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At least 145 records · Page 8

Panel Session 34: US DOE Featured Site: Savannah River Operations Office: 70 Years of Service

The Savannah River Site celebrates its 70. anniversary on November 28, 2020. On this date in 1950, President Harry S. Truman requested the Dupont Company to design, build and operate what was then known as the Savannah River Plant in response to the Soviet Union's detonation of its first atomic weapon, which set the Cold War into motion. During the 1950's, six South Carolina towns were relocated for the construction of SRS and by 1953, the 310 square mile site was complete. Nearly 40,000 workers were employed t build five nuclear reactors and support facilities, two chemical separations plants, heavy water extraction plant, nuclear fuel and target fabrication facility tritium extraction facility and waste management facilities. SRS played a key role in winning the Cold War and for seven decades, SRS has been a leader within the DOE complex. Today, the site supports environmental stewardship and maintains the nation's nuclear deterrent while ensuring the safekeeping and disposal of domestic and international nuclear materials. The site continues to support the nation's nuclear defense as it explores new potential NNSA missions. SRS has a proud 70- year history and looks forward to a future of service as a national asset and strong community partner. The session was kicked off with a video message from Secretary of Energy, Dan Brouillette, who thanked employees past and current for their efforts. The video also provided an overview of the history and future of the Site. This panel provided an overview of the Savannah River Site's 70 years of service (history, challenges, opportunities, and future) presented by the SRS's Senior leadership and the local Aiken, South Carolina Mayor. Panelists with presentations: US DOE Secretary Dan Brouillette's Overview of DOE and SRS - A Legacy of 70 Years of Service (Amy Boyette); 70 Years of Service (Michael Budney); 70 Years of Service (Stuart MacVean); SRS Liquid Waste (Thomas Foster); National Nuclear Security Administration (Nicole Nelson-Jean)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Building and Executing Aggressive Research Plans in a Large National Laboratory Consortium: Insights from the Co-Optimization of Fuels and Engines Initiative

This report describes lessons learned in the establishment, execution and termination of a large, multi-institutional consortium, derived from the Co-Optimization of Fuels and Engines experience. The decision to form a consortium comes with benefits (in advancing challenging multidisciplinary research) and costs (in time and additional management funds). Once the decision is made, key elements to a strong start include establishing a shared vision and goals; engaging an experienced project manager early; instituting feedback and oversight mechanisms to ensure relevance, strong performance, and situational awareness. Once a consortium is up and running, DOE and leadership should strike the right balance between competition and collaboration; foster an environment that builds trust; and adjust the organizational structure as needed to maintain collaboration. Finally, DOE and the labs can plan effectively for a smooth transition as a consortium winds down. This report provides some additional lessons and details on these lessons that we hope future DOE and lab leaders will find useful as they contemplate standing up new consortia.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A machine learning approach for identifying variables associated with risk of developing neutralizing antidrug antibodies to factor VIII

A key unmet need in the management of hemophilia A (HA) is the lack of clinically validated markers that are associated with the development of neutralizing antibodies to Factor VIII (FVIII) (commonly referred to as inhibitors). This study aimed to identify relevant biomarkers for FVIII inhibition using Machine Learning (ML) and Explainable AI (XAI) using the My Life Our Future (MLOF) research repository. The dataset includes biologically relevant variables such as age, race, sex, ethnicity, and the variants in the F8 gene. In addition, we previously carried out Human Leukocyte Antigen Class II (HLA-II) typing on samples obtained from the MLOF repository. Using this information, we derived other patient-specific biologically and genetically important variables. These included identifying the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity calculated using NetMHCIIpan. The data were processed and trained with multiple ML classification models to identify the top performing models. The top performing model was then chosen to apply XAI via SHAP, (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patient. Using XAI we provide a robust and ranked identification of variables that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. These variables could be validated as biomarkers and used in making clinical decisions and during drug development. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles), (iv) the minimum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.

60 APPLIED LIFE SCIENCES↗

Root exudate composition reflects drought severity gradient in blue grama (Bouteloua gracilis)

Abstract Plant survival during environmental stress greatly affects ecosystem carbon (C) cycling, and plant–microbe interactions are central to plant stress survival. The release of C-rich root exudates is a key mechanism plants use to manage their microbiome, attracting beneficial microbes and/or suppressing harmful microbes to help plants withstand environmental stress. However, a critical knowledge gap is how plants alter root exudate concentration and composition under varying stress levels. In a greenhouse study, we imposed three drought treatments (control, mild, severe) on blue grama ( Bouteloua gracilis Kunth Lag. Ex Griffiths), and measured plant physiology and root exudate concentration and composition using GC–MS, NMR, and FTICR. With increasing drought severity, root exudate total C and organic C increased concurrently with declining predawn leaf water potential and photosynthesis. Root exudate composition mirrored the physiological gradient of drought severity treatments. Specific compounds that are known to alter plant drought responses and the rhizosphere microbiome mirrored the drought severity-induced root exudate compositional gradient. Despite reducing C uptake, these plants actively invested C to root exudates with increasing drought severity. Patterns of plant physiology and root exudate concentration and composition co-varied along a gradient of drought severity.

59 BASIC BIOLOGICAL SCIENCES↗

Finalizing Transition to the New Data Center at BNL

Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and Materials Science, as well as our participation in international research collaborations, such as the ATLAS Experiment at Europe's Large Hadron Collider (LHC) at CERN (Switzerland) and the Belle II Experiment at KEK (Japan). The construction of a new data center is an acknowledgement of the increasing demand for computing and storage services at BNL in the near term and enable the Lab to address the needs of the future experiments at the High-Luminosity LHC at CERN and the Electron-Ion Collider (EIC) at BNL in the long term. The Computing Facility Revitalization (CFR) project is aimed at repurposing the former National Synchrotron Light Source (NSLS-I) building as the new data center for BNL. The construction of the new data center was finished in 2021Q3, and it was delivered for production in early FY2022 for all collaborations supported by the Scientific Data and Computing Center (SDCC), including STAR, PHENIX and sPHENIX experiments at RHIC collider at BNL, the Belle II Experiment at KEK (Japan), and the Computational Science Initiative at BNL (CSI). This paper highlights the key mechanical, electrical, and networking components of the new data center in its final configuration as used in production since 2021Q4 and gives an overview for the extension of the central network systems into the new data center and the migration of a significant portion of IT load and services from the old data center to the new data center carried out in 20212023, with expected completion of the main phase of the gradual IT equipment replacement and migration from the old data center into the new one set to the end of FY2023 (Sep 30, 2023).

99 GENERAL AND MISCELLANEOUS↗

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗

Axom

Axom is an open-source library of "building block" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.

Zagaris, George↗

Programmatic Equipment Procurement: An Improved System for Coordinating the Procurement of New Programmatic Equipment

A better structured system that outlines the communication required between the Project Manager (PM) and all the Key Stakeholders. This system will help the PM work with the SMEs to define the scope of the equipment to be procured. It will also help the PM confirm that all associated key stakeholders (WCI IT, FPOC, etc.) have been contacted and have reviewed the new equipment being proposed to be procured. This step is crucial in order to confirm that the piece of equipment being procured not only meets the SME requirements but also the security, safety and building requirements on site. This is a step that is currently missed or overlooked and can cause delays in procurement after the piece of equipment has already been decided on. This new system should help mitigate any delays or miscommunication regarding the piece of equipment being procured.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States (2023 Edition)

Estimates of the potential of renewable energy are essential for understanding how we can decarbonize our electric grid and economy. They provide key data for policymakers, land managers, and energy modelers by defining the quantity, quality, and cost of renewable resources. However, estimating renewable energy potential is challenging and requires frequent updates because of rapid advances in technology, cost reductions, and uncertainty about developable land that are due to social, regulatory, and environmental factors. Additionally, the complex processes involved in renewable energy development require regular reviews of methods and assumptions, which can also impact our understanding of renewable potential. In this, the 2023 edition of this annual report, we present new estimates of the technical potential for land-based wind and solar photovoltaics (PV) for the contiguous United States (CONUS). We also provide cost estimates for the available resources, presenting representative supply curves that can be used in downstream modeling and analysis. Additionally, we introduce the new methodologies used to estimate wind capacity, wind energy losses, transmission cost and representation, updated technology cost and design, and scenarios of siting constraints designed to help bound the uncertainty of renewable potential.

14 SOLAR ENERGY↗

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). Here, this paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

aeronautics↗

Finalizing Construction of a New Data Center at BNL

Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source II (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and Materials Science, as well as our participation in international research collaborations, such as the ATLAS experiment at Europe's Large Hadron Collider (LHC) at CERN (Switzerland) and the Belle II experiment at KEK (Japan). The construction of a new data center is an acknowledgement of the increasing demand for computing and storage services at BNL in the near term and enable the Lab to address the needs of the future experiments at the High-Luminosity LHC at CERN and the Electron-Ion Collider (EIC) at BNL in the long term.

99 GENERAL AND MISCELLANEOUS↗

Geothermal Reserve Pits: Considerations for Installation on BLM-Administered Lands

Reserve pits, also known as sumps, are a common aspect of geothermal drilling operations. This paper describes the Bureau of Land Management's regulatory authorities and key environmental considerations associated with geothermal reserve pits. Reserve pit design, the need for environmental compliance measures, and reclamation approaches will vary depending on site-specific conditions. Groundwater and wildlife impacts are the most common environmental considerations related to reserve pits. In some cases, regulations or groundwater or soil conditions necessitate the use of a synthetic liner. However, the chemical composition of most geothermal drilling fluids and muds, completion fluids, and produced fluids that are discharged to reserve pits does not warrant pit liners. The potential for hazardous fluids, high water temperatures, and entrapment are concerns for wildlife. Common wildlife impact avoidance and mitigation measures include fencing, netting, and escape ramps. The need for these measures depends on localized site and environmental conditions. There are requirements to reclaim reserve pits following geothermal drilling operations. Reserve pits often remain in place to accommodate multiple phases of drilling and well testing. They are eventually backfilled and decommissioned.

BLM↗

Grid-Interactive Efficient Buildings Support Federal Facility Decarbonization

The Federal Energy Management Program (FEMP) plays a key role in helping agencies understand and meet energy-related goals, including those surrounding smart buildings technologies and grid-interactive efficient buildings (GEBs), which can support decarbonization. GEB enables demand flexibility that has the potential to reduce electrical infrastructure costs and transform the grid edge, where buildings connect to the power grid.

decarbonization↗

Comparing Legacy Waste Management to Advanced Reactor Waste Management

The Nuclear Energy Agency (NEA) and Natural Resources Canada (NRCan) are organizing an international workshop on the implementation of radioactive waste management and decommissioning strategies in small modular reactors (SMRs) and advance reactor technologies. The event will take place in Ottawa, Canada on 7-10 November 2022. The workshop will convene participants from various fields of expertise in the areas of radioactive waste management, decommissioning, nuclear science and development, transportation, as well as young professionals, communication experts and researchers. The goal of the workshop is to devise a guideline document that will serve implementers in understanding key issues in decommissioning and waste management of new reactors from the design perspective, aiding in the licensing process and in future decommissioning and waste management activities. DOE has invested considerably in the innovation of advanced reactors. Interaction in this workshop allows INL and DOE to articulate the importance of looking at the back-end of the fuel cycle for advanced reactors. The back-end of the fuel cycle is important to the success of advanced reactors, and DOE may need to manage this material in the future after it is discharged from reactors. I have been asked to present at the track titled "Operational and Design Optimization Consideration Related to Decommissioning and Radioactive Waste Management for SMRs/Advanced Reactors".

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Blockchain and PKI-Based Secure Vehicle-to-Vehicle Energy-Trading Protocol

With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.

Stackelberg game↗

Li-Ion Battery Thermal Characterization for Thermal Management Design

Battery design efforts often prioritize enhancing the energy density of the active materials and their utilization. However, optimizing thermal management systems at both the cell and pack levels is also key to achieving mission-relevant battery design. Battery thermal management systems, responsible for managing the thermal profile of battery cells, are crucial for balancing the trade-offs between battery performance and lifetime. Designing such systems requires accounting for the multitude of heat sources within battery cells and packs. This paper provides a summary of heat generation characterizations observed in several commercial Li-ion battery cells using isothermal battery calorimetry. The primary focus is on assessing the impact of temperatures, C-rates, and formation cycles. Moreover, a module-level characterization demonstrated the significant additional heat generated by module interconnects. Characterizing heat signatures at each level helps inform manufacturing at the design, production, and characterization phases that might otherwise go unaccounted for at the full pack level. Further testing of a 5 kWh battery pack revealed that a considerable temperature non-uniformity may arise due to inefficient cooling arrangements. To mitigate this type of challenge, a combined thermal characterization and multi-domain modeling approach is proposed, offering a solution without the need for constructing a costly module prototype.

25 ENERGY STORAGE↗