Toward estimation of biodiesel production from castor oil using ANN

Nowadays, a green replacement for the conventional petrodiesel introduced as biodiesel in which its economical production way is using feedstock. Also, environmentally friendly fuels attracted more attention due to the serious global warming problem. In the present study, two different artificial intelligencebased modeling was utilized to predict the production of biodiesel from castor oil. Also, a comparison between the two methods was carried out, and the more applicable method for the prediction of biodiesel production was introduced. To this end, biodiesel production yield from castor oil assumed to be the target of the model and various parameters such as temperature (T), time (S), methanol to oil molar ratio, and catalyst weight (C) expected as input parameters. ANN modeling shows high accuracy and robustness for the prediction of biodiesel production, and statistical parameters such as coefficient of determination and root-mean-square error are 0.9984 and 1.13, respectively.     

Potential hybrid feedstock for biodiesel production in the tropics

Recently, mixture of different oils at various proportions have been used as feedstock for biodiesel production. The primary aim is to improve fuel properties which are strongly influenced by the fatty acid composition of the individual oil that makes up the feedstock mix. The tropics are renowned for abundant oil-bearing crops of which palm kernel oil (PKO) from palm seed and groundnut oil (GNO) are prominent. This present paper investigated biodiesel production from hybrid oil (HO) of PKO (medium carbon chain and highly saturated oil) and GNO (long carbon chain and highly unsaturated oil) at 50/50 (v/v) blending. The principal fatty acids (FAs) in the HO are oleic (35.62%) and lauric acids (24.23%) with 47.80% of saturated FA and 52.26% of unsaturated FA contents. The chemical conversion of the oil to methyl ester (ME) gave 86.56% yield. Fuel properties of hybrid oil methyl ester (the HOME) were determined in accordance with standard test methods and were found to comply with both ASTM D6751 and EN 14214 standards. The oxidative stability, cetane number and kinematic viscosity (KV) of HOME were observed to be improved when compared with those of GNO methyl ester from single parent oil, which could be accredited to the improved FA composition of the HO. The KV (3.69 mm²/s) of HOME obtained in this paper was remarkably low compared with those reported in literature for most biodiesels. This value suggests better flow, atomization, spray and combustion of this fuel. Conclusively, the binary blend of oils can be a viable option to improve the fuel properties of biodiesel feedstock coupled with reduced cost.     

Biodiesel production from neem towards feedstock diversification: Indian perspective

In developing countries like India where 70% of country's petroleum needs are met by import, energy security assumes significance in view of uncertainty of supply and increasing price of petroleum fuels. Fuels of bio origin not only provide energy security, but also reduce emissions of harmful pollutants and greenhouse gases and ensure rural upliftment by increasing employment in agricultural sector. India cannot afford to produce biodiesel from edible oil seeds as it is done in the American and European countries. Extensive focus has been given on producing biodiesel from non-edible sources, specifically from Jatropha. Discrepancies between the expectation and realities regarding Jatropha as a feedstock necessitate efforts for diversification of the feedstocks. Scientific research should therefore be directed towards oilseeds like Karanja, Sal, Mahua, Neem, etc. that are widely available and sustainable to the diverse socio-economic and environmental conditions of rural India. Among them the evergreen neem with its wide availability and various useful uses may be a potential feedstock for biodiesel production. In this paper attempts have been made to overview the morphology of neem tree, various useful uses, physical and chemical characteristics of neem oil and optimized production process for biodiesel production from neem oil.     

Biodiesel production from castor oil using potassium hydroxide as a catalyst: Simulation and validation

The key objective of the present research is to optimize and investigate the biodiesel production from ricinuscommunis (castor) oil using microwave-assisted hybrid transesterfication process under various conditions such as microwave power, treatment time, ethanol:oil ratio and catalyst concentration (KOH). Response surface methodology (RSM) coupled with four factors with a three-level Box–Behnken response surface design (BBD) was employed to model the transesterfication technique. The obtained results were analyzed by analysis of variance (ANOVA) and a second-order polynomial model was developed to study the interactive effect of process factors on biodiesel production. Derringer’s desired function methodology was used for the optimization and optimum conditions for maximizing the biodiesel production. Under optimum conditions, the predicted biodiesel production was found to be 95% with a desirability value of 0.998. The fuel properties of the produced biodiesel were compared with the ASTM D6751 standards.     

Biodiesel production from two stage esterification of simarouba glauca seed oil and its characterization

In this work, biodiesel was produced from simarouba glauca seed oil through a two-stage acid-alkali esterification process. Concentrated sulphuric acid and sodium hydroxide were used as catalysts for acid and alkaline catalyzed esterification process, respectively. The free fatty acid content of the oil was reduced from 3.5 to 0.2%. The major properties of oil and its biodiesel were studied. Upon two-stage esterification, kinematic viscosity was reduced from 45.75 to 3.1 cSt and the acid value was reduced from 6.9348 to 0.4 mg KOH/g. The measured physio-chemical properties are within the limits set by ASTM biodiesel standards.     

Biodiesel production from degummed Jatropha curcas oil using constant-temperature ultrasonic water bath

This paper studied tri-basic potassium phosphate for transesterification process with degummed crude Jatropha curcas oil using constant-temperature, ultrasonic water bath generating low-intensity pulses with good energy distribution converting the maximum amount of biodiesel. Tri-basic potassium phosphate is suitable for J. curcas oil when the free fatty acid (FFA) content is less than 2%. The optimal reaction levels are catalyst 1.0 wt%, temperature of 50°C, and methanol-to-oil molar ratio of 12:1. The yield is 98% after 45 min, at 20 kHz frequency. The catalytic activity is found similar to potassium hydroxide and the catalyst solubility is only 4.27 ppm.     

氨基磺酸非均相催化菜籽油及废油脂制备生物柴油

采用正交试验和单因素试验的方法研究了氨基磺酸催化菜籽油及废油脂与甲醇的酯交换过程,考察了醇油物质的量比、催化剂用量、反应温度和反应时间对反应收率的影响。结果表明:菜籽油酯交换的最佳反应条件为醇油物质的量比6∶1,氨基磺酸用量为原料油质量的1.0%,反应温度60℃,反应时间20 min,此工艺条件下,脂肪酸甲酯的收率达到95.6%;废油脂酯交换的最佳反应条件为醇油物质的量比8∶1,氨基磺酸用量为原料油质量的1.0%、反应温度65℃,反应时间30 min,此工艺条件下,脂肪酸甲酯的收率达到87.5%。利用红外光谱表征了菜籽油和生物柴油的结构,气相色谱分析了生物柴油的组成。     

Evaluation of Biodiesel Fuel Obtained from Waste Cooking Oil

Abstract

In this study, usage of methyl ester obtained from waste cooking oil (WCO) is evaluated as an alternative energy source. Potential of obtained biodiesel from WCO in the World and Turkey was determined. Physical and chemical properties of methyl ester were determined in the laboratory. The methyl ester was tested in a diesel engine with turbocharged, four cylinders and direct injection. Obtained results were compared with No. 2 diesel fuel. In addition, if WCO is evaluated as biodiesel, environmental pollution caused by waste cooking oil diminished.     

Biodiesel combustion: Advances in chemical kinetic modeling

Burgeoning global demand for energy has increased concerns about the fuel security issues and deleterious environmental impacts that result from the ubiquitous use of fossil fuels to meet these needs. This article is a review of completed work towards the goal of creating chemical kinetic mechanisms for biodiesel, which will aid in the development of clean and efficient combustors that utilize alternative fuels. As the composition of biodiesel is too complex to directly model, efforts have instead focused on the development of mechanisms for surrogates, simpler molecules that can produce the primary characteristics of biodiesel combustion. Research initially targeted smaller molecules like methyl butanoate to investigate the role of the characteristic ester group that is present in the fatty acid alkyl esters that comprise biodiesel. The study of isomers and similar unsaturated compounds elucidated the effects of molecular structure on combustion. Subsequent efforts involved the study of larger molecules that are close in scale to biodiesel molecules, such as methyl decanoate, as well as molecules that are present in biodiesel, such as methyl stearate. Applications of kinetic modeling demonstrate its utility in the study of combustion through, for example, revealing the chemistry in the early formation of CO₂ in biodiesel and its soot reduction tendencies. The results of this review illustrate key limitations in kinetic modeling, namely a need for high-pressure kinetic methodology and a need for continuous improvement of kinetic mechanisms through theory and experiment. These limitations suggest direction for future research; further experimental and theoretical work will produce accurate mechanisms for appropriate biodiesel surrogates. All of these efforts represent significant advances in kinetic modeling that are important towards the goal of building a predictive capability for biodiesel combustion. Such predictive capability will aid the development of combustion technologies that will help society meet its energy needs in an environmentally conscious manner.     

蓖麻油制备生物柴油的研究

研究了以蓖麻油为原料,采用化学酯交换方法制备生物柴油的工艺过程.测定了最佳反应条件：催化剂用量为油重的1.0%,甲醇用量为油重的20%,反应温度为65℃,反应时间为90 min,酯交换率可达到86%.     

A rapid ultrasound-assisted production of biodiesel from a mixture of Karanj and soybean oil

Karanj oil having high free fatty acid was neutralized with a dilute alkali solution and then mixed with soybean oil in different ratios in order to reduce the free fatty acid content significantly. The mixture of the oils was then transesterified with methanol to produce fatty acid methyl ester. The transesterification was carried out using ultrasonication energy of 20 kHz in pulse mode. It was found that up to 60% Karanj oil in the blended mixture could produce good quality biodiesel that met the ASTM standards. However, the lesser content of Karanj oil in the mixture, the lesser the reaction parameters viz. alcohol to oil molar ratio, catalyst concentration, and reaction time. About 99% yield of methyl esters was obtained when the Karanj oil content in the mixture was 20% with a reaction time of 30 min, catalyst concentration 1 wt%, and a temperature of 55°C.     

生物柴油转化效果测定方法的研究

生物柴油的生产原料、催化剂、工艺流程等存在多样化特点,为比较各种方法的优劣,需要建立一种适宜、通用的测定方法.通过分析国内外相关测定方法,提出以气相色谱测定反应产物,十七碳脂肪酸甲酯为标准物,内标法计算反应转化率和产率的方法.     

Biodiesel production from waste sunflower oil by using Amberlyst 46 as a catalyst

In this study, simultaneous transesterification and esterification of high acid value sunflower oil to fatty acid methyl esters was studied using Amberlyst 46 as a heterogeneous catalyst. The influence of reaction conditions such as molar ratio of methanol/oil, reaction time, and reaction temperature was investigated. The highest fatty acids methyl esters yield of 75.8% was obtained in presence of 6 wt% oleic acid content under reaction conditions of 20 wt% Amberlyst 46 catalyst amount, 6/1 methanol/oil molar ratio, reaction temperature of 130°C, and reaction time of 10 h.     

利用超临界技术制备生物柴油的研究现状

分析了超临界技术制备生物柴油的反应机理,重点阐述了温度、醇油比、压力、水、游离酸对超临界法制备生物柴油的影响.研究表明:超临界技术制备生物柴油在反应时间、对原料要求和产物回收等方面均具有传统碱催化法无法比拟的优势.展望了超临界技术制备生物柴油的工业应用前景,并对超临界技术制备生物柴油的研究提出了建议.     

超声波制备生物柴油技术的研究进展

超声波技术作为一门新兴的技术已受到普遍关注.文章综述了近年来国内外超声波技术在生物柴油制备中应用的研究现状、制备原理和优缺点,指出了该技术在生物柴油制备中须要解决的问题,在此基础上提出超声波制备生物柴油技术的发展方向,认为开发更优良的的制备工艺是今后超声波制备生物柴油技术研究领域的主要任务.     

Production of biodiesel from citrus maxima (Chakotara) seed oil,a potential of non-food feedstock and its blends with n butanol-diesel and purification,utilization of glycerol obtained as by-product from biodiesel

The aim of the study is to enhance the production and performance of biodiesel from non-food feedstock seeds of citrus maxima through base catalyzed transesterification process. The Performance of biodiesel was increased by the blends with butanol-diesel (Biodiesel + Butanol + Diesel) in different proportions. The obtained biodiesel and its blends were characterized by ASTM. In this study, Glycerol was obtained as a by-product of citrus maxima biodiesel. Crude glycerol was purified by the H₃PO₄, H₂SO₄, HCl, and HNO₃. The characterization of glycerol included Flash Point, ash Content, alkalinity, FT-IR, etc..     

Cyprinus carpio fish oil: A novel feedstock for biodiesel production

Biodiesel was developed from a novel nonedible oil source, namely Cyprinus carpio fish oil. The acid value of fish oil was very low (0.70 mg KOH/g oil, 0.35 free fatty acid content). As a result, biodiesel was produced through a one-step transesterifcation process, i.e. alkali-catalyzed transesterification with methanol. The optimal conditions for producing biodiesel from fish oil were investigated. The highest biodiesel yield (97.22% ~ 96.88% w/w ester content) was obtained under optimum conditions of 0.75% KOH w/w, 7:1 methanol to oil molar ratio, 60°C reaction temperature and 60-minute duration. Properties of the produced biodiesel as well as its blends with petro-diesel fulfilled the standard limits as prescribed by ASTM D6751 and EN 14214 indicating its suitability as a fuel for diesel engines.     

Biodiesel production from Cannabis sativa oil from Pakistan

The present study was appraised using response surface methodology for process optimization owing to strong interaction of reaction variables: NaOCH₃ catalyst concentration (0.25–1.50%), methanol/oil molar ratio (3:1–9:1), reaction time (30–90 min), and reaction temperature (45–65°C). The quadratic polynomial equation was determined using response surface methodology for predicting optimum methyl esters yield from Cannabis sativa oil. The analysis of variance results indicated that molar ratio and reaction temperature were the key factors that appreciably influence the yield of Cannabis sativa oil methyl esters. The significant (p < 0.0001) variable interaction between molar ratio × catalyst concentration and reaction time × molar ratio was observed, which mostly affect the Cannabis sativa oil methyl esters yield. The optimum Cannabis sativa oil methyl esters yield, i.e., 86.01% was gained at 53°C reaction temperature, 7.5:1 methanol/oil molar ratio, 65 min reaction time, and 0.80% catalyst concentration. The results depicted a linear relationship between observed and predicted values. The residual analysis predicted the appropriateness of the central composite design. The Cannabis sativa oil methyl esters, analyzed by gas chromatography, elucidated six fatty acid methyl esters (linoleic, α-linolenic, oleic, palmitic, stearic, and γ-linolenic acids). In addition, the fuel properties, such as kinematic viscosity at 40°C; cetane number; acid value; flash point; cloud, pour, and cold filter plugging points; ash content; density; and sulphur content, of Cannabis sativa oil methyl esters were evaluated and discussed with reference to ASTM D 6751 and EU 14214 biodiesel specifications.     

Accurate modeling of biodiesel production from castor oil using ANFIS

Research for finding alternative fuel sources has been concluded that the renewable fuels such as biodiesel can be used as an alternative to fossil fuels because of the energy security reasons and environmental benefits. In this contribution, transesterification of castor oil with methanol to form biodiesel has been modeled by using artificial neural network fuzzy interference system (ANFIS) approach. Methanol to oil molar ratio, catalyst amount (C), temperature (T), and time (S) were used as input parameters and fatty acid methyl ester yield was used as output parameter for modeling the efficiency of biodiesel production from castor oil. Obtaining low value of absolute deviation (2.2391), high value of R-squared (0.98704), and other modeling results proves that ANFIS modeling is an effective approach for biodiesel production from castor oil. In conclusion, comparison between our model and other previous predictive models reported in open literature indicates the priority of our model.     

Prediction of selected biodiesel fuel properties using artificial neural network

Biodiesel is an alternative fuel to replace fossil-based diesel fuel. It has fuel properties similar to diesel which are generally determined experimentally. The experimental determination of various properties of biodiesel is costly, time consuming and a tedious process. To solve these problems, artificial neural network (ANN) has been considered as a vital tool for estimating the fuel properties of biodiesel, especially from its fatty acid (FA) composition. In this study, four ANNs have been designed and trained to predict the cetane number (CN), flash point (FP), kinematic viscosity (KV) and density of biodiesel using ANN with logsig and purelin transfer functions in the hidden layer of all the networks. The five most prevalent FAs from 55 feedstocks found in the literature utilized as the input parameters for the model are palmitic, stearic, oleic, linoleic and linolenic acids except for density network with a sixth parameter (temperature). Other FAs that are present in the biodiesels have been considered based on the number of carbon atom chains and the level of saturation. From this study, the prediction accuracy and the average absolute deviation of the networks are CN (96.69%; 1.637%), KV (95.80%; 1.638%), FP (99.07%; 0.997%) and density (99.40%; 0.101%). These values are reasonably better compared to previous studies on empirical correlations and ANN predictions of these fuel properties found in literature. Hence, the present study demonstrates the ability of ANN model to predict fuel properties of biodiesel with high accuracy.