scholarly journals Calibration of numerical models based on advanced optimization and penalization techniques

2017 ◽  
Vol 68 (5) ◽  
pp. 396-400
Author(s):  
Pavel Karban ◽  
David Pánek ◽  
František Mach ◽  
Ivo Doležel
Keyword(s):  
Boundary Conditions ◽  
Numerical Models ◽  
Probability Distributions ◽  
Random Variables ◽  
Measured Data ◽  
Optimization Techniques ◽  
Physical Models ◽  
New Approach ◽  
Material Parameters ◽  
Normal Probability

Abstract A new approach to estimation of unknown material parameters and boundary conditions of physical models was developed. The approach is based on processing measured data by advanced optimization techniques connected with penalization. The data are supposed to be in the form of random variables with normal probability distributions. Several examples were calculated proving the strength of the proposed algorithm.

Twister Generator of Poisson Random Numbers with the Use of Cumulative Frequency Technology

2020 ◽  
pp. 101-123
Author(s):  
A.F. Deon ◽  
D.D. Dmitriev ◽  
Yu.A. Menyaev
Keyword(s):  
Poisson Distribution ◽  
Probability Distributions ◽  
Random Variables ◽  
Convergence In Probability ◽  
Random Numbers ◽  
Cumulative Frequency ◽  
New Approach ◽  
Frequency Distributions ◽  
Simulation Results

The widely known generators of Poisson random variables are associated with different modifications of the algorithm based on the convergence in probability of a sequence of uniform random variables to the created stochastic number. However, in some situations, this approach yields different discrete Poisson probability distributions and skipping in the generated numbers. This paper offers a new approach for creating Poisson random variables based on the complete twister generator of uniform random variables, using cumulative frequency technology. The simulation results confirm that probabilistic and frequency distributions of the obtained stochastic numbers completely coincide with the theoretical Poisson distribution. Moreover, combining this new approach with the tuning algorithm of basic twister generation allows for a significant increase in length of the created sequences without using additional RAM of the computer

scholarly journals Poisson Twister Generator by Cumulative Frequency Technology

Algorithms ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 114 ◽  
Author(s):  
Aleksei F. Deon ◽  
Yulian A. Menyaev
Keyword(s):  
Poisson Distribution ◽  
Probability Distributions ◽  
Random Variables ◽  
Convergence In Probability ◽  
Cumulative Frequency ◽  
New Approach ◽  
Frequency Distributions ◽  
Simulation Results

The widely known generators of Poisson random variables are associated with different modifications of the algorithm based on the convergence in probability of a sequence of uniform random variables to the created stochastic number. However, in some situations, this approach yields different discrete Poisson probability distributions and skipping in the generated numbers. This article offers a new approach for creating Poisson random variables based on the complete twister generator of uniform random variables, using cumulative frequency technology. The simulation results confirm that probabilistic and frequency distributions of the obtained stochastic numbers completely coincide with the theoretical Poisson distribution. Moreover, combining this new approach with the tuning algorithm of basic twister generation allows for a significant increase in length of the created sequences without using additional RAM of the computer.

scholarly journals On the Dispersive Ordering and Applications

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Tran Loc Hung ◽  
Nguyen Van Son
Keyword(s):  
Unbiased Estimator ◽  
Probability Distributions ◽  
Random Variables ◽  
New Approach ◽  
Laws Of Large Numbers ◽  
Large Numbers ◽  
Dispersive Ordering

The purpose of this paper is to present some results related to the dispersive ordering of probability distributions via dispersion functions of the ℒ1-random variables. A new approach to the Laws of Large Numbers in ℒ1-norm can be applied via received results. A new concept on minimum-dispersive unbiased estimator is considered, too.

scholarly journals Experimental and numerical study of the air distribution inside a car cabin

2019 ◽  
Vol 85 ◽  
pp. 02014 ◽  
Author(s):  
Paul Dancă ◽  
Florin Bode ◽  
Ilinca Năstase ◽  
Cristiana Verona Croitoru ◽  
Amina Meslem
Keyword(s):  
Boundary Conditions ◽  
Numerical Study ◽  
Ventilation System ◽  
Measured Data ◽  
Experimental Session ◽  
Air Velocity ◽  
New Approach ◽  
The People ◽  
Measurement Session ◽  
Simulation Results

The main declared goal of all car manufacturers is to ensure high comfort inside the cabin and to reduce the fossil fuel. It is well-known that the time spent by the people indoor has raised in the last decade. The distance between the home and the workplace increased due to diversity of activities and hence job diversity. The thermal comfort during the travel must to be ensured to reduce the occupant’s thermal stress. The present study is investigating a comparison between the measured data and the numerical simulation results in the case when the ventilation system is functioning. It was evaluated the effect of the boundary conditions air flow and air velocity distribution in a passenger compartment in two cases: first is the general used constant inlet flow and the second is a new approach of importing the measured data obtained during the experimental measurement session as a boundary condition.CFD simulations were made taking as input the measured data obtained during experimental session. We have observed differences between initial simulation results and the measured data, therefore, for more accurate results, a new approach is needed, to impose as boundary conditions the measured data.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

scholarly journals Two-Dimensional Numerical Modeling of Flow in Physical Models of Rock Vane and Bendway Weir Configurations

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 458
Author(s):  
Drew C. Baird ◽  
Benjamin Abban ◽  
S. Michael Scurlock ◽  
Steven B. Abt ◽  
Christopher I. Thornton
Keyword(s):  
Numerical Modeling ◽  
Physical Model ◽  
Numerical Models ◽  
Hydraulic Performance ◽  
Physical Models ◽  
Protection Measures ◽  
Design Engineers ◽  
Model Study ◽  
Study Results ◽  
Wide Range

While there are a wide range of design recommendations for using rock vanes and bendway weirs as streambank protection measures, no comprehensive, standard approach is currently available for design engineers to evaluate their hydraulic performance before construction. This study investigates using 2D numerical modeling as an option for predicting the hydraulic performance of rock vane and bendway weir structure designs for streambank protection. We used the Sedimentation and River Hydraulics (SRH)-2D depth-averaged numerical model to simulate flows around rock vane and bendway weir installations that were previously examined as part of a physical model study and that had water surface elevation and velocity observations. Overall, SRH-2D predicted the same general flow patterns as the physical model, but over- and underpredicted the flow velocity in some areas. These over- and underpredictions could be primarily attributed to the assumption of negligible vertical velocities. Nonetheless, the point differences between the predicted and observed velocities generally ranged from 15 to 25%, with some exceptions. The results showed that 2D numerical models could provide adequate insight into the hydraulic performance of rock vanes and bendway weirs. Accordingly, design guidance and implications of the study results are presented for design engineers.

scholarly journals An Alternative Statistical Model for Predicting Salinity Variations in Estuaries

2020 ◽  
Vol 12 (24) ◽  
pp. 10677
Author(s):  
Ronghui Ye ◽  
Jun Kong ◽  
Chengji Shen ◽  
Jinming Zhang ◽  
Weisheng Zhang
Keyword(s):  
Statistical Model ◽  
River Discharge ◽  
Numerical Models ◽  
Low Cost ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Large River ◽  
Physical Models ◽  
Long Term Effects ◽  
Salinity Variations

Accurate salinity prediction can support the decision-making of water resources management to mitigate the threat of insufficient freshwater supply in densely populated estuaries. Statistical methods are low-cost and less time-consuming compared with numerical models and physical models for predicting estuarine salinity variations. This study proposes an alternative statistical model that can more accurately predict the salinity series in estuaries. The model incorporates an autoregressive model to characterize the memory effect of salinity and includes the changes in salinity driven by river discharge and tides. Furthermore, the Gamma distribution function was introduced to correct the hysteresis effects of river discharge, tides and salinity. Based on fixed corrections of long-term effects, dynamic corrections of short-term effects were added to weaken the hysteresis effects. Real-world model application to the Pearl River Estuary obtained satisfactory agreement between predicted and measured salinity peaks, indicating the accuracy of salinity forecasting. Cross-validation and weekly salinity prediction under small, medium and large river discharges were also conducted to further test the reliability of the model. The statistical model provides a good reference for predicting salinity variations in estuaries.

DISSONANCE — A MEASURE OF VARIABILITY FOR ORDINAL RANDOM VARIABLES

2001 ◽  
Vol 09 (01) ◽  
pp. 39-53 ◽  
Author(s):  
RONALD R. YAGER
Keyword(s):  
Distribution Function ◽  
Cumulative Distribution Function ◽  
Probability Distributions ◽  
Random Variables ◽  
Cumulative Distribution ◽  
General Properties

We look at the issue of obtaining a variance like measure associated with probability distributions over ordinal sets. We call these dissonance measures. We specify some general properties desired in these dissonance measures. The centrality of the cumulative distribution function in formulating the concept of dissonance is pointed out. We introduce some specific examples of measures of dissonance.

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