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At least 1,477 records · Page 82

Logic in Memory Emulator

Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects. Uses: Logging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software simulation. Emulate acceleration hardware co-located with the memory subsystem. Features: Capture and log external memory accesses to a separate off-chip memory device without affecting application execution. Memory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis. Configure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories. Specify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device. Applications can be run under Linux or in bare metal mode on the ARM cores.

Jain, AbhishekK↗

The Mu2e straw tracker detector status and prototype results

The Mu2e experiment will search for charge-lepton flavor violating (CLFV) muon to electron conversion. It aims to achieve a four-orders of magnitude improvement in sensitivity over previous experiments, allowing it to probe new physics at mass scales up to 10 4 TeV . A precision momentum measurement is needed to resolve the monoenergetic electron that is the signal of CLFV conversion from muon decay-in-orbit backgrounds. Here, this is achieved in Mu2e using a low-mass cylindrical straw tracker operated in vacuum, consisting of 21,000 thin-wall mylar straws held at tension. The Mu2e tracker is now in production and will be completed during 2025. We will discuss the design and status of the experiment and the tracker detector, and show results from data taken with the first tracker module.

Gaseous detector↗

Activation of Insulation in Low Power Nuclear Experiments

Nuclear experiments aim to test new designs, procedures, and materials. Similar to conventional power reactors, potential sources of worker exposure to radiation is a primary concern. One such concern is the insulation materials that are used in or near the reactor, which can often create dust when being handled. If this material receives a substantial neutron dose, then it can become activated, which can pose a health risk if inhaled or ingested. This analysis looked at the activation of, and conservative dose estimates from, industrial grade insulations that may be used in a reactor experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

System design and prototyping for the CMS Level-1 Trigger at the High-Luminosity LHC

For the High-Luminosity Large Hadron Collider, the trigger and data acquisition system of the CMS experiment will be entirely replaced. Novel design choices have been explored, including ATCA prototyping platforms with SoC controllers and newly available interconnect technologies with serial optical links with data rates up to 28 Gb/s. Trigger analyses will be performed through sophisticated algorithms, including widespread use of Machine Learning, in large FPGAs, such as the Xilinx Ultrascale family. The system will process over 50 Tb/s of detector data with an event rate of 750 kHz. Here, we describe system design and prototyping and review trigger algorithm exemplars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report

Constructing accurate statistical models of critical system responses typically requires an enormous amount of data from physical experiments or numerical simulations. Unfortunately, data generation is often expensive and time consuming. To streamline the data generation process, optimal experimental design determines the 'best' allocation of experiments with respect to a criterion that measures the ability to estimate some important aspect of an assumed statistical model. While optimal design has a vast literature, few researchers have developed design paradigms targeting tail statistics, such as quantiles. In this project, we tailored and extended traditional design paradigms to target distribution tails. Our approach included (i) the development of new optimality criteria to shape the distribution of prediction variances, (ii) the development of novel risk-adapted surrogate models that provably overestimate certain statistics including the probability of exceeding a threshold, and (iii) the asymptotic analysis of regression approaches that target tail statistics such as superquantile regression. To accompany our theoretical contributions, we released implementations of our methods for surrogate modeling and design of experiments in two complementary open source software packages, the ROL/OED Toolkit and PyApprox.

97 MATHEMATICS AND COMPUTING↗

Lessons Learned from Ecosystem-Scale Experimental Field Studies (Workshop Report)

Efforts to understand and predict ecosystem responses to environmental change require long-term, large-scale, spatially representative experiments and observations that capture natural variability, test predictive models, and generate transferable knowledge. Such studies are indispensable for unraveling the complexities of terrestrial ecosystems and their responses to disturbances and evolving environmental conditions, while generating the data necessary for developing mechanistic models and predictive tools that inform decision-making processes. Having a rich history of designing and executing large-scale ecosystem experiments, the U.S. Department of Energy’s Environmental System Science program convened a workshop in January 2025 that brought together leaders in the field to distill critical lessons from decades of experience in large-scale experiments. The workshop aimed to (1) provide an ecosystem experiment primer for best practices, thus ensuring a high scientific return on investment for funding agencies, and (2) offer a robust framework for the design and management of future research initiatives. This report synthesizes insights and experiences from workshop participants and is structured to capture the entire research life cycle, from goal setting and design to operations, adaptive management, team dynamics, collaborations, and the often overlooked aspect of decommissioning. By synthesizing decision-making and lessons learned across diverse research approaches, the report aims to provide a template of essential factors to consider when designing successful long-term, large-scale ecosystem experiments.

54 ENVIRONMENTAL SCIENCES↗

A Fast Radio Burst Backend for the Tianlai Dish Pathfinder Array

The Tianlai Dish Pathfinder Array is a radio interferometer array consisting of 16 six-meter dish antennas. The original digital backend integration time is at the seconds level, designed for H I intensity mapping experiment. A new digital backend with millisecond response is added to enable it to search for fast radio burst during its observations. The design and calibration of this backend, and the real time search pipeline for it are described in this paper. It is capable of forming 16 digital beams for each linear polarization, covering an area of 19.6 square degrees. The search pipeline is capable of searching for, recording and classifying FRBs automatically in real time. Finally, in commissioning, we succeeded in capturing the signal pulses from the pulsars PSR B0329+54 and B2021+51.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A measurement of absolute efficiency of the ARAPUCA photon detector in liquid argon

In the Fall of 2017, two photon detector designs for the Deep Underground Neutrino Experiment (DUNE) Far Detector were installed and tested in the TallBo liquid argon (LAr) cryostat at the Proton Assembly (PAB) facility, Fermilab. The designs include two light bars developed at Indiana University and a photon detector based on the ARAPUCA light trap engineered by Colorado State University and Fermilab. The performance of these devices is determined by analyzing 8 weeks of cosmic ray data. The current paper focuses solely on the ARAPUCA device as the performance of the light bars will be reported separately. The article briefly describes the ARAPUCA concept, the TallBo setup, and focuses on data analysis and results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

HSLA-100 Forging Contract Vendor Post-Award Meeting [Slides]

LANL utilizes thick-walled, spherical vessels for numerous basic science, materials, and system performance experiments. These pressure retaining vessels are designed and fabricated to meet the intent of ASM E B&PV Section VIII, Division 3 and Code Case 2564. LANL has successfully contracted past production of component parts (nozzle and cover forgings, plate production and head forming) and overall vessel construction (welding, inspection, hydrostatic testing) utilizing HSLA-100 steel. As current vessel inventories approach design lifetimes, we are once again embarking upon a series of fabrication contracts to produce replacement components and vessel assemblies to ensure continued experiment cadence at LANL. We anticipate releasing additional future vessel production contracts as experimental demands at LANL continue to increase

36 MATERIALS SCIENCE↗

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Beam Non-Uniformity Characterization at the SpinQuest and DarkQuest Experiments

The SpinQuest experiment, including upgrades to SpinQuest designed to increase sensitivity to dark sector searches (commonly known as DarkQuest), utilizes the high-intensity 120 GeV proton beam delivered by the Fermilab Accelerator Complex to probe the inner structure of nucleons and search for new physics beyond the Standard Model. The SpinQuest beam is extracted from the Main Injector synchrotron at Fermilab in what is known as a slow spill . The slow spill involves a complex non-linear half-integer extraction method, which results in non-uniform beam behavior. SpinQuest observes spikes of very high intensity beam which can saturate detectors and reduce trigger efficiency, significantly impacting the experiment's sensitivity. In this project we address this challenge by developing an analysis framework to characterize the beam delivered to SpinQuest. By discovering trends within each spill and by comparing thousands of spills, we can better inform the Accelerator Division and improve the slow spill extraction. We have also begun a collaboration with the Accelerator Division in order to simulate the slow spill and improve the magnet ramp process controls which will improve the uniformity of the beam. These improvements will directly enhance the physics reach of SpinQuest/DarkQuest, increasing their sensitivity to key measurements such as the Sivers function and searches for new physics.

Dolen, James William [Purdue U., Calumet] (ORCID:0↗

MPEX High Heat Flux Plasma Dump Design, Manufacture, and Articles Test

Here, the Material Plasma Exposure eXperiment (MPEX) device is a steady-state linear plasma device currently in the final design phase at the Oak Ridge National Laboratory. This device will reach ion fluences up to 10 31 m -2 and will be used to expose neutron-irradiated materials to divertor-relevant plasmas and to study the effects of plasma-material interactions. These studies will elucidate the complex effects of plasmas with divertor candidate materials capable of withstanding high heat flux and high fluences for next-generation fusion devices. Bidirectional plasma will be generated using a high-power (200 kW) helicon source. Plasma will be confined by superconducting magnets. The last plasma-facing component on the upstream side of the MPEX device is the dump, which has been designed to intercept plasma and energetic particles. The dump will have a total heat load of 9.2 kW. A copper alloy (Glidcop AL-15) was selected for use in the water-cooled flange design because of its high thermal conductivity, its retaining strength at elevated temperatures, and its ability to be used in the high-temperature braze joints used in this application. Titanium-zirconium-molybdenum (TZM) tiles are brazed to the Glidcop AL-15 flange using high-temperature braze alloy. External water-cooling channels are used on the dump flange to prevent water leakage inside the vacuum space. This article discusses the details of the high heat flux dump design, including the computational fluid dynamics (CFD) and structural analyses performed to validate the design to meet the operational requirements of the MPEX device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

Design, Modeling, and Testing of a Novel Inductor for Electric Vehicles: Iron Nitride Soft Magnetic Composites

New technology for electric vehicles (EVs) must meet the requirements of higher energy usage, lower costs, and more sustainable source materials. One promising material for EV power system components is iron nitride (IN) soft magnetic composites (SMCs) because of their competitive magnetic properties and high abundance of the source materials. As part of an ongoing program at Sandia National Laboratories, this project focused on using computer modeling to optimize the prototyping process for an iron nitride SMC toroidal inductor to reach a target inductance of 600 μH. Four inductors with different combinations of wiring (26 AWG and 20 AWG) and vol% loading of iron nitride (65 vol% and 50 vol%) were fabricated at Cal Poly and characterized using an LCR meter. These inductors were also modeled using COMSOL Multiphysics™ with the Magnetic Fields module. The inductance data from the experiment and the model show that the 65 vol% IN prototypes and models agree with about 8% difference, while the 50 vol% IN samples show about a 9% difference between the prototype and the model. These results suggest that the model can predict inductance with both accuracy and precision with low confidence for the given sample size of four. An additional parameter of AC resistance is studied but the AC resistance results from the inductors and from the model generally do not agree closely, suggesting that the current model used in the project does not fully capture the mechanisms behind AC resistance of the inductor. With the focus of the project on inductance, the percent difference results of less than 9% across the four inductors that were tested increases confidence in the model’s predictive capabilities for inductance only. Using the inductance results from both the model and experiment, the final suggested inductor design is a 65 vol% core with 150 windings of 20 AWG wire that is 8 cm across and 1.5 cm tall to reach the inductance goal of 600 μH based on analysis using the optimized COMSOLTM model.

33 ADVANCED PROPULSION SYSTEMS↗

Detector Simulation Challenges for Future Accelerator Experiments

Detector simulation is a key component for studies on prospective future high-energy colliders, the design, optimization, testing and operation of particle physics experiments, and the analysis of the data collected to perform physics measurements. This review starts from the current state of the art technology applied to detector simulation in high-energy physics and elaborates on the evolution of software tools developed to address the challenges posed by future accelerator programs beyond the HL-LHC era, into the 2030–2050 period. New accelerator, detector, and computing technologies set the stage for an exercise in how detector simulation will serve the needs of the high-energy physics programs of the mid 21st century, and its potential impact on other research domains.

43 PARTICLE ACCELERATORS↗

Design optimization for Richtmyer–Meshkov instability suppression at shock-compressed material interfaces

We report the Richtmyer–Meshkov instability (RMI) is a phenomenon that occurs at the interface of two substances of different densities due to an impulsive acceleration, such as a shock wave passing through this interface. Under these conditions, the instability can be seen as interface perturbations begin to grow into narrow jets or spikes of one substance that propagate into the other. In some cases, this interface may involve an elastic–plastic material, which can play a significant role in the development and behavior of the RMI. The ability to effectively control RMI jetting and spike growth is one major limiting factor in technological challenges, such as inertial confinement fusion, that involve using high-pressure shock waves to implode a fuel target. The propagation of RMI growth can lead to increased asymmetry in this implosion process and significantly reduce the obtained energy yield. We use hydrodynamics simulations of impactor shock-compression experiments and methods based in design optimization to suppress RMI spike growth by altering the geometry and other properties of a shock-compressed elastic–plastic material target that shares an interface with atmospheric air. These hydrodynamics simulations use an arbitrary Lagrangian–Eulerian method with a high-order finite element approach. Our results demonstrate that RMI suppression can be achieved by intentionally creating a separate upstream interface instability to counteract the growth of long narrow RMI spikes at an interface with initial perturbations.

36 MATERIALS SCIENCE↗

A New Era of Nuclear Criticality Experiments: The First 10 Years of Comet Operations at NCERC

Comet is a general-purpose, heavy-duty, vertical-lift assembly designed for flexibility in conducting a variety of critical experiments. It is currently located at the National Criticality Experiments Research Center (NCERC) in Nevada. In the past, Comet resided at Technical Area-18 in Los Alamos, New Mexico, as part of the Los Alamos Critical Experiments Facility (LACEF). The Comet assembly was relocated to NCERC in 2008 and became fully operational in June of 2011. The first critical experiment performed on Comet at NCERC was a verification of one of the previous configurations of the Zeus experiment series. Over the next 10 years, many additional experiments followed including other Zeus configurations as well as completely new designs. This paper discusses the Comet vertical-lift assembly, the transition from LACEF to NCERC, and a selection of experiments that have been performed on Comet during its first 10 years of operation at NCERC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimal design of acoustic metamaterial cloaks under uncertainty

In this work, we consider the problem of optimal design of an acoustic cloak under uncertainty and develop scalable approximation and optimization methods to solve this problem. The design variable is taken as an infinite-dimensional spatially-varying field that represents the material property, while an additive infinite-dimensional random field represents the variability of the material property or the manufacturing error. Discretization of this optimal design problem results in high-dimensional design variables and uncertain parameters. To solve this problem, we develop a computational approach based on a Taylor approximation and an approximate Newton method for optimization, which is based on a Hessian derived at the mean of the random field. We show our approach is scalable with respect to the dimension of both the design variables and uncertain parameters, in the sense that the necessary number of acoustic wave propagations is essentially independent of these dimensions, for numerical experiments with up to one million design variables and half a million uncertain parameters. Additionally, we demonstrate that, using our computational approach, an optimal design of the acoustic cloak that is robust to material uncertainty is achieved in a tractable manner. The optimal design under uncertainty problem is posed and solved for the classical circular obstacle surrounded by a ring-shaped cloaking region, subjected to both a single-direction single-frequency incident wave and multiple-direction multiple-frequency incident waves. Finally, we apply the method to a deterministic large-scale optimal cloaking problem with complex geometry, to demonstrate that the approximate Newton method’s Hessian computation is viable for large, complex problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗