Pochai, Nopparat

Preferred name

Pochai, Nopparat

Alternative Name

Pochai, N.

Main Affiliation

School of Science

nopparat.po@kmitl.ac.th

Now showing 1 - 10 of 34

Some of the metrics are blocked by your
consent settings
A One-dimensional Salinity Measurement Model in the Chao Phraya River with the Chao Phraya Barrage Dam Using a Shooting Method
(2023-03-01)
Vanishkorn, Buddhaporn
;
Pochai, Nopparat
Sea water receding from the Gulf of Thailand causes salinity diffusion in the Chao Phraya River, Thailand, and the amount of northern water is reduced in the dry season. It has an impact on people, particularly the generation of tap water. The Samlae raw water pumping station is the major pumping station. The Ban Krachaeng subdistrict is located in Mueang district, Pathum Thani province, and is affected by saltwater intrusion, which causes the salinity level to exceed the recommended threshold. In order for the Metropolitan Waterworks Authority (MWA)'s water supply system to achieve the standard, the salinity index at the Samlae raw water pumping station is controlled to not exceed the surveillance threshold of 0.25 g/l in this research. A barrage dam consists of a number of large gates that can be opened or closed to control the amount of fresh water passing through. There is a Chao Phraya barrage dam which is across the Chao Phraya River at Chai Nat, the northern part of the focused area. The objective of this research is to demonstrate a onedimensional steady-state salinity measurement model in a river with a barrage dam. Irrigation is done in rivers with dams using the shooting method to estimate the solution. The results obtained from simulating simulated salinity measurements from Phra-Nakhon Tai Power Plant Station to Samlae Station demonstrated that the shooting method can be used to accurately estimate the solution. Freshwater flow velocity and salinity dissolving efficiency were discovered to be the most important elements controlling salinity levels. The suggested salinity control approach may help to regulate the salinity level until it reaches a normal level.
Some of the metrics are blocked by your
consent settings
A Mathematical Model of Hazardous Smoke Emission Control Considering Primary and Secondary Pollution Concentrations
(2024-01-01)
Oyjinda, Pravitra
;
Pochai, Nopparat
The major cause of air pollution concerns is industrial development, which has an influence on human health, human lifestyle, and the environment around an industrial zone. Air quality management assists in the control and improvement of air pollution in order to lower the quantity of numerous air contaminants. The purpose of this investigation is to examine various air pollution emission control and quality control mechanisms. Several atmospheric diffusion equations are used to solve numerous air pollution concentration indices that can represent how air pollutants disperse in the atmosphere. Primary and secondary pollutant concentrations are approximated by using the finite difference technique. Monitoring points are installed for checking the air pollutant concentration levels of sulfur dioxide (SO2), sulfur trioxide (SO3), and sulfuric acid (H2SO4). Suitable emission control scenarios are proposed. The approximate solutions of air pollution control simulations at each monitoring point are compared. The air quality standard is also used to compare the results of the experiments. There are suitable emission control scenarios presented. At each monitoring location, the approximate solutions of air pollution control models are compared. The proposed strategy selects a good decision-monitoring point. According to the research, an observation area should be near an industrial area. The chosen monitoring location provides the most effective overall air quality for emission control techniques around industry and residential areas. As a result, the location of collecting for each monitoring station influences the air quality of the air pollution control schedule.
Some of the metrics are blocked by your
consent settings
A Simulation of Shoreline Evolution with a Groin Structure Using an Alternative Machine Learning Algorithm
(2025-07-01)
Manilam, Surasak
;
Pochai, Nopparat
Uneven sediment transport is a major cause of coastal erosion. Using groin structures is one method to help slow the outflow of sediment from the shoreline. Studying coastal behavior and forecasting future shoreline changes are crucial for managing and assessing the viability of remediation strategies. This research presents simulations of shoreline evolution with a single groin structure using two different methods, such as mathematical modeling and an alternative machine learning. A mathematical model is a representation of a real-world shoreline evolution phenomenon using partial differential equations. A machine learning algorithm is designed to learn patterns and relationships directly from real data. In this research, an alternative machine learning algorithm is designed to learn patterns and relationships directly from mathematical simulation data and let the machine make a decision in a situation that it has never learned before. For mathematical modeling, we introduced a one-dimensional model to predict the shoreline evolution. The initial and the boundary conditions with related parameter settings are introduced. The Saulyev finite difference method is used to obtain the approximated solution. An alternative machine learning algorithm for unexpected shoreline evolution prediction is also proposed. For alternative machine learning simulations, we identified six suitable features for the training dataset and developed an alternative K-nearest neighbor algorithm. It provides a way of predicting the evolution of the shoreline with a single groin structure. Additionally, an exact solution in an ideal scenario is used to test the precision of the simulation as well. The results show that the Saulyev technique outperforms an alternative K-nearest neighbor algorithm due to the lower root mean square error value. Both results of them are closed together. According to the research, mathematical modeling outperforms the KNN regression technique in terms of computational effectiveness during time periods of 0.5, 1, 5, 10, 15, and 20 years. Based on the modeling configuration and parameter simplicity, the KNN algorithm is still a good option for non-expert users.
Some of the metrics are blocked by your
consent settings
Numerical Simulations of a Two-dimensional Vertically Averaged Air Pollution Measurement in a Street Canyon
(2022-02-01)
Thongzunhor, Hasakarn
;
Pochai, Nopparat
Air pollution is the release of pollutants into the atmosphere that are harmful to human health and the ecosystem as a whole. Initially, urban air pollution was considered to be a regional problem caused largely by domestic heating and industrial emissions, both of which are now well under control. The building's canyon structure and the geometry of the streets in urban areas are street canyons. Side Street connects the two sides of the street, which are made up of portions of buildings. Street canyons, which are urban streets bordered on both sides by structures, have shown high levels of pollution. Pedestrians, cyclists, vehicles, and residents will most likely be surrounded by pollution concentrations higher than current air quality limits on these walkways. The research is focused on detecting air pollution in a street canyon. There will be an introduction to a transient two-dimensional advection-diffusion equation. A two-dimensional vertically averaged air pollution measurement model is utilized to characterize the air pollution concentration along a street canyon. The model delivers the pollutant concentration in the air each and every time. The model's air pollutant concentration is approximated using a finite difference technique. An approximation approach to open and closed boundary conditions is proposed. Wind direction effects are also modelled. The suggested numerical approaches performed well in producing a high level of agreement. Simple explicit schemes have the benefit of being simple to compute. These techniques may be used to simulate air pollution measurements in a variety of street canyons.
Some of the metrics are blocked by your
consent settings
A Numerical Model of Groundwater Quality Assessment Using a Special A-D Cubic Spline Method
(2025-01-01)
Klankaew, Pantira
;
Pochai, Nopparat
Nowadays, when the industrial sector and human habitation have expanded rapidly, causing more and more various pollutants to come out, water is considered one type of pollution that is contaminated by these community and industrial sources. When this toxic water seeps through the soil, it can contaminate groundwater sources. Groundwater contamination can affect the health of humans and other living things, both directly and indirectly. In some areas, groundwater contamination can cause the population to become sick with various diseases. Long-term groundwater quality investigations near landfill sites need the use of mathematical models. A one-dimensional advection-diffusion equation (ADE) was used to analyze the groundwater's quality by describing the amount of contamination present. The objectives are mathematical simulations that can be used to assess the quality of groundwater that becomes contaminated over a long period of time. This study proposes numerical simulations for a one-dimensional mathematical model for long-term measurement of groundwater pollution around landfills. The natural cubic spline method, the Crank-Nicolson method, the upwind explicit method, and the special A-D cubic spline method are approximated in the model solution. The exact and approximate solutions are compared in each case. The proposed upwind explicit method analysis provides close to exact and properly accurate solutions. In five to ten years, the proposed numerical model can simulate several scenarios.
Some of the metrics are blocked by your
consent settings
One-dimensional Numerical Simulations of Oil Spill in a Coastal Bay with Delayed Removal Mechanisms
(2025-01-01)
Kasamwan, Teerat
;
Pochai, Nopparat
Oil spills in marine and coastal areas can result from various activities, such as oil drilling, transportation, shipping, tank cleaning, illegal disposal of oil-contaminated or used water, and accidents like ship collisions or sinking incidents. These events result in oil slicks or tar balls that form in the sea and eventually drift towards the coast. There are many methods for addressing oil spills, such as containment, employing skimmers, chemical dispersants, bioremediation, burning, beach cleanup, environmental restoration, and monitoring and assessing long-term impacts on the shoreline. A delay in oil spill response can have severe consequences for both the environment and local economies. When oil spills occur, rapid and effective action is essential to minimize damage. Unfortunately, delays in response can exacerbate the problem and lead to more extensive environmental harm. In this research, a one-dimensional mathematical model for an oil spill in a coastal bay with delayed removal mechanisms is considered. The governing equation for an oil spill in a coastal bay with delayed removal mechanisms is introduced. The initial and boundary conditions for an oil spill in a coastal bay are also presented. A mathematical model incorporating delayed removal mechanisms is proposed. The solution of the proposed model is approximated using a finite difference method, specifically the forward time-centered space (FTCS) method. In the simulations, two scenarios are illustrated, namely, the instant removal mechanism scenarios and the delayed removal mechanism scenarios. In the instant removal mechanism scenarios, various average removal rates and basic water flow behaviors are simulated. In the delayed removal mechanism scenarios, realistic oil spill situations are considered. Therefore, the spillage rate and removal mechanism rate throughout the simulation period are analyzed. The simulation results show that the concentration of the late-coming removal mechanism leads to a poorer recovery outcome than the faster-coming removal mechanism in all scenarios. This aligns with the reality that when oil spill removal is effectively managed, the concentration of oil in the sea should decrease. The findings of this study demonstrate that, under all circumstances, delayed oil removal has more detrimental effects on seawater recovery than speedy removal. Therefore, removing oil spills quickly and effectively will significantly reduce the amount of oil in the water.
Some of the metrics are blocked by your
consent settings
Health Behavior and Emotional Responses of Thai National Team Athletes during the COVID-19 Pandemic: A Comparative Study of Individual and Team Sports
(2025-08-01)
Pluemsamran, Theeratheeta
;
Pariyavuth, Pariya
;
Pochai, Nopparat
;
Panurushthanon, Phichayavee
;
Punthipayanon, Sirichet
Objectives: COVID-19 significantly impacted athletes’ health behavior and emotional well-being. Disruptions to training routines, competition schedules, and social structures raised concerns about psychological resilience, especially for elite athletes. In this study, we (1) adapted and validated the Emotional State Questionnaire (EST-Q-2) for Thai athletes, (2) examined the emotional responses and associated health behavior patterns of Thai national team athletes during the COVID-19 pandemic, and (3) compared emotional states between individual and team sport athletes. Methods: We surveyed 280 Thai national team athletes (146 male, 134 female) preparing for the 19th Asian Games. Participants completed the culturally adapted EST-Q-2, measuring 5 dimensions: depression, general anxiety, panic disorder, fatigue, and insomnia. We compared emotional responses by sport type. Results: The most prominent symptoms reported were fatigue and insomnia (M = 3.26), general anxiety (M = 2.84), depression (M = 2.35), and panic disorder (M = 2.17). We found no statistically significant differences between individual and team sport athletes across emotional dimensions. The adapted EST-Q-2 demonstrated strong reliability (Cronbach’s α = 0.80). Conclusion: The COVID-19 pandemic adversely affected the emotional states and health behavior of Thai national athletes, with high levels of fatigue and sleep disturbances. The lack of significant differences between sport types indicates a universal psychological impact, underscoring the need for targeted mental health interventions regardless of sport category.
Some of the metrics are blocked by your
consent settings
A Numerical Simulation of the Kratom Plant Growth Model While Treated by a Specific Nutrient Using an Explicit Finite Difference Method
(2025-01-01)
Krongsamsri, Pitchayapa
;
Komthong, Nontalee
;
Yammeng, Jidapa
;
Chaichuay, Chinda
;
Boonchom, Banjong
Kratom refers to both Mitragyna speciosa, a tree native to Southeast Asia, and products manufactured from its leaves sold as herbal supplements. Kratom leaves contain a range of chemical compounds known as bioactive alkaloids, which have physiological effects. A mathematical model of the Kratom plant under a particular nutritional treatment will be provided in this research. Also, the methods for setting the initial condition and boundary condition will be presented. Also, as the plant grows, the solution's domain shifts every time. Techniques for adjusting the specific nutrient's physical parameters are also provided. With the use of an explicit finite difference method, the solutions are approximated. The specific nutritional concentrations are calculated for each height level. As shown, the specific nutrient will spread from the root to the apex of the trunk. The nutrient has the capacity to stimulate the growth of the Kratom. The specific nutrient concentration along the trunk may be measured using the proposed mathematical model as the Kratom plant grows each day. A proposed numerical model with a specific nutrient can be used to develop a precise model, such as a one-dimensional model of branches and foliage. It would be more captivating if the plant nutrients indicated here were researched for their ability to accelerate the growth of large or medium-sized Kratom plants. In conclusion, the study shows that calcium dihydrogen phosphate monohydrate may be useful as a growth promoter for Kratom plants and suggests a way to measure its effects quantitatively.
Some of the metrics are blocked by your
consent settings
A PM2.5 Forewarning Algorithm Using k-Nearest Neighbors Machine Learning at Changpuek, Chiang Mai, Thailand
(2023-08-29)
Pochai, Nopparat
;
Thongtha, Kaboon
In Chiang Mai, Thailand, the air pollution issue caused by atmospheric particulate matter with a diameter of less than 2.5 μm, or PM2.5, has been identified as an ongoing crisis. PM2.5 not only has a direct impact on people's health and way of life, but it also has a negative impact on the national economy. Residents in such PM2.5-polluted locations are particularly susceptible to respiratory diseases, skin diseases, inflammatory eye diseases, and cardiovascular problems. As a result, this study is going to analyze PM2.5 data using the k-nearest neighbors machine learning algorithm as a guideline to warn people, particularly in Changpuek, Chiang Mai, Thailand, to handle the PM2.5 characterization problem.
Some of the metrics are blocked by your
consent settings
A Mathematical Model of the Risk Assessment for Airborne Transmission in a Classroom with a Ventilation System and Nine Distinct Face Mask Efficiency
(2023-03-01)
Janmanit, Benjawan
;
Pochai, Nopparat
TB, COVID-19, MERS, and SARS are all serious infectious diseases that are transmitted by the air or aerosol via coughing, spitting, sneezing, speaking, or wounds. When restaurants and bars reopen and continue operations in some parts of the United States, the Centers for Disease Control and Prevention (CDC) gives the following suggestions for how operators can reduce risk for employees, customers, and communities while also restricting the spread of COVID-19. The more and longer a person interacts with others, the greater the risk of COVID-19 spreading. Therefore, we need to be informed of its management and treatment. As a result, for the control and reduction of potentially polluted air, such as CO2 levels, good air quality management is required. They investigated the protective effectiveness of face masks against airborne transmission of infectious SARS-CoV-2 droplets and aerosols in response to the World Health Organization's recommendation to wear face masks to prevent the spread of COVID-19. Using nine different forms of mask efficiency, this research provides a mathematical model for calculating the chance of airborne transmission in a classroom. The fourth-order Runge-Kutta approach is used to approximate the model solution. The proposed strategy strikes a balance between the number of students allowed to stay in the classroom and the effectiveness of nine different masks. We can see how utilizing nine different masks and a well-ventilated system in the classroom can help to reduce the risk of airborne infection.

Pochai, Nopparat

Filters

Settings

Sort By

Results per page