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At least 73 records · Page 4

Integral Experiment Final Design for Thermal/Epithermal eXperiments (TEX) Plutonium Additional Mixed Spectrum Configurations

This report presents the final design (CED-2) for three additional mixed-spectra configurations for plutonium Thermal/Epithermal eXperiments (TEX) to target the intermediate energy region (IER-553). The baseline cases of IER-184 (PU-MET-MIXED-002 [2]) spanned the entire fission energy spectrum. Case 3, which had a median fission energy (MFE) of approximately 6E-5 MeV and had a fission fraction of about 42% in the intermediate energy range, resulted in a $k_{eff}$ overestimation of 1.1%. Compared to 749 previous ICSBEP plutonium benchmarks, the baseline cases accurately predicted the experiments in the thermal and fast regions where the majority of benchmarks inhabit. The benchmarks in the intermediate energy region to date are sparse and overestimate $k_{eff}$ with an average C/E between 1.02 and 1.03. The additional proposed configurations span the whole of the intermediate energy region. The experimental design utilizes the plutonium/aluminum metal alloy Zero Power Physics Reactor (ZPPR) Plutonium-Aluminum No-Nickel (PANN) plates with varying polyethylene moderator thicknesses to span the intermediate fission energy region. Each of the cases have varying fractions of thermal, intermediate, and fast fissions. The designs were chosen to maximize the intermediate energy fraction. The experiment will take place on the universal critical assembly machine, Planet. The layers will be split as equally as possible between the lower platen and the upper stationary platform of Planet. The upper half of the experimental configuration will also have an upper reflector of polyethylene of specified thicknesses to achieve criticality when the lower platen is raised fully. The previous IER-184 configurations, specifically Case 3, were used to determine the configurations for the additional experiments and neutronics calculations were used to fine-tune the configurations to ensure criticality. The quadrature sum uncertainty in Δ$k_{eff}$ for Case 3 in PU-MET-MIXED-002 was found to be 0.00219. Section 3.8 gives a detailed description of the uncertainties calculated. The additional configurations, which are based directly on Case 3, are expected to have similar uncertainties. However, it is possible to reduce the overall uncertainty of Δ$k_{eff}$ for the additional configurations using the knowledge obtained from the calculations in the benchmark.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Criticality Accident Alarm System Shielding Benchmark: Integral Experiment Request 498, Critical Engineering Decision 2 Report

A workable design to perform a CAAS benchmark experiment is detailed herein. Key dimensions, materials, source intensity levels, and detectors are listed in this report. Sensitivity to 21 perturbations was determined to be acceptable. The next step will be for NCSP management to determine whether procurement should occur and if the experiment should proceed. The perturbation study suggests that the room return shield cavity radius and runout should be maintained to within a millimeter, the room return shield should be positioned carefully (perhaps with a laser range finder), and that the detectors should be mounted in a lightweight fixture such as aluminum, so their positioning is assured. Using a 3D scanner or photogrammetry to record part shapes may be beneficial. Further work is also needed to verify source reproducibility.

36 MATERIALS SCIENCE↗

Joint LLNL, LANL, SNL, and IRSN High Multiplication Subcritical (Multiplicity) Benchmark Integral Experiment Execution (CED-3b Report)

This report documents the experimental configurations and measurements for IER-518: Joint LLNL, LANL, SNL, and IRSN High Multiplication Subcritical (Multiplicity) Benchmark Experiments. These measurements involved a series of subcritical configurations at the Sandia Critical Experiments (SCX) facility at Sandia National Laboratories (SNL). The purpose of these measurements was to produce time tagged neutron count data of configurations that exceed a subcritical multiplication of 20, which is the high end of the fundamental physics benchmarks currently available in the International Criticality Safety Benchmark Evaluation Project Handbook (ICSBEP). These measurements leverage experimental configurations 1 and detector systems 2 from previously accepted ICSBEP benchmark evaluations, allowing evaluations of these measurements to be performed at greatly reduced cost.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experiences Integrating Transmission and Distribution Simulations for DERs with the Integrated Grid Modeling System (IGMS)

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactive power impacts of PV inverter voltage support on the bulk power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Microgravity science experiment integration - When the PI and the PED differ

This paper addresses issues related to the integration of principal investigators (PIs) and payload-element developers (PEDs) for conducting effective microgravity experiments. The Crystal Growth Furnace (CGF) is used as an example to demonstrate the key issues related to the integration of a PI's sample into a facility run by a different organization. Attention is given to the typical preflight timeline, documentation required for experimental implementation, and hardware deliverables. A flow chart delineates the payload-integration process flow, and PI inputs required for an experiment include equipment and procedure definitions, detailed design and fabrication of the experiment-specific equipment, and specifications of the contract-end item. The present analysis is of interest to the coordination of effective microgravity experiments on the Space Station Freedom that incorporate PIs and PEDs from different organizations.

Baer-Peckham, M. S.↗

Integral Experiment Final Design for Thermal/Epithermal eXperiments (TEX) using Highly Enriched Uranium with Polyethylene at Low Temperature (IER-479 CED-2 Report)

The goal of IER-479 is to design uranium critical experiments that can be used to validate low temperature cross sections and criticality safety analyses over multiple neutron energy regimes. Currently, there are no benchmarks in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook at temperatures lower than room temperature (International Criticality Safety Benchmark Evaluation Project Handbook, 2019). However, there are many needs for validation of criticality safety analysis at lower temperatures, including meeting transportation requirements and operations conducted outside or in unheated facilities. Additionally, NCSP has funded North Carolina State (NCSU) to generate new thermal scattering laws, including at lower temperatures, and the lack of integral benchmarks impedes data testing of these new cross sections. To address these needs, this report will present a critical experiment design covering various fission energy regimes with a goal temperature of -40°C (-40°F), which is based on the lower bound of expected non-cryogenic operational temperatures. The goal of the U.S. Nuclear Criticality Safety Program’s (NCSP) Thermal/Epithermal eXperiments (TEX) is to design and conduct new critical experiments to address high priority nuclear data needs from the nuclear criticality safety and nuclear data communities. The TEX program includes two series of baseline experimental configurations, one based on plutonium fuel (plutonium-aluminum Zero Power Physics Reactor (ZPPR) plates) and the other based on uranium fuel (highly enriched uranium (HEU) plates), that are moderated with varying thickness of polyethylene to create assemblies which span the thermal, intermediate, and fast fission energy regimes. The configurations are designed to be easily modified (for example, to add diluent materials of interest) to allow for efficient generation of additional benchmark configurations and allow for added nuclear data testing utility when comparing modified configurations to baseline configurations. The goal of IER-479 is to use the TEX-HEU concept (stack of HEU plates and polyethylene moderators) to design a critical experiment that can be used to validate low temperature cross sections and criticality safety analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗

Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites

The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.

Athanasiou, Christos↗

Reimagining metal-organic framework discovery: Integrating experiment, computation, and artificial intelligence

The traditional development of novel metal–organic frameworks (MOFs) is often hindered by challenges such as synthetic accessibility and time- and resource-intensive experimentation. High-throughput, automated experimental and computational techniques have enabled rapid chemical space exploration and theoretical MOF design. When combined with artificial intelligence (AI), these methods can be used to lead autonomous laboratories to new frontiers for MOF discovery, where these materials can be designed for a specific application, efficiently synthesized, characterized, and evaluated. Here, this perspective highlights the role of AI in advancing automated MOF synthesis and characterization, computational MOF design and screening, and the integration of these approaches within autonomous workflows to ultimately enable the MOF laboratories of the future.

Gaidimas, Madeleine A. [Northwestern University, E↗

Integrating Experiments and Well Logs to Predict Caney Shale Static Mechanical Properties During Production with Supervised Machine Learning

Caney shale is one of the emerging oil reservoirs in Oklahoma. Understanding the impact of effective stress on its mechanical properties is critical for predicting hydraulic fracture geometry and overall hydrocarbon production. The objective of our study is to evaluate the impact of effective stress on the dynamic Young’s modulus using ultrasonic velocity measurements for Caney shale samples. A triaxial cell was utilized to measure ultrasonic (P-wave and S-wave) velocities for ten downhole Caney shale samples under various effective stresses to indirectly assess the impact of pore pressure change. The dynamic Young’s moduli estimated from these measurements were integrated with available conventional well logs (excluding sonic logs) and triaxial test results from Benge et al. (2021) to predict the static Young’s modulus using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that the estimated dynamic Young’s moduli from ultrasonic measurements were higher than the corresponding static Young’s modulus of cores from the same vertical well at similar depths. With increasing effective stress, the dynamic Young’s modulus increased for all samples. The estimated dynamic-to-static correction factor tended to be higher in zones of high neutron porosity (PHIN) and low density compared to other zones. Finally, SHapley Additive exPlanations (SHAP) for RF and XGBoost models identified depth, gamma ray (GR), and PHIN as key features for predicting the static Young’s modulus. This study enhances our understanding of the dynamic and static Young’s moduli for the Caney shale interval, as a function of effective stress and conventional well logs. The findings from this study can improve predictions of production throughout the well's lifespan by offering insights into the mechanical property degradation resulting from pore pressure depletion.

Kholy, Sherif M.↗

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and there are typically inherent degeneracies in fitting the EOS, there are actually multiple EOSs that might be consistent with calibration data. In this work, we perform uncertainty quantification (UQ) for the reactant and product equations of state for the high explosive PBX 9501 to yield an ensemble of EOSs that match the uncertain small-scale calibration data. We then simulate an experiment of an explosively formed penetrator repeatedly with different EOSs to both validate the UQ analysis and determine the effects of EOS uncertainty on the prediction of quantities of interest in the experiment. In general, we find good agreement between the simulation predictions and the experimental measurements, and we identify an EOS variable that contributes most directly to the spread in the predictions as the EOSs are varied.

36 MATERIALS SCIENCE↗