Search NASA⌕ Search

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.

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

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Conceptual Design and Analysis of In-Vessel Components for the Materials Plasma Exposure eXperiment (MPEX)

The materials plasma exposure experiment (MPEX) is a linear plasma divertor simulator currently undergoing conceptual design. The facility will expose material samples to steady-state plasma fluxes to examine plasma–material interactions (PMIs) that are expected in the next generation of fusion devices. The plasmas will be generated by a helicon source, with electron and ion heating sources of up to 800 kW possible. The peak heat fluxes of the target are expected to be up to 10 MW/m 2 . The facility will be capable of handling low-activation neutron-irradiated samples in order to examine the multivariate effects of neutron damage and plasma fluence. Neutron-irradiated samples are planned to be roughly of 10-mm diameter; however, plasma-facing components up to 60×600 mm can be accommodated. The steady-state nature of the device will require the magnetic confinement of the plasma to be achieved with superconducting magnets, with a maximum on-axis field of 2.5 T. In addition, since MPEX will be a steady-state device, in-vessel components need to be water cooled. The primary in-vessel components will be the target, the dump plate, the limiter, the skimmers, and the microwave absorber. The conceptual design of these components is presented here, including analyses that confirm that the designs are adequate to meet the requirements of MPEX operation.

Lumsdaine, Arnold↗
DOE OSTI2022

Game-Theoretic Strategies for Cyber-Physical Infrastructures Under Component Disruptions

In this work, networked infrastructures of recursively defined systems composed of discrete cyber and physical components are considered. The components of basic systems at the finest levels can be disrupted by cyber or physical means, and can be reinforced to survive at certain costs. A problem of ensuring the infrastructure performance is formulated as a game between a provider and an attacker, who probabilistically choose components to reinforce and attack, respectively. The disruptions of this infrastructure are characterized using the aggregate failure correlation function that specifies the conditional failure probability of the infrastructure given the failure of an individual system at that level. The survival probabilities of basic systems satisfy simple product-form, first-order differential equations expressed in terms of the multiplier functions. The utility functions of the provider and attacker are composed of the reward and cost terms, both expressed in terms of the component reinforcement and attack probabilities. The Nash equilibrium of this game is characterized, along with the sensitivity functions of the survival probabilities of basic systems that highlight their dependence individually on the cost-benefit terms, the correlation functions, and the multiplier functions. These results are illustrated using simplified models of a distributed cloud servers infrastructure, a 5G data network infrastructure, a high performance computing federation, and a smart energy grid infrastructure.

42 ENGINEERING↗
DOE OSTI2021

Single-component-at-a-time variation study for glass-ceramic waste forms

Here, a 51-sample composition variation study was performed on glass-ceramic waste forms for a raffinate waste stream from aqueous reprocessing of used nuclear fuel containing high fractions of Mo, alkalis, alkaline earths (AEs), and rare earths (REs). The study was designed with a single-component-at-a-time variation approach off a centroid composition. The components that were varied included Al, B, Ca, Li, Mo, Na, REs, Si, Zr, and Others (containing minor components). Data analysis included crystallization curves, microstructure, and phase compositions. A number of components (i.e., Li 2 O, B 2 O 3 , REO x , MoO 3 , Na 2 O, and ZrO 2 ) significantly impacted the concentration and chemistry of phases, especially the primary phases of oxyapatite [i.e., Ca 2 RE 8 (SiO 4 ) 6 O 2 ] and powellite (i.e., AEMoO 4 ), precipitated in the slow-cool heat-treated waste forms; minor phases included cerianite [i.e., Ce x Zr (1-x) O 2 ], Ba-molybdate [i.e., Ba(Gd 0.67 Mo 0.33 O 3 ], noble metals, pollucite (i.e., CsAlSiO 4 ), and RE-borosilicate (i.e., RE 3 BSi 2 O 10 ).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Preliminary Component Design and Cost Estimation of a Novel Electric-Thermal Energy Storage System Using Solid Particles

Energy storage will become indispensable to complement the uncertainty of intermittent renewable resources and to firm the electricity supply as renewable power generation becomes the mainstream new-built energy source and fossil fuel power plants are phased out to meet carbon-neutral utility targets. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system is projected to have promising cost and performance characteristics to meet the future growing energy storage needs. This paper introduces the system and components required for particle TES to become technically and economically competitive. The system integrates electric particle heaters, particle TES within insulated concrete silos, and an efficient air-Brayton combined-cycle power system to provide power for storage durations up to several days via low-cost, high-performance storage cycles. Design specifications and cost estimation of major components in a commercial-scale system are presented in this paper. A techno-economic analysis based on preliminary component designs and performance indicates that particle TES integrated with an air-Brayton combined-cycle power system has a path to achieve the targeted levelized cost of storage of 5 ¢/kWh-cycle at a round-trip efficiency of 50% when taking low-cost energy-specific components and leveraging basic assets from existing thermal power plants. The cost model provides insights for further development and economic potentials for long-duration energy storage.

14 SOLAR ENERGY↗
DOE OSTI2024

Iterative Stress Reconstruction Algorithm to Estimate Three-Dimensional Residual Stress Fields in Manufactured Components

Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data result in convergence with fewer iterations. Finally, although ISRA yields a nonunique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.

42 ENGINEERING↗
DOE OSTI2020

Application of entropy and signal energy for ultrasound-based classification of three-dimensional printed polyetherketoneketone components

This paper describes a preliminary method for the classification of annealed and unannealed polyetherketoneketone (PEKK) components manufactured using a material extrusion three-dimensional (3D) printing process. PEKK is representative of a class of high-performance thermoplastics that are increasingly employed as feedstocks for use in 3D printing. PEKK components may be used continuously at elevated temperatures, are chemically resistant, and able to withstand large mechanical loads. These properties render PEKK suitable as a metal component replacement in aerospace applications, high-temperature industrial applications, and surgical implants. The structure of PEKK is semi-crystalline with the specific crystallinity correlating to the final properties during application, making determination of this property crucial. This study compares three different signal processing techniques intended to distinguish annealed (high crystallinity) from unannealed (low crystallinity) components using backscattered ultrasound. The first is energy-based and is unable to detect annealing. The second two are based on different entropies of the backscattered signal: a limiting form of Renyi's entropy and a limiting form of joint entropy. The joint entropy values for the annealed and unannealed specimens fall into two non-overlapping intervals and have a statistical separation of two standard deviations.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Dynamics of a Three-Component Delocalized Nonlinear Vibrational Mode in Graphene

The dynamics of a three-component nonlinear delocalized vibrational mode in graphene is studied with molecular dynamics. This mode, being a superposition of a root and two one-component modes, is an exact and symmetrically determined solution of nonlinear equations of motion of carbon atoms. The dependences of a frequency, energy per atom, and average stresses over a period that appeared in graphene are calculated as a function of amplitude of a root mode. We showed that the vibrations become periodic with certain amplitudes of three component modes, and the vibrations of one-component modes are close to periodic one and have a frequency twice the frequency of a root mode, which is noticeably higher than the upper boundary of a spectrum of low-amplitude vibrations of a graphene lattice. The data obtained expand our understanding of nonlinear vibrations of graphene lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Two-component axionic dark matter halos

We consider a two-component dark matter halo (DMH) of a galaxy containing ultra-light axions (ULA) of different mass. The DMH is described as a Bose–Einstein condensate (BEC) in its ground state. In the mean-field (MF) limit, we have derived the integro-differential equations for the spherically symmetrical wave functions of the two DMH components. We studied, numerically, the radial distribution of the mass density of ULA and constructed the parameters which could be used to distinguish between the two- and one-component DMH. Here, we also discuss an interesting connection between the BEC ground state of a one-component DMH and Black Hole temperature and entropy, and Unruh temperature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The role of individual surface flux components in the passive and active ocean heat uptake

Ocean model experiments forced by different combinations of heat, freshwater, and momentum perturbations associated with CO$_2$ increase, are used to isolate the role of individual surface forcing components on the passive and active ocean heat uptake components. The forcings are derived from a fully coupled CO2-quadrupling experiment. The passive uptake is due to the passive absorption of surface heat flux anomalies directly caused by CO2 increase by ocean circulation, while the active or redistributive feedback uptake is the indirectly forced ocean heat uptake caused by ocean circulation change. The passive component is similar among the experiments, therefore, is not sensitive to the circulation anomaly variation among the experiments, but the active component shows large differences. Surface heat flux perturbation causes the passive heat uptake and most of the AMOC weakening, however, it results in a net active heat loss (14% of the passive uptake). This net active heat loss is the residual of the active heat gain, primarily in the North Atlantic and heat loss, largely in the tropical Pacific. Fresh-water perturbation weakens the AMOC a little more, but causes a large active heat gain (40% of the passive uptake), largely in the North Atlantic. Wind perturbation causes about the same amount of active heat loss as heat flux perturbation, due to the poleward shift of the subtropical cells in the Southern Hemisphere. The experiments show that active ocean heat uptake is not simply determined by the degree of AMOC weakening.

Garuba, Oluwayemi A.↗
DOE OSTI2024

Tomographic FLEET with a wedge array for multi-point three-component velocimetry

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is an important diagnostic technique for seedless velocimetry measurements particularly in supersonic and hypersonic flows. Typical FLEET measurements feature a single laser line and camera system to achieve one-component velocimetry along a line, although some multiple-spot and multiple-component configurations have been demonstrated. In this work, tomographic imaging is used to track the three-dimensional location of many FLEET spots. A quadscope is used to combine four unique views onto a single high-speed image intensifier and camera. Tomographic reconstructions of the FLEET emission are analyzed for three-component velocimetry from multiple FLEET spots. Glass wedges are used to create many (nine) closely spaced FLEET spots with less than 10% transmission losses. These developments lead to a significant improvement in the dimensionality and spatial coverage of a FLEET instrument with some increases in experimental complexity and data processing. Multiple-point three-component FLEET velocimetry is demonstrated in an underexpanded jet.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components

Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.

3D printing, Additive Manufacturing, polymer, sint↗
DOE OSTI2018

Additive Manufacture of Plasma Diagnostic Components Final Report Phase II

There is now a well-established set of plasma diagnostics (see e.g. [3]), but these remain some of the most expensive assemblies in fusion systems since for every system they have to be custom built, and time for diagnostic development can pace the project. Additive manufacturing (AM) has the potential to decrease production cost and significantly lower design time of fusion diagnostic subsystems, which would realize significant cost reduction for standard diagnostics. In some cases, these basic components can be additively manufactured for less than 1/100th costs of conventional manufacturing.In our DOE Phase II SBIR, we examined the impact that AM can have on plasma diagnostic cost by taking 15 separate diagnostics through an engineering design using Conventional Manufacturing (CM) techniques, then optimizing the design to exploit the benefits of AM. The impact of AM techniques on cost is found to be in several areas. First, the cost of materials falls because AM parts can be manufactured with little to no waste, and engineered to use less material than CM. Next, the cost of fabrication falls for AM parts relative to CM since the fabrication time can be computed exactly, and often no post-processing is required for the part to be functional. We find that AM techniques are well suited for plasma diagnostics since typical diagnostic complexity comes at no additional cost. Cooling channels, for example, can be builtin to plasma-facing components at no extra cost. Fabrication costs associated with assembly are lower for AM parts because many components can be combined and printed as monoliths, thereby mitigating the need for alignment or calibration. Finally, the cost of engineering is impacted by exploiting AM design tools that allow standard components to be customized through web-interfaces. Furthermore, we find that concept design costs can be impacted by scripting interfaces for online engineering design tools.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Energy Cost Savings of Systems-Based Building Retrofits: A Study of Three Integrated Lighting Systems in Comparison with Component Based Retrofits

Most building retrofit projects are still component-based in that they typically address only one piece or type of equipment at a time. Systems-based retrofits that seek to address multiple components in an integrated manner have the potential to provide significantly greater energy savings. Lawrence Berkeley National Laboratory (LBNL) partnered with several utilities to develop and evaluate three different integrated retrofit packages involving lighting systems: automated shading with daylight dimming controls, workstation-specific lighting with daylight controls, and task/ambient lighting with plug load occupancy controls. Specifically, our analysis sought to quantify the marginal benefits of these systems (energy savings as well as lighting performance and visual comfort) relative to component based approaches. The analysis was based on a combination of measured performance data from LBNL’s FLEXLAB® test facility and energy simulations. All three systems were compared to a simple fluorescent-to-LED retrofit, which represents the component-based approach. While the simple LED upgrade provides significant lighting energy savings of 63%, the systems yielded energy savings of 81-93%, which equates to additional savings of 49-82% over the simple LED upgrade. All systems tested provided satisfactory visual comfort as well, indicating good potential for market acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Design Guidance for High Temperature Concentrating Solar Power Components

This report provides guidance for the design of components for concentrating power facilities operating at high temperatures and undergoing high, secondary thermal stresses relative to the applied primary pressure stress. The design rules were developed for the design of Generation 3 CSP tubular receivers manufactured from Alloy 740H, but are generally applicable to a wide range of component types undergoing similar loads. Part 1 of the report provides procedural design rules for components to be used in conjunction with the 2019 edition of the ASME Boiler & Pressure Vessel Code. Part 2 provides corresponding design data for Alloy 740H. Part 3 of the report is a commentary describing the rationale behind the design rules and the data underlying the design material properties. Finally, Part 4 provides an extensive set of worked sample problems detailing the application of the rules to CSP components.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Multiscale-Informed Modeling of High Temperature Component Response with Uncertainty Quantification

This report summarizes a joint effort between Argonne National Laboratory, Idaho National Laboratory, and Los Alamos National Laboratory to develop and deploy constitutive models targeted at predicting the life of Grade 91 alloy components subjected to high temperature environments typical of those that structural components in advanced nuclear reactors would experience. Two distinct, but complementary constitutive modeling approaches have been taken here. The first employs a phenomenological viscoplastic model for which parameters have been calibrated based on experimental data for a wide range of Grade 91 alloy that has undergone a variety of processing. A Bayesian approach was used to derive distributions of uncertain parameters for this model based on this data set. The second approach is a reduced order model suitable for engineering-scale analysis that is based on the results of a large set of mesoscale simulations. Mesoscale models allow for the microstructure and composition of a particular alloy to be directly taken into account in the computation of the viscoplastic response, but are computationally expensive, which makes it impractical to directly call those models for the material constitutive response in an engineering-scale simulation. The reduced-order representation of the response of the underlying model used here allows for an engineering-scale model to take into account the characteristics of the underlying microstructure, while only incurring a reasonable computational expense. Both of these approaches have different strengths, and are applicable for different parts of the design/analysis process. The phenomenological models can be readily parameterized based on a set of experimental data for a given class of materials and used for scoping calculations. Once a specific material is chosen and adequately characterized, the reduced order models can accurately predict the response of that specific alloy, and because the models are based on predictive models of the underlying microstructure, they can be used to more confidently predict the response under conditions in regions where there is limited experimental data. Both of these models have been integrated in the Grizzly code, which is used here to perform proof-of-concept uncertainty quantification analyses of a simple component under prototypical conditions. The built- in stochastic analysis capabilities in the MOOSE framework that Grizzly is built on are used here to run large sets of simulations for this uncertainty quantification analysis. As would be expected, because the reduced order models are developed for a much more tightly defined alloy, they predict tighter distributions of the time to failure than the phenomenological models, which are calibrated to a broader set of data. Also important is that these simulations demonstrate that a reduced order modeling approach can be successfully deployed to propagate uncertainties from the material scale to practical engineering-scale component simulations.

42 ENGINEERING↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Comparative Study of Direct and Indirect Additive Manufacturing Approaches for the Production of a Wind Energy Component

Additive manufacturing (AM) was developed in the 1980s to create three-dimensional prototypes through layer-wise approaches to fabrication. Since then, these approaches have seen improvements in both materials and processing technologies. To date, there are now 7 types of additive manufacturing processes and hundreds of materials, which can be directly printed – going directly from digital design to fabricated components. In this project, Oak Ridge National Laboratory (ORNL), Vestas Wind Systems, and The National Renewable Energy Laboratory (NREL) collaborated to evaluate the effectiveness of state-of-the-art large-scale AM processes in the production of a structural component for use in a wind turbine nacelle, through both direct and indirect manufacturing approaches. Here, experienced AM design engineers detail techniques for AM design, including topology optimization (TO), support minimization, reverse engineering, and techniques for mitigating poor interlaminar performance. Fabrication of the components is presented, including printing parameters and postprocessing, and followed with full-scale component testing by a 3rd party testing laboratory. To evaluate the potential of the developed approaches, a complete techno-economic analysis is provided which evaluates the cost of these techniques given current and near to long-term projections of AM system capabilities.

17 WIND ENERGY↗
DOE OSTI2021

Advanced Ultra-Supercritical Component Test (ComTest) Project for 760*C Steam Conditions

ComTest is a $27M Department of Energy-funded project. Phase I, which began in November 2015, served to identify the technology gaps, as well as the scope and cost of required testing. Phase II, which was awarded in December 2018, includes an advanced manufacturing effort to complete U.S. based supply chain development for full commercial scale (800-850 MWe) AUSC components made of nickel-based alloys, components operating at up to 760°C. Completion of Phase II scheduled for September 30, 2021. Strategic Objectives of U.S. AUSC Project include: Power Plant Efficiency Improvements –Develop cost-effective, reliable technologies to improve the efficiency of new and existing high-temperature advanced generation power plants. Close gaps to achieve readiness for commercial scale demonstration of Advanced Ultra-Supercritical (AUSC) technology. Fabricate full-scale versions of key nickel-based alloy components. Validate capabilities of US supply chain for cost certainty. Support cross-cutting high-temperature generation technologies. Obtain ASME Code approval for new materials, components and processes. Increase power plant steam temperatures for higher cycle efficiency (Note: Average efficiency of US coal-fired fleet = 33% HHV; A-USC plant efficiency over 47% HHV at 1,400°F (760°C) steam temperature).

fireside corrosion↗