scholarly journals CRUMPLED-TO-TUBULE TRANSITION AND SHAPE TRANSFORMATIONS OF A MODEL OF SELF-AVOIDING SPHERICAL MESHWORK

2013 ◽  
Vol 24 (10) ◽  
pp. 1350075
Author(s):  
HIROSHI KOIBUCHI ◽  
ANDREY SHOBUKHOV
Keyword(s):  
Monte Carlo ◽  
Fractal Dimension ◽  
Pressure Difference ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Pressure Term ◽  
Second Order Transition ◽  
The Mean ◽  
Mc Simulation ◽  
The One

This paper analyzes a new self-avoiding (SA) meshwork model using the canonical Monte Carlo (MC) simulation technique on lattices that consist of connection-fixed triangles. The Hamiltonian of this model includes a SA potential and a pressure term. The model identifies a crumpled-to-tubule (CT) transition between the crumpled and tubular phases. This is a second-order transition, which occurs when the pressure difference between the inner and outer sides of the surface is close to zero. We obtain the Flory swelling exponents [Formula: see text] and [Formula: see text] corresponding to the mean square radius of gyration [Formula: see text] and enclosed volume V, where Df is the fractal dimension. The analysis shows that [Formula: see text] at the transition is almost identical to the one of the smooth phase of previously reported SA model which has no crumpled phase.

Monte Carlo Simulation on Conformation Properties of Polymer Multiple Chain System

2013 ◽  
Vol 734-737 ◽  
pp. 3141-3144
Author(s):  
Lin Lin Cui ◽  
Hua Nan Guan
Keyword(s):  
Monte Carlo ◽  
Polymer Chain ◽  
Volume Fraction ◽  
Solvent Molecule ◽  
Radius Of Gyration ◽  
Mean Square ◽  
End Distance ◽  
The Mean ◽  
Multiple Chain ◽  
Linear Polymer Chain

The author adopts Monte Carlo compute method to simulate the linear polymer chain lattice model in multiple chain systems of different volume fraction Φ while chain lengthn=50, and makes a research on the variational situation of the size (measured with the mean-square end-to-end distance <R2> and the mean-square radius of gyration <S2>), shape (measured with the mean asphericity factor ) with changing of the interaction energy between solvent molecule and polymer chain segment moleculeεPS. Results indicate <R2>, <S2> and have the changing rules that they become small with the increase of theεPS.

scholarly journals Study on the Leakage and Inter-Stage Pressure Drop Characteristics of Two-Stage Finger Seal

2021 ◽  
Vol 11 (5) ◽  
pp. 2239
Author(s):  
Hailin Zhao ◽  
Hua Su ◽  
Guoding Chen ◽  
Yanchao Zhang
Keyword(s):  
Pressure Drop ◽  
Pressure Difference ◽  
Radial Displacement ◽  
Mean Square ◽  
The Finite Element Method ◽  
Axial Pressure ◽  
Two Stage ◽  
One Stage ◽  
The One ◽  
Lower Contact

To solve the high leakage and high wear problems faced by sealing devices in aeroengines under the condition of high axial pressure difference, the two-stage finger seal is proposed in this paper. The finite element method and computational fluid dynamics (FEM/CFD) coupling iterative algorithm of the two-stage finger seal is developed and validated. Then the performance advantages of two-stage finger seal compared to the one-stage finger seal are studied, as well as the leakage and the inter-stage pressure drop characteristics of two-stage finger seal are investigated. Finally, the measure to improve the inter-stage imbalance of pressure drop of two-stage finger seal is proposed. The results show that the two-stage finger seal has lower leakage and lower contact pressure than the one-stage finger seal at high axial pressure difference, but there exists an inter-stage imbalance of pressure drop. Increasing the axial pressure difference and the root mean square (RMS) roughness of finger element can aggravate the imbalance of pressure drop, while the radial displacement excitation of rotor has little influence on it. The results also indicate that the inter-stage imbalance of pressure drop of the two-stage finger seal can be improved by increasing the number of finger elements of the 1st finger seal and decreasing the number of finger elements of the 2nd finger seal.

scholarly journals Bicluster CC Algoritm Analysis to Identify Patterns of Food Insecurity in Indonesia

2020 ◽  
Vol 17 (2) ◽  
pp. 325-338
Author(s):  
Raditya Novidianto ◽  
Rini Irfani
Keyword(s):  
Food Insecurity ◽  
Agricultural Sector ◽  
Parameter Tuning ◽  
Mean Square ◽  
Calorie Consumption ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
The Mean ◽  
Best Parameter ◽  
The One

Indonesia is known as an agricultural country. This means that most of the population work in the agricultural sector related to food. However, food insecurity still occurs in Indonesia. With the COVID-19 pandemic, the Food and Agriculture Organization (FAO) stated that there was a threat of food scarcity which had an impact on food insecurity conditions. This would undermine the second goal of the SDGs, which is to end hunger and create sustainable agriculture. The purpose of this study was to determine the spatial pattern of food insecurity in each province in Indonesia using the bicluster method. The data used are data from Susenas and Sakernas by BPS in 2019. Several studies show that the bicluster method with the CC algorithm shows that each province group has a different characteristic pattern. In the bicluster approach, the researcher runs parameter tuning to select the best parameter based on the Mean Square Residual in Volume (MSR / V). The CC algorithm tries to get a bicluster with a low MSR value, therefore the best parameter is the one that produces the smallest MSR / V value, in this study the smallest MSR / V is 0,01737 with δ = 0,01. The application of the CC biclustering algorithm to the food insecurity structure in Indonesia results in 5 bicluster. Bicluster 1 consists of 15 provinces with 8 variables, Bicluster 2 consists of 10 provinces with 5 variables, Bicluster 3 consists of 3 provinces with 7 variables, Bicluster 4 consists of 4 provinces with 4 variables and Bicluster 5 consists of 2 provinces with 5 variables. Biculster 4 represents a cluster of food insecurity areas with the characteristics of the bicluster P0, P1, P2 and calorie consumption of less than 1400 KKAL.

Calculation of the mean-square radius of gyration for polymer chains with side-groups

1992 ◽  
Vol 28 (11) ◽  
pp. 1339-1343 ◽  
Author(s):  
Zhou Zhiping ◽  
Xu Jianmin ◽  
Song Xubing ◽  
Yan Deyue
Keyword(s):  
Polymer Chains ◽  
Radius Of Gyration ◽  
Mean Square ◽  
The Mean

Computer Simulation on Conformation Properties of Polymer Chain

2013 ◽  
Vol 341-342 ◽  
pp. 195-198
Author(s):  
Lin Lin Cui ◽  
Hua Nan Guan
Keyword(s):  
Polymer Chain ◽  
Volume Fraction ◽  
Solvent Molecule ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Chain Segment ◽  
End Distance ◽  
The Mean ◽  
Multiple Chain ◽  
Linear Polymer Chain

The author adopts Monte Carlo compute method to simulate the linear polymer chain lattice model in multiple chain systems of chain lengthn=20, 50, 100 while the volume fraction Φ=0.125, and makes a research on the variational situation of the size (measured with the mean-square end-to-end distance <R2> and the mean-square radius of gyration <S2>), shape (measured with the mean asphericity factor <A>) with changing of the interaction energy between solvent molecule and polymer chain segment molecule εPS. Results indicate <R2>, <S2> and <A> have the changing rules that they become small with the increase of the εPS

Excluded-volume effects on the mean-square radius of gyration of oligo- and polystyrenes in dilute solutions

1993 ◽  
Vol 26 (8) ◽  
pp. 1884-1890 ◽  
Author(s):  
Fumiaki Abe ◽  
Yoshiyuki Einaga ◽  
Takenao Yoshizaki ◽  
Hiromi Yamakawa
Keyword(s):  
Excluded Volume ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dilute Solutions ◽  
Excluded Volume Effects ◽  
The Mean ◽  
Volume Effects

scholarly journals Econometric Estimation of Production Function with Applications

2019 ◽  
pp. 57-61 ◽  
Author(s):  
Awoingo Adonijah Maxwell ◽  
Isaac Didi Essi
Keyword(s):  
Monte Carlo ◽  
Mean Square Error ◽  
Production Function ◽  
Least Square ◽  
Production Model ◽  
Mean Square ◽  
Unknown Parameters ◽  
Data Generating Process ◽  
The Mean ◽  
Input Variables

This study focuses on Monte Carlo Methods in parameter estimation of production function. The ordinary least square (OLS) method is used to estimate the unknown parameters. The Monte Carlo simulation methods are used for the data generating process. The Cobb-Douglas production model with multiplicative error term is fitted to the data generated. From tables 1.1 to 1.3, the mean square error (MSE) of 1 are 0.007678, 0.001972 and 0.001253 respectively for sample sizes 20, 40 and 80. Our finding showed that the mean square error (MSE) value varies with the sum of the powers of the input variables.

High-Order Distributed Consensus with One-Bit Adaptive Quantization

2012 ◽  
Vol 591-593 ◽  
pp. 1299-1302
Author(s):  
Wen Kai Wang ◽  
Huan Xin Peng
Keyword(s):  
Convergence Rate ◽  
High Order ◽  
Consensus Algorithm ◽  
Quantization Scheme ◽  
Mean Square ◽  
Distributed Consensus ◽  
Adaptive Quantization ◽  
Convergence Performance ◽  
The Mean ◽  
The One

The convergence performance of distributed consensus algorithm with adaptive quantization communication depends on the convergence rate of the distributed consensus algorithm. In order to improve the convergence performance of distributed consensus under adaptive quantization communication, based on the one-bit adaptive quantization scheme, we propose the high-order distributed consensus to update the state of every node. We analyze the convergence performance and calculate the mean square error of the high-order distributed consensus algorithm with one-bit adaptive quantization. The high-order distributed consensus with one-bit adaptive quantization achieves a consensus in a mean square sense. Simultaneously, Simulations are done about the high-order distributed consensus based on one-bit adaptive quantization. Results show that the high-order distributed consensus algorithm based on one-bit adaptive quantization can reach an average consensus, and its convergence rate is higher than those of the first-order adaptive quantized distributed consensus algorithm and second-order adaptive quantized distributed consensus algorithm.

Geometrical analysis of self-compensating suspension systems for railcar engineering

2002 ◽  
Vol 216 (3) ◽  
pp. 185-196 ◽  
Author(s):  
F Sorge
Keyword(s):  
The Other ◽  
Mean Square ◽  
Geometrical Analysis ◽  
Suspension Systems ◽  
Longitudinal Plane ◽  
Articulated Systems ◽  
Gradient Type ◽  
The Mean ◽  
The One ◽  
Acceleration Component

The present analysis addresses several passive tilt systems for railroad cars aiming to compensate for the cart deficiency on curved tracks. To this end, the virtual centre of suspension must be located as close as possible to the longitudinal plane of symmetry of the coach, above the mass centre level for stability reasons. On the one hand, pantograph or Peaucellier's mechanisms may achieve the correct self-compensation. On the other hand, simpler articulated systems yield the desired goal with an excellent approximation. For example, selective algorithms can be applied for designing eight-link mechanisms, to be optimized thereafter by some method of the gradient type, minimizing the mean square value of the transverse acceleration component.

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