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Source Physics Experiment Data Quality Using Background Noise

We computed time-domain root-mean-square (TRMS) amplitudes and power spectral densities (PSD) from the Source Physics Experiment (SPE) seismic data using the 2018 version 1.4 of the instrument response metadata. The geophone instrument gains were set lower about a few weeks prior to the SPE shots to record on-scale and then reset soon afterward to record background noise and seismicity. When the gains were set lower, we determined that the 1-2 Hz bandpass filtered geophone amplitudes increased 20 decibels (dB) or factor of 10 relative to the geophone baseline or background noise levels from nearby broadband sensors. This indicates an inconsistency between the released metadata reporting a decrease in gain factor of 32 and the likely true geophone gain setting of 3.2. After the shots, the geophone gains were reset and recorded background noise levels similar to nearby broadbands consistent with the metadata for those time intervals. There was also a similar issue with line-3, line-4 and AF Trillium broadband horizontals gains during SPE-5 where there is a factor of 32 difference relative to baseline levels. The other Guralp and Trillium broadbands performed very well recording a 1-2 Hz noise level of -150 to -160 dB similar to the nearby station at Tonopah Springs, Nevada (US.TPNV) and compared with -170 dB from the new low noise model (NLNM) for the continental US (e.g., McNamara and Buland, 2004). The geophones were only 5-10 dB higher but performed as well as broadbands above 6 Hz. The accelerometers have poor low frequency response and were 40-50 dB higher in the 1-2 Hz band relative to broadbands.

58 GEOSCIENCES↗

High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.

Oleynik, D↗

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

EMAPS: An Efficient Multiscale Approach to Plasma Systems with Non-MHD Scale Effects

Global interactions of energetic ions with magnetoplasmas and neutral gases lie at the core of many space and laboratory plasma phenomena ranging from solar wind entry into and transport within planetary magnetospheres and exospheres to fast-ion driven instabilities in fusion devices to astrophysics-in-lab experiments. The ability of computational models to properly account for physical effects that underlie such interactions, namely ion kinetic, ion cyclotron, Hall, collisional and ionization processes is important for the success and planning of experimental research in plasma physics. Understanding the physics of energetic ions, in particular their nonlinear resonance interactions with Alfvén waves, is central to improving the heating performance of magnetically confined plasmas for future energy generation. Fluid models are not adequate for high-beta plasmas as they cannot fully capture ion kinetic and cyclotron physics (e.g., ion behavior in the presence of magnetic nulls, shock structures, plasma interpenetration, etc.). Recent results from global reconnection simulations show that even in a MHD-like regime there may be significant differences between kinetic and MHD simulations. Therefore, kinetic modeling becomes essential for meeting modern day challenges in plasma physics. The hybrid approximation is an intermediate approximation between the fluid and fully kinetic approximations. It eliminates light waves, removes the electron inertial temporal and spatial scales from the problem and enables full-orbit ion kinetics. As a result, hybrid codes have become effective tools for exploring ion-scale driven phenomena associated with ion beams, shocks, reconnection and turbulence that control the large-scale behavior of laboratory and space magnetoplasmas. A number of numerical issues, however, make three-dimensional (3D) large-scale hybrid simulations of inhomogeneous magnetized plasmas prohibitively expensive or even impossible. To resolve these difficulties we have developed a novel Event-driven Multiscale Asynchronous Parallel Simulation (EMAPS) technology that replaces time stepping with self-adaptive update events. Local calculations are carried out only on an “as needed basis”. EMAPS (i) guarantees accurate and stable processing of physical variables in time accurate simulations, and (ii) eliminates unnecessary computation. Applying EMAPS to the hybrid model has resulted in the development of a unique parallel code, dimension-independent (compile-time-configurable) HYPERS (Hybrid Parallel Event-Resolved Simulator) that scales to hundreds of thousands of parallel processors. HYPERS advances electromagnetic fields and particles asynchronously on time scales determined by local physical laws and mesh properties. To achieve high computational accuracy in complex device geometries, HYPERS employs high-fidelity Cartesian grids with masked conductive cells. The HYPERS model includes multiple ion species, energy and momentum conserving ion-ion collisions, and provides a number of approximations for plasma resistivity and vacuum regions. Both local and periodic boundary conditions are allowed. The HYPERS solver preserves zero divergence of magnetic field. The project has demonstrated HYPERS capabilities on a number of applications of interest to fusion and astrophysical plasma physics applications listed below. 1. Theta-pinch formation of FRCs The formation, spontaneous spin-up, and stability of theta-pinch formed field-reversed configurations have been studied self-consistently in 3D. The end-to-end hybrid simulations reveal poloidal profiles of implosion-driven fast toroidal plasma rotation and demonstrate three discharge regimes as a function of experimental parameters: the decaying stable configuration, the tilt unstable configuration, and the nonlinear evolution of a fast growing tearing mode. 2. FRC collisions with magnetic mirrors Interactions of fast plasma streams and objects with magnetic obstacles (dipoles, mirrors, etc) lie at the core of many space and laboratory plasma phenomena ranging from magnetoshells and solar wind interactions with planetary magnetospheres to compact fusion plasmas. HYPERS simulations are compared with data from the MSX experiment (LANL) that focuses on the physics of magnetized collisionless shocks through the acceleration and subsequent stagnation of FRC plasmoids against a strong magnetic mirrors and flux-conserving boundaries. 3. Exploding magnetoplasmas Results from hybrid simulations of two experiments at the LAPD and Nevada Terawatt Facility are discussed where short-pulse lasers are used to ablate solid targets to produce plasmas that expand across external magnetic fields. The first simulation recreates flutelike density striations observed at the leading edge of a carbon plasma and predicts an early destruction of the magnetic cavity in agreement with experimental evidence. In the second simulation a polyethylene target is ablated into a mixture of protons and carbon ions. A mechanism is demonstrated that allows protons to penetrate the magnetic field in the form of a collimated flow. The results are compared to experimental data and single-fluid MHD simulations. The EMAPS framework has the potential for wide application in many other engineering and scientific fields, such as climate models, biological systems, electronic devices, seismic events, oil reservation simulators that all involve advancing solutions of partial differential equations in time where the rate of activity can be adapted widely over the spatial domain depending on locally space/time phenomena (“events”).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Knowledge based and interactive control for the Superfluid Helium On-orbit Transfer Project

NASA's Superfluid Helium On-Orbit Transfer (SHOOT) project is a Shuttle-based experiment designed to acquire data on the properties of superfluid helium in micro-gravity. Aft Flight Deck Computer Software for the SHOOT experiment is comprised of several monitoring programs which give the astronaut crew visibility into SHOOT systems and a rule based system which will provide process control, diagnosis and error recovery for a helium transfer without ground intervention. Given present Shuttle manifests, this software will become the first expert system to be used in space. The SHOOT Command and Monitoring System (CMS) software will provide a near real time highly interactive interface for the SHOOT principal investigator to control the experiment and to analyze and display its telemetry. The CMS software is targeted for all phases of the SHOOT project: hardware development, pre-flight pad servicing, in-flight operations, and post-flight data analysis.

Castellano, Timothy P.↗

Helium bubble flow visualization of the spanwise separation on a NACA 0012 with simulated glaze ice

Research was performed to experimentally visualize and document the flow separation due to simulated glaze ice accretion on a NACA 0012 semispan with 30 deg sweep using helium bubbles as flow tracers. Results are compared to Navier-Stokes computational simulations for different angles of attack. Prior to acquiring data for the semispan model, a two dimensional experiment was conducted to determine the accuracy of using the helium bubbles as flow tracers. Results from the three dimensional experiment compare well to the computational simulations.

Kerho, M.↗

Cross-Cutting Computational Modeling Project: Integrative Modeling Approach

A wide range of computational models and analyses have been applied to spaceflight risk assessment and countermeasure development. The benefits of using computational modeling to enhance Human Research Program (HRP) goals include the ability to mathematically represent physiological systems, integrate multiple, discrete experimental measures, span multiple temporal and spatial scales, determine important factors within the system and provide estimates of unmeasurable quantities. In the area of application, computational models provide a means of developing simulations to test hypotheses, determining key factors of the system to aid experimental design and bridging gaps in sparse data by mathematically simulating large populations. Specifically, computational models and their supporting analysis tools have the proven potential to integrate analyses of risk factors to enhance mission planning and preparation capabilities and to inform spacecraft design and countermeasure development. Appropriately applied, computational models may allow intelligent, unbiased physiological parameter assessment to enable hypothesis testing and model based design of experiments. HRP recently formed the Computational Modeling Project (CMP), managed out of Glenn Research Center, as a cross-cutting activity aimed at leveraging the growing power and acceptance of computational modeling in informing clinical, physiological, and biological studies. This presentation will provide an overview of the challenges and opportunities in implementing various forms of computational models in support of the HRPs path to risk reduction.

biomechanics↗

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Distributing User Code with the CernVM FileSystem

The CernVM FileSystem (CVMFS) is widely used in High Throughput Computing to efficiently distributed experiment code. However, the standard CVMFS publishing tools are designed for a small group of people from each experiment to maintain common software, and the tools are not a good fit for publishing software from numerous users in each experiment. As a result, most user code, such as code to do specific physics analyses, is still sent with every job to the place the job is run. That process is relatively inefficient, especially when the user code is large. To overcome these limitations, we have built a CVMFS user code publication system. This publication system enables users to still submit their code with their jobs but the code is distributed and accessed through the standard CVMFS infrastructure. The user code is automatically deleted from CVMFS after a period of no use. Most of the software for the system is available as a single self-contained open source rpm called cvmfs-user-pub and is available for other deployments.

97 MATHEMATICS AND COMPUTING↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

Verification of Upcoming MCNP Features For Estimating Nuclear Data Sensitivities in Fixed Source Simulations [Abstract]

Predictive simulation codes, like the Monte Carlo N-Particle (MCNP) transport code, are used throughout the nuclear community. These simulations are based on nuclear data. Maximizing the accuracy and precision of nuclear data maximizes the accuracy and precision of the overall simulation. This is imperative to applications that rely on simulations. For example, improving nuclear data for special nuclear material improves simulation accuracy in stockpile stewardship applications, which results in larger safety margins and decreased operational costs. The improvement and validation of nuclear data is completed through integral benchmark experiments. Past benchmarks have primarily been limited to focus on the effective multiplication factor ($\kappa$ eff ); broadening the purview of benchmarks beyond $\kappa$ eff -dependent nuclear data addresses nuclear data deficiencies. Different response types depend on different areas of nuclear data. This dependence is quantified as nuclear data sensitivity: the change in response due to perturbation of a contributing parameter. The larger the nuclear data sensitivity of a response, the more the experiment is influenced by the uncertainties of the nuclear data. The optimization of nuclear data sensitivities in future benchmarks would result in more detailed validation of lesser studied areas of nuclear data. Currently, direct sensitivity capabilities are not easily found for all experiment types and parameters. An MCNP tool to directly estimate the cross section sensitivities of tallied values is under development. Additionally, updates have been made to the perturbation feature of MCNP, which can be used in a less direct approach to estimating sensitivities. This work verifies these features to estimate nuclear data sensitivities in fixed source simulations of a 4.5-kg sphere of alpha- phase weapons-grade plutonium surrounded by differing amounts of copper and polyethylene. Integrated estimates made using MCNP’s tools were found to statistically agree with integrated estimates made from manual perturbation of nuclear data proving the validity of the MCNP tools.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quake Final Video

Critical infrastructures of the world are at constant risks for earthquakes. Most of these critical structures are designed using archaic, seismic, simulation methods that were built from early digital computers from the 1970s. Idaho National Laboratory’s Seismic Research Group are working to modernize the simulation methods through computational research and large-scale laboratory experiments.

58 GEOSCIENCES↗

Combined computational and experimental investigation of high temperature thermodynamics and structure of cubic ZrO 2 and HfO 2

Structure and thermodynamics of pure cubic ZrO 2 and HfO 2 were studied computationally and experimentally from their tetragonal to cubic transition temperatures (2311 and 2530 degrees C) to their melting points (2710 and 2800 degrees C). Computations were performed using automated ab initio molecular dynamics techniques. High temperature synchrotron X-ray diffraction on laser heated aerodynamically levitated samples provided experimental data on volume change during tetragonal-to-cubic phase transformation (0.55 +/- 0.09% for ZrO 2 and 0.87 +/- 0.08% for HfO 2 ), density and thermal expansion. Fusion enthalpies were measured using drop and catch calorimetry on laser heated levitated samples as 55 +/- 7 kJ/mol for ZrO 2 and 61 +/- 10 kJ/mol for HfO 2 , compared with 54 +/- 2 and 52 +/- 2 kJ/mol from computation. Volumetric thermal expansion for cubic ZrO 2 and HfO 2 are similar and reach (4 +/- 1).10 -5 /K from experiment and (5 +/- 1).10 -5 /K from computation. Finally, an agreement with experiment renders confidence in values obtained exclusively from computation: namely heat capacity of cubic HfO 2 and ZrO 2 , volume change on melting, and thermal expansion of the liquid to 3127 degrees C. Computed oxygen diffusion coefficients indicate that above 2400 degrees C pure ZrO 2 is an excellent oxygen conductor, perhaps even better than YSZ.

36 MATERIALS SCIENCE↗

Crowding-Induced Spatial Organization of Gene Expression in Cell-Sized Vesicles

Cell-free protein synthesis is an important tool for studying gene expression and harnessing it for applications. In cells, gene expression is regulated in part by the spatial organization of transcription and translation. Unfortunately, current cell-free approaches are unable to control the organization of molecular components needed for gene expression, which limits the ability to probe and utilize its effects. In this work, we show, using complementary computational and experimental approaches, that macromolecular crowding can be used to control the spatial organization and translational efficiency of gene expression in cell-sized vesicles. Computer simulations and imaging experiments reveal that, as crowding is increased, DNA plasmids become localized at the inner surface of vesicles. Ribosomes, in contrast, remain uniformly distributed, demonstrating that crowding can be used to differentially organize components of gene expression. We further carried out cell-free protein synthesis reactions in cell-sized vesicles and quantified mRNA and protein abundance. At sufficiently high levels of crowding, we observed localization of mRNA near vesicle surfaces, a decrease in translational efficiency and protein abundance, and anomalous scaling of protein abundance as a function of vesicle size. These results are consistent with high levels of crowding causing altered spatial organization and slower diffusion. Our work demonstrates a straightforward way to control the organization of gene expression in cell-sized vesicles and provides insight into the spatial regulation of gene expression in cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of Computational Results with a Low-g, Nitrogen Slosh and Boiling Experiment

This paper compares a fluid/thermal simulation, in Fluent, with a low-g, nitrogen slosh and boiling experiment. In 2010, the French Space Agency, CNES, performed cryogenic nitrogen experiments in a low-g aircraft campaign. From one parabolic flight, a low-g interval was simulated that focuses on low-g motion of nitrogen liquid and vapor with significant condensation, evaporation, and boiling. The computational results are compared with high-speed video, pressure data, heat transfer, and temperature data from sensors on the axis of the cylindrically shaped tank. These experimental and computational results compare favorably. The initial temperature stratification is in good agreement, and the two-phase fluid motion is qualitatively captured. Temperature data is matched except that the temperature sensors are unable to capture fast temperature transients when the sensors move from wet to dry (liquid to vapor) operation. Pressure evolution is approximately captured, but condensation and evaporation rate modeling and prediction need further theoretical analysis.

Cryogenic Fluid Storage↗

Modeling Approach to Critical in the Upcoming CERBERUS Experiment

The planned Critical Experiment Reflected By coppEr to betteR Understand Scattering (CERBERUS) seeks to maximize sensitivity to elastic neutron scattering in the intermediate energy region (0.625 eV to 100 keV). It will be performed near the end of FY 2023 at the National Criticality Experiments Research Center (NCERC). Very few International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks are sensitive to copper in this region. Creating a benchmark sensitive in this area will make the Zeus benchmark series, an intermediate benchmark evaluation that uses a copper reflector, more useful for code and nuclear data validation. Approaching criticality in a safe manner is of utmost importance to avoid a criticality accident, which would present a safety concern and could cause damage to equipment. The two rules that are followed closely to ensure that a criticality accident does not occur are the 3/4 rule and the 1/2 rule. The 3/4 rule states that no more than 3/4 of a critical mass can be assembled by hand, and the 1/2 rule states that no more than 1/2 of the material expected to reach criticality, or 1/2 the distance needed to reach criticality, can be added before another measurement of the count rate has been taken. This work will discuss the approach to criticality as modeled in MCNP6® 1 particle transport code with the ENDF/B- VIII.0 cross-section library and the .00c data library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Design of Nuclear Criticality Safety Framework for Hands-on Construction of Fast Systems Over Ranges of Multiplication

Since 1945, Los Alamos National Laboratory (LANL) has performed critical experiments, primarily at the Los Alamos Critical Experiments Facility (LACEF) at Technical Area 18 (TA-18). Since 2011, these experiments have been conducted by the National Criticality Experiments Research Center (NCERC), operated by LANL, at the Device Assembly Facility (DAF) in the Nevada National Security Site (NNSS). These experiments utilize various types of Special Nuclear Material (SNM). Some of these experiments utilize what is referred to as the Rocky Flat Shells, which are called such as they came from the Rocky Flats Plant. These concentric hemi-shells are made of Highly Enriched Uranium (HEU), which is 93 w/o 235U. Fig. 1. Subset of the Rocky Flat Shells LANL is designing a new subcritical hands-on experiment with the goal of achieving a neutron multiplication in the range of 50 to 200, which correlates to Keff values of 0.98 to 0.995. ANSI/ANS-1 is the standard for Conduct of Critical Experiments which governs critical operations at NCERC. Section 3.9 of ANSI/ANS-1 states that when manipulating a critical assembly by hand, the predicted k eff of a known configuration should not exceed 0.95 (a neutron multiplication of 20). This presents a challenge, as this system would have a higher multiplication than 20 and the assembly would have to remain subcritical in normal and credible accident scenarios. To ensure the safety of such an assembly, the different normal and abnormal conditions that could alter the criticality 1 MCNP® and Monte Carlo N-Particle® are registered trademarks owned by Triad National Security, LLC, manager and operator of Los Alamos National Laboratory. Any third party use of such registered marks should be properly of the system must be considered and analyzed. If such a condition is deemed to be credible, it will be further investigated using the Monte Carlo N-Particle (MCNP) transport code. If the results of these simulations show that a k eff larger than one could be possible, modifications to the assembly will be made until such an event is deemed no longer possible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗