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Assessment of HRA method predictions against operating crew performance: Part I: Study background, design and methodology

This is the first in a series of four papers document ing two large -scale human reliability analysis (HRA) empirical studies – the International HRA Empirical Study and the US HRA Empirical Study. The two studies are the first major efforts in recent years to benchmark HRA methods by comparing HRA method predictions against actual operator performance in accident scenarios simulated on nuclear power plant (NPP) simulators. When a met hod was applied by different analyst teams, the predictions of the different teams were also compared against each other. The purpose of the comparisons was to obtain insights concerning the strengths and weaknesses of the HRA methods addressed in the studies as well as the factors contributing to inter-analyst (or intra-method) variability. The background and motivation for the studies is first presented in the article. Then, the overall study design is described with a discussion on high-level tasks and participants. Next, the methodology to achieve the high-level tasks is discussed. Finally, concluding remarks are made concerning lessons learned on benchmarking HRA methods with crew performance of scenarios on NPP simulators.

97 MATHEMATICS AND COMPUTING↗

Criticality Accident Alarm System Shielding Benchmark: Integral Experiment Request 498, Critical Engineering Decision 1 Report

This report supports Critical/Subcritical Experiment Decision 1 (CED-1) for Integral Experiment Request (IER) 498, a shielding benchmark produced using the Godiva IV critical assembly at the National Critical Experiments Research Center (NCERC). Shielding benchmarks are datasets collected to provide a comparison for computer models that simulate the effect of shielding on radiation transmission from a source to a detector. The purpose of a CED-1 report is to produce a conceptual design for an integral experiment and to identify the long lead-time items. The design presented in this report favors certain detailed design options such as material selections. However, alternative options can be selected as the project evolves. Dimensions are specified only as needed to evaluate feasibility and performance. Development of Criticality Accident Alarm System (CAAS) shielding benchmarks supports two main programmatic needs. The first need is to improve confidence in models of facilities that house nuclear material handling operations. Better models can support effective CAAS detector placement when criticality may result in dose, and it enables more accurate analysis of criticality accident impacts at various locations in a facility. A key quantity that can be verified is the secondary gamma production caused by neutron interactions with various materials. The second programmatic need supported by shielding benchmarks is the ongoing development of methods being integrated into nuclear simulation codes such as the Monte Carlo N-Particle (MCNP) transport code and the SCALE code system used in efforts funded by the Nuclear Criticality Safety Program (NCSP). Previous work performed under the International Criticality Safety Benchmark Experimental Program (ICSBEP) to produce shielding benchmark data is primarily limited to a set of measurements at the SILENE critical assembly at the Valduc facility in France. The experiment used an open configuration and a burst mode operation, which limited detector options to thermoluminescent dosimeters (TLDs) and activation foils. Because TLDs do not record gamma spectra, it was difficult to verify the gamma energy spectrum from the experiment. In this work, the Godiva IV assembly will be used because it is a fast system capable of producing a wide range of source strengths, including super-prompt critical bursts. The room return for the facility is expected to be substantial and challenging to characterize, so a more closed, shielded experimental configuration is considered. Furthermore, because the physics of radiation transport outside the assembly does not change between the burst mode and the delayed critical mode, it is anticipated that most measurements will be made with the Godiva IV assembly in delayed critical mode, operating within a range that will allow electronic counters to collect accurate data. Scoping calculations concluded that a workable room return shield is comprised of 40 cm of 5% borated polyethylene backed by 7 cm of lead. This configuration was shown to produce a ratio of signal–to–room return of over 100 for up to 2 mean free paths of shield sample material, and over 10 for up to 4 mean free paths of shield sample material, ensuring that useful results can be obtained. With no shielding sample in the room return shield, it was shown that the neutron and gamma spectra do not appreciably change with a change in room size. This scoping calculation does not preclude the use of tungsten powder in a binder, some other effective gamma shielding material, or a hybrid design. Dose rates for various source intensities at an unshielded detector are listed herein to inform detector selection during CED-2, and calibration chains are identified. Preliminary estimates of costs and schedules are outlined but remain to be verified. Values could double or triple as estimates become more accurate and are principally included here to demonstrate feasibility. Preliminary estimates indicate that the apparatus can be installed within a feasible schedule and budget. Two measurements per day are assumed. Producing a shielding benchmark at NCERC using the Godiva IV assembly has been shown to be feasible, with manageable uncertainties and risks. A clear, continuing need for shielding benchmark data remains present, and this report identifies and evaluates a method for creating integrated shielding benchmark datasets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Image segmentation with a novel regularized composite shape prior based on surrogate study

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulated in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.

60 APPLIED LIFE SCIENCES↗

Tensor-decomposition techniques for ab initio nuclear structure calculations: From chiral nuclear potentials to ground-state energies

The computational resources needed to generate the ab initio solution of the nuclear many-body problem for increasing mass number and/or accuracy necessitates innovative developments to improve upon (i) the storage of many-body operators and (ii) the scaling of many-body methods used to evaluate nuclear observables. The storing and efficient handling of many-body operators with high particle ranks is currently one of the major bottlenecks limiting the applicability range of ab initio studies with respect to mass number and accuracy. Recently, the application of tensor decomposition techniques to many-body tensors has proven highly beneficial to reduce the computational cost of ab initio calculations in quantum chemistry and solid-state physics. The impact of applying state-of-the-art tensor factorization techniques to modern nuclear Hamiltonians derived from chiral effective field theory is investigated. Subsequently, the error induced by the tensor decomposition of the input Hamiltonian on ground-state energies of closed-shell nuclei calculated via second-order many-body perturbation theory is benchmarked. The first proof-of-principles application of tensor-decomposition techniques to the nuclear Hamiltonian is performed. Two different tensor formats are investigated by systematically benchmarking the approximation error on matrix elements stored in various bases of interest. The analysis is achieved while including normal-ordered three-nucleon interactions that are nowadays used as input to the most advanced ab initio calculations in medium-mass nuclei. With the aid of the factorized Hamiltonian, the second-order perturbative correction to ground-state energies is decomposed and the scaling properties of the underlying tensor network are discussed. The employed tensor formats are found to lead to an efficient data compression of two-body matrix elements of the nuclear Hamiltonian. In particular, the sophisticated tensor hypercontraction scheme yields low tensor ranks with respect to both harmonic-oscillator and Hartree-Fock single-particle bases. It is found that the tensor rank depends on the two-body total angular momentum J for which one performs the decomposition, which is itself directly related to the sparsity of the corresponding tensor. Furthermore, including normal-ordered two-body contributions originating from three-body interactions does not compromise the efficient data compression. Ultimately, the use of factorized matrix elements authorizes controlled approximations of the exact second-order ground-state energy corrections. In particular, a small enough error is obtained from low-rank factorizations in He4,O16, and Ca40. It is presently demonstrated that tensor-decomposition techniques can be efficiently applied to systematically approximate the nuclear many-body Hamiltonian in terms of lower-rank tensors. Beyond the input Hamiltonian, tensor-decomposition techniques can be envisioned to scale down the cost of state-of-the-art nonperturbative many-body methods in order to extend ab initio studies to (i) higher precisions, (ii) larger masses, and (iii) nuclei of doubly open-shell character.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Adding Fault Tolerance to NPB Benchmarks Using ULFM

In the world of high-performance computing, fault tolerance and application resilience are becoming some of the primary concerns because of increasing hardware failures and memory corruptions. While the research community has been investigating various options, from system-level solutions to application-level solutions, standards such as the Message Passing Interface (MPI) are also starting to include such capabilities. The current proposal for MPI fault tolerant is centered around the User-Level Failure Mitigation (ULFM) concept, which provides means for fault detection and recovery of the MPI layer. This approach does not address application-level recovery, which is currently left to application developers. In this work, we present a modification of some of the benchmarks of the NAS parallel benchmark (NPB) to include support of the ULFM capabilities as well as application-level strategies and mechanisms for application-level failure recovery. As such, we present: (i) an application-level library to "checkpoint" and restore data, (ii) extensions of NPB benchmarks for fault tolerance based on different strategies, (iii) a fault injection tool, and (iv) some preliminary results that show the impact of such fault tolerant strategies on the application execution.

97 MATHEMATICS AND COMPUTING↗

Adding Fault Tolerance to NPB Benchmarks Using ULFM

In the world of high-performance computing, fault tolerance and application resilience are becoming some of the primary concerns because of increasing hardware failures and memory corruptions. While the research community has been investigating various options, from system-level solutions to application-level solutions, standards such as the Message Passing Interface (MPI) are also starting to include such capabilities. The current proposal for MPI fault tolerant is centered around the User-Level Failure Mitigation (ULFM) concept, which provides means for fault detection and recovery of the MPI layer. This approach does not address application-level recovery, which is currently left to application developers. In this work, we present a mod- ification of some of the benchmarks of the NAS parallel benchmark (NPB) to include support of the ULFM capabilities as well as application-level strategies and mechanisms for application-level failure recovery. As such, we present: (i) an application-level library to checkpoint and restore data, (ii) extensions of NPB benchmarks for fault tolerance based on different strategies, (iii) a fault injection tool, and (iv) some preliminary results that show the impact of such fault tolerant strategies on the application execution.

Parchman, Zachary W↗

Error-mitigated data-driven circuit learning on noisy quantum hardware

Application-level benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and generative modeling, the choice of target distribution. Gradient-based training has become a useful benchmarking task for noisy intermediate-scale quantum computers because of the additional requirement that the optimization step uses the quantum device to estimate the loss function gradient. In this work, we use gradient-based data-driven circuit learning to qualitatively evaluate the performance of several superconducting platform devices and present results that show how error mitigation can improve the training of quantum circuit Born machines with 28 tunable parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Direct Randomized Benchmarking for Multiqubit Devices

Benchmarking methods that can be adapted to multiqubit systems are essential for assessing the overall or “holistic” performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which measures a single error rate that quantifies overall performance. But, scaling Clifford RB to many qubits is surprisingly hard. It has only been performed on one, two, and three qubits as of this writing. This reflects a fundamental inefficiency in Clifford RB: the n-qubit Clifford gates at its core have to be compiled into large circuits over the one- and two-qubit gates native to a device. As n grows, the quality of these Clifford gates quickly degrades, making Clifford RB impractical at relatively low n. In this Letter, we propose a direct RB protocol that mostly avoids compiling. Instead, it uses random circuits over the native gates in a device, which are seeded by an initial layer of Clifford-like randomization. We demonstrate this protocol experimentally on two to five qubits using the publicly available ibmqx5. We believe this to be the greatest number of qubits holistically benchmarked, and this was achieved on a freely available device without any special tuning up. Our protocol retains the simplicity and convenient properties of Clifford RB: it estimates an error rate from an exponential decay. But, it can be extended to processors with more qubits—we present simulations on 10+ qubits—and it reports a more directly informative and flexible error rate than the one reported by Clifford RB. Here, we show how to use this flexibility to measure separate error rates for distinct sets of gates, and we use this method to estimate the average error rate of a set of cnot gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Parallels between enzyme catalysis, electrocatalysis, and photoelectrosynthesis

Catalysts are central to accelerating chemistry in biology and technology. In biochemistry, the relationship between the velocity of an enzymatic reaction and the concentration of chemical substrates is described via the Michaelis-Menten model. Additionally, the modeling and benchmarking of synthetic molecular electrocatalysts are also well developed. However, such efforts have not been as rigorously extended to photoelectrosynthetic reactions, where, in addition to chemical substrates and charge carriers, light is a required reagent. In this perspective, we draw parallels between concepts involving enzyme catalytic efficiency, the benchmarking of molecular electrocatalysts, and the performance of photoelectrosynthetic assemblies, while highlighting key differences, assumptions, and limitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗

Research advances towards large-scale solar hydrogen production from water

Solar hydrogen production from water is a sustainable alternative to traditional hydrogen production route using fossil fuels. However, there is still no existing large-scale solar hydrogen production system to compete with its counterpart. In this Review, recent developments of four potentially cost-effective pathways towards large-scale solar hydrogen production, viz. photocatalytic, photobiological, solar thermal and photoelectrochemical routes, are discussed, respectively. The limiting factors including efficiency, scalability and durability for scale-up are assessed along with the field performance of the selected systems. Some benchmark studies are highlighted, mostly addressing one or two of the limiting factors, as well as a few recent examples demonstrating upscaled solar hydrogen production systems and emerging trends towards large-scale hydrogen production. Finally, a techno-economic analysis provides a critical comparison of the levelized cost of hydrogen output via each of the four solar-to-hydrogen conversion pathways.

08 HYDROGEN↗

Attention-based convolutional capsules for evapotranspiration estimation at scale

Evapotranspiration (ET) measures the amount of water lost from the Earth's surface to the atmosphere and is an integral metric for both agricultural and environmental sciences. Understanding and quantifying ET is critical for achieving effective management of freshwater and irrigation systems. However, current ET estimation models suffer from a trade-off between accuracy and spatial coverage. In this study, we introduce our model Quench, a neural network architecture that achieves highly-accurate ET estimates over large continuous spatial extents. Quench uses our novel Attention-Based Convolutional Capsule for its neural network layers to identify areas of focus and efficiently extract ET information from satellite imagery. Benchmarks that profile our model's performance show substantive improvements in accuracy, with up to 128% increase in accuracy compared to traditional convolutional-based and process-based models. Finally, Quench also demonstrates consistent model performance over high geospatial variability and a diverse array of regions, seasons, climates, and vegetations.

54 ENVIRONMENTAL SCIENCES↗

55Fe effect on enhancing ferritic steel He/dpa ratio in fission reactor irradiations to simulate fusion conditions

How to increase the ferritic steel He(appm)/dpa ratio in a fission reactor neutron spectrum is an important question for fusion reactor material testing. An early experiment showed that the accelerated He(appm)/dpa ratio of about 2.3 was achieved for 96% enriched 54Fe in iron with 458.2 effective full power days (EFPD) irradiation in the High Flux Isotope Reactor (HFIR), ORNL. Greenwood suggested that the transmutation produced 55Fe has a thermal neutron helium production cross section which may have an effect on this result. In the current work, the ferritic steel He(appm)/dpa ratio is studied in the neutron spectrum of HFIR with 55Fe thermal neutron helium production taken into account. The available ENDF-b format 55Fe incident neutron cross section file from TENDL, Netherlands, is first input into the calculation model. A benchmark calculation for the same sample as used in the aforementioned experiment was used to adjust and evaluate the TENDL 55Fe (n, a) cross section values. The analysis shows a decrease of a factor of 6700 for the TENDL 55Fe (n, a) cross section in the intermediate and low energy regions is required in order to fit the experimental results. The best fit to the cross section value at thermal neutron energy is about 27 mb. With the adjusted 55Fe (n, a) cross sections, calculation show that the 54Fe and 55Fe isotopes can be enriched by the isotopic tailoring technique in a ferritic steel sample irradiated in HFIR to significantly enhance the helium production rate. The results show that a 70% enriched 54Fe and 30% enriched 55Fe ferritic steel sample would produce a He(appm)/dpa ratio of about 13 initially in the HFIR peripheral target position (PTP). After one year irradiation, the ratio decreases to about 10. This new calculation can be used to guide future isotopic tailoring experiments designed to increase the He(appm)/dpa ratio in fission reactors. A benchmark experiment is suggested to be performed to evaluate the 55Fe (n, a) cross section at thermal energy.

55Fe(n,helium) reaction, He(appm)/dpa ratio, isoto↗

Arbitrary-order time-accurate semi-Lagrangian spectral approximations of the Vlasov–Poisson system

The Vlasov–Poisson system, modeling the evolution of non-collisional plasmas in the electrostatic limit, is approximated by a semi-Lagrangian technique. Spectral methods of periodic type are implemented through a collocation approach. Groups of particles are represented by the Fourier Lagrangian basis and evolve, for a single timestep, along a high-order accurate representation of the local characteristic lines. The time-advancing technique is based on truncated Taylor series that can be, in principle, of any order of accuracy. A variant is obtained by coupling the phase space discretization with high-order accurate Backward Differentiation Formulas (BDF). At each timestep, particle displacements are reinterpolated and expressed in the original basis to guarantee the order of accuracy in all the variables at relatively low costs. Thus, these techniques combine the excellent features of spectral approximations with high-order time integration. The resulting method has excellent conservation properties. Indeed, it can be proven that the total number of particles, proportional to the total mass and charge, is conserved up to the machine precision. Series of numerical experiments are performed in order to assess the real performance. In particular, comparisons with standard benchmarks are examined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Peroxide-treated metal-organic framework templated adsorbents for remediation of high level nuclear waste

Remediation of legacy nuclear waste is one of the greatest challenges faced by the US Department of Energy, with projected cleanup efforts requiring over five decades and hundreds of billions of dollars. New materials are necessary to accelerate waste processing, achieving time and financial savings. Herein we report a peroxide treatment to a Ti metal-organic framework (MOF) and related MOF-templated adsorbents. Furthermore, the resulting materials displayed exceptional affinity for Am(III), achieving distribution coefficients in excess of 10 5 mL/g, and out-performing state-of-the-art benchmarks monosodium titanate (MST) and peroxo-treated modified MST (mMST) for removal of 85 Sr(II) and 239, 240 Pu(IV) from legacy nuclear waste simulant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Streaming data analytics via message passing with application to graph algorithms

The need to process streaming data, which arrives continuously at high-volume in real-time, arises in a variety of contexts including data produced by experiments, collections of environmental or network sensors, and running simulations. Streaming data can also be formulated as queries or transactions which operate on a large dynamic data store, e.g. a distributed database. We describe a lightweight, portable framework named PHISH which enables a set of independent processes to compute on a stream of data in a distributed-memory parallel manner. Datums are routed between processes in patterns defined by the application. PHISH can run on top of either message-passing via MPI or sockets via ZMQ. The former means streaming computations can be run on any parallel machine which supports MPI; the latter allows them to run on a heterogeneous, geographically dispersed network of machines. We illustrate how PHISH can support streaming MapReduce operations, and describe streaming versions of three algorithms for large, sparse graph analytics: triangle enumeration, subgraph isomorphism matching, and connected component finding. Lastly, we also provide benchmark timings for MPI versus socket performance of several kernel operations useful in streaming algorithms.

97 MATHEMATICS AND COMPUTING↗

X-ray Absorption Spectroscopy Investigation of Iodine Capture by Silver-Exchanged Mordenite

Capture of radioactive iodine is a significant consideration during reprocessing of spent nuclear fuel and disposal of legacy wastes. While silver-exchanged mordenite (AgZ) is widely regarded as a benchmark material for assessing iodine adsorption performance, previous research efforts have largely focused on bulk material properties rather than the underpinning molecular interactions that achieve effective iodine capture. As a result, the fundamental understanding necessary to identify and mitigate deactivation pathways for the recycle of AgZ is not available. In this paper, we applied X-ray Absorption Fine Structure (XAFS) spectroscopy to investigate AgZ following activation, adsorption of iodine, regeneration, and recycle, observing no appreciable degradation in performance due to the highly controlled conditions under which the AgZ was maintained. Fits of the extended XAFS (EXAFS) data reveal complete formation of Ag 0 nanoparticles upon treatment with H 2 , and confirm the formation of α-AgI within the mordenite channels in addition to surface γ/β-AgI nanoparticles following iodine exposure. Analysis of the nanoparticle size and fractional composition of α-AgI to γ/β-AgI supports ripening of surface nanoparticles as a function of recycle. Finally, this work provides a foundation for future investigation of AgZ deactivation under conditions relevant to spent nuclear fuel reprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗