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At least 55 records · Page 3

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.

Towards Unlocking Insights from Logbooks Using AI

Electronic logbooks contain valuable information about activities and events concerning their associated particle accelerator facilities. However, the highly technical nature of logbook entries can hinder their usability and automation. As natural language processing (NLP) continues advancing, it offers opportunities to address various challenges that logbooks present. This work explores jointly testing a tailored Retrieval Augmented Generation (RAG) model for enhancing the usability of particle accelerator logbooks at institutes like DESY, BESSY, Fermilab, BNL, SLAC, LBNL and CERN. The RAG model uses a corpus built on logbook contributions and aims to unlock insights from these logbooks by leveraging retrieval over facility datasets, including discussion about potential multimodal sources. Our goals are to increase the FAIR-ness (findability, accessibility, interoperability, and reusability) of logbooks by exploiting their information content to streamline everyday use, to enable macro-analysis for root cause analysis, and to facilitate problem-solving automation.

43 PARTICLE ACCELERATORS

Uncertainty Quantification and Sensitivity Analysis of Low-Dimensional Manifold via Co-Kurtosis PCA in Combustion Modeling

For multi-scale multi-physics applications e.g., the turbulent combustion code Pele, robust and accurate dimensionality reduction is crucial to solving problems at exascale and beyond. A recently developed technique, Co-Kurtosis based Principal Component Analysis (CoK-PCA) which leverages principal vectors of co-kurtosis, is a promising alternative to traditional PCA for complex chemical systems. To improve the effectiveness of this approach, we employ Artificial Neural Networks for reconstructing thermo-chemical scalars, species production rates, and overall heat release rates corresponding to the full state space. Our focus is on bolstering confidence in this deep learning based non-linear reconstruction through Uncertainty Quantification (UQ) and Sensitivity Analysis (SA). UQ involves quantifying uncertainties in inputs and outputs, while SA identifies influential inputs. One of the noteworthy challenges is the computational expense inherent in both endeavors. To address this, we employ the Monte Carlo methods to effectively quantify and propagate uncertainties in our reduced spaces while managing computational demands. Our research carries profound implications not only for the realm of combustion modeling but also for a broader audience in UQ. By showcasing the reliability and robustness of CoK-PCA in dimensionality reduction and deep learning predictions, we empower researchers and decision-makers to navigate complex combustion systems with greater confidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Quantum Random Walk Simulator Using Ultrafast Optical Switches

Quantum random walk processes have many intriguing applications in high energy physics including the simulation of parton shower evolution. We will present the design and initial results of a fiber loop time-bin quantum walk architecture using the hardware platform already in operation at the Fermilab Quantum Network in which the state of the photon is defined by its time-of-arrival. The fiber loop consists of an unbalanced Mach-Zehnder interferometer implemented using an ultrafast electro-optical switch. The input switch controls the photon path within the interferometer, while the output switch will direct the photon back into the interferometer or to single photon detectors to measure the probability distribution of arrival times. Depending on which path the photon takes each pass through the loop, its wave function will interfere on these optical switches similar to quantum interference on a beam splitter. This work is an important step towards utilizing real-world advantages of quantum information protocols to solve problems in high energy physics.

Cameron, Andrew [Fermilab]

Weapon Material Program: FY24 Annual Report

The Weapon Material Program (WMP) framework was started in July of Fiscal Year (FY) 2022, along with other Mission Support organizations. The first year was about building the organization with the right people, identifying needs, and developing a vision for expectations. It was also a year to move forward with new equipment and technology for weapon material processes. With numerous improvements, WMP is building world-class systems for production, warehousing, and analytical testing. FY 2023 was a year of development. The WMP was a new organization defining its identity, its focus, and its mission. At the end of FY 2023, WMP evaluated its current position and its immediate needs along with its future goals. The entire organization set out on this FY 2024 journey to success. The lack of funding, staffing, and visibility dramatically impacted weapon material operations, testing, and qualifications. This neglect required numerous areas to be addressed and improvement plans to be developed and implemented. WMP processes, procedures, and overall business operations were dramatically in need of updating, revision, and formal documentation. This included all areas: technology, equipment, facility modifications/upgrades, and testing improvements. To ensure organizational improvement and forward momentum in FY 2024, WMP executed a multi-faceted strategic vision. Action items included the following: • Filling open positions with capable personnel who would contribute to a more robust organization • Establishing more formal operations and problem-solving techniques • Improving departmental procedures to align with expanding scope • Improving training • Establishing collaboration meetings with other departments/organizations • Focusing on the importance of identifying and mitigating concerns with At-Risk Materials (@RM) • Leading modernization eff orts for Blending and Packaging (B&P) We are on the verge of a transformational improvement in all of our processes in support of the mission. The following area achievements outlined in this report reflect the hard work toward achieving the goal of “being the material Subject Matter Experts in the nuclear enterprise”.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Distributed Energy Resource Interconnection Roadmap

Adopting strategic reforms to DER interconnection can help reduce interconnection delays, fairly allocate costs, improve transparency and equity, and support efficient and strategic investment in distribution and sub-transmission grids that can accommodate a rapidly evolving energy landscape. The Interconnection Innovation e-Xchange envisions this roadmap and its transmission system companion volume as collaborative resources to facilitate continued stakeholder discussions, problem-solving, and innovation as the U.S. works together to enable simpler, faster, and fairer interconnection of clean energy resources all while enhancing the reliability, resiliency, and security of our electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION

History of the Chemical Stockpile Emergency Preparedness Program – Volume 2: Lessons Learned (Final Report 2026)

The CSEP Program involved multiple federal agencies, multiple states, and numerous local units of government. The involvement of diverse agencies at different levels of government led to conflict and difficulty in resolving issues. That, in turn, led to slow progress in achieving program goals. Program management was criticized repeatedly by the U.S. General Accounting Office (GAO). After other mechanisms for interagency coordination had failed to give the desired results, FEMA and the Army agreed to form site-specific and national-level IPTs. The IPTs worked well to break the logjam and accelerate implementation of the program. Key elements of the IPTs’ success included constant interagency communication, solving problems at the lowest level, and obtaining buy-in from higher authority. The IPT technique could be applied to other emergency management and homeland security programs that require interagency coordination.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Fermilab 2025 Summer Internship: Repairing Pre-Amplifiers with Mu2e Electronics Installation Team

The author spent nine weeks over summer 2025 working on the tracker electronics installation team for the Mu2e experiment. One of her main responsibilities was repairing high voltage (HV) and calibration (Cal) pre-amplifiers (pre-amps). During installation, the fragile wires connecting the two sockets to the pre-amp board must be bent, often leading to breakage. During production, the sockets and wires were initially soldered to the board at UC Berkely, then the whole pre-amp was coated in parylene before transport to Fermilab. The interns were able to expedite the repairs, and thus whole installation process, by using an alternative method on-site with epoxy. Another task they were responsible for, not included in the original project specifications, was attaching copper clips to specific vias on the Cals to reduce noise. The talk will give listeners insight into the daily problem-solving required by the novel technologies in the Mu2e project. The author would like to acknowledge her fellow Monmouth College undergraduate interns, Lizzie Durfee and Gianna Maughan, advisor and PI of the DOE RENEW Grant Dr. Christopher G. Fasano, and the Mu2e team lead by co-spokesperson Dr. Bob Bernstein and tracker L2 manager Dr. Brendan Kiburg.

de Zwart, Bronte [Monmouth Coll.]

Filament Extension Atomization for High Solids Loading in Energy Efficient Spray Drying Systems

We demonstrate that we could scale FEA to reach outputs needed by industrial production, while increasing solids loading of the sprayed product by at least 30% and maintaining equal or better spray powder. After testing a wide range of products, in collaboration with industry partners we decided on our primary spray products of dry whey and WPC-80, two common materials processed and sold by US manufacturers with different parameters. We sprayed these with FEA at solids loadings of 70% for dry whey and 45% for WPC-80 with a spray output with particle sizes similar to industrial particles sizes and reduced variation in particle size. We simultaneously scaled up FEA first with a multi-nip with 6 nips surrounding a central roller with parallel axis of rotation and eventually with a tapered design that solved problems we encountered with our initial design. We were able to achieve output from a single array from our first design of up to 4.7 liters per minute (L/min) and from an array of our second multi-nip of 8 L/min exceeding expectations. This demonstrates that FEA technology can indeed be scaled up to meet the needs of industrial production. More arrays can be added as necessary to meet a wide range of spray dryer designs. We also tested FEA to create dried powders from a small scale (10 L/hour of water removal) spray dryer. Though we were not able to produce large quantities of powder from FEA due to challenges in integration, the powder we produced was higher quality and produced from higher solids loading materials. From our technoeconomic analysis we for a typically sized spray dryer, we estimate a 27% cost reduction and 41% energy and carbon reduction for WPC-80 and a 39-57% cost reduction and 52-76% energy reduction for sweet dry whey (depending on the exact product).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Fermilab 2025 Summer Internship Skills Learned from Working with Mu2e Tracker Team

As part of a DOE RENEW Grant, the undergraduate authors interned at Fermilab. They spent nine weeks over summer 2025 working on the tracker team for the Mu2e experiment. They gained practical experience in a multitude of new skills including electronics installation, testing, and repairs. Their work particularly increased productivity by helping repair the high voltage and calibration pre-amplifiers, over 20,000 of which are needed in the tracker. These components are very fragile and often break during the installation process. The experience also taught them several soft skills such as the importance of thoughtful data storage, record- keeping, and problem-solving skills. They learned the demands of a large, international collaboration and how to work in a team. The authors would like to acknowledge their advisor and PI of the grant, Dr. Christopher G. Fasano, and the Mu2e team lead by co- spokesperson Dr. Bob Bernstein and tracker L2 manager Dr. Brendan Kiburg.

de Zwart, Brontë

A Parameter-masked Mock Data Challenge for Beyond-two-point Galaxy Clustering Statistics

The past few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge named “Beyond-2pt,” initiated during the Aspen 2022 Summer Program “Large-Scale Structure Cosmology beyond 2-Point Statistics,” whose first round of results we present here. The challenge data set consists of high-precision mock galaxy catalogs for clustering in real space, in redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown (“masked”) cosmological parameters of the underlying ΛCDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available, and we welcome future submissions from methods that are not yet represented.

Krause, Elisabeth [Univ. of Arizona, Tucson, AZ (U

Workshop: Advanced Metering for Decarbonization: Electric Vehicles and 24/7 Carbon-Free Electricity

The purpose of this workshop is to learn more about advanced metering best practices for meeting the goals of EO 14057. This will be a 2-part session, first part to include presentations on the FEMP best practice work related to metering: 1) Electric Vehicles (EVs) and EV charging station electricity use. 2) Integrating data sources to calculate hourly carbon pollution-free electricity (CFE). Second part will facilitate small group discussions with a problem-solving activity.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC

Active Learning for Metamaterial Optimization on HPC and QC Integrated Systems

Active learning algorithms, integrating machine learning, quantum computing and optics simulation in an iterative loop, offer a promising approach to optimizing metamaterials. However, these algorithms can face difficulties in optimizing highly complex structures due to computational limitations. High-performance computing (HPC) and quantum computing (QC) integrated systems can address these issues by enabling parallel computing. In this study, we develop an active learning algorithm working on HPC-QC integrated systems. We evaluate the performance of optimization processes within active learning (i.e., training a machine learning model, problem-solving with quantum computing, and evaluating optical properties through wave-optics simulation) for highly complex metamaterial cases. Our results showcase that utilizing multiple cores on the integrated system can significantly reduce computational time, thereby enhancing the efficiency of optimization processes. Therefore, we expect that leveraging HPC-QC integrated systems helps effectively tackle large-scale optimization challenges in general.

Kim, Seongmin

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS

Overview of Large Helical Device experiments of basic plasma physics for solving crucial issues in reaching burning plasma conditions

Recently, experiments on basic plasma physics issues for solving future problems in fusion energy have been performed on a Large Helical Device. There are several problems to be solved in future devices for fusion energy. Emerging issues in burning plasma are: alpha-channeling (ion heating by alpha particles), turbulence and transport in electron dominant heating helium ash exhaust, reduction of the divertor heat load. To solve these problems, understanding the basic plasma physics of (1) wave–particle interaction through (inverse) Landau damping, (2) characteristics of electron-scale (high-k) turbulence, (3) ion mixing and the isotope effect, and (4) turbulence spreading and detachment, is necessary. This overview discusses the experimental studies on these issues and turbulent transport in multi-ion plasma and other issues in the appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

What can solve the strong CP problem?

Three possible strategies have been advocated to solve the strong CP problem. The first is the axion, a dynamical mechanism that relaxes any initial value of the CP violating angle $\overline{θ}$ to zero. The second is the imposition of new symmetries that are believed to set $\overline{θ}$ to zero in the UV. The third is the acceptance of the fine tuning of parameters. We argue that the latter two solutions do not solve the strong CP problem. The θ term of QCD is not a parameter — it does not exist in the Hamiltonian. Rather, it is a property of the quantum state that our universe finds itself in, arising from the fact that there are CP violating states of a CP preserving Hamiltonian. It is not eliminated by imposing parity as a symmetry since the underlying theory is already parity symmetric and that does not preclude the existence of CP violating states. Moreover, since the value of θ realized in our universe is a consequence of measurement, it is inherently random and cannot be fine tuned by choice of parameters. Rather any fine tuning would require a tuning between parameters in the theory and the random outcome of measurement. Our results considerably strengthen the case for the existence of the axion and axion dark matter. The confusion around θ arises from the fact that unlike classical mechanics, the Hamiltonian and Lagrangian are not equivalent in quantum mechanics. The Hamiltonian defines the differential time evolution, whereas the Lagrangian is a solution to this evolution. Consequently, initial conditions could in principle appear in the Lagrangian but not in the Hamiltonian. This results in aspects of the initial condition such as θ misleadingly appearing in the Lagrangian as parameters. We comment on the similarity between the θ vacua and the violations of the constraint equations of classical gauge theories in quantum mechanics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Simulations of Quantum Approximate Optimization Algorithm on HPC-QC Integrated Systems

The Quantum Approximate Optimization Algorithm (QAOA) has emerged as a promising tool for accelerating optimization processes in the Noisy Intermediate-Scale Quantum (NISQ) era. Compared to classical methods, QAOA efficiently solves optimization problems, often formulated as Quadratic Unconstrained Binary Optimization (QUBO) problems. Classical quantum simulators are crucial for evaluating quantum algorithms due to limited quantum resources. However, QAOA's performance can vary with different simulation methods. This study analyzes QAOA's performance using various quantum simulators (e.g., density _matrix, statevector, and matrix_product_state) and demonstrates the benefits of HPC-QC integrated systems in solving QUBO problems on an active learning workflow. By simulating QAOA on dense, large-matrix QUBO problems, we evaluate accuracy and problem-solving time. We also assess QAOA's performance on local computers and HPC-QC inte-grated systems, using Oak Ridge Leadership Computing Facility (OLCF)'s Frontier supercomputer with local Qiskit Aer and remote IBM Quantum simulators.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)

An Iterative Approach for Solving the SCOPF Problem Applying LP, SOCP, and NLP Subproblems

We propose to develop efficient algorithms and software for the SCOPF problem. We will employ an iterative approach that will: a) use linear subproblems and other active set filtering techniques to identify the most important contingencies and drastically reduce the SCOPF model size; b) solve SOCP relaxations of the reduced SCOPF to converge to the neighborhood of the global optimal solution and establish a lower bound on the solution, and; c) use a non-convex, nonlinear interior-point solver, Artelys Knitro, to converge quickly to the optimal solution. To identify the most effective approach, we will experiment with several techniques to identify the tradeoffs between contingency subproblem complexity and fast solvability.

29 ENERGY PLANNING, POLICY, AND ECONOMY