K.K. Manesh

Bio: K.K. Manesh is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Organic Rankine cycle & Surface roughness. The author has an hindex of 2, co-authored 2 publications receiving 76 citations.

Numerical generation of anisotropic 3D non-Gaussian engineering surfaces with specified 3D surface roughness parameters

Abstract: Three-dimensional surface roughness of mating parts of engineering assemblies has a significant influence on their functional behaviour. Studies on load bearing capacity in elastohydrodynamic contacts, gap flow analysis in precision hydraulic assemblies using modeled 3D fluid continuum micro gap geometry, etc., have made it possible to quantify the effect of certain 3D surface roughness parameters on frictional behaviour of the assemblies. This set forth the need for artificially generated three-dimensional engineering surfaces having prescribed roughness values for a better understanding and prediction of tribological problems. In this paper, an algorithm is developed for the numerical generation of three-dimensional anisotropic surfaces with prescribed 3D surface roughness parameters. The procedures employ either the Non-linear Conjugate Gradient Method (NCGM) or 2-D Digital Filter method. The results show that both the methods can adequately produce surfaces at small correlation distances, while at higher correlation distances the NCGM yields better results. Comparison between model-simulated output and measurement results of three-dimensional surface roughness of engineering surface show a good match, supporting the validity of the model.

Modelling of fluid continuum considering 3D surface parameters in hydraulic assemblies

Abstract: Friction in servo hydraulic assemblies reduces the response characteristics of the system. The friction is influenced by various factors including the geometry (form and surface errors) of the sliding surfaces. In this work, functionally significant 3D surface parameters from the Birmingham parameters are investigated for reduced friction. A 3D surface modelling approach is presented using random process modelling as the basis. An exponential decay areal autocorrelation function is used to model the grinding and honing processes which are commonly employed for the manufacture of the hydraulic assemblies. Honed surface is modelled with the crosshatches of appropriate angle. Method of surface modelling is validated using the data obtained through measurements on a practical surface. Different surface maps with varying surface parameters of the ground and honed surfaces are generated. The fluid continuum gap geometries of the hydraulic assemblies are modelled using these surface maps as envelopes. Pressure distribution, velocity and viscous friction force are used as measurands of the frictional characteristics. Using computational fluid dynamics (CFD) approach, these measurands are evaluated for different functionally significant Birmingham parameters. Based on further analysis, negative skewness, lower kurtosis values, higher valley fluid retention index were found to have lower frictional characteristics.

Availability and 6E assessment and optimal design of a novel cogeneration system based on integrated turbo compressor station - SOFC-solar-geothermal-steam and organic Rankine cycles with machine learning

Abstract: A novel integrated cogeneration system for a real gas turbocompressor station has been proposed. Also, a new systematic approach has been introduced for analysis and optimization of the considered system based on using energy, electrochemical, exergy, exergoeconomic, exergoenvironmental, emergoeconomic, and emergoenvironmental analyses along with advanced exergy, economic and environmental evaluations, and availability assessment. In addition, a powerful machine learning tool has been employed to reduce optimization algorithm computational time. To show the ability of the proposed system and systematic approach, a gas injection station with three gas turbine (GT) drivers have been studied. To improve the performance from the thermodynamic, economic, and environmental points of view and to the application of renewable energies, the integrated system includes turbocompressors with solid oxide fuel cells (SOFC), steam, and organic Rankine cycles (SORCs) while using solar and geothermal energies has been proposed for the power and steam production. In addition, six-objective optimization has been done with a genetic algorithm, and finally, the availability assessment was applied for basic (turbocompressors) and the proposed cycle. To reduce the computational time of the optimization algorithm, the machine learning method has been employed to generate 6E objective functions. show the power generation is increased by about 60%, and 6370 kg/h of process steam is produced. Five organic fluids were examined, and among them, R11 was found to be the best selection. Energy and exergy efficiencies increased by 12.8% and 10.8%, respectively, compared to the base cycle. Also, the results show that cost, environmental impact, and total emergy of electricity generation are 49.59 $/MWh, 26.99 Pts/MWh, and 4.09e12 sej/MWh. The advanced analysis states that REC1, LPSUP, and REC2 have the greatest potential for energetic, economic, and environmental improvements. In the optimal conditions, the results of the 6E analyses indicate that thermal and exergy efficiencies of 3.06% and 2.84%, and perspective of economic, environmental, and emergy per unit of power generation, 9.54%, 8.86%, and 9.05% of improvement is achieved, respectively. The availability of the proposed system was obtained at 87.28%, and the probability of failure of a GT is reduced by 0.14% compared to the base cycle, indicating the proposed plan's attractiveness.

Numerical generation of anisotropic 3D non-Gaussian engineering surfaces with specified 3D surface roughness parameters

Abstract: Three-dimensional surface roughness of mating parts of engineering assemblies has a significant influence on their functional behaviour. Studies on load bearing capacity in elastohydrodynamic contacts, gap flow analysis in precision hydraulic assemblies using modeled 3D fluid continuum micro gap geometry, etc., have made it possible to quantify the effect of certain 3D surface roughness parameters on frictional behaviour of the assemblies. This set forth the need for artificially generated three-dimensional engineering surfaces having prescribed roughness values for a better understanding and prediction of tribological problems. In this paper, an algorithm is developed for the numerical generation of three-dimensional anisotropic surfaces with prescribed 3D surface roughness parameters. The procedures employ either the Non-linear Conjugate Gradient Method (NCGM) or 2-D Digital Filter method. The results show that both the methods can adequately produce surfaces at small correlation distances, while at higher correlation distances the NCGM yields better results. Comparison between model-simulated output and measurement results of three-dimensional surface roughness of engineering surface show a good match, supporting the validity of the model.

Influencing factors and theoretical modeling methods of surface roughness in turning process: State-of-the-art

Abstract: A systematic review of influencing factors and theoretical modeling methods of surface roughness in turning process is presented in this work. The modeling methods of surface roughness are firstly classified into theoretical and empirical solutions according to their modeling processes. Subsequently, the definitions of surface roughness parameters are analyzed in accordance with the ISO standard. Based on the definitions, the influencing factors of turned surface roughness are accordingly divided into the ‘easy’ and ‘difficult’ modeling factors. Correspondingly, the advances of theoretical modeling methods are summarized in the light of ‘easy’ and ‘difficult’ modeling factors. Moreover, the advantages and disadvantages of these theoretical models of surface roughness are commented, and the corresponding challenges are also pointed out. Finally, the future works in theoretical modeling of surface roughness are discussed.

Generating randomly rough surfaces with given height probability distribution and power spectrum

Abstract: In this work we present a simple method to generate surface topography. The main advantage of the presented method as compared with those available in the literature is that the power spectrum and the height probability distribution can be specified independently. In this article we present the method and show its versatility by generating surface topographies with three different height probability distributions: the Weibull distribution, a bimodal distribution and a distribution containing a delta function that represents worn surfaces. The MATLAB-code we used to generate the numerical examples are also provided to the reader.

Characterization of 3D surface topography in 5-axis milling

Abstract: Within the context of 5-axis free-form machining, CAM software offers various ways of tool-path generation, depending on the geometry of the surface to be machined. Therefore, as the manufactured surface quality results from the choice of the machining strategy and machining parameters, the prediction of surface roughness in function of the machining conditions is an important issue in 5-axis machining. The objective of this paper is to propose a simulation model of material removal in 5-axis based on the N-buffer method and integrating the Inverse Kinematics Transformation. The tooth track is linked with the velocity giving the surface topography resulting from actual machining conditions. The model is assessed thanks to a series of sweeping over planes according to various tool axis orientations and cutting conditions. 3D surface topography analyses are performed through the new areal surface roughness parameters proposed by recent standards.

Model for the prediction of 3D surface topography in 5-axis milling

Abstract: The paper deals with the prediction of the 3D surface topography obtained in 5-axis milling in function of the machining conditions. For this purpose, a simulation model for the prediction of machined surface patterns is developed based on the well-known N-buffer method. As in sculptured surface machining the feed rates locally vary, the proposed model can be coupled to a feed-rate prediction model. Thanks to the simulation model of 3D surface topography, the influence of the machining strategy on resulting 3D surface patterns is analyzed through an experimental design. Results enhance the major influence of the tool inclination on 3D topography. Surface parameters used in the study are strongly affected by the variation of the yaw angle. The effect of the feed rate is also significant on amplitude parameters. Finally, the analysis brings out the interest of using surface parameters to characterize 3D surface topography obtained in 5-axis milling.