Simulating Engineering Flows through Complex Porous Media via the Lattice Boltzmann Method

Adapting to the Abyss: Passive Ventilation in the Deep-Sea Glass Sponge Euplectella aspergillum

We analyze the flow physics inside the body cavity and downstream the deep-sea glass sponge Euplectella aspergillum. We provide evidence that the helical skeletal motifs of the sponge give rise to a rich fluid dynamic field, allowing the organism to scavenge flow from the bottom of the sea and promoting a spontaneous, organized vertical flow within its body cavity toward the osculum. Our analysis points at a functional adaptation of the organism, which can passively divert flow through the osculum in unfavorable, low ambient currents, with no need for active pumping, with potential repercussions in functional ecology, as well as the design of chemical reactors, air-treatment units, and civil and aeronaval structures.

Study on Interparticle Interaction Force Model to Correct Saturation Density of Real Cryogenic Fluid for LBM Simulation

Cryogenic liquefaction energy storage is an important form of storage for sustainable energy liquid hydrogen and other gases. The weighting parameter A in the parameter-adjusted two-phase LBM model is important for the deviation of simulation results. The aim of this paper is to discover the appropriate parameter to eliminate the deviation, and to solve the problem of large deviation between the theoretical solution and the simulated value that is caused by using different equations of state in LBM simulation. The modified PT equation of state, which is suitable for cryogenic fluids, is combined with the parameter-adjustable two-phase model to simulate the saturation density at different temperatures. Four typical cryogenic fluids—nitrogen, hydrogen, oxygen, and helium—are exploratively simulated to find the suitable parameters to eliminate errors by analyzing the results with theoretical solutions. This is an efficient solution to the deviation between the simulated value and the theoretical solutions, which is caused by the different equation of state in LBM. The optimal A-value of the model based on the PT equation of state was obtained as −0.21, while droplets and bubbles were set into the calculation region, and an inverse relationship between the interface density gradient and temperature was analyzed. The analysis and comparison of the simulation results under the optimal value and the experimental values have laid an important foundation for the phase change simulation of the real cryogenic fluids at the mesoscopic scale.

A scalable model of fluid flow, substrate removal and current production in microbial fuel cells

Mathematical modelling can reduce the cost and time required to design complex systems, and is being increasingly used in microbial electrochemical technologies (METs). To be of value such models must be complex enough to reproduce important behaviour of MET, yet simple enough to provide insight into underlying causes of this behaviour. Ideally, models must also be scalable to future industrial applications, rather than limited to describing existing laboratory experiments. We present a scalable model for simulating both fluid flow and bioelectrochemical processes in microbial fuel cells (MFCs), benchmarking against an experimental pilot-scale bioreactor. The model describes substrate transport through a two-dimensional fluid domain, and biofilm growth on anode surfaces. Electron transfer is achieved by an intracellular redox mediator. We find significant spatial variations in both substrate concentration and current density. Simple changes to the reactor layout can greatly improve the overall efficiency, measured in terms of substrate removal and total current generated.

Pore-Scale Investigation on Natural Convection Melting in a Square Cavity with Gradient Porous Media

In this paper, natural convection melting in a square cavity with gradient porous media is numerically studied at pore-scale level by adopting the lattice Boltzmann method. To generate the gradient porous media, a Monte Carlo technique based on the random sampling principle is used. The effects of several factors, such as Rayleigh number, gradient porosity structure, gradient direction, and particle diameters on natural convection melting are investigated in detail. Based on the numerical data, it is observed that the thermal performance of the gradient porous media always depends on the Rayleigh number and, specifically, as the Rayleigh number is set to 106, the total melting time obtained for the case of the negative gradient porous media is always shorter than the cases of positive gradient and uniform porous media. However, if the Rayleigh number is equal to 104, at which the heat transfer is dominated by the heat conduction, it is noted that the performance of the positive gradient porous media is better than the other cases. To have a better understand on this point, various simulations are also performed and we found that there usually exists a critical value of Rayleigh number to determine the thermal performance of the gradient porous media. Moreover, our numerical results also show that the influence of the particle diameter on the liquid fraction is insignificant as Rayleigh number is set to 104, while it has a great impact on the liquid fraction when Rayleigh number equals 106.

Optimized Modeling and Design of a PCM-Enhanced H2 Storage

Thermal and mechanical energy storage is pivotal for the effective exploitation of renewable energy sources, thus fostering the transition to a sustainable economy. Hydrogen-based systems are among the most promising solutions for electrical energy storage. However, several technical and economic barriers (e.g., high costs, low energy and power density, advanced material requirements) still hinder the diffusion of such solutions. Similarly, the realization of latent heat storages through phase change materials is particularly attractive because it provides high energy density in addition to allowing for the storage of the heat of fusion at a (nearly) constant temperature. In this paper, we posit the challenge to couple a metal hydride H2 canister with a latent heat storage, in order to improve the overall power density and realize a passive control of the system temperature. A highly flexible numerical solver based on a hybrid Lattice Boltzmann Phase-Field (LB-PF) algorithm is developed to assist the design of the hybrid PCM-MH tank by studying the melting and solidification processes of paraffin-like materials. The present approach is used to model the storage of the heat released by the hydride during the H2 loading process in a phase change material (PCM). The results in terms of Nusselt numbers are used to design an enhanced metal-hydride storage for H2-based energy systems, relevant for a reliable and cost-effective “Hydrogen Economy”. The application of the developed numerical model to the case study demonstrates the feasibility of the posited design. Specifically, the phase change material application significantly increases the heat flux at the metal hydride surface, thus improving the overall system power density.

Long-term operation of bio-catalyzed cathodes within continuous flow membrane-less microbial fuel cells

Microorganisms were observed to facilitate cathodic oxygen reduction and enhance cathode performance of microbial fuel cells (MFCs). However, the long-term activity and stability of bio-catalyzed cathode needs to be explored. This study evaluated the long-term performance of bio-catalyzed cathode and iron(II) phthalocyanine (FePc)-catalyzed cathode MFCs through effluent water quality, electricity production and electrochemical impedance spectroscopy (EIS) analysis under different scenarios, including conventional wastewater treatment and energy harvesting using a power management system (PMS). During the continuous operation, both systems demonstrated high chemical oxygen demand and ammonium removal, but bio-catalyzed cathode MFCs could achieve significantly better total nitrogen removal than FePc-catalyzed cathode MFCs. The FePc-coated cathode showed constant cathode potential during the entire operation period, but the biocathode showed varied but step-wise increased cathode potential to achieve more than 500 mV versus the standard hydrogen electrode, likely due to the gradual enrichment of biocathode biofilm. EIS analysis revealed that biocathode had higher ohmic resistance than bare carbon felt cathode but the microbial biofilm could largely decrease polarization resistance of cathode material. Microbial community analysis has shown the presence of nitrifying and denitrifying bacteria in the bio-catalyzed cathode biofilm. When connecting PMS, both bio-catalyzed cathode and FePc-catalyzed cathode MFCs successfully charged a capacitor, but the bio-catalyzed cathode MFC voltage significantly dropped to less than 100 mV after charging for 91 h, and gradually recovered when disconnecting PMS. This study has demonstrated the potential application of oxygen reduction bio-catalyzed cathode MFCs for continuous wastewater treatment and energy harvesting for long period of time.

Modeling and optimization strategies towards performance enhancement of microbial fuel cells

Considering the complexity associated with bioelectrochemical processes, the performance of a microbial fuel cell (MFC) is governed by input operating parameters. For scaled-up applications, a MFC system needs to be modeled from engineering perspectives in terms of optimum operating conditions to get higher performance and energy recovery. Several conceptual numerical models to advanced computational simulation approaches have been developed to represent simple-form of a complex MFC system. Application of mathematical and computation models are explored to establish the relationship between operating input-variables and power output. The present review discusses about the complexity of system, modeling strategies used and reality of such modeling for scaling-up applications of MFCs. Additionally, the selection of an appropriate mathematical model reduces the computational duration and provides better understanding of the system process. It also explores the possibility and progress towards commercialization of MFCs and thus the need of development of model-based optimization and process-control approaches.

Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach

Microbial fuel cells (MFCs) is a promising technology that is able to simultaneously produce bioenergy and treat wastewater. Their potential large-scale application is still limited by the need of optimising their power density. The aim of this study is to simulate the absolute power output by ceramic-based MFCs fed with human urine by using a fuzzy inference system in order to maximise the energy harvesting. For this purpose, membrane thickness, anode area and external resistance, were varied by running a 27-parameter combination in triplicate with a total number of 81 assays performed. Performance indices such as R² and variance account for (VAF) were employed in order to compare the accuracy of the fuzzy inference system designed with that obtained by using nonlinear multivariable regression. R² and VAF were calculated as 94.85% and 94.41% for the fuzzy inference system and 79.72% and 65.19% for the nonlinear multivariable regression model, respectively. As a result, these indices revealed that the prediction of the absolute power output by ceramic-based MFCs of the fuzzy-based systems is more reliable than the nonlinear multivariable regression approach. The analysis of the response surface obtained by the fuzzy inference system determines that the maximum absolute power output by the air-breathing set-up studied is 450  μ W when the anode area ranged from 160 to 200 cm², the external loading is approximately 900 Ω and a membrane thickness of 1.6 mm, taking into account that the results also confirm that the latter parameter does not show a significant effect on the power output in the range of values studied.

On the effects of surface corrugation on the hydrodynamic performance of cylindrical rigid structures

In this work, we perform fully three-dimensional numerical simulations of the flow field surrounding cylindrical structures characterized by different types of corrugated surface. The simulations are carried out using the Lattice Boltzmann Method (LBM), considering a flow regime with a Reynolds number [Formula: see text]. The fluid-dynamic wake structure and stability are investigated by means of PSD analyses of the velocity components and by visual inspection of the vortical coherent structure evolution. Moreover, the energy dissipation of the flow is assessed by considering an equivalent discharge coefficient [Formula: see text], which measures the total pressure losses of the flow moving around the various layout under investigation. Outcomes from our study demonstrate that the helical ridges augment energy dissipation, but might also have a role in the passive control of the characteristic frequencies of the unsteady wake flow.

Statistics of Heat Transfer in Two-Dimensional Turbulent Rayleigh-Bénard Convection at Various Prandtl Number

Statistics of heat transfer in two-dimensional (2D) turbulent Rayleigh-Bénard (RB) convection for Pr=6,20,100 and 106 are investigated using the lattice Boltzmann method (LBM). Our results reveal that the large scale circulation is gradually broken up into small scale structures plumes with the increase of Pr, the large scale circulation disappears with increasing Pr, and a great deal of smaller thermal plumes vertically rise and fall from the bottom to top walls. It is further indicated that vertical motion of various plumes gradually plays main role with increasing Pr. In addition, our analysis also shows that the thermal dissipation is distributed mainly in the position of high temperature gradient, the thermal dissipation rate εθ already increasingly plays a dominant position in the thermal transport, εu can have no effect with increase of Pr. The kinematic viscosity dissipation rate and the thermal dissipation rate gradually decrease with increasing Pr. The energy spectrum significantly decreases with the increase of Pr. A scope of linear scaling arises in the second order velocity structure functions, the temperature structure function and mixed structure function(temperature-velocity). The value of linear scaling and the 2nd-order velocity decrease with increasing Pr, which is qualitatively consistent with the theoretical predictions.