Experimental and numerical study of heat transfer characteristics of single-phase free-surface fan jet impingement with automatic transmission fluid
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Feng, Xuhui (ORCID:0000000261559356)↗
SEARCH · Engineering Papers
Results for “power coefficient”
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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Plasma decay in hydrocarbons and hydrocarbon- and H 2 O-containing mixtures excited by high-voltage nanosecond discharge at elevated gas temperatures
Plasma decay after a high-voltage nanosecond discharge was experimentally and numerically studied in pure hydrocarbons (C 2 H 6 and C 3 H 8 ), and H 2 O:N 2 and C 3 H 8 :O 2 mixtures for pressures in the range 2–4 Torr and gas temperatures from 300 to 600 K. In a stoichiometric C 3 H 8 :O 2 mixture, plasma decay was also studied in a repetitively pulsed discharge for varing numbers of discharge pulses (varying degrees of fuel oxidation). The rate of plasma decay was determined from the temporal evolution of electron density measured using the microwave interferometer. It was observed that gas heating to 600 K leads to a decrease in the rate of plasma decay in all cases. The effect of heating on plasma decay was most profound in the H 2 O:N 2 mixture (after a single discharge pulse) and in the C 3 H 8 :O 2 mixture for high degrees of fuel oxidation. A kinetic scheme was developed to numerically simulate the plasma decay in hydrocarbons and combustible mixtures. Numerical analysis showed that, under the conditions studied, plasma decay was controlled by dissociative electron recombination with simple molecular and cluster ions. Gas heating led to a decrease in the rate of the electron-ion recombination and the rate of conversion of molecular ions to cluster ions. As a result, the gas temperature increase caused a decrease in the fraction of cluster ions for which the recombination coefficients are an order of magnitude higher than the recombination coefficients for molecular ions. The influence of gas heating on the decrease of the amount of cluster ions was more important when the ion composition was dominated by hydrated H 3 O + (H 2 O) k ions. The rates of the formation of these ions are extremely sensitive to any variations in gas temperature. A result, in agreement with our observations, gas heating led to an anomalous decrease in the rates of plasma decay in the H 2 O:N 2 mixture, as well as in the C 3 H 8 :O 2 mixture when H 2 O molecules were produced due to fuel oxidation.
20 FOSSIL-FUELED POWER PLANTS↗
Encapsulation of Ba in InSb Framework Introduces Chirality in Clathrate-Like BaIn 4 Sb 4
The discovery of Zintl compounds remains a powerful strategy for identifying materials with tunable electronic and thermal transport properties. During a concerted search for new inorganic clathrates with In–Sb frameworks, we discovered BaIn 4 Sb 4 . The composition of this phase deviates from that expected for a type-I clathrate with tetrahedral coordination of all In and Sb atoms (Ba 8 In 31 Sb 15 ). Instead, in the chiral structure of BaIn 4 Sb 4 (space group P 3 1 21, No. 152), a part of the In atoms have a trigonal planar coordination of 1In + 2Sb, forming Sb 2 –In–In–Sb 2 nonplanar fragments isostructural to diborane(4) B 2 H 4 with D 2 d symmetry. Ba atoms are located inside 16-vertex In 8 Sb 8 polyhedra, which share vertices and edges to form a chiral framework around the 3 1 screw axes. The title compound is electron-balanced, [Ba 2+ ][In 2+ ] 2 [In 3+ ] 2 [Sb3–] 4 , which was confirmed by characterization of the charge and heat transport properties. BaIn 4 Sb 4 exhibits a low thermal conductivity and high Seebeck coefficient, suggesting its untapped potential for thermoelectric applications. Finally, density functional theory (DFT) calculations indicate that chemical doping may enhance carrier concentration and improve the originally low electrical conductivity, thus enhancing thermoelectric performance.
electrical properties↗
A combined SECM and electrochemical AFM approach to probe interfacial processes affecting molecular reactivity at redox flow battery electrodes
Redox flow batteries are attractive technologies for grid energy storage since they use solutions of redox-active molecules that enable a superior scalability and the decoupling of power and energy density. However, the reaction mechanisms of the redox active components at RFB electrodes are complex, and there is currently a pressing need to understand how interfacial processes impact the kinetics and operational reversibility of RFB systems. Here, we developed a combined electrochemical imaging methodology rooted in scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM) for exploring the impact of electrode structure and conditioning on the electron transfer properties of model redox-active dialkoxybenzene derivatives, 2,5-di-tert-butyl-1,4-bis(2-methoxyethoxy)benzene (C1) and 2,3-dimethyl-1,4-dialkoxybenzene (C7). Using AFM and secondary-ion mass spectrometry (SIMS), we observed the formation of interfacial films with distinct mechanical properties compared to those of cleaved graphitic surfaces, and exclusively during reduction of electrogenerated radical cations. These films had an impact on the median rate and distribution of the electron transfer rate constant at the basal plane of multilayer and single layer graphene electrodes, displaying kinetically-limited values that did not yield the activation expected per the Butler–Volmer model with a transfer coefficient ~0.5. These changes were dependent on redoxmer structure: furthermore, SECM showed strong attenuation of C7 kinetics by a surface layer on MLG and SLG, while C1 kinetics were only affected by SLG. SECM and AFM results together show that these limiting films operate exclusively on the basal plane of graphite, with the edge plane showing a relative insensitivity to cycling and operation potential. Ultimately, this integrated electrochemical imaging methodology creates new opportunities to understand the unique role of interfacial processes on the heterogeneous reactivity of redoxmers at electrodes for RFBs, with a future role in elucidating phenomena at high active concentrations and spatiotemporal variations in electrode dynamics.
25 ENERGY STORAGE↗
Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps
Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.
54 ENVIRONMENTAL SCIENCES↗
Computational thermodynamics and its applications
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.
36 MATERIALS SCIENCE↗
Investigating feasible light configurations for fish restoration: an ethological insight
Light environment significantly impacts the effectiveness of fish population restoration in developed watersheds, subserving fish passage reconstruction in hydraulic complex and habitat rehabilitation. To develop an interior connection between light-related fish response from the laboratory and field fish conservation practice, we employed a new indexing system, consisting of phototaxis rate, relative swimming speed (RSS), and optic evasion coefficient (OEC), to quantify the light-induced behaviors in Ptychobarbus kaznakovi, a representative rare cyprinid in Tibet, China, at four experimental illuminance levels (15 lx, 30 lx, 60 lx, 120 lx) and four wavelengths (red, yellow, green, blue). The fish showed negative phototaxis at all given illuminances and wavelengths. Under red light, the OEC increased significantly from 0.642 at 15 lx to 0.782 at 30 lx (P = 0.029), while the RSS decreased significantly from 3.752 to 2.383 (P < 0.001). Behaviorally, the fish shifted from sprint to wandering around, indicating the alteration of dominant physiological activity from behavioral stress response to negative phototaxis. Under the green treatment, P. kaznakovi swam around quickly and presented slight negative phototaxis, and OEC values were uniform among all illuminances, probably because of the similarity of green light to the ambient color of the habitat. Accordingly, ecologists and fisheries practitioners can utilize red light to exclude fish from dangerous waters and green light to guide them to ideal habitats, laying the necessary groundwork for the light-driven fish recovery effort. Furthermore, the appropriate light configuration can yield economic benefits through the tradeoff among fish protection, power generation, and investment costs.
Lin, Chenyu↗
Case Study of Integrating High-Temperature Heat Pump with LiBr-H2O Absorption Chiller for Data Center Liquid Cooling
Data centers (DCs) are physical infrastructures that support artificial intelligence workloads. The rapid growth of artificial intelligence is putting substantial pressure on the US power grid. Most of electricity consumed by IT equipment, accounting for 50%-60% of total DC power, ultimately becomes waste heat. This heat is dissipated by DC’s cooling facilities, accounting for an additional 30%-40% of total DC power. Recovering and repurposing this waste heat offers a significant opportunity to enhance energy efficiency and reduce operating costs of DCs. One potential pathway is converting heat to cold using thermal-driven absorption chillers, therefore, reducing the power consumption in DC cooling facilities. Existing studies mainly demonstrate the technical and economic feasibility of repurposing DC’s waste heat for cooling applications but provide limited technical details on how to integrate the thermal-driven absorption chillers with DC cooling systems. In addition, the low-grade waste heat available from DCs must be upgraded to higher temperatures suitable for absorption chillers. This paper presents a case study on integrating high-temperature heat pumps with a LiBr-H2O absorption chiller to use DC waste heat for cooling. A thermodynamic model of single-effect, LiBr-H2O absorption chiller and an empirical model of high-temperature heat pumps were built. The case study considers ASHRAE W17 liquid-cooled DC, with facility service water supplied at 17.0℃ and returned at 25.3℃. The thermal behaviors of absorption chiller components were predicted for the generation temperature ranging from 75.0℃ to 115.0℃. Based on the available waste heat in the integrated system, two waste heat recovery strategies were evaluated: a facility service water-based strategy and cooling water-based strategy. Results indicated that the cooling water-based strategy achieves higher Coefficient of Performance (COPs) than the facility service water-based strategy. The relatively low cooling COPs of single-effect LiBr-H2O absorption chillers could be offset by high heating COP of high temperature heat pumps. The maximum cooling COP of absorption chiller and the overall COP of integrated systems occur at lower generation temperatures, but these conditions also yield lower cooling capacities. In practice, system operation should balance the trade-off between the COP and cooling capacity
Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗
Rapid Solidification Effects in Additively Manufactured Si and SiGe Compositions
SiGe alloys have a proven track record as robust high-temperature thermoelectric materials, powering NASA missions like SNAP-10A, LES-9, and Voyager 1 and 2. Enhancing thermoelectric efficiency hinges on minimizing thermal conductivity while preserving electrical conductivity. Rapid solidification via LPBF can generate microstructural features such as subgrain cellular boundaries and twinning, which may help reduce thermal conductivity while preserving semiconducting behavior. Here, this study investigates the potential of laser powder bed fusion (LPBF) additive manufacturing to fabricate nanostructured Si and SiGe thermoelectric materials. High cooling rates (10 5 to 10 7 K/s) rates inherent to the LPBF process are conducive to forming such nanostructures. Moreover, this fabrication technique could also be suitable for fabricating complex geometries needed to achieve improved device level performance. Process mapping of commercial Si powder with irregular morphology was first performed to understand the LPBF processing behavior of this semiconductor material. Subsequent studies included in-house synthesized B-doped (p-type) Si7 8 Ge 22 spherical powder that was produced via ultrasonic atomization. Scan strategies involved multiple laser exposures to mitigate solidification cracking: a high density of >98% was achieved, but solidification cracking could not be fully eliminated. Subsequently, a high electrical resistivity (i.e., low conductivity) was observed, but the measured Seebeck coefficient, ∼230 μV/K @ 500 °C, proved that good semiconductor material was being fabricated. A subgrain cellular structure (5–10 μm) was observed as defined by Ge segregation to the intercellular boundaries. The remelting strategies helped lower the cooling rates in processing SiGe, but this still resulted in high residual stresses, which induced a remarkably high density of twins (78–95%) to accommodate the deformation. This unique grain structure offers an avenue for phonon scattering and potential improvements in thermoelectric performance.
figure of merit↗
Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services
A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.
Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗
Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model
Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.
79 ASTRONOMY AND ASTROPHYSICS↗
Revealing the role of redox reaction selectivity and mass transfer in current–voltage predictions for ensembles of photocatalysts
Photocatalysts are conceptually simple reaction units where nanoscale semiconductors integrated with catalysts drive a pair of redox reactions on illumination. However, the proximity of reaction sites performing cathodic and anodic reactions poses dire challenges to realize large light-to-fuel conversion efficiencies. In this study, a powerful, yet straightforward, equivalent-circuit detail-balance modeling framework is developed and applied to evaluate the performance of photocatalytic systems featuring multiple light absorbers. Specifically, low bandgap iridium-doped strontium titanate is modeled as a Z-scheme photocatalyst to achieve desirable hydrogen evolution and iron-based redox shuttle oxidation reactions. Our model has unique capabilities to simulate competing redox reactions and address mass-transfer limitations. In a significant departure from state-of-the-art circuit models, our study develops tools to perform load-line analyses by incorporating a net electrochemical load curve that includes both desired and competing redox reactions. Consequently, reaction selectivity is predicted from equivalent circuit models for photocatalytic and photoelectrochemical systems. Our investigation into ensembles comprised of multiple, semi-transparent light absorbers reveals their potential to outperform a single, optically thick light absorber, particularly when operated under mass-transfer-limited conditions. However, this outcome hinges on minimizing mass-transfer rates of select redox species to prevent undesired reactions of hydrogen oxidation and/or redox shuttle reduction. Our findings demonstrate that reaction selectivity can be achieved by tuning asymmetry in redox species mass-transfer even with perfectly symmetric electrocatalytic charge-transfer coefficients. The influences of various kinetic, mass-transfer, and thermodynamic parameters are explored to offer crucial insights for synthesis of the next-generation of photocatalysts and selective coatings, and reactor designs.
25 ENERGY STORAGE↗
Hydrogen transport in yttrium hydride under asymmetric heat
Metal hydrides are a promising moderator material for high temperature fission reactors. Yttrium hydride can be loaded to a high hydrogen density with relatively high hydrogen stability at temperatures up to 800°C. This makes yttrium hydride a potential moderator material for microreactors as foreseen in the fission surface power program. However, during the operation of such advanced reactors temperature gradients are expected which can change the local hydrogen density in the moderator. Hydrogen diffusion in metals is driven by a concentration gradient (Fick’s law) and thermal diffusion (Soret diffusion). Thermal diffusion is the transport of hydrogen, or other species, due to a temperature gradient. For example, hydrogen might migrate from the hot side of a sample to the cold side of a sample. Measuring Fickian diffusion is achieved through various permeation or absorption experiments, however measuring thermal diffusion is challenging and has rarely been performed. The Hydrogen Experimental Apparatus for Thermal Diffusion (HEATD) experiment is designed to induce thermal diffusion in samples and quench those samples so that the hydrogen distribution can be analyzed using hot vacuum extraction (HVE). One side of the sample was heated to a high temperature e.g., 800°C, while the other side of the sample is at a lower temperature. The sample was held under the applied temperature gradient for a given time until the anticipated hydrogen diffusion has occurred. The actual time depends depend on the sample composition and hydrogen concentration. The results from HVE showed that thermal diffusion took place in the specimen and the Soret coefficient was calculated.
36 MATERIALS SCIENCE↗
Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts
Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.
36 MATERIALS SCIENCE↗
Enhancing Sensitivity in Targeted Single-Cell Proteomics by Coupling a Dual Ion Funnel Interface with Triple Quadrupole Mass Spectrometer
Single-cell proteomics (SCP) has emerged as a powerful approach for understanding cellular heterogeneity and biological processes at unprecedented resolution. However, the extremely limited protein content of individual cells (femtogram to picogram levels) pushes current mass spectrometry instrumentation to its sensitivity limits, creating a critical analytical bottleneck. While selected reaction monitoring (SRM) using triple quadrupole (QqQ) instruments 1 offers advantages in sensitivity and reproducibility for targeted proteomics quantification, SRM still struggles with sensitivity for quantification of moderate- or low-abundance proteins from single-cell sample amounts. Here, we report the development and systematic evaluation of a dual ion funnel interface designed to address the sensitivity limitation by significantly enhancing ion transmission efficiency in commercial QqQ mass spectrometers. The dual ion funnel interface, composed of a curved S-funnel followed by a conventional ion funnel, improves ion transmission efficiency while reducing chemical noise through selective ion focusing. The performance of the dual ion funnel interface was systematically compared to standard interface on a TSQ Vantage platform across samples with different levels of complexity. The dual funnel interface demonstrated to provide up to 25-fold improvement in sensitivity across a wide range of protein concentrations in different biological matrices (low complex mouse macrophage and high complex human cells). Critically, enhanced sensitivity was accompanied by increased analytical reproducibility with lower coefficient of variations. Most importantly, the dual funnel interface enabled reliable quantification of low-abundance proteins that were barely detectable or not detected by the standard interface, extending analysis to single-cell equivalent amounts while maintaining excellent reproducibility. These results demonstrate that the dual funnel interface addresses the critical bottleneck in quantitative targeted proteomics, providing a technological foundation for ultrasensitive targeted SCP that requires both high sensitivity and robust quantitative performance.
Min, Sehong↗
Comparison of Fission Product Release Predictions using PARFUME and BISON with Results from the AGR-3/4 Irradiation Experiment
The PARFUME (PARticle Fuel ModEl) fuel performance modeling code and the BISON nuclear fuel performance application built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library were used to predict the fission product release from tristructural isotropic (TRISO) coated fuel particles and compacts during the third and fourth irradiation experiment of the Advanced Gas Reactor (AGR-3/4) Fuel Development and Qualification Program. The fuel performance modeling codes PARFUME and BISON modeled the AGR-3/4 irradiation experiment using the fuel compact time-averaged volume averaged (TAVA) daily temperatures for a total irradiation duration of 369.1 effective full power days (EFPD) to predict the release fraction of the fission product silver (Ag-110m) from a representative TRISO-coated fuel particle from AGR-3/4 compacts. Post-irradiation examination (PIE) measurements provided data on the release of these fission products in the compacts outside of the silicon carbide (SIC) layer. The PARFUME and BISON results were then compared to the silver release measured from compact gamma scanning. The results showed good agreement between PARFUME and BISON but both codes under-predicted the silver release fraction for all the compacts. In addition, BISON was used to model and predict the fission product concentration radial profile outside of the compacts in capsules’ inner and outer rings. These rings were either comprised of matrix and/or structural graphite. To obtain the concentration profiles of silver, cesium, and strontium, a sorption isotherm model was developed in BISON to capture the effects of fission product transport across the gaps between the concentric rings. The general shape of the concentration radial profiles as calculated by BISON were similar in the inner ring (IR) but varied in the outer ring (OR) depending on the fission product of interest or capsule temperature. Using this methodology and model, BISON now has the capability to aid in developing new fission product diffusion coefficients for matrix or structural graphite materials.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Cosmic topology. Part I. Limits on orientable Euclidean manifolds from circle searches
The Einstein field equations of general relativity constrain the local curvature at every point in spacetime, but say nothing about the global topology of the Universe. Cosmic microwave background anisotropies have proven to be the most powerful probe of non-trivial topology since, within ΛCDM, these anisotropies have well-characterized statistical properties, the signal is principally from a thin spherical shell centered on the observer (the last scattering surface), and space-based observations nearly cover the full sky. The most generic signature of cosmic topology in the microwave background is pairs of circles with matching temperature and polarization patterns. No such circle pairs have been seen above noise in the WMAP or Planck temperature data, implying that the shortest non-contractible loop around the Universe through our location is longer than 98.5% of the comoving diameter of the last scattering surface. We translate this generic constraint into limits on the parameters that characterize manifolds with each of the nine possible non-trivial orientable Euclidean topologies, and provide a code which computes these constraints. In all but the simplest cases, the shortest non-contractible loop in the space can avoid us, and be shorter than the diameter of the last scattering surface by a factor ranging from 2 to at least 6. Further, this result implies that a broader range of manifolds is observationally allowed than widely appreciated. Probing these manifolds will require more subtle statistical signatures than matched circles, such as off-diagonal correlations of harmonic coefficients.
79 ASTRONOMY AND ASTROPHYSICS↗
Conversion Kinetics and Ionic Conductivity in Na-β”-Alumina + YSZ (Naβ”AY) Sodium Solid Electrolyte via Vapor Phase Conversion Process
Sodium ion batteries have been receiving increasing attention and may see potential revival in the near future, particularly in large-scale grid energy storage coupling with wind and solar power generation, due to the abundant sodium resources, low cost, and sufficiently high energy density. Among the known sodium ion conductors, the Na-β”-alumina electrolyte remains highly attractive because of its high ionic conductivity. This study focuses on the vapor phase synthesis of a Na-β”-Alumina + YSZ (Naβ”AY) composite sodium electrolyte, which has higher mechanical strength and stability than conventional single phase β”-Alumina. The objectives are the measurement of conversion kinetics through a newly developed weight-gain based model and the determination of sodium ionic conductivity in the composite electrolyte. Starting samples contained ~70 vol% α-Alumina and ~30 vol% YSZ (3 mol% Y 2 O 3 stabilized Zirconia) with and without a thin alumina surface layer made by sintering in air at 1600 °C. The sintered samples were placed in a powder of Na-β”-alumina and heat-treated at 1250 °C for various periods. Sample dimensions and weight were measured as a function of heat treatment time. The conversion of α-Alumina in the α-Alumina + YSZ composite into Naβ”AY occurred by coupled diffusion of sodium ions through Na-β”-alumina and of oxygen ions through YSZ, effectively diffusing Na2O. From the analysis of the time dependence of sample mass and dimensions, the effective diffusion coefficient of Na 2 O through the sample, D eff , was estimated to be 1.74 x 10 -7 cm2 s -1 , and the effective interface transfer parameter, k eff , was estimated as 2.33 x 10 -6 cm s -1 . By depositing a thin alumina coating layer on top of the bulk composite, the chemical diffusion coefficient of oxygen through single phase Na-β”-alumina was estimated as 4.35 x 10 -10 cm 2 s -1 . An AC impedance measurement was performed on a fully converted Naβ”AY composite, and the conductivity of the composite electrolyte was 1.3 x 10 -1 S cm -1 at 300 °C and 1.6 x 10 -3 S cm -1 at 25 °C, indicating promising applications in solid state or molten salt batteries at low to intermediate temperatures.
36 MATERIALS SCIENCE↗