SEARCH · Search NASA

Results for “Observer Variation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

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

At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Exploiting 20 Ne Isotopes for Precision Characterizations of Collectivity in Small Systems

Whether or not femto-scale droplets of quark-gluon plasma (QGP) are formed in so-called small systems at high-energy colliders is a pressing question in the phenomenology of the strong interaction. For proton-proton or proton-nucleus collisions the answer is inconclusive due to the large theoretical uncertainties plaguing the description of these processes. While upcoming data on collisions of 16 O nuclei may mitigate these uncertainties in the near future, here we demonstrate the unique possibilities offered by complementing 16 O + 16 O data with collisions of 20 Ne ions. We couple both nuclear lattice effective field theory (NLEFT) and projected generator coordinate method (PGCM) ab initio descriptions of the structure of 20 Ne and 16 O to hydrodynamic simulations of 16 O + 16 O and 20 Ne + 20 Ne collisions at high energy. We isolate the imprints of the bowling-pin shape of 20 Ne on the collective flow of hadrons, which can be used to perform quantitative tests of the hydrodynamic QGP paradigm. In particular, we predict that the elliptic flow of 20 Ne + 20 Ne collisions is enhanced by as much as 1.174⁢(8) stat ⁢(31) syst for NLEFT and 1.139⁢(6) stat ⁢(39) syst for PGCM relative to 16 O + 16 O collisions for the 1% most central events. At the same time, theoretical uncertainties largely cancel when studying relative variations of observables between two systems. This demonstrates a method based on experiments with two light-ion species for precision characterizations of the collective dynamics and its emergence in a small system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Ultrathin epitaxial MgB 2 on SiC: Substrate surface-polarity-dependent properties

High-quality, ultrathin superconducting films are required for advanced devices such as hot-electron bolometers, superconducting nanowire single-photon detectors, and quantum applications. Using hybrid physical-chemical vapor deposition, we show that MgB 2 films as thin as 4 nm can be fabricated on the carbon-terminated 6⁢H-SiC (0001) surface with a superconducting transition temperature above 33 K and a rms roughness of 0.7 nm. Remarkably, the film quality is a function of the SiC surface termination, with the C-terminated surface preferred to the Si-terminated surface. To understand the MgB 2 thin film/SiC substrate interactions giving rise to this difference, we characterized the interfacial structures using Rutherford backscattering spectroscopy/channeling, electron-energy-loss spectroscopy, and x-ray photoemission spectroscopy. The MgB 2 /SiC interface structure is complex and different for the two terminations. Both terminations incorporate substantial unintentional oxide layers influencing MgB 2 growth and morphology, but with a different extent, intermixing, and interface chemistry. In this paper, we report measurements of transport, resistivity, and the critical superconducting temperature of MgB 2 /SiC that are different for the two terminations, and they link interfacial structure variations to observed differences. The result shows that the C face of SiC is a preferred substrate for the deposition of ultrathin superconducting MgB 2 films.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Microscopic theory of angular momentum distributions across the full range of fission fragments

Modern nuclear theory provides qualitative insights into the fundamental mechanisms of nuclear fission and is increasingly capable of making reliable quantitative predictions. Most quantities of interest pertain to the primary fission fragments, whose subsequent decay is typically modeled using statistical reaction models. Consequently, a key objective of fission theory is to inform these models by predicting the initial conditions of the primary fragments. Here, in this work, we employ a framework that combines joint angular momentum and particle number projection with time-dependent configuration mixing to calculate the angular momentum distributions of primary fragments. Focusing on the benchmark cases of neutron-induced fission of 235 U and 239 Pu , we predict—for the first time—microscopic angular momentum distributions for all fragments observed in experiments. Our results reveal a pronounced sawtooth pattern in the average angular momentum as a function of fragment mass, consistent with recent measurements. Additionally, we observe substantial variations in angular momentum distributions along isobaric chains, indicating that commonly used empirical formulas lack sufficient accuracy. We also quantify a strong correlation between the angular momentum and the deformation of the fragments at scission, and a weak correlation in the magnitude of the angular momentum between fragment partners. The generated data will enable estimation of the impact of microscopic distributions on fission spectra, paving the way toward fission modeling based on microscopic inputs.

Physics - Nuclear physics and radiation physics↗

DOE OSTI2024

Distributed Automatic Generation Control Considering DPV Using T&D Dynamic Co-Simulation

The increasing adoption of distributed energy resources (DERs) over the last decade warrants a reconsideration of control of generation resources. This paper proposes a distributed Automatic Generation Control (AGC) using transmission-and-distribution (T&D) dynamic co-simulation framework for the efficient DPV frequency regulation services. The co-simulation framework allows AGC units to exchange the information for distributed AGC, based on their adopted communication network topology. As a result, a cost-effective automatic generation control is achieved with DPV and conventional generators. The proposed distributed AGC is based on the gossip algorithm in which the neighboring AGC units share the relevant local information with each other and updates their share of AGC regulation signal. Distributed photovoltaics (DPV) unit contribute to AGC response based on their headroom capacity via DER aggregators. The algorithm is tested on IEEE-14 bus transmission system under conditions of generation failure and random load variation to observe effective frequency regulations service offered by DPVs and other AGC units. The study shows that DPV can effectively participate in AGC with the proposed distributed control framework.

automatic generation control↗

DOE OSTI2022

Optimal Control of Biomass Feedstock Processing System Under Uncertainty in Biomass Quality

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput.

09 BIOMASS FUELS↗

DOE OSTI2018

Asymmetrical subcortical plasticity entails cognitive progression in older individuals

Abstract Structural brain asymmetries have been associated with cognition. However, it is not known to what extent neuropsychological parameters and structural laterality covary with aging. Seventy‐five subjects drawn from a larger normal aging cohort were evaluated in terms of MRI and neuropsychological parameters at two moments (M1 and M2), 18 months apart. In this time frame, asymmetry as measured by structural laterality index (ΔLI) was stable regarding both direction and magnitude in all areas. However, a significantly higher dispersion for this variation was observed in subcortical over cortical areas. Subjects with extreme increase in rightward lateralization of the caudate revealed increased M1 to M2 Stroop interference scores, but also a worsening of general cognition (MMSE). In contrast, subjects showing extreme increase in leftward lateralization of the thalamus presented higher increase in Stroop interference scores. In conclusion, while a decline in cognitive function was observed in the entire sample, regional brain asymmetries were relatively stable. Neuropsychological trajectories were associated with laterality changes in subcortical regions.

Esteves, Madalena↗

DOE OSTI2019

Winter hardiness of Miscanthus (I): Overwintering ability and yield of new Miscanthus × giganteus genotypes in Illinois and Arkansas

Abstract Miscanthus ×giganteus (M×g) is an important bioenergy feedstock crop. However, biomass production of Miscanthus has been largely limited to one sterile triploid cultivar, M×g ‘1993‐1780’, which we demonstrate can have insufficient overwintering ability in temperate regions with cold winters. Key objectives for Miscanthus breeding include greater biomass yield and better adaptation to different production environments than M×g ‘1993‐1780’. In this study, we evaluated 13 M×g genotypes, including ‘1993‐1780’, in replicated field trials conducted for three years at Urbana, IL; Dixon Springs, IL; and Jonesboro, AR. Entries were phenotyped for first‐winter overwintering ability and plant hardiness (ratio of new tillers to old), yield in years 2 and 3, and first heading date, plant height, and culm number in years 1 and 2. We observed substantial variation for overwintering ability and biomass yield among the M×g genotypes tested and identified ones with better overwintering ability and/or higher biomass yield than ‘1993‐1780’. Most entries at Urbana were damaged during the first winter, whereas few or no entries were damaged at Dixon Springs or Jonesboro. However, M×g ‘Nagara’ was entirely undamaged during the first winter and produced high biomass yields at Urbana (19.7 Mg/ha in year 2 and 20.9 Mg/ha in year 3), whereas M×g ‘1993‐1780’ exhibited an overwintering loss of 29%, had severely damaged survivors (hardiness score of 25%), and reduced biomass yield (8.1 Mg/ha in year 2 and 16.2 Mg/ha in year 3), indicating that M×g ‘Nagara’ could be a better choice in hardiness zone 5 (average annual minimum air temperature of −23.3 to −28.9°C) or lower. In Dixon Springs, where M×g ‘1993‐1780’ was undamaged by the first winter, it yielded highest among all the entries (21.6 Mg/ha in year 3), though not significantly higher than M×g ‘Nagara’ (18.2 Mg/ha in year 3).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Reduced global plant respiration due to the acclimation of leaf dark respiration coupled with photosynthesis

Summary Leaf dark respiration ( R d ) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that R d and Rubisco carboxylation capacity ( V cmax ) at 25°C ( R d,25 , V cmax,25 ) are coordinated so that R d,25 variations support V cmax,25 at a level allowing full light use, with V cmax,25 reflecting daytime conditions (for photosynthesis), and R d,25 / V cmax,25 reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives: R d,25 declines linearly with daily average prior temperature; R d at average prior night temperatures tends towards a constant value; and R d,25 / V cmax,25 is constant. Our hypothesis accounted for more variation in observed R d,25 over time ( R 2 = 0.74) and space ( R 2 = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course of R d , with an apparent response time scale of c. 2 wk. V cmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global R d in response to rising CO 2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Plant Sciences↗

DOE OSTI2024

Mycorrhizal fungi modify decomposition: a meta‐analysis

Summary It has been proposed that ectomycorrhizal fungi can reduce decomposition while arbuscular mycorrhizal fungi may enhance it. These phenomena are known as the ‘Gadgil effect’ and ‘priming effect’, respectively. However, it is unclear which one predominates globally. We evaluated whether mycorrhizal fungi decrease or increase decomposition, and identified conditions that mediate this effect. We obtained decomposition data from 43 studies (97 trials) conducted in field or laboratory settings that controlled the access of mycorrhizal fungi to substrates colonized by saprotrophs. Across studies, mycorrhizal fungi promoted decomposition of different substrates by 6.7% overall by favoring the priming effect over the Gadgil effect. However, we observed significant variation among studies. The substrate C : N ratio and absolute latitude influenced the effect of mycorrhizal fungi on decomposition and contributed to the variation. Specifically, mycorrhizal fungi increased decomposition at low substrate C : N and absolute latitude, but there was no discernable effect at high values. Unexpectedly, the effect of mycorrhizal fungi was not influenced by the mycorrhizal type. Our findings challenge previous assumptions about the universality of the Gadgil effect but highlight the potential of mycorrhizal fungi to negatively influence soil carbon storage by promoting the priming effect.

Plant Sciences↗

DOE OSTI2020

Quantum phase crossover in the spherical mean-field plus quadrupole–quadrupole and pairing model with two j-orbits

The shape phase crossover in the mean-field plus the geometric quadrupole–quadrupole and pairing model within two [Formula: see text]-orbits is analyzed, for which a simple description of [Formula: see text]Sn confined in the lowest [Formula: see text] and [Formula: see text] orbits above the [Formula: see text]Sn core is demonstrated to reveal the crossover behavior of the model. It is shown that [Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text] in this case may serve as effective order parameters for even–even and odd-A systems, respectively, from which the shape phase crossover from the rotation-like phase to the superconducting-like phase can be observed with variation of the number of valence neutrons.

Physics↗

DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗

DOE OSTI2019

Genome-wide association analysis of stalk biomass and anatomical traits in maize

Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area). Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes ( Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22 . Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Finally, results of this study provide insights into the genetic control of maize stalk anatomy and biomass.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Zymomonas diversity and potential for biofuel production

Abstract Background Zymomonas mobilis is an aerotolerant α-proteobacterium, which has been genetically engineered for industrial purposes for decades. However, a comprehensive comparison of existing strains on the genomic level in conjunction with phenotype analysis has yet to be carried out. We here performed whole-genome comparison of 17 strains including nine that were sequenced in this study. We then compared 15 available Zymomonas strains for their natural abilities to perform under conditions relevant to biofuel synthesis. We tested their growth in anaerobic rich media, as well as growth, ethanol production and xylose utilization in lignocellulosic hydrolysate. We additionally compared their tolerance to isobutanol, flocculation characteristics, and ability to uptake foreign DNA by electroporation and conjugation. Results Using clustering based on 99% average nucleotide identity (ANI), we classified 12 strains into four clusters based on sequence similarity, while five strains did not cluster with any other strain. Strains belonging to the same 99% ANI cluster showed similar performance while significant variation was observed between the clusters. Overall, conjugation and electroporation efficiencies were poor across all strains, which was consistent with our finding of coding potential for several DNA defense mechanisms, such as CRISPR and restriction–modification systems, across all genomes. We found that strain ATCC31821 (ZM4) had a more diverse plasmid profile than other strains, possibly leading to the unique phenotypes observed for this strain. ZM4 also showed the highest growth of any strain in both laboratory media and lignocellulosic hydrolysate and was among the top 3 strains for isobutanol tolerance and electroporation and conjugation efficiency. Conclusions Our findings suggest that strain ZM4 has a unique combination of genetic and phenotypic traits that are beneficial for biofuel production and propose investing future efforts in further engineering of ZM4 for industrial purposes rather than exploring new Zymomonas isolates.

09 BIOMASS FUELS↗

DOE OSTI2018

Structure of the 30S ribosomal decoding complex at ambient temperature

The ribosome translates nucleotide sequences of messenger RNA to proteins through selection of cognate transfer RNA according to the genetic code. To date, structural studies of ribosomal decoding complexes yielding high-resolution data have predominantly relied on experiments performed at cryogenic temperatures. New light sources like the X-ray free electron laser (XFEL) have enabled data collection from macromolecular crystals at ambient temperature. Here, we report an X-ray crystal structure of the Thermus thermophilus 30S ribosomal subunit decoding complex to 3.45 Å resolution using data obtained at ambient temperature at the Linac Coherent Light Source (LCLS). We find that this ambient-temperature structure is largely consistent with existing cryogenic-temperature crystal structures, with key residues of the decoding complex exhibiting similar conformations, including adenosine residues 1492 and 1493. Minor variations were observed, namely an alternate conformation of cytosine 1397 near the mRNA channel and the A-site. Our serial crystallography experiment illustrates the amenability of ribosomal microcrystals to routine structural studies at ambient temperature, thus overcoming a long-standing experimental limitation to structural studies of RNA and RNA–protein complexes at near-physiological temperatures.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Genomic Dissection of Anthracnose ( Colletotrichum sublineolum ) Resistance Response in Sorghum Differential Line SC112-14

Sorghum production is expanding to warmer and more humid regions where its production is being limited by multiple fungal pathogens. Anthracnose, caused by Colletotrichum sublineolum , is one of the major diseases in these regions, where it can cause yield losses of both grain and biomass. In this study, 114 recombinant inbred lines (RILs) derived from resistant sorghum line SC112-14 were evaluated at four distinct geographic locations in the United States for response to anthracnose. A genome scan using a high-density linkage map of 3,838 single nucleotide polymorphisms (SNPs) detected two loci at 5.25 and 1.18 Mb on chromosomes 5 and 6, respectively, that explain up to 59% and 44% of the observed phenotypic variation. A bin-mapping approach using a subset of 31 highly informative RILs was employed to determine the disease response to inoculation with ten anthracnose pathotypes in the greenhouse. A genome scan showed that the 5.25 Mb region on chromosome 5 is associated with a resistance response to nine pathotypes. Five SNP markers were developed and used to fine map the locus on chromosome 5 by evaluating 1,500 segregating F 2:3 progenies. Based on the genotypic and phenotypic analyses of 11 recombinants, the locus was narrowed down to a 470-kb genomic region. Following a genome-wide association study based on 574 accessions previously phenotyped and genotyped, the resistance locus was delimited to a 34-kb genomic interval with five candidate genes. All five candidate genes encode proteins associated with plant immune systems, suggesting they may act in synergy in the resistance response.

Genetics & Heredity↗

DOE OSTI2018

Dispersion Validation for Flow Involving a Large Structure

The atmospheric dispersion of contaminants in the wake of a large urban structure is a challenging fluid mechanics problem of interest to the scientific and engineering communities. Magnetic Resonance Velocimetry (MRV) is a relatively new technique that leverages diagnostic equipment used primarily by the medical field to make 3D engineering measurements of flow and contaminant dispersal. SIERRA/Fuego, a computational fluid dynamics (CFD) code at Sandia National Labs is employed to make detailed comparisons to the dataset to evaluate the quantitative and qualitative accuracy of the model. The comparison exercise shows good comparison between model and experimental results, with the wake region downstream of the tall building presenting the most significant challenge to the quantitative accuracy of the model. Model uncertainties are assessed through parametric variations. Some observations are made in relation to the future utility of MDV and CFD, and some productive follow-on activities are suggested that can help mature the science of flow modeling and experimental testing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Shortening the Design and Certification Cycle for Additively Manufactured Materials by Improved Mesoscale Simulations and Validation Experiments: Fiscal Year 2019 Status Report.

This report outlines the fiscal year (FY) 2019 status of an ongoing multi-year effort to develop a general, microstructurally-aware, continuum-level model for representing the dynamic response of material with complex microstructures. This work has focused on accurately representing the response of both conventionally wrought processed and additively manufactured (AM) 304L stainless steel (SS) as a test case. Additive manufacturing, or 3D printing, is an emerging technology capable of enabling shortened design and certification cycles for stockpile components through rapid prototyping. However, there is not an understanding of how the complex and unique microstructures of AM materials affect their mechanical response at high strain rates. To achieve our project goal, an upscaling technique was developed to bridge the gap between the microstructural and continuum scales to represent AM microstructures on a Finite Element (FE) mesh. This process involves the simulations of the additive process using the Sandia developed kinetic Monte Carlo (KMC) code SPPARKS. These SPPARKS microstructures are characterized using clustering algorithms from machine learning and used to populate the quadrature points of a FE mesh. Additionally, a spall kinetic model (SKM) was developed to more accurately represent the dynamic failure of AM materials. Validation experiments were performed using both pulsed power machines and projectile launchers. These experiments have provided equation of state (EOS) and flow strength measurements of both wrought and AM 304L SS to above Mbar pressures. In some experiments, multi-point interferometry was used to quantify the variation is observed material response of the AM 304L SS. Analysis of these experiments is ongoing, but preliminary comparisons of our upscaling technique and SKM to experimental data were performed as a validation exercise. Moving forward, this project will advance and further validate our computational framework, using advanced theory and additional high-fidelity experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Identify the influence of microstructure on mesoscale creep and fatigue damage

This report describes the development of a microstructural model that can quantify the uncertainty in the observed rupture life of Grade 91 steel. The model is microstructural, meaning it relates microstructural characteristics of the material to the resulting material response. As such, one of the uses of this model is to identify the key microstructural parameters controlling the development of damage in Grade 91 operating at elevated temperatures. The report describes two veins of work: improvements to the crystal plasticity model required to run the uncertainty quantification analysis and the results of that UQ analysis. For creep, the model identifies the grain boundary diffusivity as the critical parameter controlling the rupture life of the material. The report demonstrates that a reasonable microstructural distribution of grain boundary diffusivity can account for the observed macroscale variation in rupture life at fixed temperature and load.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗