Anantpinijwatna, Amata

Preferred name

Alternative Name

Anantpinijwatna, A.

Main Affiliation

School of Engineering

amata.an@kmitl.ac.th

Now showing 1 - 10 of 30

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Modeling of Non-Isothermal Adsorption Process in a Silica Gel Desiccant Packed Bed
(2018-01-01)
Murathatunyaluk, Siripan
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Srichanvichit, Koranut
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Anantpinijwatna, Amata
;
Kitchaiya, Prakob
This study investigated a numerical simulation of a column packed bed using silica gel. This bed is either stationary or steadily rotating, leading to different operation-regeneration schemes. Although models of these systems have already been developed and fitted with available data, they require large number of costly and time-consuming experiment to be applicable. Therefore, the development of a fundamental predictive mathematical model is necessary. The present model is a one-dimensional numerical solution of the conservation equations for heat, water vapor, and adsorbed water inside the silica gel desiccant under the constraint of local equilibrium between the two phases, which is characterized by fundamental sorption isotherms. The system of a non-isothermal adiabatic under constant pressure containing heat and mass transfer phenomena between vapor and solid phases are considered. The numerical results show good agreement with a maximum root of mean square of errors of 6.6% and 9.6% for exit air temperature and humidity, respectively
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The kinetic model and temperature effect of Caulerpa Lentillifera drying process
(2018-10-29)
Anantpinijwatna, Amata
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Nuntamongkol, Sitanan
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Tudkesorn, Benjamaporn
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Sukchoy, Orawan
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Deetae, Pawinee
The drying mechanism of the seaweed, Caulerpa Lentillifera, at different temperature were studied. This involved the modelling of the drying kinetic and the studied of the effect of the relative humidity. Five empirical drying kinetic models of Newton, Page, Modified Page, Logarithmic, and Henderson-Pabis were fitted to the experimental data with the kinetic parameters following the modified Arrhenius equation. The decency of the fit of different model was statistically evaluated. Moreover, the milestones for optimization of the drying procedure towards the energy preservation and the valuable constituent saving have been set through the modelling of the drying process energy consumption and the studied of the effect of drying temperature to the seaweed physical appearance. This work should be an interesting starting point for the further study, analysis, and improvement of the Caulerpa Lentillifera drying process.
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Perspectives, challenges and future directions
(2022-01-01)
Thongchul, Nuttha
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Charoensuppanimit, Pongtorn
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Anantpinijwatna, Amata
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Gani, Rafiqul
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Assabumrungrat, Suttichai
As discussed extensively in this book, biorefinery is perceived as a promising platform for the sustainable conversion of biomass into a variety of value-added products. As a result of attempts to replace a nonrenewable feedstock with renewable biomass, the technological advances in biorefineries have been immense in recent years. However, the commercialization of biorefineries currently face challenges from various directions, such as the availability of feedstock, the competitiveness of bio-based products, the processing technologies and unit operations, as well as methods and associated computer-aided tools for the synthesis and design of biorefinery processes. To facilitate readers’ insight, crucial elements are summarized in this chapter for each issue in terms of the current situation, the challenges, and the anticipated future developments.
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Novel method for properties prediction of pure organic compounds using machine learning
(2021-01-01)
Chorbngam, Nattasinee
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Chawuthai, Rathachai
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Anantpinijwatna, Amata
In classical thermodynamic, the estimation method of pure compounds properties was based on Newtonian physics, which required experimental data. It is proven to be inadequate for the growing demand of the novel chemical synthesis. There were several studies on the prediction of the pure compound properties based on QSPR methods. However, the conventional group-contribution based methods predictive capability was limited by the available measured data. Therefore, this study aims to approach the property prediction with a novel statistical-based method. The proposed method is derived using supervised machine learning algorithms. The experimental data used to train and validate the models were collected from the published literature. These data set are composed of the alkanes, alkenes, and alkynes derivatives containing 1-12 carbon atoms. The results show the improved accuracy of the model prediction compare to the conventional method in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE).
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Process development of sustainable biorefinery system integrated into the existing pulping process
(2020-05-10)
Mongkhonsiri, Ghochapon
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Charoensuppanimit, Pongtorn
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Anantpinijwatna, Amata
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Gani, Rafiqul
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Assabumrungrat, Suttichai
The change of paper consumption trend may jeopardize the future of pulp and paper industry. This work aims to design and develop the integrated network of biochemical and biofuel productions into existing pulp mills for sustainable purposes. The systematic methodology aided by computation tools is undertaken using the three-stage approach including process synthesis, design and innovation. Previously, the optimal technologies of the biorefinery-integrated pulping processes were successfully determined in the synthesis stage providing the highest cost-effective incorporation; 48 million USD/year of profit was estimated according to the integration of succinic acid and dimethyl ether productions into the soda pulping process. Herein, the process designs of the integrated processes were performed followed by evaluations of the process performances and identifications of the hot spots and targets for establishments of the innovations. In this work, the biomass gasification option is designed and implemented to enhance the material and energy utilizations in the previously determined biorefinery-integrated pulping processes. Electricity and biofuel are produced and sold, which contributes positively to the economic and environmental impacts of these processes. The hot spots and targets are subsequently identified prior to the innovation stage. According to this stage, the cleaner alternatives that implements the CO<inf>2</inf> utilization via methanol synthesis and solar cell installations are selected in order to minimize the CO<inf>2</inf> emission. A net CO<inf>2</inf> reduction of 42% is achieved when the cleaner alternatives are applied. Accordingly, these biorefinery-integrated innovations are not only conducive to the enhanced sustainability of existing pulp mills but also adaptive in response to the change of paper consumption trend.
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Integration of Genetic Algorithm with Machine Learning for Properties Prediction
(2025-01-01)
Chawuthai, Rathachai
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Murathathunyaluk, Siripan
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Amornratthamrong, Nalin
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Arunchaipong, Run
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Anantpinijwatna, Amata
Numerous studies have demonstrated that machine learning (ML) provides more accurate estimations of properties for oxygenated organic derivatives compared to the conventional Quantitative Structure-Property Relationship (QSPR) method. Consequently, ML’s predictive capabilities have been extended to encompass a broader range of properties, including Partition Coefficient, Boiling Point, and Solubility, among others, for oxygenated hydrocarbon derivatives. Algorithms such as Linear Regression, Support Vector Machine, Random Forest, and Gaussian Process are selected through trial-and-error to identify the most suitable approach. The models are trained and validated using experimental data from published literature. Despite the accuracy of these property predictions, they have limited practical utility in industry, where specific property ranges are essential for processes. To address this, Genetic Algorithms (GA) are employed to design chemical compounds that meet industrial requirements. Integrating GA with ML could yield alternative chemical compounds, enhancing overall production processes by increasing economic potential, sustainability, and reducing environmental impact.
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A reaction database for small molecule pharmaceutical processes integrated with process information
(2017-12-01)
Papadakis, Emmanouil
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Anantpinijwatna, Amata
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Woodley, John M.
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Gani, Rafiqul
This article describes the development of a reaction database with the objective to collect data for multiphase reactions involved in small molecule pharmaceutical processes with a search engine to retrieve necessary data in investigations of reaction-separation schemes, such as the role of organic solvents in reaction performance improvement. The focus of this reaction database is to provide a data rich environment with process information available to assist during the early stage synthesis of pharmaceutical products. The database is structured in terms of reaction classification of reaction types; compounds participating in the reaction; use of organic solvents and their function; information for single step and multistep reactions; target products; reaction conditions and reaction data. Information for reactor scale-up together with information for the separation and other relevant information for each reaction and reference are also available in the database. Additionally, the retrieved information obtained from the database can be evaluated in terms of sustainability using well-known "green" metrics published in the scientific literature. The application of the database is illustrated through the synthesis of ibuprofen, for which data on different reaction pathways have been retrieved from the database and compared using "green" chemistry metrics.
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Modification of a solar thermal collector to promote heat transfer inside an evacuated tube solar thermal absorbe
(2021-05-01)
Supankanok, Rasa
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Sriwong, Sukanpirom
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Ponpo, Phisan
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Wu, Wei
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Chandra-Ambhorn, Walairat
Evacuated-tube solar collector (ETSC) is developed to achieve high heating medium temperature. Heat transfer fluid contained inside a copper heat pipe directly affects the heating medium temperature. A 10 mol% of ethylene-glycol in water is the heat transfer fluid in this system. The purpose of this study is to modify inner structure of the evacuated tube for promoting heat transfer through aluminum fin to the copper heat pipe by inserting stainless-steel scrubbers in the evacuated tube to increase heat conduction surface area. The experiment is set up to measure the temperature of heat transfer fluid at a heat pipe tip which is a heat exchange area between heat transfer fluid and heating medium. The vapor/ liquid equilibrium (VLE) theory is applied to investigate phase change behavior of the heat transfer fluid. Mathematical model validated with 6 experimental results is set up to investigate the performance of ETSC system and evaluate the feasibility of applying the modified ETSC in small-scale industries. The results indicate that the average temperature of heat transfer fluid in a modified tube increased to 160.32 °C which is higher than a standard tube by approximately 22 °C leading to the increase in its efficiency by 34.96%.
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Prediction of solvatochromic polarity parameters for aqueous mixed-solvent systems
(2020-12-01)
Duereh, Alif
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Anantpinijwatna, Amata
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Latcharote, Panon
Solvent polarity is important data being used in solvent selections for preliminary engineering design of chemical processes. In this work, a predictive model is proposed for estimating the solvatochromic polarity of electronic transition energy (E<inf>T</inf>) of Reichardt indicator for aqueous mixtures. To validate the model, the E<inf>T</inf> values of eighteen aqueous mixtures collected from the literature were used. The predictive model provided a good estimation of E<inf>T</inf> values with an overall deviation of 2.1%, compared with an ideal model (5.1%) from the mole fraction average. The linear relationship of the contribution factor of hydrogen bond donor interactions (CF<sup>HBD</sup>) in the predictive model with Kamlet–Taft acidity was newly proposed in order to extend the model for other aqueous mixtures. The predictive model is applicable to many aqueous mixtures and simply requires three properties of pure components as: (i) E<inf>T</inf> values, (ii) gas-phase dipole moment and (iii) Kamlet–Taft acidity.
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Experimental and Modelling Analysis of Liquid-Liquid Formation in Alcohol-mixed Gasoline Fuel
(2019-01-01)
Wongpromrat, Patthranit
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Rukquan, Muntira
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Anantpinijwatna, Amata
To tackle the environmental and sustainability problems, substituting gasoline, partially or solitary with bio-based alcohols becomes global practice. Bioethanol and biomethanol are being blended with gasoline in the ratio between 5-100 % by volume varying on the region. Various studies show positive impact of utilizing the blended fuel environmentally, while the others report the adequate efficiency of the blended fuel compare to the conventional gasoline; however, there were nearly no report on the failure or the shorten lifespan of the engine parts such as a high pressure pump (HPP) or an injector. It has been reported that water residue in the blended-bioethanol and biomethanol could cause the formation of the second liquid phase, leading to the chemical ageing reaction, which resulted in the corrosion of the HPP. To understand and prevent the damage, a quaternary behaviour of the blended gasoline-ethanol-methanol-water at the HPP operating condition is needed. In this work, an experimental study of the quaternary behaviour of the blended fuels has been conducted, the experimental data have been matching with the simulated results for better predictive of the mixture behaviour at different conditions. These results could potentially lead to limit or eliminate the HPP-corrosive problem.

Anantpinijwatna, Amata

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