Published June 1, 2018 | Version v1
Journal article

Prediction of performace parameters using artificial neural network for 4-stroke C I engine fueled with esterified neem oil and biogas

  • 1. Mechanical Engineering, Sambhram Institute of Technology, Bengaluru (India)
  • 2. Mechanical Engineering, MSRIT, Bengaluru (India)

Description

Experiments on the technical feasibility of the use of esterified neem oil and biogas under dual fuel mode has been carried out in a 3.7 kW diesel engine. Esterified neem oil (ENO) blends and bottled biogas was used for the experimentation. Biogas is directly mixed with the inlet air in the induction manifold and tests were carried out for varying loads and pressures. The performance parameters obtained from test were within the acceptable range for ENO and biogas combination. Mechanical efficiency was improved and ENO consumption was reduced due to higher biogas introduction; however, a distinguishable noise was noticed when further increase in supply of biogas. Artificial neural network (ANN) technique was also applied for prediction of thermal efficiency and BSFC of the engine. The input parameters for ANN method were speed, gas flow rate, temperature, total fuel consumption, and load. It was seen that ANN predicted performance values were close to experimentally obtained data when 90% of data were in training set. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/376/1/012038

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
376
Journal Issue
1
Journal Page Range
[11 p.]
ISSN
1757-899X

Conference

Title
International Conference on Advances in Manufacturing, Materials and Energy Engineering
Acronym
ICon MMEE 2018
Dates
2-3 Mar 2018
Place
Moodbidri (India)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52082276
Subject category
S10: SYNTHETIC FUELS; S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
Resource subtype / Literary indicator
Conference
Descriptors DEI
DIESEL ENGINES; FLOW RATE; FUEL CONSUMPTION; FUELS; GAS FLOW; INDUCTION; MECHANICAL EFFICIENCY; METHANE; NEURAL NETWORKS; OILS; PERFORMANCE; THERMAL EFFICIENCY
Descriptors DEC
ALKANES; EFFICIENCY; ENERGY CONSUMPTION; ENGINES; FLUID FLOW; HEAT ENGINES; HYDROCARBONS; INTERNAL COMBUSTION ENGINES; ORGANIC COMPOUNDS; OTHER ORGANIC COMPOUNDS