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State Energy Program Operations Manual: 2022 Edition

The State Energy Program (SEP) Operations Manual is a reference tool for the SEP network of states and program officials within the U.S. Department of Energy. "States," when referred to in the manual, includes the 50 states, the District of Columbia, and the U.S. territories: American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, Puerto Rico, and the U.S. Virgin Islands. This manual contains information needed to administer the State Energy Program.

state energy program, state energy offices, territ↗

Application Characterization at Scale: Lessons learned from developing a distributed Open Community Runtime system for High Performance Computing

Since 2012, the U.S. Department of Energy’s X-Stack program has been developing solutions including runtime systems, programming models, languages, compilers, and tools for the Exascale system software to address crucial performance and power requirements. Fine grain programming models and runtime systems show a great potential to efficiently utilize the underlying hardware. Thus, they are essential to many X-Stack efforts. An abundant amount of small tasks can better utilize the vast parallelism available on current and future machines. Moreover, finer tasks can recover faster and adapt better, due to a decrease in state and control. Nevertheless, current applications have been written to exploit old paradigms (such as Communicating Sequential Processor and Bulk Synchronous Parallel processing). To fully utilize the advantages of these new systems, applications need to be adapted to these new paradigms. As part of the applications’ porting process, in-depth characterization studies, focused on both application characteristics and runtime features, need to take place to fully understand the application performance bottlenecks and how to resolve them. This paper presents a characterization study for a novel high performance runtime system, called the Open Community Runtime, using key HPC kernels as its vehicle. This study has the following contributions: one of the first high performance, fine grain, distributed memory runtime system implementing the OCR standard (version 0.99a); and a characterization study of key HPC kernels in terms of runtime primitives running on both intra and inter node environments. Running on a general purpose cluster, we have found up to 1635x relative speed-up for a parallel tiled Cholesky Kernels on 128 nodes with 16 cores each and a 1864x relative speed-up for a parallel tiled Smith-Waterman kernel on 128 nodes with 30 cores.

Application characterization↗

Omics Tools

The Omics Tools package provides several small trivial tools for work in genomics. This single portable package, the “omics.jar” file, is a toolbox that works in any Java-based environment, including PCs, Macs, and supercomputers. The number of tools is expected to grow. One tool (called cmsearch.hadoop or cmsearch.local), calls the external cmsearch program to predict non-coding RNA in a genome. The cmsearch program is part of the third-party Infernal package. Omics Tools does not contain Infernal. Infernal may be installed separately. The cmsearch.hadoop subtool requires Apache Hadoop and runs on a supercomputer, though cmsearch.local does not and runs on a server. Omics Tools does not contain Hadoop. Hadoop mat be installed separartely The other tools (cmgbk, cmgff, fastats, pal, randgrp, randgrpr, randsub) do not interface with third-party tools. Omics Tools is written in Java and Scala programming languages. Invoking the “help” command shows currently available tools, as shown below: schaumbe@gpint06:~/proj/omics$ java -jar omics.jar help Known commands are: cmgbk : compare cmsearch and GenBank Infernal hits cmgff : compare hits among two GFF (version 3) files cmsearch.hadoop : find Infernal hits in a genome, on your supercomputer cmsearch.local : find Infernal hits in a genome, on your workstation fastats : FASTA stats, e.g. # bases, GC content pal : stem-loop motif detection by palindromic sequence search (code stub) randgrp : random subsample without replacement, of groups randgrpr : random subsample with replacement, of groups (fast) randsub : random subsample without replacement, of file lines For more help regarding a particular command, use: java -jar omics.jar command help Usage: java -jar omics.jar command args

Schaumberg, Andrew↗

Caravel: A C++ framework for the computation of multi-loop amplitudes with numerical unitarity

We present the first public version of Caravel, a C++17 framework for the computation of multi-loop scattering amplitudes in quantum field theory, based on the numerical unitarity method. Caravel is composed of modules for the D-dimensional decomposition of integrands of scattering amplitudes into master and surface terms, the computation of tree-level amplitudes in floating point or finite-field arithmetic, the numerical computation of one- and two-loop amplitudes in QCD and Einstein gravity, and functional reconstruction tools. Here, we provide programs that showcase Caravel's main functionalities and allow to compute selected one- and two-loop amplitudes.

97 MATHEMATICS AND COMPUTING↗

Physical Security Timeline Analysis in Support of Advanced Reactor Demonstration and Deployment

This report presents the regulatory requirements and directions on the physical security of advanced nuclear reactors in USA. Presently, a rule is being proposed that allows for a performance-based analysis. In determining the physical security requirements for an advanced reactor, new tools may be desired to conduct a performance-based analysis. These tools should incorporate dynamic analysis methods to provide as much realism as possible. In comparison, the security requirements for existing light water reactors (LWRs) are much more prescriptive and the analysis conducted to establish the required physical security strategies were more easily performed with static analysis. In order to achieve the cost goals that advanced reactors require for adoption; the nuclear security force required should not be excessive. Dynamic physical security analysis methods and tools have been developed by the US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program. This report details how the dynamic risk analysis tools developed in the LWRS program using the dynamic risk modelling tool, EMRALD, may be adapted for use in analyzing the physical security designs for advanced reactors accounting for variable performance-based requirements. This report provides an example analysis of a hypothetical SFR using publicly available information and generic assumptions to demonstrate the methods and potential presentation and analysis of the results. No actual plant information is used in this example analysis. Future work in this area will create additional models that can be adapted for any advanced reactor concept and use various security features to create a physical security system that provides adequate protection from radiological theft and sabotage.

97 MATHEMATICS AND COMPUTING↗

An introduction to PYTHIA 8.2

The Pythia program is a standard tool for the generation of events in high-energy collisions, comprising a coherent set of physics models for the evolution from a few-body hard process to a complex multiparticle final state. It contains a library of hard processes, models for initial- and final-state parton showers, matching and merging methods between hard processes and parton showers, multiparton interactions, beam remnants, string fragmentation and particle decays. It also has a set of utilities and several interfaces to external programs. Pythia 8.2 is the second main release after the complete rewrite from Fortran to C++, and now has reached such a maturity that it offers a complete replacement for most applications, notably for LHC physics studies. The many new features should allow an improved description of data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Tools and Methods for Optimization of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plants (NPP) operating cycle. Refueling outages are extremely costly for a NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities in a duration of around 30 days on average. Outage staff begin working on the schedule more than a year ahead of the outage start and make every effort to build a robust schedule. Despite the robust and detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjusting. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. The Optimization of Outage Activities project under the Risk-Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program focuses on developing tools and methods to support nuclear power plants with optimization of outage schedules. The goal of the outage optimization is the completion of all planned and emergent outage activities as fast as possible while maintaining highest level of safety. This report describes the initial development of tools to support outage management that leverage computational and machine learning methods developed in other RISA and LWRS projects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Summary Report Of The FY25 Reactor Physics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Valdiation and verification of numerical tools is critical for ensuring reasonable predictions for design scoping, licensing, and safety analsyis. In this report, two reactor physics verification and validation exercises are presented. The first of these exercises focuses on burnup analysis with data from the Advanced Gas Reactor (AGR) program. Simulations are performed with Monte Carlo N-Particle (MCNP) and are compared with the experimental measurements for the AGR 1 and 2 experiments that utilize both UCO and UO2 fuel. The second exercises utilizes data from the HTR-Proteus experiments to perform reactor physics validation. Specifications of the experimental facility are provdied, along with a demonstration of initial modeling efforts in Serpent for one of the determistic packing experiments. Both cases are part of the Generation-IV international forum (GIF) Very High-Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) program, an international collaborative organization dedicated to the verification and validation of High-Temperature Gas-Cooled Reactor (HTGR) analysis. Participation in the CMVB allows the US Department of Energy (DOE) to leverage these existing validation activities to provide extra value through benchmarking activities with other CMVB members.

and Benchmarking (CMVB) program↗

SU-E-T-595: Design of a Graphical User Interface for An In-House Monte Carlo Based Treatment Planning System: Planning and Contouring Tools

Purpose: An in-house Monte Carlo based treatment planning system (MC TPS) has been developed for modulated electron radiation therapy (MERT). Our preliminary MERT planning experience called for a more user friendly graphical user interface. The current work aimed to design graphical windows and tools to facilitate the contouring and planning process. Methods: Our In-house GUI MC TPS is built on a set of EGS4 user codes namely MCPLAN and MCBEAM in addition to an in-house optimization code, which was named as MCOPTIM. Patient virtual phantom is constructed using the tomographic images in DICOM format exported from clinical treatment planning systems (TPS). Treatment target volumes and critical structures were usually contoured on clinical TPS and then sent as a structure set file. In our GUI program we developed a visualization tool to allow the planner to visualize the DICOM images and delineate the various structures. We implemented an option in our code for automatic contouring of the patient body and lungs. We also created an interface window displaying a three dimensional representation of the target and also showing a graphical representation of the treatment beams. Results: The new GUI features helped streamline the planning process. The implemented contouring option eliminated the need for performing this step on clinical TPS. The auto detection option for contouring the outer patient body and lungs was tested on patient CTs and it was shown to be accurate as compared to that of clinical TPS. The three dimensional representation of the target and the beams allows better selection of the gantry, collimator and couch angles. Conclusion: An in-house GUI program has been developed for more efficient MERT planning. The application of aiding tools implemented in the program is time saving and gives better control of the planning process.

60 APPLIED LIFE SCIENCES↗

ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creating a collection of reliable, highly specialized, and optimized AI assistants for HPC based on the cost-effective and fast Code Llama fine-tuning processes and expert supervision. We target major components of the HPC software stack, including programming models, runtimes, I/O, tooling, and math libraries. Thanks to AI, ChatHPC provides a more productive HPC ecosystem by boosting important tasks related to portability, parallelization, optimization, scalability, and instrumentation, among others. With relatively small datasets (on the order of KB), the AI assistants, which are created in a few minutes by using one node with two NVIDIA H100 GPUs and the ChatHPC library, can create new capabilities with Meta’s 7-billion parameter Code Llama base model to produce high-quality software with a level of trustworthiness of up to 90% higher than the 1.8-trillion parameter OpenAI ChatGPT-4o model for critical programming tasks in the HPC software stack.

Young, Aaron [ORNL] (ORCID:0000000254484667)↗

cclib 2.0: An updated architecture for interoperable computational chemistry

Interoperability in computational chemistry is elusive, impeded by the independent development of software packages and idiosyncratic nature of their output files. The cclib library was introduced in 2006 as an attempt to improve this situation by providing a consistent interface to the results of various quantum chemistry programs. The shared API across programs enabled by cclib has allowed users to focus on results as opposed to output and to combine data from multiple programs or develop generic downstream tools. Initial development, however, did not anticipate the rapid progress of computational capabilities, novel methods, and new programs; nor did it foresee the growing need for customizability. Here, we recount this history and present cclib 2, focused on extensibility and modularity. We also introduce recent design pivots—the formalization of cclib’s intermediate data representation as a tree-based structure, a new combinator-based parser organization, and parsed chemical properties as extensible objects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Business Value of Superior Energy Performance

Industrial facilities participating in the U.S. Department of Energy’s (US DOE) Superior Energy Performance (SEP) program are finding that it provides them with significant business value. This value starts with the implementation of ISO 50001-Energy management system standard, which provides an internationally-relevant framework for integration of energy management into an organization’s business processes. The resulting structure emphasizes effective use of available data and supports continual improvement of energy performance. International relevance is particularly important for companies with a global presence or trading interests, providing them with access to supporting ISO standards and a growing body of certified companies representing the collective knowledge of communities of practice. This paper examines the business value of SEP, a voluntary program that builds on ISO 50001, inviting industry to demonstrate an even greater commitment through third-party verification of energy performance improvement to a specified level of achievement. Information from 28 facilities that have already achieved SEP certification will illustrate key findings concerning both the value and the challenges from SEP/ISO 50001 implementation. These include the facilities’ experience with implementation, internal and external value of third-party verification of energy performance improvement; attractive payback periods and the importance of SEP tools and guidance. US DOE is working to bring the program to scale, including the Enterprise-Wide Accelerator (SEP for multiple facilities in a company), the Ratepayer-Funded Program Accelerator (supporting tools for utilities and program administrators to include SEP in their program offerings), and expansion of the program to other sectors and industry supply chains.

McKane, Aimee↗

Solar Energy Technologies Office Workforce Request for Information and Convenings (Summary)

On May 4, 2021, the U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO) published a Request for Information (RFI) on programs that support the development of a diverse and skilled clean energy workforce. The purpose of the RFI was to solicit feedback from industry, academia, government agencies, worker organizations (including unions), and other stakeholders on issues related to the employment needs of the solar industry, and the perceived value of different workforce development programs, training strategies, and tools. To supplement the RFI, SETO hosted four virtual convenings that brought together the utility-scale solar industry, the distributed generation solar industry, and labor and other workforce training organizations to hear direct feedback on the questions in the RFI. In addition, SETO held listening sessions with about a dozen other organizations and staff who could not participate in the virtual convenings. Altogether, SETO received 45 responses from the RFI and heard directly from 80-100 other stakeholders via the convenings and listening sessions. This document summarizes the stakeholder feedback that SETO received as a result of this process. While both the RFI and convening series were focused on solar deployment and solar industry members, much of this information is relevant across clean energy technologies and programs. It is important to recognize that DOE is intentionally reviewing our workforce development programming and support to focus on clean energy careers more holistically.

14 SOLAR ENERGY↗

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗

Advanced dismantling techniques applied in an industrial project for the dismantling of highly activated equipment - 15446

Commissioned in 1958 on the CEA nuclear site of Marcoule (France) and shut down in 1997, the former UP1 plant was dedicated to reprocess the spent fuel from G1, G2 and G3 GCR reactors. Since 1998, a wide program for cleaning-up and dismantling the plant has been developed in order to dismantle the process equipment, eliminate any radiological risk in all buildings concerned and remove all the resulting waste. Major technical challenges are related to the wide range of complex components and equipment in the facilities such as chemical dissolvers, extractor batteries, evaporators, tanks; and to a high risk of exposure, due to the presence of fission products. To address these challenges, CEA led R and D programs to develop advanced tools for complex dismantling projects: immersive virtual reality, laser cutting techniques, special remote-controlled arms combining dexterity and high resistance to irradiation The purpose of this paper is to provide an overview of a practical implementation and to show first results of these advanced techniques on a real case: the dismantling of dissolver's equipment from the dissolution workshop of UP1 plant. ONET Technologies has been chosen by CEA to design, build and operate the overall dismantling and waste treatment system for this project. ONET Technologies designed two main subsystems to meet all the requirements for this project: first, the 'Remotely-Operated Handling and Cutting Unit' and second the 'Waste Extraction and Conditioning Unit' and the combining innovative technologies. During the design phase, the 'Immersive Virtual Reality' has been used to qualify the kinematics in the final environment and the preliminary dismantling scenario. Following a first R and D program of CEA regarding the laser cutting technique applied to nuclear decommissioning, ONET Technologies and CEA realized elementary inactive tests based on a 6 kW Nd-Yag laser source to qualify the cutting performance according to material and thickness. Main objective was to meet the safety criteria and to check the physical characteristics of waste resulting from the laser cutting operation. The Remotely-Operated Handling and Cutting Unit was equipped with a MAESTRO manipulator, resulting from ten years of research and development cooperation between CEA and Cybernetix. This manipulator, a 6 axis hydraulic manipulator-arm specifically designed to work in harsh environment, entered in its industrial phase. ONET Technologies was responsible for the overall system integration, confinement and performance. A comprehensive qualification program in real conditions has been driven during 2014. The dismantling scenario was tested with a mockup at a full scale of dissolver equipment and confirmed at this stage the expected level of performance and safety. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Diagnosing and Destroying Non-Markovian Noise

Nearly every protocol used to analyze the performance of quantum information processors is based on an assumption that the errors experienced by the device during logical operations are constant in time and are insensitive to external contexts. This assumption is pervasive, rarely stated, and almost always wrong. Quantum devices that do behave this way are termed "Markovian:' but nearly every system we have ever probed has displayed drift or crosstalk or memory effects they are all non-Markovian. Strong non-Markovianity introduces spurious effects in characterization protocols and violates assumptions of the fault-tolerance threshold theorems. This SAND report details a three year laboratory-directed research and development (LDRD) project entitled, "Diagnosing and Destroying non-Markovian Noise in Quantum Information Processors." This program was initiated to build tools to study non-Markovian dynamics and quantum systems and develop robust methodologies for eliminating it. The program achieved a number of notable successes, including the first statistically rigorous protocol for identifying and characterizing drift in quantum systems, a formalism for modeling memory effects in quantum devices, and the successful suppression of drift in a Sandia trapped-ion quantum processor.

97 MATHEMATICS AND COMPUTING↗

Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity

The 2018 Basic Research Needs Workshop on Extreme Heterogeneity identified five Priority Research Directions for realizing the capabilities needed to address the challenges posed in this era of rapid technological change. This report captures the outcomes of that workshop. In the context of extreme heterogeneity, it defines basic research needs and opportunities in computer science research to develop smart and trainable operating and runtime systems, programming environments, and predictive tools that will make future systems easier to adapt to scientists’ computing needs and easier for facilities to deploy securely.

97 MATHEMATICS AND COMPUTING↗