improvements Be able to list relevant performance tests. The second talk will focus on gamma cameras. The Nuclear Medicine subcommittee has charged a task group (TG177) to develop a report on the current state of physics testing of gamma cameras, SPECT, and SPECT/CT systems. The report makes recommendations for performance tests to be done for routine quality assurance, annual physics testing, and acceptance tests, and identifies those needed satisfy the ACR accreditation program and The Joint Commission imaging standards. The report is also intended to be used as a manual with detailed instructions on how to perform tests under widely varying conditions. Learning Objectives: At the end of the presentation members of the audience will: Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of gamma cameras for planar imaging. Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of SPECT systems. Be familiar with the tests of a SPECT/CT system that include the CT images for SPECT reconstructions. Become knowledgeable of items to be included in annual acceptance testing reports including CT dosimetry and PACS monitor measurements. T. Turkington, GE Healthcare.

61 RADIATION PROTECTION AND DOSIMETRY↗

High-Speed Ionic Synaptic Memory Based on 2D Titanium Carbide MXene

Synaptic devices with linear high-speed switching can accelerate learning in artificial neural networks (ANNs) embodied in hardware. Conventional resistive memories however suffer from high write noise and asymmetric conductance tuning, preventing parallel programming of ANN arrays. Electrochemical random-access memories (ECRAMs), where resistive switching occurs by ion insertion into a redox-active channel, aim to address these challenges due to their linear switching and low noise. ECRAMs using 2D materials and metal oxides however suffer from slow ion kinetics, whereas organic ECRAMs enable high-speed operation but face challenges toward on-chip integration due to poor temperature stability of polymers. Here, ECRAMs using 2D titanium carbide (Ti 3 C 2 T x ) MXene that combine the high speed of organics and the integration compatibility of inorganic materials in a single high-performance device are demonstrated. These ECRAMs combine the speed, linearity, write noise, switching energy, and endurance metrics essential for parallel acceleration of ANNs, and importantly, they are stable after heat treatment needed for back-end-of-line integration with Si electronics. The high speed and performance of these ECRAMs introduces MXenes, a large family of 2D carbides and nitrides with more than 30 stoichiometric compositions synthesized to date, as promising candidates for devices operating at the nexus of electrochemistry and electronics.

2D materials↗

Probabilistic Nanomagnetic Memories for Uncertain and Robust Machine Learning

This project evaluated the use of emerging spintronic memory devices for robust and efficient variational inference schemes. Variational inference (VI) schemes, which constrain the distribution for each weight to be a Gaussian distribution with a mean and standard deviation, are a tractable method for calculating posterior distributions of weights in a Bayesian neural network such that this neural network can also be trained using the powerful backpropagation algorithm. Our project focuses on domain-wall magnetic tunnel junctions (DW-MTJs), a powerful multi-functional spintronic synapse design that can achieve low power switching while also opening the pathway towards repeatable, analog operation using fabricated notches. Our initial efforts to employ DW-MTJs as an all-in-one stochastic synapse with both a mean and standard deviation didn’t end up meeting the quality metrics for hardware-friendly VI. In the future, new device stacks and methods for expressive anisotropy modification may make this idea still possible. However, as a fall back that immediately satisfies our requirements, we invented and detailed how the combination of a DW-MTJ synapse encoding the mean and a probabilistic Bayes-MTJ device, programmed via a ferroelectric or ionically modifiable layer, can robustly and expressively implement VI. This design includes a physics-informed small circuit model, that was scaled up to perform and demonstrate rigorous uncertainty quantification applications, up to and including small convolutional networks on a grayscale image classification task, and larger (Residual) networks implementing multi-channel image classification. Lastly, as these results and ideas all depend upon the idea of an inference application where weights (spintronic memory states) remain non-volatile, the retention of these synapses for the notched case was further interrogated. These investigations revealed and emphasized the importance of both notch geometry and anisotropy modification in order to further enhance the endurance of written spintronic states. In the near future, these results will be mapped to effective predictions for room temperature and elevated operation DW-MTJ memory retention, and experimentally verified when devices become available.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Differentiable physics-enabled closure modeling for Burgers’ turbulence

Abstract Data-driven turbulence modeling is experiencing a surge in interest following algorithmic and hardware developments in the data sciences. We discuss an approach using the differentiable physics paradigm that combines known physics with machine learning to develop closure models for Burgers’ turbulence. We consider the one-dimensional Burgers system as a prototypical test problem for modeling the unresolved terms in advection-dominated turbulence problems. We train a series of models that incorporate varying degrees of physical assumptions on an a posteriori loss function to test the efficacy of models across a range of system parameters, including viscosity, time, and grid resolution. We find that constraining models with inductive biases in the form of partial differential equations that contain known physics or existing closure approaches produces highly data-efficient, accurate, and generalizable models, outperforming state-of-the-art baselines. Addition of structure in the form of physics information also brings a level of interpretability to the models, potentially offering a stepping stone to the future of closure modeling.

97 MATHEMATICS AND COMPUTING↗

Wind Power as a Virtual Synchronous Generator (WindVSG)

This project investigated the theory, implemented it in hardware, and validated the Wind as a Virtual Isochronous Generator (WindVSG) concept by combining the advantages of modern dynamic inverter technologies with static, dynamic, and transient electromechanical properties of synchronous machines. During this project we demonstrated how to control the inverters of wind turbine generators (wind alone or in parallel with other GFM sources, such battery energy storage) so that wind power behaves like a synchronous machine-based power plant with a conventional prime mover. For this purpose, testing was conducted at NLR ARIES facility with real 2.5 MW wind-turbine generator operating in GFM mode under dynamic and transient conditions. The team also developed models and conducted simulations for GFM wind power to evaluate stability impacts of GFM operation on power grid. This report describes efforts by the NLR team working in collaboration GE Vernova during 3-year project.

17 WIND ENERGY↗

Proactive Data Containers for Scientific Storage (Final Report)

Emerging HPC systems are expected to be deployed with an unprecedented level of complexity, due to a deep system memory/storage hierarchy and heterogeneity of the storage hardware. This hierarchy is expected to range from CPU cache through several levels of volatile memory to nonvolatile memory, traditional hard disks, and tape. Simple and efficient methods of data management and movement through this hierarchy is critical for scientific applications using exascale systems. Existing storage system and I/O (SSIO) technologies face severe challenges in dealing with these requirements. POSIX and MPI I/O standards that are the basis for existing I/O libraries and parallel file systems present fundamental challenges in the areas of scalable metadata operations, semantics-based data movement performance tuning, asynchronous operation, and support for scalable consistency of distributed operations. Moving toward new paradigms for SSIO in the extreme-scale era, we have proposed to investigate novel object-based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these overarching goals, we initiated an effort to develop a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-centric manner. Managing data as objects enables powerful optimization opportunities for data movement and transformations. The R&D focus of this project are: 1) formulation of object-oriented PDCs and their mapping in different levels of the exascale storage hierarchy; 2) efficient strategies for moving data in deep storage hierarchies using PDCs; 3) techniques for transforming and reorganizing data based on application requirements; and 4) novel analysis paradigms for enabling data transformations and user-defined analysis on data in PDCs. Toward achieving these overarching goals, we designed an object-centric application programing interface (API) for HPC, scalable metadata management for object-centric storage systems, and data movement optimizations such as Data Elevator for moving data between two levels of storage devices and TAPIOCA for efficient aggregation of data on compute nodes. We then implemented several components of the PDC system. They include metadata management, data placement services, remote procedure calls, data aggregation, etc. We have put them together into the overall PDC framework.

97 MATHEMATICS AND COMPUTING↗

Reliability Assessment of Safety-Critical Network Communication in a Digitalized Nuclear Power Plant

In analog instrumentation and control (I and C) systems for nuclear power plants (NPPs), most connections are comprised of hardwired point-to-point types. Since they are based on analog technologies, they are fragile to noise and require analog-to-digital conversion time. Therefore, many NPPs have adopted communication network for the exchange of safety-critical data between programmable logic controllers (PLCs) in digital I and C systems to effectively accommodate a huge number of field controllers. However, the primary issue of digital network communication in a safety-critical system involves potential hazards, such as partial or total loss of communication between PLCs, which may result in a failure of safety critical signal generation when it is needed. Therefore, the probability that a safety-critical system in digitalized NPP becomes unsafe due to a network failure must be evaluated to quantify the risk of digital I and C system. In Korea, the Engineered Safety Feature-Component Control System (ESF-CCS) was developed as one of the digital safety-critical system in Advanced Power Reactor- 1400 (APR-1400). The function of a digital engineered safety feature (ESF) actuation system and field actuator controllers of conventional NPPs are performed by the ESF-CCS. In this system, safety-critical network, High Reliable- Safety Data Network (HR-SDN), was employed for the safety-critical data transmission from group controllers (GCs) to loop controllers (LCs). In this study, a framework for assessing the reliability of a HR-SDN network communication between GCs and LCs in the ESF-CCS in addition to a fault-tree model for ESF components considering network failure between GCs and LCs were developed to assess the plant risk effect of a newly developed digitalized ESF-CCS. Based on the case studies and cut set analysis, the risk effect of network failure on plant risk and the important risk contributors of network failure were quantitatively addressed. A framework for identifying the potential hazardous states of network communication in the ESFCCS was proposed. In addition, a fault-tree model for network communication failure was developed to estimate the risk effects of network failure between the GCs and LCs on ESF-CCS signal failure. The developed fault-tree model was then applied to several case studies. The fault-tree model of ESF-CCS signal failure for ESF components required for various mitigation actions regarding NPP DBAs was designed by considering the identified hazardous states of network failure that would result in a failure to provide input signals to the corresponding LC. As a sensitivity study, three case studies were performed based on the periodic test methods for hardware components in HR-SDN module and their test intervals in this study. The quantitative results for three case studies demonstrated that the probability of overall network communication failure, which was calculated as the sum of the failure probability associated with each failure cause, contributed up to 1.58% on the Small-LOCA CD frequency. The results also revealed the important basic events related to network failure in the case studies which included CCF of hardware and software in HR-SDN module. This study is expected to provide insight into the development of the fault-tree model for the network failure in digital I and C system and into the quantification of the risk effect of network failure for safety-critical data transmission in NPPs. As a further study, the risk effects of network failure in the ESF-CCS on the plant risk can be estimated in a more detailed manner by analyzing the failure modes and causes in a sub-component level and the fault detection coverage of the fault tolerance techniques for network failure implemented in ESF-CCS after the detailed configuration of ESF-CCS is decided. In terms of the failure of manual ESF actuation, the relationship among the human action failures must be investigated to consider multiple human error condition since ESF-CCS provides multiple manual actuation to assure the diversity of the system. Since the conventional HEP method cannot accommodate the multiple conditions in a fault tree, condition-based human reliability assessment (CBHRA) method or the dynamic human reliability modeling approach can be applied to include a complex relationship among the automated safety signal generation and the human operator's manual actuation, avoiding the optimistic estimation of HEP of the human action failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Machine learning for continuous quantum error correction on superconducting qubits

Abstract Continuous quantum error correction has been found to have certain advantages over discrete quantum error correction, such as a reduction in hardware resources and the elimination of error mechanisms introduced by having entangling gates and ancilla qubits. We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identify bit-flip errors from continuous noisy syndrome measurements. The algorithm is designed to operate on measurement signals deviating from the ideal behavior in which the mean value corresponds to a code syndrome value and the measurement has white noise. We analyze continuous measurements taken from a superconducting architecture using three transmon qubits to identify three significant practical examples of non-ideal behavior, namely auto-correlation at temporal short lags, transient syndrome dynamics after each bit-flip, and drift in the steady-state syndrome values over the course of many experiments. Based on these real-world imperfections, we generate synthetic measurement signals from which to train the recurrent neural network, and then test its proficiency when implementing active error correction, comparing this with a traditional double threshold scheme and a discrete Bayesian classifier. The results show that our machine learning protocol is able to outperform the double threshold protocol across all tests, achieving a final state fidelity comparable to the discrete Bayesian classifier.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗