Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

CO2 mitigation in Thailand’s low-carbon society: The potential of renewable energy

Abstract: This study aims at the development of Thailand’s low-carbon society in 2030 by using the Asia-Pacific Integrated Model/Extended Snap Shot model for analysis of greenhouse gas (GHG) mitigation through renewable energy (RE) utilization. This article presents the potentials of RE in power generation, industrial, and transport sectors in Thailand for GHG mitigation in 2030. The deployment of the RE sources is used in the analyses with potentials of mini-hydro of 390 MW, wind power of 960 MW, solar power of 600 MW, biomass energy of 4,400 MW, biogas power of 144 MW, waste to power of 192 MW, bioenergy of 4,634 ktoe, and RE for thermal of 8,088 ktoe in 2030. According to the proposed development, the amount of GHG emissions is estimated based on business-as-usual (BAU) without mitigation measures and countermeasures with GHG mitigation options of adopted RE technologies available during 2005–2030. Results show that annual GHG emissions in the base year of 2005 are 185,983 kt-CO2. In 2030 the GHG emissio...

A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees

Abstract: Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, Ki of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted Ki values from the proposed model show a strong coefficient of determination, R2=0.996, to experimental Ki values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low Ki values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted Ki should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low Ki.

Sensorless DC motor drive via optimal observer‐based servo control

Abstract: This paper proposes an alternative design of a sensorless DC motor drive via optimal observer-based servo control. Without the speed sensor, the extended Luenberger observer is implemented to estimate the rotor speed of the DC motor in the presence of the disturbance torque. With this knowledge of the speed estimated from the observer, the servo state-feedback controller can drive such a rotor speed to follow the desired one. The stability and performance of the DC drive system can be guaranteed by the optimal control which minimizes the H2 norm of the closed-loop feedback control and observer system. The simulation and experiment studies are demonstrated for the effectiveness of the proposed control methodology in a practical approach for the sensorless DC drive. Copyright © 2002 John Wiley & Sons, Ltd.

CO2 mitigation model of future power plants with integrated carbon capture and storage in Thailand

Abstract: Thailand currently relies on natural gas, coal, and oil for electricity production. Natural gas and oil fields are the plentiful domestic energy resources in the Gulf of Thailand, but are projected to be available only in the next decade. Using domestic natural gas would reduce national energy security. Due to its low price, coal will dominate in electricity generation in Thailand. However, more utilization of coal results in increasing CO2 emissions. To comply with the low-carbon society policy of the Royal Thai Government, carbon dioxide capture and storage (CCS) for the future committed power plants in Thailand is introduced and analysed using the market allocation model, a least-cost energy planning tool. In this study, CO2 mitigation scenarios include integrated CCS to new gas- and coal-based power plants, nuclear power and renewable-based power plants and these were introduced as mitigation options. In energy-demand forecasting, share of coal-based plants is projected to increase from 0.72% in 2006 ...