NUMERICAL APPROACH FOR SIMULATING THE TENSIONING PROCESS OF COMPLEX PRESTRESSED CABLE-NET STRUCTURES

The stability of cable-net structures depends on the prestress of the system. Due to the large displacement and mutual effect of the cables, it is difficult to simulate the tensioning process and control the forming accuracy. The Backward Algorithm (BA) has been used to simulate the tensioning process. The traditional BA involves complicated and tedious matrix operations. In this paper, a new numerical method based on the Vector Form Intrinsic Finite Element (VFIFE) method is proposed for BA application. Moreover, the tensioning sequence of a complex cable-net structure is introduced. Subsequently, a new approach for BA application in the simulation of the tensioning process is presented, which combines the VFIFE approach and the notion of form-finding. Finally, a numerical example is simulated in detail and the results of different tensioning stages are analyzed to verify the feasibility of the proposed approach. This study provides a significant reference for improving the construction control and forming accuracy of complex prestressed cable-net structures.

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A new approach to the stability and control of nonlinear processes

AIChE Journal ◽

10.1002/aic.690100113 ◽

1964 ◽

Vol 10 (1) ◽

pp. 16-25 ◽

Cited By ~ 12

Author(s):

J. F. Leathrum ◽

E. F. Johnson ◽

L. Lapidus

Keyword(s):

Nonlinear Processes ◽

New Approach ◽

Stability And Control ◽

The Stability ◽

And Control

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A Dynamical Modelling of the Epidemic Diseases to Assessing the Rates of Spread of COVID-19 in Saudi Arabia: SEIQR Model

10.21203/rs.3.rs-77792/v2 ◽

2020 ◽

Author(s):

Hamdy Youssef ◽

Najat Alghamdi ◽

Magdy Ezzat ◽

Alaa El-Bary ◽

Ahmed Shawky

Keyword(s):

Saudi Arabia ◽

Reproductive Number ◽

Adequate Treatment ◽

New Approach ◽

Safe Place ◽

Epidemic Dynamics ◽

Internal Parameters ◽

The Stability ◽

And Control ◽

Epidemic Diseases

Abstract A model of critical epidemic dynamics for the emergence of the new coronavirus COVID-19 is being established in this paper. A new approach to the assessment and control of the COVID-19 epidemic is given with the SEIQR pandemic model. This paper uses real knowledge on the distribution of COVID-19 in Saudi Arabia for mathematical modeling and dynamic analyses. The reproductive number and detailed stability analysis are provided in the SEIQR model dynamics. In a Jacobian method of linearization, we will address the domain of the solution and the equilibrium situation based on the SEIQR model. The equilibrium and its importance have been proven, and a study of the stability of the equilibrium free from diseases has been implemented. The reproduction number was evaluated in accordance with its internal parameters. The Lyapunov theorem of stability has proven the global stability of the current model's equilibrium. The SEIQR model was contrasted by comparing the results based on the SEIQR model with the real COVID-19 spread data in Saudi Arabia. Numerical evaluation and predictions were given. The results indicate that the SEIQR model is a strong model for the study of the spread of epidemics, such as COVID-19. At the end of this work, we implemented an optimum protocol that can quickly stop the spread of COVID-19 among the Saudi populations. The key solution to slowing COVID-19 transmission is to stay home and bring sick persons as far as possible in a remote location or in a safe place. Ultimately, it is vital to offer safe and adequate treatment to ill people, and to avoid them, medications, tones, and nutrients should be provided to non-infected persons.

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A New Approach to Controlling Thermal Processes

Measurement and Control ◽

10.1177/002029406900201102 ◽

1969 ◽

Vol 2 (11) ◽

pp. T181-T185 ◽

Cited By ~ 2

Author(s):

William K. Roots ◽

Loren D. Meeker

Keyword(s):

Transient Response ◽

Closed Loop ◽

Open Loop ◽

Thermal Processes ◽

New Approach ◽

Plasma Torches ◽

The Stability ◽

Fluidised Beds ◽

Response Determination ◽

And Control

Roots and Wu (1967) established that meaningful models of common thermal processes (boilers without superheaters, furnaces, ovens, vats, kilns etc.) can be made from a cascade comprising an open-loop gain μ, a transit delay L, and a salient time constant T. They used this model to establish facile procedures for stability determination when such processes were closed-loop controlled. A new procedure is now presented that not only facilitates stability studies but also greatly simplifies transient response determination for all commands and disturbances likely to be encountered by such closed loop controlled processes. This new approach is based on a generalised parameter v that incorporates μ, L and T. Then by means of a new plane, the w plane, displays are presented that readily predict the stability criteria and the transient response for any practical combination of command and disturbance; as is shown by the examples contained in the Appendix. This has radically simplified the control amd instrumentation of the processes with which the authors are associated (induction furnaces, fluidised beds, plasma torches, zone refining, etc.) and the presentation is intended for industrial engineers concerned with the design and control of similar thermal processes.

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A new approach on the modelling, chaos control and synchronization of a fractional biological oscillator

Advances in Difference Equations ◽

10.1186/s13662-021-03224-z ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Ali Saleh Alshomrani ◽

Malik Zaka Ullah ◽

Dumitru Baleanu

Keyword(s):

Chaos Control ◽

Control Method ◽

Phase Portraits ◽

New Approach ◽

Control Scheme ◽

Biological Oscillator ◽

The Stability ◽

Control And Synchronization ◽

And Control ◽

Active Control Method

AbstractThis research aims to discuss and control the chaotic behaviour of an autonomous fractional biological oscillator. Indeed, the concept of fractional calculus is used to include memory in the modelling formulation. In addition, we take into account a new auxiliary parameter in order to keep away from dimensional mismatching. Further, we explore the chaotic attractors of the considered model through its corresponding phase-portraits. Additionally, the stability and equilibrium point of the system are studied and investigated. Next, we design a feedback control scheme for the purpose of chaos control and stabilization. Afterwards, we introduce an efficient active control method to achieve synchronization between two chaotic fractional biological oscillators. The efficiency of the proposed stabilizing and synchronizing controllers is verified via theoretical analysis as well as simulations and numerical experiments.

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A New Dynamical Modelling of the Epidemic Diseases to Assessing the Rates of Spread of COVID-19 in Saudi Arabia: SEIRQ Model

10.21203/rs.3.rs-77792/v1 ◽

2020 ◽

Author(s):

Hamdy Youssef ◽

Najat Alghamdi ◽

Magdy Ezzat ◽

Alaa El-Bary ◽

Ahmed Shawky

Keyword(s):

Saudi Arabia ◽

Reproductive Number ◽

New Approach ◽

Epidemic Dynamics ◽

Internal Parameters ◽

Model Dynamics ◽

Dynamic Analyses ◽

The Stability ◽

And Control ◽

Epidemic Diseases

Abstract A new model of critical epidemic dynamics for the emergence of the new coronavirus COVID-19 is being established in this paper. A new approach to the assessment and control of the COVID 19 epidemic is given with the SEIRQ pandemic model. This paper uses real knowledge on the distribution of COVID-19 in Saudi Arabia for mathematical modeling and dynamic analyses. The reproductive number and detailed stability analysis are provided in the SEIRQ model dynamics. In a Jacobian method of linearization, we will address the domain of the solution and the equilibrium situation based on the SEIRQ model. The equilibrium and its importance have been proven, and a study of the stability of the equilibrium free from diseases has been implemented. The reproduction number was evaluated in accordance with its internal parameters. The Lyapunov theorem of stability has proven the global stability of the current model's equilibrium. The SEIRQ model was contrasted by comparing the results based on the SEIRQ model with the real COVID-19 spread data in Saudi Arabia. Numerical evaluation and predictions were given. The results indicate that the SEIRQ model is a strong model for the study of the spread of epidemics, such as COVID-19. At the end of this work, we implemented an optimum protocol that can quickly stop the spread of COVID-19 among the Saudi populations.

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Host-Guest Interactions on Electrode Surfaces for Immobilization of Molecular Catalysts

10.26434/chemrxiv.12115026.v1 ◽

2020 ◽

Author(s):

Laurent Sévery ◽

Jacek Szczerbiński ◽

Mert Taskin ◽

Isik Tuncay ◽

Fernanda Brandalise Nunes ◽

...

Keyword(s):

Aqueous Media ◽

Heterogeneous Systems ◽

Catalytic Systems ◽

New Approach ◽

Molecular Systems ◽

Electrode Surfaces ◽

Catalytic Surfaces ◽

Oxide Electrodes ◽

The Stability ◽

Molecular Catalysts

The strategy of anchoring molecular catalysts on electrode surfaces combines the high selectivity and activity of molecular systems with the practicality of heterogeneous systems. The stability of molecular catalysts is, however, far less than that of traditional heterogeneous electrocatalysts, and therefore a method to easily replace anchored molecular catalysts that have degraded could make such electrosynthetic systems more attractive. Here, we apply a non-covalent “click” chemistry approach to reversibly bind molecular electrocatalysts to electrode surfaces via host-guest complexation with surface-anchored cyclodextrins. The host-guest interaction is remarkably strong and allows the flow of electrons between the electrode and the guest catalyst. Electrosynthesis in both organic and aqueous media was demonstrated on metal oxide electrodes, with stability on the order of hours. The catalytic surfaces can be recycled by controlled release of the guest from the host cavities and readsorption of fresh guest. This strategy represents a new approach to practical molecular-based catalytic systems.

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On-Surface Radical Oligomerisation: A New Approach to STM Tip-Induced Reactions

10.26434/chemrxiv.6860105 ◽

2018 ◽

Author(s):

Gaolei Zhan ◽

Younes Makoudi ◽

Judicael Jeannoutot ◽

Simon Lamare ◽

Michel Féron ◽

...

Keyword(s):

Sample Surface ◽

Scanning Tunnelling Microscope ◽

Transfer Event ◽

New Approach ◽

The Past ◽

Organic Nanostructures ◽

Scanning Tunnelling ◽

New Strategy ◽

Surface Fabrication ◽

And Control

Over the past decade, on-surface fabrication of organic nanostructures has been widely investigated for the development of molecular electronic devices, nanomachines, and new materials. Here, we introduce a new strategy to obtain alkyl oligomers in a controlled manner using on-surface radical oligomerisations that are triggered by the electrons/holes between the sample surface and the tip of a scanning tunnelling microscope. The resulting radical-mediated mechanism is substantiated by a detailed theoretical study. This electron transfer event only occurs when Vs < -3 V or Vs > + 3 V and allows access to reactive radical species under exceptionally mild conditions. This transfer can effectively ‘switch on’ a sequence leading to formation of oligomers of defined size distribution due to the on-surface confinement of reactive species. Our approach enables new ways to initiate and control radical oligomerisations with tunnelling electrons, leading to molecularly precise nanofabrication.

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Data-Driven Stability Assessment of Multilayer Long Short-Term Memory Networks

Applied Sciences ◽

10.3390/app11041829 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1829

Author(s):

Davide Grande ◽

Catherine A. Harris ◽

Giles Thomas ◽

Enrico Anderlini

Keyword(s):

Neural Network ◽

Network Architecture ◽

Short Term Memory ◽

Moving Average ◽

Machine Learning Algorithms ◽

Physical Models ◽

Data Driven ◽

The Stability ◽

And Control ◽

Nonlinear Autoregressive

Recurrent Neural Networks (RNNs) are increasingly being used for model identification, forecasting and control. When identifying physical models with unknown mathematical knowledge of the system, Nonlinear AutoRegressive models with eXogenous inputs (NARX) or Nonlinear AutoRegressive Moving-Average models with eXogenous inputs (NARMAX) methods are typically used. In the context of data-driven control, machine learning algorithms are proven to have comparable performances to advanced control techniques, but lack the properties of the traditional stability theory. This paper illustrates a method to prove a posteriori the stability of a generic neural network, showing its application to the state-of-the-art RNN architecture. The presented method relies on identifying the poles associated with the network designed starting from the input/output data. Providing a framework to guarantee the stability of any neural network architecture combined with the generalisability properties and applicability to different fields can significantly broaden their use in dynamic systems modelling and control.

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On the optimal control of coronavirus (2019-nCov) mathematical model; a numerical approach

Advances in Difference Equations ◽

10.1186/s13662-020-02982-6 ◽

2020 ◽

Vol 2020 (1) ◽

Author(s):

N. H. Sweilam ◽

S. M. Al-Mekhlafi ◽

A. O. Albalawi ◽

D. Baleanu

Keyword(s):

Mathematical Model ◽

Optimal Control ◽

Weighted Average ◽

Necessary Optimality Conditions ◽

Numerical Approach ◽

Population Number ◽

Infected People ◽

The Stability ◽

Novel Coronavirus ◽

Theoretical Results

Abstract In this paper, a novel coronavirus (2019-nCov) mathematical model with modified parameters is presented. This model consists of six nonlinear fractional order differential equations. Optimal control of the suggested model is the main objective of this work. Two control variables are presented in this model to minimize the population number of infected and asymptotically infected people. Necessary optimality conditions are derived. The Grünwald–Letnikov nonstandard weighted average finite difference method is constructed for simulating the proposed optimal control system. The stability of the proposed method is proved. In order to validate the theoretical results, numerical simulations and comparative studies are given.

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Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods

Mathematics ◽

10.3390/math9151820 ◽

2021 ◽

Vol 9 (15) ◽

pp. 1820

Author(s):

Ekaterina V. Orlova

Keyword(s):

Interest Rates ◽

Additional Data ◽

Risk Level ◽

Gradient Boosting ◽

Cluster Number ◽

New Approach ◽

Credit Risks ◽

Stochastic Gradient Boosting ◽

The Stability ◽

Digital Footprints

This research deals with the challenge of reducing banks’ credit risks associated with the insolvency of borrowing individuals. To solve this challenge, we propose a new approach, methodology and models for assessing individual creditworthiness, with additional data about borrowers’ digital footprints to implement comprehensive analysis and prediction of a borrower’s credit profile. We suggest a model for borrowers’ clustering based on the method of hierarchical clustering and the k-means method, which groups actual borrowers having similar creditworthiness and similar credit risks into homogeneous clusters. We also design the model for borrowers’ classification based on the stochastic gradient boosting (SGB) method, which reliably determines the cluster number and therefore the risk level for a new borrower. The developed models are the basis for decision making regarding the decision about lending value, interest rates and lending terms for each risk-homogeneous borrower’s group. The modified version of the methodology for assessing individual creditworthiness is presented, which is to reduce the credit risks and to increase the stability and profitability of financial organizations.

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