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"Summary:A unified theory of multiphase flows, providing tools for practical applications"

"Starting from fundamentals of classical stability theory, an overview is given of the transition phenomena in subsonic, wall-bounded shear flows. At first, the consideration focuses on elementary small-amplitude velocity perturbations of laminar shear layers, i.e. instability waves, in the simplest canonical configurations of a plane channel flow and a flat-plate boundary layer. Then the linear stability problem is expanded to include the effects of pressure gradients, flow curvature, boundary-layer separation, wall compliance, etc. related to applications. Beyond the amplification of instability waves is the non-modal growth of local stationary and non-stationary shear flow perturbations which are discussed as well. The volume continues with the key aspect of the transition process, that is, receptivity of convectively unstable shear layers to external perturbations, summarizing main paths of the excitation of laminar flow disturbances. The remainder of the book addresses the instability phenomena found at late stages of transition. These include secondary instabilities and nonlinear features of boundary-layer perturbations that lead to the final breakdown to turbulence. Thus, the reader is provided with a step-by-step approach that covers the milestones and recent advances in the laminar-turbulent transition. Special aspects of instability and transition are discussed through the book and are intended for research scientists, while the main target of the book is the student in the fundamentals of fluid mechanics. Computational guides, recommended exercises, and PowerPoint multimedia notes based on results of real scientific experiments supplement the monograph. These are especially helpful for the neophyte to obtain a solid foundation in hydrodynamic stability."

"Gas suar bakar merupakan gas yang dihasilkan oleh kegiatan eksplorasi dan produksi atau pengolahan minyak atau gas bumi yang dibakar karena tidak dapat ditangani oleh fasilitas produksi atau pengolahan yang tersedia sehingga belum termanfaatkan. Berdasarkan data pemanfaatan gas bumi tahun 2016 yang dikeluarkan oleh ESDM, jumlah gas suar bakar di Indonesia masih cukup besar yaitu sebesar 214.3 MMSCFD. Gas to Liquid merupakan salah satu teknologi yang dapat digunakan dalam pemanfaatan gas suar bakar. Penggunaan teknologi ini membuat produk hasil pengolahan gas menjadi lebih mudah untuk didistribusikan. Penelitian ini bertujuan untuk mengetahui kelayakan teknis dan ekonomi pemanfaatan gas suar bakar dari lapangan onshore X dan lapangan offshore Y dan Z dengan menggunakan teknologi GTL. Metode yang digunakan pada penelitian ini adalah simulasi pemodelan proses dan perhitungan keekonomian. Dengan membuat rancangan simulasi proses sesuai dengan konversi pada reaktor microchannel pada pembuatan syngas dan syncrude, dihasilkan produk berupa syncrude, dari Lapangan X sebesar 714 bbl/day, Lapangan Y menghasilkan 557 bbl/day, sedangkan Lapangan Z sebesar 614 bbl/day. Pada perhitungan keekonomian, dengan menggunakan asumsi harga gas suar bakar 0.35 US$/MMBTU dan harga syncrude 57 US$/bbl, didapatkan IRR untuk Lapangan X sebesar 18.28%, Lapangan Y 13.29% dan Lapangan Z 26.47%.

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Gas flare is a gas produced by exploration activities and production or processing of oil or natural gas which is burned because it can not be handled by production or processing facilities that is available so it has not been utilized. Based on data of utilization of natural gas issued 2016 by ESDM, the amount of flare gas in Indonesia is still quite large that is equal to 214.3 MMSCFD. Gas to Liquid is one of the technologies that can be used in the utilization of flare gas. The use of this technology makes the product of gas processing becomes easier to distribute.

This study aims to determine the technical and economic viability of the use of flare gas from X onshore field and Y offshore field by using GTL technology. The method used in this research is the simulation of process modeling and economical calculation. By making process simulation with conversion for microchannel reactor on syngas and syncrude production, syncrude is produced from X Field with flowrate 714 bbl/day, whereas from Y Field is 557 bbl/day and Z Field produces 614 bbl/day. Then, the economic calculation obtained IRR result for X field 18.28%, Y Field 13.29% and Z Field 26.47%."

"In this project, Physics-Informed Neural Networks (PINNs) will be used to predict 2D unsteady flows. PINNs is a deep learning application to solve partial differential equations where neural networks learn from data and from physics. In this project, PINNs will be used to predict the velocity and pressure fields of a 2D unsteady flow by learning from the pressure and velocity data from flow simulations and fitting the output velocity and pressure data and its derivatives to the Navier-Stokes equations (NSE) as the governing equations. PINNs learns from data by developing a model that performs nonlinear regression on a set of training velocity and pressure data to produce a predicted output velocity and pressure values that is close to the training pressure and velocity data values. To learn from physics, the derivatives of the output velocity and pressure fields are computed which will be fitted into the Navier-Stokes equations. This becomes an optimization problem where the neural network needs to minimize the error of the predicted and training data and the error from fitting the data and the derivatives to the Navier-Stokes equations.PINNs will be implemented in 3 different scenarios, which are super resolution, data noise- filtering and pressure gradient prediction, and finally, time series prediction. In super resolution, the neural network will be trained with low resolution pressure and velocity field data to reconstruct accurate high-resolution velocity and pressure fields. In data noise- filtering and pressure gradient prediction, the neural network will be trained only with data from noisy velocity fields and no pressure data, mimicking data processing of Particle Image Velocimetry (PIV) measurements which will produce an accurate noise free velocity field and pressure gradient data. In time series prediction, the network will train with velocity and pressure fields at a limited time range and must predict the velocity and pressure data beyond the time range.The result of this project shows that PINNs make excellent tools to the field of experimental and computational fluid dynamics. PINNs can reconstruct accurate high- resolution velocity and pressure fields with less than 0.01 normalized error even if training data has a resolution 10 times smaller than the validation data. PINNs can also remove noise with a normalized error of less than 0.02 despite the noisy data having a 0.25 mean squared error. PINNs are however not effective enough to predict flows in a domain without training data or boundary conditions."

"Karakteristik pencampuran aliran gas dan cairan yang mengalir searah ke atas di dalam pipa vertikal yang dilengkai dengan static mixer diteliti secara numerik. Perbandingan dilakukan terhadap hasil dari simulasi komputasi fluida dinamika (CFD) dengan model Euler-Euler untuk tiga static mixer yang memiliki rasio antara panjang dan diameter (L/D) yang berbeda. Semua static mixer yang diuji pada studi ini memberikan kondisi pencampuran yang lebih baik dibandingkan dengan pipa yang tidak dilengkapi dengan static mixer. Kenaikan kekuatan putaran yang diindikasikan oleh velocity curl dari cairan dapat diamati dari hasil simulasi pada lokasi dimana aliran gas-cairan memasuki zona di dalam static mixer. Velocity curl cairan tertinggi diperoleh dengan menggunakan static mixer yang memiliki L/D terkecil pada jarak aksial terkecil yang memberikan proses pencampuran yang paling efektif diantara static mixer yang diuji pada penelitian ini. Karakteristik pencampuran terbaik yang ditunjukkan oleh distribusi gas radial diperoleh dengan menggunakan static mixer dengan L/D terkecil"