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At least 19 records

COLLABORATIVE DEVELOPMENT PROJECTS - PHOTONIC MEMORY CONTROLLER MODULE (P-MCM)

As computational density for high-performance computing and big-data services continues to scale, performance scalability of next generation computing systems is becoming increasingly constrained by limitations in memory access, power dissipation and chip packaging. The processor-memory communication bottleneck, a major challenge in current multicore processors due to limited pin-out and power budget, presents a detrimental scaling barrier to data-intensive computing. A consortium team of small businesses and leading researchers that includes experts from photonics processor-memory architecture, III/V photonic laser design/fabrication, silicon photonics design/fabrication, photonics packaging and assembly, and FPGA-based high-performance memory controller IP development – to collaboratively develop a commercialization path for a Photonic Memory Controller Module (P-MCM).

97 MATHEMATICS AND COMPUTING↗

AMMT-Regulatory Development Collaboration Scoping Project

This project was initiated by the Regulatory Development (RD) Program to identify potential collaborations in work scope between the Advanced Materials and Manufacturing Technologies (AMMT) Program and the Regulatory Development Program. During Fiscal Year 2025, RD Program staff met with members of the AMMT Program, including the national technical director and multiple technical area leads to discuss ongoing work and areas where regulatory interactions with the Nuclear Regulatory Commission (NRC) would increase the efficiency to get new materials and manufacturing technologies approved for industry use. RD staff would like to thank the AMMT staff for their participation in these interactions to identify areas of potential collaboration.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and -related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

60 APPLIED LIFE SCIENCES↗

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗

Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region

U.S. Department of Energy (DOE), Office of Science, Award DE-SC0023215, Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region, supported capacity and partnership building between researchers at Central Michigan University (CMU) and scientists at DOE laboratories. The work involved identifying potential collaborations both internal to CMU and between CMU researchers and DOE staff, developing collaborative research proposals, and partnering on pilot-scale research projects focused on enhancing resilience of Great Lakes communities, ecosystems, and infrastructure to global change and environmental stressors. DOE funds supported travel, time to develop collaborations, investigate new research pathways, and draft grant proposals, and a loan of DOE equipment to collect pilot data in support of future work. The project achieved its goal of strengthening research collaborations between interdisciplinary researchers at CMU and establishing new collaborations and partnerships between CMU and DOE scientists. These collaborations resulted in 5 pre-applications and 4 full applications for funding to DOE BER Funding Opportunities, a successfully funded DOE BER award (DE-SC0025260), a new pilot project that leveraged DOE resources (AquaBOT) to improve understanding of water quality conditions in Michigan rivers, and two presentations of preliminary results at national scientific conferences. This project’s outcomes will benefit the Great Lakes Region via new lines of collaborative research focused on improving the resilience of Michigan communities, ecosystems, and infrastructure.

58 GEOSCIENCES↗

Lessons Learned from Site Selection Efforts for Deep Geological Disposal

This report discusses international experiences from site selection of deep geological repositories (DGR) for radioactive waste disposal. Based on experiences from three countries with recent or ongoing site selections, the report describes different site selection approaches and summarizes lessons learned. The German and Swiss programs are two slightly different examples of one end of the spectrum of potential siting approaches: Starting with the entire country, a technically based downselection is performed to select the repository site. The Canadian program is an example of the other end of the spectrum: Here, the program started with an extensive engagement program with Canadians to collaboratively develop a socially acceptable and technically sound national approach for the long-term management of used nuclear fuel. This was followed by the launch of a collaboratively developed consent-based siting process designed to seek an informed and willing host with suitable sites, considering both technical and community well-being site requirements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thirdhand tobacco smoke exposure increases the genetic background-dependent risk of pan-tumor development in Collaborative Cross mice

Increasing evidence has shown that thirdhand smoke (THS) exposure is likely to induce adverse health effects. An important knowledge gap remains in our understanding of THS exposure related to cancer risk in the human population. Population-based animal models are useful and powerful in investigating the interplay between host genetics and THS exposure on cancer risk. Here, we used the Collaborative Cross (CC) mouse population-based model system, which recapitulates the genetic and phenotypic diversity observed in the human population, to assess cancer risk after a short period of exposure, between 4 and 9 weeks of age. Eight CC strains (CC001, CC019, CC026, CC036, CC037, CC041, CC042 and CC051) were included in our study. We quantified pan-tumor incidence, tumor burden per mouse, organ tumor spectrum and tumor-free survival until 18 months of age. At the population level, we observed a significantly increased pan-tumor incidence and tumor burden per mouse in THS-treated mice as compared to the control (p = 3.04E-06). Lung and liver tissues exhibited the largest risk of undergoing tumorigenesis after THS exposure. Tumor-free survival was significantly reduced in THS-treated mice compared to control (p = 0.044). At the individual strain level, we observed a large variation in tumor incidence across the 8 CC strains. CC036 and CC041 exhibited a significant increase in pan-tumor incidence (p = 0.0084 and p = 0.000066, respectively) after THS exposure compared to control. We conclude that early-life THS exposure increases tumor development in CC mice and that host genetic background plays an important role in individual susceptibility to THS-induced tumorigenesis. Genetic background is an important factor that should be taken into account when determining human cancer risk of THS exposure.

60 APPLIED LIFE SCIENCES↗

Design and Prototyping of a Novel Toroidal Magnet System for MOLLER Experiment at Jefferson Lab

The Thomas Jefferson National Accelerator Facility (JLab) has designed a unique spectrometer system to measure the weak interaction between electrons. The experiment— Measurement of Lepton-Lepton Electroweak Reaction (MOLLER)—requires leveraging the recent 12 GeV electron beam upgrade and will run in JLab for three years. Focusing the signal for the MOLLER experiment requires five water-cooled toroidal magnets, each with unique geometry and with 7-fold symmetry. The five magnets operate in a vacuum and provide the magnetic field required to separate the incident beam electrons scattered from the target electrons (Møller scattering) and protons (elastic e-p scattering) in a liquid hydrogen target. The conceptual design was developed by the MOLLER Collaboration and was given to JLab in the form of amp turns and physical location, with additional physics requirements. This article presents prototyping of the coils and magnet support system and discusses the lessons learned during the process along with the plans for full magnet testing and installation. The JLab Magnet Group along with the MOLLER Collaboration developed the specification document that includes keep out zones to design the set of magnets. JLab contracted the design of the first toroid magnet (TM0) of the magnet system to Massachusetts Institute of Technology. The other four toroid magnets (TM1 through TM4) have been designed by JLab and are in the process of fabrication and assembly. Prototype coils of TM1-TM4 were fabricated by Everson-Tesla Incorporated, PA (USA). Finally, this article presents the unique challenges of the design, alignment, high current density, operating range, high radiation dose, and vacuum environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Design and Prototyping of a Novel Toroid Magnet System for the MOLLER Experiment at Jefferson Lab

The Thomas Jefferson National Accelerator Facility (JLab) has designed a unique spectrometer system to measure the weak interaction between electrons. The experiment ?Measurement of Lepton-Lepton Electroweak Reaction? (MOLLER) requires leveraging the recent 12 GeV electron beam upgrade and will run in JLab for 3 years. Focusing the signal for the MOLLER experiment requires five water-cooled toroidal magnets, each with unique geometry and with 7-fold symmetry. This system of magnets provides the magnetic field required to separate the incident beam electrons scattered from the target electrons (Møller scattering) and protons (elastic e-p scattering) in a liquid hydrogen target. The conceptual design was developed by the MOLLER collaboration and was given to JLab in the form of amp turns and physical location, with additional physics requirements. This paper presents prototyping of the coils and magnet support system and discusses the lessons learned during the process along with the plans for full magnet testing and installation. The JLab Magnet Group along with the MOLLER collaboration developed the specification document that includes keep out zones to design the set of magnets. JLab contracted the design of the first toroid magnet in the magnet (TM0) to Massachusetts Institute of Technology. The other four toroid magnets (TM1 through TM4) have been designed by JLab and are in the process of fabrication and assembly. Prototype coils of TM1-TM4 have been fabricated by Everson-Tesla Incorporated, PA (USA). The manuscript presents the unique challenges of the design, alignment, high current density, operating range, high radiation dose, and vacuum environment.

Kashy, David↗

Enabling Dark Energy Measurements from DESI and LSST (Final Technical Report)

This grant enabled efforts to lead the Survey Validation of the Luminous Red Galaxy (LRG) sample for DESI, entailing intensive work to prepare target samples, test their performance with DESI data, and validate that the requirements of the survey for this key sample are met. Luminous Red Galaxies represent the gold standard target class for Baryon Acoustic Observation experiments to study Dark Energy. It also funded work to co-leading the Follow-up Task Force within the LSST Dark Energy Science Collaboration (LSST DESC), which is intended to help develop collaborations with external groups and to produce cross-working group proposals for telescope time, policy proposals and white papers as needed in order to help the collaboration obtain and make use of complementary data which will strengthen LSST Dark Energy constraints. The PI has been particularly engaged in efforts to obtain access to spectroscopic training sets for LSST photometric redshifts in the first years of the survey, which requires developing relationships with groups that are obtaining such data for other purposes. This group has evolved into an External Synergies working group within DESC, also co-led by the PI. These groups have developed white papers for Astro2020, letters of intent and white papers for Snowmass2021, and a response to a DOE-NASA RFI. It also has enabled smaller contributions to improving LSST DESC pipeline infrastructure for photometric redshifts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

OpenCHAMI Developer Summit [Slides]

The mission of the OpenCHAMI consortium is to steward the collaborative development and continuous evolution of cloud-like software to manage High Performance Computing capacity regardless of the size or deployment platform. We are guided by the operators and practitioners who use modern tooling and concepts to address the needs of classical HPC applications and the growing AI/ML and Data Science community that wish to leverage HPC capacity within their own workflows, to meet their needs with their own tools.

97 MATHEMATICS AND COMPUTING↗

Facilitating Machine Learning Collaborations Between Labs, Universities, And Industry

It is clear from numerous recent community reports, papers, and proposals that machine learning is of tremendous interest for particle accelerator applications. The quickly evolving landscape continues to grow in both the breadth and depth of applications including physics modeling, anomaly detection, controls, diagnostics, and analysis. Consequently, laboratories, universities, and companies across the globe have established dedicated machine learning (ML) and data science efforts aiming to make use of these new state-of-the-art tools. The current funding environment in the U.S. is structured in a way that supports specific application spaces rather than larger collaboration on community software. Here, we discuss the existing collaboration bottlenecks and how a shift in the funding environment, and how we develop collaborative tools, can help fuel the next wave of ML advancements for particle accelerators.

Edelen, J.P.↗

Thoroughly testing and integrating hundreds of Pull Requests per month: ROOT’s new Cost-efficient and Feature Rich GitHub-based CI

ROOT is an open source framework, freely available on GitHub, at the heart of data acquisition, processing and analysis of HE(N)P experiments, and beyond. It is developed collaboratively: contributions are not authored only by ROOT team members, but also by the user community at large: developers and scientists from universities, labs as well as the private sector. More than 1500 GitHub Pull Requests are merged on average per year. It is in this context that code integration acquires a primary role. The review of code contributions isn’t enough: not only they need to be thoroughly reviewed, they also need to be thoroughly tested through a powerful CI infrastructure on several different platforms to comply with the high code quality standards of the project. Since the end of 2023, ROOT moved its continuous integration system from Jenkins to GitHub Actions. In this contribution, we characterise the transition to the GitHub CI, focussing on our strategy, its implementation and the lessons learned, as well as the advantages the new system offers with respect to the previous one. Particular emphasis will be given to the evaluation of the cost-benefit ratio for Jenkins and GitHub Actions for the ROOT project. We also describe how we manage to run in less than one hour thousands of unit, integration, functional and end-to-end tests on different flavours of Windows, four versions of macOS, as well as about ten of the most used Linux distributions, taking advantage of the CERN computing infrastructure.

Piparo, Danilo [CERN]↗

FNAL-NIU collaboration on magnet development

We are presenting an overview of our (MTD) collaboration with NIU on superconducting magnet development. Through multiple endeavors over the last years we succeeded building a strong collaboration and attracted additional support for it. One of the key aspects of the collaboration is that it heavily benefits NIU students who are offered excellent opportunities to work with world leading experts in the field, make a mark for themselves and possibly start a carrier in an area they start to appreciate and like.

Stoynev, Stoyan [Fermilab]↗

WETO Software Stack Best Practices

Wind energy researchers typically share one key characteristic: a passion for increasing wind energy in the global energy mix. The U.S. Department of Energy (DOE) supports this mission in a number of ways including allocating funding directly to various aspects of wind energy research through the Office of Energy Efficiency and Renewable Energy (EERE) via the Wind Energy Technologies Office (WETO). While the traditional output of research is academic publication, software development efforts are increasingly a major focus. Software tools in the research environment allow researchers to describe an idea and quickly increase the scope and scale as they study it further. As a product of research, these tools represent a direct pipeline from researcher to industry practitioners since they are the implementation of ideas described in academic publications. Given this vital role in wind energy research and commercial development, the broad research software portfolio supported by WETO must maintain a minimum level of quality to support the wind energy field in the growing transition to renewable energy. This report outlines a series o f best practices to be adopted by all WETO-supported software projects, as well as expectations that the communities interacting with these projects should have of the developers and tools themselves. Wind energy research software has a unique standing in the field of scientific software. The stakeholders are varied with a subset being: (1) DOE EERE leadership, (2) DOE WETO leadership and program managers, (3) National lab leadership, (4) Associated project principle investigators, (5) Research software engineers, (6) Wind energy researchers in academia (including graduate students, post docs, and national lab staff), (7) Industry researchers and practitioners, (8) Commercial software developers, and (9) The general public interested in wind energy. These software are typically the end-user of other generic software libraries, so the funding cycles are often tied to applied research rather than the development of the software itself. Since the developers are also wind energy researchers, these tools are typically designed in a way that closely resembles the application in which they're used. Additionally, the expertise and incentives for the developers have a high variability, and often neither are aligned with software engineering or computer science. Given the unique environment in which wind energy research software is produced and consumed, it is critical for model owners to understand the context of their software. A framework for developing this understanding is to answer the following questions of a given software project: What is it's purpose? What is its role in the field of wind energy? What is the profile of the expected users? For how long will it be relevant? What is the expected impact? These questions allow model owners to identify the appropriate methods for the design, development, and long term maintenance of their software. Additionally, the answer provide context for future planners to understand why particular decisions were made and discern the consequences of changing course. The information is aggregated from experience within WETO-supported software development groups as well as external organizations and efforts to define the craft of research software engineering. These best practices aim to make the collaborative development process efficient and effective while improving the model understanding across stakeholders. Additionally, the general adoption of a common framework for software quality ensures that the end users of WETO software can trust these tools and accurately understand the risks to workflow integration.

17 WIND ENERGY↗

Reducing Mass of Steel Auto Bodies using Thin Advanced High Strength Steel with Carbon-Fiber Reinforced Epoxy

Diversitak, a company based in Detroit, MI, has developed a proprietary, low specific gravity, carbon fiber-reinforced epoxy (CFRE) under U.S. patent number 9,963,58832. Preliminary testing on this new material conducted in collaboration with ArcelorMittal Steel Company proved out the CFRE concept. A thin layer of this CFRE was applied to a stamped sheet of steel with residual stamping oils from a mill, in a time corresponding to automotive processing (e.g., ~15 seconds), and processed following automotive e-coat procedures (phosphating + 175–200°C heating), to complete the curing. No problems with adherence or performance were noted. While the CFRE does add weight to a thin gauge steel panel, it weighs much less than what is displaced by using thicker conventional mild steel gauges. The application of the coating showed a significant increased dent resistance, oil canning resistance, and part stiffness.This current two-year project was designed to mature this new technology to near manufacturing readiness to reduce the weight of a vehicle and lower the cost of weight reduction. The process involves the use of thinner gauge steels than are currently used. The collaborative development team included two industrial manufacturers: Diversitak and ArcelorMittal Steel Company; LightMAT; and two National Laboratories: Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL). The team developed a new manufacturing process to reduce the weight of a vehicle and lower the cost of weight reduction, as well as a better understanding of how to apply the coating so that it will perform to a high standard in-service. The team also performed an in-depth study to determine the long-term durability of the materials manufactured using this technology and well-known automotive industry standard tests.The overall process involved stiffening the thinner gauge steel by applying the CFRE on only one side. To accomplish this goal, the optimal reinforcement fiber length and fiber concentration was first determined. This was followed by measuring the coefficient of thermal expansion (CTE) in all three directions, so it could be fed into manufacturing models and methods for rapidly and inexpensively applying the coating. This was followed by panel level evaluations of the coating and steel combination, and then by full part demonstration of the technology on door panels. The final step was corrosion testing of the parts.ArcelorMittal characterized the advanced high strength steel (AHSS) (e.g., metallurgy-heat treatment for required AHSS properties as a function of the sheet thickness, state of internal stress) and quantified CFRE adhesion to the steel as a function of sheet preparation (e.g., rolling and stamping).ORNL optimized the fiber length, fiber concentration, and coating thickness for best vehicle function and performance at the least cost. Along with the suppliers, ORNL developed a durable CFRE application process (e.g., gun material, design, robotic dispensing process) and identified the adhesion stability of the CFRE during process holding. An approach to ensure that application/curing timing conforms to conventional assembly line speed and plant cycle times was determined. ORNL also determined the CTE of the material in all three directions and performed material scanning electron microscopy (SEM) analyses.INL characterized the corrosion properties of the steel panels coated with CFRE. The panels were investigated for corrosion resistance and stability as replacement materials used in automotive body panels to reduce mass. The coupons tested at INL were supplied by Diversitak after an optimized CFRE formulation was achieved in the already coated form for corrosion testing.

99 GENERAL AND MISCELLANEOUS↗