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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.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mechanical Consequences of Oxygen Inhibition in Vat Polymerization

Vat polymerization is a type of additive manufacturing that is used extensively to produce micro-architected structures for mechanical applications, which brings the mechanical properties of photopolymerized resins into sharp focus. However, it is known that photopolymerization is sensitive to a number of factors, perhaps the most notorious of which is oxygen inhibition. Herein, the degree to which oxygen inhibition influences the macroscopic and microscopic properties of structures made using vat polymerization is explored. This work is motivated by an observation of lattices being >4 times softer in the experiment than predicted by simulation, which is hypothesized to be due to the material at the surface being incompletely cured. Furthermore, this hypothesis is supported by four-point bending tests in which flexural modulus is found to increase with beam thickness. Nanoindentation and bulk compression studies show that this surface softening is present for three distinct resins. Importantly, it is observed that structures post-print cured in nitrogen are stiffer than those post-print cured in air, however, regardless of the post-print curing environment, printing samples in the presence of oxygen makes them softer than samples photocured in nitrogen. Collectively, these results show the outsized influence of oxygen inhibition on micro-architected structures realized using vat polymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Electrochemical Corrosion Behavior of 5083 Aluminum Alloy Subjected to Laser Shock Peening

This paper investigates the effect of ablative coating used during laser shock peening (LSP) on corrosion behavior of 5083 aluminum alloy in artificial seawater. Micro-hardness, residual stress, and surface morphology of the specimens were measured. The corrosion behavior was investigated by electrochemical test. Surface corrosion morphologies after electrochemical tests were examined by SEM and EDS. The results show that surface roughness and surface compressive residual stress of the specimen treated by LSP without ablative coating (LSPwC) are lower than that of the specimen treated by LSP with ablative coating under the same laser energy. The open-circuit potentials and self-corrosion potentials of the specimens treated by LSP and LSPwC both shift positively, and the diameters of the capacitor arcs were larger after LSP and LSPwC. The corrosion resistance of 5083 aluminum alloy is improved by LSP and LSPwC. Moreover, superior corrosion resistance is achieved without using the ablative coating during LSP.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Very High-Cycle Fatigue Properties and Residual Stress Relaxation of Micro-shot-Peened EA4T Axle Steel

In this paper, EA4T alloy railway axle steel was shot peened with steel balls and ceramic balls with a diameter of 50 μm, and 10{sup 9}-cycle fatigue tests of unpeened and peened specimens were carried out. The fatigue properties and the surface compression residual stress relaxation processes were investigated. The results of surface fracture observation indicated that all the cracks initiated from the surface, and both peened and unpeened specimens have conventional fatigue limits in the very high-cycle fatigue regime. Moreover, compared with unpeened (UP) specimens, the fatigue limits were improved by 31 and 28% for ceramic shot-peened (CSP) and steel shot-peened (SSP) specimens, respectively. The improvement of fatigue limit is related to the surface compressive residual stresses (SCRS) and the surface-hardened layer. The SCRS and full-width half-maximum (FWHM) values during the relaxation processes have been analyzed. At stress amplitudes lower than the cyclic yield strength, the residual stress of SSP specimens relaxed quickly in the first loading cycle and then remained stable, while the residual stress of CSP specimens relaxed quickly in the first loading cycle and relaxed slowly afterward, then remained stable. For all SSP and CSP specimens with applied stress amplitudes larger than the cyclic yield strength, the residual stress relaxed quickly in the initial cycles, and then remained stable after the first loading cycle.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Assessment of four strain energy decomposition methods for phase field fracture models using quasi-static and dynamic benchmark cases

Abstract Strain energy decomposition methods in phase field fracture models separate strain energy that contributes to fracture from that which does not. However, various decomposition methods have been proposed in the literature, and it can be difficult to determine an appropriate method for a given problem. The goal of this work is to facilitate the choice of strain decomposition method by assessing the performance of three existing methods (spectral decomposition of the stress or the strain and deviatoric decomposition of the strain) and one new method (deviatoric decomposition of the stress) with several benchmark problems. In each benchmark problem, we compare the performance of the four methods using both qualitative and quantitative metrics. In the first benchmark, we compare the predicted mechanical behavior of cracked material. We then use four quasi-static benchmark cases: a single edge notched tension test, a single edge notched shear test, a three-point bending test, and a L-shaped panel test. Finally, we use two dynamic benchmark cases: a dynamic tensile fracture test and a dynamic shear fracture test. All four methods perform well in tension, the two spectral methods perform better in compression and with mixed mode (though the stress spectral method performs the best), and all the methods show minor issues in at least one of the shear cases. In general, whether the strain or the stress is decomposed does not have a significant impact on the predicted behavior.

Zhang, Shuaifang↗
DOE OSTI2023

Exploitation of Defects in High Entropy Ceramic Barrier Materials

A critical mission need exists to develop new materials that can withstand extreme environments and multiple sequential threats. High entropy materials, those containing 5 or more metals, exhibit many exciting properties which would potentially be useful in such situations. However, a particularly hard challenge in developing new high entropy materials is determining a priori which compositions will form the desired single phase material. The project outlined here combined several modeling and experimental techniques to explore several structure-property-relationships of high entropy ceramics in an effort to better understand the connection between their compositional components, their observed properties, and stability. We have developed novel machine learning algorithms which rapidly predict stable high entropy ceramic compositions, identified the stability interplay between configurational entropy and cation defects, and tested the mechanical stability of high entropy oxides using the unique capabilities at the Dynamic Compression Sector facility and the Saturn accelerator.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A compact x-ray diffraction system for dynamic compression experiments on pulsed-power generators

Pulsed-power generators can produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies using the magnetic loading technique. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength–strain rate dependence, structural phase transitions, and density of crystal defects, such as dislocations. Here, we present a cost-effective, compact, pulsed x-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically driven ramp compression of materials with a single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials’ community to investigate in situ dynamic phase transitions critical to equation of states. Finally, we present results using this new diagnostic to evaluate lattice compression in Zr and Al and to capture signatures of phase transitions in CdS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Real-fluid behavior in rapid compression machines: Does it matter?

Rapid compression machines (RCMs) have been extensively used to quantify fuel autoignition chemistry and validate chemical kinetic models at high-pressure conditions. Historically, the analyses of experimental and modeling RCM autoignition data have been conducted based on the adiabatic core hypothesis with ideal gas assumption, where real-fluid behavior has been completely overlooked, though this might be significant at common RCM test conditions. Here, this work presents a first-of-its-kind study that addresses two significant but overlooked questions for autoignition studies within RCMs in the fundamental combustion community: (i) experiment-wise, can unaccounted-for real-fluid behavior in RCMs affect the interpretation and analysis of RCM experimental data? and (ii) simulation-wise, can unaccounted-for real-fluid behavior in RCMs affect RCM autoignition modeling and the validation of chemical kinetic models? To this end, theories for real-fluid isentropic change are newly proposed and derived based on high-order Virial EoS, and are further incorporated into an effective-volume real-fluid autoignition modeling framework newly developed for RCMs. With detailed analyses, the strong real-fluid behavior in representative RCM tests is confirmed, which can greatly influence the interpretation of RCM autoignition experiments, particularly the determination of end-of-compression temperature and evolution of the adiabatic core in the reaction chamber. Furthermore, real-fluid RCM modeling results reveal that considerable error can be introduced into simulating RCM autoignition experiments when following the community-wide accepted effective-volume approach by assuming ideal-gas behavior, which can be as high as 64% in the simulated ignition delay time at compressed pressure of 125 bar and lead to contradictory validation results of chemical kinetic models. Therefore, we recommend the community to adopt frameworks with real-fluid behavior fully accounted for (e.g., the one developed in this study) to analyze and simulate past and future RCM experiments, so as to avoid misinterpretation of RCM autoignition experiments and eliminate the potential errors that can be introduced into the simulation results with the existing RCM modeling frameworks.

High-order Virial equation of state↗
DOE OSTI2021

A Scalable Process for Upcycling Carbon Dioxide (CO 2 ) and Coal Combustion Residues into Construction Products

Anthropogenic sources of carbon dioxide are generated from a number of sources, but the key among these are ordinary Portland cement (OPC) production and combustion of fossil fuels. Cement production is the largest global CO 2 source from the mineral decomposition of carbonates. Combination of the limestone decomposition and thermal requirements of the clinkering process causes cement production to contribute 8-9% of annual global CO 2 emissions. Combustion of fossil fuels (coal, oil and gas) was shown to contribute a much larger portion of global CO 2 emissions. As of 2018, combustion of fossil fuels accounted for 65% of global CO 2 , where 41% was derived from stationary sources for electricity and heat generation and the other 24% was related to transport. To reduce these contributions, key steps forward in CO 2 utilization technologies are required. The purpose of this project is to demonstrate the feasibility of the Reversa process evolving from a TRL-3 technology at the bench-scale up to TRL-6 technology at the pilot-scale. The reliability of the Reversa technology was tested to prove the effective production of concrete masonry units (CMUs) at bench scale, where the units exceeded the required 13.8 MPa compressive strength requirements. The overall goal of this project was to accelerate the development of a CO 2 mineralization process that synergistically utilizes CO 2 in flue gas and coal combustion residues (CCRs) to synthesize carbonated concrete, a functional replacement for traditional concrete. The culmination of this work resulted in 12 successful production runs at the Integrated Test Center (ITC), Gillette, WY using coal flue gas as a CO 2 source. This was followed by 6 production runs which were completed at the National Carbon Capture Center (NCCC), Wilsonville, AL, using coal-fired and natural gas (NG) flue gas as the CO 2 source. Over the course of the production runs at NCCC and ITC, the CO 2 utilization as a function of time, 24-h CO 2 uptake, electricity usage, and 28-d net area compressive strength recorded for each run. The ITC and NCCC demonstrations achieved an average of 0.19 and 0.1 g CO 2 /g reactant, respectively. Both demonstrations exceeded the project’s target goals of uptake > 0.05 g CO 2 /g reactant. Average compressive strength of the ITC blocks was 18.24 MPa at 28-days. This exceeded the target strength of 13.8 MPa specified by ASTM C90. ITC and NCCC produced an average CO 2 utilization efficiency of 74.9 and 57.9%, respectively. Both demonstration averages were within the target range of 50 to 90% utilization efficiency. For some production runs the NCCC demo did exceeded the a CO 2 utilization efficiency of 75%. An LCA of the Reversa process compared to an industry standard product revealed a net CO 2 reduction of 39% to 42%. This exceeded the target requirement of >25% net CO 2 reduction. Collection of this data was used to determine that the project was successful as the demonstration goals were achieved: (1) achieving in excess of 75% CO 2 utilization efficiency, (2) utilizing greater than 250 kg of CO 2 per production batch/run, and (3) ensuring compliance of carbonated blocks with industry standard specifications (ASTM C90).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

An Algorithm for Atom-Centered Lossy Compression of the Atomic Orbital Basis in Density Functional Theory Calculations

Large atomic-orbital (AO) basis sets of at least triple and preferably quadruple-ζ (QZ) size are required to adequately converge Kohn–Sham density functional theory (DFT) calculations toward the complete basis set limit. However, incrementing the cardinal number by one nearly doubles the AO basis dimension, and the computational cost scales as the cube of the AO dimension, so this is very computationally demanding. Here, in this work, we develop and test a threshold-based natural atomic orbital (NAO) scheme in which ϵ-NAOs are obtained as eigenfunctions of atomic blocks of the density matrix in a one-center orthogonalized representation. This enables compression of the AO basis that is optimal for a given threshold, 10 –ϵ , by discarding NAOs with occupation numbers below that threshold. Extensive pilot test calculations using the Hartree–Fock functional and taking the converged density matrix as input suggest that a threshold of 10 –5 can yield a compression factor (ratio of AO to compressed ϵ-NAO dimension) between 2.5 and 4.5 for the QZ pc-3 basis. The errors in relative energies are typically less than 0.1 kcal/mol when the compressed basis is used instead of the uncompressed basis. Between 10 and 100 times smaller errors (i.e., usually less than 0.01 kcal/mol) can be obtained with a threshold 10 –7 , while the compression factor is typically between 2 and 2.5.

basis sets↗
DOE OSTI2024

CCUS 2024, Interpreting the strain tensor Larry Murdoch Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring during CCUS. We have demonstrated this method by deploying strainmeters at shallow depths (30 to 40m) and then conducting injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. We have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS. Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and our objective was to evaluate opportunities for strain monitoring during characterization and monitoring for CCUS. Our approach was to deploy strainmeters at shallow depths (30 to 40m) and then conduct injection well tests in an underlying reservoir at 530m depth. The results indicate that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. In conclusion, we have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS.

Murdoch, Larry↗
DOE OSTI2024

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Using the Shallow Strain Tensor to Characterize Deep Geologic Reservoirs

Abstract Storing and recovering water, carbon, and heat from geologic reservoirs is central to managing resources in a changing climate. We tested the hypothesis that the strain tensor caused by injecting or producing fluids can be measured at shallow depths and interpreted to advance understanding of underlying deep aquifers or reservoirs. Geodetic‐grade strainmeters were deployed at 30 m depth overlying the Bartlesville Formation, a 500‐m‐deep sandstone near Tulsa, OK. The strainmeters are 220 m east of injection well 9A completed in a permeable lens at the base of the Bartlesville Formation. Water was injected into well 9A at approximately 1.0 L/s during four tests that ranged in duration from a few hours to a few weeks. The horizontal strain increased (tension) and the circumferential strain was a few times larger than the radial strain. The vertical strain decreased (compression) during injection. Strain rates were approximately 100 nε/day during the first few hours, but the rates decreased and were approximately 10 nε/day during most of the tests. Four independent methods of poroelastic simulation and inversion predict reservoir properties and geometries that are similar to each other and consistent with independent information about the reservoir. All strain interpretations predict that a boundary to the permeable lens occurs beneath the vicinity of the strainmeters, which is consistent with core data from the site. The boundary of the permeable lens is located by matching the vertical, radial and circumferential strains, which demonstrates the value of measuring the strain tensor.

Murdoch, Lawrence C.↗
DOE OSTI2022

Mechanisms of Mitigating Chloride-Induced Stress Corrosion Cracking of Austenitic Steels by Laser Shock Peening

This study investigates the effect of laser shock peening (LSP) on the chloride-induced stress corrosion cracking (SCC) of 304 austenitic steels. LSP can induce a high compressive residual stress to a depth of 700 µm and plastic deformation structures of dislocations, deformation twins, and stacking faults. Constant-load SCC tests in MgCl2 solution suggested that LSP can retard the crack initiation and slow the crack growth. LSP-treated subsurface layers experience ductile fracture while the central regions exhibit intergranular SCC. The LSP-induced deformation structures may impede dislocation slips, while the LSP-induced compressive residual stress can lessen the stress intensity factor of crack tips and decrease the local stress for film rupture.

Materials Science↗
DOE OSTI2026

BoBa

BoBa is a C++ software library for working with large matrices, tensors, and tensor decompositions. The library provides tools for dense matrix and tensor operations, tensor decompositions, and tensor decomposition methods that support modern CPU and GPU architectures. It includes portable abstractions for linear algebra, tensor algebra, and multidimensional computation. BoBa is intended for scientific computing applications that involve large multidimensional data sets or high dimensional mathematical models. Its capabilities support tasks such as data compression, linear algebra, efficient numerical computation, and the development of scalable algorithms for heterogeneous hardware. Tutorials, tests, and example applications are included to help users learn and apply the library.

Yao, Jin [Lawrence Livermore National Laboratory (↗
DOE OSTI2019

DE-SC0004913: The role of microstructural neighborhoods in forming and evolving slip localization in polycrystalline metals during cyclic plasticity (Final Report)

During this grant we processed and analyzed data from High Energy X-ray Diffraction (HEXD). We conducted a study of the evolution of an aggregate of commercially pure copper crystals subjected to cyclic loading conditions consistent with low cycle fatigue (LCF); each fatigue cycle contains macroscopically elastic-plastic deformation. The uniaxial test specimen initially loads elastically and yields in tension, then unloads elastically and re– yields in compression. The macroscopic cyclic stress-strain curve forms characteristic hysteresis loops that change in size (typically increase) with each cycle reflecting the plasticity-induced material evolution that is taking place within each crystal. It has been hypothesized that at some point, the to-and-fro plastic slip within one crystal or a group of crystals initiates a fatigue crack. Using HE x-ray diffraction we studied the cyclic plasticity within every deforming crystal by measuring how the lattice misorientation changes as the sample is loaded around the hysteresis loop.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Equations of State in Computational Physics: What, Why, and How

Summary: 1. Equations of state furnish thermodynamic properties of a material. 2. Usually involve P, p (or V), and T, or P, r, and E 3. Necessary ingredient to solve compressible flow problems. 4. Varieties: i. Analytical expressions (ideal gas, Grüneisen) – fast, convenient for verification and test problems ii. Graphs and charts – good for hand calculations iii. Tables and databases – generally most accurate, require interpolation i. Steam tables ii. NIST database iii. SESAME EOS Library 5. Constructed by using semi-empirical models from Statistical Mechanics and fitting to available data

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fiberboard Properties and Degradation Rates for Storage of 9975 Shipping Package in KAC (2020 Status Report)

Savannah River Site (SRS) stores plutonium materials within model 9975 shipping packages in the K-Area Complex (KAC). The 9975 shipping package consists of a 35 gallon stainless steel drum, Celotex fiberboard insulation, lead shield, and primary and secondary containment vessels. The 9975 shipping package design, performance, and analysis for safe transport of radioactive material are described in the Safety Analysis Report for Packaging (SARP). Celotex fiberboard provides three safety functions: thermal insulation to limit internal temperature during a fire, criticality control, and resistance to package crushing. The fiberboard material must retain its dimensions and density within certain ranges to provide the required impact resistance, criticality control, and fire resistance. The SRS Surveillance Program monitors material performance to establish a basis for service life and ensures the continued integrity of 9975 packages. Fiberboard samples, taken from multiple fiberboard assemblies fabricated from cane and softwood fiberboard, have been conditioning in elevated temperature environments since 2005. The samples are periodically examined to monitor thermal, mechanical, and physical properties, and assess degradation trends. Fiberboard properties of interest that are evaluated to demonstrate acceptable long-term performance include dimensional stability, density, compressive strength, thermal conductivity, and specific heat capacity. Duplicate samples from multiple package sources have been tested to identify the range of variability in fiberboard properties and degradation rates. Baseline and long-term testing of fiberboard material properties have been reported previously; reference 6 summarized experimental results of cane and softwood fiberboard through May 2019 and presented degradation models for the measured properties. This report presents the cumulative data collected through June 2020 and the corresponding updated aging models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗