Computational Fluid Dynamic (CFD)

𝜕𝑡(𝜌Υ_𝑖) + ∇. (𝜌𝜈Υ_𝑖) = −∇. 𝐽_𝑖+ 𝑅_𝑖 + 𝑆_𝑖 (3.27)

Dimana 𝑅_𝑖adalah net rate of production of species I oleh reaksi kimia, dan karena sistem yang digunakan tidak terjadi reaksi maka nilai ini menjadi nol. 𝑆_𝑖 adalah rate of creation oleh penambahan dari dispersed phase dan atau referensi yang digunakan oleh penulis. Persamaan ini akan diselesaikan dengan N-1 species, dimana N total fase fluida yang ada didalam campuran. Pada persamaan diatas juga, 𝐽_𝑖adalah diffusion flux dari species i yang akan meningkat sejalan dengan peningkatan konsentrasi dan temperatur. Secara aturan, ANSYS menggunakan dilute approximation, dimana diffusion flux dapat ditulis sebagai :

𝐽_𝑖 = −𝜌𝐷_𝑖,𝑚∇Υ_𝑖 (3.28)

Disini 𝐷_𝑖,𝑚 adalah diffusion coefficient untuk species i didalam campuran. (El-Amin, 2011)

II.8 Computational Fluid Dynamic (CFD)

Computational Fluid Dynamic adalah metode penyelesaian numerik dari aliran fluida, heat transfer, dan fenomena sejenisnya. Dengan bantuan computer digital, CFD dapat prediksi kuantitatis dari peristiwa aliran fluida berdasarkan hukum konservasi (massa, momentum, dan energi) dari governing fluid motion. Prediksi ini akan terjadi pada beberapa kondisi seperti dalam geometri aliran (kecepatan, tekanan, dan temperatur), physical properties dari fluida, dan kondisi awal dimulainya aliran.

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Gambar III.9 Proses Penyelesaian CFD

Dalam penyelesaian aliran fluida, terlebih dahulu perlu diketahui physical properties dari fluida menggunakan fluid mechanics. Setelah itu, dapat digunakan persamaan matematis untuk mendeskripsikan physical properties menggunakan persamaan Stokes dan governing equation dari ANSYS FLUENT. Dikarenakan persamaan Navier-Stokes bersifat analisis dan dibuat oleh manusia, diperlukan untuk menerjamahkan persamaan yang ada menjadi bentuk diskret, seperti metode Finite Difference, Finite Element, dan Finite Volume . Setelah itu, program dapat digunakan untuk menyelesaikan permasalahan. Pada hasil akhir, kita mendapat hasil dari simulasi dan dapat dibandingkan dengan data yang diperoleh secara eksperimen. Terdapat beberapa keuntungan dan kesalahan umum yang dapat terjadi pada saat menggunakan CFD sebagai metode penyelesaian

Tabel III.7 Kelebihan dan Kesalahan Umum yang Terjadi pada Penggunaan CFD

Kelebihan Kesalahan Umum

Dapat diproduksi secara murah dan cepat tanpa effort training yang cukup besar, meskipun pengalaman penggunaan akan sangat membantu pengoperasian simulasi

Discretization error,

error intrinsic pada metode numerik

Dapat menghasilkan informasi yang menyeluruh secara detail dan komprehensif untuk segala jenis variabel

yang ingin dipelajari

Input Data Error,

Kesalahan ini muncul ketika geometri aliran dan property dari fluida memiliki

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Kelebihan Kesalahan Umum

Kemampuan untuk mensimulasikan sesuai dengan kondisi realistic yang ada, dimana

jika pada eksperimen membutuhkan rangkaian alat baik pada skala kecil

maupun besar

Modelling error,

Kesalahan ini muncul ketika aliran kompleks terjadi dan membutuhkan beberapa parameter khusus yang belum

pernah dilakukan studi sebelumnya

kemampuan untuk melakukan simulasi secara ideal, dimana beberapa kondisi yang tidak diinginkan dapat diabaikan sehingga studi dapat lebih terfokuskan

(Howard Hu, 2012) III.9 Penelitian Terdahulu

Table III.8 Penelitian Terdahulu

No. Peneliti Judul Penelitian Hasil Penelitian

1. Zhang et al. 2016

Hydrodynamics and Mass Transfer Analysis of Vapor-Liquid Flow of

Dual-Flow Tray

It has been found that high point efficiency areas are concentrated around the wall for its longer contact time. Comparison between the fluctuating regime and the froth regime shows that the froth regime has higher and homogeneous point efficiency at bulk zone around the center.

2. Rahimi, Rahbar. 2015

Hydrodynamics of Sieve Tray Distillation Column Using CFD Simulation

CFD simulations prior to constructing the trays are beneficial

3. Xingang Li et al. 2015

Investigation and Simulation on the Performance of the Elliptical Tray Placed in

the Unconventional “s” Shape Distillation Column

Elliptical sieve tray has less channeling, recirculation , stagnant zones and a longer average residence time than circular sieve tray which provides a better basis for mass-transfer

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No. Peneliti Judul Penelitian Hasil Penelitian

4. Rahimi, Rahbar et al. 2011 Effects of Inlet Downcomer on the Hydrodynamics Parameters of Sieve Trays

Using CFD Analysis

The inlet downcomer has a great effect on mass transfer in distillation and absorption columns

5. Ali Zarei et al. 2013

CFD and Experimental studies of Liquid Weeping in the Circular Sieve Trays

Columns

The numerical model predicted the behavior of liquid weeping on the different positions of the tray similarlyto the experimental findings. the majority of liquid volumefraction appears near the wall and along the centerline of thetray in x-direction, whereas, the gas bubbles prevail betweenthese regions. The oscillatory behavior of the liquid weepingwas revealed by changes in the gas velocity profile along thetest tray with time. This proves that CFD works well with to provide information on the details of the gas and liquid flows in the distillation column containing circular sieve trays. 6. Gondosuroha rdjo. 2019 Comparison of Performance Characteristic Prediction

of Sieve Tray with and without Downcomer

The sieve tray without downcomer showed a 50% higher capacity compared to the sieve tray with downcomer. Meanwhile, sieve tray without has 40% lower pressure drop compared to that with downcomer. Sieve trays show smaller efficiency compared to that with downcomer.

7. Meng Tang et al. 2019

Hydrodynamics of the Tridimensional Rotational

Flow Sieve Tray in a Countercurrent

Gas-Liquid Column

(1) According to the increasing range of the pressure drop, the operating field can be divided into low and high loading areas. The increasing range is relatively small in the low loading area with the increase of the gas-liquid flux. The

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No. Peneliti Judul Penelitian Hasil Penelitian

increasing range is large in the high loading area, which is mainly due to the water head loss formed by the foam liquid layer on the surface of the tray. (2) The flow patterns formed when gas-liquid flows out of the tray are droplet-column and continuous film flows. A foam liquid layer will be accumulated on the surface of the tray in the high loading area. As the gas-liquid flux increases, the height of the liquid layer will gradually rise until the flooding occurs, and the liquid volume inside the tray will be correspondingly reduced.

(3) Pressure drops of the trays at different installed locations are different, showing that the gas-liquid load is unbalanced. The situation is slightly better when trays are in backward installation, but the load of the third and fifth trays is also low.

(4) Compared with the TRST in concurrent flow operation, the pressure drop in the low loading area is similar, while it is far larger in the high loading area. The operating range of the gas-liquid flux is narrow. The range of gas flux is at least 45% less than that in concurrent flow, and the liquid flux range is at least 37.5% less. Compared with other new types of trays under countercurrent flow conditions, the pressure drop of the TRST is smaller, but the gas-liquid flux range is narrow.

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No. Peneliti Judul Penelitian Hasil Penelitian

(5) Established mathematical models for the loading curve, flooding curve and wet pressure drop fit well with the experimental data. The relative error is within 20%.

(6) The performance of the TRST under the gas-liquid countercurrent operation is not ideal. The structure of the TRST or process still requires more significant improvements.

8. Sumit Singh et al. 2012

Enchancement of Sieve Tray Efficiency using

Computational Fluid Dynamics Fluid

CFD can be used as a powerful tool for sieve tray design, simulation, visualization and troubleshooting, by means of CFD a virtual experiment can be developed to evaluate the tray performance .

9. Meng Tang et al. 2019

CFD simulation of gas flow field distribution and design optimization of the tridimensional rotational

flow sieve tray with different structural

parameters

(1) With the exception of the C1-type tray, the gas flow field distributions for all other types of trays are similar, and only the velocity magnitudes are different. Because the gradient of the blades in the C1-type tray is larger, the diversion and restriction of the blades is weaker, and the magnitude and the extent of the change in velocity are lower. The relative influence of the different structural parameters on the gas flow field distribution is b > ds > ht > n. (2) When two trays are installed, the gas flow field of the second tray in a forward installation is clearly different from that in a backward installation. This is mainly caused by the respectively identical or contrasting direction of the rotational gas flow and the twist direction of the blades.

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No. Peneliti Judul Penelitian Hasil Penelitian

The velocity distribution of the tray is also more stable in the forward installation, while it exhibits a large fluctuation in the backward installation. (3) The gas flow field distribution of those trays with either a closed internal cylinder or without a supporting ring is similar to that of the reference A-type tray, with only the velocity magnitude being different. In a tray without sieve holes there is no vortex generated in the flow field, and the magnitude and extent of velocity change are both relatively large.

(4) The transformed location of the rotational flow of in most types of trays is about half the depth of the tray. When the number of blades are increased (e.g. n = 12) and the tray is installed in the forward installation, the transformed location occurs earlier at about a quarter the depth of the tray. When the sieve hole diameter is small (ds = 3 mm), the transformed location is intermediate, at about a third of the depth.

(5) Based on our comprehensive evaluation, the optimized parameters for the tray structure are n = 8, b = 90, ht = 40 -

mmand ds = 5 mm. In addition, the tray should have an open internal cylinder without a supporting ring. When a multitray is installed, the backward installation method should be adopted.

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No. Peneliti Judul Penelitian Hasil Penelitian

10. Carlo Pirola et al. 2019

Learning distillation by a combined experimental and simulation approach

in a three steps laboratory: Vapor pressure, vapor-liquid

equilibria

The simulation of all these activities by a commercial software allows toverify the thermodynamc characteristics of the mixture and to ana-lyze the distillation column performance. The synergy of all thesedifferent activities can help the learning of the distillation principles. 11. Bin Jiang et

al. 2013

Hydrodynamics and Mass-Transfer Analysis of a

Distillation Ripple Tray by Computational

Fluid Dynamics Simulation

The study showed that mass transfer in the spray zone, where all of the downflow liquid comes into contact with the rising vapor, made a significant contribution to the tray efficiency. The additional mass transfer in the spray zone must be considered,especially at lower Fs factors. In addition, it has been obtained that the ripple tray efficiency increases with increasing Fs factor, unlike the tray with downcomers