An Improved Finite Element Meshing Strategy for Dynamic Optimization Problems

Gong, Minliang; Jiang, Aipeng; Zhang, Quannan; Wang, Haokun; Hu, Junjie; Lin, Yi

doi:10.1155/2017/4829195

Cited by 4 publications

(5 citation statements)

References 16 publications

(13 reference statements)

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“…The length of each finite element i is given by α i . Moreover, Radau collocation points feature a better numerical stability compared with other frameworks such as Gauss collocation points 24 . Nevertheless, Gauss collocation points can achieve a higher algebraic precision (

O (α_{i}^{K + 2})

).…”

Section: Problem For the Integration Of Design And Controlmentioning

confidence: 99%

Selection and refinement of finite elements for optimal design and control: A Hamiltonian function approach

Palma-Flores

Ricardez‐Sandoval

2023

AIChE Journal

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In this work, we propose a /methodology for the selection and refinement of finite elements for the integration of process design and control. The proposed methodology is based on the selection criteria of the Hamiltonian function through the implementation of the Pontryagin's minimum principle. The Hamiltonian function features to be continuous and constant over time for autonomous systems; nevertheless, the Hamiltonian function shows a nonconstant profile for underestimated discretization meshes, which is exploited in this work for the refinement of the discretization. Furthermore, the residuals at noncollocation points are evaluated to estimate the collocation error, this is used as a second refinement criterion in the proposed framework. The methodology is illustrated using two case studies featuring a reaction system with two CSTRs in series and the Williams–Otto reactor, respectively. The results showed that an accurate selection of the finite elements return economically attractive designs with fewer elements than those obtained with equidistributed finite element strategies.

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O (α_{i}^{K + 2})

).…”

Section: Problem For the Integration Of Design And Controlmentioning

confidence: 99%

Selection and refinement of finite elements for optimal design and control: A Hamiltonian function approach

Palma-Flores

Ricardez‐Sandoval

2023

AIChE Journal

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“…The higher the mesh density, the higher the accuracy of the simulation results will be, but it will compute resources and may lead to model distortion. 23 Therefore, it is necessary to select a reasonable mesh density to divide the mesoscopic model.…”

Section: Finite Element Simulation Of Knitting Yarnmentioning

confidence: 99%

Numerical simulation and tension regulation of yarn mechanics on warp knitting machines

Zheng

Jiang

2022

Textile Research Journal

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This research aims to solve the problem of large yarn tension fluctuation in different angle regions of one course. The importance of yarn tension regulation is demonstrated by numerical simulation and a yarn tension regulation system is designed. In particular, by combining the motion of the loop forming mechanism, the force on the yarn is simulated and calculated by the finite element method; the knitting accuracy deviation caused by the yarn force acting on the guide needle and knitting needle is also analyzed and simulated. On the basis of theoretical analysis, the hardware and software platform of the tension regulation system are developed, the selection of the tension control device is optimized, the software control module is designed, and the motion curves of quintic polynomial displacement, velocity and acceleration are planned to realize yarn tension regulation. Experiments are conducted under different lapping and speeds. Experimental results show that compared with the traditional let-off control system, the designed tension regulation system can reduce the yarn tension peak by at least 51.7% and the yarn tension fluctuation range by at least 54.9% in one course. The experimental results verify that the designed tension regulation system has excellent control performance for dynamic yarn tension, and thus improves the yarn knittability and knitting accuracy.

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“…Moreover, the factor experiment method and other regression and statistical methods were applied [212,228,232,235,[243][244]. The questions of the optimal control and processes control were considered in the works [220,[236][237][245][246][247][248].…”

Section: Optimization and Process Controlmentioning

confidence: 99%

“…For the solution of the considered optimization problems the wide range of the software and programing languages was applied including Matlab [73,203,250,252], gPROMS [63,218,235], GAMS [49,209,211,246,254], Design-Expert [232], ASPEN [214], ChemCAD [215], ROSA [206][207], Modelica [219], C++ [36,38], R [244].…”

Section: Optimization and Process Controlmentioning

confidence: 99%

Simulation of Reverse Osmosis Process: Novel Approaches and Development Trends

Huliienko

Korniyenko

Muzyka

et al. 2022

JES

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Reverse osmosis is an essential technological separation process that has a large number of practical applications. The mathematical simulation is significant for designing and determining the most effective modes of membrane equipment operation and for a deep understanding of the processes in membrane units. This paper is an attempt at systematization and generalizing the results of the investigations dedicated to reverse osmosis simulation, which was published from 2011 to 2020. The main approaches to simulation were analyzed, and the scope of use of each of them was delineated. It was defined that computational fluid dynamics was the most used technique for reverse osmosis simulation; the intensive increase in using of molecular dynamics methods was pointed out. Since these two approaches provide the deepest insight into processes, it is likely that they will further be widely used for reverse osmosis simulations. At the same time, for the simulation of the membrane plant, it is reasonable to use the models that required the simplest solutions methods. The solution-diffusion model appears to be the most effective and flexible for these purposes. Therefore, this model was widely used in considering the period. The practical problems solved using each of the considered approaches were reviewed. Moreover, the software used for the solution of the mathematical models was regarded.

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An Improved Finite Element Meshing Strategy for Dynamic Optimization Problems

Cited by 4 publications

References 16 publications

Selection and refinement of finite elements for optimal design and control: A Hamiltonian function approach

Selection and refinement of finite elements for optimal design and control: A Hamiltonian function approach

Numerical simulation and tension regulation of yarn mechanics on warp knitting machines

Simulation of Reverse Osmosis Process: Novel Approaches and Development Trends

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