Direct Arc Plasma Generator with Six Nozzles, Applications of Plasma Technology and Progress in Nuclear Fusion and Thailand Tokamak-1 (TT1) Development
เทคโนโลยีพลาสมาเป็นนวัตกรรมที่สำคัญในอุตสาหกรรมการผลิต อิเล็กทรอนิกส์ และการแพทย์ โดยช่วยเพิ่มประสิทธิภาพและคุณภาพของผลิตภัณฑ์ อีกทั้งยังมีบทบาทสำคัญในพลังงานสะอาด เช่น โทคามัค ซึ่งใช้พลาสมาในการสร้างปฏิกิริยาฟิวชันเพื่อผลิตพลังงานจากไฮโดรเจนอย่างยั่งยืน โทคามัคมีศักยภาพในการลดการพึ่งพาเชื้อเพลิงฟอสซิลและแก้ไขปัญหาการเปลี่ยนแปลงสภาพภูมิอากาศ ทำให้เป็นกุญแจสำคัญสู่พลังงานแห่งอนาคต
คณะวิทยาศาสตร์
Air pollution, particularly PM2.5, is a major environmental and public health concern in Bangkok. Instead of predicting PM2.5 levels, this project aims to identify the most significant factors influencing PM2.5 concentration. By analyzing historical air quality, weather, and other environmental data, we will determine which variables—such as temperature, humidity, wind speed, or other pollutants—have the greatest impact on PM2.5 fluctuations.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
A sweet made from flour and added to give it a chewy texture similar to chewing gum.
คณะวิศวกรรมศาสตร์
This research suggested natural hemp fiber-reinforced ropes (FRR) polymer usage to reinforce recycled aggregate square concrete columns that contain fired-clay solid brick aggregates in order to reduce the high costs associated with synthetic fiber-reinforced polymers (FRPs). A total of 24 square columns of concrete were fabricated to conduct this study. The samples were tested under a monotonic axial compression load. The variables of interest were the strength of unconfined concrete and the number of FRRlayers. According to the results, the strengthened specimens demonstrated an increased compressive strength and ductility. Notably, the specimens with the smallest unconfined strength demonstrated the largest improvement in compressive strength and ductility. Particularly, the compressive strength and strain were enhanced by up to 181% and 564%, respectively. In order to predict the ultimate confined compressive stress and strain, this study investigated a number of analytical stress–strain models. A comparison of experimental and theoretical findings deduced that only a limited number of strength models resulted in close predictions, whereas an even larger scatter was observed for strain prediction. Machine learning was employed by using neural networks to predict the compressive strength. A dataset comprising 142 specimens strengthened with hemp FRP was extracted from the literature. The neural network was trained on the extracted dataset, and its performance was evaluated for the experimental results of this study, which demonstrated a close agreement.