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At least 379 records · Page 21

Tough Errors Are no Match (TEAM): Optimizing the quantum compiler for noise resilience

This report summarizes Unitary Fund’s contributions to the Department of Energy’s TEAM project (DE-SC0020266) under Thrust 2: Quantum Programming and Compilation. The central outcomes of this work have been the development of Mitiq, an open-source Python toolkit for applying quantum error mitigation (QEM) techniques to noisy quantum programs, and the invention, benchmarking and theoretical investigation of novel QEM techniques. Additional outcomes include the development of other open source software packages for the usage, simulation and control of quantum computers.

97 MATHEMATICS AND COMPUTING↗

Grain2Mesh: Mesh Generation for Grain-Scale Nonlinear Elasticity Modeling

The nonlinear hysteretic behavior of rocks under cyclic loading is a crucial area of study in geomechanics. The macroscopic response of a variety of materials has been found to be contingent upon the behavior of the micro-scale structure. This project aims to develop a functional and maintainable software package for generating a multi-phase numerical mesh and accompanying simulation files for finite element modeling used in computational mechanics solvers. Meshes generated from images often lack key preprocessing that reduces noise and prevents mesh element distortion that can increase computational cost. By incorporating user feedback throughout, grain2mesh ensures a high-fidelity mesh that can be used to model grain-scale interactions such as shearing, crack propagation, and interfacial material contrast. Scientific applications of this software include material fracturing, stress-strain analysis for natural and engineered materials, and nonlinear meso-scale analysis.

54 ENVIRONMENTAL SCIENCES↗

COMSOL Results for the Nominal Steady-State Operation of the Proposed 95-MW LEU Silicide Core for HFIR Conversion

Engineering design studies are being performed to determine the feasibility of converting the High Flux Isotope Reactor (HFIR) from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel at Oak Ridge National Laboratory. This activity is sponsored by the Office of Reactor Conversion and Uranium Supply (ORCUS) under the auspices of the US Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization. HFIR is a very high flux, pressurized, light water–cooled and moderated, flux trap–type research reactor with a core made of involute shaped U 3 O 8 /Al cermet fuel plates and coolant channels. HFIR currently operates at a thermal power of 85 MW and supports key national and international missions in neutron scattering, isotope production, materials/fuels irradiation, neutron activation analysis, gamma irradiation, and neutrino research. Advanced multiphysics computational fluid dynamics models have been developed in the COMSOL Multiphysics software to simulate the steady-state operating conditions for the proposed low-and high-density LEU U 3 Si 2 -Al (uranium silicide dispersion) fuel designs. The COMSOL models for HFIR inner and outer fuel element models incorporate various essential inputs and physics such as spatially dependent nuclear heat deposition, multilayer heat conduction, conjugate heat transfer, turbulent flows (using Reynolds-averaged Navier Stokes turbulence models), structural mechanics (thermal–structural interactions and fuel swelling), and oxide layer build-up. This report presents the best-estimate thermal hydraulics results for the low- and high-density optimized silicide LEU core designs at 95 MW steady-state nominal operation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

REDESIGNING A PERFORMANCE MONITORING SOFTWARE FOR SUPERCOMPUTERS

The objective of this project was to improve upon the existing Watchr software that charts performance test metrics from the Trilinos project run on supercomputers at Sandia and elsewhere across the DOE complex. Software was iteratively designed and developed using Python Pandas and Dash data visualization to improve the extensibility and user experience of Watchr. Documentation is being maintained for future developers who want to extend the application.

Camacho, Dane Joseph [Sandia National Laboratories↗

Novel Tools for Analyzing Life Cycle Energy Use, Carbon Emissions, and Cost of Additive Manufacturing

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM.

GHG emissions↗

Novel Instrumentation for Advanced Quantum Chromodynamics Studies with Flavor Sensitivity

The true nature of ordinary matter has always fascinated humankind, whose imagination has been pointed to the right direction since the 5th century BC with the first known atomic theory by Leucippus and Democritus. They described the matter as formed by small, invisible, indivisible, and eternal particles: the atoms. A long investigation followed them, including contributions from several of history?s greatest philosophers and scientists. The progress led to the understanding that atoms have an internal structure consisting of a central nucleus composed of protons and neutrons, surrounded by a cloud of electrons. About 50 years ago, scientists discovered that nucleons also have an internal structure. Through the Deep Inelastic Scattering (DIS) experiments, on which a lepton is scattered off a nucleon, it was possible to access the distribution of partons inside the nucleon along the longitudinal direction defined by the hard-scale probe. It was a crucial step in developing Quantum Chromodynamics (QCD), currently the best theory describing the subatomic matter. Ultimately, DIS was recognized as a limited tool to investigate the nucleon structure because it is mainly sensitive to observables at the probe?s energy scale. In recent decades, theoretical developments have allowed defining soft-scale observables by measuring more complex processes. Reactions such as Semi-Inclusive Deep Inelastic Scattering (SIDIS) with single or di-hadron production, can provide information about the momentum of parton inside the nucleon. In particular, polarized SIDIS allows access to the Transverse-Momentum-Dependent (TMD) parton distributions describing the correlations of the quark and gluon degrees of freedom in transverse momentum and spin. This study can provide three-dimensional imaging of nucleon structure and inner dynamics, as long as the hadronic component in the final state can be measured. Identifying the species of the produced particles provides information on the quark flavor and assumes a crucial role in this context. The thesis describes the work carried out by the author in preparing novel instrumentation for particle identification in the final state of DIS experiments, to support modern analysis of the parton dynamics within the basic confined object (nucleon) with flavor sensitivity. The work has been focused on the CLAS12 spectrometer in operation at Jefferson Laboratory (JLab), Newport News, VA, USA, and the ePIC experiment in preparation for the future Electron-Ion Collider (EIC) at Brookhaven National Laboratory (BNL), Long Island, NY, USA. CLAS12 is a fixed-target experiment using a 12 GeV beam of polarized electrons scattering off polarized nuclear targets. In 2018 and 2022, two Ring Imaging Cherenkov (RICH) detector modules were installed to improve the ?±/K± separation in the high-momentum region (3÷8 GeV/c) of the experiment. The author contributed to the assembly, installation, and com- missioning of the second RICH module, to the efficiency studies of the first module, and to the first SIDIS analysis with high-momentum kaons identified by the RICH. These studies led to the observation of the first spin asymmetry with high-momentum kaons from the CLAS12 experiment, and an initial assessment of the systematic error associated with the hadron identification. ePIC will be the first experiment at the future EIC, the new collider designed to expand the frontiers of QCD. The author was involved in the development of the dual-radiator Ring Imaging Cherenkov (dRICH). This detector will interpolate the measurements of the Cherenkov angles of photons produced by relativistic particles crossing two different radiators to identify charged hadrons. The author contributed to the studies conducted with the dRICH prototype, developing the reconstruction and analysis software and simulations, characterizing the aerogel radiator samples, and being responsible for the tracking system used during the beam tests. The performance obtained by the prototype has been progressively improved and the results are now comparable with the expectation derived from the simulation and satisfy the requirements of the experiment. In Chapter 1, the SIDIS theory is briefly introduced, outlying the connection with the experimental measurement. Chapter 2 includes the description of the CLAS12 RICH, its assembly and installation, and the efficiency study. In Chapter 3, the analysis of the Beam-Spin Asymmetry associated with SIDIS kaons is described. Chapter 4 describes the contribution to the dRICH for EIC, starting from a description of the ePIC experiment and focusing on the studies performed for the dRICH prototype. The conclusions of this work are summarized at the end.

Vallarino, Simone↗

A Simulation and Optimization Framework for Managing Wind-Driven Loading on PV Systems

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. We are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software and present the latest outcomes from our ongoing validation campaign in which we compare statistical structural responses with field data. From there, we will present simulated results from a larger, multi-row array and highlight the effect of varying tracker angles on stability as measured by both acceleration and deformation, focusing on the stability differences between positive and negative tilt angles.

fluid structure interaction↗

Simulating Wind-Driven Loading on PV Systems

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on compliant solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. We are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within single-axis, solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software and present the latest outcomes from our ongoing validation campaign in which we compare time series and statistical structural responses with field data. From there, we will present simulated results from a larger, multi-row array and highlight the effect of varying tracker angles on stability and the differences between positive and negative tilt angles.

fluid↗

Economic and Jobs Impacts of Point-Source Carbon Capture in Cement Industry – Case Study

The cement industry accounts for an estimated 8% of global CO2 emissions, which surpasses that of the entire aviation sector. In contrast with other industries, where CO2 emissions can be drastically reduced via electrification or fuels substitution, cement production releases CO2 as part of its process, during the calcination of carbonates to yield oxides. Thus, point-source carbon capture has become a key technology in the cement industry’s decarbonization. Apart from the expected environmental benefits, point-source carbon capture in the cement industry can yield important economic benefits and create jobs. The objective of this study was to perform a preliminary assessment of the economic and workforce impacts associated with the construction and operation of a point-source carbon capture retrofit of an existing cement production facility, using as a basis the data from a front-end engineering design (FEED) study to install a 3.9 million metric tons per year (Mtpy) CO2 capture facility at Holcim Ste Genevieve cement plant in Missouri, United States of America. The advanced carbon capture technology used in this FEED study was Air Liquide’s Cryocap™ FG carbon capture technology. The study evaluated the direct, indirect, and induced economic impacts of the construction, operation, and maintenance activities of the project over its lifespan. It also covered how the project will generate new jobs, their nature, and quantity, along with strategies to prepare the workforce. To perform this study, construction, operation, and maintenance cost estimates, as well as construction and operation staffing plans from the FEED study were input into IMPLAN version 7.5 software, licensed by IMPLAN Group LLC (Huntersville, VC), to predict the direct, indirect and induced economic impacts of the project using industry multipliers from the software. Additionally, recruitment strategies were developed for hiring individuals who belong to groups that are historically underserved or underrepresented, as well as anticipated recruitment of workers from the local community (whether training will be required or if the skills are associated with an existing labor force). The analysis estimated that the construction and operation of the carbon capture at Holcim Ste. Genevive will result in over 24 thousand work-years of job opportunities, close to USD 10 billion of economic impacts, including over USD 460 million of tax revenue. These results encompass the direct, indirect, and induced effects. A strategy to maximize hiring from the project and neighboring counties was developed, leveraging training agreements with local trade groups and universities. The result of this study can be used for a strategic preliminary assessment of the potential regional economic and job impacts of retrofitting existing cement plants with point source carbon systems, and its methodology can be replicated to individual projects to aid in planning and workforce development.

01 COAL, LIGNITE, AND PEAT↗

Advancing \textit{otsdaq}: Enhancements for Usability, Accuracy, and Robustness

High-energy physics (HEP) experiments require data acquisition (DAQ) systems that can orchestrate complex detector operations, high data throughput, and responsive, real-time feedback to operators. Traditional DAQ stacks, which are often bespoke, command-line driven and highly specific, impose large learning curves on users. The Off-The-Shelf Data Acquisition (\textit{otsdaq}) framework was created to address these issues by offering a highly customizable and scalable browser-based ’desktop’ environment, in which experiment-specific control and monitoring applications can be easily deployed and integrated. Although the initial development of the \textit{otsdaq} software was aimed at the Fermilab Test Beam Facility, \textit{otsdaq} is now being leveraged for broader deployment, including the upcoming Mu2e experiment, where real-time monitoring of field-programmable gate array (FPGA)-based Data Transfer Controllers (DTCs), Clock and Fanout (CFO) boards, and several other subsystems are critical. We contribute a set of targeted improvements to \textit{otsdaq}: bitmap visualization functionality for configured data, improved and corrected delta-based DTC throughput metrics, version control (VC)-backed source navigation for console messages, custom navigation hooks to eliminate disruptive user interface glitches, and copy-to-clipboard support for macro execution history. These changes improve usability, reduce debugging time, and increase accuracy in performance data as Mu2e moves toward commissioning.

Mohammed, A. [Unlisted, US]↗

Bioreactor Optimization through Multi-Phase Flow Models (CRADA Final Report)

Chemical manufacturing uses 29% of energy in the United States and produces 925 million metric tons of CO2 annually. Biomanufacturing offers the potential to leverage America’s rich agricultural resources to produce critical chemicals such as lubricants, pharmaceutical precursors, and components of energetic materials that today are sourced extensively from overseas. The bioreactors used in biomanufacturing applications, such as one developed by Capra Biosciences, involve multiphase flow of biofilm-coated solid support particles that are continuously circulated in a fluidized state within the reactor along with a constant supply of oxygen via an aeration mechanism. In this project, Capra Biosciences and LBNL developed a multiscale modeling framework to simulate the multiphase flows of solid particles in a liquid-gas bubble mixture that occurs in the bioreactor using the current MFIX-Exa software, an opensource multiphase flow solver developed and maintained at LBNL and NETL. By leveraging HPC capabilities, this high-fidelity multiscale model was used to inform design decisions for bioreactor architecture to make them operationally efficient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Visualizing a Vulnerability: Its Connections to Hardware and Software

All Hazards Analysis (AHA) is a framework developed by Idaho National Laboratory that provides capabilities to collect, store, analyze, and visualize critical infrastructure information. A core function of AHA is its ability to simulate faults or outages in networks of infrastructure originating from a plethora of causes, ranging from natural disasters to cyberattacks. AHA utilizes Hardware and Software Bills of Material (HBOM and SBOM, respectively) along with Known Exploited Vulnerabilities (KEVs) to document the potential attack vectors for each piece of infrastructure. The objective of this contribution to AHA was to create a visualization tool that could capture the small details held in each individual artifact as well as preserve the large-scale connections that link them together to aid threat modeling.

58 GEOSCIENCES↗

“Frameworks, Algorithms and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute” (Final Technical Report)

SMU personnel formed a portion of the overall “Time Integration” team within the FASTMath SciDAC-5 Institute, and we interacted very closely with team members from collaborating institutions. The major goals of our team within the FASTMath institute may be categorized into two groups: the development of advanced and application-aware time integration methods and software, and close interactions with DOE application scientists to facilitate their use of these new methods and software. The two goals are intimately linked, since our research and development of novel tools is informed by the needs of our application partners, who in turn benefit from subsequent mathematical and software advances. While the SMU personnel collaborated with the rest of the Time Integration FASTMath team on most of our shared deliverables within the larger FASTMath institute, SMU personnel primarily contributed to the following subset of those goals: ● expanding capabilities for higher-order and solve-decoupled multirate methods, ● enhancing support for temporal adaptivity within multirate methods, and ● adding structure-aware time integration methods. Each of these goals focused both on intellectual contributions through journal articles or research presentations, and on enhancements to the open-source SUNDIALS library of time integrators and nonlinear solvers, of which the SMU PI Reynolds is a core developer.

97 MATHEMATICS AND COMPUTING↗

Integration of RNTuple in ATLAS Athena

After using ROOT’s TTree I/O subsystem for over two decades and storing more than an exabyte of compressed High Energy Physics (HEP) data, advances in technology have motivated a complete redesign, RNTuple, which breaks backward-compatibility to take better advantage of these storage options. The RNTuple I/O subsystem has been designed to address performance bottlenecks and other shortcomings of TTree. Specifically, RNTuple comes with an updated, more compact binary data format that can be stored both in ROOT files and natively in object stores. It is designed for modern storage hardware (e.g. high-throughput low-latency NVMe SSDs), and provides robust and easy to use interfaces. The binary format of RNTuple is scheduled to become production grade in 2024, and recently has become mature enough to start exploring the integration into software used by HEP experiments. In this contribution, we discuss the developments to support the features as required by the ATLAS analysis Event Data Model (EDM) in RNTuple, which will enable its integration into the Athena software framework. With these developments in place, we evaluate the performance of the current most recent versions of RNTuple-based ATLAS data sets and compare this to that of TTree.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Capability Enhancements for System-level thermal Hydraulic Modeling of Lead Fast Reactors

This project has focused on the use, assessment, and development of the SAS4A/SASSYS-1 (SAS) safety analysis software. Although SAS was originally intended as a safety analysis tool for Liquid Metal cooled Fast Reactors (LMFRs), which includes both Sodium Fast Reactors (SFRs) and Lead Fast Reactors (LFRs), the vast majority of its recent development and customization has been tailored to SFRs. In general, enhancements that are made to the software for SFRs are applicable to LFRs, however, the fuel composition and corrosive nature of lead requires careful consideration when performing safety analysis of an LFR. In this project an emphasis was placed on closing gaps that are associated with modeling LFRs using SAS. The principal objective of the project was to enhance the ability of SAS as a licensing tool for LFRs. This objective was to be accomplished through three tasks: 1) Enhance the ability of SAS to couple with external software; 2) Improve the underlying physics models in SAS, with priority given to models that are highly relevant to LFRs; 3) Extend the Verification and Validation (V&V) basis of the software

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Commercialization of a Non-Intrusive Optical (NIO) Technology to Measure Heliostat Optical Errors in Utility-Scale Concentrating Solar Power Plants: Final TCF Report

The drone-based Non-Intrusive Optical (NIO) Technology has been developed at NREL to allow for efficient and automated optical characterization of heliostats in Concentrating Solar Power (CSP) plants. For this project, the technology will be developed into a commercial tool package, including software and user-interface (UI), operations manual, and training and support services. The project team will partner with Tietronix to perform market assessment and stakeholder engagement, develop the tool package and business model, and perform data collection and analysis to demonstrate and refine the capabilities for use at a commercial plant. The team will collaborate with a commercial plant to conduct the data collection operations and provide optical error deliverables. The goal of the project is to advance the commercialization of the technology to a stage where a beta version can be demonstrated at additional commercial plants and developed into a licensable product.

14 SOLAR ENERGY↗

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗