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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 OSTI2016

Distribution of Dengue Virus Types 1 and 4 in Blood Components from Infected Blood Donors from Puerto Rico

Dengue is a mosquito-borne viral disease caused by the four dengue viruses (DENV-1 to 4) that can also be transmitted by blood transfusion and organ transplantation. The distribution of DENV in the components of blood from infected donors is poorly understood. Here, we used an in-house TaqMan qRT-PCR assay to test residual samples of plasma, cellular components of whole blood (CCWB), serum and clot specimens from the same collection from blood donors who were DENV-RNA-reactive in a parallel blood safety study. To assess whether DENV RNA detected by TaqMan was associated with infectious virus, DENV infectivity in available samples was determined by culture in mosquito cells. As a result, DENV RNA was detected by TaqMan in all tested blood components, albeit more consistently in the cellular components; 78.8% of CCWB, 73.3% of clots, 86.7% of sera and 41.8% of plasma samples. DENV-1 was detected in 48 plasma and 97 CCWB samples while DENV-4 was detected in 21 plasma and 31 CCWB samples. In mosquito cell cultures, 29/111 (26.1%) plasma and 32/97 (32.7%) CCWB samples were infectious. A subset of samples from 29 donors was separately analyzed to compare DENV viral loads in the available blood components. DENV viral loads did not differ significantly between components and ranged from 3–8 log 10 PCR-detectable units/ml. In conclusion, DENV was present in all tested components from most donors, and viral RNA was not preferentially distributed in any of the tested components. Infectious DENV was also present in similar proportions in cultured plasma, clot and CCWB samples, indicating that these components may serve as a resource when sample sizes are limited. However, these results suggest that the sensitivity of the nucleic acid tests (NAT) for these viruses would not be improved by testing whole blood or components other than plasma.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO 2 -based Enhanced Oil Recovery

TOGA is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO 2 , multicomponent oil, and related gas components for applications including CO 2 -enhanced oil recovery (CO 2 -EOR) and geologic carbon sequestration in depleted oil and gas reservoirs. TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase. The phase behavior (e.g., occurrence and disappearance of the three phases, gas + oil + aqueous) and the partitioning of non-aqueous components (e.g., CO 2 , CH 4 , and n-oil components) between coexisting phases are modeled using K-values derived from assumptions of equal-fugacity that have been demonstrated to be very accurate as shown by comparison to measured data. Models for saturated (water) vapor pressure and water solubility (in the oil phase) are used to calculate the partitioning of the water (H 2 O) component between the gas and oil phases. All components (e.g., CO 2 , H 2 O, and n hydrocarbon components) are allowed to be present in all phases (aqueous, gaseous, and oil). TOGA uses a multiphase version of Darcy’s Law to model flow and transport through porous media of mixtures with up to three phases over a range of pressures and temperatures appropriate to hydrocarbon recovery and geologic carbon sequestration systems. Transport of the gaseous and dissolved components is by advection and Fickian molecular diffusion. New methods for phase partitioning and thermophysical property modeling in TOGA have been validated against experimental data published in the literature for describing phase partitioning and phase behavior. Flow and transport has been verified by testing against related TOUGH2 EOS modules and CMG. The code has also been validated against a CO 2 -EOR experimental core flood involving flow of three phases and 12 components. Results of simulations of a hypothetical 3D CO 2 -EOR problem involving three phases and multiple components are presented to demonstrate the field-scale capabilities of the new code. This user guide provides instructions for use and sample problems for verification and demonstration.

97 MATHEMATICS AND COMPUTING↗

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↗

NASA NTRS1990

Model reduction by weighted Component Cost Analysis

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Kim, Jae H.↗

NASA NTRS2002

Differential adaptation of the linear and nonlinear components of the horizontal vestibuloocular reflex in squirrel monkeys

Previous work in squirrel monkeys has demonstrated the presence of linear and nonlinear components to the horizontal vestibuloocular reflex (VOR) evoked by high-acceleration rotations. The nonlinear component is seen as a rise in gain with increasing velocity of rotation at frequencies more than 2 Hz (a velocity-dependent gain enhancement). We have shown that there are greater changes in the nonlinear than linear component of the response after spectacle-induced adaptation. The present study was conducted to determine if the two components of the response share a common adaptive process. The gain of the VOR, in the dark, to sinusoidal stimuli at 4 Hz (peak velocities: 20-150 degrees /s) and 10 Hz (peak velocities: 20 and 100 degrees /s) was measured pre- and postadaptation. Adaptation was induced over 4 h with x0.45 minimizing spectacles. Sum-of-sines stimuli were used to induce adaptation, and the parameters of the stimuli were adjusted to invoke only the linear or both linear and nonlinear components of the response. Preadaptation, there was a velocity-dependent gain enhancement at 4 and 10 Hz. In postadaptation with the paradigms that only recruited the linear component, there was a decrease in gain and a persistent velocity-dependent gain enhancement (indicating adaptation of only the linear component). After adaptation with the paradigm designed to recruit both the linear and nonlinear components, there was a decrease in gain and no velocity-dependent gain enhancement (indicating adaptation of both components). There were comparable changes in the response to steps of acceleration. We interpret these results to indicate that separate processes drive the adaptation of the linear and nonlinear components of the response.

Non-NASA Center↗

NASA NTRS2004

Method for vacuum pressing electrochemical cell components

Assembling electrochemical cell components using a bonding agent comprising aligning components of the electrochemical cell, applying a bonding agent between the components to bond the components together, placing the components within a container that is essentially a pliable bag, and drawing a vacuum within the bag, wherein the bag conforms to the shape of the components from the pressure outside the bag, thereby holding the components securely in place. The vacuum is passively maintained until the adhesive has cured and the components are securely bonded. The bonding agent used to bond the components of the electrochemical cell may be distributed to the bonding surface from distribution channels in the components. To prevent contamination with bonding agent, some areas may be treated to produce regions of preferred adhesive distribution and protected regions. Treatments may include polishing, etching, coating and providing protective grooves between the bonding surfaces and the protected regions.

Andrews, Craig C.↗

NASA NTRS2013

The XRD Amorphous Component in John Klein Drill Fines at Yellowknife Bay, Gale Crater, Mars

Drill fines of mudstone (targets John Klein and Cumberland) from the Sheepbed unit at Yel-lowknife Bay were analyzed by MSL payload elements including the Chemistry and Mineralogy (CheMin), APXS (Alpha Particle X-Ray Spectrometer), and Sample Analysis at Mars (SAM) instruments. CheMin XRD results show a variety of crystalline phases including feldspar, pyroxene, olivine, oxides, oxyhydroxides, sulfates, sulfides, a tri-octahedral smectite, and XRD amorphous material. The drill fines are distinctly different from corresponding analyses of the global soil (target Rocknest) in that the mudstone samples contained detectable phyllosilicate. Here we focus on John Klein and combine CheMin and APXS data to calculate the chemical composition and concentration of the amorphous component. The chemical composition of the amorphous plus smectite component for John Klein was calculated by subtracting the abundance-weighted chemical composition of the individual XRD crystalline components from the bulk composition of John Kline as measured by APXS. The chemical composition of individual crystalline components was determined either by stoichiometry (e.g., hematite and magnetite) or from their unit cell parameters (e.g., feldspar, olivine, and pyroxene). The chemical composition of the amorphous + smectite component (approx 71 wt.% of bulk sample) and bulk chemical composition are similar. In order to calculate the chemical composition of the amorphous component, a chemical composition for the tri-octahedral smectite must be assumed. We selected two tri-octahedral smectites with very different MgO/(FeO + Fe2O3) ratios (34 and 1.3 for SapCa1 and Griffithite, respectively). Relative to bulk sample, the concentration of amorphous and smectite components are 40 and 29 wt.% for SapCa1 and 33 and 36 wt.% for Griffithite. The amount of smectite was calculated by requiring the MgO concentration to be approx 0 wt.% in the amorphous component. Griffithite is the preferred smectite because the position of its 021 diffraction peak is similar to that reported for John Klein. In both cases, the amorphous component has low SiO2 and MgO and high FeO + Fe2O3, P2O5, and SO3 concentrations relative to bulk sample. The chemical composition of the bulk drill fines and XRD crystalline, smectite, and amorphous components implies alteration of an initially basaltic material under near neutral conditions (not acid sulfate), with the sulfate incorporated later as veins of CaSO4 injected into the mudstone.

Morris, Richard V.↗

NASA NTRS2017

The Effect of Shock on the Amorphous Component in Altered Basalt

Investigation of the geochemical and mineralogical composition of the Martian surface provides insight into the geologic history of the predominantly basaltic crust. The Chemistry and Mineralogy (CheMin) instrument onboard the Curiosity rover has returned the first X-Ray diffraction data from the Martian surface. However, large proportions (27 +/- 14 with some estimates as high as 50 weight percentage) of an amorphous component have been reported. As a remedy to this problem, mass balance equations using geochemistry, volatile chemistry, and mineralogy have been employed to constrain the geochemistry of the amorphous component. However, "the nature and number of amorphous phases that constitute the amorphous component is not unequivocally known". Multiple hypotheses have been proposed to explain the origin of this amorphous component: Allophane (Al2O); Basaltic glass (Volcanic and impact); Palagonite (Altered basaltic glass); Hisingerite (Fe (sup 3 plus)-bearing phyllosilicate); S/Cl-rich component (sulfates and/or akaganeite); Nanophase ferric oxide component (npOx). Establishing a multi-phase amorphous component from a basaltic precursor that has undergone physical and chemical weathering within geochemical constraints is of paramount importance to better understand the composition of a large portion of the Martian surface (up to 50 weight percentage). Shocked basalts from Lonar Crater in India are valuable analogs for the Martian surface because it is a well-preserved impact crater in a basaltic target. Having undergone pre- and post-shock aqueous alteration, these rocks provide crucial data regarding the effect of shock on the amorphous component in altered basalt. By conducting mass balance equations similar to what has been performed for Gale crater materials, we attempt to calculate the geochemistry of the amorphous component in altered basalts ranging from unshocked to Class 5 (Table 1). This has the potential to reveal the nature and origin (i.e. primary igneous, shock metamorphic, and/or aqueous alteration occurring before or after the impact event) of the amorphous component in shocked basalt with the goal of unravelling the history of the Martian surface.

Eckley, S. A.↗

DOE OSTI2015

Component Repair Times Obtained from MSPI Data

Information concerning times to repair or restore equipment to service given a failure is valuable to probabilistic risk assessments (PRAs). Examples of such uses in modern PRAs include estimation of the probability of failing to restore a failed component within a specified time period (typically tied to recovering a mitigating system before core damage occurs at nuclear power plants) and the determination of mission times for support system initiating event (SSIE) fault tree models. Information on equipment repair or restoration times applicable to PRA modeling is limited and dated for U.S. commercial nuclear power plants. However, the Mitigating Systems Performance Index (MSPI) program covering all U.S. commercial nuclear power plants provides up-to-date information on restoration times for a limited set of component types. This paper describes the MSPI program data available and analyzes the data to obtain median and mean component restoration times as well as non-restoration cumulative probability curves. The MSPI program provides guidance for monitoring both planned and unplanned outages of trains of selected mitigating systems deemed important to safety. For systems included within the MSPI program, plants monitor both train UA and component unreliability (UR) against baseline values. If the combined system UA and UR increases sufficiently above established baseline results (converted to an estimated change in core damage frequency or CDF), a “white” (or worse) indicator is generated for that system. That in turn results in increased oversight by the US Nuclear Regulatory Commission (NRC) and can impact a plant’s insurance rating. Therefore, there is pressure to return MSPI program components to service as soon as possible after a failure occurs. Three sets of unplanned outages might be used to determine the component repair durations desired in this article: all unplanned outages for the train type that includes the component of interest, only unplanned outages associated with failures of the component of interest, and only unplanned outages associated with PRA failures of the component of interest. The paper will describe how component repair times can be generated from each set and which approach is most applicable. Repair time information will be summarized for MSPI pumps and diesel generators using data over 2003 – 2007. Also, trend information over 2003 – 2012 will be presented to indicate whether the 2003 – 2007 repair time information is still considered applicable. For certain types of pumps, mean repair times are significantly higher than the typically assumed 24 h duration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

Following the successful completion of a 15-year effort to develop and test materials that would allow coal-fired power plants to be operated at advanced ultra-supercritical (A-USC) steam conditions, a United States-based consortium is presently engaged in Phase 2 of a project which includes an advanced manufacturing effort to complete US-based supply chain development for full commercial scale (800-850 MWe) A-USC components made of nickel-based alloys, components operating at up to 760°C. The project, funded under U.S. Department of Energy Award No. DE-FE0025064, falls under the US DOE overall goal to Develop cost-effective, reliable technologies to improve the efficiency of new and existing coal-fired power plants. A-USC steam cycles have the potential to improve cycle efficiency, reduce fuel costs, and reduce greenhouse gas emissions. Current development and demonstration efforts are focused on enabling the construction of A-USC plants, operating with steam temperatures as high as 1400°F (760°C) and steam pressures up to 5000 psi (35 MPa), which can potentially increase cycle efficiencies to 47% HHV (higher heating value), or approximately 50% LHV (lower heating value), and reduce CO 2 emissions by roughly 25%, compared to today’s U.S. fleet. A-USC technology provides a lower-cost method to reduce CO 2 emissions, compared to CO 2 capture technologies, while retaining a viable coal option for owners of coal generation assets. Among the specific goals of Phase 2 of the ComTest Project are to: validate that components made from advanced nickel-based alloys can operate and perform under A-USC conditions accelerate the development of a U.S.-based supply chain for the full complement of A-USC components close the remaining gaps and reduce the risks for manufacturing components from advanced materials for commercial demonstration fabricate full-scale versions of selected key components made of nickel-based alloys validate a qualified U.S. supply chain, to provide greater cost certainty for components obtain American Society of Mechanical Engineers (ASME) code approval for new materials, components and processes Additional benefit: Manufacturing technology will be applicable to other advanced fossil energy high temperature cycles, and can support increased flexibility of existing power plants The ComTest project is managed by Energy Industries of Ohio, and technically directed by the Electric Power Research Institute, Inc., with General Electric designing the A-USC components. As stated earlier, the current phase of the effort is primarily funded by the U.S. Department of Energy, through the National Energy Technology Laboratory. This presentation outlines the motivation for the project, explains the project’s structure and schedule, and provides some of the technical details on the design of the ComTest components.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Metallic components with enhanced mechanical strength through surface mechanical grinding

A method of strengthening a component made of a metallic material. The method includes subjecting the component to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure on the surface of the component, resulting in increased tensile strength of the component. A method of strengthening a component made of a TWIP steel. The method includes subjecting the component made of TWIP steel to a mechanical grinding process incorporating a relative motion between a tool and the component forming a gradient structure containing a surface nanolaminate layer, a shear band layer, and an inner deformation twinned layer, resulting in increased tensile strength of the component. A component made of a TWIP steel containing a gradient structure with a surface nanolaminate layer, a shear band layer, and a deformation twinned layer.

Ding, Jie↗

DOE OSTI2023

Metallic components with enhanced mechanical strength through surface mechanical grinding

Ding, Jie↗