Performance analysis of a novel oil-free rotary compressor

2018 ◽  
Vol 232 (7) ◽  
pp. 870-887 ◽  
Author(s):  
Balázs Farkas ◽  
JenőMiklós Suda
Keyword(s):  
Genetic Algorithm ◽  
Rotary Compressor ◽  
Model Parameters ◽  
State Variables ◽  
Manufacturing Tolerances ◽  
Rolling Piston ◽  
Conventional Rolling ◽  
The Mathematical Model ◽  
Conventional Oil ◽  
Amesim Simulation

A novel rotating piston-type compressor is presented. The conventional rolling piston architecture was redesigned to allow oil-free operation. The spring activated vane was replaced by a directly driven swinging vane to provide constant contact to the rotating piston. The model of the compressor was implemented in the AMESim simulation platform. Experiments were conducted on prototypes and the data were evaluated based on the simulation results. Directly unobservable geometric dimensions were estimated by adjusting the mathematical model parameters to the measured thermodynamic state variables with the use of a multi-parametric genetic algorithm. The simple genetic algorithm proved fast and adequate solutions. According to the collected results, the oil-free rotating piston architecture is significantly more sensitive to the sealing clearances compared to the conventional oil lubricated rolling piston compressors. Therefore, the theoretically estimated performance can only be achieved with extremely small manufacturing tolerances, which has to be maintained during the operation.

Study on the Dynamic Models of Systems Biology from the View of Engineering

2012 ◽  
Vol 220-223 ◽  
pp. 952-957
Author(s):  
Chen Liu ◽  
Xiao Yan Liu
Keyword(s):  
Mathematical Model ◽  
Systems Biology ◽  
Dynamic Process ◽  
Biological System ◽  
Dynamic Models ◽  
Model Parameters ◽  
State Variables ◽  
Biochemical Pathway ◽  
The Right ◽  
The Mathematical Model

From the view of engineering, based on expatiating the features of systems biology, the paper discusses the workflows and the research emphasis of systems biology. It also explains how to model and analyze the dynamic process of signal transmitting network for a biological system by an example. Based on the complexity and uncertainty of the mathematical model, the right methods are chosen to realize the effective estimation of state variables and model parameters for the biochemical pathway.

Lubrication Analysis of a Rolling Piston Rotary Compressor: Part 2: Experimental Validation and Results

1994 ◽  
Vol 208 (2) ◽  
pp. 95-104
Author(s):  
S K Padhy
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Experimental Validation ◽  
Sensitivity Study ◽  
Rotary Compressor ◽  
Oil Flow ◽  
Different Dimensions ◽  
Rolling Piston ◽  
The Mathematical Model ◽  
Good Agreement

In this paper the experiments conducted for the measurement of oil flow in the rotary compressor are described. The experimental data are compared against the theoretical prediction from the mathematical model developed (1) and a good agreement is found. In addition, experimental data from previously published literature are also used to verify the mathematical model. A sensitivity study is carried out to predict the behaviour of the rotary compressor for the oil flow at different conditions and with different dimensions.

Estimation of State Variables in the Ćuk Converter Mathematical Model with Partially Unknown Parameters

2021 ◽  
Vol 22 (9) ◽  
pp. 451-458
Author(s):  
A. A. Bobtsov ◽  
R. Ortega ◽  
N. A. Nikolaev ◽  
O. V. Slita ◽  
O. A. Kozachek ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Finite Time ◽  
Control Algorithm ◽  
Power Converter ◽  
The State ◽  
Model Parameters ◽  
State Variables ◽  
Unknown Parameters ◽  
Proportional Integral ◽  
The Mathematical Model

In this paper the solution was proposed for the state variables estimation problem in the mathematical model of the DC switch-mode power converter built according to the Ćuk scheme. Pulse converters are one of the main components of most modern electrical devices and the circuit proposed by Slobodan Ćuk in the 70s of the 20th century is still relevant and demanded. Traditionally, PI (proportional-integral) controllers or proportional-integral adaptive control algorithm (PI-PBC), based on passification methods and superior to standard PI controllers in accuracy, are used as the control algorithm for power converters. However, you need to know the entire vector of the state variables of the converter to build a PI-PBC controller, and moreover, all its parameters must be accurately known. Unfortunately, in practice, such assumptions are not fulfilled, since parametric drifting is possible, and measurements of the converter’s state require additional sensors, which in some cases does not justify itself. Thus, there is a need to develop additional observers or estimators that allow obtaining data on all variables of the converter, as well as its parameters. The solution is based on the GPEBO method (generalized parameter estimation-based observers). The problem was solved under assumption that only the output signal (the output voltage of the converter) is measurable and some of the mathematical model parameters are unknown. An important aspect of the observer design is the development of an algorithm for unknown parameters and the state vector of a mathematical model estimation that ensures convergence in a finite time. Finite-time convergence is extremely important when designing observers since transients in pulse converters occur very quickly.

An Introductory and Analysis of the Stationary Blade Rotary Compressor

2011 ◽  
Vol 317-319 ◽  
pp. 2063-2068
Author(s):  
Ai Nong Geng ◽  
Kui Hua Geng ◽  
Xin Mo Li
Keyword(s):  
Research Result ◽  
Piston Compressor ◽  
Friction Reduction ◽  
Chamber Pressure ◽  
Rotary Compressor ◽  
Structure Characteristics ◽  
New Type ◽  
Working Principle ◽  
Rolling Piston ◽  
Conventional Rolling

A new type of stationary blade rotary compressor is developed to overcome the rolling piston compressor’s weaknesses such as severe leaking loss and friction waste. The new compressor has unique sealing structures and friction-reducing techniques, featuring in that the compressor adopts a stationary blade whose out-end is hermetically fastened to the cylinder’s inner wall and the blade’s two side-ends are hermetically fastened to the end-covers which respectively set in both ends of the cylinder. Due to that the cylinder, the blade and the end-covers all are closely fitted to each other, the leakage and friction occurred from these parts are completely eliminated. This paper introduces the compressor’s working principle and structure characteristics, deduces the calculation formulas for displacement volume, chamber pressure and thermodynamic properties, and discusses the design principles of compressor structure parameters and what effects these parameters have on leakage and friction. The research result shows that the stationary blade compressor, in comparison with the conventional rolling piston compressor, has displayed some unique advantages in seal property, friction reduction, manufacturing and assembling techniques.

scholarly journals A Novel Identification Method for Generalized T-S Fuzzy Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Ling Huang ◽  
Kai Wang ◽  
Peng Shi ◽  
Hamid Reza Karimi
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Systems ◽  
Ant Colony Algorithm ◽  
State Space Model ◽  
The State ◽  
Model Parameters ◽  
State Variables ◽  
Space Model ◽  
Affine Nonlinear Systems ◽  
Simulation Results

In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm.

Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models*

2021 ◽  
Author(s):  
Marcello Pericoli ◽  
Marco Taboga
Keyword(s):  
Bayesian Estimation ◽  
Term Structure ◽  
Broad Class ◽  
Model Parameters ◽  
State Variables ◽  
Computationally Efficient ◽  
Macroeconomic Factors ◽  
No Arbitrage ◽  
Term Structure Models ◽  
Non Linear

Abstract We propose a general method for the Bayesian estimation of a very broad class of non-linear no-arbitrage term-structure models. The main innovation we introduce is a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree of accuracy. Once the pricing function is approximated, the posterior distribution of model parameters and unobservable state variables can be estimated by standard Markov Chain Monte Carlo methods. As an illustrative example, we apply the proposed techniques to the estimation of a shadow-rate model with a time-varying lower bound and unspanned macroeconomic factors.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

Model of the influence of Internet finance on monetary policy based on gibbs sampling and vector autoregression

2020 ◽  
pp. 1-11
Author(s):  
Hui Wang ◽  
Huang Shiwang
Keyword(s):  
Monetary Policy ◽  
Gibbs Sampling ◽  
Posterior Distribution ◽  
Estimation Method ◽  
Financial Supervision ◽  
Var Model ◽  
Model Parameters ◽  
State Variables ◽  
Frequency Data ◽  
Internet Finance

The various parts of the traditional financial supervision and management system can no longer meet the current needs, and further improvement is urgently needed. In this paper, the low-frequency data is regarded as the missing of the high-frequency data, and the mixed frequency VAR model is adopted. In order to overcome the problems caused by too many parameters of the VAR model, this paper adopts the Bayesian estimation method based on the Minnesota prior to obtain the posterior distribution of each parameter of the VAR model. Moreover, this paper uses methods based on Kalman filtering and Kalman smoothing to obtain the posterior distribution of latent state variables. Then, according to the posterior distribution of the VAR model parameters and the posterior distribution of the latent state variables, this paper uses the Gibbs sampling method to obtain the mixed Bayes vector autoregressive model and the estimation of the state variables. Finally, this article studies the influence of Internet finance on monetary policy with examples. The research results show that the method proposed in this article has a certain effect.

Research on cargo-loading optimization based on genetic and fuzzy integration

2021 ◽  
Vol 40 (4) ◽  
pp. 8493-8500
Author(s):  
Yanwei Du ◽  
Feng Chen ◽  
Xiaoyi Fan ◽  
Lei Zhang ◽  
Henggang Liang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Three Dimensional ◽  
Distribution Center ◽  
Long Time ◽  
Low Efficiency ◽  
Decision Making Model ◽  
The Mathematical Model ◽  
Loading Scheme

With the increase of the number of loaded goods, the number of optional loading schemes will increase exponentially. It is a long time and low efficiency to determine the loading scheme with experience. Genetic algorithm is a search heuristic algorithm used to solve optimization in the field of computer science artificial intelligence. Genetic algorithm can effectively select the optimal loading scheme but unable to utilize weight and volume capacity of cargo and truck. In this paper, we propose hybrid Genetic and fuzzy logic based cargo-loading decision making model that focus on achieving maximum profit with maximum utilization of weight and volume capacity of cargo and truck. In this paper, first of all, the components of the problem of goods stowage in the distribution center are analyzed systematically, which lays the foundation for the reasonable classification of the problem of goods stowage and the establishment of the mathematical model of the problem of goods stowage. Secondly, the paper abstracts and defines the problem of goods loading in distribution center, establishes the mathematical model for the optimization of single car three-dimensional goods loading, and designs the genetic algorithm for solving the model. Finally, Matlab is used to solve the optimization model of cargo loading, and the good performance of the algorithm is verified by an example. From the performance evaluation analysis, proposed the hybrid system achieve better outcomes than the standard SA model, GA method, and TS strategy.

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