SEARCH · Search NASA

Results for “component”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Transfer Learning-Based Independent Component Analysis

Understanding the underlying component structure is crucial for multivariate signal analysis. Among all the techniques that try to learn the latent structure, independent component analysis (ICA) is one of the most important and popular methods, which aims to extract independent components from multivariate signals and enables further analysis. For example, in electroencephalogram (EEG) analysis, artifacts filtering and disease detection are conducted based on the independent components of the signals. One critical challenge in existing ICA approaches is that the component extraction accuracy may degrade when the available data of a unit are limited. To address this issue, this paper proposes a transfer learning-based ICA method by innovatively transferring component distribution from a source domain, so that accurate component extraction results can be achieved even when only limited data are available in the target domain. To the best of our knowledge, this is the first work that leverages transfer learning to improve ICA accuracy with limited available data. In particular, we first extract all the independent components from the source domain by maximizing the log-likelihood function with a Newton-like method on a smooth manifold. Then for the target domain, the component with the largest negentropy is extracted in each round. To effectively leverage the knowledge from the source domain and to prevent the negative transfer, we try to find a component in the source domain that matches the component we are extracting. The probability density function of the matched component will then be used to improve the component extraction accuracy if such matched component can be found; otherwise, no knowledge will be transferred. Finally, numerical simulations and a case study with electrocardiogram (ECG) data are conducted, showing the effectiveness of the proposed method in transferring knowledge and reducing negative transfer.

42 ENGINEERING↗

DOE OSTI2022

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

The U.S. Advanced Ultra-Supercritical (A-USC) Consortium was formed in 2001 as a government/industry program, sponsored by the U.S. Department of Energy (DOE) and the Ohio Coal Development Office (OCDO) and cost shared by industrial and not-for-profit partners. The purpose of the consortium was to advance the state of the art for power generation by evaluating and developing materials that allow the use of advanced steam cycles in coal-based power plants. These advanced cycles, with steam temperatures up to 1400°F (760°C), can increase the efficiency of coal-fired boilers from an average of 35% (current U.S. fleet) to more than 45% higher heating value (HHV) (>49% lower heating value [LHV]). The increase in a plant’s efficiency is limited unless new materials able to withstand these higher operating temperatures and pressures are identified and approved for use. The A-USC Consortium identified these needed materials during earlier phases of the program. It developed the welding and joining techniques along with manufacturing processes for casting and wrought products made from these new high-nickel alloys. It subjected these materials to extensive laboratory and steam loop testing. It then obtained ASME code approval for their use in U.S. boiler systems. The program’s successes leave this last remaining activity (ComTest Phase 2) that the U.S. utility industry has recommended to be accomplished prior to commercialization. The focus of the activity is the evaluation and demonstration of commercial readiness for “full scale” components to be made from these nickel-based alloy materials and provided by a U.S. domestic supply chain that is new to working with these alloys. According to studies completed by the Electric Power Research Institute (EPRI), the cost of an A-USC plant is approximately 20% higher than a non-A-USC plant because of its use of nickel-based alloys needed for the high temperature operating conditions. However, CO 2 reductions of approximately 30% from the current fleet average provide a strong incentive for its consideration. The actual costs and perceived value for CO 2 abatement will determine whether new or retrofitted plants are undertaken, although decisions to build A-USC plants in India would indicate its economic feasibility while also being part of a global carbon emissions strategy. The work by the A-USC Consortium, prior to the start of the ComTest project, has included lab scale and pilot scale materials testing, both in air and oxy-combustion. This testing has included air-cooled and steam-cooled “loops” that were installed into existing operating utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion caused by the constituents in the coal ash. The A-USC Consortium also gained ASME Code approval of the Inconel 740 material, has cast and extruded the largest high nickel precipitation hardened alloys, and developed unique welding techniques to avoid problems identified by the competing European program. However, as valuable as these material test loops and accomplishments have been for obtaining information, their scale is below that required to minimize the risk associated for a U.S. utility to build a multibillion-dollar A-USC power plant. To reduce the final identified risk barrier to full-scale commercialization of these advanced materials and systems, the A-USC Consortium (guided by a utility industry advisory committee) has identified the key areas of the technology they desire to see as being capable of full-scale manufacturing and/or fabrication from an identified, capable U.S. domestic supplier base. 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. The Phase 2 effort used Phase 1 findings for designing these key full-scale components for A-USC boilers and turbines to include large castings; extrusions, forgings, fabrication of water walls and steam loops with headers from advanced materials, raw material (such as pipe extrusion billets) are at the commercial readiness level to permit advancement to a demonstration project. The Phase 2 work scope was addressed by a diverse team, including government, industry, and not-for-profit partners. The work scope under Phase 2 addressed fabrication of components identified as being outside of the proven capabilities of the existing supply chain, including the following: Steam turbine rotor forging and Haynes 282 nozzle carrier casting Superheater and reheater header and tube assemblies Large-diameter pipe extrusions and forgings Test valve articles to support ASME Code approval. In addition, key fabrication steps were completed, including boiler weld overlays and simulated field repairs. Throughout, extensive inspection and quality assurance testing of the components were performed. The team worked to advance ASME Code approval for key components and processes. Although much of the focus of ComTest Phase 2 was the high-temperature nickel-based alloy materials, a broader range of materials were incorporated, which would be representative of the materials used in full-scale A-USC power plant applications and have cross-cutting applicability on other high-temperature power generation options, such as advanced nuclear, supercritical CO 2 cycles, and central solar receivers. This report that has been submitted is organized in the following manner: Section 1 contains an Executive Summary. Section 2 discusses the ComTest project background and organization. Section 3 discusses project management and reporting. Section 4 discusses the procurement of nickel-based alloy and other A-USC materials and components. Section 5 discusses the fabrication of procurement of nickel-based alloy and other A-USC materials and components. Section 6 discusses the fabrication of cast nickel-based A-USC steam turbine components. Section 7 discusses the fabrication of forged nickel-based A-USC steam turbine piping and steam pipe components. Section 8 discusses the qualification of pressure relieve valves (PRVs) for A-USC power plants. Section 9 discusses proposed plans for future evaluation of A-USC components. Section 10 contains the summary and conclusion.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

NASA NTRS2001

Jet Stability and the Generation of Superluminal and Stationary Components

We present a numerical simulation of the response of an expanding relativistic jet to the ejection of a superluminal component. The simulation has been performed with a relativistic time-dependent hydrodynamical code from which simulated radio maps are computed by integrating the transfer equations for synchrotron radiation. The interaction of the superluminal component with the underlying jet results in the formation of multiple conical shocks behind the main perturbation. These trailing components can be easily distinguished because they appear to be released from the primary superluminal component instead of being ejected from the core. Their oblique nature should also result in distinct polarization properties. Those appearing closer to the core show small apparent motions and a very slow secular decrease in brightness and could be identified as stationary components. Those appearing farther downstream are weaker and can reach superluminal apparent motions. The existence of these trailing components indicates that not all observed components necessarily represent major perturbations at the jet inlet; rather, multiple emission components can be generated by a single disturbance in the jet. While the superluminal component associated with the primary perturbation exhibits a rather stable pattern speed, trailing components have velocities that increase with distance from the core but move at less than the jet speed. The trailing components exhibit motion and structure consistent with the triggering of pinch modes by the superluminal component. The increase in velocity of the trailing components is an indirect consequence of the acceleration of the expanding fluid, which is assumed to be relativistically hot; if observed, such accelerations would therefore favor an electron-positron (as opposed to proton rest mass) dominated jet.

Agudo, Ivan↗

NASA NTRS2006

Leveraging Existing Mission Tools in a Re-Usable, Component-Based Software Environment

Emerging methods in component-based software development offer significant advantages but may seem incompatible with existing mission operations applications. In this paper we relate our positive experiences integrating existing mission applications into component-based tools we are delivering to three missions. In most operations environments, a number of software applications have been integrated together to form the mission operations software. In contrast, with component-based software development chunks of related functionality and data structures, referred to as components, can be individually delivered, integrated and re-used. With the advent of powerful tools for managing component-based development, complex software systems can potentially see significant benefits in ease of integration, testability and reusability from these techniques. These benefits motivate us to ask how component-based development techniques can be relevant in a mission operations environment, where there is significant investment in software tools that are not component-based and may not be written in languages for which component-based tools even exist. Trusted and complex software tools for sequencing, validation, navigation, and other vital functions cannot simply be re-written or abandoned in order to gain the advantages offered by emerging component-based software techniques. Thus some middle ground must be found. We have faced exactly this issue, and have found several solutions. Ensemble is an open platform for development, integration, and deployment of mission operations software that we are developing. Ensemble itself is an extension of an open source, component-based software development platform called Eclipse. Due to the advantages of component-based development, we have been able to vary rapidly develop mission operations tools for three surface missions by mixing and matching from a common set of mission operation components. We have also had to determine how to integrate existing mission applications for sequence development, sequence validation, and high level activity planning, and other functions into a component-based environment. For each of these, we used a somewhat different technique based upon the structure and usage of the existing application.

Greene, Kevin↗

NASA NTRS2002

Method for distributed object communications based on dynamically acquired and assembled software components

A method for acquiring and assembling software components at execution time into a client program, where the components may be acquired from remote networked servers is disclosed. The acquired components are assembled according to knowledge represented within one or more acquired mediating components. A mediating component implements knowledge of an object model. A mediating component uses its implemented object model knowledge, acquired component class information and polymorphism to assemble components into an interacting program at execution time. The interactions or abstract relationships between components in the object model may be implemented by the mediating component as direct invocations or indirect events or software bus exchanges. The acquired components may establish communications with remote servers. The acquired components may also present a user interface representing data to be exchanged with the remote servers. The mediating components may be assembled into layers, allowing arbitrarily complex programs to be constructed at execution time.

Sundermier, Amy↗

DOE OSTI2021

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Riveted assemblies and methods for riveting components

Riveted assemblies are provided that can include: a first component having opposing first and second sidewalls; a second component having opposing third and fourth sidewalls, wherein the second sidewall of the first component abuts the third sidewall of the second component to bind and form an affixing interface comprising the second and third sidewall between the first component to the second component; and a rivet extending between a head along a shank to an end, the rivet piercing the first sidewall with the end of the rivet being between the first and fourth sidewalls. Methods for affixing at least two components using a rivet are also provided. The methods can include: providing a first component having opposing first and second sidewalls; providing a second component having opposing third and fourth sidewalls; abutting the second sidewall of the first component to the third sidewall of the second component; providing a rivet extending between a head along a shank to an end; projecting the rivet through at least the first sidewall of the first component to form an affixing interface comprising the second and third sidewalls.

Joshi, Vineet V.↗

DOE OSTI2024

Riveted assemblies and methods for riveting components

Joshi, Vineet V.↗

DOE OSTI2018

Failure Rate Estimates for Passive Mechanical Components

Fusion design projects that reach the stage of design reviews typically require reliability, availability, maintainability and inspectability (RAMI) assessments. While many kinds of reliability and maintainability data are needed for a wide variety of fusion components to quantify a RAMI assessment, one of the types of components requiring data is the passive mechanical component. Passive mechanical components can be items such as metal plates, rods, shafts, brackets, bolts, and other items. Generally these passive components tend to have low failure rates since they are simple designs, have no or few moving parts, and do not need control signals to perform their design function. However, there are no widely recognized datasets for such components, so analysts must use multiple datasets and judgment for failure rates. This report gives recommended failure rates for various failure modes of these components, and gives suggested failure rate multipliers to apply to these failure rates if they reside in harsh environments. If the component resides far from the tokamak then typical industrial failure rates would suffice. Components near the tokamak find conditions can be demanding; similar to those in a fission reactor containment building. Some component failure rates can be modified if the components reside inside the tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1990

Evaluation of composite components on the Bell 206L and Sikorsky S-76 helicopters

Progress on two programs to evaluate structural composite components in flight service on Bell 206L and Sikorsky S-76 commercial helicopters is described. Forty ship sets of composite components that include the litter door, baggage door, forward fairing, and vertical fin have been installed on Bell Model 206L helicopters that are operating in widely different climates. Component installation started in 1981 and selected components were removed and tested at prescribed intervals over a ten year evaluation. Four horizontal stabilizers and eleven tail rotor spars that are production components on the S-76 helicopter were tested after prescribed periods of service to determine the effects of the operating environment on their performance. Concurrent with the flight evaluation, materials used to fabricate the components were exposed in ground racks and tested at specified intervals to determine the effects of outdoor environments. Results achieved from 123,000 hours of accumulated service on the Bell 206L components and 53,000 hours on the Sikorsky S-76 components are reported. Seventy-eight Bell 206L components were removed and tested statically. Results of seven years of ground exposure of materials used to fabricate the Bell 206L components are presented. Results of tests on four Sikorsky S-76 horizontal stabilizers and eleven tail rotor spars are also presented. Panels of material used to fabricate the Sikorsky S-76 components that were exposed for six years were tested and results are presented.

Baker, Donald J.↗

NASA NTRS2007

Space Flight Requirements for Fiber Optic Components; Qualification Testing and Lessons Learned

"Qualification" of fiber optic components holds a very different meaning than it did ten years ago. In the past, qualification meant extensive prolonged testing and screening that led to a programmatic method of reliability assurance. For space flight programs today, the combination of using higher performance commercial technology, with shorter development schedules and tighter mission budgets makes long term testing and reliability characterization unfeasible. In many cases space flight missions will be using technology within years of its development and an example of this is fiber laser technology. Although the technology itself is not a new product the components that comprise a fiber laser system change frequently as processes and packaging changes occur. Once a process or the materials for manufacturing a component change, even the data that existed on its predecessor can no longer provide assurance on the newer version. In order to assure reliability during a space flight mission, the component engineer must understand the requirements of the space flight environment as well as the physics of failure of the components themselves. This can be incorporated into an efficient and effective testing plan that "qualifies" a component to specific criteria defined by the program given the mission requirements and the component limitations. This requires interaction at the very initial stages of design between the system design engineer, mechanical engineer, subsystem engineer and the component hardware engineer. Although this is the desired interaction what typically occurs is that the subsystem engineer asks the components or development engineers to meet difficult requirements without knowledge of the current industry situation or the lack of qualification data. This is then passed on to the vendor who can provide little help with such a harsh set of requirements due to high cost of testing for space flight environments. This presentation is designed to guide the engineers of design, development and components, and vendors of commercial components with how to make an efficient and effective qualification test plan with some basic generic information about many space flight requirements. Issues related to the ~ physics of failure, acceptance criteria and lessons learned will also be discussed to assist with understanding how to approach a space flight mission in an ever changing commercial photonics industry.

Ott, Melanie N.↗

DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Status Report on ASME Code Development for Nonmetallic Core Components in 2020

The purpose of this report is to provide a status update on the progress and ongoing activities of the current ASME Boiler Pressure Vessel (BPV) Code Section III, Division 5, on nonmetallic core components and assemblies which includes the design rules for graphite and ceramic composite materials. Section III is concerned with the design and construction of nuclear reactor components and Division 5 focuses on high temperature reactors (HTR). The ASME Section III Committee’s function for nuclear items other than pressure-retaining components, is to establish rules of safety related to structural integrity. The term “construction” refers to the all-inclusive effort comprising of materials, design, fabrication, examination, inspection, testing, certification, and pressure relief. The Department of Energy (DOE) supports industry codes and standards development through focused research providing the technical basis for new or modified codes and standards and the participation of subject matter experts in codes and standards committees. The activities for the nonmetallic core components and assemblies committees are the pursuit of two working groups that meet quarterly during ASME BPV Code Week meetings. The two working groups are General Requirements for Graphite and Ceramic Composite Core Components and Assemblies (GR GCCCCA) and Nonmetallic Design and Materials (NDM). The rules on general requirements for nonmetallic core components are discussed in the articles of Subsection HA subpart B. Ceramic composites were recently incorporated within the rules, and the GR GCCCCA working group is now in the process of aligning the requirements with the subsections and articles of ASME BPV Code Section III NCA, the general requirements for Division 1 and 2 of the code. The NDM working group is concerned with the design rules for graphite and composite materials for core components and assemblies discussed in Subsection HH (Class SN Nonmetallic Core Components) subpart A and subpart B which reference graphite and composite materials respectively. The bulk of the progress and work is done within this working group. A significant undertaking, with discussion that started in 2015, is to gain endorsement of ASME Section III, Division 5, by the U.S. Nuclear Regulatory Commission (NRC). In June 2018, ASME formally recommended endorsement to the NRC. The NRC has since initiated the endorsement review process, which is to be concluded early in 2021. ASME task groups on metallic structures and components, as well as non-metallic core support structures, have been formed to define potential pathways and schedules for NRC endorsement of Division 5. NRC determined to perform a review on the 2017 edition of Section III Division 5 as a baseline. As a result, the use of graphite as nonmetallic core components formed part of the review, but it excluded composite materials (which were first introduced in the 2019 edition). This report documents progress in FY 2020 directed toward ASME’s efforts to develop design codes for graphite and composites. Progress includes a major code review by NRC, the first code enquiry, and its solution, an overhaul of the treatment of Weibull Statistics, and the addition of Nonmandatory Appendices to the composites code relating to carbon-carbon composite materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Development of a Novel Magnesium Alloy for Thixomolding® of Automotive Components (Final Report)

Magnesium (Mg) alloy die-castings are increasingly used in the automobile industry to achieve cost effective mass reduction, especially in systems where multiple components can be integrated into a single thin wall die-casting. However, there are several component quality restrictions in thin-walled Mg die castings, including variability in dimensional accuracy, part-to-part variation in mechanical properties, and porosity in the final part, which has limited the continued growth of die-cast components in the automobile industry. An alternative to die-casting is the process of thixomolding®. While the die-casting process relies on filling a mold at high speeds with the alloy in the completely molten state, the thixomolding® process fills a mold with a thixotropic alloy in a semi-solid slurry state at a temperature between the liquidus and solidus temperatures. Ideally, the material should be ~30–65% solid rather than being completely liquid at the beginning of the injection process. Advantages of the thixomolding® process include a finer grain structure, lower porosity, improved dimensional accuracy, improved part-to part consistency, improved mechanical properties, particularly ductility in the component, the ability to reduce wall thickness for mass savings, and longer tool life due to lower process temperatures. The objective of this collaborative project between Oak Ridge National Laboratory, FCA US LLC, and Leggera Technologies was to develop one or more novel Mg alloys more suitable for thixomolding® automotive structural components than the current die-casting alloys used for this process. The primary interest was to improve ductility while maintaining tensile and fatigue strengths, as these are properties that are critical for use in body and chassis structural applications. Since good corrosion resistance is also desirable for this application, this property was also considered when evaluating promising alloy compositions. An initial evaluation of existing components thixomolded® using AM60 was performed and microstructure, and tensile properties were evaluated for the baseline alloy. Targets were established for ease of processing (characterized by the melting range defined as the difference between the liquidus and the solidus), strength, and ductility. Computational modeling was used to identify promising alloys and selected alloys were cast in laboratory scale heats. Properties measured from laboratory scale heats were used to down-select two alloys for further evaluation and component fabrication. Two alloys were prepared in industrial scale heats, cut into small pieces (chips), and thixomolding® trials were initiated. Trial components were successfully fabricated using one alloy composition, but it was concluded that further refinement of the thixomolding® process parameters are required to successfully fabricate component using second alloy. Microstructure and mechanical properties were evaluated on the material removed from the fabricated component and properties were compared to the baseline alloy. Although mechanical properties of the alloys showed improvement over the baseline alloy, it was determined that modifications to the thixomolding® process would result in better microstructure control with further improvement in properties leading to successful commercialization. A provisional patent application has already been filed on the new alloys developed as part of the project.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1988

Block-Krylov component synthesis method for structural model reduction

A new analytical method is presented for generating component shape vectors, or Ritz vectors, for use in component synthesis. Based on the concept of a block-Krylov subspace, easily derived recurrence relations generate blocks of Ritz vectors for each component. The subspace spanned by the Ritz vectors is called a block-Krylov subspace. The synthesis uses the new Ritz vectors rather than component normal modes to reduce the order of large, finite-element component models. An advantage of the Ritz vectors is that they involve significantly less computation than component normal modes. Both 'free-interface' and 'fixed-interface' component models are derived. They yield block-Krylov formulations paralleling the concepts of free-interface and fixed-interface component modal synthesis. Additionally, block-Krylov reduced-order component models are shown to have special disturbability/observability properties. Consequently, the method is attractive in active structural control applications, such as large space structures. The new fixed-interface methodology is demonstrated by a numerical example. The accuracy is found to be comparable to that of fixed-interface component modal synthesis.

Craig, Roy R., Jr.↗

NASA NTRS1990

Dynamic substructuring by the boundary flexibility vector method of component mode synthesis

Component mode synthesis (CMS) is a method of dynamic analysis, for structures having a large number of degrees of freedom (DOF). These structures often required lengthy computer CPU time and large computer memory resources, if solved directly by the finite-element method (FEM). In CMS, the structure is divided into independent components in which the DOF are defined by a set of generalized coordinates defined by displacement shapes. The number of the generalized coordinates are much less than the original number of physical DOF, in the component. The displacement shapes are used to transform the component property matrices and any applied external loads, to a reduced system of coordinates. Reduced system property matrices are assembled, and any type of dynamic analysis is carried out in the reduced coordinate system. Any obtained results are back transformed to the original component coordinate systems. In all conventional methods of CMS, the mode shapes used for components are dynamic mode shapes, supplemented by static deflected shapes. Historically, all the dynamic mode shapes used in conventional CMS are the natural modes (eigenvectors) of components. A new method of CMS, namely the boundary flexibility vector method of CMS, is presented. The method provides for the incorporation of a set of static Ritz vectors, referred to as boundary flexibility vectors, as a replacement and/or supplement to conventional eigenvectors, as displacement shapes for components. The generation of these vectors does not require the solution of a costly eigenvalue problem, as in the case of natural modes in conventional CMS, and hence a substantial saving in CPU time can be achieved. The boundary flexibility vectors are generated from flexibility (or stiffness) properties of components. The formulation presented is for both free and fixed-interface components, and for both the free and forced vibration problems. Free and forced vibration numerical examples are presented to verify the accuracy of the method and the saving in CPU time. Compared to conventional methods of CMS, the results indicate that by using the new method, more accurate results can be obtained with a substantial saving in CPU time.

Abdallah, Ayman Ahmed↗