Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “multiple cycles”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Flexible Oxy-Fuel Combustion for High-Penetration Variable Renewables

A thermodynamic model was developed for the oxy-combustion Allam-Fetvedt cycle. This information was then used to develop an optimized dispatch strategy using price strips supplied by the modeling teams. The price strips represent future possible grid configurations that include a high penetration of variable renewables and a carbon tax. Multiple optimization strategies and tools were used to maximize the net present value (NPV) of the plant on these potential future grids. The optimization varied the size of the air separation unit, the size of oxygen storage tanks, the size of carbon dioxide storage tanks and the flow rate of the carbon dioxide pipeline. The team was able to determine a dispatch strategy that resulted in a positive NPV for all price strips. This indicates that an oxy-combustion plant with oxygen storage would be economically viable on a future grid with a high degree of variable renewables.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Approach to Startup Inventory for Viable Commercial Power Plant

Summary • FPP realization within the next 10-15 years will require dedicated efforts to improve DIR, burn fraction, fueling efficiency, and/or processing times. • Modest improvements from either the fuel cycle side or plasma physics side should be possible with considered allocation of R&D funding. • Current gaps in particular include blanket extraction at scale, improved efficiency in isotope separation and detritiation, and maximizing DIR efficiency. • Total costs for FPP construction and commissioning depend heavily on site regulation, so decreases in required SI and OI can lead to large decreases in capital outlay. • Some subsystems in the fuel cycle are required from a environmental management perspective but are both energetically expensive and time consuming, particularly water detritiation. • Low inventories but high capital and operational costs mean a centralized water detritiation plant could greatly improve likelihood of deployment of multiple FPPs on the same time scale.

MALONE, COLLIN↗
DOE OSTI2020

Flexible, Multipurpose Laboratory Advances Building and Thermal Energy Systems: Expanding Evaluation and Development of Grid-Interactive Buildings

Robust hardware and controls are necessary to ensure results match their intent before they can be used broadly. However, this often requires multiple field experiments in a variety of climate zones. In the field, it is more difficult to obtain information on other important factors, such as thermal, grid, and occupant interaction. Gaps also exist in understanding the performance degradation and life cycle of thermal energy systems as they relate to buildings. There is a lack of robust, high-quality performance data for projects at scale; this data can be expensive to produce and often remain proprietary.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Highly dispersed Co deposited on Al 2 O 3 particles via CoCp 2 + H 2 ALD

Highly dispersed cobalt atoms were deposited on porous alumina particles using atomic layer deposition (ALD) with a CoCp 2 /H 2 chemistry at approximately 7 wt%. H 2 did not completely reduce the cyclopentadienyl organic ligands bound to deposited Co atoms at ALD reaction conditions. A sharp decline in Co deposited per cycle for two or more ALD cycles indicates that much of the Al 2 O 3 surface is sterically blocked from further CoCp 2 deposition after the first CoCp 2 exposure. Temperature programmed reduction confirmed that the adsorbed precursor organic ligands persist after H 2 exposures during ALD and temperatures as high as 500 °C are required to fully reduce the organic ligands to CH 4 . High resolution, element sensitive imaging showed that Co atoms were dispersed on the Al 2 O 3 surface and could deposit in previously unobserved multiple growth morphologies, specifically layers that were continuous over several angstroms or discrete nanoparticles. Density functional theory calculations were used to examine Co atom adsorption, show the altered haptic binding of cracked Cp ligands, and to calculate the thermodynamics of Cp ligand decomposition. The lateral steric hindrance between organic ligands bound to deposited Co atoms, Cp ligand decomposition mechanism, and local Al 2 O 3 surface termination all likely determine the observed Co growth morphology during initial ALD cycles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Advanced Reactors Development in USA

Small and micro-reactor advanced reactor development in the USA. Advanced Reactor programs, nuclear renaissance, and INL as a test bed facility. These slides are for presentations in general on the past, INL and nuclear engineering worldwide, GEN IV reactor designs, SMRs and micro Rx designs, multiple commercial designs, and what INL as a test bed means and who uses this to their advantage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗
DOE OSTI2021

Dual-Solvent Li-Ion Solvation Enables High-Performance Li-Metal Batteries

Novel electrolyte designs to further enhance the lithium (Li) metal battery cyclability are highly desirable. Here, fluorinated 1,6-dimethoxyhexane (FDMH) is designed and synthesized as the solvent molecule to promote electrolyte stability with its prolonged –CF 2 – backbone. Meanwhile, 1,2-dimethoxyethane is used as a co-solvent to enable higher ionic conductivity and much reduced interfacial resistance. Combining the dual-solvent system with 1 m lithium bis(fluorosulfonyl)imide (LiFSI), high Li-metal Coulombic efficiency (99.5%) and oxidative stability (6 V) are achieved. Using this electrolyte, 20 µm Li||NMC batteries are able to retain ≈80% capacity after 250 cycles and Cu||NMC anode-free pouch cells last 120 cycles with 75% capacity retention under ≈2.1 µL mAh -1 lean electrolyte conditions. Such high performances are attributed to the anion-derived solid-electrolyte interphase, originating from the coordination of Li-ions to the highly stable FDMH and multiple anions in their solvation environments. This work demonstrates a new electrolyte design strategy that enables high-performance Li-metal batteries with multisolvent Li-ion solvation with rationally optimized molecular structure and ratio.

25 ENERGY STORAGE↗
DOE OSTI2023

Microstructure and defect engineering of graphite anodes by pulsed laser annealing for enhanced performance of lithium-ion batteries

We report nanosecond pulsed laser annealing significantly improves cyclability and current carrying capacity of lithium-ion batteries (LIBs). This improvement is achieved by engineering of microstructure and defect contents present in graphite in a controlled way by using pulsed laser annealing (PLA) to increase the number density of Li + ion trapping sites. The PLA treatment causes the following changes: (1) creates surface steps and grooves between the grains to improve Li + ion charging and intercalation rates; (2) removes inactive polyvinylidene difluoride (PVDF) binder from the top of graphite grains and between the grains which otherwise tends to block the Li + migration; and (3) produces carbon vacancies in (0001) planes which can provide Li + charging sites. From X-ray diffraction data, we find upshift in diffraction peak or reduction in planar spacing, from which vacancy concentration was estimated to be about 1.0%, which is higher than the thermodynamic equilibrium concentration of vacancies. The laser treatment creates single and multiple C vacancies which provide sites for Li + ions, and it also produces steps and grooves for Li + ions to enter the intercalating sites. It is envisaged that the formation of these sites enhances Li+ ion absorption during charge and discharge cycles. The current capacity increases from an average 360 mAh/g to 430 mAh/g, and C–V shows significant reduction in SEI layer formation after the laser treatment. If the vacancy concentration is too high and charge-discharge cycles are long, then trapping of electrons by Li + may occur, which can lead to Li 0 formation and Li plating causing reduction in current capacity.

25 ENERGY STORAGE↗
DOE OSTI2025

Ensemble cure kinetics network (ECK-Net): A method to derive cure kinetics of thermosetting resin

This paper introduces an Ensemble Cure Kinetics Network (ECK-Net), a neural network (NN)–based framework for modeling the cure kinetics of thermosetting resins within a phenomenological context. ECK-Net replaces traditional analytic models, which require extensive chemical insight and multiple isothermal/non-isothermal experiments, with a data-driven surrogate that maps nonlinear relationships between temperature, degree of cure, and reaction rate from differential scanning calorimetry data. The proposed approach predicts input-dependent kinetic coefficients of a generalized nth-order reaction equation rather than reaction rates directly, enabling a single unified model to represent various epoxy systems without relying on iso-conversional analysis or predefined functional forms. To ensure robustness, multiple independently trained networks under different random initializations are blended through an ensemble strategy, effectively mitigating the stochastic variability inherent to neural networks. The framework is validated using experimental datasets from multiple resin systems, including aerospace-grade materials (Toray 3900-2, Cycom 5320-1, and Hexcel 8552) and a windmill-grade resin (RIMR 035c). The model accurately reproduces the temporal evolution of the degree of cure under manufacturers’ recommended cure cycles across all tested resins systems, yielding Pearson’s correlation coefficients of 0.992, 0.994, 0.993, 0.997, respectively. To demonstrate process-level applicability, the trained network was implemented within the Abaqus environment to simulate out-of-autoclave (OOA) curing process of the CFRP panel composed of Toray T830H-6K/3900-2D prepreg. The simulation results showed excellent agreement with experimental temperature response (maximum peak temperature, simulation: 189.6 °C, experiment: 188.5 °C) and the final degree of cure (simulation: 0.948, experiment: 0.960 ± 0.013), confirming ECK-Net’s capability as a reliable alternative to conventional cure kinetics modeling methods.

Composite curing↗
DOE OSTI2026

Climate-eutrophication-anoxia interactions in Late Glacial Soppensee, Switzerland: Forcings, non-linear responses and recovery

Combined effects of climate warming and anthropogenic nutrient loadings lead to lake eutrophication and anoxia globally. Because of chemical feedbacks, lakes under multiple stressors often respond in non-linear ways. However, it remains unclear whether climate change alone can lead to non-linear lake responses in the absence of anthropogenic nutrient disturbances. Here, we investigate the interactions between climate variability, nutrient cycling and trophic state changes, mixing regimes, anoxia and related chemical feedback in a small kettle-hole lake in Switzerland during Late Glacial times (15.2–12.6 cal ka BP), a period known for high-amplitude climate change in pre-anthropogenic times. After its formation during Heinrich Stadial 1 (>15 cal ka BP), Soppensee was oligotrophic and well-mixed. Soppensee became eutrophic and developed anoxia at 14.25 cal ka BP. Phosphorus (P) was released from sediments through the reductive dissolution of Fe-oxyhydroxides, fuelling eutrophication. Eutrophication lagged the Bølling warming (14.65 cal ka BP) by 400 years, suggesting that rising temperatures were not the trigger for eutrophication. Instead, eutrophication responded non-linearly to forest closure (threshold at 76 % arboreal pollen AP), which shielded Soppensee from wind mixing, enhancing lake stratification, anoxia and P release, intensifying eutrophication. These conditions ended during the 200-years cold period of the Aegelsee Oscillation (GI-1d, ca. 14.0 cal ka BP) when the landscape regionally opened (AP<76 %); the lake became well-mixed, oxygenated and P was efficiently sequestered. Throughout the Allerød (13.9–12.8 cal ka BP), enhanced Fe input prompted diagenetic vivianite formation, sequestering P in sediments, naturally remediating lake eutrophication despite closed forests, warm temperatures, lake stratification and anoxia.

Environmental sciences↗
DOE OSTI2020

Neutral gas analysis for JET DT operation

Neutral gas analysis, the measurement and evaluation of total and partial pressures, is a key technique to study the impact of neutral gas dynamics on retention, recycling and release processes of fuel or impurity species in fusion devices. At JET, the experiment closest to ITER in terms of operating parameters and size, various detectors and techniques for partial pressure and total pressure measurements are deployed together to characterise neutral gas dynamics during and after plasma operation on various toroidal and poloidal locations. An extensive modification of JET's sub-divertor neutral gas diagnostic system aims at retaining and extending established measurement capabilities in the forthcoming Deuterium-Tritium (DT) experiments (DTE2). To achieve DT compatibility, a separation of radiation-sensitive electronics from the sensor and adequate radiation shielding is required, as well as utilisation of a DT compatible differential pumping system with adjustable throughput to account for the strong pressure variation in the sub-divertor region. Finally, the sub-divertor neutral gas diagnostic will be equipped with multiple Residual Gas Analysers (RGAs), utilising quadrupole mass spectrometry and electrostatic ion-trap-principles, all operating with remote electronics located behind the biological radiation shield. These RGAs will record data in a fast selected discrete mass mode during plasma pulses (cycle ~2 s) and will automatically switch back to continuous data recording (cycle ~100 s) afterwards. They will be complemented by a newly improved Penning gauge spectroscopy configuration in particular supporting the He and D 2 separation relevant for DT operation. The distance between these devices and their associated control unit is typically 15m . A newly developed RGA with a cable length of 80 m, compatible with the ITER environment, will also be employed for the first time. Finally, this set-up and its operation in DTE2 will provide vital input to the development of the ITER divertor RGA in the most relevant environment currently available.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Genomes to ecosystem function: Targeting critical knowledge gaps in methanogenesis and translation to updated global biogeochemical models

Natural freshwater temperate wetland systems currently represent the largest natural source of atmospheric methane, but are relatively understudied using systems biology tools (e.g. meta-omics) compared to other high producing methane systems (e.g. peat, tropical, or reconstructed wetlands). Using field investigations at the NOAA operated sentinel site on Lake Erie, methane producing activities and responses to geochemical conditions will be determined along seasonal and spatial gradients (Objective 1). Here, a combination of high-throughput activity and gas measurements, combined with high-resolution systems biology and analytical methods, will provide in depth knowledge of the microbiological, chemical, and physical constraints on methane production in wetlands. Using laboratory microcosms, the formation of anoxic microsites and their capacity to facilitate methane production in wetland soils will be simulated (Objective 2). This objective will validate the findings from the field investigations, offering a more controlled environment for teasing out the role of different yet interrelated variables. Lastly, these field and laboratory data will be used for multi-scale, process-level evaluation of an ecosystem biogeochemical model that accommodates these newly identified processes and parameterizes representation of these processes along relevant environmental gradients (Objective 3).This research will identify multiple interacting geochemical, ecological, and metabolic constraints that are poorly understood, oversimplified, or missing in global biogeochemical methane models. This proposal targets the role of oxygen limitation on methane processes in soil domains, to improve reactive transport models of microbial carbon cycling across terrestrial-aquatic soils and generate data on nutrient cycling activities in Great Lake wetlands. This information could provide new insights into the microbial controllers of Lake Erie eutrophication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Polaris-PARCS Sensitivity Study on LWR Fuel Cycles: Polaris Input Options

This study is the first of a multi-phase effort to assess the sensitivity of light-water reactor (LWR) core-level prediction biases to changes in lattice-level calculation parameters. Prediction bias is the measured-to-predicted difference in a core-level quantity of interest (QOI) which can be estimated by comparing the simulation results with the plant-measured data for key nuclear parameters. The LWR two-step neutronics codes employed herein are the SCALE–Polaris lattice physics code (v6.3.1) and the Purdue Advanced Reactor Core Simulator (PARCS) nodal diffusion simulator (v3.4.2), both funded and used for confirmatory analysis to support licensing by the US Nuclear Regulatory Commission (NRC). Polaris–PARCS is used to model Watts Bar Unit 1 cycles 1–3 and Peach Bottom Unit 2 cycles 1–3. This study focuses on the impact of changes to Polaris input options such as scattering treatment or quadrature settings and how these input options induce changes in core-level quantities of interest (QOIs)bias. The report documents multiple bias assessments for different modeling choices and compares the bias magnitude to the QOI measurement uncertainties. Future companion reports will investigate the sensitivity of core-level LWR prediction bias to Polaris input options and Polaris-computed QOIs such as few-group assembly-homogenized cross sections to gain an understanding of the key drivers of prediction bias at lattice and core levels for application of a two-step LWR neutronics procedure in a licensing scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development and performance of INCONEL® alloy 740H® seam-welded piping

INCONEL® alloy 740H® is an age-hardenable nickel-based alloy approved for pressure vessels and piping within ASME Section I, VIII, and B31.1. Currently, the code applies a weld strength reduction factor (WSRF) of 0.7 to the allowable stresses for longitudinal seam welds in the time dependent creep regime. In this work, a full-scale seam weld was successfully produced using typical industrial practices. The component was solution heat-treated and aged after fabrication to improve the performance of the weldment. Tensile, bend, impact, and low-cycle fatigue tests showed the component met all the specification requirements and elevated temperature properties were within base metal expectations with failures predominately in the weld metal. Long-term creep tests, including large samples more representative of the entire weldment, were fabricated and tested to times in excess of 10,000 h at multiple temperatures. Analysis of the creep data supports a WSRF of 0.9 for the solution annealed + aged weldments in contrast to the WSRF of 0.7 currently applied to welded + aged weldments. Metallurgical analysis shows that the solution annealing causes recrystallization of the weld metal and reduces the chemical compositional and microstructural gradients in the weldments resulting in acceptable short-term performance. In long-term creep, evidence for coarsened zones in the weldments due to discontinuous coarsening reactions were identified as the mechanism leading to accelerated creep damage formation in the weld metal and sample failure.

14 SOLAR ENERGY↗