P.M.V. Subbarao

Performance of iterative tomographic algorithms applied to non-destructive evaluation with limited data

Iterative tomographic algorithms have been applied to the reconstruction of a two-dimensional object with internal defects from its projections. Nine distinct algorithms with varying numbers of projections and projection angles have been considered. Each projection of the solid object is interpreted as a path integral of the light-sensitive property of the object in the appropriate direction. The integrals are evaluated numerically and are assumed to represent exact data. Errors in reconstruction are defined as the statistics of difference between original and reconstructed objects and are used to compare one algorithm with respect to another. The algorithms used in this work can be classified broadly into three groups, namely the additive algebraic reconstruction technique (ART), the multiplicative algebraic reconstruction technique (MART) and the maximization reconstruction technique (MRT). Additive ART shows a systematic convergence with respect to the number of projections and the value of the relaxation parameter. MART algorithms produce less error at convergence compared to additive ART but converge only at small values of the relaxation parameter. The MRT algorithm shows an intermediate performance when compared to ART and MART. An increasing noise level in the projection data increases the error in the reconstructed field. The maximum and RMS errors are highest in ART and lowest in MART for given projection data. Increasing noise levels in the projection data decrease the convergence rates. For all algorithms, a 20% noise level is seen as an upper limit, beyond which the reconstructed field is barely recognizable.

Performance evaluation of iterative tomographic algorithms applied to reconstruction of a three-dimensional temperature field

Iterative tomographic algorithms have been applied to the reconstruction of a three-dimensional temperature field (from its projections) for Rayleigh-Renard-type natural-convection problems. Nine distinct algorithms with varying numbers of projections and projection angles have been considered. The three-dimensional temperature field is sliced into a set of two-dimensional planes and reconstruction algorithms are applied to each individual plane. Projection of the temperature field is interpreted as a path integral along a line in the appropriate direction. The integrals are evaluated numerically and are assumed to represent exact data. Errors in reconstruction are defined with field data as reference and are used to compare one algorithm with respect to another. The algorithms used in this work can be broadly classified into three groups: additive algebraic reconstruction technique (ART), multiplicative algebraic reconstruction technique (MART), and maximization reconstruction technique (MRT). Additive A...

Effective utilization of low-grade steam in an ammonia—water cycle

Abstract Effective utilization of low-grade steam in a Rankine cycle power plant is one of the challenging tasks for researchers. In a condensing turbine, last few stages of the turbine operate in two phase region leading to losses due to flow of wet steam, which results loss of work in low pressure turbine. Either wet or saturated steam normally called low grade is difficult to handle in a steam turbine due to its higher specific volume. Major portion of the heat in the cycle is rejected to cooling water, which results in thermal pollution of the environment and higher energy loss. Ammonia—water cycle or Kalina cycle is more efficient for the utilization of various low grade heat sources such as gas turbine exhaust gas, geothermal hot water, exhaust from steel plant etc. In this work, a new methodology was proposed for the utilization of low-grade steam in ammonia—water cycle to obtain a better power output and higher plant efficiency. The suggested ammonia—water cycle that utilizes low-grade steam produces higher-power output and it is more efficient than the Rankine steam cycle utilizing the low-grade steam and operates on a condensing mode.

Effect of Jet Design on Commingling of Glass/Nylon Filaments:

In this study, a computational fluid dynamics (CFD) model is applied to study the airflow patterns inside the commingling jets, for different configurations. The CFD package, FLUENT 6.1, is used to predict the two-dimensional flow field inside a yarn channel. The parameters viz. velocity profile, pressure gradient, and air particle trajectory, obtained from this CFD analysis give important information for further analysis. The design parameters of commingling jets are related to the flow characteristics and their effect on the structure and properties of Glass/Nylon commingled yarns. The results show that the number of air orifice and the angle of orifice have significant effect on the airflow profile inside the jet and consequently on the structure of the commingled yarns. The jet orifice angle affects the axial velocity. The effect of air pressure is also important, since the nip frequency of commingled yarns is a function of the speed of rotation of the vortex and it is observed that with increase in air pressure, axial and tangential velocities in the nozzle increase. This work shows that, the CFD modeling can be used to optimize nozzle design parameters to develop commingled yarns with better properties.

Intelligent Decision Support System for Detection and Root Cause Analysis of Faults in Coal Mills

Coal mill is an essential component of a coal-fired power plant that affects the performance, reliability, and downtime of the plant. The availability of the milling system is influenced by poor controls and faults occurring inside the mills. There is a need for automated systems, which can provide early information about the condition of the mill and help operators to take informed decisions. In this paper, a model-based residual evaluation approach, which is capable of online fault detection and diagnosis of major faults occurring in the milling system, is proposed. A dynamic mathematical model of mill, which can authentically replicate the mill behavior under different conditions, is selected for residual generation. Fuzzy logic is employed for residual evaluation to determine the type and magnitude of the fault, while Bayesian network is used for troubleshooting the root cause. The proposed technique is validated using historical data of coal mills obtained from an actual coal-fired power plant in India. Two case studies are presented to demonstrate the effectiveness of the approach. The results indicate that the proposed approach has potential to provide useful information regarding the condition of the mills and can help operators to take appropriate control action timely. This application also shows that how fuzzy logic and Bayesian networks (probability theory) can complement each other and can be used appropriately to solve parts of the problem.

A Hybrid Approach Using CGM and DE Algorithm for Estimation of Boundary Heat Flux in a Parallel Plate Channel

An inverse convection problem for estimation of transient boundary heat flux of a hydrodynamically and thermally developing laminar forced convective flow in a parallel plate channel is studied. A hybrid differential evolution approach with a local optimization algorithm is proposed for this purpose. The conjugate gradient method with adjoint equation is used as a local optimization algorithm to speed up the convergence. In comparison to the conjugate gradient method or conventional differential evolution approach, the proposed hybrid differential evolution approach is found to be more accurate. A variety of cases considering locations and numbers of sensors and transient profile of boundary heat flux have been tested to see the performance of this hybrid method.

Estimation of transient boundary flux for a developing flow in a parallel plate channel

Purpose – The purpose of this paper is to develop a numerical model for estimating the unknown boundary heat flux in a parallel plate channel for the case of a hydrodynamically and thermally developing laminar flow. Design/methodology/approach – The conjugate gradient method (CGM) is used to solve the inverse problem. The momentum equations are solved using an in-house computational fluid dynamics (CFD) source code. The energy equations along with the adjoint and sensitivity equations are solved using the finite volume method. Findings – The effects of number of measurements, distribution of measurements and functional form of unknown flux on the accuracy of estimations are investigated in this work. The prediction of boundary flux by the present algorithm is found to be quite reasonable. Originality/value – It is noticed from the literature review that study of inverse problem with hydrodynamically developing flow has not received sufficient attention despite its practical importance. In the present work...

Efficiency enhancement in a Rankine cycle power plant: Combined cycle approach

Abstract Efficiency enhancement in a Rankine cycle power plant operating on a condensing mode is one of the challenging tasks for researchers. In a modern fossil-fired steam power plant even a fraction of percentage difference in efficiency can mean very large savings in annual fuel costs. In this study, effort was put into improving the cycle efficiency by reducing energy loss and irreversibility in the major portion of the cycle such as heat input part, work output part, and heat rejection part. In this study, a new combined cycle concept is proposed to reduce: energy loss in the condenser; power output and efficiency loss in the low pressure turbine due to expansion of low grade or low temperature steam; and irreversibility in the boiler due to higher degree of enthalpy of evaporation. The proposed combined cycle plant uses water as a working fluid in the topping cycle and an ammonia—water mixture in the bottoming cycle and it is 4 per cent more efficient than the standalone Rankine cycle operating on a condensing mode.

A Novel and Efficient Method for Particle Locating and Advancing over Deforming, NonOrthogonal Mesh

ABSTRACT A method developed for particle locating and advancing in nonorthogonal curvilinear grids is presented. The method is uniformly applicable for deforming as well as fixed Eulerian grids. The method is equally applicable to coupled as well as uncoupled two-phase flows. Guidelines are presented on which the present and previous schemes are evaluated. The algorithm yields a generalized and efficient method and is being used in practical applications. The accuracy of the method is demonstrated by verifying with analytical and experimental data.

Characterization of leaf waste based biochar for cost effective hydrogen sulphide removal from biogas

Installation of decentralized units for biogas production along with indigenous upgradation systems can be an effective approach to meet growing energy demands of the rural population. Therefore, readily available leaf waste was used to prepare biochar at different temperatures and employed for H2S removal from biogas produced via anaerobic digestion plant. It is found that biochar prepared via carbonization of leaf waste at 400 °C effectively removes 84.2% H2S (from 1254 ppm to 201 ppm) from raw biogas for 25 min in a continuous adsorption tower. Subsequently, leaf waste biochar compositional, textural and morphological properties before and after H2S adsorption have been analyzed using proximate analysis, CHNS, BET surface area, FTIR, XRD, and SEM-EDX. It is found that BET surface area, pore size, and textural properties of leaf waste biochar plays a crucial role in H2S removal from the biogas.