Numerical Optimization of the β-Type Stirling Engine Performance Using the Variable-Step Simplified Conjugate Gradient Method
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Numerical Optimization of the β-Type Stirling Engine Performance Using the Variable-Step Simplified Conjugate Gradient Method
Authors
Keywords
-
Journal
Energies
Volume 14, Issue 23, Pages 7835
Publisher
MDPI AG
Online
2021-11-24
DOI
10.3390/en14237835
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Exchanging data between computational fluid dynamic and thermodynamic models for improving numerical analysis of Stirling engines
- (2021) Chin‐Hsiang Cheng et al. Energy Science & Engineering
- Development of a beta‐type Stirling heat pump with rhombic drive mechanism by a modified non‐ideal adiabatic model
- (2020) Chin‐Hsiang Cheng et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Numerical Optimization of a Four-Cylinder Double-Acting Stirling Engine Based on Non-Ideal Adiabatic Thermodynamic Model and SCGM Method
- (2020) Chin-Hsiang Cheng et al. Energies
- Optimization of a Stirling Engine by Variable-Step Simplified Conjugate-Gradient Method and Neural Network Training Algorithm
- (2020) Chin-Hsiang Cheng et al. Energies
- Numerical and experimental study of a compact 100‐W‐class β‐type Stirling engine
- (2020) Chin‐Hsiang Cheng et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Numerical model for predicting the performance and transient behavior of a gamma-type free piston Stirling engine
- (2020) Hang-Suin Yang APPLIED THERMAL ENGINEERING
- A novel methodology on beta-type Stirling engine simulation using CFD
- (2019) Bryan Castro Caetano et al. ENERGY CONVERSION AND MANAGEMENT
- Dynamic performance analysis and optimization of dish solar Stirling engine based on a modified theoretical model
- (2019) Xiaotian Lai et al. ENERGY
- A complete model for dynamic simulation of a 1-kW class beta-type Stirling engine with rhombic-drive mechanism
- (2018) Hang-Suin Yang et al. ENERGY
- Modelling and parametric study of an efficient Alpha type Stirling engine performance based on 3D CFD analysis
- (2017) Ahmad K. Almajri et al. ENERGY CONVERSION AND MANAGEMENT
- Enhanced thermodynamic modelling of a gamma-type Stirling engine
- (2016) S. Alfarawi et al. APPLIED THERMAL ENGINEERING
- Multi-objective optimization of a Stirling heat engine using TS-TLBO (tutorial training and self learning inspired teaching-learning based optimization) algorithm
- (2016) Vivek Patel et al. ENERGY
- Multi-objective thermo-economic optimization of solar parabolic dish Stirling heat engine with regenerative losses using NSGA-II and decision making
- (2016) Rajesh Arora et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm
- (2014) Chen Duan et al. ENERGY CONVERSION AND MANAGEMENT
- Theoretical and experimental study of a 300-W beta-type Stirling engine
- (2013) Chin-Hsiang Cheng et al. ENERGY
- Application of the multi-objective optimization method for designing a powered Stirling heat engine: Design with maximized power, thermal efficiency and minimized pressure loss
- (2013) Mohammad H. Ahmadi et al. RENEWABLE ENERGY
- Numerical model for predicting thermodynamic cycle and thermal efficiency of a beta-type Stirling engine with rhombic-drive mechanism
- (2010) Chin-Hsiang Cheng et al. RENEWABLE ENERGY
- Dynamic simulation of a beta-type Stirling engine with cam-drive mechanism via the combination of the thermodynamic and dynamic models
- (2010) Chin-Hsiang Cheng et al. RENEWABLE ENERGY
- Thermodynamic analysis of a gamma type Stirling engine in non-ideal adiabatic conditions
- (2008) Nezaket Parlak et al. RENEWABLE ENERGY
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started