GREEN SYNTHESIS NANOPARTIKEL GRAPHENE DENGAN AGEN PEREDUKSI URIN MANUSIA DAN APLIKASINYA SEBAGAI ADITIF BIONANOLUBRICANT BERBASIS CPO (CRUDE PALM OIL)

Graphene is a nanomaterial that has been widely applied to various fields because of the uniqueness of the material, therefore this material is very interesting to be developed as an additive in lubricant. This study aims to determine the optimum additive weight ratio and obtain optimum operating conditions in the graphene dispersion process in base oil. This research is divided into 2 stages: preliminary research and main research. The preliminary study aims to transform the chemical structure of crude palm oil (CPO) through a three-stage reaction into a polyol as a base oil. The main research is the process of making bionanolubricant. Graphene is synthesized using a combination technique with a human urine as reducing agent. The formulations are known by varying the weight of the additive and the time of the dispersion. Variation of additive weight was 0% (A1), 0.25% (B1), 0.5% (C1), 1% (D1) while for dispersion time variation ranged from 0 min (A2), 60 min (B2), 90 minutes (C2) and, 120 minutes (D2). Based on the SEM-EDX test results, the SEM image formed graphene and spectrum layers on EDX show that the oxide in graphene has been successfully reduced. Bionanolubricant was tested for quality with 7 parameters. The composition of base oil formula 250 gr and graphene nanoparticles 0.5% w / w is the optimum additive weight ratio for C1 sample code whereas the economical dispersion time is 60 minutes. The result of the viscosity index test is 121,72, its pour point is 10,4oC, flash point equal to 228oC with lubrication capability tested through four ball tester got scar diameter equal to 0,87 mm. This Bionanolubricant belongs to the SAE 250 class and is classified as a GL-4 lubricant based on the quality level of API (American Petroleum Institute) performance test

Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression

In this study, the Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) was proposed in order to estimate standard errors of regression coefficients in the presence of high leverage points and heteroscedastic errors in multiple linear regression. Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) is the combination of a robust method and Heteroscedasticit Consistent Covariance Matrix (HCCM). The robust method is used to eliminate the effect of high leverage points while HCCM is mainly used to eliminate the effect of heteroscedastic errors. The performance of RHCCM was assessed through an empirical study and compared with results obtained when the original Heteroscedastic Consistent Covariance Matrix was used

Identification of discrete-time dynamic systems using modified genetic algorithm

The purpose of this study is to investigate the application of genetic algorithm (GA) in modelling linear and non-linear dynamic systems and develop an alternative model structure selection algorithm based on GA. Orthogonal least square (OLS), a gradient descent method was used as the benchmark for the proposed algorithm. A model structure selection based on modified genetic algorithm (MGA) has been proposed in this study to reduce problems of premature convergence in simple GA (SGA). The effect of different combinations of MGA operators on the performance of the developed model was studied and the effectiveness and shortcomings of MGA were highlighted. Results were compared between SGA, MGA and benchmark OLS method. It was discovered that with similar number of dynamic terms, in most cases, MGA performs better than SGA in terms of exploring potential solution and outperformed the OLS algorithm in terms of selected number of terms and predictive accuracy. In addition, the use of local search with MGA for fine-tuning the algorithm was also proposed and investigated, named as memetic algorithm (MA). Simulation results demonstrated that in most cases, MA is able to produce an adequate and parsimonious model that can satisfy the model validation tests with significant advantages over OLS, SGA and MGA methods. Furthermore, the case studies on identification of multivariable systems based on real experimental data from two systems namely a turbo alternator and a continuous stirred tank reactor showed that the proposed algorithm could be used as an alternative to adequately identify adequate and parsimonious models for those systems

Identification of discrete-time dynamic systems using modified genetic algorithm

The purpose of this study is to investigate the application of genetic algorithm (GA) in modelling linear and non-linear dynamic systems and develop an alternative model structure selection algorithm based on GA. Orthogonal least square (OLS), a gradient descent method was used as the benchmark for the proposed algorithm. A model structure selection based on modified genetic algorithm (MGA) has been proposed in this study to reduce problems of premature convergence in simple GA (SGA). The effect of different combinations of MGA operators on the performance of the developed model was studied and the effectiveness and shortcomings of MGA were highlighted. Results were compared between SGA, MGA and benchmark OLS method. It was discovered that with similar number of dynamic terms, in most cases, MGA performs better than SGA in terms of exploring potential solution and outperformed the OLS algorithm in terms of selected number of terms and predictive accuracy. In addition, the use of local search with MGA for fine-tuning the algorithm was also proposed and investigated, named as memetic algorithm (MA). Simulation results demonstrated that in most cases, MA is able to produce an adequate and parsimonious model that can satisfy the model validation tests with significant advantages over OLS, SGA and MGA methods. Furthermore, the case studies on identification of multivariable systems based on real experimental data from two systems namely a turbo alternator and a continuous stirred tank reactor showed that the proposed algorithm could be used as an alternative to adequately identify adequate and parsimonious models for those systems

The Implementation Of Maintenance Works For Historical Buildings – A Review On The Current Scenario

The conservation of historical buildings is a method on preserving structures which are historically and culturally important to the nation

Multi-layer micro channels system: interpretation and developments

During the last three decades the concept of the traditional cooling systems was modified to include single, double, and multi-layer micro channels. The new studies, applications, fabrication, and research focus on four main areas: the geometrical shape of the micro channels, the number of stacked layers, the type of the coolants, and the heat performance optimization. The previous studies have shown a significant reduction in the power consumption as the optimization is accomplished. In this paper, a semi-review for the previous works is provided, an attempt to interpret the nature of the work done, and show another trial for optimization. In this study, water was used as a coolant agent, stacked multi-channel was adopted, and thermal resistance network was calculated.The heat sink under consideration is a rectangle of width ?? and length ??. The thickness ???????? of the base of the micro-channel is 100 [?m] while the depth ????of the micro-channel is 500[?m], both kept constant for all future optimization cases

Introduction to control engineering

This book is intended to serve as a text book for a first course in control system engineering in higher institutes and universities. The text has been written through the experience of the authors in teaching this subject. Control systems are found in a broad range of applications within various engineering disciplines namely electrical, mechanical, chemical or aerospace engineerings. This book emphasizes particularly on the principle, design and analysis of feedback control system. The contents have been written to be suitable for all branches of engineering

Thermal Analysis of Radial Piezoelectric-Magnetic Fan (RPMF) for Electronics Cooling

Application of piezoelectric fan in electronic cooling system has been proven that it is more efficient than natural convection with least power consumption and has high potential to replace existing rotary fan for its simplicity and longer life. An integration of piezoelectric fan with magnet is to widen the cooling coverage area with similar power consumption and cost of running a single piezoelectric fan. By optimizing the repulsive magnetic force generated in between the magnets, the overall fans oscillate with significant average amplitude. The purpose of this paper is to investigate the performance of multiple piezoelectric-magnetic fan and its significance in reducing temperature while enhance the heat transfer. The parameters under investigation are the distance between magnets and fans orientation. In this study four magnetic fans were activated by a piezoelectric fan.  It is found that at distance between magnets is 14 millimeters; the average amplitude is largest at highest resonant frequency. The multiple fans is better to be arranged in radial orientation for its ability to produce larger repulsive magnetic force to oscillate the adjacent fans. The distribution of repulsive magnetic force in radial orientation is five times better than array orientation. Therefore, radial piezoelectric-magnetic fan (RPMF) produces larger average amplitude of fans which is 111%. 30% of power consumption per unit coverage area is secured. RPMF generates average wind velocity of 0.4m/s compared to array orientation 0.17m/s

Optimization of multilayer micro channels heat sinks cooling system using genetic algorithm

Cooling of electronic devices is problematic by its nature simply because of the space restriction. Recent advances in high powered miniaturized electronic systems have come at the expanse of very high heat fluxes that pose challenges to thermal management research. Uncontrolled excessive heat may cause thermal fatigue and stresses and the current micro electro-mechanical cooling systems (MEMS) which utilize the single layer micro channel heat sink, introduced a decade ago, may no longer be an adequate solution. Possible extension of the layer of parallel micro channels into a stacked system, by developing two, three, and multi-layer channel systems are being investigated. The design of all these systems depends on several parameters; coolant type, channel geometry, channel dimensions, and the number of the channels. This paper reports a new model for optimizing the thermal resistance, developed based on specific parameters of the dimensions of the channel, the wall width between the channels, and using water as a coolant at 27°C. The outcomes of the model were compared with other published studies. The results showed that the model is valid and reliable for further studies

Single-objective optimization of a thermoacoustic refrigerator

Optimization of energy-related systems with by-products that involve environmental degradation has never been so crucial today with depleting resources and global concerns over negative impacts on our environment. This paper reports the results of an optimization scheme on the coefficient of performance (COP) of a standing wave thermoacoustic refrigerator based on genetic algorithm. The environmentally friendly refrigerator operates without any CFCs, which has been associated with the depletion of ozone, a substance that prevents uv light from reaching the earth’s atmosphere. A single- objective optimization to maximize the COP of a thermoacoustic refrigerator has been completed. The variables investigated include the length of the stack, Lsn, center position of the stack, xsn, blockage ratio, B and drive ratio, DR. The results show that a COP of up to 1.64 is achievable which provides promise for future improvements in the present systems