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At least 361 records · Page 20

Status of the IOTA Proton Injector

The IOTA Proton Injector (IPI), currently under installation at the Fermilab Accelerator Science and Technology facility (FAST), is a machine capable of delivering 20 mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. First beam in the IPI beamline is anticipated in the first half of 2024, when it will operate alongside the existing electron injector beamline to facilitate further beam physics research and continued development of novel accelerator technologies at the IOTA ring. This report details the expected operational profile, known challenges, and the current state of installation.

43 PARTICLE ACCELERATORS↗

Experiments On Electron Cooling and Intense Space-charge at IOTA

The Integrable Optics Test Accelerator at Fermilab will explore beam dynamics in a ring with intense space-charge using 2.5 MeV proton beams with an incoherent tune shift approaching -0.5. We will use this machine to explore the interplay between electron cooling, intense space-charge, and coherent instabilities. In this contribution, we describe the machine setup including the design of the electron cooler and the lattice, list specific experiments and discuss the results of numerical simulations which include the effects of electron cooling and transverse space-charge forces.

43 PARTICLE ACCELERATORS↗

Computational Modeling, Simulation, and Potential Applications of Optical Stochastic Cooling

With the rising demand for intense particles beams, much research is being conducted in the area of particle beam cooling. One of these methods, called Stochastic Cooling (SC) (developed at CERN in the 1970's), delivered a feedback method to improve the quality and lifetime of circulating proton beams by reducing their 6D phase-space and has been widely implemented in a number of hadron machines. However, traditional stochastic cooling schemes are limited by the bandwidth of microwave frequency systems. Optical Stochastic Cooling (OSC) is a promising extension of the stochastic cooling beam cooling technique. OSC instead uses optical wavelengths which allows for improved control and increased cooling but creates its own technical challenges. This lays out work conducted toward the experimental demonstration of OSC at Fermilab's Integrable Optics Test Accelerator (IOTA) storage ring. This includes the design and characterization of parts of the optical delay system, the development and validation of a high-fidelity computational model of the OSC process, and the investigations into possible applications of the OSC mechanism to advanced beam manipulations.

43 PARTICLE ACCELERATORS↗

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗

IOTA Experiment for Proton Pulse Compression at Extreme Space-Charge

The longitudinal compression of high-intensity, space-charge-dominated proton bunches is a critical requirement for future proton-driven muon colliders. We propose a proton bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to investigate optimal radio-frequency (RF) cavity parameters and lattice configurations. IOTA is a compact, fixed-energy storage ring dedicated to beam physics Research and Development and capable of circulating a 2.5 MeV proton beam under extreme space-charge conditions. Using the ImpactX code with its 3D space-charge solver, simulations indicate that the bunch length can be rapidly reduced by at least a factor of two without appreciable degradation of transverse beam quality--even in the strong space-charge regime. However, longitudinal defocusing due to the space-charge remains a significant challenge in short-pulsed intense proton bunches, and the optimization of compression under these conditions is discussed.

Simons, B. D. [Northern Illinois U.]↗

Using "AI Poincare" to analyze non-linear integrable optics

This study dives into the applicability of using automated discovery of conserved quantities in dynamical systems relevant to accelerator physics. Specifically, we explore the performance of AI Poincaré in analyzing numerical trajectory data obtained using the McMillan system of non-linear integrable optics. A comprehensive evaluation of the algorithm's performance is conducted through diverse methodologies. These include the analysis of the estimated number of conserved quantities embedded in a dataset and the deviation of interpolated points on the inferred manifold with respect to points in actually in the dataset. the investigation identifies an optimal range of perturbation distances where the underlying manifold extraction algorithm inside AI Poincaré exhibits optimal performance. Additionally, an improved neural network architecture is proposed based on the observed results. Finally, we apply the algorithm to preliminary experimental data from the Integrable Optics Test Accelerator at Fermilab to successfully infer the number of conserved quantities even in the presence of fast decoherence of the measured signal.

Osmanov, Lazare [Free U. Tbilisi]↗

Experimental Demonstration of a Two-Dimensional Nonlinear Integrable System in a Particle Accelerator

A two-dimensional nonlinear integrable system was experimentally demonstrated at the Fermilab Integrable Optics Test Accelerator. The system was implemented by inserting a special nonlinear magnet in a conventional accelerator lattice. We characterized the system by measuring lifetimes, transverse profiles and transverse oscillation frequencies of the 150-MeV electron beam as a function of the strength of the nonlinear insert. The measured shift of the working point and the amplitude-dependent detuning were consistent with theoretical predictions. We also observed the predicted bifurcation of the stable closed orbit. A striking consequence of the system's implementation was the possibility to operate the storage ring with integer tunes without lifetime degradation. This research opens up novel ways to design particle accelerators and to stabilize particle beams.

Wieland, John [Fermilab] (ORCID:0000000289718523)↗

Hands-On, Heads-Up: Blending Cyber T&E with Data Science-Driven Training in Jupyter Notebooks

In an era of increasingly sophisticated threats to critical infrastructure, cybersecurity professionals must be more than just aware; they must be immersed, agile, and equipped to operate in environments where failure is not an option. Nowhere is this truer than in the nuclear sector, where cyber-physical systems, regulatory scrutiny, and insider threat potential demand a new generation of hands-on, technically fluent defenders. This paper presents a unified training approach that integrates Cybersecurity Test and Evaluation (T&E) with data science techniques using Jupyter Notebooks as the interactive lab environment. The program centers on a modular, scenario-driven curriculum designed to build not just knowledge but practical capability in the assessment and defense of radiation detection systems, firmware interfaces, and operational security postures.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Improved measurements of nonlinear integrable optics at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents on the improved calibrations of the NIO for nonlinear invariant measurements.

43 PARTICLE ACCELERATORS↗

Improved Measurements of Nonlinear Integrable Optics Invariants at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents the results of improved measurements of nonlinear invariants.

43 PARTICLE ACCELERATORS↗

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗

An ERCOT test system for market design studies

An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over highvoltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unrmed wind and solar power. Users can congure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modied or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Finally, detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Blast Effects on Buildings (Final Report)

Lawrence Livermore National Laboratory (LLNL) has conservatively reduced the explosive safety standards suggested by the Small Quantities in Research Laboratories (SQRL) program testing by 60%. For this reason, further research into the detailed effects of small amounts of explosives in typically constructed rooms is needed in order to improve their factor of safety. The team was tasked with designing an experiment to investigate the effect of different variables on drywall under explosive blasts. In order to meet this objective, the team conducted a comprehensive literature review to gain an understanding of industry-standard construction practices and review previous tests conducted by the Army corp of engineers. Since the team used PBXN-5 rather than C4, as in SQRL, an initial shot was conducted to compare damage levels. From those results and the physical constraints of the testing chamber, the team redesigned multiple single-panel drywall frames to capture the entirety of the incurred damage. Proposed designs were narrowed down using a decision matrix. From the study of previous tests and literature review, variables were chosen that the team hypothesized to have an impact on drywall strength. The variables that were tested were chosen from the results of that work and specific variables the sponsor was interested in, and they were paint, humidity/moisture content, and explosive positioning relative to the studs. Detailed plans were made for each variable according to what conditions the team wanted to investigate. For humidity, this involved testing low, ambient, and high conditions by treating the panels in a chamber. Preliminary shots were performed to test the structural integrity of the frame and streamline the test diagnostics which involved a high-speed camera placed behind the drywall, outside of the chamber, and a pressure probe placed behind the drywall, inside the chamber. Once the instrumentation, diagnostics, and frame design were finalized, a quantitative damage criteria matrix was created to categorize the results of the main shot series. In conjunction with evidence from the high-speed video, the achieved damage levels indicate that high moisture content drywall is better able to withstand explosive blasts. Larger stud damage and lower drywall damage occurred when the explosive was located directly in front of a stud. Paint had no noticeable impact on strength. Ultimately, the team conducted a total of 17 tests, leaving the door open for future in-depth research into the impact of humidity.

36 MATERIALS SCIENCE↗

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗

In‐operando thermal transport characterization of moving particle bed heat exchanger

The project aimed to develop modulated photothermal radiometry (MPR) for conducting in-operando measurements of thermal transport in moving particle bed heat exchangers (MPBE) located at Sandia National Laboratory (SNL). The plan was to initially conduct lab-scale measurements on a 1-meter-long particle channel at UCSD, followed by in- operando measurements at SNL on a 20 kWth MPBE prototype built for this project, and if time permitting, potential final deployment on SNL’s 1 MWth G3P3 MPBE. The first two goals were successfully achieved but due to changes with commissioning timeline of the G3P3 MPBE, in-operando measurements on the G3P3 MPBE could not be conducted. The measurement campaigns have resulted in some promising results and the MPR tool has been handed over to trained SNL personnel for future use. MPR measurements on UCSD’s 1-meter-long particle channel showed a peculiar length dependence of the particle bed thermal conductivity and near-wall thermal resistance. The bed thermal conductivity increased, and the near-wall thermal resistance decreased, with increasing distance from the channel inlet, both eventually reaching a plateau. This was found to be due to hydrostatic pressure screening by the channel walls, known as the “Janssen effect”, and is the first experimental study on its role in granular heat transfer. A 20 kWth small-scale MPBE prototype, the first of its kind with 3 mm particle channels and 2 mm sCO2 plates, was designed and manufactured by Vacuum Process Engineering (VPE) for this project. This MPBE prototype was installed in SNL’s HEX test stand and the MPR tool was integrated into the test stand for in-operando measurements. Several modifications have been made to the MPR setup for facile installation and easy operation at SNL. Measurements with Carbo HSP40/70 particles were conducted with various particle and sCO2 temperatures and flow rates. Further, apart from regular MPBE operation, fault scenarios such as plate warping, particle stagnation, and choking were also detected and MPR showed excellent sensitivity to the detection of such conditions. Through the course of this project, MPR has evolved from a sensitive laboratory technique to a rugged industrial tool with various applications in high temperature measurements and diagnostics.

14 SOLAR ENERGY↗

Containerization in ATLAS Software Development and Data Production

The ATLAS experiment's software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS dis-tribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packag-ing and installation steps. For opportunistic sites that can not access CVMFS, containerized releases are needed. These standalone containers are currently created manually to support Monte-Carlo data production at such sites. In this paper we will describe an automated procedure for the containerization of AT-LAS software releases in the existing software development infrastructure, its motivation, integration and testing in the distributed computing system.

97 MATHEMATICS AND COMPUTING↗

BeeSwarm: Enabling Parallel Scaling Performance Measurement in Continuous Integration for HPC Applications

Testing is one of the most important steps in software development–it ensures the quality of software. Continuous Integration (CI) is a widely used testing standard that can report software quality to the developer in a timely manner during development progress. Performance, especially scalability, is another key factor for High Performance Computing (HPC) applications. There are many existing profiling and performance tools for HPC applications, but none of these are integrated into CI tools. In this work, we propose BeeSwarm, an HPC container based parallel scaling performance system that can be easily applied to the current CI test environments. BeeSwarm is mainly designed for HPC application developers who need to monitor how their applications can scale on different compute resources. We demonstrate BeeSwarm using a multi-physics HPC application with Travis CI, GitLab CI and GitHub Actions while using ChameleonCloud and Google Compute Engine as the compute backends. Finally, our results show that BeeSwarm can be used for scalability and performance testing of HPC applications.

97 MATHEMATICS AND COMPUTING↗

Networked HIL Simulation System for Modeling Large-scale Power Systems

This paper presents a networked hardware-in-the-loop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAr regulation technologies as an example to illustrate system setups, communication requirements among different HIL simulation systems, and system connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.

Xie, Fuhong↗