In this research, the performance of oil palm empty fruit bunch (OPEFB) fiber-reinforced epoxy composite with varying fiber orientation and stacking sequence as the material for mountain bike frame was studied utilizing ANSYS software.The choice of OPEFB fiber was motivated by the fact that the waste by-product of oil palm extraction in Malaysia alone might reach 70-80 million tons per year, with 90% of oil palm biomass lost as waste.The properties of epoxy OPEFB composite in principal 1, 2, and 3 directions were calculated using Whitney and Riley estimates.10 stacking sequences and five loading conditions were taken.The results show that the fibre orientation of epoxy OPEFB composite on the bicycle frame had little effect on the performance contrary to the number of plies in the laminate or number of laminates which had major effects.
This research is a temperature controller that will be implemented to ensure that the water temperature of the solar water heating unit is maintained at the desirable level at all times of use.This control circuit is designed to control the On/Off action of the immersed electrical heater according to specific temperature range.A temperature sensor will sense the water temperature constantly and send signal to a micro-controller unit.The micro-controller will process the data according to a written program and control the actions of electrical heater.At the same time, temperature reading will be displayed through LCD and real-time data can be viewed from a computer via serial port.During times of sufficient sunlight, solar energy will be the main source used for heating water; otherwise, there will be an automatic switching to the electrical operated immersion heater.This controller will give reliability to users of solar water heating systems.
The main objective of this project is to fabricate a complete functional seed sprayer machine which is fully powered by solar energy.The solar seed sprayer machine should be able to spray different types of vegetable seeds.Further analysis about the performance has been conducted through the seed amount sprayed over time and area covered by the machine.Solar energy i s u s e d a s the power supply for the machine.Wireless communication is used to remotely control the machine, and the 3D printing technology is used to assist in the fabrication of required components.The solar seed sprayer machine under research is composed of four main systems.The remote driving system, solar charging system, seed storage dispenser system, and impeller spreader system.Different experiments have been conducted to assess the performance of the machine.The performance of machine is indicated through the capability of machine on spreading different types of seeds with various size and shape.The spread seed count has been also tested as well with the area covered by the machine.
Plastic wastes have caused serious environmental issues worldwide, and thus viable solutions for their replacement are now urgently needed. This work aimed to develop biocomposite materials based on polyethylene (PE) wastes as matrix reinforced with coconut fiber, without any additional chemical treatments, using extrusion and compression molding. The effects of polymer matrix type (high-density and low-density PE (HDPE and LDPE)) and fiber loading (5-15 wt%) on the mechanical properties and long-term water absorption behaviour of the materials were evaluated. Tensile strength results showed the optimum performance at 5 wt% fiber – of 16.6 MPa for the HDPE matrix and 7.3 MPa for the LDPE matrix, but flexural and impact strengths reduced with the fiber loading. An increasing trend of water absorption capacity was noted as a function of filler loading and of the water temperature during immersion, with a weight gain of up to 5%, following the trend: cold water > room temperature tap water > hot water. From the results, HDPE based biocomposites had better mechanical performance and lower water absorption capacity, compared with LDPE based biocomposites.
Abstract In light of the adverse environmental impact of the R134a refrigerant, replacing it with a more environmentally friendly refrigerant has become imperative than ever. This study presents an experimental investigation into the utilization of R152a and R134a refrigerants in a vapor compression refrigeration (VCR) system employing a variable displacement oil-free linear compressor. The potential for the replacement of R134a with R152a was examined based on energy, environmental, and economic performance analyses. The outcomes indicated that R152a exhibited a higher coefficient of performance (COP) in comparison to R134a under identical operating conditions. Specifically, when the pressure ratio was 2.0 and the piston stroke was 11 mm, R152a's COP was 13.0% higher than R134a. It was also discovered that reducing the operating stroke and increasing the pressure ratio could effectively lower CO 2 emissions and total costs. Under the 2.0 pressure ratio and 9 mm piston stroke, R134a produced 1082.4 kg more CO 2 emissions than R152a, representing a 209% increase. Additionally, In addition, the R152a and R134a total cost was reduced by 8.3% with the 2.5 pressure ratio and 11 mm piston stroke. Notably, the results of the current study demonstrated that R152a outperformed R134a in energy consumption, environmental friendliness, and economy in oil-free linear compressor refrigeration systems. R152a used less electric power, generated fewer CO 2 emissions, and naturally reduced predicted running costs in order to maintain the same COP.
Advancement of technologies in computing such as internet of things, cloud computing, and artificial intelligence drive manufacturing industries to adopt and implement automation in production. One of the key technologies or preferable methods to increase the productivity is implementing prediction models or machine learning (ML) algorithms in production. This article is aimed to show a comprehensive review on AI implementation in machining of materials, and to present methodology in prediction model development. The characteristic of experimental data and the key attributes in the model development are presented and discussed with a case study.
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