R. Uppaluri

Multiparameter Estimation in a Transient Conduction-Radiation Problem Using the Lattice Boltzmann Method and the Finite-Volume Method Coupled with the Genetic Algorithms

This article deals with the exploration of the lattice Boltzmann method (LBM) and the finite-volume method (FVM) in conjunction with the genetic algorithms (GA) for estimation of unknown parameters in an inverse transient conduction-radiation problem. The conducting-radiating planar participating medium is absorbing, emitting, and scattering. Its boundaries are diffuse gray. In both the direct and inverse methods, the energy equations are solved using the LBM, and the FVM is employed to compute the radiative information. In the inverse method, the optimization is achieved using the GA. For a given set of parameters, first a direct problem is solved using the LBM-FVM, and temperature fields are estimated at various time levels, which, in the inverse problem, are taken as exact. Effects of measurement errors are also considered. With temperature fields known from the direct method, in the inverse method, too, the LBM-FVM combination is used to solve the energy equation involving volumetric radiation, and the GA is used to optimize the objective function. The LBM-FVM-GA combination in the inverse method has been found to provide correct estimates of the unknown parameters in a transient conduction-radiation heat transfer problem.

Lattice Boltzmann Method Applied to the Analysis of Transient Conduction-Radiation Problems in a Cylindrical Medium

The lattice Boltzmann method (LBM) is applied to solve the energy equation of a transient conduction-radiation heat transfer problem in a 1-D concentric cylindrical participating medium. The finite-volume method (FVM) is used to obtain the radiative information. To study the effectiveness of the LBM-FVM combination to conduction-radiation problems in cylindrical media, the energy equation of the problem is also solved using the finite-difference method (FDM) in which the FVM is used to compute radiative information. The effects of different parameters, such as the conduction-radiation parameter, the scattering albedo, the extinction coefficient, and the radius ratio on temperature distributions in the medium are studied. Results of the present work are benchmarked against those available in the literature. LBM-FVM results are also compared with those obtained by the FDM-FVM combination. In all cases, excellent agreement has been obtained.

Optimization of Heat Fluxes on the Heater and the Design Surfaces of a Radiating-Conducting Medium

In a radiating-conducting planar medium with a boundary as the heater surface using an inverse analysis, this work deals with the design methodologies to understand the inherent relationship between heater surface temperature/flux, design surface temperature/flux, and medium properties. The heat flux on the heater surface is chosen as the fitness function. Subsequently, to achieve maximum and minimum design surface heat fluxes, an optimization was done to evaluate the zone of operation of the heater. In addition, the effect of medium properties on the temperature-flux relationships on both surfaces has been studied. The distance between the two surfaces is also considered a parameter. The medium properties, the distance between the surfaces, and the heater surface temperature have been found to have a great impact on the design surface heat flux. The inverse mixed boundary problem has been solved using the lattice Boltzmann method (LBM), the finite-volume method (FVM), and the genetic algorithm (GA). Results of the present study provide a guideline towards the efficient design of a heater in which conduction and radiation are the dominant modes of heat transfer.

Application of a Particle Swarm Algorithm for Parameter Retrieval in a Transient Conduction-Radiation Problem

This article addresses the application the particle swarm optimization (PSO) algorithm as an optimization tool for retrieval of parameters in a combined mode 1-D transient conduction-radiation heat transfer problem. In the chosen problem, the participating medium is absorbing, emitting, and scattering. The boundaries are taken to be diffuse gray. In both direct and inverse methods, the energy equation is solved using the lattice Boltzmann method (LBM) and the finite volume method (FVM) is used to compute the radiative information. In the inverse method, the objective function is minimized using the PSO algorithm. The objective function considered in the inverse formulation is an error function evaluated with the exact and inverse temperature fields for the simultaneous retrieval of the extinction coefficient and the scattering albedo. The inverse analysis constituted the effect of measurement errors on solution efficacies. In addition, the effect of important PSO parameters such as swarm size, inertia factor and constriction factor on the parameter retrieval is considered. For the chosen problem, it is found that the PSO with 20 discrete particles and 50 iterations is adequate for accurate parameter retrieval. The PSO has been found to provide a better accuracy than the genetic algorithm.

Preparation, characterization, and performance evaluation of LTA zeolite-ceramic composite membrane by separation of BSA from aqueous solution

ABSTRACT Using low-cost clay supports as substrates, ceramic–LTA zeolite composite membranes (Z1–Z4) were fabricated with hydrothermal crystallization. The composite membranes were achieved with variations in the sequential zeolite depositional steps. For Z1–Z4 membranes, various characterization techniques such as thermogravimetric (TG), particle size distribution (PSD), X-ray diffraction (XRD), and field emission scanning electron microscopic (FE-SEM) analysis were applied. For the Z1–Z4 membranes, the pure water permeability, porosity, and average pore size varied from 1.22 × 10−7 to 1.19 × 10−8 m3/m2s kPa, 30–23%, and 215–76 nm, respectively. For the Z4 membrane, ultrafiltration experiments were conducted at a pH of 2.5 and transmembrane pressure differential of 207 kPa using aqueous bovine serum albumin (BSA) solutions. The optimal flux and rejection correspond to 4.54 × 10−7 m3/m2s and 80%, respectively.

Global optimality of RO seawater desalination networks with permeate reprocessing and recycle

ABSTRACT In conjunction with the optimality of single-stage reverse osmosis (SRO) system, this work addresses the economic competence of prominent seawater desalination reverse osmosis systems with permeate reprocessing and recycle using differential evolution as global optimization tool. The optimization approach refers to nonlinear programming formulation consisting of mass balances and design specifications as equality constraints and other design specifications as inequality constraints. Further, MATLAB optimization toolbox-based analysis was conducted to compare the obtained solutions with deterministic optimization methods. Among all considered alternatives such as two stages reverse osmosis (TRO) series arrangement with retentate reprocessing and permeate recycle (TRO-TSRR-PR), SRO, TRO series arrangement with permeate bypass and permeate reprocessing and TRO with permeate reprocessing series arrangement processes, TRO-TSRR-RP process configuration has been evaluated to competitive with the SRO process with an optimal cost of 0.9527

Preparation and characterization of low cost ceramic membranes for micro-filtration applications

/m3 obtained with DE-SQP. While the SRO remains the simplest cost-effective system in terms of topological complexity, the TRO-TSRR-PR process has been evaluated to be 5.75% better than the optimal freshwater production cost of SRO process reported in the literature with an optimal decision variable set values [68.51 bar, 7688, 5881.7 m3/h, 259.8 ppm, 2422, 322.9 m3/h and 1764.9 ppm] for [P1F, NM1, WRORF, C1RP, NM2, W2RP, C2RP].