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At least 307 records · Page 17

AGC-4 Specimen Post-Irradiation Examination Data Interim Report

This interim report documents preliminary results of the post-irradiation examination material property testing from the fourth advanced graphite creep (AGC), AGC 4, capsule specimens. This is the fourth of a series of six irradiation test trains planned as part of the AGC experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphite grades to moderate dose levels (=7 dpa). The AGC 4 capsule was irradiated in the Idaho National Laboratory Advanced Test Reactor at a nominal temperature of 800°C and to a peak dose of 8 dpa. Half of the AGC-4 specimens were subjected to compressive stresses to induce irradiation creep. Post-irradiation testing and measurement results are reported with the exception of thermal testing, which is still in progress, and irradiation mechanical strength testing. Additionally, some specimens initially deemed too hot to be examined in the ART Graphite laboratory may still be measured. The data reported includes specimen dimensions for both stressed and unstressed specimens to establish the irradiation creep rates, mass and dimensional data necessary to derive density, elastic constants (Young?s modulus, shear modulus, and Poisson?s ratio) from ultrasonic time of flight velocity measurements, Young?s modulus from the fundamental frequency of vibration, and electrical resistivity. A more complete evaluation of trends in the material property changes, as well as irradiation-induced creep due to the irradiation environment and applied load on the specimens, will be discussed later in AGC 4 post-irradiation examination analysis reports.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The cyclotron gas stopper at FRIB getting ready for operations

Linear gas stopping cells have been used for nearly two decades to slow down projectile fragments at the National Superconducting Cyclotron Laboratory, now the Facility for Rare Isotope Beams, for experiments with low-energy and reaccelerated beams. In order to efficiently stop and rapidly extract light to medium-mass fast ions, a cyclotron gas-stopper has been constructed. It uses a cyclotron-type magnet and a helium-gas filled stopping chamber to slow down the injected beam. RF ion guides transport the stopped ions to the center of the magnet and axially through the bore before acceleration to <60 keV. Following successful offline tests, the cyclotron stopper was moved to an experimental vault and connected to a new momentum–compression beam line. Beam transport to and into the cyclotron stopper was tested with stable beams. Finally, using 46 K fragments, the first successful stopping and extraction of a high-energy beam with the cyclotron stopper was demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mechanical Modeling and Testing of Pouch Cells under Various Loading Conditions

Understanding the mechanical behaviors of batteries is critical to improve battery safety since mechanical failure may directly lead to short-circuits. Nevertheless, mechanical modeling of batteries is challenging since a cell usually contains multiple thin layers with drastically different material properties, and they exhibit different responses under different loading conditions. In this work, we developed a mechanical model for a large-format pouch cell, where the cell is represented by thick shell elements that are not only computationally efficient but also account for different thickness and material properties of individual components. Moreover, the mechanical properties of active materials in electrodes are described by a continuous surface cap model that can capture both compaction and shear deformation modes and can include strain rate effect and damage. Furthermore, to evaluate the model capabilities, we conducted abuse tests under various loading conditions (quasi-static compression, shear and impact). It is shown that the model prediction of load-displacement relationship and failure condition agree with experimental results, which demonstrates that the developed model can capture the mechanical behaviors of a cell in different abuse events. Details of element formulation, material parameters evaluation and test setup are presented. Capabilities, limitations and future directions of model development are also discussed.

25 ENERGY STORAGE↗

Long-term strength retrogression of silica-enriched oil well cement: A comprehensive multi-approach analysis

The strength retrogression of a Class G cement enriched by adding 60–80% silica cured under the condition of 200 °C and 50 MPa were investigated by multiple different analysis methods. Short-term strength analysis suggests sonic strength testing is a poor indicator of real mechanical strength at such curing condition. Long-term testing up to 142 d shows all designed systems experiences dramatic deterioration in physical and mechanical properties, such as compressive strength, Young's modulus, water permeability and gas permeability. Further testing was conducted using X-ray diffraction, thermal gravimetric analysis, mercury intrusion and scanning electron microscope. The study reveals that the set cement experiences significant microstructure coarsening with increasing curing time, especially after 30 d curing. The strength retrogression and microstructure coarsening seem to be accompanied with the continued consumption of silica, and are likely caused by the gradual conversion of semi-crystalline C-S-H into crystalline tobermorite and xonolite over the long-term curing.

36 MATERIALS SCIENCE↗

Collective Summary of sCO2 Materials Development (Supercritical Transformational Electric Power Generation (STEP) Level 2 Milestone Report) (Parts I - II)

Polymers such as PTFE (polytetrafluorethylene or Teflon), EPDM (ethylene propylene diene monomer) rubber, FKM fluoroelastomer (Viton), Nylon 11, Nitrile butadiene (NBR) rubber, hydrogenated nitrile rubber (HNBR) and perfluoroelastomers (FF_202) are commonly employed in super critical CO 2 (sCO2) energy conversion systems. O-rings and gaskets made from these polymers face stringent performance conditions such as elevated temperatures, high pressures, pollutants, and corrosive humid environments. In FY 2019, we conducted experiments at high temperatures (100°C and 120°C) under isobaric conditions (20 MPa). Findings showed that elevated temperatures accelerated degradation of polymers in sCO2, and that certain polymer microstructures are more susceptible to degradation over others. In FY 2020, the focus was to understand the effect of sCO2 on polymers at low (10 MPa) and high pressures (40 MPa) under isothermal conditions (100°C). It was clear that the same selectivity was observed in these experiments wherein certain polymeric functionalities showed more propensity to failure over others. Fast diffusion, supported by higher pressures and long exposure times (1000 hours) at the test temperature, caused increased damage in sCO2 environments to even the most robust polymers. We also looked at polymers under compression in sCO2 at 100°C and 20 MPa pressure to imitate actual sealing performance required of these materials in sCO2 systems. Compression worsened the physical damage that resulted from chemical attack of the polymers under these test conditions. In FY 2021, the effect of cycling temperature (from 50°C to 150°C to 50°C) for polymers under a steady sCO2 pressure of 20 MPa was studied. The aim was to understand the influence of cycling temperatures of sCO2 for typical polymers under isobaric (20 MPa) conditions. Thermoplastic polymers (Nylon, and PTFE) and elastomers (EPDM, Viton, Buna N, Neoprene, FF202, and HNBR) were subjected to 20 MPa sCO2 pressure for 50 cycles and 100 cycles in separate experiments. Samples were extracted for ex-situ characterization at 50 cycles and upon the completion of 100 cycles. Each cycle constituted of 175 minutes of cycling from 50°C to 150°C. The polymer samples were examined for physical and chemical changes by Dynamic Mechanical and Thermal Analysis (DMTA), Fourier Transform Infrared (FTIR) spectroscopy, and compression set. Density and mass changes immediately after removal from test were measured for degree of swell comparisons. Optical microscopy techniques and micro computer tomography (micro CT) images were collected on select specimens. Evaluations conducted showed that exposures to super-critical CO2 environments resulted in combinations of physical and/or chemical changes. For each polymer, the dominance of cycling temperatures under sCO2 pressures, were evaluated. Attempts were made to qualitatively link the permanent sCO2 effects to polymer micro- structure, free volume, backbone substitutions, presence of polar groups, and degree of crystallinity differences. This study has established that soft polymeric materials are conducive to failure in sCO2 through mechanisms of failure that are dependent on polymer microstructure and chemistry. Polar pendant groups, large atom substitutions on the backbone are some of the factors that are influential structural factors.

36 MATERIALS SCIENCE↗

Graphene nanoplatelet for enhancement the mechanical properties and durability characteristics of alkali activated binder

The effects of the addition of graphene nanoplatelets (GNPs) on the microstructure, heat of hydration, mechanical properties and durability characteristics of alkali activated binders were investigated. A simple mixing process led to reasonably uniform dispersion of GNPs in the matrix, with minor agglomeration of GNPs detected via scanning electron microscopy. Tests on engineering properties indicated that the compressive strength of the alkali activated binder increased with the addition of GNPs at relatively low concentrations. Gains were also realized in the abrasion resistance and moisture sorptivity of the binder with GNPs addition. The heat of hydration investigations indicated that the addition of GNPs accelerates the hydration process and increases the amount of hydration products, especially at early ages. Scanning electron microscope investigations further indicated that GNPs could impede the development of microcracks and mitigate their propagation within matrix; indications of good bonding between the GNPs and the alkali activated matrix were also noted.

36 MATERIALS SCIENCE↗

Volumetric efficiency and pressure pulsations of a triplex reciprocating supercritical CO 2 pump

A reciprocating triplex pump has been integrated into a closed-loop supercritical carbon dioxide test facility. The pump is designed to compress liquid or supercritical carbon dioxide and has a maximum volumetric flow rate of 51 L/min. A sweep across the pump’s speed range of 100–1000 rev/min was performed with inlet conditions between 60 and 160 bar. The volumetric efficiency was found to increase as pump speed increased from 10 to 40 % before it plateaued at higher pump speeds. The mechanical efficiency increased linearly with pump speed and was not affected by system pressure. Pressure pulsations caused by the plungers and valves were also measured at each speed. Additionally, a 35-liter buffer volume, connected near the pump’s discharge was isolated at each speed to determine its effectiveness as a pulsation dampener. Overall the reciprocating pump was shown to perform exceptionally with liquid or supercritical inlet conditions applicable to many supercritical fluid applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Divergent evolution of slip banding in CrCoNi alloys

Abstract Metallic materials under high stress often exhibit deformation localization, manifesting as slip banding. Over seven decades ago, Frank and Read introduced the well-known model of dislocation multiplication at a source, explaining slip band formation. Here, we reveal two distinct types of slip bands (confined and extended) in compressed CrCoNi alloys through multi-scale testing and modeling from microscopic to atomic scales. The confined slip band, characterized by a thin glide zone, arises from the conventional process of repetitive full dislocation emissions at Frank–Read source. Contrary to the classical model, the extended band stems from slip-induced deactivation of dislocation sources, followed by consequent generation of new sources on adjacent planes, leading to rapid band thickening. Our findings provide insights into atomic-scale collective dislocation motion and microscopic deformation instability in advanced structural materials.

Science & Technology - Other Topics↗

Dynamical tuning of the chemical potential to achieve a target particle number in grand canonical Monte Carlo simulations

We present a method to facilitate Monte Carlo simulations in the grand canonical ensemble given a target mean particle number. The method imposes a fictitious dynamics on the chemical potential, to be run concurrently with the Monte Carlo sampling of the physical system. Corrections to the chemical potential are made according to time-averaged estimates of the mean and variance of the particle number, with the latter being proportional to thermodynamic compressibility. Here, we perform a variety of tests, and in all cases find rapid convergence of the chemical potential—inexactness of the tuning algorithm contributes only a minor part of the total measurement error for realistic simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗

Weak-Form Latent Space Dynamics Identification

This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.

Choi, Youngsoo↗

Milliradian precision ultrafast pulse control for spectral phase metrology

A pulse-shaper-based method for spectral phase measurement and compression with milliradian precision is proposed and tested experimentally. Measurements of chirp and third-order dispersion are performed and compared to theoretical predictions. The single-digit milliradian accuracy is benchmarked by a group velocity dispersion measurement of fused silica.

Stamm, Jacob↗

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗

Cellulose Nanofibrils Dewatered with Poly(Lactic Acid) for Improved Bio-Polymer Nanocomposite Processing

Cellulose nanofibrils (CNFs) have theoretically ideal properties for bio-based composite applications; however, the incorporation of these materials into polymers is made challenging by the strong binding of water to CNFs and the irreversible agglomeration of CNFs during drying. Previous methods used “contact dewatering”, wherein the addition of wood flour (WF) to CNFs facilitated the mechanical removal of water from the system via cold pressing, which showed potential in producing dried CNF fibrils attached to wood fibers for biocomposite applications. In this work, the viability of contact dewatering with poly(lactic) acid (PLA) powder for PLA/CNF composites was evaluated. The energy efficiency of dewatering, preservation of nanoscale CNF morphology, and mechanical properties were examined by mixing wet CNFs with pulverized PLA at various loading levels, pressing water out of the system, and compression molding and shear mixing composites for testing. The most impressive results from this dewatering method were the preservation of micron-to-nanoscale fibers with high aspect ratios in PLA-CNF composites; increased strength and modulus of 1.7% and 4.2%, respectively, compared to neat PLA; equivalent or better properties than spray-dried nanocellulose at similar loading levels; and an 11-194x reduction in drying energy compared to spray-drying CNFs.

Chemistry↗

ANS MiNES 2023 Poster

The dynamic mechanical properties of four varieties of high purity graphite as well as the depth of penetration (DoP) of a small-scale shaped charge into these grades was experimentally determined. The grades chosen were PCEA, NBG-18, and NBG-25. These grades provide a wide range of physical properties: in density from 1.80 – 1.85 g/cc, in maximum particle size from 10s to 1000s of µm, and in porosity from 18% to 20%. The quasistatic and dynamic compressive strengths of each grade were determined and correlated to their physical properties. The split Hopkinson pressure bar experiments showed both the dynamic strength and dominant shear failure mechanisms. A small scale shaped charge was used to compare the resistance of graphite to hypervelocity jet impacts: the Teledyne RP-4. The RP-4 has a 1.01” outer diameter and 3.44 g of RDX with an RP-80 booster (86 mg PETN + 123 mg RDX). A select number of samples were analyzed using X-Ray Computed Tomography (XCT), allowing for the full characterization of the undisturbed wound channel. A selection of other samples were physically sectioned and wound channels mapped from the sections. In addition to DoP, the wound geometry was characterized in terms of total volume and diameter at different depths. The wound channel characteristics for each grade were correlated to the compressive strengths and physical properties. In several of the test samples, the wound channel diameter was smaller than the diameter of the shaped charge slug just behind where the slug had penetrated the sample. These results indicated that the wound geometry was dependent on the compressive hysteresis behavior of graphite.

36 MATERIALS SCIENCE↗

Performance of high-order Godunov-type methods in simulations of astrophysical low Mach number flows

High-order Godunov methods for gas dynamics have become a standard tool for simulating different classes of astrophysical flows. Their accuracy is mostly determined by the spatial interpolant used to reconstruct the pair of Riemann states at cell interfaces and by the Riemann solver that computes the interface fluxes. In most Godunov-type methods, these two steps can be treated independently, so that many different schemes can in principle be built from the same numerical framework. Because astrophysical simulations often test out the limits of what is feasible with the computational resources available, it is essential to find the scheme that produces the numerical solution with the desired accuracy at the lowest computational cost. However, establishing the best combination of numerical options in a Godunov-type method to be used for simulating a complex hydrodynamic problem is a nontrivial task. In fact, formally more accurate schemes do not always outperform simpler and more diffusive methods, especially if sharp gradients are present in the flow. For this work, we used our fully compressible Seven-League Hydro (SLH) code to test the accuracy of six reconstruction methods and three approximate Riemann solvers on two- and three-dimensional (2D and 3D) problems involving subsonic flows only. We considered Mach numbers in the range from 10 −3 to 10 −1 , which are characteristic of many stellar and geophysical flows. In particular, we considered a well-posed, 2D, Kelvin–Helmholtz instability problem and a 3D turbulent convection zone that excites internal gravity waves in an overlying stable layer. Although the different combinations of numerical methods converge to the same solution with increasing grid resolution for most of the quantities analyzed here, we find that (i) there is a spread of almost four orders of magnitude in computational cost per fixed accuracy between the methods tested in this study, with the most performant method being a combination of a low-dissipation Riemann solver and a sextic reconstruction scheme; (ii) the low-dissipation solver always outperforms conventional Riemann solvers on a fixed grid when the reconstruction scheme is kept the same; (iii) in simulations of turbulent flows, increasing the order of spatial reconstruction reduces the characteristic dissipation length scale achieved on a given grid even if the overall scheme is only second order accurate; (iv) reconstruction methods based on slope-limiting techniques tend to generate artificial, high-frequency acoustic waves during the evolution of the flow; and (v) unlimited reconstruction methods introduce oscillations in the thermal stratification near the convective boundary, where the entropy gradient is steep.

79 ASTRONOMY AND ASTROPHYSICS↗

An Integrated High Pressure SOFC and Premixed Compression Ignition (PCI) Engine System

Components for a transformative, high pressure, intermediate temperature solid oxide fuel cell (SOFC) and premixed compression ignition (PCI) engine system were developed. The resulting system is a 1 MWe natural gas fueled hybrid SOFC and reciprocating internal combustion engine system capable of achieving over 70% electrical efficiency at a cost of $0.87/W. To achieve 70% electric efficiency, the SOFC system operates at 80% fuel utilization; however, when operating at this high level of fuel utilization, fuel to the engine (anode tailgas) is extremely dilute. Accordingly, a substantial portion of the effort focused on development and assessment of the combustion strategy capable of consuming this dilute fuel mixture. The engine testing effort showed that pre-chamber assisted compression ignition provides the best combination of controllability, efficiency and emissions. The engine experiments showed that high efficiency combustion can be achieved with near zero criteria pollutants. It is likely that the engine system could operate with minimal aftertreatment requirements, reducing complexity, cost, and precious metal usage. System level modeling was used to assess the overall efficiency, determine cost and efficiency tradeoffs, and demonstrate the potential to perform load following with the hybrid system. Finally, advanced manufacturing was used to demonstrate the potential to fabricate heat exchangers needed for the hybrid system from low chromium materials, which addresses the issue of chromium poisoning of the SOFC stack material.

03 NATURAL GAS↗