A Method for Representing the Configuration, and Analyzing the Motion of Complex Cable-Pulley Systems

2000 ◽  
Author(s):  
Dennis W. Hong ◽  
Raymond J. Cipra
Keyword(s):  
Reduction Process ◽  
System Model ◽  
Pulley System ◽  
Basic Strategy ◽  
Constraint Equations ◽  
Input Variables ◽  
Row Reduction ◽  
The Relationship

Abstract In this paper a systematic way of representing complex cable-pulley mechanism configurations and a method to analyze and synthesize the motion of these cable-pulley devices is presented. The cable-pulley system model that is being considered is composed of three basic elements which are pulleys, blocks, and cables. A configuration table is used to identify the constraint equations by systematically defining the connections between the cables, pulleys, and blocks. The basic strategy is to use the constraint equations to generate the relationship between each variable and a subset of the variables identified as the inputs. The number of input variables is equal to the total number of variables minus the number of independent constraints. This choosing of the set of inputs is done in conjunction with a row reduction process on the system of constraint equations which identifies the number of inputs and ultimately generates the relationships of each variable to the input(s). Examples are given to illustrate the procedure.

A Method for Representing the Configuration and Analyzing the Motion of Complex Cable-Pulley Systems

2003 ◽  
Vol 125 (2) ◽  
pp. 332-341 ◽  
Author(s):  
Dennis W. Hong ◽  
Raymond J. Cipra
Keyword(s):  
Reduction Process ◽  
System Model ◽  
Pulley System ◽  
Basic Strategy ◽  
Constraint Equations ◽  
Interchange Process ◽  
Input Variables ◽  
Simple Column ◽  
Row Reduction ◽  
The Relationship

In this paper a systematic way of representing complex cable-pulley mechanism configurations and a method to analyze their motion is presented. This technique can also be used as an aid for synthesis. The cable-pulley system model that is being considered is planar and composed of three basic elements which are pulleys, blocks, and cables. A configuration table is used to identify the constraint equations by systematically defining the connections between the cables, pulleys, and blocks. The basic strategy is to use the constraint equations to generate the relationship between each variable and a subset of the variables identified as the inputs. A row reduction process on the system of constraint equations identifies the number of inputs and ultimately generates the relationships of each variable to the input(s). Results with different input variables can be easily obtained by a simple column interchange process. Examples are given to illustrate the procedure.

Mechanically Aspirated Solar Radiation Shields: A CFD and Neural Network Design Analysis

2001 ◽  
Author(s):  
B. M. Fichera ◽  
R. L. Mahajan ◽  
T. W. Horst
Keyword(s):  
Neural Network ◽  
Solar Radiation ◽  
Temperature Sensor ◽  
Temperature Measurements ◽  
Analysis And Design ◽  
Computational Fluid Dynamics Analysis ◽  
Radiation Shields ◽  
Input Variables ◽  
The Relationship

Abstract Accurate air temperature measurements made by surface meteorological stations are demanded by climate research programs for various uses. Heating of the temperature sensor due to inadequate coupling with the environment can lead to significant errors. Therefore, accurate in-situ temperature measurements require shielding the sensor from exposure to direct and reflected solar radiation, while also allowing the sensor to be brought into contact with atmospheric air at the ambient temperature. The difficulty in designing a radiation shield for such a temperature sensor lies in satisfying these two conditions simultaneously. In this paper, we perform a computational fluid dynamics analysis of mechanically aspirated radiation shields (MARS) to study the effect of geometry, wind speed, and interplay of multiple heat transfer processes. Finally, an artificial neural network model is developed to learn the relationship between the temperature error and specified input variables. The model is then used to perform a sensitivity analysis and design optimization.

An improvement to the ANN-enhanced flow rating method

2021 ◽  
Author(s):  
Bernhard Schmid
Keyword(s):  
Neural Network ◽  
Electrical Conductivity ◽  
Water Resources ◽  
Flow Rate ◽  
Major Ions ◽  
Rate Of Change ◽  
Data Set ◽  
Input Variables ◽  
Relationship Of ◽  
The Relationship

<p>The work reported here builds upon a previous pilot study by the author on ANN-enhanced flow rating (Schmid, 2020), which explored the use of electrical conductivity (EC) in addition to stage to obtain ‘better’, i.e. more accurate and robust, estimates of streamflow. The inclusion of EC has an advantage, when the relationship of EC versus flow rate is not chemostatic in character. In the majority of cases, EC is, indeed, not chemostatic, but tends to decrease with increasing discharge (so-called dilution behaviour), as reported by e.g. Moatar et al. (2017), Weijs et al. (2013) and Tunqui Neira et al.(2020). This is also in line with this author’s experience.</p><p>The research presented here takes the neural network based approach one major step further and incorporates the temporal rate of change in stage and the direction of change in EC among the input variables (which, thus, comprise stage, EC, change in stage and direction of change in EC). Consequently, there are now 4 input variables in total employed as predictors of flow rate. Information on the temporal changes in both flow rate and EC helps the Artificial Neural Network (ANN) characterize hysteretic behaviour, with EC assuming different values for falling and rising flow rate, respectively, as described, for instance, by Singley et al. (2017).</p><p>The ANN employed is of the Multilayer Perceptron (MLP) type, with stage, EC, change in stage and direction of change in EC of the Mödling data set (Schmid, 2020) as input variables. Summarising the stream characteristics, the Mödling brook can be described as a small Austrian stream with a catchment of fairly mixed composition (forests, agricultural and urbanized areas). The relationship of EC versus flow reflects dilution behaviour. Neural network configuration 4-5-1 (the 4 input variables mentioned above, 5 hidden nodes and discharge as the single output) with learning rate 0.05 and momentum 0.15 was found to perform best, with testing average RMSE (root mean square error) of the scaled output after 100,000 epochs amounting to 0.0138 as compared to 0.0216 for the (best performing) 2-5-1 MLP with stage and EC as inputs only.    </p><p> </p><p>References</p><p>Moatar, F., Abbott, B.W., Minaudo, C., Curie, F. and Pinay, G.: Elemental properties, hydrology, and biology interact to shape concentration-discharge curves for carbon, nutrients, sediment and major ions. Water Resources Res., 53, 1270-1287, 2017.</p><p>Schmid, B.H.: Enhanced flow rating using neural networks with water stage and electrical conductivity as predictors. EGU2020-1804, EGU General Assembly 2020.</p><p>Singley, J.G., Wlostowski, A.N., Bergstrom, A.J., Sokol, E.R., Torrens, C.L., Jaros, C., Wilson, C.,E., Hendrickson, P.J. and Gooseff, M.N.: Characterizing hyporheic exchange processes using high-frequency electrical conductivity-discharge relationships on subhourly to interannual timescales. Water Resources Res. 53, 4124-4141, 2017.</p><p>Tunqui Neira, J.M., Andréassian, V., Tallec, G. and Mouchel, J.-M.: A two-sided affine power scaling relationship to represent the concentration-discharge relationship. Hydrol. Earth Syst. Sci. 24, 1823-1830, 2020.</p><p>Weijs, S.V., Mutzner, R. and Parlange, M.B.: Could electrical conductivity replace water level in rating curves for alpine streams? Water Resources Research 49, 343-351, 2013.</p>

Design method of a novel variable speed ratio line gear mechanism

2020 ◽  
pp. 095440622093772
Author(s):  
Yangzhi Chen ◽  
Xiaoping Xiao ◽  
Daoping Zhang ◽  
Haifei Xiao ◽  
Yueling Lyu
Keyword(s):  
Design Method ◽  
Speed Ratio ◽  
Variable Speed ◽  
Element Analysis ◽  
Constraint Equations ◽  
Order Curve ◽  
Contact Curve ◽  
Gear Mechanism ◽  
Parallel Axis ◽  
The Relationship

Based on the space curve meshing theory, a novel noncircular line gear mechanism was advanced, namely, this paper presented a design method of the variable speed ratio noncircular line gear with coplanar axes. Firstly, the universal contact curve equations of the constant speed ratio and variable speed ratio line teeth were established. After the constraint equations of the rotating angle of the driving and driven variable speed ratio noncircular line gears were analyzed and established, the relationship between the rotating angle of the driven variable speed ratio noncircular line gear and the parameter t in the VSR area was assumed to be a piecewise fourth-order curve. Then, the contact curve equations of the variable speed ratio noncircular line gears were derived, and the entity models of variable speed ratio noncircular line gears were built. The prototypes of the parallel axis and intersecting axis variable speed ratio noncircular line gears were manufactured by Stereo Lithography Apparatus, and the speed ratios were measured on the kinematic test rig. The kinematic and finite element analysis results demonstrate that the relationship between the rotating angle of the driven variable speed ratio noncircular line gear and the parameter t conforms to the designed function and the noncircular line teeth smoothly achieve the preset VSR transmission. The proposed design method is helpful to design the variable speed ratio noncircular line gears with lower theoretical sliding rate and wider variation range of the speed ratio; consequently, the designed variable speed ratio noncircular line gears have better applicability in specific variable speed ratio applications.

scholarly journals System Dynamic Model for Lake’s Water Flow: A Case Of Situ Binong, Cikarang, West Java, Indonesia

2018 ◽  
Vol 9 (2) ◽  
Author(s):  
Muchammad Chusnan Aprianto
Keyword(s):  
Water Resources ◽  
Dynamic System ◽  
Water Flow ◽  
Natural Water ◽  
Surface Flow ◽  
System Model ◽  
Domestic Waste ◽  
The Relationship ◽  
Lake Size

This study aims to develop a dynamic system model that describes the relationship ofwater, socio-economic, and water resources (lake size) sub-systems in Situ Binong. In addition,this study also aims to make predictions of water resources conditions (lake size) Situ Binong forthe next 5 years. The model is prepared using a dynamic system approach. The Situ Binong waterflow model is available water resources consisting of 3 sub-systems namely natural water flowsub-systems, socio-economic, and water resources Situ Binong. The result of the research showsthat the requirement of Situ Binong water resources every year is increasing so that the volume ofSitu Binong is decreasing. In addition, the volume of water resources Situ Binong influenced bysupply and demand. Supply comes from domestic waste and natural water flow such asprecipitation, infiltration and surface flow. While demand comes from WTP intake, irrigation, andevaporation.

scholarly journals Market Structure Conduct Performance Hypothesis Revisited Using Stochastic Frontier Efficiency Analysis

2012 ◽  
Vol 48 (3) ◽  
Author(s):  
Saleem Shaik ◽  
Albert J. Allen ◽  
Seanicaa Edwards ◽  
James Harris
Keyword(s):  
Market Structure ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficiency Measure ◽  
Frontier Analysis ◽  
Input Variables ◽  
And Performance ◽  
Frontier Efficiency ◽  
The Relationship

Stochastic frontier analysis, which is used to estimate technical efficiency, is extended to examine the market structure, conduct and performance hypothesis for the U.S. trucking industry. The technical efficiency measure takes into account not only the relationship between inputs used in the production of output, but it also examines the importance of market structure conduct factors to the performance of the firm. An empirical application to U.S. trucking carriers over the period 1994-2003 is examined. Results reveal that average haul, average load, debt-to-equity and market concentration significantly affected technical efficiency. Capital, fixed and variable input variables were significant in the production function equation.

scholarly journals The Role Of Literacy In The Economic Growth Of Cameroon

2018 ◽  
Vol 14 (22) ◽  
pp. 25
Author(s):  
Dudjo Yen G. Boris ◽  
Sonkeng Germain ◽  
Njong Mom Aloysius ◽  
Tafah Edokat O. Edward
Keyword(s):  
Economic Growth ◽  
Significant Relationship ◽  
Poverty Reduction ◽  
Empirical Studies ◽  
Reduction Process ◽  
Literacy Rate ◽  
The World ◽  
The Relationship ◽  
Positive Effect

This paper focuses on how education contributes to economic growth. That is to say that there is a significant relationship between the variables of education and the economic growth of Cameroon. Education is therefore a priority for all nations. This shows the prominent place it occupies in the Constitution of almost every state. There are several studies that have focused on the relationship between education and economic growth of the microeconomic perspective, as macroeconomic, both theoretically and empirically. Empirical studies, which have been carried out everywhere around the world, do not agree with the fact that education has a positive effect on economic growth. The estimation results show that literacy rate, however, remains ambiguous and contradictory when OLS is going to GMM. Investing in Literacy is a challenge for development and it is the heart of poverty reduction process at all levels.

scholarly journals Research on Governor Parameter Optimization to Suppress Ultra-Low Frequency Oscillation of Power System Caused by Hydropower Unit

2021 ◽  
Vol 2087 (1) ◽  
pp. 012001
Author(s):  
Wei Yan ◽  
Yunbang Sun
Keyword(s):  
Single Machine ◽  
Optimization Algorithm ◽  
Low Frequency ◽  
System Model ◽  
Regulation System ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Speed Regulation ◽  
Damping Torque ◽  
The Relationship

Abstract In the actual power system with hydropower, long-time and ultra-low frequency oscillation events occur many times. It is found that the unreasonable setting of governor parameters is an important reason for the oscillation. Firstly, the single machine on load system model is used to analyse the relationship between the PID parameters of the governor and the system stability, then the relationship between oscillation mode and PID parameters of governor is analyzed by eigenvalue analysis method, and the negative damping provided by speed regulation system is analyzed by damping torque method, and then the particle swarm optimization algorithm is used to optimize the PID parameters. Through the analysis of the step response of the single machine system before and after the optimization and the damping torque coefficient provided by the speed regulation system, it shows the effectiveness of the optimization algorithm. Finally, in the simulation platform MATLAB/SIMULINK, a single machine load system model which is closer to the actual power grid is built. The governor parameters of the generator are simulated and verified, and the PID parameters are adjusted by using the parameters obtained by the optimization algorithm. The results show that the optimized parameters have a good suppression for the ultra-low frequency oscillation.

Moment Matching for Sensitivity Analysis of Probabilistic Model Output

2004 ◽  
Author(s):  
Mahmoud Awad ◽  
Agus Sudjianto ◽  
Nanua Singh
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Models ◽  
Moment Matching ◽  
Model Output ◽  
Sensitivity Indices ◽  
Variance Contribution ◽  
Complex Engineering ◽  
Input Variables ◽  
The Relationship ◽  
Effective Sensitivity

With the advent of highly complex engineering simulation models that describe the relationship between input variables and output response, the need for an efficient and effective sensitivity analysis is more demanding. In this article, a generalized approach that can provide efficient as well as accurate global sensitivity indices is developed. The approach consists of two steps: running an orthogonal array based experiment using moment-matched levels of the input variables and followed by a variance contribution analysis. The benefits of the approach are demonstrated through three different examples.

scholarly journals Time Series Prediction Based on Complex-Valued S-System Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Bin Yang ◽  
Wenzheng Bao ◽  
Yuehui Chen
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Financial Time Series ◽  
Time Series Prediction ◽  
System Model ◽  
Series Data ◽  
Classification Problems ◽  
Mathematical Formulas ◽  
Input Variables ◽  
Complex Valued

Symbolic regression has been utilized to infer mathematical formulas in order to solve the complex prediction and classification problems. In this paper, complex-valued S-system model (CVSS) is proposed to predict real-valued time series data. In a CVSS model, input variables and rate constants are complex-valued. The time series data need to be translated into complex numbers. The hybrid evolutionary algorithm based on complex-valued restricted additive tree and firefly algorithm is proposed to search the optimal CVSS model. Three financial time series data and Mackey–Glass chaos time series are collected to evaluate our proposed method. The experiment results show that the predicted data are very close to the target ones and our method could obtain the better RMSE, MAP, MAPE, POCID, R2, and ARV performances than ARIMA, radial basis function neural network (RBFNN), flexible neural tree (FNT), ordinary differential equation (ODE), and S-system.

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