The railway brake system usually uses compressed air brake system which uses high-pressure air to press the brake shoe on the surface of the wheel to reduce the speed of the train. Repeated friction generates heat at the contact surface, increasing thermal stress on the cast iron brake shoe. The purpose of this study is to investigate the thermal stress on a prototype of cast iron brake shoe using the finite element method compare the analytical results to the actual brake shoe and redesign a brake shoe prototype to reduce thermal stress. Based on the results of the thermal stress study using the finite element method, it has shown that the location of the thermal stress on the prototype brake shoe according to the location of the crack on the real brake shoe. The brake shoe's design which includes single notch in the center of brake shoe which is can help to reduce thermal stress. The results from this study should be validated with the results from the field test to evaluate both of thermal distribution and braking efficiency in term of braking distances as well.
ระบบเบรกของรถไฟนิยมใช้ระบบเบรกแบบลมอัด โดยใช้อากาศแรงดันสูงกดแท่งห้ามล้อไปสัมผัสกับผิวของล้อเพื่อลดความเร็วของรถไฟ เมื่อเกิดการเสียดสีกันซ้ำ ๆ จึงเกิดความร้อนขึ้นบริเวณผิวสัมผัส ทำให้เกิดความเค้นสะสมเนื่องจากความร้อนบนแท่งห้ามล้อวัสดุเหล็กหล่อ งานวิจัยนี้จึงมีวัตถุประสงค์เพื่อศึกษาความเค้นเนื่องจากความร้อน (Thermal stress) บนแท่งห้ามล้อวัสดุเหล็กหล่อรูปแบบต้นแบบด้วยระเบียบวิธีไฟไนต์เอลิเมนต์เพื่อเปรียบเทียบผลการวิเคราะห์ที่ได้กับแท่งห้ามล้อชิ้นงานจริง และออกแบบแท่งห้ามล้อวัสดุเหล็กหล่อในรูปแบบใหม่เพื่อลดความเค้นเนื่องจากความร้อนที่เกิดขึ้น
คณะวิทยาศาสตร์
This work presents the fabrication of the handheld meter for potentiometric detection of Hg (II). The meter was constructed based on using an ion-sensitive field-effect transistor (ISFET) platform. The developed meter provides high accuracy and precision (%Recovery was in the range of 92.55 - 109.32 and %RSD was 2.38). It was applied to the analysis of cosmetic samples. The results by the developed electrode were not significantly different at a 95% confidence level compared to the results by using ICP-OES.
คณะวิศวกรรมศาสตร์
One of the most important aspects of responding to a medical case is the response time. In general, most fatalities are due to the patient not being able to reach the hands of the doctor in time. This also includes the arrival of medical equipment to the scene. The human brain will start to degrade in function after 3 minutes of oxygen starvation which conventional road transportation method first responders presently use is usually unable to reach the site in this golden 3 minutes, resulting in fatalities during transport or before the arrival of first responders at the scene. Therefore, medical equipment transport by fully autonomous aircraft is explored. This is done through drone deliveries which is much quicker than road methods as the equipment could be flown straight to the site as it is not affected by traffic, road conditions, and navigation. In this project, we will explore an aerial delivery system for medical equipment such as Automatic External Defibrillators (AEDs), First aid equipment, and other small requested medical devices. This will be done through a DJI drone platform and their SDK application. The main goal for this project is to decrease the response time by using an autonomous aerial drone to deliver medical equipment.
คณะวิศวกรรมศาสตร์
Jaundice, a common condition in infants that results from high bilirubin levels in the blood, often requires early diagnosis and monitoring to prevent severe complications, especially in newborns. Traditional diagnostic methods can be time-consuming and subject to human error. This study proposes an approach for real-time jaundice detection using advanced image processing techniques and machine learning algorithms. By analyzing images captured in RGB color spaces, pixel values are extracted and processed through Otsu’s thresholding and morphological operations to detect color patterns indicative of jaundice. A classifier model is then trained to distinguish between normal and jaundiced conditions, offering an automated, accurate, and efficient diagnostic tool. The system’s potential to operate in real-time makes it particularly suited for clinical settings, providing healthcare professionals with timely insights to improve patient outcomes. The proposed method represents a significant innovation in healthcare, combining artificial intelligence and medical imaging to enhance the early detection and management of jaundice, reducing reliance on manual interventions and improving overall healthcare delivery.