Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

ABSTRAKValve adalah alat mekanis yang mengatur aliran atau tekanan cairan. Fungsinya adalah menutup atau membuka aliran, mengontrol laju aliran, mengalihkan aliran, mencegah aliran balik, mengontrol tekanan, atau mengurangi tekanan. Masalah yang umumnya ditemui adalah penutupan valve tidak sempurna dikarenakan adanya kotoran-kotoran yang menghalangi penutupnya untuk menutup secara sempurna. Penanganannya yang paling sederhana yaitu membersihkan dudukan dari kotoran-kotoran tadi secara intensif dan dilakukan pelumasan. Penelitian ini bertujuan untuk menjelaskan gambaran tentang simulasi aliran pada ball valve dan butterfly valve. Dan menjelaskan perbandingan tekanan, temperatur dan kecepatan distribusi air pada dua jenis valve. Tekanan fluida pada kondisi tertutup berbeda dengan kondisi terbuka. Hal ini akan berdampak terhadap kekuatan ball valve dan butterfly valve. Tekanan yang besar atau melebihi spesifikasi akan mempengaruhi mekanisme kerja dan kekuatan material. Pengaruh tekanan ini menjadi sangat penting dalam ball valve dan butterfly valve karena tekanan fluida dengan temperatur, pada kondisi tertentu bisa di luar batas spesifikasi khususnya pada ball valve Sanitary SS316 Mounting Pad 3 inci dan butterfly valve Sanitary SS 304 3 inci. Metode yang digunakan adalah Computational Fluid Dynamics dengan bantuan Software Flow Simulasi Solidwork 2014.Kata Kunci: Ball and Butterfly Valve, Solidwork, Flow Simulasi, CFD, Tekanan, Temperatur, Kecepatan aliran. ABSTRACTValves are mechanical devices that regulate fluid flow or pressure. Its function can close or open the flow, control the flow rate, divert flow, prevent backflow, control pressure, or reduce pressure. The problem commonly encountered is that the valve closure is not perfect due to the impurities that prevent the cover from closing completely. The simplest handling is to clean the holder from the dirts earlier and do lubrication. This study aims to explain the description of the flow simulation on ball valve and butterfly valve. This study also explain the comparison of pressure, temperature and velocity of water distribution in two types of valve heads. Fluid pressure under closed conditions is different from opening conditions. This will affect the strength of the ball valve and butterfly valve as a valve. Pressure that is large or exceeds specifications will affect the working mechanism and material strength. The effect of this pressure becomes very important in the ball valve and butterfly valve because of fluid pressure with temperature under certain conditions it can be out of the specification limits, especially in Sanitary SS316 Mounting Pad 3-inch ball valve and SS 304 3 inch Sanitary butterfly valve. This method was used in research is Computational Fluid Dynamics by utilizing of Flow Simulation Solidwork 2014 Software.Keywords: Ball Valve, Butterfly Valve, Solidwork 2014, Flow Simulation, CFD, Pressure, Temperature, Velocity

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A Rapid and Computationally Inexpensive Method to Virtually Implant Current and Next-Generation Stents into Subject-Specific Computational Fluid Dynamics Models

Annals of Biomedical Engineering ◽

10.1007/s10439-010-0238-5 ◽

2011 ◽

Vol 39 (5) ◽

pp. 1423-1437 ◽

Cited By ~ 32

Author(s):

Timothy J. Gundert ◽

Shawn C. Shadden ◽

Andrew R. Williams ◽

Bon-Kwon Koo ◽

Jeffrey A. Feinstein ◽

...

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Next Generation ◽

Inexpensive Method ◽

Subject Specific ◽

Dynamics Models

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Computational fluid-dynamics models

Numerical Weather and Climate Prediction ◽

10.1017/cbo9780511763243.016 ◽

2012 ◽

pp. 401-406

Author(s):

Thomas Tomkins Warner

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Dynamics Models

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SIMULASI DISTRIBUSI TEMPERATUR DAN KELEMBABAN RELATIF RUANGAN DARI SISTEM DEHUMIDIFIKASI MENGGUNAKAN COMPUTATIONAL FLUIDS DYNAMICS (CFD)

ROTASI ◽

10.14710/rotasi.19.1.1-11 ◽

2017 ◽

Vol 19 (1) ◽

pp. 1

Author(s):

Eflita Yohana ◽

Bambang Yunianto ◽

Ade Eva Diana

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Flow Simulation ◽

Liquid Desiccant ◽

Humidity Ratio ◽

Computational Fluids Dynamics ◽

Computational Fluids ◽

Computational Fluid Dynamics Cfd

Dehumidifikasi merupakan proses pengurangan kadar uap air yang berpengaruh terhadap besar nilai kelembaban relatif dan temperatur suatu ruangan. Dalam mengkondisikan kadar uap air dalam suatu ruangan tersebut agar dapat sesuai dengan kebutuhan, maka perlu diketahui distribusi kelembaban relatif dan temperatur dalam ruangan menggunakan Computational Fluid Dynamics (CFD). Pada penelitian ini, pengambilan data dilakukan selama 20 menit dan dilakukan pada pukul 08.00 WIB. Liquid desiccant yang digunakan dijaga pada temperatur 10°C dengan variasi konsentrasi 40% dan 50%. Sensor DHT 11 dipasang pada lima sisi, atap, dinding, lantai, inlet, outlet, yang berfungsi untuk mencatat perubahan kelembaban dan temperatur selama pengujian berlangsung. Pada kondisi normal tanpa menyalakan alat dehumidifier, sensor mencatat temperatur rata-rata di dalam ruangan sebesar 29,9°C dan RH 58,9%. Simulasi dilakukan menggunakan software CFD Solidworks Flow Simulation 2014. Validasi hasil eksperimen dengan hasil simulasi dengan membandingan bahwa liquid desiccant 40% dan 50%, nozzle sprayer 0.2 mm dengan temperatur yang dijaga pada 10°C mempunyai distribusi yang cukup merata dengan konsentrasi 40% memiliki nilai RH terendah sebesar 65,21%, nilai RH tertinggi sebesar 68,99%, nilai ω = 18 gr/kg, serta mempunyai temperatur tertinggi 31,11°C dan temperatur terendah 30,05°C. Sedangkan dengan konsentrasi 50% distribusi dalam ruangan juga cukup merata karena memiliki nilai RH terendah sebesar 59,21%., nilai RH tertinggi sebesar 62,80%, nilai ω = 17 gr/kg, serta mempunyai temperatur tertinggi 31,71°C dan temperatur terendah 30,93°C. Sehingga liquid desiccant dengan konsentrasi 50% mempunyai nilai Humidity Ratio (ω) lebih rendah dibandingkan dengan yang memiliki konsentrasi 40%.

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Model order reduction in aerodynamics: Review and applications

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410019853472 ◽

2019 ◽

Vol 233 (15) ◽

pp. 5816-5836

Author(s):

Gonçalo Mendonça ◽

Frederico Afonso ◽

Fernando Lau

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Model Reduction ◽

Adaptive Sampling ◽

Stokes Equations ◽

Order Reduction ◽

High Fidelity ◽

Least Mean Squares ◽

Speed Up ◽

Dynamics Models

The need of the aerospace industry, at national or European level, of faster yet reliable computational fluid dynamics models is the main drive for the application of model reduction techniques. This need is linked to the time cost of high-fidelity models, rendering them inefficient for applications like multi-disciplinary optimization. With the goal of testing and applying model reduction to computational fluid dynamics models applicable to lifting surfaces, a bibliographical research covering reduction of nonlinear, dynamic, or steady models was conducted. This established the prevalence of projection and least mean squares methods, which rely on solutions of the original high-fidelity model and their proper orthogonal decomposition to work. Other complementary techniques such as adaptive sampling, greedy sampling, and hybrid models are also presented and discussed. These projection and least mean squares methods are then tested on simple and documented benchmarks to estimate the error and speed-up of the reduced order models thus generated. Dynamic, steady, nonlinear, and multiparametric problems were reduced, with the simplest version of these methods showing the most promise. These methods were later applied to single parameter problems, namely the lid-driven cavity with incompressible Navier–Stokes equations and varying Reynolds number, and the elliptic airfoil at varying angles of attack for compressible Euler flow. An analysis of the performance of these methods is given at the end of this article, highlighting the computational speed-up obtained with these techniques, and the challenges presented by multiparametric problems and problems showing point singularities in their domain.

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