Agustinus Winarno
Department Of Mechanical Engineering, Vocational College, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia

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The Origin, Physicochemical Properties, and Removal Technology of Metallic Porphyrins from Crude Oils Jumina Jumina; Yehezkiel Steven Kurniawan; Dwi Siswanta; Bambang Purwono; Abdul Karim Zulkarnain; Agustinus Winarno; Joko Waluyo; Johan Syafri Mahathir Ahmad
Indonesian Journal of Chemistry Vol 21, No 4 (2021)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijc.62521

Abstract

Crude oil is an indispensable energy feedstock for daily activities, although some amounts of metallic porphyrins components with undesired characteristics have been identified. These constituents are assumed to originate from the geochemical process of chlorophyll and heme derivatives. In addition, their chemical structures have been thoroughly characterized using spectroscopy techniques, while several analytical methods were adopted in the detection and concentration quantification in the crude oils. The metallic porphyrins have several demerits, including the deactivation of used catalysts, contamination of the treated petrochemical products, and corrosion of the industrial equipment. Also, the removal process is considered challenging due to the strong interaction with the asphaltene fraction of crude oil. This review article, therefore, provides brief information on the origin, physicochemical properties, and possible removal technology of metallic porphyrins from crude oil samples. Besides, a better understanding of chemistry contributes a useful insight towards the development and establishment of better futuristic processing technology.
PERMODELAN INVERSI PEREDAM MAGNET-REOLOGI BERBASIS JARINGAN SARAF TIRUAN UNTUK SISTEM KENDALI Rafly Asprilla Alwi; Irfan Bahiuddin; Ryandhi Rofifu Chazim; Agustinus Winarno; Fitrian Imaduddin
Jurnal Rekayasa Mesin Vol. 13 No. 2 (2022)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jrm.v13i2.962

Abstract

The application of artificial neural network (ANN) models in magnet-rheological damper modeling is of great interest in recently challenges. Therefore, this study aims to propose a solution to overcome this problem by conducting inverse modeling using an artificial neural network. This inverse model is applied to a meandering magnet-rheological valve damper to predict the current to produce the appropriate damping force. The simulation scheme is selected with current as output and damping force, velocity, and displacement as input. The best model is formulated by varying the architecture of the artificial neural network. The best artificial neural network architecture is obtained after doing these variations. The data is divided into 80% training data, 10% validation data, and 10% test data. The activation function used is a logsig function using three hidden layers with the number of neurons in each layer [30-20-30]. The algorithm used in the chosen architecture is Levenberg-Marquardt. The regression value of 0.991 and the MSE value of 0.001 were obtained from the modeling results. The required damping force is ensured that it can be predicted well using the selected artificial neural network. The test proves that the results of the regression constant are 0.999 and the MSE value is 0.0005 when the current output value is inverted to the damper artificial neural network.