scholarly journals Parametric Optimization of Medical Plastic Wastes Conversion into Transportation Fuel using Mamdani Fuzzy Inference Systems (FIS)

2020 ◽  
Vol 8 (6) ◽  
pp. 1438-1446
Keyword(s):  
Liquid Fuel ◽  
Catalyst Concentration ◽  
Fuzzy Inference ◽  
Batch Reactor ◽  
Maximum Yield ◽  
Value Added ◽  
Transportation Fuel ◽  
Inference System ◽  
Plastic Wastes ◽  
Medical Plastic

Rapid growth of medical plastic wastes required attention for its scientific disposal along with conversion into value added products. Pyrolysis method is found suitable process for such conversion of such wastes into liquid oil. The experiment was carried out with the medical plastic wastes collected from local medicals and treated in a batch reactor taking appropriate range of temperature change and use of Calcium bentonite (CB) and Zeolite-A (ZA) as catalysts. The yield of liquid oil, gas and char produced from the process are collected in scale. The yield of liquid fuel in this process was influenced by factors such as temperature, catalyst concentration and acidity of catalyst. It was observed that yield of liquid fuel in this process were significantly dependent on temperature, nature of catalyst and catalyst concentration. The maximum yield of oil reported at 500 C and even increased by adding 20% by weight of CB as catalyst and 10% by weight of Z-A. In this study, Mamdani Fuzzy inference System (FIS) is used in order to measure the performance of the process and can be analyzed with more objectives, oriented through mathematical modelling and simulation. Mamdani Fuzzy inference was also introduced to identify the significant factors affecting the response and helps to determine the best possible factor level of combination. Finally, a regression model for liquid fuel from catalytic degradation of medical plastic wastes has been developed and mapped as a function of process parameters.

Rule-based fuzzy inference system for estimating the influent COD/N ratio and ammonia load to a sequencing batch reactor

2006 ◽  
Vol 53 (1) ◽  
pp. 199-207 ◽  
Author(s):  
Y.J. Kim ◽  
H. Bae ◽  
J.H. Ko ◽  
K.M. Poo ◽  
S. Kim ◽  
...  
Keyword(s):  
Fuzzy Inference System ◽  
Sequencing Batch Reactor ◽  
Fuzzy Inference ◽  
Batch Reactor ◽  
Rule Generation ◽  
Decision Tree Algorithm ◽  
Inference System ◽  
Rule Based ◽  
Close Relationship ◽  
Rule Set

A fuzzy inference system using sensor measurements was developed to estimate the influent COD/N ratio and ammonia load. The sensors measured ORP, DO and pH. The sensor profiles had a close relationship with the influent COD/N ratio and ammonia load. To confirm this operational knowledge for constructing a rule set, a correlation analysis was conducted. The results showed that a rule generation method based only on operational knowledge did not generate a sufficiently accurate relationship between sensor measurements and target variables. To compensate for this defect, a decision tree algorithm was used as a standardized method for rule generation. Given a set of inputs, this algorithm was used to determine the output variables. However, the generated rules could not estimate the continuous influent COD/N ratio and ammonia load. Fuzzified rules and the fuzzy inference system were developed to overcome this problem. The fuzzy inference system estimated the influent COD/N ratio and ammonia load quite well. When these results were compared to the results from a predictive polynomial neural network model, the fuzzy inference system was more stable.

scholarly journals The influence of PET and PBT contamination during transportation fuel production via pyrolysis

2021 ◽  
Vol 15 (1) ◽  
pp. 82-87
Author(s):  
Zsolt Dobó ◽  
Tamara Mahner ◽  
Balázs Hegedüs ◽  
Gábor Nagy
Keyword(s):  
Batch Reactor ◽  
Value Added ◽  
Oil Production ◽  
Gas Analysis ◽  
Plastic Waste ◽  
Piping System ◽  
Pyrolysis Oil ◽  
Fuel Production ◽  
Transportation Fuel ◽  
Transportation Fuels

The pyrolysis of plastic waste is a promising method to reduce waste accumulation while it could provide value-added transportation fuels. The main goal of this study is to investigate the influence of PET and PBT contamination during plastic pyrolysis oil production utilizing HDPE, LDPE, PP, and PS mixtures as these plastics are good candidates for transportation fuel production via pyrolysis and distillation. Seven different waste blends were prepared and pyrolyzed in a laboratory-scale batch reactor equipped with reflux. Mass balance, gas analysis, thermogravimetric analysis, and deposit formation were evaluated. It was concluded that by increasing the PET or PBT concentration in the initial solid waste mixtures, the oil production decreases while the amount of gases increases. Additionally, either PET or PBT generates operational difficulties due to they form deposits in piping system in form of benzoic acid. The maximum concentration of these plastic waste materials was 20% (PET) and 25% (PBT) in this study as further increase blocked the cross-section of piping, causing operational difficulties. Based on the obtained results the concentration of PET and PBT should be limited in waste mixtures when transportation fuel production is desired.

scholarly journals Production of Liquid Hydrocarbons from Plastic Wastes

2019 ◽  
Vol 4 (4) ◽  
pp. 345-350
Author(s):  
Zsolt Dobó ◽  
Gergő Kecsmár ◽  
Zsófia Jakab ◽  
Gábor Nagy ◽  
Tamás Koós
Keyword(s):  
Fuel Consumption ◽  
Batch Reactor ◽  
Value Added ◽  
Spark Ignition Engine ◽  
Transportation Fuels ◽  
Exhaust Gas Emission ◽  
Plastic Wastes ◽  
Commercial Gasoline ◽  
Pyrolysis Oils ◽  
Fuel Blending

Thermal pyrolysis of HDPE, LDPE, PP and PS plastic wastes were performed in a batch reactor and the yields of pyrolysis oils and liquid transportation fuels prepared by atmospheric distillation were determined. The gasoline fractions were tested in a traditional spark-ignition engine without any modifications or fuel blending. Fuel consumption and exhaust gas emission (NOx, CO) were measured and compared to a commercial fuel (RON = 95). PS generated 70.5% gasoline range hydrocarbons from the solid waste, followed by PP with 42.1%, LDPE with 40.8% and HDPE with 37.3%. The fuel consumption was reduced by 9.1-9.4% in the case of PS compared to reference measurement. Reduction in fuel consumption was noticeable at HDPE, LDPE and PP as well. PS gasoline decreased by 91-96%, while HDPE, LDPE and PP more likely increased the CO emission of the engine compared to commercial gasoline. The results show that pyrolysis of plastic wastes is a promising method to generate value added liquid transportation fuels and reduce the footprint of waste accumulation in landfills.

Aplikasi Peramalan Kebutuhan Beban Listrik Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS)

2017 ◽  
Vol 3 (1) ◽  
pp. 36-48
Author(s):  
Erwan Ahmad Ardiansyah ◽  
Rina Mardiati ◽  
Afaf Fadhil
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy

Prakiraan atau peramalan beban listrik dibutuhkan dalam menentukan jumlah listrik yang dihasilkan. Ini menentukan  agar tidak terjadi beban berlebih yang menyebabkan pemborosan atau kekurangan beban listrik yang mengakibatkan krisis listrik di konsumen. Oleh karena itu di butuhkan prakiraan atau peramalan yang tepat untuk menghasilkan energi listrik. Teknologi softcomputing dapat digunakan  sebagai metode alternatif untuk prediksi beban litrik jangka pendek salah satunya dengan metode  Adaptive Neuro Fuzzy Inference System pada penelitian tugas akhir ini. Data yang di dapat untuk mendukung penelitian ini adalah data dari APD PLN JAWA BARAT yang berisikan laporan data beban puncak bulanan penyulang area gardu induk majalaya dari januari 2011 sampai desember 2014 sebagai data acuan dan data aktual januari-desember 2015. Data kemudian dilatih menggunakan metode ANFIS pada software MATLAB versi b2010. Dari data hasil pelatihan data ANFIS kemudian dilakukan perbandingan dengan data aktual dan data metode regresi meliputi perbandingan anfis-aktual, regresi-aktual dan perbandingan anfis-regresi-aktual. Dari perbandingan disimpulkan bahwa data metode anfis lebih mendekati data aktual dengan rata-rata 1,4%, menunjukan prediksi ANFIS dapat menjadi referensi untuk peramalan beban listrik dimasa depan.

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Pengaruh Jenis Co-Solvent terhadap Rendemen dan Mutu Biodiesel secara Transesterifikasi In Situ Menggunakan Radiasi Gelombang Mikro

2016 ◽  
Vol 10 (2) ◽  
pp. 119-126
Author(s):  
Mahlinda Mahlinda ◽  
Fitriana Djafar
Keyword(s):  
Catalyst Concentration ◽  
Maximum Yield ◽  
Acid Value ◽  
Experimental Result ◽  
In Situ Transesterification ◽  
Yield And Quality ◽  
Solvent Type ◽  
Biodiesel Quality

The main purpose of this research was to observer effect co-solvent type (n-Hexane, chloroform and without co-solvent)  toward yield and quality of biodiesel via in situ transesterification process using microwave irradiation. The process was studied at microwave power 450 watt, reaction time 4 minutes, methanol to seed ratio 25:1 and catalyst concentration 5%. The physicochemical parameters of the biodiesel produced such as viscosity, density and acid value were analysed and compared with the SNI 7182-2012 standard. The experimental result showed the maximum yield biodiesel 78,32% obtained by using co-solvent chloroform.Test result of physicochemical properties (viscosity, density and acid value) of biodiesel products using co solvent n-Hexane, chloroform and without co solvent showed that these products conform to the SNI 7182-2012 standars. The type of co-solvent only affectedon biodiesel yield dan not affected on biodiesel quality (viscosity, density and acid value).  ABSTRAKTujuan penelitian ini adalah untuk mempelajari pengaruh jenis co-solvent (n-Hexane, chloroform dan tanpa co-solvent) terhadap rendemen dan mutu biodiesel secara trasesterifikasi in situ menggunakan radiasi gelombang mikro. Proses dilakukan pada daya gelombang mikro 450 watt, waktu reaksi 4 menit, perbandingan berat metanol terhadap bahan baku 25:1 dan jumlah katalis 5%. Parameter fisiko kimia dari produk biodiesel seperti viskositas, densitas dan angka asam di analisa dan dibandingkan dengan standar SNI 7182-2012 tentang biodiesel. Hasil penelitian menunjukkan rendemen maksimum biodiesel sebesar 78,32% diperoleh dengan menggunakan co-solvent chloroform. Hasil pengujian  karakteristik fisiko kimia (viskositas, densitas dan angka asam) dari produk biodiesel menggunakan co-solvent n-Hexane, chloroform dan tanpa co-solvent menunjukkan bahwa semua parameter ini masih memenuhi standar SNI 1782-2012 tentang biodiesel. Jenis co-solvent hanya berpengaruh pada rendemen biodiesel dan tidak berpengaruh terhadap mutu biodiesel (viskositas, densitas dan bilangan asam).Kata kunci: co-solvent, in situ transesterifikasi, microwave, rendemen, mutu   

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