scholarly journals Pemodelan Produksi Biogas pada Reaktor Tipe Batch Menggunakan Metode Hamming Predictor-Corrector

2019 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Ali Assegaf ◽  
Rian Febrian Umbara ◽  
Isman Kurniawan
Keyword(s):  
Anaerobic Digestion ◽  
Predictor Corrector

<p>Penelitian ini memiliki tujuan untuk membuat sebuah model prediksi hasil produksi biogas pada reaktor tipe <em>batch</em>. Simulasi pencernaan anaerobik akan glukosa sebagai substrat utama dengan konsentrasi awal 500 mgCOD/l, dan simulasi akan dilakukan selama 120 jam. Dalam penelitian ini juga bertujuan untuk mengetahui konsentrasi mikroorganisme yang terlibat dalam proses pencernaan anaerobik, serta akan dilakukan beberapa analisis seperti perbandingan metana yang dihasilkan pada simulasi dan eksperimen, pengaruh jumlah iterasi terhadap waktu yang dibutuhkan untuk melakukan <em>running </em>program, perbandingan jumlah glukosa dan mikroorganisme yang digunakan dalam simulasi terhadap jumlah metana yang akan dihasilkan. Untuk memprediksi jumlah produksi biogas, terdapat sebuah model yang umum digunakan yaitu <em>Anaerobic Digestion Model</em> <em>No 1</em> (ADM1). ADM1 dikembangkan oleh Asosiasi Water International (IWA) pada tahun 2002. Agar mendapatkan model yang memiliki akurasi yang tinggi akan digunakan sebuah metode numerik yaitu Hamming <em>Predictor-Corrector</em>. Setelah simulasi pencernaan anaerobik dilakukan, metana yang dihasilkan sebesar 417,48 MgCOD/l. Lalu mikroorganisme glukosa mengalami pertumbuhan yang maksimum jika dibandingkan dengan mikroorganisme lain yaitu sebesar 77 MgCOD/l. Konsentrasi awal substrat glukosa dan konsentrasi mikroorganisme yang digunakan pada proses simulasi sangat berpengaruh terhadap jumlah metana yang dihasilkan. Namun untuk konsentrasi awal mikroba yang lebih dari 30 MgCOD/l, cenderung menghasilkan metana yang konstan.</p>

Symmetric Multistep Methods Revisited: II. Numerical Experiments

1999 ◽  
Vol 173 ◽  
pp. 309-314 ◽  
Author(s):  
T. Fukushima
Keyword(s):  
Multistep Methods ◽  
Computational Time ◽  
Integration Time ◽  
Implicit Methods ◽  
Symmetric Methods ◽  
Celestial Bodies ◽  
The Stability ◽  
Predictor Corrector ◽  
Symmetric Multistep Methods ◽  
Integration Errors

AbstractBy using the stability condition and general formulas developed by Fukushima (1998 = Paper I) we discovered that, just as in the case of the explicit symmetric multistep methods (Quinlan and Tremaine, 1990), when integrating orbital motions of celestial bodies, the implicit symmetric multistep methods used in the predictor-corrector manner lead to integration errors in position which grow linearly with the integration time if the stepsizes adopted are sufficiently small and if the number of corrections is sufficiently large, say two or three. We confirmed also that the symmetric methods (explicit or implicit) would produce the stepsize-dependent instabilities/resonances, which was discovered by A. Toomre in 1991 and confirmed by G.D. Quinlan for some high order explicit methods. Although the implicit methods require twice or more computational time for the same stepsize than the explicit symmetric ones do, they seem to be preferable since they reduce these undesirable features significantly.

THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

2020 ◽  
Vol 2020 (57) ◽  
pp. 35-41
Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Error ◽  
Average Energy ◽  
Interpolation Formula ◽  
Wind Speed Prediction ◽  
Wind Generator ◽  
Prediction Horizon ◽  
Speed Prediction ◽  
Using Data ◽  
Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

Kinetics of Batch Anaerobic Digestion of Vegetable Oil Wastewater

2014 ◽  
Vol 2014 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Chinenyenwa Nweke ◽  
◽  
Philomena Igbokwe ◽  
Joseph Nwabanne ◽  
◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Vegetable Oil ◽  
Kinetics Of ◽  
Oil Wastewater

Anaerobic Digestion of Slaughterhouse Wastewater: A Kinetics Study

2014 ◽  
Vol 2014 (2) ◽  
pp. 71-80
Author(s):  
Chinenyenwa Nweke ◽  
◽  
Philomena Igbokwe ◽  
Joseph Nwabanne ◽  
◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Kinetics Study ◽  
Slaughterhouse Wastewater

Anaerobic Digestion Treatment of Soft Drink Wastewater

2015 ◽  
Vol 2 (1) ◽  
pp. 25-35 ◽  
Author(s):  
Chinenyenwa Nweke ◽  
◽  
Joseph Nwabanne ◽  
Philomena Igbokwe ◽  
◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Soft Drink ◽  
Soft Drink Wastewater

Application of the IWA Anaerobic Digestion Model (ADM1) for the Valorization of Maize Residues in Morocco

2019 ◽  
Vol 7 (6) ◽  
pp. 220
Author(s):  
Mohamed Amine Bellahkim ◽  
Kamal Gueraoui ◽  
Moad Mahboub ◽  
Mohamed Taibi ◽  
Rihab Belgada ◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Maize Residues
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