scholarly journals DETERMINATION OF RHEOLOGICAL PARAMETERS OF POLYMERIC MATERIALS USING NONLINEAR OPTIMIZATION METHODS

2020 ◽  
Vol 3 (5) ◽  
pp. 15-23
Author(s):  
S. Yazyev ◽  
A. Chepurnenko ◽  
S. Litvinov

The article is devoted to the problem of processing the experimental creep curves of polymers. The task is to determine their rheological characteristics from tests for any of the simplest types of deformation. The basis for the approximation of the experimental curves is the nonlinear Maxwell-Gurevich equation. The task of finding the rheological parameters of the material is posed as a nonlinear optimization problem. The objective function is the sum of the squared deviations of the experimental values on the creep curve from the theoretical ones. Variable input parameters of the objective function are the initial relaxation viscosity and velocity modulus m*. A theoretical creep curve is constructed numerically using the fourth-order Runge-Kutta method. The nonlinear optimization problem is solved in the Matlab environment using the internal point method. The values m* and are found for which the objective function takes the minimum value. To test the technique, the inverse problem was solved. For given values of the rheological parameters of the material, a theoretical curve of creep under bending was constructed, and the values m* and were found from it. The technique was also tested on experimental stress relaxation curves of secondary polyvinyl chloride and creep curves of polyurethane foam with a pure shear. A higher quality approximation of experimental curves is shown in comparison with existing methods. The developed technique allows us to determine the rheological characteristics of materials from tests for bending, central tension (compression), torsion, shear, and it is enough to test only one type of deformation, and not a series, as was suggested earlier by some researchers

2019 ◽  
pp. 2022-2029
Author(s):  
Saba Nasser Majeed

In this paper, we propose new types of non-convex functions called strongly --vex functions and semi strongly --vex functions. We study some properties of these proposed functions. As an application of these functions in optimization problems, we discuss some optimality properties of the generalized nonlinear optimization problem for which we use, as an objective function, strongly --vex function and semi strongly --vex function.


Author(s):  
Sakitha Kumarage ◽  
Mehmet Yildirimoglu ◽  
Mohsen Ramezani ◽  
Zuduo Zheng

Demand management aiming to optimize system cost while ensuring user compliance in an urban traffic network is a challenging task. This paper introduces a cooperative demand redistribution strategy to optimize network performance through the retiming of departure times within a limited time window. The proposed model minimizes the total time spent in a two-region urban network by incurring minimal disruption to travelers’ departure schedules. Two traffic models based on the macroscopic fundamental diagram (MFD) are jointly implemented to redistribute demand and analyze travelers’ reaction. First, we establish equilibrium conditions via a day-to-day assignment process, which allows travelers to find their preferred departure times. The trip-based MFD model that incorporates individual traveler attributes is implemented in the day-to-day assignment, and it is conjugated with a network-level detour ratio model to incorporate the effect of congestion in individual traveler route choice. This allows us to consider travelers with individual preferences on departure times influenced by desired arrival times, trip lengths, and earliness and lateness costs. Second, we develop a nonlinear optimization problem to minimize the total time spent considering both observed and unobserved demand—that is, travelers opting in and out of the demand management platform. The accumulation-based MFD model that builds on aggregated system representation is implemented as part of the constraints in the nonlinear optimization problem. The results confirm the resourcefulness of the model to address complex two-region traffic dynamics and to increase overall performance by reaching a constrained system optimum scenario while ensuring the applicability at both full and partial user compliance conditions.


2015 ◽  
Vol 38 (2) ◽  
pp. 413-429 ◽  
Author(s):  
Muhammad Aslam ◽  
Saminathan Balamurali ◽  
Chi-Hyuck Jun ◽  
Batool Hussain

In this paper, we present the designing of the skip-lot sampling plan including the re-inspection  called SkSP-R. The plan parameters of the proposed plan are determined through a  nonlinear optimization problem by minimizing the average sample number satisfying both the producer's risk and the consumer's risks. The proposed plan is shown to perform better than the existing sampling plans in terms of the average sample number. The application of the proposed plan is explained with the help of illustrative examples.


1988 ◽  
Vol 110 (3) ◽  
pp. 324-328 ◽  
Author(s):  
Ka C. Cheok ◽  
Hongxing Hu ◽  
Nan K. Loh

This paper describes a technique for modeling and identifying a class of nonlinear servomechanism systems with stick-slip friction. The physics of the stick-slip friction is considered in modeling the process. Identification of the system parameters is formulated as a nonlinear optimization problem. A modified simplex algorithm is proposed as the optimization procedure. The difficulties encountered in choosing identification algorithm and input signals for the problem are discussed. A simulation example of a servomotor system is provided.


2013 ◽  
Vol 284-287 ◽  
pp. 1087-1093 ◽  
Author(s):  
Ya Chin Chang ◽  
Rung Fang Chang

As electricity demands and power transactions continuously increase, it becomes vulnerable to voltage instability for power systems, generally incurred by over-utilized facilities or any contingency. The transmission system loading margin (LM) enhancement problem with Static Synchronous Compensator (STATCOM) installation can be formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP); due to the complexity of the MDCP, the computing burden might be very heavy. In the paper, the proposed ordinal optimization (OO) based STATCOM installation method is applied to the MDCP to solve for good enough solutions rather than the best solution, so as to largely reduce the computation burden. In the method, the crude method is first used to solve the MDCP and, based on OO theory, the exact method is then used to determine the good enough solutions. Finally, the good enough solution, as uses the fewest STATCOM device units for installation and makes the power system able to provide the required LM, is recommended for network reinforcement.


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