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Active Experiments in Space: Past, Present, and Future

Between 1958 and 1962 the United States and the Soviet Union performed several nuclear detonation tests in the atmosphere, including the Starfish Prime event which involved a 1.4 Mt explosion at 400 km altitude over Johnston island on July 9, 1962 (Gombosi et al., 2017). These tests can be considered as the beginning of active experiments in space (i.e., experiments that deliberately perturb the local environment). They demonstrated the potential destructive power of high-altitude nuclear explosions, both in terms of the resulting electromagnetic pulse as well as for the creation of a potentially long-lasting artificial radiation belt from the radioactive fission debris. For instance,one of the unintended consequences of Starfish Prime was to cripple at least seven spacecraft in low-Earth orbit (LEO), about a third of the LEO spacecraft of the time (Gombosi et al., 2017).

79 ASTRONOMY AND ASTROPHYSICS↗

High Flux Isotope Reactor Neutron Spectrum Shape Estimation From Activation Experiment Data

Here, this article provides a comprehensive review of historical irradiation dosimetry available for different locations within the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). This article includes a summary of the available measured activation target data covering a span of over 15 years and 39 experimental campaigns, including 200 individual sample locations evaluated. Using this broad set of data, we reconstruct historic average neutron spectra shapes for HFIR at various locations, including within the flux trap region, beryllium reflectors, and hydraulic tube (HT) regions, at both the 100- and 85-MW operational power. Our findings indicate that the general axial flux distribution shows a relatively small change in transition from 100- to 85-MW operating power, with differences of -6% to +15% for the thermal energy range and around -16% to +8% for the fast range, indicating a sharper drop-off of the thermal neutron flux away from the axial center. Compared with historical dosimetry estimates of the HFIR flux shape, we generally find a moderately broader axial profile shape for thermal neutrons in the interior target regions for the 100-MW samples evaluated but relatively close agreement for the present 85-MW flux shape for both thermal and fast fluxes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cubic-meter scale laboratory fault re-activation experiments to improve the understanding of induced seismicity risks

Abstract To understand fluid induced seismicity, we have designed a large-scale laboratory experiment consisting of a one-cubic-meter sandstone with an artificial fault cut and fluid-injection boreholes. The sandstone block is assembled in a true triaxial loading frame and equipped with 38 piezoelectric sensors to locate and characterise acoustic emission events. The differential stress on the artificial fault is increased in stages to bring it towards a critically stressed state. After each stage of differential stress increase, fluids are injected at low pressures through boreholes to test the potential of fault re-activation. In addition, a high-pressure injection was conducted that created a hydraulic fracture from the injection borehole towards the artificial fault. The newly generated fluid pathway resulted in an activation of the complete block through a stick–slip movement. We compare acoustic emission measurements from the laboratory experiment with seismicity observations from the field-scale CO 2 injection at Decatur, Illinois, U.S., and conclude that the existence of fluid pathways plays a decisive role for the potential of induced seismicity.

47 OTHER INSTRUMENTATION↗

Complexity of Fault Rupture and Fluid Leakage in Shale: Insights From a Controlled Fault Activation Experiment

Abstract We observed rupture growth caused by controlled fluid injections at 340‐m depth within a fault zone in the low‐permeability Opalinus Clay in the Mont Terri Underground Research Laboratory (Switzerland). The rupture mechanisms were evaluated using measurements of the three‐component borehole wall displacements and fluid pressure in two sections of the fault zone and located horizontally 3 m apart from each other. One section was set across a secondary segment of the fault and used for stepwise fluid injection intended to trigger rupture growth. The other section was set across the principal shear zone of the fault for monitoring. After stepwise pressure increase up to 5.95 MPa at injection, rupture initiated as slip activation, followed by an overall opening of the fault planes connected to the injection. After 19 s of continued injection, displacements arrived at the monitoring point on the principal shear zone. These displacements are about 2.4 times larger than in the secondary fault segment. Overall, the displacements corresponded to a normal fault activation. About 9 s after the displacement front arrived, a strong pressure increase of 4.17 MPa was measured at the monitoring point, indicating a hydraulic connection had formed along the initially very low permeability fault planes between the injection and the monitoring points. Our analyses highlight that the fault activation is consistent with the state of stress but that injection pressure must be close to the normal stress acting on the fault for permeability to be generated and for fluid leakage to occur.

Guglielmi, Yves↗

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

ORNL FACE Tree Height, with data on height of a subset of trees measured every year, 1997-2009. Free-Air CO2 Enrichment (FACE) Experiment Synthesis Activities.

Height of 20 sweetgum trees in three rows of each of the plots in the Oak Ridge National Laboratory (ORNL) free-air CO2 enrichment (FACE) experiment was measured each year of the experiment (1997-2009). The trees were exposed to ambient or elevated CO2. Tree height data contribute to the overall project objectives to determine the integrated response of a deciduous forest to elevated CO2. Average tree height per plot was used in allometric equations to calculate tree dry mass each year and to test whether there were effects of elevated CO2 on canopy development. Height was derived from trigonometric calculation from measurements of horizontal distance of observer from the bole and the angles from observer’s eye to top and base of tree, using a Haglof sonic hypsometer. The data are presented in a csv file, with plot number in the first column, tree number in the second column, and height recorded to 0.1 m in 1997 to 2009 in remaining columns. Plots 1 and 2 had elevated CO2, and plots 3-5 were in ambient CO2. Missing data occur after the tree died. The experiment and the height measurement are described in: Norby, R. J., D. E. Todd, J. Fults, and D. W. Johnson. 2001. Allometric determination of tree growth in a CO2-enriched sweetgum stand. New Phytologist 150: 477-487. The ORNL FACE experiment is described at: https://richnorby.org/home/face-home/.

54 ENVIRONMENTAL SCIENCES↗

Neutron moderation at IPF

We discuss here the possibility of using the Isotope Production Facility (IPF) at LANSCE to test the feasibility and performance of a graphite cube to create a neutron target. The idea of a neutron target enables the measurement of neutron induced reactions in inverse kinematics. This idea is part of the LANSCE strategy to stay a worldwide leader for neutron-induced research. The proof of-principle is the core of the LDRD project 20240004DR. The first steps are a series of activation experiments with different neutron energy distributions. Figs. 1 and 2 show a graphite cube built and simulated from pieces available at LANSCE. First activation experiments have already been performed at lower neutron energies utilizing (p,n) reactions on Li and Be.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced Test Reactor Safety Basis Update for Gas-Cooled Experiments

The Advanced Test Reactor (ATR) supports neutron irradiation of several types of experiments. One such experiment type is referred to as a gas leadout. Gas leadout experiments actively flow gas through the experiment which allows for active temperature control. It also allows for in-situ data of the experiment. For example, fission gas migration through a fuel sample can be monitored via activity of the sweep gas. Historically, ex-pile equipment and fission product monitors were housed in shielded ATR cubicles. Due to other facility updates, cubicle space is no longer available for gas leadout experiment equipment. To support continued operation of gas leadout experiments, ATR completed a safety basis update that supports a new housing for leadout equipment that may process potentially contaminated gas. In addition to the structure and associated equipment, technical safety requirements regarding handling and storage of experiments needed to be revised to support fueled gas leadout experiments and associated outage configurations. The safety basis update addressed the full lifecycle of these experiments, including experiment movement and interim storage, and credible abnormal events such as failures or leaks in contaminated gas tubing in occupied areas. This paper discusses the completed analyses performed to support the safety basis update associated with gas leadout experiments, including thermal-hydraulic evaluation, probabilistic analysis, and dose consequence analyses.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterization of D-T Generator Neutron Flux Spectrum for Cyclic Neutron Activation Analysis Experiments

Improving nuclear data for short-lived fission product yields will further our fundamental understanding of fission, which is needed across various scientific fields and applications. One method of attaining the needed product yield data is through cyclic neutron activation, which allows a target to be irradiated in a neutron environment and then transported for counting of the radionuclides produced, typically via g spectroscopy. Recently, such a system has been constructed and commissioned at Pacific Northwest National Laboratory. Targets are shuttled between the head of a D-T neutron generator and a counting station with a transit time of 2 seconds. As part of the characterization of this system, the neutron flux was studied using two activation targets. The neutron flux from the deuterium-tritium fusion generator was determined to be 9.95(33) x10^8 n/cm2-s with a peak energy of 14.9 MeV and a spread of approximately 4 decades between the epithermal and 14 MeV peak group flux.

cyclic neutron activation, gamma-ray spectroscopy,↗

Combining High-Throughput Experiments and Active Learning to Characterize Deep Eutectic Solvents

The high tunability of deep eutectic solvents (DESs) stems from the ease of changing their precursors and relative compositions. However, measuring the physicochemical properties across large composition and temperature ranges, necessary to properly design target-specific DESs, is tedious and error-prone and represents a bottleneck in the advancement and scalability of DES-based applications. As such, active learning (AL) methodologies based on Gaussian processes (GPs) were developed in this work to minimize the experimental effort necessary to characterize DESs. Owing to its importance for large-scale applications, the reduction of DES viscosity through the addition of a low-molecular-weight solvent was explored as a case study. A high-throughput experimental screening was initially performed on nine different ternary DESs. Then, GPs were successfully trained to predict DES viscosity from its composition and temperature, showcasing the ability of these stochastic, nonparametric models to accurately describe the physicochemical properties of complex mixtures. Finally, the ability of GPs to provide estimates of their own uncertainty was leveraged through an AL framework to minimize the number of data points necessary to obtain accurate viscosity modes. This led to a significant reduction in data requirements, with many systems requiring only five independent viscosity data points to be properly described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The NASA ACTIVATE Mission

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol–cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020–22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration N d , including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scavenging, and mesoscale organization. Remote sensing advances range from new retrieval methods for N d , cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technological advances along with efforts in outreach and open data science.

aerosol indirect effect↗

Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ~ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020).

54 ENVIRONMENTAL SCIENCES↗

Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.

54 ENVIRONMENTAL SCIENCES↗

Study of cosmogenic activation above ground for the DarkSide-20k experiment

The activation of materials due to exposure to cosmic rays may become an important background source for experiments investigating rare event phenomena. DarkSide-20k, currently under construction at the Laboratori Nazionali del Gran Sasso, is a direct detection experiment for galactic dark matter particles, using a two-phase liquid-argon Time Projection Chamber (TPC) filled with 49.7 tonnes (active mass) of Underground Argon (UAr) depleted in 39 Ar. Despite the outstanding capability of discriminating γ / β background in argon TPCs, this background must be considered because of induced dead time or accidental coincidences mimicking dark-matter signals and it is relevant for low-threshold electron-counting measurements. Here, the cosmogenic activity of relevant long-lived radioisotopes induced in the experiment has been estimated to set requirements and procedures during preparation of the experiment and to check that it is not dominant over primordial radioactivity; particular attention has been paid to the activation of the 120 t of UAr used in DarkSide-20k. Expected exposures above ground and production rates, either measured or calculated, have been considered in detail. From the simulated counting rates in the detector due to cosmogenic isotopes, it is concluded that activation in copper and stainless steel is not problematic. The activity of 39 Ar induced during extraction, purification and transport on surface is evaluated to be 2.8% of the activity measured in UAr by DarkSide-50 experiment, which used the same underground source, and thus considered acceptable. Other isotopes in the UAr such as 37 Ar and 3 H are shown not to be relevant due to short half-life and assumed purification methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy. This, in turn, necessitates the development of active learning methods capable of exploring relevant parameter spaces with the smallest number of steps. In this work, an active learning approach based on conavigation of the hypothesis and experimental spaces is introduced. This is realized by combining the structured Gaussian processes containing probabilistic models of the possible system's behaviors (hypotheses) with reinforcement learning policy refinement (discovery). This approach closely resembles classical human-driven physical discovery, when several alternative hypotheses realized via models with adjustable parameters are tested during an experiment. This approach is demonstrated for exploring concentration-induced phase transitions in combinatorial libraries of Sm-doped BiFeO 3 using piezoresponse force microscopy, but it is straightforward to extend it to higher-dimensional parameter spaces and more complex physical problems once the experimental workflow and hypothesis generation are available.

36 MATERIALS SCIENCE↗

DECOVALEX-2019 (Task B Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. This document is the final report of Task B which was proposed and coordinated by the Swiss Federal Nuclear Safety Inspectorate (ENSI) and Lawrence Berkeley National Laboratory (LBNL), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task B focused mainly on modelling of fault activation experiments (FS experiment) recently performed at the Mont Terri underground research laboratory, Switzerland. The FS experiment explores the coupling between fault reactivation in a clay host rock and the potential-enhanced fluid displacement through a previously low-permeability formation. Based on this experiment, the DECOVALEX-2019 Task B addresses how the change in permeability induced by the fault activation and the resulting fluid flow within the fault can be simulated including the dependence on its mechanical behavior. This will support the understanding of the processes during fault activation itself and it can help to determine consequences for contaminant transport due to potentially created permeable flow paths in otherwise low permeability argillaceous rocks.

58 GEOSCIENCES↗