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Created July 4, 2025 10:22
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IHI TRE Expected Performance Curve
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{
"cells": [
{
"cell_type": "markdown",
"id": "99c04e5a",
"metadata": {},
"source": [
"### Analisis Kurva Performa Kompresor Sentrifugal IHI TRE\n",
"\n",
"| **Suction Condition** | | **Design Condition** | |\n",
"|------------------------------|-------------|-----------------------------|---------------|\n",
"| Atmospheric Pressure | 0.1 MPa | Gas Type | N₂ |\n",
"| Suction Pressure | 0.105 MPa | Flow Rate | 6000 Nm³/h |\n",
"| Suction Temperature | 37 °C | Discharge Pressure | 0.62 MPaG |\n",
"| Humidity | 0% | Shaft Input Power | 560 kW |\n",
"| Cooling Water Temperature | 32 °C | Discharge Temperature | 40 °C |\n",
"\n",
"Referensi: [Ketika Kompresor Sentrifugal Tidak Sesuai Harapan – Peran Kurva Performa dalam Evaluasi Operasional](https://blog.kiiota.com/ketika-kompresor-sentrifugal-tidak-sesuai-harapan-peran-kurva-performa-dalam-evaluasi-operasional/)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a708dc73",
"metadata": {},
"outputs": [],
"source": [
"%pip install matplotlib\n",
"%pip install numpy\n",
"%pip install scipy"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "f353389f",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Inlet flow pada tekanan 610.00 kPaG: 6039.98 Nm³/h\n"
]
}
],
"source": [
"# Script: flow_vs_pressure.py\n",
"# Dibuat oleh: Ketut Kumajaya dengan bantuan AI (ChatGPT - OpenAI)\n",
"# Tujuan: Visualisasi hubungan antara flow dan pressure kompresor sentrifugal\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from scipy.interpolate import interp1d\n",
"\n",
"# Data mentah multiline dari WebPlotDigitizer\n",
"raw_data = \"\"\"\n",
"4919,472916557808; 0,7195637513128157\n",
"4961,3674412613655; 0,7189408390167136\n",
"5003,261965964924; 0,7178786433051867\n",
"5046,749422444929; 0,7163987718744562\n",
"5090,236878924934; 0,7151241370206238\n",
"5133,724335404939; 0,7134246238821809\n",
"5177,211791884944; 0,7114595618158561\n",
"5220,69924836495; 0,7093882801783788\n",
"5264,186704844955; 0,7070514496130196\n",
"5307,67416132496; 0,7044490701197788\n",
"5351,161617804965; 0,7015811416986562\n",
"5394,649074284971; 0,6986601034919573\n",
"5438,136530764976; 0,6948893087160368\n",
"5481,6239872449805; 0,6906936356555058\n",
"5525,111443724986; 0,686444852809398\n",
"5568,598900204992; 0,681930521035409\n",
"5612,086356684997; 0,6768850914056563\n",
"5655,573813165001; 0,6716803324191745\n",
"5699,061269645007; 0,6665286832182691\n",
"5742,548726125012; 0,6608459361616004\n",
"5786,0361826050175; 0,6551100793193552\n",
"5829,523639085022; 0,6488431246213466\n",
"5873,011095565028; 0,6421512916387273\n",
"5916,498552045033; 0,6347690314436156\n",
"5957,122744634297; 0,62810235684708\n",
"5999,986593379741; 0,6200937443448646\n",
"6036,964513983378; 0,6113243334639744\n",
"6073,5489711114105; 0,6026950239645685\n",
"6110,133428239442; 0,5930765530770257\n",
"6143,819347281424; 0,5827692403858173\n",
"6179,399993492337; 0,5704132487714808\n",
"6209,050532001432; 0,5581240237447262\n",
"6234,74766537598; 0,5456331079846517\n",
"6257,479744899619; 0,5317094925327202\n",
"6275,874648497887; 0,5187985036591112\n",
"6293,664971603344; 0,5060043563137697\n",
"6307,885660365079; 0,49395507371113667\n",
"6321,72257833599; 0,48137026743727573\n",
"6333,582793739628; 0,4690045390289168\n",
"6345,443009143266; 0,4559572350389951\n",
"6356,919453756079; 0,4406461264388817\n",
"6365,814615308807; 0,426186987315722\n",
"6377,352636300673; 0,4111540728305323\n",
"6385,717436498511; 0,396993570874681\n",
"6392,883870757817; 0,38186023252906587\n",
"6401,53645456024; 0,3671715832610942\n",
"6408,697491296; 0,354305105445873\n",
"6416,604301565093; 0,34067359381461126\n",
"6424,511111834185; 0,3267499783626797\n",
"6432,417922103276; 0,3129237308509716\n",
"6438,4132142406315; 0,30231062536663234\n",
"\"\"\"\n",
"\n",
"# Konversi string ke array\n",
"flow = []\n",
"pressure = []\n",
"\n",
"for line in raw_data.strip().split('\\n'):\n",
" # Ganti koma dengan titik agar bisa diproses sebagai angka float\n",
" line = line.replace(',', '.')\n",
" try:\n",
" f, p = map(float, line.split(';'))\n",
" flow.append(f)\n",
" pressure.append(p * 1000) # Konversi tekanan ke kPa\n",
" except ValueError:\n",
" # Lewati baris jika formatnya tidak sesuai\n",
" pass\n",
"\n",
"# print(\"Flow:\", flow)\n",
"# print(\"Pressure:\", pressure)\n",
"\n",
"# Data IGV 100%\n",
"inlet_100 = flow\n",
"pressure_100 = pressure\n",
"\n",
"\n",
"# Target pressures\n",
"target_pressure_100 = 610.0\n",
"target_pressure_design = 620.0\n",
"target_inlet_design = 6000.0\n",
"\n",
"\n",
"# Fungsi Moving Average\n",
"def moving_average(data, window_size):\n",
" return np.convolve(data, np.ones(window_size)/window_size, mode='valid')\n",
"\n",
"\n",
"# Fungsi gabungan smoothing dan interpolasi\n",
"def smooth_and_interpolate(inlet, pressure, window_size=5):\n",
" smoothed_inlet = moving_average(inlet, window_size)\n",
" smoothed_pressure = moving_average(pressure, window_size)\n",
" interp = interp1d(smoothed_inlet, smoothed_pressure, kind='linear')\n",
" inlet_smooth = np.linspace(min(smoothed_inlet), max(smoothed_inlet), 500)\n",
" pressure_smooth = interp(inlet_smooth)\n",
" return inlet_smooth, pressure_smooth\n",
"\n",
"\n",
"# Fungsi anotasi titik dengan panah\n",
"def annotate_point(x, y, label, color, offset=(60, 60)):\n",
" plt.plot(x, y, 'o', color=color)\n",
" plt.annotate(f'{label:.0f} Nm³/h', xy=(x, y),\n",
" xytext=(x + offset[0], y + offset[1]),\n",
" arrowprops=dict(facecolor=color, arrowstyle='->'), color=color)\n",
"\n",
"\n",
"# Proses smoothing dan interpolasi\n",
"inlet_100_smooth, pressure_100_smooth = smooth_and_interpolate(inlet_100, pressure_100)\n",
"\n",
"\n",
"# Titik pertemuan untuk tekanan target\n",
"target_inlet_100 = inlet_100_smooth[np.argmin(np.abs(pressure_100_smooth - target_pressure_100))]\n",
"\n",
"# Plot\n",
"plt.plot(inlet_100_smooth, pressure_100_smooth, color='black')\n",
"\n",
"# Garis horizontal\n",
"plt.axhline(y=target_pressure_100, color='red', linestyle='--')\n",
"plt.axhline(y=target_pressure_design, color='black', linestyle='--')\n",
"\n",
"# Garis vertikal\n",
"plt.axvline(x=target_inlet_100, color='red', linestyle='--')\n",
"plt.axvline(x=target_inlet_design, color='black', linestyle='--')\n",
"\n",
"# Anotasi target pressure\n",
"plt.text(inlet_100_smooth[0], target_pressure_100 + 5, f'{target_pressure_100:.2f} kPaG', color='red')\n",
"plt.text(inlet_100_smooth[0], target_pressure_design + 5, f'{target_pressure_design:.2f} kPaG', color='black')\n",
"\n",
"# Anotasi titik\n",
"annotate_point(target_inlet_100, target_pressure_100, target_inlet_100, 'red')\n",
"annotate_point(target_inlet_design, target_pressure_design, target_inlet_design, 'black')\n",
"\n",
"# Label dan style\n",
"plt.title(\"Inlet Flow vs Discharge Pressure TRE Cikande\", fontsize=14)\n",
"plt.xlabel(\"Inlet flow, Nm³/h\")\n",
"plt.ylabel(\"Discharge pressure, kPaG\")\n",
"plt.grid(True)\n",
"plt.tight_layout()\n",
"\n",
"# Simpan sebagai SVG\n",
"plt.savefig(\"TRE_Cikande_Flow_vs_Pressure.svg\", format='svg')\n",
"\n",
"# Tampilkan\n",
"plt.show()\n",
"\n",
"# Output\n",
"print(f\"Inlet flow pada tekanan {target_pressure_100:.2f} kPaG: {target_inlet_100:.2f} Nm³/h\")"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "6b9cf498",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Coupling power pada flow 6039.98 Nm³/h : 560.65 kW\n"
]
}
],
"source": [
"# Script: flow_vs_power.py\n",
"# Dibuat oleh: Ketut Kumajaya dengan bantuan AI (ChatGPT - OpenAI)\n",
"# Tujuan: Visualisasi hubungan antara flow dan power kompresor sentrifugal\n",
"\n",
"# Data mentah multiline dari WebPlotDigitizer\n",
"raw_data = \"\"\"\n",
"4924,531287018777; 514,9937081121434\n",
"4972,780113493805; 517,793274186462\n",
"5019,436583280936; 520,122570225446\n",
"5062,908339692271; 522,6662883465483\n",
"5106,380096103606; 524,6441448893561\n",
"5149,851852514941; 526,8364235142817\n",
"5193,3236089262755; 529,2342282602949\n",
"5236,79536533761; 531,289489471163\n",
"5280,267121748945; 533,6961901782074\n",
"5323,73887816028; 535,4685205999281\n",
"5367,210634571615; 537,3867643967383\n",
"5410,68239098295; 539,3050081935485\n",
"5454,154147394285; 541,6935220256937\n",
"5497,62590380562; 543,5241122797397\n",
"5541,097660216954; 544,9009886791114\n",
"5584,569416628289; 546,9623108550104\n",
"5624,336193800022; 548,4125626108539\n",
"5671,512929450959; 549,8276454727165\n",
"5714,984685862294; 551,4211376564463\n",
"5758,456442273629; 552,7845430399634\n",
"5801,928198684964; 554,0597903828889\n",
"5845,399955096298; 555,5508626732744\n",
"5888,871711507634; 556,7590041745134\n",
"5929,578959780256; 558,0513786941956\n",
"5965,678694488359; 558,8645872175111\n",
"6036,795532286813; 560,6725014833582\n",
"6071,052261569108; 561,5014343180887\n",
"6106,230493564308; 562,2393057839922\n",
"6149,702249975642; 562,9929015613106\n",
"6193,1740063869765; 563,6094799245711\n",
"6236,645762798313; 563,8400212709403\n",
"6280,117519209647; 563,9770386849982\n",
"6323,589275620981; 563,5570904817928\n",
"6363,375021180702; 562,7438819584772\n",
"6404,163361692059; 561,0129774078541\n",
"6442,532243528149; 558,9784252286922\n",
"\"\"\"\n",
"\n",
"# Konversi string ke array\n",
"flow = []\n",
"power = []\n",
"\n",
"for line in raw_data.strip().split('\\n'):\n",
" # Ganti koma dengan titik agar bisa diproses sebagai angka float\n",
" line = line.replace(',', '.')\n",
" try:\n",
" f, p = map(float, line.split(';'))\n",
" flow.append(f)\n",
" power.append(p) # Konversi tekanan ke kPa\n",
" except ValueError:\n",
" # Lewati baris jika formatnya tidak sesuai\n",
" pass\n",
"\n",
"# print(\"Flow:\", flow)\n",
"# print(\"Power:\", power)\n",
"\n",
"# Data IGV 100%\n",
"inlet_100 = flow\n",
"power_100 = power\n",
"\n",
"\n",
"# Target powers\n",
"target_inlet_100 = 6039.98\n",
"target_inlet_design = 6000.0\n",
"target_power_design = 560.0\n",
"\n",
"\n",
"# Fungsi Moving Average\n",
"def moving_average(data, window_size):\n",
" return np.convolve(data, np.ones(window_size)/window_size, mode='valid')\n",
"\n",
"\n",
"# Fungsi gabungan smoothing dan interpolasi\n",
"def smooth_and_interpolate(inlet, power, window_size=5):\n",
" smoothed_inlet = moving_average(inlet, window_size)\n",
" smoothed_power = moving_average(power, window_size)\n",
" interp = interp1d(smoothed_inlet, smoothed_power, kind='linear')\n",
" inlet_smooth = np.linspace(min(smoothed_inlet), max(smoothed_inlet), 500)\n",
" power_smooth = interp(inlet_smooth)\n",
" return inlet_smooth, power_smooth\n",
"\n",
"\n",
"# Fungsi anotasi titik dengan panah\n",
"def annotate_point(x, y, label, color, offset=(5, 5)):\n",
" plt.plot(x, y, 'o', color=color)\n",
" plt.annotate(f'{label:.2f} kW', xy=(x, y),\n",
" xytext=(x + offset[0], y + offset[1]),\n",
" arrowprops=dict(facecolor=color, arrowstyle='->'), color=color)\n",
"\n",
"\n",
"# Proses smoothing dan interpolasi\n",
"inlet_100_smooth, power_100_smooth = smooth_and_interpolate(inlet_100, power_100)\n",
"\n",
"\n",
"# Titik pertemuan untuk tekanan target\n",
"target_power_100 = power_100_smooth[np.argmin(np.abs(inlet_100_smooth - target_inlet_100))]\n",
"\n",
"# Plot\n",
"plt.figure(figsize=(10, 6))\n",
"plt.plot(inlet_100_smooth, power_100_smooth, color='black')\n",
"\n",
"# Garis horizontal\n",
"plt.axhline(y=target_power_100, color='red', linestyle='--')\n",
"plt.axhline(y=target_power_design, color='black', linestyle='--')\n",
"\n",
"# Garis vertikal\n",
"plt.axvline(x=target_inlet_100, color='red', linestyle='--')\n",
"plt.axvline(x=target_inlet_design, color='black', linestyle='--')\n",
"\n",
"# Anotasi target flow\n",
"plt.text(target_inlet_100 - 25, power_100_smooth[0], f'{target_inlet_100:.0f} Nm³/h', color='red', rotation=90, fontsize=10)\n",
"plt.text(target_inlet_design - 25, power_100_smooth[0], f'{target_inlet_design:.0f} Nm³/h', color='black', rotation=90, fontsize=10)\n",
"\n",
"# Anotasi titik\n",
"annotate_point(target_inlet_100, target_power_100, target_power_100, 'red')\n",
"annotate_point(target_inlet_design, target_power_design, target_power_design, 'black')\n",
"\n",
"# Label dan style\n",
"plt.title(\"Inlet Flow vs Coupling Power TRE Cikande\", fontsize=14)\n",
"plt.xlabel(\"Inlet flow, Nm³/h\")\n",
"plt.ylabel(\"Coupling power, kW\")\n",
"plt.grid(True)\n",
"plt.tight_layout()\n",
"\n",
"# Simpan sebagai SVG\n",
"plt.savefig(\"TRE_Cikande_Flow_vs_Power.svg\", format='svg')\n",
"\n",
"# Tampilkan\n",
"plt.show()\n",
"\n",
"# Output\n",
"print(f\"Coupling power pada flow {target_inlet_100:.2f} Nm³/h : {target_power_100:.2f} kW\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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