{"title":"Conceptual Design and Analysis of Small Power Station for Supporting Unmanned Aerial Vehicle (UAV) Deployment","authors":"Surya Alhadi, Suchada Rianmora, M. Phlernjai","doi":"10.4186/ej.2021.25.8.51","DOIUrl":"https://doi.org/10.4186/ej.2021.25.8.51","url":null,"abstract":"“Flight time” of unmanned aerial vehicle (UAV) or drone flying robot is the key component for supporting industrial activities. In practice, most battery-powered drones can fly 20 30 minutes for a single charging cycle. When the battery depleted, the drone is forced to come back to the station to recharge, or swap in a charged battery. However, these tasks are manually done by human multiple times. Aside from the inconvenience, human error and inappropriate force application may damage the socket compartment or loosen the locking system between battery and socket, making higher risk of the battery accidentally fall off from the socket during the flight. This research presents a “Small power station” to automatically load and unload battery from the drone’s mainframe with a constant force. The station has two main functions: drone positioning, and six-slot-battery exchange mechanism. Product design and development (PDD) and Kano analysis method were applied to properly list necessary compartments of the designed station. Finite element analysis (FEA) and kinematic calculation were applied to virtually check whether or not the developed platform was designed in the safety boundary. “DJI Matrice 100” drone was applied as the case study to demonstrate the proposed approach.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"990 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77127734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Watchara Uraisakul, B. Chalermsinsuwan, P. Piumsomboon
{"title":"Simulation of Process Structure and Operating Parameters on the Efficiency of the Chemical Looping Combustion Combined with Humid Air Turbine Cycle Using Statistical Experimental Design","authors":"Watchara Uraisakul, B. Chalermsinsuwan, P. Piumsomboon","doi":"10.4186/ej.2021.25.8.21","DOIUrl":"https://doi.org/10.4186/ej.2021.25.8.21","url":null,"abstract":"This study’s objective is to investigate the process structure and operating variables that affect the efficiency of the CLC combined with humid air turbine (HAT) unit to produce electricity. The investigation was carried out by using the Aspen Plus program with Peng-Robinson-Boston-Mathias (PR-BM) thermodynamics properties. In this study, the process structure and operating parameters were investigated. The process structure was related to process configuration, which reflected the number of compressor stages. The operating parameters were pressure, airflow rate, and compression methods. The four investigated responses consist of LHV efficiency, power production from the air reactor, work of air compressors, and air compressor discharge temperature. The 3k factorial experimental design was employed. After that, the result was analyzed by the analysis of variance (ANOVA). The result showed that the highest LHV efficiency was at 55.87 % when seven stages of compressors were used and the operating condition was at 15 atm of pressure in the air reactor, air compression using method 3, and 61,000 kmol/hr of airflow rate. The pressure and the method of compression highly affected LHV efficiency, as shown by their p-values. The pressure had the highest effect on LHV efficiency. The high pressure provided high power production. Method 3 provided the highest discharged temperature from the air compressor, which was the reason for the high power production in the air reactor. The compression ratio of the last compressor would be 65% of the pressure in the air reactor. Moreover, the efficiency could be improved to 57.67% by increasing the loading of Ni on the oxygen carrier from 25% to 40%. The benefit of the paper will be preliminary data for operation and investment decisions on a CLC power production because this result has not yet been demonstrated.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79388880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Kodaka, N. Leelawat, Yasushi Onda, Jing Tang, A. Laosunthara, Kumpol Saengtabtim, Piyaporn Sochoeiya, N. Kohtake
{"title":"Influential Factors on Aerosol Change During COVID-19 in Ayutthaya, Thailand","authors":"A. Kodaka, N. Leelawat, Yasushi Onda, Jing Tang, A. Laosunthara, Kumpol Saengtabtim, Piyaporn Sochoeiya, N. Kohtake","doi":"10.4186/ej.2021.25.8.187","DOIUrl":"https://doi.org/10.4186/ej.2021.25.8.187","url":null,"abstract":"Various interventions were made by the Thai government to prevent the COVID-19 spread by controlling socioeconomic activities, but the effectiveness of these interventions and other factors have not yet been fully clarified. Thus, this study aims to provide further scientific evidence on those potential factors which affect the socioeconomic activities changes during the pandemic, by using spatial analysis on atmospheric composition. By taking Phra Nakhon Si Ayutthaya Province, Thailand as the case area. Results of the government's COVID-19 measures and statuses of industries were compared with changes in aerosols, including PM 2.5 which was analyzed by Google Earth Engine with nine open datasets including meteorological and hydrological factors. The analysis revealed that the aerosol index in ueban area of the province decreased at 28.03% in 2020 compared in 2019. Besides, PM 2.5 drastically decreased from March 2020, even without the influence of wind speed which as the highest causal relationship, and kept low level compared with previous years. The reason of the tendency would be explained that other than government interventions including national-level state of the emergency decree, reduction of factories' activities at Rojana Industrial Park and reduction of the number of tourists had significant influence to reduce the mean value of PM 2.5.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74184182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Life Cycle Carbon Dioxide Emissions Assessment in the Design Phase: A Case of a Green Building in Vietnam","authors":"Dinh-Linh Le, The-Quan Nguyen, Khoa Do Huu","doi":"10.4186/ej.2021.25.7.121","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.121","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81516686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ngoc-Tri Ngo, H. Le, V. Huynh, Thi-Phuong-Trang Pham
{"title":"Machine Learning Models for Inferring the Axial Strength in Short Concrete-Filled Steel Tube Columns Infilled with Various Strength Concrete","authors":"Ngoc-Tri Ngo, H. Le, V. Huynh, Thi-Phuong-Trang Pham","doi":"10.4186/ej.2021.25.7.135","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.135","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73591974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment","authors":"Doan Hoang Tuan, N. Chiadamrong","doi":"10.4186/ej.2021.25.7.31","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.31","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84356840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Support Vector Machine for Regression of Ultimate Strength of Trusses: A Comparative Study","authors":"V. Truong, H. Pham","doi":"10.4186/ej.2021.25.7.157","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.157","url":null,"abstract":". Thanks to the rapid development of computer science, direct analyses have been increasingly used in the design of structures in lieu of member-based design methods using the effective length factor. In a direct analysis, the ultimate strength of a whole structure can be sufficiently estimated, so that the need for member capacity checks is eliminated. However, in complicated structural design problems where many structural analyses are required, the use of direct analyses requires an excessive computation cost. In such cases, Machine Learning (ML) algorithms are used to build metamodels that can predict the structural responses without performing costly structural analysis. In this paper, the support vector machine (SVM) algorithm is employed for the first time to develop a metamodel for predicting the ultimate strength of trusses using direct analysis. Several kernel functions for the SVM model, including linear, sigmoid, polynomial, radial basis function (RBF), are considered. A planar 39-bar nonlinear inelastic steel truss is taken to study the performance of the kernel functions. The results confirm the applicability of the SVM-based metamodel for predicting the ultimate strength of trusses. In particular, the RBF appears to be the best kernel among others. This investigation also provides a deeper understanding of the effect of the parameters on the efficiency of the kernel functions.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80133319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Coastal Upwelling Investigation in the Gulf of Thailand Using Ekman Transport and Sea Surface Temperature Upwelling Indices","authors":"Pacharamon Sripoonpan, Suriyan Saramul","doi":"10.4186/ej.2021.25.7.1","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.1","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77621192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Wongpatikaseree, Y. Kaewpitakkun, Sumeth Yuenyong, Siriwon Matsuo, P. Yomaboot
{"title":"EmoCNN: Encoding Emotional Expression from Text to Word Vector and Classifying Emotions—A Case Study in Thai Social Network Conversation","authors":"K. Wongpatikaseree, Y. Kaewpitakkun, Sumeth Yuenyong, Siriwon Matsuo, P. Yomaboot","doi":"10.4186/ej.2021.25.7.73","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.73","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73520044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing BIM Diffusion through Pilot Projects in Vietnam","authors":"Quynh To Thi Huong, E. Lou, Nam Le Thi Hoai","doi":"10.4186/ej.2021.25.7.167","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.167","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"94 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85472076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}