A Solar Reactor for Bio-diesel Production from Pongamia Oil: Studies on transesterfication Process Parameters and Energy Efficiency

2020 ◽  
Author(s):  
Subbaiyan Naveen ◽  
Kannappan Panchamoorthy Gopinath ◽  
Rajagopal Malolan ◽  
Ramesh Sai Jayaraman ◽  
Krishnan Aakriti ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Process Parameters ◽  
Solar Reactor ◽  
Pongamia Oil ◽  
Diesel Production

scholarly journals Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

2014 ◽  
Vol 1 (4) ◽  
pp. 256-265 ◽  
Author(s):  
Hong Seok Park ◽  
Trung Thanh Nguyen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Injection Molding ◽  
Product Quality ◽  
Process Parameters ◽  
Optimization Problems ◽  
Computational Cost ◽  
Injection Molding Process ◽  
Molding Process ◽  
Nsga Ii

Abstract Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using nondominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

scholarly journals Machinability and Energy Efficiency in Micro-EDM Milling of Zirconium Boride Reinforced with Silicon Carbide Fibers

Materials ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 3920 ◽  
Author(s):  
Mariangela Quarto ◽  
Giuliano Bissacco ◽  
Gianluca D’Urso
Keyword(s):  
Energy Efficiency ◽  
Process Parameters ◽  
Advanced Materials ◽  
Cavity Surface ◽  
Main Process ◽  
Zirconium Boride ◽  
Electrode Wear ◽  
Micro Edm ◽  
Process Performance ◽  
Sic Fibers

Several types of advanced materials have been developed to be applied in many industrial application fields to satisfy the high performance required. Despite this, research and development of process suited to machine are still limited. Due to the high mechanical properties, advanced materials are often considered as difficult to cut. For this reason, EDM (Electrical Discharge Machining) can be defined as a good option for the machining of micro components made of difficult to cut electrically conductive materials. This paper presents an investigation on the applicability of the EDM process to machine ZrB2 reinforced by SiC fibers, with assessment of process performance and energy efficiency. Different fractions of the additive SiC fibers were taken into account to evaluate the stability and repeatability of the process. Circular pocket features were machined by using a micro-EDM machine and the results from different process parameters combinations were analyzed with respect to material removal, electrode wear and cavity surface quality. Discharges data were collected and characterized to define the actual values of process parameters (peak current, pulse duration and energy per discharge). The characteristics of the pulses were used to evaluate the machinability and to investigate the energy efficiency of the process. The main process performance indicators were calculated as a function of the number of occurred discharges and the energy of a single discharge. The results show interesting aspects related to the process from both the performances and the removal mechanism point of view.

Process Optimization of One-Stage Propane Pre-Cooled MRC Cycle for Small-Scale LNG Plant

2012 ◽  
Vol 516-517 ◽  
pp. 1184-1187
Author(s):  
Heng Sun ◽  
Dan Shu ◽  
Hong Mei Zhu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Process Parameters ◽  
Large Scale ◽  
High Energy ◽  
Small Scale ◽  
Main Process ◽  
One Stage ◽  
High Energy Efficiency ◽  
The One

One-stage pre-cooled mixture refrigerant cycle can be applied in small-scale LNG plant and be special suitable for skit mounted LNG plant. It has different character with the C3MR cycle used in large-scale LNG plant. The optimization of the mixture refrigerant is carried out using HYSYS software. The effect of the main process parameters on the performance of the cycle is calculated and discussed. The result shows that appropriate ranges of the process parameters exist. Higher and lower values of the parameters will increase the energy consumption significantly. The results also indicate that the optimization of the one-stage pre-cooled mixture refrigerant cycle can obtain rather high energy efficiency that is competitive with that of the SMR which is widely employed in small-scale LNG plant.

scholarly journals Regular Neural Network Based Machining Parameters Optimization Model Of NC Machine Tool

2018 ◽  
Vol 232 ◽  
pp. 01006
Author(s):  
Sanping Wang ◽  
Junwen Chen ◽  
Wei Yan
Keyword(s):  
Neural Network ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Machine Tool ◽  
Process Parameters ◽  
Machine Tools ◽  
Machining Process ◽  
Machining Parameters ◽  
Nc Machine Tool ◽  
Nc Machine

Energy consumption process is the basis for energy efficiency improvement of machine tools. Most of the existing researches focus on the static modelling of energy consumption of a machine tool; however, there are a few studies that paid attention to that how process parameters influence the energy consumption of machine tools during processing. It is noted that the process parameters can be selected to reduce energy consumption during machining processes without additional investment. In this paper, a characteristic energy consumption model for NC machine tool was proposed. Then, the mapping rule between process parameters and energy consumption of machine tool was studied, and the model was solved with the regular neural network (RNN). Finally, the result was verified with an experiment of milling the surface of aluminium block, which can effectively improve the energy efficiency of machine tool. The experiment results are shown that regular neural network is used to optimize the process parameters and process the same machining characteristics; we analyze the in machining process of machine tool based on the three cutting parameters, and then, a model of energy consumption. We employ to learn, and use this trained model to select optimal parameters.

Mit explorativer Datenanalyse und Data Mining zu hoch effizienten polymeren Tribo-Schicht-Systemen

2021 ◽  
Author(s):  
Anna Buling ◽  
Laura Dongmo Guetse ◽  
Jörg Zerrer
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Process Parameters ◽  
Film Formation ◽  
Machine Building ◽  
Polymeric Coating ◽  
Coating Process ◽  
Coating System ◽  
Wear Protection ◽  
Lightweight Metals

Since current developments in machine building and automotive industry are dealing with the amplification of energy efficiency and sustainability of components, the reduction of friction and wear losses plays the most important key role. A further aspect of energy saving by mass reduction can be taken into account by substituting steel by lightweight metals. To fulfill these requirements, this study focuses on the development of a tribo-coating system, based on PEEK (poly-ether-ether-ketone) as a base coating material for Al substrates. The coating is applied by using laser radiation to increase the energy efficiency of the coating process on the one hand and to reduce thermal stress on the component on the other hand. Furthermore, the laser process improves the mechanical prosperties of the polymeric coating. In the first step the correlation between the coating process parameters and the resulting coating morphology accompanied by its mechanical properties and the tribological behavior was elucidated by using explorative data analysis. Here, the influence of different wear and/or friction reducing additives and their variable concentrations was also taken into account, while the tribological response of the resulting coating systems was examined and valuated under dry sliding conditions. Using data mining, the most dominant correlations between the process parameters and the tribological answer of the coating system could be found. Utilizing these findings, the process parameters for different additives in the PEEK dispersions could be optimized, and a multilayer system was established, which combines high corrosion and wear protection accompanied by a tribo-film formation resulting in low friction and an increased lifetime of the coating system.

scholarly journals Optimization of a divided wall column for the separation of C4-C6 normal paraffin mixture using Box-Behnken design

2013 ◽  
Vol 19 (1) ◽  
pp. 107-119 ◽  
Author(s):  
Vikas Sangal ◽  
Vineet Kumar ◽  
Mani Mishra
Keyword(s):  
Energy Efficiency ◽  
Response Surface Methodology ◽  
Product Quality ◽  
Response Surface ◽  
Process Parameters ◽  
Ternary Mixture ◽  
Normal Paraffin ◽  
Box Behnken Design ◽  
Optimization Of Parameters ◽  
Divided Wall Column

In the present study, simulation of a divided wall column (DWC) was carried out to study the product quality and energy efficiency as a function of reflux rate, liquid spilt and vapour split for the separation of C4-C6 normal paraffin ternary mixture. Rigorous simulation of the DWC was carried out using Multifrac model of ASPEN Plus software. Box-Behnken design (BBD) was used for the optimization of parameters and to evaluate the effects and interaction of the process parameters such as reflux rate (r), liquid split (l) and vapour split (v). It was found that the number of simulation runs reduced significantly for the optimization of DWC by BBD. Optimization by BBD under response surface methodology (RSM) vividly underscores interactions between variables and their effects. The predictions agree well with the results of the rigorous simulation.

scholarly journals Experimental study of Food Court Waste air gasification process performances in a batch reactor

2019 ◽  
Vol 112 ◽  
pp. 01019 ◽  
Author(s):  
Raluca Nicoleta Tîrtea ◽  
Gabriela Ionescu ◽  
Cora Bulmău ◽  
Cosmin Mărculescu
Keyword(s):  
Energy Efficiency ◽  
Process Parameters ◽  
Conversion Rate ◽  
Batch Reactor ◽  
Operational Parameters ◽  
Glass Waste ◽  
Influence Of Process Parameters ◽  
Equivalent Ratio ◽  
Gasification Process ◽  
Waste Air

The paper presents the experimental results of Food Court Waste air gasification using a batch reactor. This type of waste is generated mainly in the food court areas of services spaces, shopping centers, airports and malls and is generally composed of paper & cardboard, plastic, organic, wood, metal and glass waste. The process operating parameters were: temperatures between 650°C and 850°C and an equivalent ratio of 0.25 and 0.4 respectively. The study focused on the influence of process parameters on the energy conversion rate considering the cold gas and hot gas efficiency correlated with the feedstock carbon conversion rate. The recorded instantaneous concentrations of sampled gas species were plotted in time dependent graphs for accurate variation curves of gases concentrations. The results can be used to isolate the startup stage of the gasification process and to establish the optimal process parameters for increased overall energy efficiency. In conclusion, considering the current setup, operational parameters and process energy efficiency, the optimal temperature for the air gasification of Food Court Waste is 850ºC with an equivalent ratio of 0.40.

Sign in / Sign up

Export Citation Format

Share Document