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At least 451 records · Page 25

Measurement of high-mass $t\bar{t}\ell ^{+}\ell ^{-}$ production and lepton flavour universality-inspired effective field theory interpretations at $\sqrt{s}=13$ $\text {T}\text {e}\hspace{-1.00006pt}\text {V}$ with the ATLAS detector

Measurements of $t\bar{t}\ell ^{+}\ell ^{-}$ production in the region of high dilepton invariant mass with effective field theory (EFT) interpretations are presented. They are performed using final states with three isolated leptons (electrons or muons) and are based on $\sqrt{s} = 13$ TeV proton–proton collision data with an integrated luminosity of $140\,\textrm{fb}^{-1}$, recorded from 2015 to 2018 with the ATLAS detector at the Large Hadron Collider. Measurements of the $t\bar{t}\ell ^{+}\ell ^{-}$ signal strength and cross-section upper-limits are performed inclusively in lepton flavour and separately for electrons and muons. The study also aims to probe anomalous four-fermion interactions including to test for possible lepton flavor universality violation. No significant deviations from the Standard Model predictions are observed and the measurements are interpreted through the EFT formalism to provide new constraints on the relevant operators.

Aad, G. [CNRS/IN2P3] (ORCID:0000000266654934)↗

Search for electroweak production of vector-like leptons in $\tau$-lepton and b-jet final states in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for pair-production of vector-like leptons is presented, considering their decays into a third-generation Standard Model (SM) quark and a vector leptoquark ( U 1 ) as predicted by an ultraviolet-complete extension of the SM, referred to as the ‘4321’ model. Given the assumed decay of U 1 into third-generation SM fermions, the final state can contain multiple τ-leptons and b-quarks. This search is based on a dataset of pp collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of up to $140~\textrm{fb}^{-1}$. No significant excess above the SM background prediction is observed, and 95% confidence level limits on the cross-section times branching ratio are derived as a function of the vector-like lepton mass. A lower observed (expected) limit of 910 GeV (970 GeV) is set on the vector-like lepton mass. Additionally, the results are interpreted for a supersymmetric model with an R-parity violating coupling to the third-generation quarks and leptons. Lower observed (expected) limits are obtained on the higgsino mass at 880 GeV (940 GeV) and on the wino mass at 1170 GeV (1170 GeV).

Aad, G. [CPPM, Aix-Marseille Université, CNRS/IN2P↗

Measurements of Higgs boson production via gluon–gluon fusion and vector-boson fusion using $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decays in pp collisions with the ATLAS detector and their effective field theory interpretations

Higgs boson production cross-sections via gluon–gluon fusion and vector-boson fusion in proton–proton collisions are measured in the $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decay channel. The Large Hadron Collider delivered proton–proton collisions at a centre-of-mass energy of 13 TeV between 2015 and 2018, which were recorded by the ATLAS detector, corresponding to an integrated luminosity of $140\,\text {fb}^{-1}.$ The total cross-sections for Higgs boson production by gluon–gluon fusion and vector-boson fusion times the $H\rightarrow WW^*$ branching ratio are measured to be $12.4^{+1.3}_{-1.2}\,\text {pb}$ and $0.79^{+0.18}_{-0.16}\,\text {pb},$ respectively, in agreement with the Standard Model predictions. Higgs boson production is further characterised through measurements of Simplified Template Cross-Sections in a total of fifteen kinematic fiducial regions. A new scheme of kinematic fiducial regions has been introduced to enhance the sensitivity to CP-violating effects in Higgs boson interactions. Both schemes are used to constrain CP-even and CP-odd dimension-six operators in the Standard Model effective field theory.

Aad, G. [CPPM, Aix-Marseille Université, CNRS/IN2P↗

Search for squarks and gluinos in pp collisions at $\sqrt{s} = 13$ TeV and 13.6 TeV in events with $\tau$-leptons, jets and missing transverse momentum using the ATLAS detector

A search for R-parity-conserving supersymmetry in events with large missing transverse momentum, jets and at least one hadronically decaying $\tau$-lepton is presented. Both gluino and squark pair production are considered, with the cascade decay of each gluino or squark producing either a $\tau$-slepton or a $\tau$-sneutrino. Three channels are examined, requiring either exactly one hadronically decaying $\tau$-lepton and no other leptons, exactly one hadronically decaying $\tau$-lepton and at least one other lepton, or two or more hadronically decaying $\tau$-leptons. Analyses in the three channels are optimised independently and combined statistically. Two separate analysis strategies, either a cut-and-count or machine-learning approach, are used. The search uses 140 and 51.8 of pp collision data recorded by the ATLAS detector at the Large Hadron Collider during 2015–2018 at TeV and 2022–2023 at TeV, respectively. Gluino masses below 2.25 TeV and squark masses up to 1.7 TeV are excluded

Aad, G. [CNRS/IN2P3] (ORCID:0000000266654934)↗

The environmental impact, carbon emissions and sustainability of computing in the ATLAS experiment

ATLAS, a general-purpose experiment at the Large Hadron Collider (LHC), makes use of a large internationally-distributed computing infrastructure, including over 10 6 TB of managed data on disk and tape and almost one million simultaneously running CPU cores. Upgrades for the High-Luminosity LHC (HL-LHC) will increase the required computing resources by a factor of 3–4 by the beginning of the 2030s, and by an order of magnitude before the conclusion of data taking at the beginning of the 2040s. These resources are spread over around 100 computing sites worldwide. Efforts are underway within the experiment to evaluate and mitigate various aspects of the environmental impact of the sites, with the additional long-term goal of making recommendations to the sites that will significantly reduce the total expected environmental impact in the HL-LHC era. These efforts take several forms: building awareness in the experiment community, adjusting aspects of the computing policy, and modifications of data center configurations, either in ways that take advantage of particular features of ATLAS workloads or in generic ways that reduce the environmental impact of the computing resources. This paper describes the ongoing investigations and approaches that have already provided useful and actionable outcomes.

Aad, G. [CNRS/IN2P3] (ORCID:0000000266654934)↗

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗

ACCERT

The main function of ACCERT (The Algorithm for the Capital Cost Estimation of Reactor Technologies) is to provide an item-by-item estimate of the cost of a facility, at present a nuclear reactor complex, primarily nuclear power stations. The core of ACCERT is the large number of algorithms that have been developed and will continue to be developed. ACCERT is also a general methodology for identifying and organizing the individual items that are estimated using the ACCERT algorithms. ACCERT also summarize status and results; to save results and pull information from previous analyses; and to provide an interactive dynamic graphical user interface for a wide range of functions and visualizations.

Zhou, Jia [Argonne National Laboratory (ANL), Argo↗

ADVANCED REACTOR ARCHETYPE LIBRARY

SF-25-142 An archetype library for Cyclus that can model more complex reactor operations.

Bachmann, Amanda [Argonne National Laboratory (ANL↗

SCALE 6.2.4 Validation: Radiation Shielding

For safe and reliable use of computer codes by the community, accuracy must be clearly evaluated. In particular, the nuclear reactor engineering and licensing field needs accurate tools for radiation shielding modeling. Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) is one such tool, with built-in variance reduction methods distributed within the SCALE code, and its validity is demonstrated in this report for the released version 6.2.4. Representative benchmarks corresponding to shielding analysis are selected for the validation study. Typical experimental results analyzed from those benchmarks include neutron fluxes, detector count rates, detector energy response functions, neutron and gamma doses, foil neutron activation rates and activities, neutron leakage fluxes, and skyshine dose rates. Thousands of points of comparison between experiment and calculation are presented in this work. Other than rare outliers typically explained by either a lack of information or large uncertainties in the experiment conditions, material, or dimensions, MAVRIC agrees well with the experiment results. MAVRIC is also compared to Monte Carlo N-Particle (MCNP) calculations when available, and both codes generally produce good agreements within estimated uncertainties. The selected benchmarks are obtained from reliable sources such as the International Criticality Safety Benchmark Evaluation Project Handbook (ICSBEP Handbook), the Shielding Integral Benchmark Archive & Database (SINBAD), and other shielding validation work found in the literature. Additional datapoints and benchmarks will be added to future versions of this report to incrementally expand the shielding validation suite incrementally.

61 RADIATION PROTECTION AND DOSIMETRY↗

Simulating a Reactor with PID Temperature Control

A Simulation of a Reactor, Built Using CrowPis, which are simple and accessible programmable systems of various electronics, as ground stations and a Box containing heaters as the reactor. The goal of this project is to learn various skills and to demonstrate the feasibility of a simulated reactor, utilizing a PID control and wireless connectivity.

42 - ENGINEERING↗

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Photographic Mitigation Documentation Related to the Engine Assembly and Disassembly Facility, Area 25, Nevada National Security Site, Nye County, Nevada

This letter report provides documentation in partial fulfillment of the mitigation of adverse effects to the Engine Maintenance Assembly and Disassembly (E-MAD) facility, a major component of the Nuclear Rocket Development Station (NRDS) Historic District located in Area 25 of the Nevada National Security Site (NNSS). Construction of the E-MAD facility began in 1962 for the purpose of disassembling and maintaining nuclear-powered rocket engines. Once the building was complete in 1967, the E-MAD facility remained in continuous operation until the nuclear rocket program was terminated in 1973. The mothballed facility was repurposed in 1977 for spent nuclear fuel handling and packaging activities. By the mid-1980s, all activities at the E-MAD facility had ceased (Reno et al. 2019). This submission is intended to comply with Stipulation III.D.1 of the Memorandum of Agreement DE-GM58-20NA25534 between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Corrective Action Activities and Demolition of the Engine Maintenance Assembly and Disassembly Facility and the Test Cell C Historic District, Major Components of the Nuclear Rocket Development Station Historic District Located in Area 25 at the Nevada National Security Site Nye County (hereafter referred to as the MOA). Stipulation III.D.1 states the U.S. Department of Energy (DOE) will submit the existing supplementary collection of the large-format, black-and-white photographic prints taken during the 1996 Historic American Engineering Record (HAER) documentation of the E-MAD facility to the Nuclear Testing Archive (NTA), located on the second floor of the Rogers Building at Desert Research Institute (DRI) in Las Vegas, Nevada.

54 ENVIRONMENTAL SCIENCES↗