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At least 937 records · Page 52

Angularly resolved spectral reconstruction of x rays via filter pack attenuation

We have designed a new filter pack array to measure angular variations in x-ray spectra during a single shot. The filter pack was composed of repeating identical columns of aluminum and copper filters of varying thicknesses. These columns were located at different positions to measure the spectrum at each corresponding angle. This array was utilized in an experiment to measure the energy evolution of betatron x rays in a laser wakefield accelerator by curving the wakefield with a transverse density gradient, streaking the x rays across the array in front of an x-ray charge-coupled device (CCD) camera. After subtracting the background and “flattening” the image to remove spatial nonuniformities, a critical energy was calculated for each position that produced the best agreement with the measured signal. There was a clear change in critical energy with angle, shedding light on the dynamics of the electrons that traveled through the accelerator. Furthermore, these angles correspond to distinct emission times, covering a timescale of tens of picoseconds. The filter pack was capable of recovering these angular details without the impact of errors introduced by shot-to-shot variability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding SYCL Portability for Pseudorandom Number Generation: a Case Study with Gene-Expression Connectivity Mapping

Towards the goal of improving functional and performance portability of SYCL, we study a bioinformatics application that has been accelerated with CUDA and fast pseudorandom number generation on a GPU. We describe the experience of migrating pseudorandom number generation from CUDA to SYCL, evaluate the performance of pseudorandom number generators using the CUDA random number generation library, suggest the support of the XORWOW pseudorandom number generator in the oneAPI math kernel library (oneMKL) interface for performance portability, and identify the performance gap using the MKL interface in SYCL that supports pseudorandom number generation with third-party libraries. We hope that the results are valuable for the development of the SYCL ecosystem.

Jin, Zheming↗

Exploring neutrino–nucleus interactions in the GeV regime using MINERvA

With the advance of particle accelerator and detector technologies, the neutrino physics landscape is rapidly expanding. As neutrino oscillation experiments enter the intensity and precision frontiers, neutrino–nucleus interaction measurements are providing crucial input. MINERvA is an experiment at Fermilab dedicated to the study of neutrino–nucleus interactions in the regime of incident neutrino energies from one to few GeV. The experiment recorded neutrino and antineutrino scattering data with the NuMI beamline from 2009 to 2019 using the Low-Energy and Medium-Energy beams that peak at 3GeV and 6GeV, respectively. This article reviews the broad spectrum of interesting nuclear and particle physics that MINERvA investigations have illuminated. The newfound, detailed knowledge of neutrino interactions with nuclear targets thereby obtained is proving essential to continued progress in the neutrino physics sector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Coupling Pulse Radiolysis with Nanosecond Time-Resolved Step-Scan Fourier Transform Infrared Spectroscopy: Broadband Mid-Infrared Detection of Radiolytically Generated Transients

We describe the first implementation of broadband, nanosecond time-resolved step-scan Fourier transform infrared (S 2 -FT-IR) spectroscopy at a pulse radiolysis facility. This new technique allows the rapid acquisition of nano- to microsecond time-resolved infrared (TRIR) spectra of transient species generated by pulse radiolysis of liquid samples at a pulsed electron accelerator. Wide regions of the mid-infrared can be probed in a single experiment, which often takes < 20–30 min to complete. It is therefore a powerful method for rapidly locating the IR absorptions of short-lived, radiation-induced species in solution, and for directly monitoring their subsequent reactions. Time-resolved step-scan FT-IR detection for pulse radiolysis thus complements our existing narrowband quantum cascade laser-based pulse radiolysis-TRIR detection system, which is more suitable for acquiring single-shot kinetics and narrowband TRIR spectra on small-volume samples and in strongly absorbing solvents, such as water. We have demonstrated the application of time-resolved step-scan FT-IR spectroscopy to pulse radiolysis by probing the metal carbonyl and organic carbonyl vibrations of the one-electron-reduced forms of two Re-based CO 2 reduction catalysts in acetonitrile solution. Transient IR absorption bands with amplitudes on the order of 1 × 10 −3 are easily detected on the sub-microsecond timescale using electron pulses as short as 250 ns.

(S2-FT-IR)↗

Searches for Sub-GeV Dark Matter with NOvA and LDMX and Performance Studies of the Cosmic-Ray Veto for Mu2e

The constituents of dark matter are still unknown, and the viable possibilities span a very large mass range. Specific scenarios for the origin of dark matter sharpen the focus to within about an MeV to 100 TeV. Most of the stable constituents of known matter have masses in the lower range, and a thermal origin for dark matter works in a simple and predictive manner in this mass range as well. Non-gravitational couplings of dark matter to Standard Model particles would make it possible to produce dark matter at accelerators. Through 120 GeV proton-nucleus collisions, NOvA is effectively a beam dump experiment for producing and detecting dark matter. This thesis presents a search for dark matter – electron scattering in the NOvA near detector from sub-GeV dark matter produced at the target. A future search for sub-GeV dark matter with the Light Dark Matter eXperiment (LDMX) is discussed, along with a study of LDMX's expected sensitivity to visibly decaying dark photons. Additionally, performance studies of the Mu2e cosmic ray veto (CRV) are presented. A calibration procedure for the CRV counters is discussed, along with tests of the efficiency, position resolution, and light yield decline of the CRV counters.

Horoho, Tyler Gregory [Virginia U.] (ORCID:0000000↗

JLAB LLRF 3.0 Development and Tests

The Jefferson Lab LLRF 3.0 system is being developed to replace legacy LLRF systems in the CEBAF accelerator. The new design builds upon 25 years of design and operational RF control experience, and our recent collaboration in the design of the LCLSII LLRF system. The new cavity control algorithm is a fully functional phase and amplitude locked Self Exciting Loop (SEL). This paper discusses the progress of the LLRF 3.0 hardware design, FPGA firmware development, User Datagram Protocol (UDP) operation, and recent LLRF 3.0 system tests on the CEBAF Booster cryomodule in the Upgrade Injector Test Facility (UITF).

Plawski, T. E.↗

Lattice design of 250 MeV version of PERLE

The PERLE (Powerful Energy Recovery LINAC for Experiment) collaboration is working on a high power energy recuperation linac facility with three acceleration (up to 500 MeV) and three deceleration passes through two cryomodules with an injection current of 20 mA. Here we present the lattice design of the first phase of this machine, which features a single cryo-module and demonstrates six-pass operation at a maximum energy of 250 MeV at a high current. This initial lattice design boasts a simpler structure with fewer elements, resulting in lower initial costs and faster construction and shorter commissioning time. Furthermore, all magnets and cryo-modules are designed to be compatible with both phases, keeping upgrade costs to a minimum.

Fomin, A.↗

Simulations of Hypervelocity Impact Plasmas

The space environment is fraught with complex plasmas spanning a wide range of densities and temperatures. Much of space plasma research has focused on large-scale changes in the ambient plasma and fields from the Sun to the Earth’s atmosphere, driven primarily by the solar wind. Yet one particular type of space plasma, which forms from a hypervelocity impact (HVI), remains poorly understood. Hypervelocity impactors include both meteoroids and space debris. Meteoroids are naturally occurring objects in space that travel between 11 and 72.8 km/s and originate primarily from comets and asteroids. In contrast, space debris are human-made objects with speeds typically < 11 km/s. Hypervelocity impactors routinely hit spacecraft, yet the physics behind the formation of the plasma and the dynamics of its expansion remain largely unknown. The complexity of this phenomenon necessitates a research approach that includes both experimental studies and numerical simulation in order to understand the underlying physical processes that occur upon formation and expansion of the impact plasma. Our research has focused on providing a comprehensive understanding of plasma generated by hypervelocity impacts by meteoroids and space debris on spacecraft in order to characterize the behavior of the expanding plasma and its interactions with the ambient environment. Previously. we conducted experimental campaigns at a dust accelerator facility that can accelerate particles up to 60 km/s, which is representative of meteoroid speeds, and at a light gas gun facility that can accelerate larger projectiles up to 7 km/s, which is representative of orbital debris. The experiments included plasma, optical and radio frequency (RF) sensors in order to understand the dynamics and associated RF emission resulting from hypervelocity plasmas. For this research, we developed and applied machine learning algorithms to identify which type of impactor would produce RF and physics-based models to determine the source of the RF. This was a one-year research program that resulted in 2 refereed journal publications (uploaded separately).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic System Scaling Applied to Zr-4 Cladding under RIA Conditions

The research and development lifecycle for new fuel designs currently has an ideal 20-25 year timeline. Efforts are currrently underway to accelerate fuel design and development using high performance fuel modeling codes and reduced scale experiments with new instrumentation techniques. However current tools available require a full scale prototype to be designed and tested for fuel qualification. The thermal-hydraulics community has leveraged scaling methodologies to use reduced scale integral effect test facilities (Westinghouse AP600/1000, NuScale Power Module) in lieu of building full scale prototypes for reactor design certification. Dynamic System Scaling (DSS) is a recent development to scaling methodologies that enable the tracking and quantification of dynamic scaling distortions experienced throughout a transient. Recent TREAT experiments performed reactivity initiated accident (RIA) pulses on UO2 fuel rodlets in Zr-4 cladding and were accompanied by BISON predictions for the cladding temperature. DSS is applied to pyrometer data of outer cladding temperatures and two BISON predictions after peak cladding temperature has been reached. One BISON case uses a constant gap conductance value between the fuel and cladding and the other using a conventional gap conductance model. Results from the DSS analysis show that there is good agreement between both BISON predictions and the experimental data and that there is not a significant distortion seen between using either gap conductance model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Application of Dynamical System Scaling for Accelerated Fuel Qualification Efforts

There are considerable ongoing research and testing campaigns to qualify new fuel designs such as metallic fuels for advanced reactor designs and the Accident Tolerant Fuel (ATF) campaign for light water reactors (LWR). The typical research and development lifecycle needed to qualify a nuclear fuel design, under ideal conditions, can take up to 20-25 years which limits the ability for new fuels to make fast deployments into commercial, test, and research reactors. While there are several efforts to accelerate nuclear fuel qualification through advanced modeling coupled with state-of-the-art experiments, there is not yet a framework to methodically quantify and rank distortions occurring in experimental test specimens needed to validate nuclear fuel performance codes. This study uses the Dynamical System Scaling (DSS) methodology to quantify transient scaling distortions that occur over experiment and simulated transients. DSS analysis metrics provide a researcher with several tools and information embedded within test data to identify dominant phenomena, associated timescales, and quantify a transient?s overall dynamic distortion. This is demonstrated with separate analyses of the SETH-C and CHF-SERTTA thermal-hydraulic experiments in the TREAT facility at Idaho National Laboratory. The outcome of this work is a scaling and data analysis approach to account for the influence a scaled fuel test specimen?s geometric and temporal distortions have on its ability to be representative of the full-scale design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of Irradiation Creep Effects in HT9 Cladding for FAST Experiments

The push for advanced reactor fuels for improved reactor safety and efficiency had led to a renewed interest in metallic fuel for nuclear reactor applications. Experimental investigation is necessary to ensure a robust understanding of the thermomechanical properties of new metallic fuel designs. Unfortunately, with the current experimental facilities, thoroughly investigating the responses of metallic fuel burnup would take a prohibitively long time. To alleviate this, the Fission Accelerated Steady State Test (FAST) was developed to accelerate the irradiation testing while simultaneously decreasing the sensitivity to fabrication tolerances by reducing the fuel diameter and scaling the experiment. This method successfully scales the radiation effects on the fuel, but the HT9 cladding is not exposed to prototypic radiation conditions. This raises questions on whether the FAST experiment results are truly indicative of the HT9 cladding performance due to radiation induced creep effects not being appropriately accounted for. Using BISON fuel performance code, the simulated FAST cladding strain is compared to simulated EBR-II cladding strain. This is done through a sensitivity study of input parameters and scaling of neutron fluence on the cladding. This allows a parametric comparison of physical phenomena on the effective difference between cladding strains between FAST and equivalent burnup EBR-II fuel pins. The results show that the irradiation induced deformation (creep or swelling) is insignificant compared to the thermal-mechanical deformation. Therefore, the difference between the FAST experiment cladding and the EBR-II experiment cladding is negligible and comparison of fuel system performance between the two experiments is appropriate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Collective Summary of sCO2 Materials Development (Supercritical Transformational Electric Power Generation (STEP) Level 2 Milestone Report) (Parts I - II)

Polymers such as PTFE (polytetrafluorethylene or Teflon), EPDM (ethylene propylene diene monomer) rubber, FKM fluoroelastomer (Viton), Nylon 11, Nitrile butadiene (NBR) rubber, hydrogenated nitrile rubber (HNBR) and perfluoroelastomers (FF_202) are commonly employed in super critical CO 2 (sCO2) energy conversion systems. O-rings and gaskets made from these polymers face stringent performance conditions such as elevated temperatures, high pressures, pollutants, and corrosive humid environments. In FY 2019, we conducted experiments at high temperatures (100°C and 120°C) under isobaric conditions (20 MPa). Findings showed that elevated temperatures accelerated degradation of polymers in sCO2, and that certain polymer microstructures are more susceptible to degradation over others. In FY 2020, the focus was to understand the effect of sCO2 on polymers at low (10 MPa) and high pressures (40 MPa) under isothermal conditions (100°C). It was clear that the same selectivity was observed in these experiments wherein certain polymeric functionalities showed more propensity to failure over others. Fast diffusion, supported by higher pressures and long exposure times (1000 hours) at the test temperature, caused increased damage in sCO2 environments to even the most robust polymers. We also looked at polymers under compression in sCO2 at 100°C and 20 MPa pressure to imitate actual sealing performance required of these materials in sCO2 systems. Compression worsened the physical damage that resulted from chemical attack of the polymers under these test conditions. In FY 2021, the effect of cycling temperature (from 50°C to 150°C to 50°C) for polymers under a steady sCO2 pressure of 20 MPa was studied. The aim was to understand the influence of cycling temperatures of sCO2 for typical polymers under isobaric (20 MPa) conditions. Thermoplastic polymers (Nylon, and PTFE) and elastomers (EPDM, Viton, Buna N, Neoprene, FF202, and HNBR) were subjected to 20 MPa sCO2 pressure for 50 cycles and 100 cycles in separate experiments. Samples were extracted for ex-situ characterization at 50 cycles and upon the completion of 100 cycles. Each cycle constituted of 175 minutes of cycling from 50°C to 150°C. The polymer samples were examined for physical and chemical changes by Dynamic Mechanical and Thermal Analysis (DMTA), Fourier Transform Infrared (FTIR) spectroscopy, and compression set. Density and mass changes immediately after removal from test were measured for degree of swell comparisons. Optical microscopy techniques and micro computer tomography (micro CT) images were collected on select specimens. Evaluations conducted showed that exposures to super-critical CO2 environments resulted in combinations of physical and/or chemical changes. For each polymer, the dominance of cycling temperatures under sCO2 pressures, were evaluated. Attempts were made to qualitatively link the permanent sCO2 effects to polymer micro- structure, free volume, backbone substitutions, presence of polar groups, and degree of crystallinity differences. This study has established that soft polymeric materials are conducive to failure in sCO2 through mechanisms of failure that are dependent on polymer microstructure and chemistry. Polar pendant groups, large atom substitutions on the backbone are some of the factors that are influential structural factors.

36 MATERIALS SCIENCE↗

Transforming polymorphs, melting, and boiling during cookoff of PETN

Transforming polymorphs, melting, and boiling are physical processes that can accelerate decomposition rates during cookoff of PETN and make measurements difficult. For example, splashing liquids from large bubbles filled with decomposition products clog pressure tubing in sealed experiments. Boil over can also extinguish thermal excursions in vented experiments making ignition difficult. For better measurements, we have modified the Sandia Instrumented Thermal Ignition (SITI) experiment to obtain better sealed and vented cookoff data for PETN by reducing the sample size and including additional gas space to prevent clogged tubing and boil over. Ignition times were not affected by 1) increasing the gas space by a factor of 3 in sealed SITI experiments or by 2) venting the decomposition gasses. That is, thermal ignition of PETN is not pressure dependent and the rate-limiting step during PETN decomposition likely occurs in the condensed phase. A simple decomposition model was calibrated using these observations and includes rate acceleration caused by melting and boiling. The model is used to predict internal temperatures, pressurization, and thermal ignition in a wide variety of experiments. Furthermore, the model is also used with SITI data to estimate the previously unreported latent enthalpy (5 J/g) associated with the α (PETN-I) to β (PETN-II) polymorphic phase transformation of PETN.

42 ENGINEERING↗

Dynamic System Scaling Application to Accelerated Nuclear Fuel Testing

The development of nuclear fuel and materials requires a continuous effort to investigate the acute and prolonged effects of irradiation, thermal-material stress, chemical change, or other conceivable damage mechanics acquired during normal operation or accident scenarios throughout its lifetime. As in-core fuel property measurement techniques advance to support in the real-time, non-invasive, and enhanced accuracy realm, it is the future of fuel development to pursue to higher degrees of control, predictability of integral test behavior via separate effects test (SET), and shorter test time intervals. The fuel development life cycle from initial concept to commercial licensing is approximated to be 20 years and current literature suggests by optimizing fuel performance codes with SETs, the process could possibly be compressed to 5 to 10 years. Recently, a research group in the Idaho National Laboratory (INL) is testing reduced scale fuel rods and increased power density to accelerate evolution of fuel phenomena in metallic fuels. In support of nuclear fuel rod development, compressing fuel test process, and accelerating fuel phenomena, it was the purpose of this study to investigate nuclear fuel performance phenomena via literature review and effectively scale the initial conditions, boundary conditions, and geometric properties to describe the time-dependent response including to fuel burnup, thermal and mechanical stress, transmutations and inter-diffusion, and other relevant observed phenomena. The study was based on BISON simulations of historic EBR-II metallic fuel experiments and Dynamical System Scaling (DSS) method are utilized to assess effects of scaling activity including fuel phenomena acceleration and calculations of time-dependent distortions. The research successfully scaled metallic fuel phenomena, accelerated fuel testing, and assessed the distortions for each scaled case derived.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Track Matching in the DUNE Near Detectors

The Deep Underground Neutrino Experiment (DUNE) is an international particle physics experiment looking answer some of the largest unanswered questions in neutrino physics. DUNE uses a high power neutrino beam produced at Fermi National Accelerator Laboratory (Fermilab), and consists of a near detector (ND) also located at Fermilab and a far detector (FD) 1300 km away at the Sanford Underground Research Facility (SURF) in South Dakota. In the first phase of the experiment, the ND complex will contain a modular liquid argon TPC (ND-LAr) and a solid scintillator-based muon spectrometer (TMS), in addition to a beam monitoring detector (SAND) and systems for moving ND-LAr and TMS away from the neutrino beam axis (PRISM). A prototype of ND-LAr, the 2x2 demonstrator, alongside a solid scintillator muon tagger provided by repurposed MINERvA planes, has been built and taken data at Fermilab. For analyses with the ND, connecting particle tracks (such as muons) that exit the liquid argon active volume into the solid scintillator muon detector can improve particle identification and energy reconstruction, and alleviate pileup due to the intense beam. To match tracks between detectors during reconstruction, we have explored using Graph Neural Networks (GNNs) to connect tracks segments between the liquid argon detector region and the solid scintillator detector planes. We have trained a GNN on reconstructed simulated data from the 2×2 demonstrator and repurposed MINERvA planes. We will evaluate its performance and then train a similar network on reconstructed ND-LAr and TMS simulations.

Xing, Daniel [U. Colorado, Boulder]↗

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗

Deep-learning-based domain adaptation for cavity fault prediction at Jefferson Laboratory

Superconducting radio-frequency (SRF) cavities are the core components of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab, providing high-power electron beams for nuclear physics experiments. The facility comprises 418 SRF cavities, and any fault in these cavities can lead to interruptions in the electron beam supply. Cavity faults are the leading cause of beam trips in CEBAF. Predicting and mitigating those faults before onset can help maintain normal operation. Existing models face challenges in distinguishing between normal and fault signals when changes occur in the underlying time-series data, from changes in control software, operational parameters, or the environment. This work proposes a deep learning domain adaptation model that leverages transfer learning to address fault prediction challenges by improving accuracy. The model is trained and fine-tuned using a dataset collected for faulty and normal operation using a data acquisition system in CEBAF. Our deep learning-based domain adaptation model achieves a prediction accuracy of 89.61% of the fault and normal signals. The developed model effectively predicts normal running signals compared to the baseline approach without domain adaptation. This capacity is essential for the fault prediction task in the CEBAF because of heavily imbalanced data containing vast amounts of normal signals. The model performs well for predicting faults several hundred milliseconds before the fault onset compared to other models where no adaptation is applied. Incorporating deep learning-based domain adaptation techniques will significantly improve the fault prediction performance.

Rahman, Md Monibor [Old Dominion Univ., Norfolk, V↗

Carbon cycle extremes accelerate weakening of the land carbon sink in the late 21st century

Increasing surface temperature could lead to enhanced evaporation, reduced soil moisture availability, and more frequent droughts and heat waves. The spatiotemporal co-occurrence of such effects further drives extreme anomalies in vegetation productivity and net land carbon storage. However, the impacts of climate change on extremes in net biospheric production (NBP) over longer time periods are unknown. Using the percentile threshold on the probability distribution curve of NBP anomalies, we computed negative and positive extremes in NBP. Here we show that due to climate warming, about 88% of global regions will experience a larger magnitude of negative NBP extremes than positive NBP extremes toward the end of 2100, which accelerate the weakening of the land carbon sink. Our analysis indicates the frequency of negative extremes associated with declines in biospheric productivity was larger than positive extremes, especially in the tropics. While the overall impact of warming at high latitudes is expected to increase plant productivity and carbon uptake, high-temperature anomalies increasingly induce negative NBP extremes toward the end of the 21st century. Using regression analysis, we found soil moisture anomalies to be the most dominant individual driver of NBP extremes. The compound effect of hotness, dryness, and fire caused extremes at more than 50% of the total grid cells. The larger proportion of negative NBP extremes raises a concern about whether the Earth is capable of increasing vegetation production with a growing human population and rising demand for plant material for food, fiber, fuel, and building materials. The increasing proportion of negative NBP extremes highlights the consequences not only of reduction in total carbon uptake capacity but also of conversion of land to a carbon source.

54 ENVIRONMENTAL SCIENCES↗