Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Internal Combustion Engine01:20

Internal Combustion Engine

The internal combustion engine is a heat engine that uses the byproducts of combustion as the working fluid instead of using a heat transfer medium to transfer heat. The combustion is done in a way that produces high-pressure combustion products that can be expanded through a turbine or piston to create work. Internal combustion engines can again be categorized into three kinds: (1) spark ignition gasoline engines, most commonly used in automobiles, (2) compression ignition diesel engines that...
Turnover Number and Catalytic Efficiency01:19

Turnover Number and Catalytic Efficiency

The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
Chymotrypsin is a pancreatic enzyme that breaks down proteins during digestion. The...
Otto and Diesel Cycle01:27

Otto and Diesel Cycle

An Otto engine is a four-stroke engine that uses a mixture of gasoline and air as the working fuel. The fuel is injected into the cylinder, and the piston is moved completely down so that the cylinder is at maximum volume. By moving the piston up, adiabatic compression takes place. The spark plug ignites the gasoline-air mixture, and the burning fuel adds heat to the system at a constant volume. The heated mixture expands adiabatically and gets further cooled by exhausting heat, and this cyclic...
Batteries and Fuel Cells03:12

Batteries and Fuel Cells

A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
Heat Engines01:10

Heat Engines

A heat engine is a device used to extract heat from a source and then convert it into mechanical work used for various applications. For example, a steam engine on an old-style train can produce the work needed for driving the train.
Whenever we consider heat engines (and associated devices such as refrigerators and heat pumps), we do not use the standard sign convention for heat and work. For convenience, we assume that the symbols Qh, Qc, and W represent only the amounts of heat transferred...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Optimization of frying conditions for the development of <i>Moringa oleifera</i> leave-based tortilla chips and its quality evaluation.

Journal of food science and technology·2026
Same author

Functional and hypoglycemic dietary fiber from Queen pineapple peel waste by ultrasound-assisted alkaline extraction.

Scientific reports·2026
Same author

Sustainable synthesis and optimization of aluminium matrix composites reinforced with laboratory waste borosilicate glass for resource sustainability circularity.

Scientific reports·2026
Same author

Investigation of microstructure, mechanical properties and fracture behaviour of AA8011/TiB₂ composites for sustainable engineering applications.

Scientific reports·2026
Same author

Impact of Al<sub>2</sub>O<sub>3</sub> particles on the hardness, metallurgical and corrosion behaviour of Al 6061-10 wt. % Al<sub>2</sub>O<sub>3</sub> functionally graded composite.

Scientific reports·2026
Same author

Carbon nanotube reinforced soybean oil for sustainable machining of Monel 400: experimental investigation and FIS-based optimization.

Scientific reports·2026
Same journal

A tri-axis optomechanical accelerometer with plasmonic MIM waveguide and structural direction-dependent optical signatures.

Scientific reports·2026
Same journal

Holographic leaky-wave antennas with independently controlled multiple counter-rotating vortex beams.

Scientific reports·2026
Same journal

Differential associations of longitudinal hearing and vision trajectories with dementia and mild cognitive impairment in older adults.

Scientific reports·2026
Same journal

Abdominal obesity and leisure-time sedentary behavior in relation to gastroesophageal reflux disease risk: a prospective cohort study from the UK Biobank.

Scientific reports·2026
Same journal

Effect of nitrogen-rich COF incorporation on the structure and separation performance of polyamide nanofiltration membranes.

Scientific reports·2026
Same journal

Withanolide A inhibits hIAPP aggregation: An In silico, biophysical, and drosophila-based In vivo validation.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 25, 2026

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure
07:58

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure

Published on: January 18, 2021

Machine learning-driven optimization of performance and emissions in a butanol/diesel CI engine.

K Siva Prasad1, T R Vijaybabu2, G Kiran Kumar3

  • 1Department of Mechanical Engineering, GMR Institute of Technology (GMRIT)- Deemed to be University, Rajam, Andhra Pradesh, India. ksivaprasad286@gmail.com.

Scientific Reports
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

This study integrates experiments, CFD, and machine learning to optimize butanol-diesel blends in DI-CI engines. The developed model accurately predicts engine performance and emissions, showing high accuracy for specific fuel consumption and NOx.

Keywords:
CI engine optimizationCONVERGE CFDEnsemble learningHybrid modelingMachine learning

More Related Videos

A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

Related Experiment Videos

Last Updated: May 25, 2026

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure
07:58

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure

Published on: January 18, 2021

A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

Area of Science:

  • Internal Combustion Engines
  • Computational Fluid Dynamics (CFD)
  • Machine Learning for Engineering

Background:

  • Direct Injection-Compression Ignition (DI-CI) engines are crucial for efficient combustion.
  • Optimizing fuel blends and engine parameters is key to improving performance and reducing emissions.
  • Butanol-diesel blends offer potential as alternative fuels.

Purpose of the Study:

  • To develop a hybrid modeling framework for predicting and optimizing DI-CI engine performance and emissions.
  • To evaluate the effectiveness of an Optuna-optimized ensemble machine learning model.
  • To investigate the impact of key engine parameters on combustion and emission characteristics.

Main Methods:

  • Hybrid modeling integrating experimental data, CONVERGE CFD simulations, and Optuna-optimized ensemble machine learning.
  • Numerical analysis using CONVERGE CFD software.
  • Machine learning models were trained to predict Indicated Specific Fuel Consumption (ISFC) and emissions like Nitrogen Oxides (NOx) and Soot.

Main Results:

  • The Optuna-optimized ensemble Meta Model demonstrated high predictive accuracy for ISFC (R²=0.98) and NOx (R²=0.97).
  • The model achieved Root Mean Square Error (RMSE) below 5% for key parameters, indicating strong generalization.
  • Accurate estimations for Soot were also achieved, alongside performance metrics.

Conclusions:

  • The hybrid modeling framework is effective for predicting and optimizing DI-CI engine performance with butanol-diesel blends.
  • Ensemble machine learning, optimized with Optuna, provides a robust tool for engine calibration and emission control.
  • The study highlights the potential of butanol-diesel blends and optimized modeling for cleaner and more efficient engine operation.