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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43

Optimization of the size and shape of the scanning aperture in autocollimator-based deflectometric profilometers

Deflectometric profilometers based on industrial electronic autocollimators (ACs), as the ELCOMAT-3000, have become indispensable tools for precision form measurements of optical surfaces. A growing number of labs at synchrotron and free electron laser x-ray facilities are going for BESSY-II NOM-like versions of the AC-based profilometers. These tools have proven capable of characterizing state-of-the-art aspherical x-ray optics with an accuracy on the level of 100 nrad (root-mean-square) over the spatial frequency range limited by the size of the aperture used in the profilometer. Normally, a round aperture with a diameter of about 2.5 mm is used. Previous investigations have shown that with the optimally aligned 2.5-mm aperture, the spatial resolution of a NOM-like profilometer corresponding to the first zero-crossing of the optical transform function (OTF) is ~1.2 mm. In this paper, we investigate the performance of an AC ELCOMAT-3000 for a slope profilometer with different aperture sizes and shapes. The results of angular calibration of the AC equipped with circular and rectangular apertures placed at different distances from the AC are discussed. The calibration was performed at the Physikalisch-Technische Bundesanstalt using the original experimental arrangements, also discussed in the paper. The OTF measurements with the specially developed test sample with chirped surface slope profiles were performed at the Advanced Light Source X-Ray Optics Laboratory (XROL) in application to a new optical surface measuring system under development at the XROL. In the OTF measurements, we have shown that application of a rectangular aperture with dimensions of 1.5 mm × 3 mm improves the spatial resolution in the tangential direction by a factor of ~1.4 compared to that of the standard circular aperture of 2.5-mm diameter. We postulate that the conclusions of our investigations are crucial for reaching fundamental metrological limits in deflectometric profilometry utilizing state-of-the-art electronic autocollimators.

47 OTHER INSTRUMENTATION↗

Understanding spectral dependance of laser-induced damage precursors in dielectric materials (Abbreviated report_23-ERD-006)

High peak and average power laser systems are typically limited by the handling fluence of the optical components. In particular, the multilayer dielectric coatings are known to be much lower operational fluence than the more ideal bulk materials. In this project we proposed and succeeded in probing different established classes of damage prone precursors at different wavelengths to understand their fundamental laser damage response as a function of wavelength. This study helped to shed light on the fundamental physics of the non-linear precursors that govern laser damage phenomena for ns-regime pulsed laser damage. In this study, we utilized the onsite coating capabilities (VPL, IBS coating lab) to purposefully generate laser damage-prone precursors in hafnia-based coatings (both single and multi-layer coatings). Specifically, we engineered coatings with craze lines initiated by nodules, generated coatings with our xenon-based coating process to suppress nanobubble formation and generated hafnia coatings under controlled oxygen flow conditions to study hafnia sub-oxides and oxygen flow dependance. In these studies we found that craze lines are rife with precursors that are sensitive to ultra-violet light but not to infrared light; we found that the removal of nanobubbles helps with all wavelengths tested, but is most impactful for ultra-violet light; we also found that ultra-violet laser damage performance of hafnia is closely matched to oxygen flow rate, while the infrared performance may be slightly better at lower flow rates. During this LDRD we also successfully stood up a new laser damage testing capability, namely a wavelength agile damage test station to study the spectral response of known laser-induced damage precursors. This is a unique and important capability for Lawrence Livermore National Lab, allowing us to understand the spectral response of materials under high intensity irradiation and damage. This is a vital tool to understand non-linear optical response at wavelengths that we have previously been unable to test at.

36 MATERIALS SCIENCE↗

Time-Based CAN IDS Paper Results Code

Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these “distribution-agnostic” based methods outperform “distribution-based” methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.

Moriano, Pablo [Oak Ridge National Lab. (ORNL), Oa↗

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies, software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.

54 ENVIRONMENTAL SCIENCES↗

MEASUR - Manufacturing Energy Assessment Software for Utility Reduction

MEASUR your energy savings with the free DOE MEASUR software The Department of Energy (DOE), with Oak Ridge National Laboratory (ORNL), released version 1.0 of their energy efficiency software tool MEASUR (Manufacturing Energy Assessment Software for Utility Reduction). MEASUR has been available for several years as a beta version, being tested by industry experts and real users, and will continue to be updated and improved in the coming years. It is an integrated suite of tools to aid manufacturers in improving the efficiency of energy systems and equipment within a plant, including motors, pumps, fans, process heating, steam, and compressed air. Additionally, there are modules for wastewater energy analysis and to help perform energy treasure hunts. Several calculators are also included, allowing users to independently perform smaller calculations and analyses (such as estimating pump head, performing a fan traverse analysis, estimating waste heat recovery potential, and cataloging compressed air leaks). The MEASUR modules are based on previous DOE software tools that have been used by industry since the early 2000s (such as MotorMaster, AirMaster+, PSAT, PHAST, and FSAT). The original tools only ran on Windows operating systems, and by Windows 10, most of them were inoperable. DOE started their energy efficiency software tool revitalization effort in 2016, first with PSAT (for pumps), then began to integrate the other tools and expand their functionality and utility. The new MEASUR suite provides an extensively more user-friendly, modern, and versatile set of tools. All the assessment modules and most of the calculators have several visual components and graphs and detailed help text for every user input. To help reach international users, the tool utilizes Google translate and users can easily change unit systems, even converting existing user inputs if desired. The assessment files can be organized within the internal file system and easily shared to other users, regardless of their operating system. The entire suite is free, open-source, and can be downloaded on Windows, Mac, or Linux operating systems.

Accawi, Gina [Oak Ridge National Lab. (ORNL), Oak ↗

Probing Electron Correlations in 1D Electronic Materials Using Single Quantum Channels (Final Technical Report)

This research focuses on the investigation of strong electron correlations in quasi-one-dimensional oxide nanostructures. The archetypical system consisting of heterostructures formed from an ultrathin layer of LaAlO 3 and TiO 2 -terminated SrTiO 3 offers a unique laboratory for probing strong correlations due to intrinsic richness of the physical system and its ability to be modulated at extreme nanoscale dimensions. Under suitable conditions, SrTiO 3 is known to exhibit a variety of important properties associated with strong electronic correlations, especially superconductivity, magnetism. Understanding the nature of these electronic correlations at fundamental scales, and in reduced spatial dimensions, will provide the scientific basis for new energy technologies, information technologies, and materials. The research program is motivated by recent discoveries and technical advances in the PIs' lab, specifically, (1) pioneering work to create conductive nanostructures to be created in LaAlO 3 /SrTiO 3 heterointerfaces with 2 nm spatial resolution, (2) the discovery of a novel correlated electronic phases in which electrons pair without forming a superconductor, and (3) the demonstrated ability to form high-quality quantum point contacts (QPCs) and achieve ballistic electron transport over micrometer-scales in LaAlO 3 /SrTiO 3 nanowires. The program has three major components. First, we have press forward to develop a full microscopic understanding of the mechanism for electron pairing in LaAlO 3 /SrTiO 3 nanostructures. Understanding the “glue” that leads to pairing and superconductivity in a doped semiconductor will help to form a scientific basis for the correlated oxide nanoelectronics platform being developed. Second, we have used their ability to create well-defined quantum channels in nanowires allows to allow novel “scattering” experiments to be performed that probe fundamentally new quasiparticle excitations using an unprecedented combination of experimental methodologies. Experiments already underway with artificially defined superlattices (5 nm period) demonstrate the feasibility of this approach. Third, we have investigated 1D correlations in proximally coupled nanowires, which are predicted exhibit Majorana-like zero modes in the absence of superconductivity or spin-orbit coupling. These studies provide insight not only into new and emergent phenomena in the rich class of complex oxides, but also fundamental mechanisms of superconductivity and magnetism. Thematically, the research aims to combine some of the most important and interesting challenges in the physics of semiconductor nanostructures and correlated electronic materials. The increased understanding of electron correlations can pave the way to the development of new materials with outstanding or novel properties, which could be relevant for energy-related technologies such as low-power high performance computing, quantum computation, or the development of novel materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analysis of Transformer Magnetizing Reactance Using Describing Function in Direct Power Control of Back-to-Back Modular Multilevel Converter with Advanced Grid Support

This paper presents a Port Controlled Hamiltonian based direct power control architecture for a back-to-back modular multilevel converter system connecting two ac sources at different frequencies. The system features advanced grid support functionalities based on IEEE 1547-2018, implemented on the inverter side. The rectifier side controller ensures reference following for active and/or reactive powers and maintains the commanded dc bus voltage. The inverter side controller ensures power command following for active and reactive powers.The proposed control architecture is designed to suppress second harmonic oscillations in powers during unbalanced grid voltage sags by dynamically adjusting the currents on each ac side. This also ensures effective elimination of any second harmonic oscillations in the equivalent dc bus voltage. Validation is performed on an OPAL-RT real-time platform with case studies on unbalanced and balanced sags, demonstrating the controller's effectiveness during real time implementation. A reduced-scale laboratory prototype further verifies these case studies, with experimental results for balanced sags due to grid simulator limitations. The results confirm the robustness and efficiency of the proposed control strategy in ensuring stable and reliable operation under various grid conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Materials for Advanced Ultra-Supercritical (AUSC) Steam Turbines – AUSC Component Demonstration

The work by the United States Department of Energy (U.S. DOE)/Ohio Coal Development Office (OCDO) Advanced Ultra-Supercritical (AUSC) Steam Boiler and Turbine Materials Consortia from 2001 through September 2015 was primarily focused on lab scale and pilot scale materials testing. The field testing included air-cooled probes and steam-cooled “loops” that were installed into existing utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion due to the constituents in the coal ash. Successful research and development resulted in identification of metallic alloy materials and fabrication processes suited for power generation applications with metal temperatures up to approximately 1472°F (800°C). These materials or alloys have shown, in extensive laboratory tests and shop fabrication studies, to have excellent applicability for high-efficiency low CO2 transformational power generation technologies. However, as valuable as these material field tests have been for obtaining information, their scale is significantly below that required to minimize the risk associated with a power company building a multi-billion-dollar AUSC power plant. To decrease the identified risk barriers to full-scale implementation of these advanced materials, the U.S. DOE/OCDO AUSC Steam Boiler and Turbine Materials Consortia identified the key areas of the technology that need to be tested at a larger scale. Based upon the recommendations and outcome of a Consortia-sponsored workshop with the U.S.’s leading utilities, a Component Test (ComTest) Program for AUSC was proposed. The AUSC ComTest program would define materials performance requirements, plan for overall advanced system integration, design critical component tests, fabricate components for testing from advanced materials, and carry out the tests. A Pre-FEED evaluation of the test facility including the evaluation of three potential sites has been completed and previously reported. This report describes the Front-End Engineering Design (FEED), Detailed Engineering and the Environmental Assessment of the ComTest project. A significant amount of work was accomplished during Phase 1 to identity the components, as well as the component size, that would be manufactured from advanced alloys such as INCONEL 740H or HAYNES 282 alloys. Pathways to supply these components for ComTest have been identified as well as any further development that would be required. Every project of this nature has challenges and this project was no exception. The greatest challenge has been the project cost. Largely due to the infrastructure and balance of plant equipment upgrades required for Youngstown Thermal, the estimated project cost for the “base case” project was greater than originally budgeted. The project team spent a significant amount of time exploring opportunities for reducing the project cost. These options included: • Youngstown Thermal was exploring building a Combined Heat and Power (CHP) unit at their facility. The Youngstown Thermal staff, supported by Thermal Engineering Group, worked with the project team to determine whether it was economically desirable to supply ComTest with steam and other utilities, which would be supplied by the CHP project. • The project team also evaluated opportunities to optimize the project scope to reduce cost, such as reducing project scope by eliminating the Superheater Outlet Header test. • Southern Company had offered two sites as possible host locations for ComTest. Both sites had infrastructure in place such as steam from an existing unit, natural gas, cooling water and ample electrical power that would be required to be added at the Youngstown Thermal site. Utilizing this existing infrastructure could reduce the project cost. An additional project challenge was the departure of Babcock and Wilcox from the project in September 2016. This project setback was overcome by GE Power’s willingness to assume the design of the ComTest superheater. Since the project could not proceed without the superheater, this was a very positive project development. The merger of the GE Power and Alstom Power steam turbine divisions created synergies leading to the conclusion that instead of building a small-scale turbine, a more practical and useful endeavor would be to validate the manufacturing technology and supplier readiness for fabricating and machining full scale steam turbine components. Consequently, in March 2017, GE Power decided that a steam turbine test would not be necessary as part of the ComTest demonstration. Removing the operational testing of the steam turbine from ComTest further reduced the total project cost. Additionally, there was an opportunity to move ComTest from Youngstown Thermal to one of the Southern Company sites and operate ComTest at supercritical steam conditions and test the steam turbine main stop/control valve at a temperature and pressure that would be representative of the conditions of a high pressure steam turbine inlet valve. The steam could also possibly be returned to the host boiler so there would be no economic penalty of using this steam for ComTest. Relocating the project could further reduce the project cost due to the infrastructure already in place, including high pressure natural gas and cooling water, and the potential for heat integration, allowing a reduction of operating costs. Due to these potential cost reductions, it was decided to move the project away from Youngstown Thermal in March 2017. As integrating ComTest at the Southern Company site was explored, an issue was raised regarding the integration of the ComTest cycle with the plant steam cycle. Steam would be supplied to ComTest at nominally ~3865 psia and 775°F. The steam would be heated with natural gas to 1400°F for the valve test and then cooled to 1000°F so that the steam would be returned to the host boiler at the same conditions as their high pressure steam turbine inlet. However, there were concerns raised that the addition of the energy (natural gas) to the steam could trigger a New Source Review on the unit. Southern Company did not want ComTest to cause this review, so condensing all of the steam exiting ComTest and returning it to the host steam cycle as condensate was explored to insure there would be no implication that ComTest was adding energy to the host plant’s steam cycle. Ultimately, Southern Company decided that they wanted to “decouple” ComTest from the operating unit, making ComTest self-supporting, similar to the Youngstown Thermal “base case.” Without the steam turbine, the project team reached a consensus that operating the ComTest Superheater and steam turbine valves at the typical pressure of a package boiler (~1000 psig) would not generate enough useful technical information to justify the cost of the test. Therefore, it was decided in the December 2017 project quarterly meeting to cancel the operational phase of ComTest. Throughout the engineering phase of ComTest, manufacturing and supply chain challenges were identified. When GE Power recommended dropping the steam turbine test from ComTest, they identified many important manufacturing issues that should be evaluated and demonstrated. Other challenges had been raised by the GE Power group designing the superheater as well as those engineering components such as pressure relief and steam turbine bypass valves. In the December 2017 meeting, the project team decided that it was more beneficial to the AUSC technology to pursue these manufacturing and supply chain issues as Phase 2 of the ComTest project. This report is organized in the following manner: • Section 2 discusses the ComTest project background and organization. • Section 3 discussed project management. • Section 4 discusses the design of the ComTest AUSC components – the Superheater, steam turbine and Superheater Outlet Header. • Section 5 discusses the implementation of ComTest at Youngstown Thermal and the Southern Company site. • Section 6 discusses the development of the AUSC Supply Chain • Section 7 discusses the recommended plan for Phase 2 of ComTest

01 COAL, LIGNITE, AND PEAT↗

ClimGen: Learning the Forcing-Response Relationship in Climate System

Solar Radiation Management (SRM) is emerging as a potential geoengineering strategy to address the anthropogenic impact on climate, but its effective implementation requires an iterative and large ensemble of highly accurate and efficient climate projections. Traditional climate projections rely on executing computationally demanding and time-consuming numerical climate models. Recent advances in machine learning (ML) aim to enhance these approaches by emulating traditional methods. In this work, we propose a novel framework for directly learning the relationship between solar radiation flux at the top of the atmosphere and the corresponding surface temperature response. To evaluate the feasibility of this direct ML-based projection, we developed a dataset using an intermediate complexity model, incorporating a comprehensive suite of different forcing patterns and evaluation metrics to rigorously assess the ML model’s performance. We introduce a Conditional Denoising Diffusion Probabilistic Model (cDDPM) for this task, which demonstrates encouraging skill in representing climate statistics under previously unseen forcing patterns. This approach provides a promising pathway for direct climate projections by accurately learning the forcing-response relationship, with a wide range of applications in impact mitigation, emissions policy design, and SRM strategies.

Chen, Tse-Chun [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

Providing Thermal Stability for an Exascale Supercomputer: A Case Study of Frontier's Cooling System

High performance computing (HPC) systems frequently produce large dynamic power swings, even under typical operating conditions, that can present a significant challenge for their direct-liquid cooling systems. Further, the primary cooling loops that must remove this waste heat have response times measured in minutes while the underlying HPC component thermal stress is measured in seconds. The per-socket power demand for both compute processing units (CPUs) and graphic processing units ( GPUs) continues to increase with each successive generation while case temperatures are declining. New HPC systems are expected to exacerbate the challenge of these dynamic power swings and the impact on effective and timely cooling systems. This paper describes the cooling and controls system for Oak Ridge National Laboratory’s Frontier Supercomputer, the first sustained exascale system, as a case study for this situation. The cooling and control system for Frontier demonstrates specific success, but with a number of trade-offs and decisions that suggest further design and operating optimizations for the community at large to consider.

42 ENGINEERING↗

Progress Updates for the Hanford Waste Treatment and Immobilization Plant Project - 17275

The Waste Treatment and Immobilization Plant (WTP) Project is vital to the U.S. Department of Energy's (DOE) mission to cleanup radioactive waste at the Hanford Site, located in southeastern Washington State. The overall WTP Project objective is to design, build, and commission the facilities and systems that will treat and immobilize approximately 211 983 m{sup 3} (56 million gallons) of radioactive waste stored in Hanford's 177 underground storage tanks. The combination of technologies in the WTP makes it a first-of-a-kind facility at a scale larger than ever built for radioactive waste processing. In 2012, DOE suspended production work on the WTP's Pretreatment (PT) Facility and to a lesser degree the High-Level Waste (HLW) Facility because of unresolved technical issues associated with those facilities. DOE is proceeding with its approach to complete the WTP Project in phases, which includes the following principal actions: - Completing construction of the Low-Activity Waste (LAW) Facility, Balance of Facilities (BOF), and Analytical Laboratory (LAB), collectively known as LBL; - Implementing a direct-feed low-activity waste (DFLAW) process to treat low-activity waste independent of the PT Facility; - Completing the design and construction of the HLW Facility; - Resolving the technical issues associated with the PT Facility; - Completing all WTP facilities to enable integrated WTP operations. In March 2016, a federal judge amended the 2010 Consent Decree, establishing revised milestone dates for the Hanford WTP that generally align with DOE's plans for completing the WTP facilities in sequence. In December 2016, DOE executed a contract modification and approved a change to the project's performance baseline to complete the LBL facilities and incorporate modifications needed to accommodate direct feed of low-activity waste to the LAW Facility. The contract modification and revised performance baseline support completion of hot commissioning of the WTP facilities needed for DFLAW operations no later than December 31, 2023. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Interplay between hydrogen, temperature, and character angle on dissociated dislocation energies in Fe–Ni–Cr austenitic stainless steels

Dislocation energy has an important role in the mechanical performance of structural metals. While dislocation energies cannot be fully obtained from continuum theories due to the contribution of the dislocation core, they have been calculated via atomistic simulations in elemental metals. However, constraints on the local atomic environments have prevented the use of such approaches in systems that incorporate alloying or interstitial solutes. In this work, we develop robust molecular dynamics methods to resolve these issues through a geometric construction of dislocation dipoles and the calculation of time-averaged energies. Furthermore, we apply these methods to calculate dislocation energies (including core energies) in an Fe 70 Ni 11 Cr 19 austenitic steel at a variety of character angles, hydrogen concentrations, temperatures, and dipole spacings. The resulting highly converged energies show an excellent agreement with continuum expressions. Overall, hydrogen concentrations up to 1.0 % do not have a significant effect on the elastic parameters and dislocation energy. The methods and insights derived in this work have the potential to facilitate the calculation of dislocation energies in a wide range of systems, and to guide our understanding of hydrogen embrittlement.

Alloyed systems↗

Materials for Advanced Ultra-supercritical (A-USC) Steam Turbines – A-USC Component Demonstration

The work by the United States Department of Energy (U.S. DOE)/Ohio Coal Development Office (OCDO) advanced ultra-supercritical (A-USC) Steam Boiler and Turbine Materials Consortia from 2001 through September 2015 was primarily focused on lab scale and pilot scale materials testing. This testing included air- or steam-cooled “loops” that were inserted into existing utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion due to the constituents in the coal. Successful research and development resulted in metallic alloy materials and fabrication processes suited for power generation applications with metal temperatures up to approximately 1472°F (800°C). These materials or alloys have shown, in extensive laboratory tests and shop fabrication studies, to have excellent applicability for high-efficiency low CO 2 transformational power generation technologies previously mentioned. However, as valuable as these material loops have been for obtaining information, their scale is significantly below that required to minimize the risk associated with a power company building a multi-billion dollar A-USC power plant. To decrease the identified risk barriers to full-scale implementation of these advanced materials, the U.S. DOE/OCDO A-USC Steam Boiler and Turbine Materials Consortia identified the key areas of the technology that need to be tested at a larger scale. Based upon the recommendations and outcome of a Consortia-sponsored workshop with the U.S.’s leading utilities, a Component Test (ComTest) Program for A-USC was proposed. The A-USC ComTest program would define materials performance requirements, plan for overall advanced system integration, design critical component tests, fabricate components for testing from advanced materials, and carry out the tests. The AUSC Component Test was premised on the program occurring at multiple facilities, with the operating temperatures, pressure and/or size of these components determining the optimum test location. The first step of the ComTest, the steam turbine test, was determined best suited for a site in Youngstown, Ohio. Efforts were also undertaken to identify and evaluate other potential sites for high pressure testing.

33 ADVANCED PROPULSION SYSTEMS↗

Design and Modeling of an Open-Source Baseline Floating Marine Turbine: Preprint

Marine energy resources such as river, tidal, and ocean currents can provide abundant, predictable, and clean power to both densely populated and remote communities globally. However, marine turbine technologies are still in an early stage of development. Recently, features have been added to the National Renewable Energy Laboratory's open-source wind turbine modeling tool OpenFAST to support the simulation of axial-flow marine turbines. These new features enable marine energy developers to predict the performance and safety of their turbines and allow researchers and students to advance the field through the exploration of novel designs. Developing and demonstrating the new capabilities of OpenFAST for marine turbines requires a baseline design that can be used as an example and test case. There are limited open-source turbine models suitable for this purpose. One existing baseline design is the Reference Model 1 (RM1), a fixed-bottom, dual-rotor marine turbine that was published in 2014 as part of the Department of Energy's Water Power Reference Model Project. To test and demonstrate OpenFAST's ability to model floating marine turbines, several modifications were made to the RM1. A floating platform and mooring system were designed to support a single RM1 rotor in a wide range of possible current and wave conditions. The system and model are intended to be a stable reference case and starting point for research efforts. The platform features all cylindrical members and familiar design elements from the offshore wind industry; the mooring system uses simple catenary chains. While not optimized for the lowest platform cost, the design is understandable and robust and can serve as a baseline for floating marine turbine technologies. This is a useful starting point for studies to explore new technologies or design methodologies. Additionally, the floating RM1 design enables cross-collaboration among industry, academia, and national lab researchers and serves as an educational platform for newcomers to marine energy. This short paper presents the specifications of the turbine, including its floating support structure and mooring system. The rationale behind the selection of certain design parameters is described. To enable adoption of this baseline case for research and educational efforts, an OpenFAST model of the full system has been made publicly available at https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/MHK_RM1_Floating.

floating↗

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the Landscape of Distributed Graph Clustering on Leadership Supercomputers

The rapid growth of large-scale datasets in fields like biology and social networks has driven the need for advanced graph analytics techniques. Community detection, a fundamental task in graph analytics, identifies closely connected groups of nodes within a network, providing valuable insights across various disciplines. This study focuses on two classic community detection methods, the Louvain algorithm and Markov Clustering (MCL), and evaluates the performance of two prominent distributed community detection algorithms: HiPDPL-GPU, our prior implementation, and HipMCL. We conduct experiments on GPU-accelerated heterogeneous HPC systems, Summit and Frontier, to assess their performance under varying conditions. Our objective is to identify the strengths and weaknesses of these algorithms in terms of scalability, and quality of solutions. We evaluate these algorithms on a diverse set of 70+ networks spanning 13 domains, with sizes ranging up to 4.2 billion edges. Our results demonstrate that HiPDPL-GPU consistently outperforms HipMCL, especially for large-scale networks. HiPDPL-GPU achieves significantly faster runtimes (47x to 1439x), higher modularity scores, and improved scalability. These findings highlight HiPDPL-GPU as a promising solution for efficient and effective large-scale graph analytics in diverse application domains, and provide insights into the feasibility of using MCL-based approaches for certain application domains.

Community detection, graph algorithms↗

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗

The Sensor Dilemma in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are at the forefront in advancing the way we interact and perceive with the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as Radar, LiDAR and Video Imaging which are the most popular modalities for ITS. Real-time perception data from these sensors allows intelligent infrastructure side decision making to improve the energy, efficiency and safety at traffic intersections. As traffic departments across the United States are transitioning from traditional loop detectors / emulators and embracing newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception which is reliable, inexpensive, easy to setup and has robust performance in varying weather conditions. However, choosing a sensor which checks all boxes is not straightforward as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long range vehicles and weather resistance but lacks high resolution. LiDAR is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines Radar, LiDAR and camera sensors capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. Through this evaluation, we hope to draw attention to the necessity of National Renewable Energy Laboratory's (NREL) Infrastructure Perception and Control (IPC) framework which presents a multi-sensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like Radar, LiDAR and cameras, offers the most robust solution for enhancing the safety and efficiency in intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗