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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide Between July 2023 and October 2023, ESnet and the Nuclear Physics program (NP) of the DOE SC organized an ESnet requirements review of NP-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the NP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Final Scientific/Technical Report Rapid Design and Manufacturing of High-Performance Materials for Turbine Blades

This research demonstrated the concept of carbide precipitation-strengthened refractory high entropy alloys (RHEA). The advantage of a precipitation strengthened alloy is all phases are in thermodynamic equilibrium promoting microstructural stability, and consequently retention of properties at elevated temperatures. Additionally, as with any precipitation strengthened – or age hardened alloy, components can be heat-treated after manufacturing to manipulate the microstructure and optimize properties for performance. This is an advantage of the precipitation strengthened alloys over composites and ceramics materials, where the microstructure and properties are essentially fixed upon the initial materials manufacturing stage. High throughput (HT), multi-scale computer modeling was used to identifying novel RHEA compositions with desired characteristics needed for precipitation strengthening. The results showed that carbides precipitated and consequently, the strength of the alloys (measured in compression) increased after heat-treatment, which is the desired effect. The project also demonstrated the feasibility of producing articles from RHEA by additive manufacturing (AM).

36 MATERIALS SCIENCE↗
DOE OSTI2023

High Energy Physics Network Requirements Review: Two-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide a range of network services tailored to meet the unique requirements of the DOE’s data-intensive science. In July 2023, the Energy Sciences Network (ESnet) and the High Energy Physics program (HEP) of the DOE SC organized an interim ESnet requirements review of HEP-supported activities, to follow up on the work started during the 2020 HEP Network Requirements Review. Preparation for these events included checking back with the key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare updates to their previously submitted case study documents, so that ESnet could update the understanding of any changes to the current, near-term, and long-term status, expectations, and processes that will support the science activities of the program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

STAT7 v1.2 User Guide: The STAT7 Code for Statistical Propagation of Uncertainties in Steady-State Thermal Hydraulics Analysis of Plate-Fueled Reactors

The STAT7 software was developed to perform steady-state, single-phase thermal hydraulics analysis of plate-fueled reactors based on statistical propagation of uncertainties. Application of the software is for non-power research and test reactors, including conversion to low-enriched uranium fuel of U.S. High-Performance Research Reactors such as Massachusetts Institute of Technology Research Reactor. Since it can be necessary to repeat analysis during fuel reloading, STAT7 accommodates flexibility in analyzing many realistic aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model uncertainty in common fuel fabrication parameters and other key reactor operating parameters required for thermal hydraulics analyses of research and test reactors. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux, or onset of flow instability. STAT7 supports water properties based on the IAPWS-IF97 functions (The International Association for the Properties of Water and Steam Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam) in addition to the fit functions. STAT7 predicts axial profiles of fuel, cladding, and coolant temperature along a lateral stripe that runs the full length of the fuel plate from the bottom to the top. STAT7 can simultaneously analyze all of the axial nodes of all of the fuel plates and all of the coolant channels for one latera stripe of a fuel element. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. By running STAT7 multiple times, full core analysis can be performed by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each fuel element in the core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Highly Permeable Rubbery Thin Film Composite Membranes for CO2 Capture from Steel Mills

For presentation at the 2024 AIChE Annual Meeting, San Diego, CA, October 27-31, 2024. High-permeance and CO2-selective membranes are needed to make membrane technology economically viable for large-scale deployment of carbon capture from various industrial point sources such as steel mills. Thin film composite (TFC) membranes are necessary for this practical implementation because they can provide high permeance by forming a thin selective layer on top of a porous support layer. This presentation reports the rational design and fabrication of National Energy Technology Laboratory’s highly permeable non-aging TFC membranes achieved by: (1) synthesizing a high-performance rubbery selective material; (2) developing a high-porosity membrane support; (3) optimizing coating methods to assemble the two materials into scalable membranes; and (4) scaling up membrane supports and TFCs via a roll-to-roll process. This talk will also cover the design, computational fluid dynamic simulation, 3D printing, construction, and permeation testing of plate-and-frame membrane modules for an upcoming field demonstration at U. S. Steel’s Edgar Thomson Plant in Braddock, PA.

Zhu, Lingxiang↗
DOE OSTI2023

Demonstration of low-density, high-performance operation of sustained spheromaks and favorable scalability toward compact, low-cost fusion power plants (Final Scientific/Technical Report)

This project worked to advance the technical viability of a novel method for efficiently sustaining stable, high-performance spheromak plasma configurations to serve as the basis of compact, low-cost fusion power plants. In particular, our group worked to improve the method of Steady Inductive Helicity Injection (SIHI) with Imposed-Dynamo Current Drive (IDCD) for spheromak plasma sustainment. Prior to this project demonstrations of this plasma sustainment technology have achieved plasma performance consistent with entry milestone 3 of the BETHE FOA. Research and development (R&D) activities for this project were focused on increasing plasma performance toward a level consistent with exit milestone 4. To do this the PI and his group worked to increase the performance of sustained spheromaks produced in an existing experimental prototype (HIT-SIU) while improving confidence in projections to and design of future, higher performance devices through three primary R&D activities: 1) Improved control over the density of plasma in the device throughout a discharge to provide a pathway for demonstration of spheromaks Ohmically heating to the Mercier beta limit via: a. Fueling the device directly with plasma through the installation of pre-ionized source on the injectors b. Optimization of electrical current waveforms in the driver circuits to enable low-density plasma formation with a lower fueling rate 2) Computational demonstration of a validated, realistic injector circuit coupled to a dynamic plasma model capable of use as a design tool for SIHI drivers and associated circuits for new experimental design points on the pathway to commercial reactors. The improvements in plasma performance achieved during research activity 1), and the computational projections performed in research activity 2) increased the technological readiness level (TRL) of this fusion energy concept toward a level sufficient to attract early-stage private investment and/or other forms of follow-on investment to pursue required R&D activities required for the eventual fusion power plants based on this novel technical approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

CFD Modeling of Concentration Polarization in High-Performance Flat-Sheet Modules

Membrane-based gas separation is a promising, regeneration-free route for industrial CO₂ capture, but its performance is often limited by concentration polarization (CP). Classical 1-D models neglect CP and thus overpredict fluxes, especially for today’s high-permeance, high-selectivity membranes. Therefore, we built a 3-D CFD model that resolves local species transport, boundary-layer resistance, permeate-side effects, and pressure drop in flat-sheet modules. Using the Concentration Polarization Coefficient (CPC) and the overall Effective Membrane CP Index (EAC), the model quantifies how geometry and operating conditions shape CP intensity. Simulations show CP becomes pronounced for advanced membranes, with feed-channel height emerging as the dominant geometric lever: shrinking the gap mitigates CP but raises pressure drop, forcing a trade-off between mass-transfer enhancement and energy cost. These insights emphasize the need for CFD-level analysis in next-generation module design, where 1-D treatments can severely underestimate required membrane area and misguide scale-up.

carbon capture↗
DOE OSTI2025

Computational Design of Cost-Effective High-Entropy Thermal/Environmental Barrier Coatings

Developing cost-effective thermal/environmental barrier coatings (TEBC) requires balance among various properties including low thermal conductivity, matching coefficient of thermal expansion (CTE), high thermal stability, high fracture toughness, and high recession resistance while being affordable. Low oxygen diffusivity is desirable as it can slow down oxygen transport to reach the underlying bond coating and hence delay oxidation of the bond coating. This project aims to design low-cost high-performance TEBC based on high entropy rare earth disilicates to protect SiC-based ceramic matrix composites from chemical and thermal attack for better performance of components in the hot section of gas turbine engines. To accelerate the TEBC design, we utilize first-principles density functional theory to predict key properties including phase stability, CTE, lattice thermal conductivity, temperature-dependent elastic constants, and oxygen diffusivity. Alloying elements including Yb, Y, Er, Eu, Gd, Lu, La, and Ce are considered, and modeling prediction are compared with available experimental results.

coefficient of thermal expansion↗
DOE OSTI2024

Rapid Design and Manufacturing of High-Performance Materials for Turbine Blades

This research demonstrated the concept of carbide precipitation-strengthened refractory high entropy alloys (RHEA). The advantage of a precipitation strengthened alloy is all phases are in thermodynamic equilibrium promoting microstructural stability, and consequently retention of properties at elevated temperatures. Additionally, as with any precipitation strengthened – or age hardened - alloy, components can be heat-treated after manufacturing to manipulate the microstructure and optimize properties for performance. This is an advantage of the precipitation strengthened alloys over composites and ceramics materials, where the microstructure and properties are essentially fixed upon the initial materials manufacturing stage. High throughput (HT), multi-scale computer modeling was used to identifying novel RHEA compositions with desired characteristics needed for precipitation strengthening. Designs were validated by producing small ingots via are melting. The results showed that carbides precipitated and consequently, the strength of the alloys (measured in compression) increased after heat-treatment, which is the desired effect. The project also demonstrated the feasibility of producing articles from RHEA by additive manufacturing (AM). Electron beam melting (EBM) and laser direct energy deposition (L-DED) additive manufacturing methods, were explored with various processing parameters were interrogated for both methods. Sound (crack-free and dense) precipitation strengthened RHEA samples were produced via EDM AM, demonstrating the feasibility of the concept.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats (Integration of Additive Manufacturing and Reinforced Polymer Composite)

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components. However, fabricating these metal polymer composite structures through traditional manufacturing processes limits their mechanical properties due to limited design freedom, lack of control over fiber orientation in composite parts, and poor interfacial bonding between the constituent materials. It is essential to develop a novel manufacturing process to enable high throughput production of lightweight automotive seats using metal and polymer composites. As such it is important to design the automotive seat suitable for manufacturing via this process and perform mechanical characterization on various subcomponents of the seat to ensure that the design and performance requirements provided by the auto manufacturer are met. The aim of this project is to develop a novel manufacturing technique to produce lightweight automotive seat by combining AM with conventional manufacturing processes. The car seat back panel will be designed via topology optimization and numerical simulations to minimize the overall weight while ensuring it meets all the performance requirements. The optimization of the seat back structure will be based on computational stress analysis to maximize the stiffness and minimize the weight. Materials currently used by Ford Motor Company will be adopted for a few subcomponents while the in-house composite materials will be used for the rest of the seat back. The composite and metallic materials will be tested to determine their mechanical properties as these are necessary for simulations. A novel manufacturing process will be developed to integrate AM metal inserts with discontinuous reinforced composite through large scale additive manufacturing and compression overmolding processes. The developed manufacturing technique will be used to fabricated various subcomponents suitable for the seat back design and mechanically tested to determine their properties. The manufacturing of the lightweight seat back design through this process involves integrated AM metal inserts with the composite structure for recliner connection. The manufacturing of the entire seat back which is lightweight through the novel manufacturing process will be discussed. The performance of the designed seat back will be investigated through numerical simulations and shown to meet all the requirements provided by the auto manufacturer. The final goal of developing a novel manufacturing process for lightweight automotive seats is met through design optimization of seat back, manufacturing of subcomponents, mechanical characterization, and validation through numerical simulations. The routes to achieve the final goal of the project and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. The project resulted in the development of a novel manufacturing process to integrate metal inserts with tailored polymer composite preforms through overmolding. Leveraging this proven manufacturing process, a lightweight seat back was designed through topology optimization and numerical simulations. The designed seat back uses AM metal inserts and compression overmolding of tailored polymer composite preforms obtained via large scale additive manufacturing. The metal polymer composite structures fabricated through this process exhibited enhancement in stiffness and improved ductility upon testing. Overall, the project provided an alternative design and manufacturing technique for automotive seat back that enables weight saving while meeting the safety and performance requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

GASNet-EX Specification Collection (Rev. 2024.5.0)

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale systems. It provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). GASNet-EX is an evolution of the popular GASNet communication system, building upon over 20 years of lessons learned, and the primary goals are high performance, interface portability, and expressiveness. The library has been used to implement parallel programming models and libraries such as UPC, UPC++, Fortran coarrays, Legion, Chapel, and many others. This anthology collects together the four separate volumes that currently comprise the GASNet-EX specification, as of the 2024.5.0 release of GASNet-EX.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Bead–Spring Simulation of Ionomer Melts—Studying the Effects of Chain-Length and Associating Group Fraction on Equilibrium Structure and Extensional Flow Behavior

Ionomers are associative polymers with diverse applications ranging from selective membranes and high-performance adhesives to abrasion- and chemical-resistant coatings, insulation layers, vacuum packaging, and foamed sheets. Within equilibrium melt, the ionic or associating groups are known to form thermally reversible, associative clusters whose presence can significantly affect the system’s mechanical, viscoelastic, and transport properties. It is, thus, of great interest to understand how to control such clusters’ size distribution, shape, and stability through the designed choice of polymer architecture and the ionic groups’ fraction, arrangement, and interaction strength. In this work, we represent linear associating polymers using a Kremer–Grest type bead–spring model and perform large-scale MD simulations to explore the effect of polymer chain-length (l) and fraction (f s ) of randomly placed associating groups on the size distribution and stability of formed clusters. We consider different chain-lengths (below and above entanglement), varying fractions of associating groups (represented by ‘sticky’ beads) between 5 and 20%, and a fixed sticky–sticky nonbond interaction strength of four times that between regular non-associating beads. For all melts containing associating groups the equilibrium structure factor S(q) displays a signature ionomer peak at low wave vector q whose intensity increases with increasing f s and l. The average cluster size Nc increases with f s . However, the effect of chain-length on Nc appears to be pronounced only at higher values of f s . Under extensional flows, the computed stress (and viscosity) is higher at higher f s and l regardless of strain rate. Beyond a critical strain rate, we observe fragmentation of the associative clusters, which has interesting effects on the stress/viscous response.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Frequency 3D Photoacoustic Computed Tomography Using an Optical Microring Resonator

3D photoacoustic computed tomography (3D-PACT) has made great advances in volumetric imaging of biological tissues, with high spatial-temporal resolutions and large penetration depth. The development of 3D-PACT requires high-performance acoustic sensors with a small size, large detection bandwidth, and high sensitivity. In this work, we present a new high-frequency 3D-PACT system that uses a microring resonator (MRR) as the acoustic sensor. The MRR sensor has a size of 80 μ m in diameter and was fabricated using the nanoimprint lithography technology. Using the MRR sensor, we have developed a transmission-mode 3D-PACT system that has achieved a detection bandwidth of ~23 MHz, an imaging depth of ~8 mm, a lateral resolution of 114 μ m, and an axial resolution of 57 μ m. We have demonstrated the 3D PACT’s performance on in vitro phantoms, ex vivo mouse brain, and in vivo mouse ear and tadpole. The MRR-based 3D-PACT system can be a promising tool for structural, functional, and molecular imaging of biological tissues at depths.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

SuperLab 2.0 Showcase: Connecting Five Labs to Tackle Grid Complexity and Unlock Unique Grid Asset Potential

SuperLab 2.0 (5-Lab Demo) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, PV, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactor (SMR), control centers, and gas turbines, across five DOE national laboratories-NLR, INL, NETL, LBNL, and SNL. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance U.S. Department of Energy's (DOE) network, and controlled via a centralized energy controller hosted at NLR's ARIES facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility. SuperLab 2.0 (5-Lab Demo) showcased a major advancement in federated national laboratory collaboration, enabling real-time, cross-laboratory experimentation to coordinate geographically dispersed distributed energy resources (DERs) using various communication protocols and networks. SuperLab 2.0 (5-Lab Demo) built on previous demonstrations conducted between NLR-PNNL and NLR-INL connecting diverse assets including distant protection devices, a SMR simulator, and a high temperature electrolyzer (HTE). Previous demos were based on a single connection between two labs with minimal coordination challenges. The 5-Lab demo with a centralized controller, distributed testbeds across different geographical locations, and use of protocols-based communication represents a scenario closer to real-world grid operations that coordinate resources across a region to meet system needs. This experiment studied how local DER controllers interact with a centralized energy controller during normal and abnormal events to maintain reliability. The SuperLab team across the five labs implemented a notional power system model equivalent of transmission and distribution lines, represented by the data networks interconnecting the labs. Each lab continuously exchanged local parameters (such as P and Q) from its Hardware-In-Loop (CHIL) and Power Hardware-In-Loop (PHIL) assets through centralized energy controller at NLR, enabling real-time interaction and coordination across sites. By leveraging ESnet as the communication backbone, the team successfully operated the distributed assets as a unified power system, with each bus represented by a different laboratory. This setup mirrors how assets interact in real-world power systems across dispersed locations with various protocols and latencies. At each lab site, assets were operated using their own local controllers which were coordinated through an overarching operation and control layer of centralized energy controller, equivalent to how an energy management system (EMS) orchestrates assets across a regional or national grid. SuperLab's federated connectivity utilized a Digital Real-Time Simulators (DRTS)-type gateway to connect Controller Hardware-In-Loop (CHIL) and PHIL assets between labs. To enable this federated connection through ESnet, a deterministic network was established where latency variations were consistent. This consistency allowed the development of digital filters for the power system assets across CHIL and PHIL interfaces to avoid unstable and unreliable grid conditions. This report provides an overview of the cross-laboratory configuration and offers insights into interconnecting geographically distributed research assets to test them as if they were co-located. This experiment represents a step toward linking nine DOE national laboratories, enabling nation-wide simulations that can address utility-driven challenges with grid resilience, flexibility, and modernization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Accelerating Materials Discovery: Artificial Intelligence for Sustainable, High-Performance Polymers

PolyID enables the discovery of polymers with advanced performance and greater sustainability while reducing material development timelines. The material design space is immense and cannot be reasonably probed using an Edisionian approach. High-throughput property prediction, enabled by artificial intelligence provides a hypothesis driven approach for down selection of candidate polymers to pursue experimentally. To aid experimentalists in the down selection of material targets this high-throughput, machine learning-based tool is capable of predicting polymer properties simply from molecular structures. Currently, transport, thermal, and mechanical properties across 7 polymer class (polyamides, polyesters, polycarbonates, polyimides, polyolefins, polyacrylates, and polyurethanes) can be predicted, and the PolyID platform has been flexibly designed so new materials and properties can be added.

artificial intelligence↗
DOE OSTI2022

MODELLING OF ADDITIVE MANUFACTURING – COMPRESSION MOLDING PROCESS USING COMPUTATIONAL FLUID DYNAMICS

A computational fluid dynamics model has been developed to predict the behavior of a printed strands during a novel material extrusion additive manufacturing and compression molding process. While the traditional additive manufacturing process enables control over the fiber orientation within the part, it would also result in high void content. On the other hand, compression molding produces parts with low porosity levels at rapid processing cycle time but lacks control over the microstructure. The novel additive manufacturing – compression molding (AM-CM) integrating both these processes offers control over both the microstructure and porosity to manufacturing high performance composite parts. The numerical model developed here enables to analyze the effect of processing parameters on the behaviour of printed layer that is subsequently compressed and to determine the optimal printing parameters for high-performance composite part design.

Seta, Berin↗
DOE OSTI2022

UPDATES FROM THE INVOLUTE WORKING GROUP

The HFIR, RHF, and FRM II reactors represent a particular class of Research and Test Reactors that provide some of the most intense and continuous neutron fluxes for science, industry, and medical applications. These high-performance reactors have achieved compact cores by operating with Highly Enriched Uranium fuel (HEU, 235U/U ≥ 20 wt. %) and utilizing fuel plates curved as an involute. Due to the proliferation risks, the international community aims to reduce or eliminate, when possible, the use of HEU fuel in civilian facilities by converting them to a Low-Enriched Uranium fuel (LEU, 235U/U < 20 wt. %). Conversion of these reactors without significantly compromising their performance or safety is a challenging endeavor that can tremendously benefit from advanced computational tools and thus, eliminate unnecessary conservatism to ensure sufficient thermal margins. Therefore, models are being developed using modern Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) software to evaluate the steady-state safety margins of various LEU designs instead of being reliant on the more traditional, conservative methods. To gain the confidence and acceptance of high-fidelity modeling by the nuclear regulators, Argonne National Laboratory (ANL) and the involute reactors have formed an informal scientific group, the Involute Working Group (IWG). The IWG facilitates inter-organizational collaboration on experimental benchmarking, code-to-code comparisons, and Verification and Validation (V&V). This paper describes some of the recent IWG efforts in validating software against the existing experimental data, as well as code-to-code comparisons of different software used by the IWG members.

Bergeron, Aurelien↗