50 Search Results

Context. Small-scale challenges to ΛCDM cosmology require a deeper understanding of dark matter physics. Aims. This paper aims to develop the maximum entropy distributions for dark matter particle velocity (denoted by X ), speed (denoted by Z ), and energy (denoted by E ) that are especially relevant on small scales where system approaches full virialization. Methods. For systems involving long-range interactions, a spectrum of halos of different sizes is required to form to maximize system entropy. While the velocity in halos can be Gaussian, the velocity distribution throughout the entire system, involving all halos of different sizes, is non-Gaussian.more » With the virial theorem for mechanical equilibrium, we applied the maximum entropy principle to the statistical equilibrium of entire system, such that the maximum entropy distribution of velocity (the X distribution) could be analytically derived. The halo mass function was not required in this formulation, but it did indeed result from the maximum entropy. Results. The predicted X distribution involves a shape parameter α and a velocity scale, v ₀ . The shape parameter α reflects the nature of force ( α  → 0 for long-range force or α  → ∞ for short-range force). Therefore, the distribution approaches Laplacian with α  → 0 and Gaussian with α  → ∞. For an intermediate value of α , the distribution naturally exhibits a Gaussian core for v  ≪  v ₀ and exponential wings for v  ≫  v ₀ , as confirmed by N -body simulations. From this distribution, the mean particle energy of all dark matter particles with a given speed, v , follows a parabolic scaling for low speeds (∝ v ² for v  ≪  v ₀ in halo core region, i.e., “Newtonian”) and a linear scaling for high speeds (∝ v for v  ≫  v ₀ in halo outskirt, i.e., exhibiting “non-Newtonian” behavior due to long-range gravity). We compared our results against N -body simulations and found a good agreement.« less

Abstract Polyolefin separators are the most common separators used in rechargeable lithium (Li)‐ion batteries. However, the influence of different polyolefin separators on the performance of Li metal batteries (LMBs) has not been well studied. By performing particle injection simulations on the reconstructed three‐dimensional pores of different polyethylene separators, it is revealed that the pore structure of the separator has a significant impact on the ion flux distribution, the Li deposition behavior, and consequently, the cycle life of LMBs. It is also discovered that the homogeneity factor of Li‐ion toward Li metal electrode is positively correlated to the longevity and reproducibility ofmore » LMBs. This work not only emphasizes the importance of the pore structure of polyolefin separators but also provides an economic and effective method to screen favorable separators for LMBs.« less

Dark matter, if it exists, accounts for five times as much as the ordinary baryonic matter. Compared to hydrodynamic turbulence, the flow of dark matter might possess the widest presence in our universe. This paper presents a statistical theory for the flow of dark matter that is compared with N-body simulations. By contrast to hydrodynamics of normal fluids, dark matter flow is self-gravitating, long-range, and collisionless with a scale-dependent flow behavior. The peculiar velocity field is of constant divergence nature on small scale and irrotational on large scale. The statistical measures, i.e., correlation, structure, dispersion, and spectrum functions, are modeledmore » on both small and large scales, respectively. Kinematic relations between statistical measures are fully developed for incompressible, constant divergence, and irrotational flow. Incompressible and constant divergence flow share the same kinematic relations for even order correlations. The limiting correlation of velocity $$\mathrm{ρ_{L}=1/2}$$ on the smallest scale (r = 0) is a unique feature of collisionless flow (⁠$$\mathrm{ρ_{L}=1}$$ for incompressible flow). On large scale, transverse velocity correlation has an exponential form $$T_{2}∝e^{–r/r_2}$$ with a constant comoving scale r₂=21.3 Mpc/h that may be related to the horizon size at matter–radiation equality. All other correlation, structure, dispersion, and spectrum functions for velocity, density, and potential fields are derived analytically from kinematic relations for irrotational flow. On small scale, longitudinal structure function follows one-fourth law of $${S}_{2}^{1}∝r^{1/4}$$. All other statistical measures can be obtained from kinematic relations for constant divergence flow. Vorticity is negatively correlated for scale r between 1 and 7 Mpc/h. Divergence is negatively correlated for r > 30 Mpc/h that leads to a negative density correlation.« less

Developing an accurate and efficient model for cross-over is critical for improving the long-term performance of redox flow batteries (RFBs). Here, this work presents a hybrid analytical and numerical model that combines a two-dimensional analytical solution to the active species, a one-dimensional analytical model for cross-over mechanisms, and a zero-dimensional numerical model for outlet concentrations of reactants. By comparing with experiment over 41 cycles (ca. 144 h), the model reported a mean voltage difference of 0.0089 V, mean time difference of 14 s per cycle (of 3.5 h), maximum relative difference for capacity and energy of 1.34% and 1.63%, respectively.more » The predicted mean concentrations for V²⁺, V³⁺, and VO$$_{2}^{+}$$ in membrane are 65%~77% of measured values from the literature. Upon validation, the model reproduced behaviors in electrolyte imbalance similar to those observed in experiments and numerical models, and revealed the control of cross-over, self-discharge, stoichiometry of side reactions, and Coulombic efficiency on electrolyte imbalance. The model also demonstrates excellent computational efficiency for simulating 41 cycles (around 37,000 points) within 3~4 s. The demonstrated efficiency and accuracy for predicting cross-over and its impacts on voltage, capacity&energy decay, membrane concentrations, and electrolyte imbalance makes it a reliable tool for optimizing RFBs’ long-term performance.« less

CO2 Capture CFD (C3FD) dataset contains STAR-CCM+ simulations of a CO2-capturing solvent flowing across packing structures in a column. This dataset contains 50 2D and 50 3D simulations, each of which spans 500 timesteps. The 2D and 3D simulation meshes have 150,073 and 3,129,815 nodes, respectively. Each node contains information about its physical location, liquid volume fraction, momentum, and node type.

In this work, a previously validated coupling of Kinetic Monte Carlo (KMC) Potts Model and finite element method (FEM) simulations was implemented to investigate the effects of microstructural features in as-cast and homogenized monolithic U-10Mo foils on the emergent microstructure after rolling and reheating. Parameters that could potentially affect recrystallization behavior of the rolled U-10Mo foils were considered: grain size distribution, uranium carbide (UC) size distribution, UC volume fraction, spatial distribution of UC, and rolling reduction magnitude. Grain structure and the magnitude of rolling reduction have the strongest influence on recrystallization kinetics and the fabricated grain size distribution. The UCmore » distribution had only a weak effect on the recrystallization kinetics and final microstructures. While particle-stimulated nucleation (PSN) occurred in simulation more frequently as grain size increased, its incidence did not appear to considerably affect the recrystallization kinetics or grain size distribution.« less

Use of aqueous redox flow batteries with organic redox-active materials holds great promise for large-scale and sustainable energy storage. The development of low-cost, highly efficient aqueous redox flow batteries lies in a comprehensive understanding of the electrochemical behaviors of redox-active compounds. In this work, an alkaline redox battery with organic dihydroxyphenazine sulfonate (DHPS) anolyte and ferro-/ferricyanide (Fe(CN)₆) catholyte is investigated as a typical example of aqueous redox flow batteries using organic redox-active materials. The electrochemical kinetics of DHPS and Fe(CN)₆ are separately characterized using the symmetrical cell design. The resistance components are calculated directly from the experimental measurement. The keymore » kinetic parameters are extracted and compared for DHPS and Fe(CN)₆ electrolytes. The extracted parameters are validated with symmetrical and full flow cell simulations at different operating conditions. Key parameters and internal loss are also compared with all-vanadium redox flow batteries, representing current state of the art. In addition, our extracted key parameters from a symmetrical flow cell are compared with the measured key parameters by cyclic voltammetry, a widely deployed electroanalytical technique. The cell performance prediction of DHPS anolyte on a 780 cm² interdigitated cell is made and found the power density is peaked at 475 mW cm^-2 at our measurement condition.« less

A three-dimensional (3-D) pore-scale model has been developed to construct multiscale fibrous electrodes for redox flow batteries (RFB). New designs, such as biporous electrodes modify electrode structures by creating secondary pores on single carbon fiber to reduce internal battery resistance. Existing pore-scale models only resolve electrodes to the single carbon fiber scale and cannot incorporate recent multiscale electrode designs into numerical models. Our new model aims to bridge this gap and provide a tool to rapidly screen new electrode configurations. Two multiscale electrodes, laser-perforated and biporous electrodes, were investigated at varying operation conditions with the proposed 3-D pore-scale models. Themore » laser-perforated electrode exhibits a reduced pressure drop, but follows the same permeability correlation compared to the corresponding pristine electrode. For the biporous electrode, the added specific surface area and faster reaction kinetics from the secondary pores are the most influential factors leading to improved battery efficiency. However, operating the biporous electrode in limiting current density conditions should be avoided due to the decreased mass transfer efficiency and a more significant voltage loss. Finally, we believe that our 3-D pore-scale model can accelerate the flow battery electrode design process and provide new insights into electrode geometry optimizations.« less

The CO2 capture efficiency in solvent-based carbon capture systems (CCSs) critically depends on the gas-solvent interfacial area (IA), making maximization of IA a foundational challenge in CCS design. While the IA associated with a particular CCS design can be estimated via a computational fluid dynamics (CFD) simulation, using CFD to derive the IAs associated with numerous CCS designs is prohibitively costly. However, previous works such as Deep Fluids (Kim et al., 2019) show that large simulation speed-ups and low error are achievable by replacing CFD simulators with neural-network (NN) surrogates that mimic the CFD simulation process. This raises the possibilitymore » for a fast, accurate replacement for a CFD simulator, and thus computationally feasible IA-based CCS-design optimization. As such, here, we explore whether an existing NN-surrogate approach (and variants we develop) can successfully be applied to our complex carbon-capture CFD simulations, with the ultimate goal of obtaining a fast and accurate simulator for our CCS-design application. Our experiments build on the Deep Fluids approach and find that resulting surrogates can produce large speed ups (4000x) while maintaining IA relative errors as low as 4% on unseen CCS configurations (interpolating between configurations seen during training). Thus, despite less faithfulness to the underlying physics of the problem, NN surrogates may be a promising tool for our CCS design optimization problem. Notably, though, the Deep Fluids approach has limitations for our application (such as model non-transferability to CCS-packing changes), which we discuss. We conclude with potential directions for future work that may, like innovations we introduced here (e.g., transformer-based dynamics prediction), improve performance on our complicated dataset of CCS CFD simulations.« less

Effective mass-transfer area plays a key role for post-combustion carbon capture. The static area, an inactive part relative to mass transfer, needs to be differentiated in the interfacial area. In the present study, CFD method is employed to investigate static and dynamic interfacial areas in Mellapak 500.Y structured packing. Here, a wide range of physical properties and loading conditions are included to understand their effects on both areas. The result shows that the relationship between interfacial area and interfacial velocity at the local scale can be described by gamma distribution with good accuracy. The influences of various physical properties derivedmore » from simulation are compared with existing experiment-based correlations for both static and interfacial areas. The result shows the dominant influence of viscosity on the static area, and the most importance of the influence of contact angle on the interfacial area. This study also highlights the importance of viscosity, which is usually ignored.« less