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At least 343 records · Page 19

A Cybersecurity Event Simulation Tool and Platform

Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling Predictive Maintenance for NuScale’s Condensate and Feedwater System Using EMRALD

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is used to model of NuScale’s feedwater and condenser system to capture component degradation and repairing process. To model the reliability of the components, a three-stage failure rate is used contrary to a constant rate leading to component failure. Results from EMRALD will be used to compare different maintenance strategies to reduce system downtime. The outcome of the project will assist in maximizing remaining useful life of the overall system and increasing the availability and revenue of the plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The MU2E Experiment at FERMILAB: R&D, Design and Status

The Mu2e Experiment at Fermilab 1) will search for coherent, neutrinoless conversion of negative muons into electrons in the field of an aluminum nucleus, µ - + N (A, Z) → e - + N (A, Z). This is an example of Charged Lepton Flavour Violation (CLFV) never observed experimentally. The dynamics of such a process is well modelled by a two-body decay, resulting in a mono-energetic electron with an energy slightly below the muon rest mass (~104.967 MeV). If no events are observed in three years of running, Mu2e will set an upper limit on the ratio between conversion and capture rate R µe ≤ 6 × 10 -17 (@ 90% C.L.). This will improve the current limit of a factor of 10 4 over previous experiments. The experiment complements and extends the current/planned searches (µ → eγdecay at MEG , mu3e) as well as the direct searches for new physics at the LHC. Indeed, such CLFV searches in the muon sector probe new physics at a mass scale inaccessible with direct searches at either present or planned high-energy colliders. To detect the muon conversion process, a very intense pulsed beam of negative muons is produced by means of a S-shape Superconducting Solenoid Magnet System that is organized into three subsystems: the Production Solenoid, the Transport Solenoid and the Detector Solenoid. The beam is stopped at 10 GHz on an Aluminum target inside the Detector Solenoid. The Mu2e detectors, also installed inside the Detector Solenoid, are a high-precision tracker made on ~20000 straw tubes, and a calorimeter composed of ~1500 pure CsI crystals organized in two disks and readout by two large area UV-extended Silicon Photomultipliers (SiPMs). The Detector Solenoid region is surrounded by a Cosmic Ray Veto based on scintillators readout by SiPMs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Discriminating Uranium Isotopes Based on Fission Signatures Induced by Delayed Neutrons

The use of active interrogation to induce delayed neutron emission is a well-established technique for the characterization of special nuclear materials. Delayed neutrons have isotope-characteristic spectral and temporal signatures, which provide the basis for isotope identification. However, in bulk materials that contain an appreciable fissile (e.g., 235 U or 233 U) fraction, such as highly enriched uranium (HEU), delayed neutrons have a high probability of inducing additional fissions. As a result, the overall delayed neutron signature consists of two distinct components: the “primary” delayed neutrons (emitted directly by fission fragments) and the “secondary prompt” fission neutrons produced in fission induced by primary delayed neutrons. These prompt products differ from “primary” delayed neutrons both in their energy spectra and in the presence of coincident radiation released by the parent fission event. The presence and relative quantity of prompt products from delayed fission depend on the cross section of the material in the energy range of delayed neutrons, which may differ significantly between isotopes, thus providing an exploitable means for isotope differentiation. Here, we demonstrate two experimental approaches for discriminating between 235 U and 238 U isotopes based on the measurement of delayed neutron-induced fission products. First, HEU and depleted uranium objects are differentiated through the detection of high-energy prompt neutrons from delayed fission using both recoil-based organic liquid scintillators and thermalization spectra from a custom-built capture-gated composite detector. Secondly, coincident radiation measurements are used as the basis for discrimination by comparing the overall rates and time evolution of fission events when delayed neutrons are present.

07 ISOTOPE AND RADIATION SOURCES↗

Robust Deep Gaussian Process-Based Probabilistic Electrical Load Forecasting Against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This article proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining the excellent performance of capturing the forecasting uncertainties.

anomalous events↗

Atomistic Insights into the Reactive Diffusion of CO 2 in Guanidine-Based Facilitated Transport Membranes

The pressing need to address climate change has led to significant advancements in carbon dioxide (CO 2 ) capture technologies. Notably, facilitated transport membranes (FTMs) are distinguished by their exceptional selectivity and permeance, attributed to their reversible chemical reactions with CO 2 . This study, for the first time, sheds light on the reactive diffusion mechanism of CO 2 in FTMs, utilizing 1,1,3,3-tetramethylguanidine (TMG) as a mobile carrier. Specifically, state-ofthe- art molecular dynamics (MD) simulations, augmented by a reparameterized reactive force field (ReaxFF) capable of describing atomistic interactions and reaction pathways, are conducted to investigate the transport of CO 2 in TMG. The analysis of mean squared displacement (MSD) and diffusion coefficients reveals a clear hierarchy in the mobility of reaction components. Our findings highlight a unique hopping diffusion mechanism between bicarbonate ions and TMG molecules, increasing the diffusivity of reacted CO 2 by 1.4 times. The hopping events observed not only enhance our understanding of molecular mobility but also offer a means to boost the performance of FTMs in CO 2 capture applications. Overall, this research lays the groundwork for the future design of FTMs with optimal carrier properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating downscaled products with expected hydroclimatic co-variances

Abstract. There has been widespread adoption of downscaled products amongst practitioners and stakeholders to ascertain risk from climate hazards at the local scale (e.g., ∼ 5 km resolution). Such products must nevertheless be consistent with physical laws to be credible and of value to users. Here we evaluate statistically and dynamically downscaled products by examining local co-evolution of downscaled temperature and precipitation during convective and frontal precipitation events (two mechanisms testable with just temperature and precipitation). We find that two widely used statistical downscaling techniques (Localized Constructed Analogs version 2, LOCA2, and Seasonal Trends and Analysis of Residuals Empirical Statistical Downscaling Model, STAR-ESDM) generally preserve expected co-variances during convective precipitation events over the historical and future projected intervals as compared to European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) and two observation-based data products (Livneh and nClimGrid-Daily). However, both techniques dampen future intensification of frontal precipitation that is otherwise robustly captured in global climate models (i.e., prior to downscaling) and with process-based dynamical downscaling across five different regional climate models. In the case of LOCA2, this leads to appreciable underestimation of future frontal precipitation event intensity. This study is one of the first to quantify a likely ramification of the stationarity assumption underlying statistical downscaling methods and identify a phenomenon where projections of future change diverge depending on data production method employed. Finally, our work proposes expected co-variances during convective and frontal precipitation as useful evaluation diagnostics that can be universally applied to a wide range of statistically downscaled products.

54 ENVIRONMENTAL SCIENCES↗

Critical heat flux on zircaloy and accident tolerant fuel cladding under prototypical conditions of pressurized and boiling water reactors

First of a kind high spatial and temporal resolution temperature measurements of Pressurized Water Reactor and Boiling Water Reactor simulated fuel pins (high heat flux cosine profile heaters) in annular rod type geometry during nucleate boiling, departure from nucleate boiling and re-wetting has been performed. Distributed fiber optic measurements of the cladding axial temperature with spatial resolutions down to 2.5 mm axially at up to three equally spaced azimuthal locations per rod have demonstrated the similarities and differences of the different accident tolerant fuel cladding materials. These experiments show the performance of accident tolerant cladding with a precise measurement of the location and evolution of dryout followed by the re-wetting phenomena (see supplementary time history of a critical heat flux event). Experimental parameters varied coolant mass fluxes from 1695 to 2712 kg/m 2 s, pressures from 10 to 20 MPa, and inlet subcooling from 10 to 55 °C. It was found that the coatings and different material have little effect on the value of the critical heat flux. Any discrepancies between the local critical heat flux verified among the cladding material are attributed to different departure from nucleate boiling phenomena captured during the experiment with the high-resolution optical fiber temperature data. Substantial differences in the performance of the different cladding material to survive a critical heat flux event were however observed by post-test X-ray and optical inspection. External evident damage and internal cracks to the simulated fuel pin having the bare zircaloy cladding were observed in regions associated with the occurrence of the critical heat flux for longer periods. Such damages were associated with zirconium oxidation, and not noticed on the Cr coated zircaloy or FeCrAl claddings. These results indicate that the use of FeCrAl or a Cr coated zircaloy as cladding in Pressurized Water Reactor and Boiling Water Reactor may increase the survivability of the cladding material for short transients.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Direct Air Capture and Utilization System (DACUS): FEED Study of CarbonCapture Inc. DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat

The effects of climate change are drastically perceived through the alarming rates of severe events such as flooding, hurricanes, wildfires, global temperature rise, sea-level rise, and ocean acidification etc., which has prompted the nations across the globe to control & reduce greenhouse gas (GHG) emissions, by massive adoption of electric vehicles, switching to renewal energy sources and promoting sustainable green products. However, recent climate studies have shown that such efforts will not be enough to keep the global temperature rising under 1.5° Celsius by the year 2050, which lead to the development of multiple Direct Air Capture (DAC) technologies. A DAC system extracts CO2 directly from the atmosphere, which is either stored underground for long term or utilized in other processes. The DACUS proposed at U.S. Steel Corporation’s Gary Works Plant in Gary, Indiana, will include an innovative DAC technology from CarbonCapture Inc. (CCI), which will be collocated and powered by waste heat from the steel plant to capture CO2 from ambient air, and CarbonCure CO2 utilization technology- which is a commercial technology that is already installed and in use by early adopters in more than 150 concrete mixing plants across North America and Asia. The University of Illinois at Urbana Champaign spearheaded this Front-End Engineering Design (FEED) study project, which was funded by US Department of Energy (DOE), aimed at designing a state-of-the art DACU system that can remove minimum of 5,000 tonne/year net CO2 from air (based on cradle-to-gate LCA) and converting the captured CO2 into low carbon intensity products. The off takers of the low Carbon product produced by the DACUS have also been identified near the steel plant in the Indiana, Illinois & Wisconsin Region. This creates a full CO2 value chain and provides a means to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. DACUS is a promising new technology for reducing greenhouse gas in the atmosphere. Operation costs are minimized by locating CCI’s innovative DAC collector at United States Steel's Gary Works site where waste heat is utilized. Carbon emissions are minimized in CO2 transportation. The captured CO2 will be permanently sequestered in concrete used as construction material. This DOE funded FEED study demonstrates a full CO2 value chain for a DACU system, supported by an industrial facility. If this project were constructed, it would have a very positive and lasting impact on both the environment and the community.

42 ENGINEERING↗

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗

Investigation of the iodate sorption mechanism by CoAl LDH through experiments and ab initio molecular dynamics simulations

Radioiodine released during the nuclear-fuel cycle constitutes a persistent radiological hazard. In this study, the IO 3 – uptake mechanism of CoAl LDH was resolved by combining pH-controlled sorption experiments, synchrotron XAFS, and DFT-based AIMD simulations. At pH close to 6, approximately 90% of IO 3 – was removed, and the equilibrium distribution coefficient reached about 1.7 × 10 4 mL g –1 . EXAFS analysis indicated an average iodine–oxygen bond length of 1.81 Å and a coordination number near 3, with the fit R-factor equal to 0.002. The simulations faithfully reproduced the experimental spectrum and revealed transient proton hopping events that generated metastable I–O–H species inside the interlayer, thereby confirming nitrate-to-iodate exchange as the controlling capture pathway. Atomic density profiles and radial distribution functions further showed that IO 3 – adopt an end-on orientation perpendicular to the hydroxide sheets, while water molecules mediate proton migration without disturbing the host lattice. In conclusion, the integrated experimental–computational evidence demonstrates that CoAl LDH can rapidly and selectively sequester IO 3 – under near-neutral conditions, offering atomic scale guidance for the rational engineering of layered sorbents for advanced radioactive-waste treatment.

Kang, Jaehyuk [Jeju National Univ. (Korea, Republi↗

Spatiotemporal Route to Understanding Metal Halide Perovskitoid Crystallization

Here, a spatiotemporal experimental route is reported for the antisolvent vapor diffusion crystal growth of metal halide perovskitoids. A computational analysis combining automated image capture and diffusion modeling enables the determination of the critical concentrations required for nucleation and crystal growth from a single experiment. Five different solvent systems and ten distinct organic ammonium iodide salts were investigated with lead iodide, from which nine previously unreported compounds were discovered. Automated image capture of the mother liquor and antisolvent vials was used to determine changes in solution meniscus positions and detect the nucleation event location. Matching the observations to a numerical solution of Fick's second law diffusion model enables the calculation of reactant, solvent, and antisolvent concentrations at both the time and position of the first stable nucleation and crystal growth. A machine learning model was trained on the resulting data, and it reveals solvent- and amine-specific crystallization tendencies. Solvent systems that interact more weakly with dissolved lead species promote crystallization, while those with stronger interactions can prevent crystallization through increased solubilities. Organic amines that interact more strongly with inorganic components and exhibit greater rigidity are more likely to be incorporated into crystalline products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Cloud Liquid-Phase Microphysical Processes in Mixed-Phase Cumuli Over the Tibetan Plateau

Numerical simulations often overpredict precipitation over the Tibetan Plateau (TP). To examine the factors causing precipitation overprediction, different parameterizations of liquid-phase microphysical processes (accretion, autoconversion, and entrainment-mixing) are implemented into the Morrison microphysics scheme to simulate a TP precipitation event in summer with the Weather Research and Forecasting (WRF) model. The general spatial distribution and temporal trend of precipitation are captured by all simulations, but the precipitation rate is overpredicted. The results from sensitivity experiments suggest that compared to other examined liquid-phase processes, the accretion process is more important in precipitation simulation over the TP region. Further investigation with the Heidke skill scores reveals that accretion parameterization that takes into account the raindrop size produces the most accurate results in terms of the total surface precipitation. This parameterization suppresses spurious accretion and does not produce liquid-phase precipitation until cloud droplets are big enough. Here, it is also confirmed that increasing the model resolution can reduce precipitation overprediction. Results from the case study are confirmed by the use of a one-month simulation.

54 ENVIRONMENTAL SCIENCES↗

Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

The extensive integration of communication, computation, and control technologies into cyber-physical power systems (CPPSs) has increased the vulnerabilities of CPPSs to cyberattacks. This calls for developing solutions that assess and reduce the impacts of cyber-induced failures on CPPSs. This paper proposes a defensive islanding strategy to isolate impacted parts of the CPPS and form self-sufficient islanded grids with an objective of minimum load curtailment. The defensive islanding aims to split a power system into smaller grids to improve its resilience against a potential extreme event. A clustering approach that leverages the hierarchical spectral clustering method is utilized for the optimal defensive islanding. The proposed approach captures the fragility behavior and loading conditions of power system components due to cyber-induced failures. A graphical-based coupling framework is used to map the impacts of cyber failures into operation of power system components. The proposed method is demonstrated on a modified 33-node distribution feeder system integrated with distributed energy resources. The amount of load curtailment and radiality constraints have been used to evaluate the performance of the proposed clustering strategies. The results show the capability of the proposed algorithm to create islands considering the cyber-induced failures for enhanced resilience.

cyber-induced failures↗

Photon-In/Photon-Out X-ray Free-Electron Laser Studies of Radiolysis

Understanding the origin of reactive species following ionization in aqueous systems is an important aspect of radiation–matter interactions as the initial reactive species lead to production of radicals and subsequent long-term radiation damage. Tunable ultrafast X-ray free-electron pulses provide a new window to probe events occurring on the sub-picosecond timescale, supplementing other methodologies, such as pulse radiolysis, scavenger studies, and stop flow that capture longer timescale chemical phenomena. We review initial work capturing the fastest chemical processes in liquid water radiolysis using optical pump/X-ray probe spectroscopy in the water window and discuss how ultrafast X-ray pump/X-ray probe spectroscopies can examine ionization-induced processes more generally and with better time resolution. Ultimately, these methods will be applied to understanding radiation effects in complex aqueous solutions present in high-level nuclear waste.

47 OTHER INSTRUMENTATION↗

Measurement of charge and light yields for 127 Xe L -shell electron captures in liquid xenon

Dark matter searches using dual-phase xenon time-projection chambers (LXe-TPCs) rely on their ability to reject background electron recoils (ERs) while searching for signal-like nuclear recoils (NRs). ER response is typically calibrated using β -decay sources, such as tritium, but these calibrations do not characterize events accompanied by an atomic vacancy, as in solar neutrino scatters off inner-shell electrons. Such events lead to emission of x rays and Auger electrons, resulting in higher electron-ion recombination and thus a more NR-like response than inferred from β -decay calibration. We present a cross-calibration of tritium β -decays and Xe 127 electron-capture decays (which produce inner-shell vacancies) in a small-scale LXe-TPC and give the most precise measurements to date of light and charge yields for the Xe 127 L -shell electron-capture in liquid xenon. We observe a 6.9 σ ( 9.2 σ ) discrepancy in the L -shell capture response relative to tritium β decays, measured at a drift field of 363 ± 14 V / cm ( 258 ± 13 V / cm ), when compared to simulations tuned to reproduce the correct β -decay response. In dark matter searches, use of a background model that neglects this effect leads to overcoverage (higher limits) for background-only multi-kiloton-year exposures, but at a level much less than the 1 - σ experiment-to-experiment variation of the 90% C.L. upper limit on the interaction rate of a 50 GeV / c 2 dark matter particle.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Darshan for HEP applications

Modern HEP workflows must manage increasingly large and complex data collections. HPC facilities may be employed to help meet these workflows’ growing data processing needs. However, a better understanding of the I/O patterns and underlying bottlenecks of these workflows is necessary to meet the performance expectations of HPC systems.Darshan is a lightweight I/O characterization tool that captures concise views of HPC application I/O behavior. It intercepts application I/O calls at runtime, records file access statistics for each process, and generates log files detailing application I/O access patterns.Typical HEP workflows include event generation, detector simulation, event reconstruction, and subsequent analysis stages. A study of the I/O behavior of the ATLAS simulation and filtering stage, and the CMS simulation workflow using Darshan is presented, including insights into the I/O operations and data access size.

Wang, Rui↗