A new thermal model based on polytropic numerical simulation of Stirling engines

Babaelahi, Mojtaba; Sayyaadi, Hoseyn

doi:10.1016/j.apenergy.2014.12.033

Cited by 89 publications

(85 citation statements)

References 25 publications

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“…Considering the fact that second order models [26e28] (and also newly developed first order closed-form models [17]) are more accurate and faster than these simplified third order models (CFD models), developing second order models for higher accuracy is mostly acquired, especially for optimization purposes. Therefore, the objective of this paper was to modify the recently developed second order models [28] for as higher accuracy as possible. In this regard, the present work attempted to correct previous PSVL models [28] of the authors so that polytropic heat losses of working spaces could be coupled to convective heat transfer models of those cylinders.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the objective of this paper was to modify the recently developed second order models [28] for as higher accuracy as possible. In this regard, the present work attempted to correct previous PSVL models [28] of the authors so that polytropic heat losses of working spaces could be coupled to convective heat transfer models of those cylinders. Thus, the polytropic indexes of expansion/compression spaces which calculated based on the gas and ambient temperatures in the original PSVL model [28] were corrected based on heat transfer thermal resistance between the working gas and environment.…”

Section: Introductionmentioning

confidence: 99%

“…They corrected their numerical results in terms of the effect of finite motion of the piston based on the theory of finite speed thermodynamics (FST), mechanical friction, and non-ideal performance of heat exchangers as well. In a most recent work, Babaelahi and Sayyaadi [28] developed a new thermal model (PSVL) based on polytropic expansion/compression processes. They developed their model based on the fact that, in a real engine, expansion/compression processes are neither isothermal nor adiabatic.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modified PSVL: A second order model for thermal simulation of Stirling engines based on convective–polytropic heat transfer of working spaces

Babaelahi

Sayyaadi

2015

Applied Thermal Engineering

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modified PSVL: A second order model for thermal simulation of Stirling engines based on convective–polytropic heat transfer of working spaces

Babaelahi

Sayyaadi

2015

Applied Thermal Engineering

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“…ACO was firstly presented by Marco Dorigo in 1992 [30,31] and is one of the most prominent classes of Swarm intelligence. This algorithm uses methods, including edge selection and pheromone update.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Higher order modeling of a free-piston Stirling engine: analysis and experiment

Zare

Shourangiz-Haghighi

2018

Int J Energy Environ Eng

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This paper focuses on higher order modeling and design of the free-piston Stirling engine (FPSE) based on Ant Colony Optimization (ACO). First, the governing thermodynamics and dynamical equations of the engine have been derived. Then, the design parameters of the engine are selected taking into account the finite heat transfer coefficient (resulting in a fifth-order model) and pressure drop (resulting in a sixth-order model) in the dynamical system and the corresponding differential equations are derived in detail. In the following, the mentioned methods and their performance in modeling the FPSE dynamics are investigated. The simulated results show that the effect of the pressure drop on the places of the closed-loop poles of the system is not significant, while the heat transfer coefficient has a considerable effect on the engine dynamics. Accordingly, a fifth-order model along with ACO algorithm is proposed to justify the FPSE behavior. To validate the presented modeling scheme, the prototype engine SUTECH-SR-1 was experimented. It is found that the values of parameters obtained from the proposed design method are close to those of the experiment. Besides, the presented higher order model predicts the engine behavior with an acceptable accuracy through which the validity of the design technique is affirmed. Initial pressure of working gas (Pa) P w Power generation (J/s) P Nonlinear pressure (Pa) R Ideal gas constant J kgVolume of expansion space m

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“…In these models, a variety of losses are quantified, and included in the analysis to predict the output of a real engine operating at specified conditions (Walker, 1980). In the most recent study, a model with polytropic working spaces has been developed (Babaelahi and Sayyaadi, 2015). A significant portion of Stirling cycle optimization studies have moved toward numerical simulations that in the past were too computationally expensive to use for optimization purposes.…”

Section: Introductionmentioning

confidence: 99%

Exergy Analysis and Optimization of an Alpha Type Stirling Engine Using the Implicit Filtering Algorithm

Wills

Bello‐Ochende

2017

Front. Mech. Eng.

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This paper presents the exergy analysis and optimization of the Stirling engine, which has enormous potential for use in the renewable energy industry as it is quiet, efficient, and can operate with a variety of different heat sources and, therefore, has multi-fuel capabilities. This work aims to present a method that can be used by a Stirling engine designer to quickly and efficiently find near-optimal or optimal Stirling engine geometry and operating conditions. The model applies the exergy analysis methodology to the ideal-adiabatic Stirling engine model. In the past, this analysis technique has only been applied to highly idealized Stirling cycle models and this study shows its use in the realm of Stirling cycle optimization when applied to a more complex model. The implicit filtering optimization algorithm is used to optimize the engine as it quickly and efficiently computes the optimal geometry and operating frequency that gives maximum net-work output at a fixed energy input. A numerical example of a 1,000 cm 3 engine is presented, where the geometry and operating frequency of the engine are optimized for four different regenerator mesh types, varying heater inlet temperature and a fixed energy input of 15 kW. The WN200 mesh is seen to perform best of the four mesh types analyzed, giving the greatest network output and efficiency. The optimal values of several different engine parameters are presented in the work. It is shown that the net-work output and efficiency increase with increasing heater inlet temperature. The optimal dead-volume ratio, swept volume ratio, operating frequency, and phase angle are all shown to decrease with increasing heater inlet temperature. In terms of the heat exchanger geometry, the heater and cooler tubes are seen to decrease in size and the cooler and heater effectiveness is seen to decrease with increasing heater temperature, whereas the regenerator is seen to increase in size and effectiveness. In terms of the regenerator mesh type, it was found that the WN200 mesh gave a shorter regenerator with greater cross-sectional flow area which gave a smaller pressure drop.

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A new thermal model based on polytropic numerical simulation of Stirling engines

Cited by 89 publications

References 25 publications

Modified PSVL: A second order model for thermal simulation of Stirling engines based on convective–polytropic heat transfer of working spaces

Modified PSVL: A second order model for thermal simulation of Stirling engines based on convective–polytropic heat transfer of working spaces

Higher order modeling of a free-piston Stirling engine: analysis and experiment

Exergy Analysis and Optimization of an Alpha Type Stirling Engine Using the Implicit Filtering Algorithm

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