Investigation on hydrodynamics and mass transfer in a feed channel of a spiral-wound membrane element using response surface methodology

Sensitivity analysis of natural convection in a porous cavity filled with nanofluid and equipped with horizontal fins using various optimization methods and MRT-LB

In the present study, natural convection heat transfer is investigated in a porous cavity filled with Cu/water nanofluid and equipped with horizontal fins. Optimization and sensitivity analysis of the fin's geometry, porous medium and nanofluid properties to maximize heat transfer rate is the aim of this work. To achieve this purpose, a design space is created by input parameters which include length, number of fins, distance between fins, porosity, Darcy number and volumetric fraction of the nanoparticles. Several tools have been used to implement optimization methods including the Taguchi method (TM) for design points generation, sensitivity analysis of design variables by using signal-to-noise ratio (SNR) and analysis of variance (ANOVA), response surface method (RSM) for interpolation and regression by using nonparametric regression, and genetic algorithm (GA) for finding optimum design point. The double multi-relaxation time lattice Boltzmann method (MRT-LBM) is used to analyze and simulate the flow field and heat transfer in each design point. The results show that the optimal configuration leads to an average Nusselt number of 5.56. This optimal configuration is at the length of fins L/2, the number of fins 2, the distance between fins L/12, porosity 0.8, Darcy number 0.1, and the volumetric fraction of the nanoparticles 0.02. By using the SNR results, the Darcy number and the number of fins have the most and the least effect in maximizing the average Nusselt number, respectively. The ANOVA results and global sensitivity analysis (GSA) findings further validated this conclusion.

Numerical Simulations of Calcium Sulphate Scaling in Full-Scale Brackish Water Reverse Osmosis Pressure Vessels Using Computational Fluid Dynamics

Coal mine waters often have high salinity, hardness and alkalinity. The treatment of coal mine water requires careful management of multi-stage reverse osmosis (RO) systems to achieve effective recovery of water for domestic reuse, as well as zero liquid discharge to minimise the impact to the local environment. Design of RO systems for coal mine water treatment has been limited to the use of commercial design packages provided by membrane manufacturers, which do not provide insights into the impact of operating parameters such as feedwater salinity, concentrations of sparingly soluble salts, feed pressure and their interactions with different RO modules on the fouling/scaling potential of RO membranes. This also restricts the use of novel RO products and the delivery of an optimum design based on real needs. In this work, a mathematical model was developed to simulate a standard brackish water RO pressure vessel consisting six full-size RO membrane elements, using computational fluid dynamics (CFD). The model can be used to predict the permeate flowrate, water recovery levels, as well as the spatial information of the accumulation and scaling potential of sparingly soluble salts on the membrane surface. The results obtained from the model showed good agreement with the results obtained from the commercial RO design software WAVE. The CFD model was then used to predict the scaling threshold on various positions of a full-scale RO element, at different operating conditions, using parametric simulations based on Central Composite Designs. Outputs from this work not only provide insights into the microscopic flow characteristics of multiple full-scale elements in the RO pressure vessel, but also predicts the position where scaling would occur, at different feed conditions, for any RO products.

Roles and performance enhancement of feed spacer in spiral wound membrane modules for water treatment: A 20-year review on research evolvement

Membrane technologies have been widely applied in water treatment, wastewater reclamation and seawater desalination. Feed spacer present in spiral wound membrane (SWM) modules plays a pivotal role in creating flow channels, promoting fluid mixing and enhancing mass transfer. However, it induces the increase of feed channel pressure (FCP) drop and localized stagnant zones that provokes membrane fouling. For the first time, we comprehensively review the research evolvement on feed spacer in SWM modules for water treatment over the last 20 years, to reveal the impacts of feed spacer on the hydrodynamics and biofouling in the spacer-filled channel, and to discuss the potential approaches and current limitations for the modification of feed spacer. The research process can be divided into three phases, with research focus shifting from hydrodynamics in Phase Ⅰ (the year of 2001-2008), to biofouling in Phase Ⅱ (the year of 2009-2015), and then to novel spacer designs in Phase Ⅲ (the year of 2016-2020). The spacer configuration has a momentous impact on the hydraulic performance regarding flow velocity field, shear stress, mass transfer and FCP drop. Biofouling initially occurs on feed spacer, especially around spacer filaments and the contact zones with membrane surface, and ultimately degrades the overall membrane performance indicating the importance of controlling spacer biofouling. The modification of feed spacer is mainly achieved by altering surface chemistry or introducing novel configurations. However, the stability of spacer coating and the economy and practicality of 3D-printed spacer remain a predicament to be tackled. Future studies are suggested to focus on the standardization of testing conditions for spacer evaluation, the effect of hydrodynamics on membrane fouling control, the design and fabrication of novel feed spacer adaptable for SWM modules, the application of feed spacer for drinking water production, organic fouling control in spacer-filled channel and the role of permeate spacer on membrane performance.

Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

A Review of CFD Modelling and Performance Metrics for Osmotic Membrane Processes

Simulation via Computational Fluid Dynamics (CFD) offers a convenient way for visualising hydrodynamics and mass transport in spacer-filled membrane channels, facilitating further developments in spiral wound membrane (SWM) modules for desalination processes. This paper provides a review on the use of CFD modelling for the development of novel spacers used in the SWM modules for three types of osmotic membrane processes: reverse osmosis (RO), forward osmosis (FO) and pressure retarded osmosis (PRO). Currently, the modelling of mass transfer and fouling for complex spacer geometries is still limited. Compared with RO, CFD modelling for PRO is very rare owing to the relative infancy of this osmotically driven membrane process. Despite the rising popularity of multi-scale modelling of osmotic membrane processes, CFD can only be used for predicting process performance in the absence of fouling. This paper also reviews the most common metrics used for evaluating membrane module performance at the small and large scales.

Optimization of an External Gear Pump using Response Surface Method

Design of a new gear pump requires many considerations to get good pump efficiency. In order to achieve optimal results, all parameters must be optimized from the design stage. In this study, ANSYS CFX was used to make parametric analysis in order to optimize a new design of gear pump. Two parameters which are inlet diameter and rotation speed are considered. The response surface method gives an optimum design point for inlet diameter of 15mm and rotation speed of 3500 rev/min. Twin vortices are created in the inlet and the outlet of pump, which strangle the flow. In order to reduce their negative effects on the flow, fillets are created at the inlet and the outlet of the pump.