Sediment and biota trace element distribution in streams disturbed by upland industrial activity: Trace element accumulation in sediment and invertebrates
Not provided.
Environmental Sciences & Ecology↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Improvements of Nuclear Data Evaluations for Lead Isotopes in Support of Next Generation Lead-Cooled Fast Systems
The neutron evaluation of the isotopes that comprise natural lead were undertaken as a part of DOE-NEUP Project #19-16739. The goal of the project was to update the neutron cross sections to account for new differential measurements and incorporate the most up-to-date physics. Shortcomings in the lead cross sections was made known by several independent reports. The work performed here repeated the simulation of all the “benchmark” validation systems and concluded that the major issue is the scattering cross sections in the major lead isotopes above 100 keV. Re-evaluation of 206,207,208 Pb included both the resolved resonance region and fast region evaluations of the cross sections. Combined these regions cover energies from thermal to 20 MeV. The most drastic improvement is the resolved resonance region evaluation of 208 Pb which is now extended from 1.0 to 1.5 MeV. Parameterization of these resonances in the R-matrix provides a superior reconstruction of not only the experimental cross section but also the scattering distributions via the Blatt-Biedenharn formalism. Fast region evaluations of the three major isotopes were done to include new inelastic experimental data from the neutron Time-of-Flight facility at CERN. The culmination of all the changes to the cross section is a drastic improvement in the scattering kernel as shown in Rensselaer Polytechnic Institute (RPI) Quasi-Differential scattering measurements and improved prediction of keff for fast integral experiments. Alongside the new cross sections, new nuclear data covariance (uncertainties) have been computed and are included in the evaluation. Little is changed in the magnitude of the uncertainties but the correlations within the covariance display non-trivial changes. The new evaluations of 206,207,208 Pb have been submitted to the National Nuclear Data Center to be included in the ENDF/B-VIII.1 library. While the cross sections have been updated extensively, knowledge and modeling of the cross sections between 1.0 and 3.0 MeV for the isotopes remain a challenge. Most notably is the double differential elastic cross section for 208 Pb and 206 Pb. New quasi-differential measurements for pure samples of these two nuclei would go a long way in reducing compensating errors in the evaluations. Qualitatively, the project has produced a prosperous collaboration between the nuclear data group at RPI with staff scientists at Brookhaven National Laboratory, Naval Nuclear Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories. Quantitatively this is reflected in seven conference presentations, at least one journal submission, and one doctoral thesis.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data
Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.
42 ENGINEERING↗
Searches for additional Higgs bosons and for vector leptoquarks in $ττ$ final states in proton-proton collisions at $\sqrt{s}$ = 13 TeV
Three searches are presented for signatures of physics beyond the standard model (SM) in $ττ$ final states in proton-proton collisions at the LHC, using a data sample collected with the CMS detector at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb -1 . Upper limits at 95% confidence level (CL) are set on the products of the branching fraction for the decay into $τ$ leptons and the cross sections for the production of a new boson $\phi$, in addition to the H(125) boson, via gluon fusion (gg$\phi$) or in association with b quarks, ranging from $\mathcal{O}$(10 pb) for a mass of 60 GeV to 0.3 fb for a mass of 3.5 TeV each. The data reveal two excesses for gg$\phi$ production with local $p$-values equivalent to about three standard deviations at m $\phi$ = 0.1 and 1.2 TeV. In a search for $t$-channel exchange of a vector leptoquark U 1 , 95% CL upper limits are set on the dimensionless U 1 leptoquark coupling to quarks and $τ$ leptons ranging from 1 for a mass of 1 TeV to 6 for a mass of 5 TeV, depending on the scenario. In the interpretations of the $M^{125}_{h}$ and $M^{125}_{h,EFT}$ minimal supersymmetric SM benchmark scenarios, additional Higgs bosons with masses below 350 GeV are excluded at 95% CL.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets
The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.
Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗
SU-G-TeP1-07: Investigation of RapidPlan Based Plan Quality for Breast IMRTSimultaneously Integrated Boost
Purpose: The aim of this study is to investigate the feasibility of using RapidPlan for breast cancer radiotherapy and to evaluate its performance for planners with different planning experiences. Methods: A training database was collected with 80 expert plan datasets from patients previously received left breast conserving surgery and IMRT-simultaneously integrated boost radiotherapy. The models were created on the RapidPlan. Five patients from the training database and 5 external patients were used for internal and external validation, respectively. Three planners with different planning experiences (beginner, junior, senior) designed manual and RapidPlan based plans for additional ten patients. The plan qualities were compared with manual and RapidPlan based ones. Results: For the internal and external validations, there were no significant dose differences on target coverage for plans from RapidPlan and manual. Also, no difference was found in the mean doses to contralateral breast and lung. The RapidPlan improved the heart (V5, V10, V20, V30, and mead dose) and ipsilateral lung (V5, V10, V20, V30, and mean dose) sparing for the beginner and junior planners. Compare to the plans from senior planner, 6 out of 16 clinically checked parameters were improved in RapidPlan, and the left parameters were similar. Conclusion: It is feasible to generate clinical acceptable plans using RapidPlan for breast cancer radiotherapy. The RapidPlan helps to systematically improve the quality of IMRT plans against the benchmark of clinically accepted plans. The RapidPlan shows promise for homogenizing plan quality by transferring planning expertise from more experienced to less experienced planners.
60 APPLIED LIFE SCIENCES↗
HIPPO – A Software Platform for Electricity Market Research and Development
The goal of this project is to provide Regional transmission organizations (RTOs) and independent system operators (ISOs) a market design and prototyping software, High-Performance Power-Grid Optimization (HIPPO), that they can evaluate electricity market design options, calculate market planning strategies and operational performance. With the high standards and strict reliability requirements for operating power systems, impacts of new technologies need to be fully investigated prior to any consideration for adoption. A market design and prototyping software tool which can be used to prototype electricity market design options, to calculate market planning strategies and operational performance with high precision, and to investigate the impacts for integrating future power grid technologies will be valuable to RTOs/ISOs who operate power systems, to vendors like GE and ABB who provide the market solvers, and to market participants and researchers who are actively doing market research. HIPPO is a such tool that can be used to improve the current market operations and provide capabilities for rigorous forward-looking design and prototyping of next-generation energy markets. HIPPO has a high-resolution model for the day-ahead SCUC, which was validated with MISO and GE-Grid Solutions. HIPPO is built with parallel and distributed computing capabilities and can be executed in both multi-thread and high-performance computing (HPC) settings. This capability provides fast solution speed necessary to handle the larger and more complex SCUC problems of real-world cases and the potentially growing size and complexity of future scenarios. In addition, HIPPO has a concurrent optimizer (CO) which manages multiple algorithm executions simultaneously and leverages the advantages from different algorithms. This structure provides flexibility to better benchmark competing approaches. Highly accurate market model, fast solution technologies and flexible model and algorithm control are the features which will make HIPPO an extensible platform for developing and testing multiple approaches to meet a wide range of future market needs.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Simulation of discrete cracks driven by nearly incompressible fluid via 2D combined finite-discrete element method
Here, we propose a novel hydraulic solver in order to simulate key mechanisms that control fluid-driven cracks in the framework of the combined finite-discrete element method (FDEM). The main innovative aspect of the present work is the independence of the fluid's critical time step size with the fracture opening. This advantage is extremely important because it means that very fine meshes can be used around areas of interest, such as boreholes, without penalizing the computational cost as fractures propagate (ie, open) and the fluid flows through them. This is a great advantage over other recently introduced approaches that exhibit a dependency of the time step in the form of Δt crit ∝ (l/a) 2 where l is the element size and a is the fracture aperture. This paper presents a series of benchmark cases for the proposed solver. The rationale adopted by the authors was to benchmark and validate the implementation of the hydraulic solver in an incremental fashion, starting from the simplest cases and building in complexity. The calculations shown in this work clearly demonstrate that the proposed approach is able to reproduce analytical results for fluid flow through a single crack. The results presented in this paper also demonstrate that the new approach is robust enough to deal with complex fracture patterns and complex geometries; the obtained fluid-driven fracture patterns in the vicinity of a borehole certainly stand to the scrutiny of human visual perception.
58 GEOSCIENCES↗
PRISMA: PARALLEL REFINEMENT AND INTEGRATION SYSTEM FOR MULTI-AZIMUTHAL ANALYSIS
The Parallel Refinement and Integration System for Multi-azimuthal Analysis (PRISMA, version 1.1.0) is a Python application for processing X-ray diffraction (XRD) image data. PRISMA wraps GSAS-II to perform azimuthally-binned peak refinement, computes per-frame strain and d-spacing from those fits, and provides three PyQt5 graphical interfaces: (1) a Recipe Builder for selecting GSAS-II control (.imctrl) files, optional mask (.immask) files or threshold-ased masking, reference and experiment image sets, peaks, zimuthal range and bin size, and an optional ceria-based auto-calibration; (2) a Batch Processor that uses Dask on local workstations and pure MPI (mpi4py.futures.MPICommExecutor) on HPC to distribute GSAS-II refinement across cores or compute nodes and write results to a 4-dimensional (peaks x frames x azimuths x measurements) Zarr dataset; and (3) a Data Analyzer that renders heatmaps of fit parameters, strain, frame-to-frame deltas, and percent-change-vs-reference, and exports user-defined subsections to CSV or Excel. The peak-refinement algorithm is deterministic. Benchmark on ALCF Crux: a 20,000-image set, single-peak fit in frame mode with 44 azimuthal bins on 128 nodes x 128 workers, 48 seconds total wall time.
Lorenzo Martin, Maria De La Cinta [Argonne Nationa↗
A New Model to Determine Installed System Cost and LCOE for ARPA-E's MOSAIC Micro-Concentrator PV Program: Preprint
The US Department of Energy's Advanced Research Projects Agency-Energy (ARPA-E) started a three-year program in December 2015 called Microscale Optimized Solar-cell Arrays with Integrated Concentration (MOSAIC). It consists of 11 teams from across the United States. Its goal is to have project teams leverage expertise from conventional flat-plate photovoltaic (PV) system configuration and concentrated photovoltaic (CPV) module technology to produce a new class of modules for residential, commercial, and utility-scale markets. The intent is to increase performance and facilitate cost-effective deployment of solar power systems across a wide range of geographical locations in part by concentrating both direct and diffuse components of the sun's irradiance. This paper describes a collaboration of ARPA-E and the National Renewable Energy Laboratory (NREL) to develop a bottom-up system cost model for MOSAIC research teams. The model includes an estimate of regional, all-in, CPV installed cost, and levelized cost of energy (LCOE) by using customized inputs parameters, such as module efficiency, cost, and physical dimensions. This techno-economic cost model can help researchers analyze tradeoffs among different design parameters and then prioritize their distinct research opportunities. Moreover, it establishes a standardized cost benchmarking for MOSAIC micro-CPV systems and a normalized comparison against traditional CPV and today's highly competitive flat-plate PV systems. The model is a valuable design tool within the program, helping validate the various technical approaches and compare future deployed system competitiveness versus incumbent technologies in the PV industry.
14 SOLAR ENERGY↗
$\mathrm{SageNet}$: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Accurate modeling of the inflationary gravitational waves (GWs) requires time-consuming, iterative numerical integrations of differential equations to take into account their backreaction on the expansion history. To improve computational efficiency while preserving accuracy, we present the Stiff-amplified Gravitational-wave Emulator Network (SageNet), a deep learning framework designed to replace conventional numerical solvers (code available at https://github.com/YifangLuo/SageNet). SageNet employs a long short-term memory architecture to emulate the present-day energy density spectrum of the inflationary GWs with possible stiff amplification, Ω GW (f). Trained on a data set of 25,689 numerically generated solutions, SageNet allows accurate reconstructions of Ω GW (f) and generalizes well to a wide range of cosmological parameters; 90.9% of the test emulations with randomly distributed parameters exhibit errors of under 4%. In addition, SageNet demonstrates its ability to learn and reproduce the artificial, adaptive sampling patterns in numerical calculations, which implement denser sampling of frequencies around changes in spectral indices in Ω GW (f). The dual capability of learning both physical and artificial features of the numerical GW spectra establishes SageNet as a robust alternative to exact numerical methods. Finally, our benchmark tests show that SageNet reduces the computation time from tens of seconds to milliseconds, achieving a speedup of ∼10 4 times over standard CPU-based numerical solvers with the potential for further acceleration on GPU hardware. These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. In a broad sense, the SageNet framework offers a fast, accurate, and generalizable solution to modeling cosmological observables whose theoretical predictions demand costly differential equation solvers.
Astronomy data modeling↗
Deep Charging Evaluation of Satellite Power and Communication System Components
Deep charging, in contrast to surface charging, focuses on electron penetration deep into insulating materials applied over conductors. A classic example of this scenario is an insulated wire. Deep charging can pose a threat to material integrity, and to sensitive electronics, when it gives rise to an electrostatic discharge or arc. With the advent of Electric Orbit Raising, which requires spiraling through Earth's radiation belts, satellites are subjected to high energy electron environments which they normally would not encounter. Beyond Earth orbit, missions to Jupiter and Saturn face deep charging concerns due to the high energy radiation environments. While predictions can be made about charging in insulating materials, it is difficult to extend those predictions to complicated geometries, such as the case of an insulating coating around a small wire, or a non-uniform silicone grouting on a bus bar. Therefore, to conclusively determine the susceptibility of a system to arcs from deep charging, experimental investigations must be carried out. This paper will describe the evaluation carried out by NASA's Marshall Space Flight Center on subscale flight-like samples developed by Space Systems/Loral, LLC. Specifically, deep charging evaluations of solar array wire coupons, a photovoltaic cell coupon, and a coaxial microwave transmission cable, will be discussed. The results of each evaluation will be benchmarked against control sample tests, as well as typical power system levels, to show no significant deep charging threat existed for this set of samples under the conditions tested.
Schneider, T. A.↗
A Validation Study of Pin Heat Transfer for MOX Fuel Based on the IFA-597 Experiments
Abstract The IFA-597 (Integrated Fuel Assessment) experiments from the International Fuel Performance Experiments (IFPE) database were designed to study the thermal behavior of mixed oxide (MOX) fuel and the effects of an annulus on fission gas release in light-water-reactor fuel. An evaluation of nuclear fuel pin heat transfer in the FRAPCON-3.4 and Exnihilo codes for MOX fuel systems was performed, with a focus on the first 20 time steps ( 6 GWd/MT(iHM)) for explicit comparison between the codes. In addition, sensitivity studies were performed to evaluate the effect of the radial power shape and approximations to the geometry to account for the thermocouple hole, dish, and chamfer. The analysis demonstrated relative agreement for both solid (rod 1) and annular (rod 2) fuel in the experiment, demonstrating the accuracy of the codes and their underlying material models for MOX fuel, while also revealing a small energy loss artifact in how gap conductance is currently handled in Exnihilo for chamfered fuel pellets. The within-pellet power shape was shown to significantly impact the predicted centerline temperatures. This has provided an initial benchmarking of the pin heat transfer capability of Exnihilo for MOX fuel with respect to a well-validated nuclear fuel performance code.
Phillippe, Aaron M↗
Developing Low Noise, Rad-hard Detectors for Parity Violating Experiments
As parity-violating electron scattering (PVeS) experiments continue to push the frontiers of precision electro-weak asymmetry measurements, the demands on the experimental techniques and apparatus are also pushed. In particular, the need for higher resolution and radiation-hardness of the main integrating detectors has increased over the successive generations of PVeS experiments. The demand for precise measurement of GHz event rates has pushed the field toward the use of thin quartz Cerenkov light based detectors. We have been designing and testing such thin quartz detectors specifically for the upcoming experiments at Jefferson Lab, PREX-II and CREX, but this work also greatly influences the detector development for several future experiments including MOLLER at Jefferson Lab. These are all PVeS experiments that will use the new thin quartz Cerenkov detector design concept for their main asymmetry measurements (as well as for beam monitoring). The new design concept gives not only significant performance improvements compared to its predecessor from PREX-I, but also we have now thoroughly characterized its operational design and performance using a combination of test-beam data and detailed particle and optical Monte Carlo Geant4 simulations. These activities have culminated in the development and implementation of a "bench-marked" Monte Carlo package, QSIM, which constitutes a powerful design tool for present and future PVeS quartz detectors. The benchmarked simulation can replicate real photoelectron distributions (RMS and Mean) from testbeam data with ~5% precision – limited mainly by the systematic uncertainty of the PMT gain measurements.
Villarreal, Carlos Bula Villarreal↗
Calculating Control Rod Differential Worth Using Adjoint-Weighted Method
Recently, there are more and more research on using Monte Carlo method to calculate reactor important parameters. Control rod worth is one of the important parameters as it can determine the critical control rod position. There are two presentations of the control rod worth for utilization purpose, integral and differential. The former is the total reactivity change, while the latter is the reactivity change caused by per unit movement. In Monte Carlo calculation, differential control rod worth of a particular position is estimated by finite difference of reactivity between a small gap divided by gap distance. Though easy to implemented, the problem of this approach lies in that too large gap will enlarge error between 'differential' and 'difference', while too small gap will be disturbed by error caused by random fluctuation. Monte Carlo perturbation theory has been used to calculate the k{sub eff} sensitivity to certain parameters for a long time. By calculating the differential coefficient along with the k{sub eff}, this method is quite time-consuming and relatively accurate compared to finite difference method. Nevertheless, most of perturbation research focus on the perturbation of nuclide density or nuclear data. For geometrical perturbation, limited research was done before. Takahashi estimated the k{sub eff} sensitivity to reflector movement of pulsed fast reactor. MCNP6 used adjoint-weighted method for Godiva, Zeus and uranium oxyfluoride solution container benchmarks. This paper tries to apply the perturbation method to the determination of control rod differential worth. In this paper, based on RMC, a continuous-energy Reactor Monte Carlo transport code, Iterated Fission Probability method (IFP) is researched to calculate control rod differential worth on assembly level. IFP was originally developed by Hurwitz, and has been adopted by most of Monte Carlo code to compute adjoint-weighted parameters. This paper is organized with four parts. The first is introduction. Adjoint-weighted method is introduced in the second part. Problem 4 of benchmark from CASL is built to verify the method. Conclusion is given in final part.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
SU-E-T-512: Electromagnetic Simulations of the Dielectric Wall Accelerator
Purpose: To characterize and parametrically study the key components of a dielectric wall accelerator through electromagnetic modeling and particle tracking. Methods: Electromagnetic and particle tracking simulations were performed using a commercial code (CST Microwave Studio, CST Inc.) utilizing the finite integration technique. A dielectric wall accelerator consists of a series of stacked transmission lines sequentially fired in synchrony with an ion pulse. Numerous properties of the stacked transmission lines, including geometric, material, and electronic properties, were analyzed and varied in order to assess their impact on the transverse and axial electric fields. Additionally, stacks of transmission lines were simulated in order to quantify the parasitic effect observed in closely packed lines. Particle tracking simulations using the particle-in-cell method were performed on the various stacks to determine the impact of the above properties on the resultant phase space of the ions. Results: Examination of the simulation results show that novel geometries can shape the accelerating pulse in order to reduce the energy spread and increase the average energy of accelerated ions. Parasitic effects were quantified for various geometries and found to vary with distance from the end of the transmission line and along the beam axis. An optimal arrival time of an ion pulse relative to the triggering of the transmission lines for a given geometry was determined through parametric study. Benchmark simulations of single transmission lines agree well with published experimental results. Conclusion: This work characterized the behavior of the transmission lines used in a dielectric wall accelerator and used this information to improve them in novel ways. Utilizing novel geometries, we were able to improve the accelerating gradient and phase space of the accelerated particle bunch. Through simulation, we were able to discover and optimize design issues with the device at low cost. Funding: Morgridge Institute for Research, Madison WI; Conflict of Interest: Dr. Mackie is an investor and board member at CPAC, a company developing compact accelerator designs similar to those discussed in this work, but designs discussed are not directed by CPAC. Funding: Morgridge Institute for Research, Madison WI; Conflict of Interest: Dr. Mackie is an investor and board member at CPAC, a company developing compact accelerator designs similar to those discussed in this work, but designs discussed are not directed by CPAC.
43 PARTICLE ACCELERATORS↗
Search for a heavy resonance decaying to a top quark and a vector-like top quark in the lepton + jets final state in pp collisions at $\sqrt{s} = 13\,\text {TeV} $
Here a search is presented for a heavy spin-1 resonance $\mathrm {Z}'$ decaying to a top quark and a vector-like top quark partner $\text {T} $ in the lepton + jets final state. The search is performed using a data set of $\mathrm {p}$ $\mathrm {p}$ collisions at a centre-of-mass energy of 13 $\,\text {TeV}$ corresponding to an integrated luminosity of $35.9{\,\text {fb}^{-1}} $ as recorded by the CMS experiment at the CERN LHC in the year 2016. The analysis is optimised for final states arising from the $\text {T} $ decay modes to a top quark and a Higgs or $\mathrm {Z}$ boson ( $\text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}$ ). The event selection makes use of resolved and merged top quark decay products, as well as decays of boosted Higgs bosons and $\mathrm {Z}$ and $\mathrm {W}$ bosons using jet substructure techniques. No significant deviation from the standard model background expectation is observed. Exclusion limits on the product of the cross section and branching fraction for $\mathrm {Z}'\rightarrow \mathrm {t}\text {T}, \text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}, \mathrm {W}\mathrm {b}$ are presented for various combinations of the $\mathrm {Z}'$ resonance mass and the vector-like $\text {T} $ quark mass. These results represent the most stringent limits to date for the decay mode $\mathrm {Z}'\rightarrow \mathrm {t}\text {T} \rightarrow \mathrm {t}\mathrm {H} \mathrm {t}$ . In a benchmark model with extra dimensions, invoking a heavy spin-1 resonance $\mathrm {G}^* $ , masses of the $\mathrm {G}^* $ between 1.5 and 2.3 $\,\text {TeV}$ and between 2.0 and 2.4 $\,\text {TeV}$ are excluded for $\text {T} $ masses of 1.2 and 1.5 $\,\text {TeV}$ , respectively.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Thermal Management for FPGA Nodes in HPC Systems
The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.
97 MATHEMATICS AND COMPUTING↗