Monte Carlo Optimization of Two-Stage Cascade R134A Refrigeration System With Flash Chamber

2008 ◽  
Author(s):  
Yousef M. Abdel-Rahim
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Pressure Ratio ◽  
Volume Ratio ◽  
Heat Rate ◽  
Cycle Performance ◽  
Specific Work ◽  
Refrigeration System ◽  
Two Stage ◽  
Monte Carlo Optimization

Present paper studies the optimal characteristics of the two-stage cascade R134A refrigeration system with flash and mixing chambers over its operating ranges of all cycle controlling parameters. The COP, total heat rate in Qin, total work rate in Win and second law efficiency ηII are used as cycle performance parameters. Compared to the practically-limited other rate-based optimization methods and to other experimentally-optimized specific cases of cycle parameters, the application of Monte Carlo method has proved to be very effective for optimizing the cycle performance in its global sense over all cycle controlling parameters. Correlations relating performance and cycle controlling parameters are presented and discussed. Study shows that COP of the cycle can reach a value of 8 at intermediate pressure P2 of about 200 kPa, and a maximum value of 9.92 at about 370 kPa and 720 kPa, beyond which COP goes as low as 4.2. P2 alone has no significant effect on Qin, Win and ηII unless values of other controlling parameters are specified. Values of Qin, Win and ηII can reach as high as 94 kW, 23 kW and 0.85 and as low as 6.8 kW, 1.1 kW and 0.57 respectively depending on other cycle parameters. Neither pressure ratio nor volume ratio of the HP compressor has any effect on Qin, Win or ηII. However, the ratio of inlet to exit temperatures of the condenser has the greatest effect on both ηII and the volumetric specific work of the HP compressor, which is about double the value of the volumetric specific work of the LP compressor. Study shows an almost linear relationship between the two mass flow rates in the upper and lower loops of the cycle, where its value in the lower LP loop is about 75% that in the upper HP loop. Findings of the present work as well as the elaborate application of Monte Carlo method to real cycles can greatly open the way for reducing the trade-off design methods currently used in developing such systems as well as direct the useful experimentations and assessment of such designed systems.

Computing Profiles of Porosity and Surface/Volume Ratio in a Packed Bed Using Monte Carlo Method

2013 ◽  
Author(s):  
Genong Li
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Particle Diameter ◽  
Volume Ratio ◽  
Packed Bed ◽  
Diameter Ratio ◽  
Accuracy Requirement ◽  
Radial Profiles ◽  
Novel Method ◽  
Rigorous Error

Porosity and surface/volume ratio are two important parameters for a packed bed. In cylindrical packed beds at low tube-to-particle diameter ratio, they vary greatly in the radial direction. In the existing literature, radial profiles of porosity and surface/volume ratio have been computed using some analytical equations which involve elliptic integrals. In this paper, a Monte Carlo method is used to compute those profiles. To the authors’ knowledge, the method has never been employed in this context. The procedure of using this novel method is explained in detail. Through a rigorous error analysis based on statistics, the accuracy of the simulation result can be controlled. Before any simulation, the number of sampling points needed in the Monte Carlo simulation can be determined given an accuracy requirement. The method is completely general and can be used to compute profiles of porosity and surface/volume ratio in any packed bed with any shape of packing elements.

scholarly journals An efficient two-stage Markov chain Monte Carlo method for dynamic data integration

2005 ◽  
Vol 41 (12) ◽  
Author(s):  
Y. Efendiev ◽  
A. Datta-Gupta ◽  
V. Ginting ◽  
X. Ma ◽  
B. Mallick
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Monte Carlo Method ◽  
Data Integration ◽  
Two Stage ◽  
Dynamic Data

A two-stage procedure for determining the number of trials in the application of a Monte Carlo method for uncertainty evaluation

Metrologia ◽  
2010 ◽  
Vol 47 (3) ◽  
pp. 317-324 ◽  
Author(s):  
Gerd Wübbeler ◽  
Peter M Harris ◽  
Maurice G Cox ◽  
Clemens Elster
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Uncertainty Evaluation ◽  
Two Stage

Numerical simulation of gas flow through the flow part of a multi-stage turbomolecular vacuum pump

2020 ◽  
pp. 76-78 ◽  
Author(s):  
M.V. Fomin ◽  
O.R. Chernyishev
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Gas Flow ◽  
Pressure Ratio ◽  
Vacuum Pump ◽  
Maximum Pressure ◽  
Pump Impeller ◽  
Multi Stage ◽  
Turbomolecular Pump ◽  
Flow Through

The modeling of gas flow through a multi-stage flowing part of a turbomolecular vacuum pump to optimize the parameters of rotor and stator impeller wheels is considered. The developed program of statistical modeling by the Monte Carlo method allows us to determine the influence of the geometric parameters of the stages on the pump performance indicators. Keywords turbomolecular pump, impeller wheels, maximum action speed, maximum pressure ratio, Monte Carlo method. [email protected]

scholarly journals A Monte Carlo Approach to Estimate the Stability of Soil–Rock Slopes Considering the Non-Uniformity of Materials

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 590
Author(s):  
Aizhao Zhou ◽  
Xianwen Huang ◽  
Na Li ◽  
Pengming Jiang ◽  
Wei Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Slope Stability ◽  
Rock Slope ◽  
Monte Carlo Algorithm ◽  
Specific Work ◽  
Rock Slopes ◽  
The Monte Carlo Method ◽  
The Stability ◽  
Minimum Safety Factor

A soil–rock slope is a heterogeneous slope composed of soil and rocks that is widely distributed throughout the world. In order to accurately analyze the slope stability of soil–rock mixture, based on a Monte Carlo algorithm (fuzzy-based method), a symmetrical stability analyzing method for soil–rock slopes is proposed, considering the dispersion of strength of soil–rock mixtures. In analyzing it, the numerical model is symmetrical to the real soil–rock slope in geometry and material properties. In addition, the effect of rock content to slope stability was studied by this symmetrical method. The specific work of this paper is as follows: (1) The acquisition method of random number series for the Monte Carlo algorithm and the method of slope stability analysis, using the Monte Carlo method, are introduced. (2) According to in situ samples and remade samples, the strength characteristics of soil–rock mixtures were measured with different rock contents, which proved the scatter of strength of soil–rock mixtures. (3) Based on the measured strength parameters of soil–rock mixtures and the slope landslide, the reliability in analyzing results and superiority in calculating time of using the Monte Carlo method to analyze stability of soil–rock slopes are detailed. (4) The stability of soil–rock slopes with different rock content is discussed with the Monte Carlo method, and it is concluded that with the increase of rock content, the stability of a soil–rock slope decreases first and then increases, and the minimum safety factor is acquired at 20% rock content. (5) Based on a large number of calculation examples, the applied situations of the Monte Carlo method to analyze stability of soil–rock slopes are detailed according to sampling results and rock size.

Thermodynamic design of a reciprocating Joule cycle engine

2003 ◽  
Vol 217 (3) ◽  
pp. 239-246 ◽  
Author(s):  
M. A. Bell ◽  
T Partridge
Keyword(s):  
Thermal Efficiency ◽  
Pressure Ratio ◽  
Volume Ratio ◽  
Thermodynamic Cycle ◽  
Operating Conditions ◽  
Specific Work ◽  
Operating Pressure ◽  
Regenerative Heat ◽  
Pressure Drops ◽  
Swept Volume

This paper describes a first-order model of a Reciprocating Joule Cycle (RJC) engine, which is then used to investigate its thermodynamic design with a view to establishing its optimum performance for a given set of operating conditions. The RJC engine is essentially the reciprocating counterpart of the gas turbine. Its performance is determined by the characteristics of a reciprocating, as opposed to a rotodynamic, compressor and expander. The thermodynamic cycle investigated incorporates regenerative heat exchange. An air standard model modified to include the effects of friction, combustion, clearance volumes, leakage and pressure drops, shows that the performance of the RJC engine is strongly dependent on its operating pressure ratio and dependent to a much lesser extent on its expander to compressor swept volume ratio. It is shown that a thermal efficiency approaching 50 per cent might be achievable under realistic conditions. Using a maximum operating temperature of 1300 K, optimum thermal efficiency with a high specific work output occurs when its nominal operating pressure ratio is in the range 6 to 8, and its expander to compressor swept volume ratio is in the range 2 to 3. The RJC engine is proposed as a suitable prime mover for micro-CHP systems, small stand-alone power units, or hybrid vehicles.

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