Santanu De

Simulation of laminar flow in a three-dimensional lid-driven cavity by lattice Boltzmann method

Purpose - The purpose of this paper is to apply lattice Boltzmann equation method (LBM) with multiple relaxation time (MRT) model, to investigate lid-driven flow in a three-dimensional (3D), rectangular cavity, and compare the results with flow in an equivalent two-dimensional (2D) cavity. Design/methodology/approach - The second-order MRT model is implemented in a 3D LBM code. The flow structure in cavities of different aspect ratios (0.25-4) and Reynolds numbers (0.01-1000) is investigated. The LBM simulation results are compared with those from numerical solution of Navier-Stokes (NS) equations and with available experimental data. Findings - The 3D simulations demonstrate that 2D models may predict the flow structure reasonably well at low Reynolds numbers, but significant differences with experimental data appear at high Reynolds numbers. Such discrepancy between 2D and 3D results are attributed to the effect of boundary layers near the side-walls in transverse direction (in 3D), due to which the vorticity in the core-region is weakened in general. Secondly, owing to the vortex stretching effect present in 3D flow, the vorticity in the transverse plane intensifies whereas that in the lateral plane decays, with increase in Reynolds number. However, on the symmetry-plane, the flow structure variation with respect to cavity aspect ratio is found to be qualitatively consistent with results of 2D simulations. Secondary flow vortices whose axis is in the direction of the lid-motion are observed; these are weak at low. Reynolds numbers, but become quite strong at high Reynolds numbers. Originality/value - The findings will be useful in the study of variety of enclosed fluid flows.

The effect of timescale variation in multiple mapping conditioning mixing of PDF calculations for Sandia Flame series D–F

A stochastic implementation of the multiple mapping conditioning (MMC) model has been used for the modelling of turbulence–chemistry interactions in a series of turbulent jet diffusion flames with varying degrees of local extinction (Sandia Flames D–F). The mapping function approximates the cumulative probability distribution of mixture fraction and the corresponding variance can be controlled by a standard implementation of the scalar mixing timescale. The conditional fluctuations are controlled by a minor dissipation timescale, τmin. The results show a clear dependence of the conditional fluctuations on the choice of the minor timescale, and the appropriate value for turbulent jet flames is similar to values determined in related direct numerical simulation (DNS) studies of homogeneous turbulent reacting flows. The predictions of means and variances of temperature and species mass fractions are very good for all flames, indicating an appropriate modelling of the conditional variances. Further sensitivity studies with respect to particle number density demonstrate a relative insensitivity of the results to the particle number in the numerical solution procedure. Good results can be obtained with as few as 10 particles per cell, allowing for a computationally inexpensive implementation of a Monte Carlo/probability density function (PDF) method.

Simulations of evaporating spray jet in a uniform co-flowing turbulent air stream

Numerical simulations are performed on the flow of fine, polydisperse droplets of acetone ejected from a round jet of air into an ambient turbulent, uniform co-flowing air stream. The objective is to validate the numerical model by comparing the predictions with experimental measurements of a well defined evaporating spray configuration (Chen et al., Int. J. Multiphase Flow 32(2006), 389–412). The carrier-phase is considered in the Eulerian context, while the dispersed phase is tracked in the Lagrangian framework. Various interactions between the two phases are taken into account by means of a two-way coupling. The stochastic separated flow (SSF) model is adopted for the spray calculations. The gas-phase turbulence terms are closed using the standard k-ε model. The spray evaporation is described using a thermal model with an infinite-conductivity. Overall, very good agreement is observed in the comparisons of the computational predictions and experimental measurements. The predicted droplet number-mean axial velocity, r.m.s. of fluctuating velocity for the various droplet classes at different downstream locations exhibit a self-similarity downstream of the nozzle exit. Near the nozzle-exit (around z/djet = 5), the r.m.s. of droplet number mean axial fluctuating velocity attains a maximum within the shear layer near r/djet = 0.4–0.6 for different droplet classes. Further downstream, the peak shifts towards the axis. A similar variation is noticed in the Sauter mean diameter (SMD) distribution of the droplets. It is concluded that, a higher level of turbulence leads to a faster depletion of the smaller droplets, resulting in an increase in the local droplet-SMD in those regions.

Gasifiers: Types, Operational Principles, and Commercial Forms

Carbonaceous solid materials are converted into gaseous fuel through the gasification process. A limited supply of steam, air, oxygen, or a combination of these serves as gasifying agent. Depending upon the gasifying agent used, the fuel gas will contain mainly hydrogen, carbon monoxide, carbon dioxide, methane, higher hydrocarbons, and nitrogen (if air is used). In gasification, different technologies are used depending upon the requirement. Technologies used for gasification can broadly be classified into four groups; fixed bed or moving bed gasification, fluidized bed gasification, entrained bed gasification, and plasma gasification. In the present chapter, a detail discussion on the design, working principle, merits and demerits of different types of gasifiers are presented. Some of the important commercial gasifiers installed worldwide are also discussed.

Theory and Application of Multiple Mapping Conditioning for Turbulent Reactive Flows

This chapter presents the basic theory and conceptual evolution of the multiple mapping conditioning (MMC) framework, and presents recent applications for turbulent reactive flows. MMC was initially formulated as a method that integrates the probability density function (PDF) and conditional moment closure (CMC) models through a generalisation of mapping closure. MMC models utilise a reference space, whose PDF is prescribed a priori or which is simulated by some means such as a Markov diffusion process. The turbulent fluctuations of all scalars in this method are divided into major and minor groups, and the former are associated with the reference space via a mapping function. The reference space describes a low-dimensional manifold which can fluctuate in any given way, while the fluctuations of the (real) scalars are fully or partially confined relative to that reference space. The dimensionality of the reference space is usually small. For example, in non-premixed combustion a reference space emulating the mixture fraction usually suffices. There are both conditional and probabilistic conceptualisations of MMC and both deterministic and stochastic mathematical formulations. In the past decade, an extension of probabilistic MMC has emerged that is known as generalised MMC that removes some of the formality of the original formulation and extends the type and usage of the reference variables. Generalised MMC is commonly associated, although not exclusively, with large eddy simulations (LES). This chapter reviews the conceptual and theoretical advances in MMC since its original formulation and also reviews some of the recently published applications of MMC in turbulent reactive flows.

Dual Fluidized Bed Gasification of Solid Fuels

In dual fluidized bed gasification technology, the gasification/pyrolysis and combustion reactions are decoupled and conducted in two separate fluidized bed reactors connected by circulating inert or catalytic bed material. Hence, a nitrogen-free high-quality syngas is produced. The configuration obviates the need of a capital-intensive air separation unit. It is a complex reactor system, and the challenge lies in selecting appropriate bed material/catalyst, understanding flow patterns and heat transfer characteristics, and designing and operating such a system. This chapter reviews the basic concept, critical components, hydrodynamics, and process characteristics of this technology presenting the current state of the art.

Hydrodynamics of Circulating Fluidized Bed Systems

Fluidized bed reactors are used in different industries to carry out multiphase chemical reactions. In these reactors, the fluid is passed through the reactor bed having granular solid materials. The velocity of the fluid is kept high enough to suspend these materials resulting to behave them like fluids. Such reactors are classified as bubbling bed, fast circulating bed or dual bed systems combining two beds depending upon the fluid velocities and constructions of the reactors. For combustion and gasification processes, circulating or dual fluidized bed systems are often preferred because they are more efficient having high throughput. However, the hydrodynamics of such fluidized beds, using normally low-grade feedstocks, is very complex and plays a critical role for successful operation of the plant. Lots of experimental and theoretical investigations are done in this area; however, the available information on the hydrodynamics is limited. In this chapter, the hydrodynamics of circulating fluidized bed systems has been discussed.

Mechanics and Modelling of Turbulence–Combustion Interaction

Engineering applications of combustion for aviation, automotive and power generation invariably encounter an underlying turbulent flow field. A proper understanding of the complex turbulence–combustion interactions, flame structure and dynamics is indispensable towards the optimal design and systematic evolution of these applications. A predictive solution of turbulent combustion phenomenon in a practical combustion system where all scales of turbulence are fully resolved is extremely difficult with currently available computational facilities. The urgent requirement for the solution of fluid engineering problems has led to the emergence of turbulence models. The turbulence models could be systematically derived based on the Navier–Stokes equations up to a certain point; however, they require closure hypotheses that depend on dimensional arguments and empirical input. Over the past several decades, turbulence models based on Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) framework have been developed and used for engineering applications. The success of turbulence models for non-reactive flows has encouraged similar approaches for turbulent reactive flows which consequently led to the development of turbulent combustion models. Modelling of the chemical source term remains the central issue of turbulent combustion simulations. In this introductory chapter, we will review the basics of turbulent flows and multiscale interactions between turbulence and combustion, and proceed towards a brief discussion on the state-of-the-art turbulent combustion models.

Numerical Modelling of Fluidized Bed Gasification: An Overview

An overview of the computational fluid dynamics (CFD) modelling techniques used to study multiphase reacting flow in fluidized bed reactors is presented in this chapter. Research in fluidized bed gasifiers has gained momentum in recent years due to their various industrial applications. Experimental investigation of such intricate process requires sophisticated and expensive measuring techniques. Moreover, it is very difficult to capture essential process details of these systems by available experimental methods. On the other hand, numerical simulation offers a viable approach to experimental investigations. The numerical simulations not only offer a better insight into the complex gas–solid flow dynamics, but it also carries paramount importance in the design and optimization of fluidized bed systems. The present chapter primarily focuses on the CFD modelling fundamentals and their application pertaining to fluidized bed reactors. Detailed description of gas–solid flow modelling and chemical reaction kinetics is given separately.

A Review on Autoignition in Laminar and Turbulent Nonpremixed Flames

This chapter presents a condensed review on the autoignition in laminar and turbulent nonpremixed flames. Both experimental and numerical aspects are discussed. Fundamental studies on autoignition in turbulent flows revealed that random ignition spots are initially observed in the lean mixtures where the scalar dissipation rate is low. The mixture fraction corresponding to this lean mixture is usually referred as the “most reactive mixture fraction”. The increase in initial turbulent intensity and mixing delays autoignition. For most of the fuels, autoignition is observed as a two-stage process with a negative temperature coefficient. Besides, the physical and chemical properties of the fuels, the complex chemical kinetics also affect auto-ignition as well as combustion characteristics. Autoignition is also a dominant flame stabilization mechanism at the base of the lifted flames. Fundamental experimental investigations on autoignition in turbulent flows are very much limited, and most of the previous work is specifically focused on the Berkley vitiated coflow burner and the Cambridge burner. The combustion models developed so far can capture the trends observed in the experiments and the direct numerical simulation (DNS) studies. However, none of the combustion models developed so far can capture the trends quantitatively.