Pochai, Nopparat

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Pochai, Nopparat
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Pochai, N.
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nopparat.po@kmitl.ac.th

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    A numerical treatment of a mathematical model of ground water flow in rice field near marine shrimp aquaculture farm
    (2012-01-01)
    Pochai, N.
    ;
    Pongnoo, N.
    The high level salinity in soil is a main problem of a plant grows less in rice field near marine shrimp aquaculture farm. The salinity in soil and ground water flow are required for soil quality assessments. The modeling often involves numerical methods to solve the equations. In this research, two mathematical models are used to simulate the salinity in the ground with varied flow velocity. The first is a potential flow model that provides the velocity field of the ground water flow. The second is a dispersion model, where the commonly used governing factor is the twodimensional dispersion equation that gives the salinity fields. In the simulation process, we used the finite difference method for the both models. Finally, we present a numerical simulation that confirms the results of the technique. © 2010 Published by Elsevier Ltd.
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    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.
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    Numerical simulation of a nonlinear thin fluid film flow velocity model of a third grade fluid on a moving belt using finite difference method with Newton iterative scheme
    (2019-01-01)
    Klankaew, Pantira
    ;
    Pochai, Nopparat
    A thin film flow problem on a moving belt has been useful in scientific, engineering, biological and biomedical problems. A thin film flow velocity on a moving belt can be modeled by a nonlinear differential equation. The model is provides the film flow velocity in each thickness layers. In this research, a finite difference method and a Newton iterative method are used to approximate the solutions of the nonlinear thin fluid film flow velocity model. Their numerical simulations of a thin film flow velocity of a third grade fluid in on a moving belt with varied physical parameters are investigated. The proposed numerical techniques give good agreement approximated solutions in several moving belts speed levels.
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    A Mathematical Model for PM2.5 Prediction based on Vehicle Density and Wind Speed in Samphanthawong district, Bangkok
    (2025-01-01)
    Hiran, Waraporn
    ;
    Pochai, Nopparat
    Bangkok frequently experiences concerning levels of air pollution, particularly during its dry season. This pollution is primarily driven by emissions from vehicles, agricultural burning in nearby regions, industrial activities, and construction dust, all exacerbated by unfavorable weather conditions that trap pollutants. Samphanthawong District, especially Yaowarat, consistently grapples with severe PM2.5 pollution during this period. Our research emphasizes the critical role of meteorological factors, such as wind speed and natural ventilation, in dispersing urban pollutants. While the simulation model proved stable and its computational results were not significantly affected by the chosen time step, it highlighted a major issue: PM2.5 concentrations in Samphanthawong decrease very slowly due to light winds and inadequate airflow. Therefore, to effectively manage air pollution in this area, additional measures are needed to improve ventilation or directly reduce PM2.5 sources, as natural factors alone cannot achieve rapid pollutant reduction.
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    An k-Nearest Neighbors Machine Learning Algorithm for the PM2.5 Early Warning System in Bang Khun Tian, Bangkok, Thailand
    (2024-12-02)
    Thongtha, Kaboon
    ;
    Pochai, Nopparat
    The problem of particulate matter with a diameter of less than 2.5-10 microns, such as PM2.5-PM10 in Bangkok, affects the health of people because there are small particles that can penetrate deep into the alveoli. If there is an early warning system to warn people about the harmful levels of PM2.5 in Bangkok, such as an early warning of 2-3 days, it can help the people have time to prevent themselves. In this research, an early warning system to warn people about the harmful levels of PM2.5 in Bangkok is proposed. The air quality data of the Bang Khun Tian station, Bangkok, for 2 months, from December 1, 2020, to January 31, 2021, were selected because the area is an air-quality-worrying area. A proposed early warning system for the harmful levels of PM2.5 around Bang Khun Tian, Bangkok, was developed using the k-nearest neighbors machine learning algorithm. As the results show, the proposed technique gives an agreeable prediction for the earliest warning by 4 days.
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    Numerical quadratic interpolation for approximating time of death
    (2018-01-01)
    Chaichuay, Chinda
    ;
    Kongprasert, Wittaya
    ;
    Kruemuen, Apiwat
    ;
    Mataynam, Chitchanok
    ;
    Pochai, Nopparat
    Time is one of the most important factors of consideration in a murder case. It might delicately convict a murderer, break a alibi, alternately dispose of a suspect. If the circumstances surrounding death indicate the possibility of homicide, then both the body and immediate surrounding area become crucial in estimating time of death. Estimating the time of death, especially in cases where there are no witnesses, is critical to the investigation. The governing equation is governed by the Newton's law of cooling that provides the time of death. The Lagrange quadratic interpolation technique is use to fitting the experimental data so as to gives the accurately thermal conductivity. The traditional Newton method is also employed to approximate the solution. The proposed numerical technique gives good agreement estimating time of death.