Refine your search
Collections
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Venkatesan, K.
- Experimental Investigation and Optimization of Machining Parameters using Grey-Relational Analysis Approach and Fuzzy Based Taguchi Loss Function Method
Abstract Views :190 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, Sri Sairam Engineering College, Chennai – 600 044, IN
2 School of Mechanical Engineering, VIT University, Vellore – 632 014., IN
1 Department of Mechanical Engineering, Sri Sairam Engineering College, Chennai – 600 044, IN
2 School of Mechanical Engineering, VIT University, Vellore – 632 014., IN
Source
Indian Journal of Science and Technology, Vol 9, No 44 (2016), Pagination:Abstract
Objectives: The objective of present study is to investigate the machinability effect on turning of hybrid metal matrix composites (Al/SiC/B4C) by coated carbide inserts. Then the application of Grey-Relational Analysis approach (GRAA) and Fuzzy-Taguchi Loss Function (FTLF)are used for the optimization ofmulti quality criteria response is reported. Methods/Statistical Analysis: The bar type hybrid composite are fabricated using stir casting technique. The composite has356Alalloy as ‘matrix’ and ‘SiC’with different wt%(volume fraction) of 5%, 10%, 15%and B4C (5%) particles as reinforcement material. Force (Fz) and roughness (Ra and Rt) are considered as two quality characteristics. L9orthogonal array, the ratio of signal to noise (S/N), multi-response performance characteristics (MPC), and variance test (ANOVA) are applied to investigate the quality characteristics for developed new composites. Findings: The optimal cutting parameters are determined using Grey-relational analysis Approach (GRAA) and fuzzy-Taguchi Loss Function (FTLF). Based on both approaches, the optimal levels of machining parameters are determined as A1B1C1D1.As a result, the grey relational analysis and the fuzzy-Taguchi method confirm the effectiveness for optimization of machining parameters with multiple quality criteria responses. Among these methods, fuzzy-Taguchi Loss Function (FTLF) is the most superior. Application/Improvements: In addition, the variance test (ANOVA)is identifies, the factor D (cutting depth) and C (feed rate),two influential parameters which account 55.77% and 69.8 % of the variance for grey-relational grade (GRA) and fuzzy- reasoning grade (FRG).Keywords
Fuzzy, Grey Relational Apporach, Investigation, Optimization, Taguchi’s Loss Function Method.- Energy Conservation for Base Transceiver Station Cooling System with Energy Plus Software
Abstract Views :180 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Instrumentation Engineering, Hindustan Institute of Technology and Science, Padur, Chennai - 603103, Tamil Nadu, IN
2 Hindustan University, Padur, Chennai - 603103, Tamil Nadu, IN
1 Department of Electronics and Instrumentation Engineering, Hindustan Institute of Technology and Science, Padur, Chennai - 603103, Tamil Nadu, IN
2 Hindustan University, Padur, Chennai - 603103, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 39 (2016), Pagination:Abstract
Background/Objectives: Green Telecommunications System aims at reducing CO2 emission and consumption of energy. Free cooling system is one which optimizes the air conditioning load of the Base Transceiver Station (BTS) shelter. Methods/Statistical Analysis: The main contribution of this paper is modeling and simulation of BTS shelter envelope with the Energy Plus for energy efficiency. The Shelter envelope absorb the heat from atmosphere which varies throughout the year. For the given shelter inside temperature, the Energy plus gives out the shelter envelope's sensible cooling load. This sensible cooling load is considered as separate variable. The sensible cooling load of the shelter and the equipment load are computed as thermal current. A fuzzy logic controller has been designed, which switches ON the free cooling fans or air conditioner depending upon atmospheric temperature and room temperature. Findings: Generally environmental influence on the room temperature is considered as atmospheric temperature variations. Instead if we consider the environmental influence as heat absorbed in kilo Watts (kW) and fed to the controller there will be further reduction in the energy consumption and improvements in contribution of free cooling fans. By modeling and simulating the BTS shelter in Energy Plus this findings are realized. On comparison of the energy consumption during simulations the proposed Energy plus model based control has saving of about 2.69% and 1.37% respectively for fixed and variable capacity air conditioner over the model derived from the basic principles which considerer atmospheric influence as temperature variations. The over all energy saving is increased from 12.04% to 14.41% by using the Energy Plus model based control proposed in this paper with free cooling for Chennai region. Analysis made to find priority city for free cooling in selected important cities. Bangalore region gives more free cooling saving and lesser energy consumption among the selected cities. Applications/Improvements: The simulated heat load data of envelope from Energy Plus can be directly used in the controller for real time applications. The other ways is cure fitting heat absorption data over atmospheric temperature for various seasons/periods. Using the equation and atmospheric temperature the heat load of the envelope calculated for control purpose This concept can be applied even for buildings.Keywords
BTS Shelter, Energy Efficiency, Energy Plus Model, Free Cooling System, Fuzzy Logic.- An Investigation of the Parametric Effects of Cutting Parameters on Quality Characteristics during the Dry Turning of Inconel 718 Alloy
Abstract Views :135 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, Sri Sairam Engineering College, Sai Leo Nagar, West Tambaram, Chennai - 600 044, Tamil Nadu, IN
2 School of Mechanical Engineering, VIT University, Near Katpadi Road, Vellore -632 014, Tamil Nadu, IN
1 Department of Mechanical Engineering, Sri Sairam Engineering College, Sai Leo Nagar, West Tambaram, Chennai - 600 044, Tamil Nadu, IN
2 School of Mechanical Engineering, VIT University, Near Katpadi Road, Vellore -632 014, Tamil Nadu, IN