High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges.
Abstract not provided.
Yamazaki, Ichitaro↗
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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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MIMO Vibration Test Design for BARC Challenge Problem
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Zwink, Brandon↗
Transformational Challenge Reactor Agile Design Enabled by Additive Manufacturing
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Betzler, Benjamin↗
CFD Modeling for the Transformational Challenge Reactor Preliminary Design
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Jain, Prashant↗
Building a custom high-throughput platform at the Joint Genome Institute for DNA construct design and assembly—present and future challenges
Abstract The rapid design and assembly of synthetic DNA constructs have become a crucial component of biological engineering projects via iterative design–build–test–learn cycles. In this perspective, we provide an overview of the workflows used to generate the thousands of constructs and libraries produced each year at the U.S. Department of Energy Joint Genome Institute. Particular attention is paid to describing pipelines, tools used, types of scientific projects enabled by the platform and challenges faced in further scaling output.
36 MATERIALS SCIENCE↗
2020 Solar Decathlon Education Partner: Cooperative Research and Development (Final Report, CRADA Number CRD-19-00802)
The U.S. Department of Energy Solar Decathlon (DOE/SD) is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. The DOE/SD is comprised of two Challenges--Design Challenge (annual, in April of each year at NREL in Golden, Colo.) and Build Challenge (biennial, held next in June/July 2020 in Washington D.C.). NREL provides competition management for DOE/SD. For over 35 years, EEBA has provided the most trusted resources for building science information and education in the construction industry. EEBA delivers turn-key educational resources and events designed to transform residential construction practices through high performance design, marketing, materials, and technologies. NREL and EEBA establish this CRADA to enable the success of the DOE/SD program in managing sponsorship funds and creating a professional education program. EEBA acted as an Education Partner to DOE/SD, which included: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing professional development content.
14 SOLAR ENERGY↗
Solar Decathlon Education Partner: Cooperative Research and Development Final Report
The U.S. Department of Energy Solar Decathlon (DOE/SD) is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges - Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the Solar Decathlon program in managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.
14 SOLAR ENERGY↗
Transformational Challenge Reactor preconceptual core design studies
In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Conceptual Design of the Transformational Challenge Reactor
The Transformational Challenge Reactor is a 3-MW(thermal) helium-cooled experimental nuclear reactor designed using an additive manufacturing–informed agile design process. This design process leverages rapid prototyping and advanced materials from emerging additive manufacturing technologies, key characteristics that enable rapid design maturation. The resulting core design incorporates a blend of advanced reactor technologies into an intermediate-spectrum microreactor, including conventionally manufactured tristructural isotropic (TRISO) fuel particles in an advanced manufactured SiC fuel element and a solid yttrium hydride moderator encapsulated in steel. Matured during the design effort, these technologies are incorporated with additively manufactured steel support and fluidic structures to form a 75-cm-outer-diameter cylindrical active core region. Below and above the active core region are axial SiC reflectors, which are housed inside the reactor pressure vessel. The reactor is controlled with an annular shroud actuated external to the pressure vessel in the gap between the pressure vessel and a steel radial reflector. A safety rod is at the center of the core to shut down the reactor when necessary. Helium pressurized at 5 MPa is forced into the pressure vessel below the core and around the core to the top plenum before it is forced down through the axial reflectors and the active core region. The primary pressurized helium loop is operated up to 500°C and includes the pressure vessel, the circulator, and the hot side of a helium-to-air heat exchanger. The secondary loop rejects all heat from the primary loop to ambient air through a heat exchanger. A vented temporary confinement building contains the entire primary loop, with penetrations for a stack, cooling, and the secondary ambient air loop. Finally, this is the first advanced nuclear microreactor designed using additive manufacturing technologies, demonstrating their applicability in an accelerated advanced design process.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Lattice QCD and the Computational Frontier
The search for new physics requires a joint experimental and theoretical effort. Lattice QCD is already an essential tool for obtaining precise model-free theoretical predictions of the hadronic processes underlying many key experimental searches, such as those involving heavy flavor physics, the anomalous magnetic moment of the muon, nucleon-neutrino scattering, and rare, second-order electroweak processes. As experimental measurements become more precise over the next decade, lattice QCD will play an increasing role in providing the needed matching theoretical precision. Achieving the needed precision requires simulations with lattices with substantially increased resolution. As we push to finer lattice spacing we encounter an array of new challenges. They include algorithmic and software-engineering challenges, challenges in computer technology and design, and challenges in maintaining the necessary human resources. In this white paper we describe those challenges and discuss ways they are being dealt with. Overcoming them is key to supporting the community effort required to deliver the needed theoretical support for experiments in the coming decade.
Boyle, Peter↗
Simultaneous enhancement of multiple functional properties using evolution-informed protein design
Abstract A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β -lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.
59 BASIC BIOLOGICAL SCIENCES↗
National Energy Education Development Project (NEED Project) (CRADA Final Report)
The U.S. Department of Energy Building Technologies Office (BTO) funds student competitions that introduce students to careers in the building sciences and increase public awareness around high-performance buildings to support the goal of developing, demonstrating, and accelerating the adoption of cost-effective technologies, techniques, tools, and services that enable high-performing, energy-efficient and demand-flexible residential and commercial buildings in both the new and existing buildings markets. The U.S. Department of Energy Solar Decathlon® (DOE/SD) is a flagship, high-visibility international competition started in 2002 that advances the goals of BTO by introducing students to building science careers; educating students and the public about the latest technologies and materials in high-performance buildings; encouraging student-led projects and research centered around building science; and demonstrating to the public the comfort and savings of homes that combine energy-efficient construction, home systems, appliances and innovative design with onsite renewable energy production. SD is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges – Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the overall Solar Decathlon program by managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Performance of HALEU and HEU-Fueled Nuclear Thermal Propulsion Reactors
Interplanetary spaceflight may be significantly improved by rockets that utilize nuclear thermal propulsion (NTP) instead of the chemically propelled rockets in use today. To be efficient, NTP reactors must be light, which presents unique design opportunities and challenges to reactor designers. One such opportunity is the enrichment of the nuclear fuel that powers the NTP reactor. The use of high-enriched uranium (HEU) instead of high-assay low-enriched uranium (HALEU) will result in a lower mass of fuel required but may present additional challenges beside the mass considerations, such as proliferation concerns, availability, public acceptance and authorization basis. Whether or not a NTP reactor fueled with HEU is significantly lighter than its HALEU counterpart is unclear and an assessment has been performed here as part of the Mars Transportation Assessment Study. This report assesses the impact of reducing the fuel enrichment form HEU (93 wt.% 235U) to HALEU fuel (19.5 wt.% 235U) on reactor design outcomes for a conceptual NTP reactor. Two reactor designs, one fueled with HEU and the other with HALEU, were prepared based on a multi-stage design process. The neutronics and thermal-hydraulics characteristics of these reactors are compared and contrasted to illustrate the impacts of fuel enrichment. Despite differences in fuel and moderator mass, the overall mass difference between the HALEU and HEU cores was only 9%. The required core size and assembly dimensions are nearly equivalent. This finding is based on a rapid design process that targeted core volume minimization. Each features some neutronics advantages - depletion is much less significant in the HEU core, but the Doppler reactivity feedback is stronger in the HALEU core. Additional discussions are made about the possible benefits of other design changes, including the possibility of utilizing a fast-spectrum reactor. Given the scope of this assessment the findings discussed in this report are not exhaustive and are only providing an initial comparison of the most obvious design and performance parameters.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
The High Luminosity LHC interaction region magnets towards series production
The High Luminosity Large Hadron Collider (HL-LHC) is the new flagship project of CERN. First endorsed in 2013 and approved in 2016, HL-LHC is an upgrade of the accelerator aiming to increase by a factor of ten the statistics of the LHC collisions at the horizon of 2035-2040. HL-LHC relies on cutting edge technologies: among them, large aperture superconducting magnets will replace the present hardware to allow a smaller beam size in two interaction points (IPs). The project involves the construction of about 150 magnets of six different types: the quadrupole triplet, two main dipoles and three orbit correctors. The triplet, manufactured at CERN and in the USA, will consist of 30 magnets based on Nb3Sn technology, with an operational peak field of 11.4 T. These will be the first quadrupole Nb3Sn magnets installed in a particle accelerator. The other five types of magnets, all relying on Nb-Ti technology, present non-trivial challenges in the design and construction; they will be manufactured as part of in-kind contribution under the responsibility of institutes in Japan, China, Spain, and Italy. The project is now in the phase of transition between qualification through short models and prototypes and the beginning of the series construction. In this paper we review the magnet requirements, the reasons for selecting the design, the technological challenges with respect to previous projects, and we summarize the steps that have been taken to validate the baseline.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Optimal Control for X-Ray Mircroscopes
In this article, a systematic framework for designing the control for fine positioning (scanning) stages of X-ray microscopes is presented. This framework facilitates designs that simultaneously achieve specifications on positioning resolution and tracking bandwidth while guaranteeing robustness of the closed loop device to unmodeled uncertainties. We use robust optimal control techniques for modeling, quantifying design objectives and system-specific challenges, and designing the control laws. The control designs were implemented on a three degree of freedom piezoactuated flexure stages dedicated for fine positioning of X-ray optics. Experimental results demonstrate significant improvements in positioning performance of 134%, 150%, and 132% in tracking bandwidths along the lateral (X), vertical (Y), and beam (Z) directions, respectively, when compared to proportional-integral-derivative controller designs. This was achieved while keeping similar or better positioning resolution and robustness measures. Fast scanning for X-ray imaging was demonstrated in both the step scan and flyscan modes, where bandwidth was improved by over 450 times with flyscan compared to the step scan.
42 ENGINEERING↗
Towards Generalizable and Efficient Circuit Topology Design: A Graph-Transformer-based Surrogate Model with Curriculum Learning
Unlike circuit parameter and sizing optimizations, the automated design of analog circuit topologies poses significant challenges for learning-based approaches. One challenge arises from the combinatorial growth of the topology space with circuit size, which limits the topology optimization efficiency. Moreover, traditional circuit evaluation methods are time-consuming, while the presence of data discontinuity in the topology space makes the accurate prediction of circuit performance exceptionally difficult for unseen topologies. To tackle these challenges, we design a novel Graph-Transformer-based Network (GTN) as the surrogate model for circuit evaluation, offering a substantial acceleration in the speed of circuit topology optimization without sacrificing performance. Our GTN model architecture is designed to embed voltage changes in circuit loops and current flows in connected devices, enabling accurate performance predictions for circuits with unseen topologies. To address the cold start problem when scaling GTN to large-scale circuits, we further introduce a curriculum learning strategy that progressively trains GTN from small-scale to large-scale circuits. This approach enables the model to first learn fundamental physical principles from simpler topologies and gradually adapt to complex configurations, effectively bridging the circuit complexity gap and improving prediction accuracy. Taking the power converter circuit design as an experimental task, our GTN model significantly outperforms an analytical approach and baseline methods directly utilizing graph neural networks. Furthermore, GTN achieves less than 5% relative error and 196× speed-up compared with high-fidelity simulation. Notably, our GTN surrogate model empowers an automatic circuit design framework to discover circuits of comparable quality to those identified through high-fidelity simulation while reducing the time required by up to 98.2%. With curriculum learning, the enhanced GTN achieves a 51% improvement for performance prediction of large-scale circuits compared to the GTN model without this strategy. These advancements establish GTN as a scalable framework for automated analog circuit design across varying circuit complexity levels.
Lu, Haoshu [New Jersey Institute of Technology (NJ↗
Effectively using multifidelity optimization for wind turbine design
Abstract. Wind turbines are complex multidisciplinary systems that are challenging to design because of the tightly coupled interactions between different subsystems. Computational modeling attempts to resolve these couplings so we can efficiently explore new wind turbine systems early in the design process. Low-fidelity models are computationally efficient but make assumptions and simplifications that limit the accuracy of design studies, whereas high-fidelity models capture more of the actual physics but with increased computational cost. This paper details the use of multifidelity methods for optimizing wind turbine designs by using information from both low- and high-fidelity models to find an optimal solution at reduced cost. Specifically, a trust-region approach is used with a novel corrective function built from a nonlinear surrogate model. We find that for a diverse set of design problems – with examples given in rotor blade geometry design, wind turbine controller design, and wind power plant layout optimization – the multifidelity method finds the optimal design using 38 %–58 % of the computational cost of the high-fidelity-only optimization. The success of the multifidelity method in disparate applications suggests that it could be more broadly applied to other wind energy or otherwise generic applications.
17 WIND ENERGY↗