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Yinuo Noah Yao

Publications and source records attributed to Yinuo Noah Yao.

4 recordsLinked to original sources

Reynolds-number-dependent entrance bias in temperature polarization of lab-scale membrane distillation

Lab-scale membrane distillation (MD) modules are commonly used for membrane characterization and developing empirical heat-transfer correlations. Entrance-induced flow structures can introduce geometry-specific effects into measured temperature polarization (TP) and heat transfer. However, the dependence of these effects on module geometry and flow condition remains unclear. We performed three-dimensional computational fluid dynamics (CFD) simulations of direct contact membrane distillation (DCMD) over inlet Reynolds numbers of $\Re_{\mathrm{in}}=10$-$1000$, focusing on side-chamber length and main-channel height. We discovered that counter-rotating streamwise vortices formed near the main-channel entrance across all geometries, but their downstream persistence increased with $\Re_{\mathrm{in}}$. At lower $\Re_{\mathrm{in}}$, the vortices mostly decayed before mid-channel, while at higher $\Re_{\mathrm{in}}$ they persisted farther downstream and produced pronounced spatial variations in TP. Increasing side-chamber length reduced the secondary-flow kinetic energy entering the main channel, and generally strengthened TP, whereas increasing main-channel height reduced the bulk velocity and streamwise kinetic energy, resulting in a thicker thermal boundary layer and stronger TP. For most geometries, the deviation from the straight-channel baseline changed from stronger TP at lower $\Re_{\mathrm{in}}$ to weaker TP at higher $\Re_{\mathrm{in}}$. Entrance effects therefore vary in both magnitude and direction with operating condition and cannot be represented by a constant correction across the Reynolds-number range.

physics.flu-dyn↗

A conservative micro-continuum-cellular automaton method for multispecies biofilm dynamics in complex flows

We develop a conservative micro-continuum-cellular automaton method for simulating multispecies biofilm dynamics in complex flows. The proposed method couples the Darcy-Brinkman-Stokes equations, reactive transport, suspended bacteria, and biofilm dynamics with a two-stage cellular automaton algorithm for biofilm redistribution and interface evolution. While treating biofilms as evolving porous media, we ensure conservative redistribution of multispecies biomass across partially occupied cells. Donor and recipient cell volumes are explicitly accounted for to conserve biomass and preserve species composition on non-uniform meshes. The proposed method is assessed against diffusion-dominated benchmark cases, including single-species fingering and multispecies stratification, and is further evaluated through a mesh-convergence study for flow and growth over a rectangular bump. The framework is then applied to counter-diffusional biofilms in a membrane-aerated biofilm reactor as a canonical example. The results demonstrate that the framework captures the expected biofilm morphology and stratification in systems involving coupled flow, substrate transport, and biofilm dynamics. The proposed method provides a flexible computational approach for simulating multispecies biofilm dynamics in complex flows and geometries.

physics.flu-dyn↗

Non-intrusive Auto-detecting and Adaptive Hybrid Scheme for Multiscale Heat Transfer: Thermal Runaway in a Battery Pack

Accurately capturing and simulating multiscale systems is a formidable challenge, as both spatial and temporal scales can span many orders of magnitude. Rigorous upscaling methods not only ensure efficient computation, but also maintains errors within a priori prescribed limits. This provides a balance between computational costs and accuracy. However, the most significant difficulties arise when the conditions under which upscaled models can be applied cease to hold. To address this, we develop an automatic-detecting and adaptive, nonintrusive two-sided hybrid method for multiscale heat transfer and apply it to thermal runaway in a battery pack. To allow adaptive hybrid simulations, two kernels are developed to dynamically map the values between the fine-scale and the upscaled subdomains in a single simulation. The accuracy of the developed hybrid method is demonstrated through conducting a series of thermal runaway test cases in a battery pack. Our results show that the maximum spatial errors consistently remain below the threshold bounded by upscaling errors.

physics.comp-ph↗

Non-intrusive Hybrid Scheme for Multiscale Heat Transfer: Thermal Runaway in a Battery Pack

Accurate analytical and numerical modeling of multiscale systems is a daunting task. The need to properly resolve spatial and temporal scales spanning multiple orders of magnitude pushes the limits of both our theoretical models as well as our computational capabilities. Rigorous upscaling techniques enable efficient computation while bounding/tracking errors and helping to make informed cost-accuracy tradeoffs. The biggest challenges arise when the applicability conditions of upscaled models break down. Here, we present a non-intrusive two-way (iterative bottom-up top-down) coupled hybrid model, applied to thermal runaway in battery packs, that combines fine-scale and upscaled equations in the same numerical simulation to achieve predictive accuracy while limiting computational costs. First, we develop two methods with different orders of accuracy to enforce continuity at the coupling boundary. Then, we derive weak (i.e., variational) formulations of the fine-scale and upscaled governing equations for finite element (FE) discretization and numerical implementation in FEniCS. We demonstrate that hybrid simulations can accurately predict the average temperature fields within error bounds determined a priori by homogenization theory. Finally, we demonstrate the computational efficiency of the hybrid algorithm against fine-scale simulations.

math.NA↗