Meta-heuristic algorithms in car engine design: A literature survey
MH Tayarani-N, X Yao, H Xu - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution
of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of …
of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of …
Internal combustion engine calibration using optimization algorithms
Engine calibration is a process of optimizing engine settings so that optimal engine
performance, like minimum fuel consumption, minimum pollutant gas emissions, maximum …
performance, like minimum fuel consumption, minimum pollutant gas emissions, maximum …
Application of artificial neural network to forecast engine performance and emissions of a spark ignition engine
Increasing the application of machine learning algorithms in engine development has the
potential to reduce the number of experimental runs and the computation cost of …
potential to reduce the number of experimental runs and the computation cost of …
A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity & …
This research aims to understand the impacts of volume concentration of Fe 3 O 4
nanoparticles and temperature on the viscosity & thermal conductivity of liquid paraffin …
nanoparticles and temperature on the viscosity & thermal conductivity of liquid paraffin …
Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II
Z Chen, X Yuan, B Ji, P Wang, H Tian - Energy Conversion and …, 2014 - Elsevier
Fractional-order PID (FOPID) controller is a generalization of traditional PID controller using
fractional calculus. Compared to the traditional PID controller, in FOPID controller, the order …
fractional calculus. Compared to the traditional PID controller, in FOPID controller, the order …
Experimental investigation and develop ANNs by introducing the suitable architectures and training algorithms supported by sensitivity analysis: measure thermal …
A Shahsavar, S Khanmohammadi, D Toghraie… - Journal of Molecular …, 2019 - Elsevier
The objective of this experimental investigation is to assess the variations of thermal
conductivity and viscosity of liquid paraffin-Al 2 O 3 nanofluid containing oleic acid surfactant …
conductivity and viscosity of liquid paraffin-Al 2 O 3 nanofluid containing oleic acid surfactant …
Performance and emission characteristics of a CI engine using nano particles additives in biodiesel-diesel blends and modeling with GP approach
The performance and the exhaust emissions of a diesel engine operating on nano-diesel-
biodiesel blended fuels has been investigated. Multi wall carbon nano tubes (CNT)(40, 80 …
biodiesel blended fuels has been investigated. Multi wall carbon nano tubes (CNT)(40, 80 …
Response surface methodology (RSM) based multi-objective optimization of fusel oil-gasoline blends at different water content in SI engine
The main objective of this study is to determine the optimal blend ratio of fusel oil–gasoline
before and after water extraction (FBWE10, FBWE20, FAWE10, and FAWE20) regarding the …
before and after water extraction (FBWE10, FBWE20, FAWE10, and FAWE20) regarding the …
Exergoeconomic multi-objective optimization of an externally fired gas turbine integrated with a biomass gasifier
S Khanmohammadi, K Atashkari… - Applied Thermal …, 2015 - Elsevier
This study deals with thermodynamic and economic analysis of a combined gas turbine and
Organic Rankine Cycle integrated with a biomass gasifier. A modified model is used to …
Organic Rankine Cycle integrated with a biomass gasifier. A modified model is used to …
Cooperative coevolutionary surrogate ensemble-assisted differential evolution with efficient dual differential grouping for large-scale expensive optimization problems
This paper proposes a novel algorithm named surrogate ensemble assisted differential
evolution with efficient dual differential grouping (SEADECC-EDDG) to deal with large-scale …
evolution with efficient dual differential grouping (SEADECC-EDDG) to deal with large-scale …