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At least 127 records · Page 7

A radiative transfer model for remote sensing of laser induced fluorescence of phytoplankton in non-homogeneous turbid water

A radiative transfer computer model was developed to characterize the total flux of chlorophyll a fluoresced or backscattered photons when laser radiation is incident on turbid water that contains a non-homogeneous suspension of inorganic sediments and phytoplankton. The radiative transfer model is based on the Monte Carlo technique and assumes that: (1) the aquatic medium can be represented by a stratified concentration profile; and (2) that appropriate optical parameters can be defined for each layer. The model was designed to minimize the required computer resources and run time. Results are presented for an anacystis marinus culture.

Venable, D. D.↗

Multi-scale topology optimization of multi-material structures with controllable geometric complexity — Applications to heat transfer problems

This study presents a topology optimization method to design assemblies of periodic cellular materials with controllable geometric complexity. The framework is based on a novel multi-scale and multi-material design model in which the structure, the layout of the material subdomains, and their micro-structures are optimized concurrently. To allow a tight control over its geometrical complexity, the layout at the macro-scale is described by level-set fields, parameterized by geometric primitives. The micro-scale geometry is represented through a density approach. A nonlinear programming algorithm drives the optimization process using design sensitivities computed by the discrete adjoint method. The proposed design framework is studied with heat transfer problems. Practical design problems, such as a heat sink and a thermal storage unit with phase change are discussed. The macro-scale analysis model relies on a generalized transient diffusion equation. At the micro-scale, homogenization is used to compute equivalent material properties. The numerical examples in this study show that the optimized multi-scale multi-material layouts outperform the corresponding mono-scale structures while maintaining geometric simplicity at the macro-scale level.

42 ENGINEERING↗

Turbulence modeling and experiments

The best way of verifying turbulence is to do a direct comparison between the various terms and their models. The success of this approach depends upon the availability of the data for the exact correlations (both experimental and DNS). The other approach involves numerically solving the differential equations and then comparing the results with the data. The results of such a computation will depend upon the accuracy of all the modeled terms and constants. Because of this it is sometimes difficult to find the cause of a poor performance by a model. However, such a calculation is still meaningful in other ways as it shows how a complete Reynolds stress model performs. Thirteen homogeneous flows are numerically computed using the second order closure models. We concentrate only on those models which use a linear (or quasi-linear) model for the rapid term. This, therefore, includes the Launder, Reece and Rodi (LRR) model; the isotropization of production (IP) model; and the Speziale, Sarkar, and Gatski (SSG) model. Which of the three models performs better is examined along with what are their weaknesses, if any. The other work reported deal with the experimental balances of the second moment equations for a buoyant plume. Despite the tremendous amount of activity toward the second order closure modeling of turbulence, very little experimental information is available about the budgets of the second moment equations. Part of the problem stems from our inability to measure the pressure correlations. However, if everything else appearing in these equations is known from the experiment, pressure correlations can be obtained as the closing terms. This is the closest we can come to in obtaining these terms from experiment, and despite the measurement errors which might be present in such balances, the resulting information will be extremely useful for the turbulence modelers. The purpose of this part of the work was to provide such balances of the Reynolds stress and heat flux equations for the buoyant plume.

Shabbir, Aamir↗

Effects of cooling time on a closed LWR fuel cycle

In this study, the effects of cooling time prior to reprocessing spent LWR fuel has on the reactor physics characteristics of a PWR fully loaded with homogeneously mixed U-Pu or U-TRU oxide (MOX) fuel is examined. A reactor physics analysis was completed using the CASM04e code. A void reactivity feedback coefficient analysis was also completed for an infinite lattice of fresh fuel assemblies. Some useful conclusions can be made regarding the effect that cooling time prior to reprocessing spent LWR fuel has on a closed homogeneous MOX fuel cycle. The computational analysis shows that it is more neutronically efficient to reprocess cooled spent fuel into homogeneous MOX fuel rods earlier rather than later as the fissile fuel content decreases with time. Also, the number of spent fuel rods needed to fabricate one MOX fuel rod increases as cooling time increases. In the case of TRU MOX fuel, with time, there is an economic tradeoff between fuel handling difficulty and higher throughput of fuel to be reprocessed. The void coefficient analysis shows that the void coefficient becomes progressively more restrictive on fuel Pu content with increasing spent fuel cooling time before reprocessing. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Radiolytic Gas Bubbles' Model and its Application to AHR's Transient Neutronics Analysis

Aqueous Homogeneous Reactor (AHR) receives much attention recently because its advantages in medical isotopes production. Fissile material and moderator is mixed in the fuel solution, leads to big negative feedback and generation of radiolytic gas bubbles; the fluidity of fuel and movement of bubbles bring out big challenge of the neutronics analysis methods. This paper aims to establish a reliable and effective gas bubbles' model, firstly a coupled Neutronics-CFD method is introduced to recognize gas bubbles' behavior characteristics, then it is simplified into mathematical expression and applied to Transient Calculation Code of Aqueous Homogeneous Reactor (TCCAHR), finally a typical AHR's transient process is simulated and compared with the experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A homogeneous heat pipe design code

A computer program was developed to facilitate parametric performance evaluation of heat pipes in lightweight heat rejection systems. A description of the code, user's manual, and sample inputs are provided. The emphasis is placed on the analysis and design of homogeneous wick heat pipes. The analysis of the annular heat pipe is included as part of the heat pipe radiator subroutine.

Nakashima, A. M.↗

A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD{sub B}). The purpose of this study is to extend the capability of the Nth-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different types of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD{sub B} in the brain layer with a step decrement of 10% while maintaining αD{sub B} values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order (N ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The Nth-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Homogenization for Periodic Heterogeneous Materials with Arbitrary Position-Dependent Material Properties

We present a rigorous homogenization approach for efficient computation of a class of physical problems in a one-dimensional periodic heterogeneous material. This material is represented by a spatially periodic array of unit cells with a length of e. More specifically, the method is applied to the diffusion, heat conduction, and wave propagation problems. Heterogeneous materials can have arbitrary position-dependent continuous or discontinuous materials properties (for example heat conductivity) within the unit cell. The final effective model includes both effective properties at the leading order and high-order contributions due to the microscopic heterogeneity. A dimensionless heterogeneity parameter ß is defined to represent high-order contributions, shown to be in the range of [-1/12, 0], and has a universal expression for all three problems. Both effective properties and heterogeneity parameter ß are independent of e, the microscopic scale of heterogeneity. The homogenized solution describing macroscopic variations can be obtained from the effective model. Solution with sub-unit-cell accuracy can be constructed based on the homogenized solution and its spatial derivatives. The paper represents a general approach to obtain the effective model for arbitrary periodic heterogeneous materials with position-dependent properties.

conduction↗

Comparison of Homogeneous and Heterogeneous CFD Fuel Models for Phase I of the IAEA CRP on HTR Uncertainties Benchmark

Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent Advances in X-ray Absorption Near Edge Structure (XANES) Simulation for Catalysis: Theories and Applications

X-ray absorption spectroscopy (XAS) is a powerful spectroscopic technique for characterizing catalytic active sites. In particular, X-ray Absorption Near Edge Structure (XANES) provides insights into the oxidation state and local coordination environment of the absorbing atom, shedding light on the catalytic structure. Computational XANES simulations provide one-on-one correspondence between the molecular structure and their corresponding spectra, making them an effective approach for interpreting experimental XANES features. This work outlines various theories used to simulate XANES spectra and highlights recent advancements in computational XANES applications for homogeneous, heterogeneous, and single-atom catalysts focusing on identifying the active site structures, the site heterogeneity, and the dynamic evolution of catalysts.

Xu, Jiayi↗

Casimir self-stress in a dielectric sphere

The dielectric sphere has been an important test case for understanding and calculating the vacuum force of a dielectric body onto itself. Here we develop a method for computing this force in homogeneous spheres of arbitrary dielectric properties embedded in arbitrary homogeneous backgrounds, assuming only that both materials are isotropic and dispersionless. Our results agree with known special cases; most notably we reproduce the prediction of Boyer and Schwinger et al. of a repulsive Casimir force of a perfectly reflecting shell. Our results disagree with the literature in the dilute limit. We argue that the Casimir self-stress cannot be regarded as due to pair-wise Casimir–Polder interactions, but rather due to reflections of virtual electromagnetic waves.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

In situ X-ray Scattering and Dynamical Modeling of Pd Catalyst Nanoparticles Formed in Flames

It has previously been demonstrated that organopalladium precursors can break down under combustion conditions, forming nanoparticles that catalyze ignition. Here, we use in situ small-angle X-ray scattering (SAXS) to probe the formation and growth of palladium nanoparticles in an ethylene fl ame doped with 28 ppm (mol) of Pd(acetate) 2 . The particles appear to nucleate in the fl ame front and are observed by SAXS to grow in size and mass in the high-temperature region of the fl ame ( ~ 2200 K) with median diameters that evolve from 1.5 to 3.0 nm. Transmission electron microscopy of particles collected on a grid located outside the fl ame shows that the particles are metallic palladium with sizes comparable to those determined by SAXS. Molecular dynamics simulation of particles of selected sizes indicates that at the fl ame temperature the particles are molten and the average mass density of the particle material is notably smaller than that of bulk, liquid Pd at the melting point. Both experimental and computational results point to homogeneous nucleation and particle - particle coalescence as mechanisms for particle formation and growth. Aerosol dynamics simulation reproduces the time evolution of the particle size distribution and suggests that a substantial fraction of the particles must be electrically charged during their growth process.

36 MATERIALS SCIENCE↗

Impact Modeling and Testing of Pouch and Prismatic Cells

Understanding battery response under impact is critical to improve the safety of electrified vehicles. Nevertheless, predicting the impact behaviors of batteries is not straightforward since a battery cell usually contains hundreds of thin layers with dramatically different material properties and multiple physical processes occur simultaneously during cell deformation. Here we utilized both empirical tests and numerical models to capture the failure process of pouch and prismatic cells in various impact scenarios. In each test, a cell was hit once by an indenter dropped from a certain height. During which the cell penetration, loading force, voltage and temperature were monitored to characterize the cell’s response. Meanwhile, numerical models were developed to capture the coupled mechanical, electrical, electrochemical and thermal responses of batteries. In these models, the cell bulk was treated as a homogeneous part to achieve computational efficiency required by large-scale simulations, and it was represented by the geologic cap model that allows both shear and compaction deformation. Simulation results showed agreement with experimental data in essential features of cell behaviors during impact. Details of the test setup, model development and cell failure behaviors are presented in this paper. Additionally, capabilities, limitations and future improvement of the battery safety modeling are discussed.

25 ENERGY STORAGE↗

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗

Programming substructure computations for elliptic problems on the CHiP system

A number of studies have been conducted with the aim to apply parallel computation to problems associated with solving finite element equations arising in structural mechanics and fluid dynamics. These studies have provided many important results. The present investigation is concerned with a set of experiments designed to test two ideas, including configurability and substructuring. The considered algorithms and tests are intended for implementation on the Configurable, Highly Parallel (CHiP) family of architecture described by Snyder (1982). The ChiP computer is composed of homogeneous processing elements (PEs) placed at regular intervals in a lattice of programmable switches. Two examples of the role of configurability and substructuring for simple iterative algorithms are considered, giving attention to conjugate gradient iterations, and tridiagonal systems of equations.

Gannon, D.↗

Direct simulation of particle dispersion in a decaying isotropic turbulence

Results of a numerical investigation of the dispersion of solid particles in decaying isotropic turbulence are presented. The 3D time-dependent velocity field of a homogeneous nonstationary turbulence is computed using the method of direct numerical simulation (DNS). The dispersion characteristics of three different solid particles (corn, copper, and glass) injected in the flow are obtained by integrating the complete equation of particle motion along the instantaneous trajectories of 22-cubed particles for each particle type, and then by performing ensemble averaging. Good agreement was achieved between the present DNS results and the measured time development of the mean-square displacement of the particles. Questions of how and why the dispersion statistics of a solid particle differ from those of its corresponding fluid point and surrounding fluid and what influences inertia and gravity have on these statistics are also discussed.

Elghobashi, S.↗