Publications by authors named "Somboon Sukpancharoen"
Article Synopsis
- This study focuses on creating an advanced growing system for microalgae by integrating innovative technologies, such as IoT, AI, and image processing, into a closed tubular photobioreactor.
- It employs seven sensors to monitor critical growth parameters like temperature, pH, and light exposure, while using an ESP8266 microcontroller for data management and an ESP32 camera for real-time growth assessment.
- The research demonstrates that consistent 24-hour lighting significantly boosts biomass productivity, and a machine learning model named XGBoost effectively predicts algal growth, indicating potential benefits for renewable energy and food supply in the future.
The growing demand for fossil fuels has motivated the search for a renewable energy source, and biodiesel has emerged as a promising and environmentally friendly alternative. In this study, machine learning techniques were employed to predict the biodiesel yield from transesterification processes using three different catalysts: homogeneous, heterogeneous, and enzyme. Extreme gradient boosting algorithms showed the highest accuracy in predictions, with a coefficient of determination accuracy of nearly 0.
View Article and Find Full Text PDFRecovered carbon black (RCB) obtained from a tire pyrolysis plant was subjected to chemical and thermal treatments for application as a filler in rubber compounds. Carbon black was chemically treated with nitric acid by varying the temperature, time, and chemical-to-carbon black ratio. The iodine number was optimized using response surface methodology (RSM) and the Design Expert software.
View Article and Find Full Text PDFIn this study, palm empty fruit bunch (PEFB) pyrolysis, bio-oil improvement, and generating electricity were all simulated using Aspen plus. This research employed a kinetic reactor for pyrolysis at 500 °C based on 1,000 tons of PEFB per day. The simulation results indicated that 1 kg/hr.
View Article and Find Full Text PDFThe principal context of this study was a combined heat and power plant (CHPP) system, with the aim of conducting the multi-objective optimization (MOO) of an energy, exergy, and economic (3E) analysis. To meet rising energy demands, optimal operational conditions for CHPPs are required. Enhancements to plant equipment and improvements in plant design are critical.
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