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Intrinsic signal processed non-linearity tolerant novel 2-Tier star constellation

OPTICAL AND QUANTUM ELECTRONICS 2022年第2期54卷 104-104页

作者： Khaki, Zahid G. Qazi, Gausia Natl Inst Technol Dept Elect & Commun Engn Srinagar 190006 Jammu & Kashmir India Islamic Univ Sci & Technol Dept Elect & Commun Engn Awantipora Pulwama India

In coherent optical systems, optical fiber non-linearity is a consistent limiting factor towards the effective signal-to-noise ratio though being mitigated by various digital signal processing based approaches. In this paper, an intrinsic method of signal processing based on the shape of the input constellation is employed to yield a novel non-linearity tolerant geometric constellation. 16-QAM back-to-back coherent system is optimized for minimum value of non-linear interference, and a novel 2-Tier star constellation using sequential quadratic programming algorithm is proposed. The values of second and fourth order moments of input obtained for the optimized 2-Tier star constellation are 1.19 and 1.70 respectively, resulting in an overall reduction of non-linear interference. The complexity of the system proposed is found to be minimal in comparison to the other existing systems employing digital compensation.

关键词： Constellation shaping Geometric shaping sequential quadratic programming Non-linearity mitigation Non-linear interference noise 16-Quadrature amplitude modulation

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Design of intelligent computing solver with Morlet wavelet neural networks for nonlinear predator-prey model

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APPLIED SOFT COMPUTING 2023年 134卷

作者： Umar, Muhammad Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Amin, Fazli Saeed, Tareq Sanchez, Yolanda Guerrero Hazara Univ Dept Math & Stat Mansehra Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Yunlin 64002 Taiwan COMSATS Univ Islamabad Dept Elect & Comp Engn Attock Campus Attock 43600 Pakistan King Abdulaziz Univ Fac Sci Dept Math Nonlinear Anal & Appl Math NAAM Res Grp Jeddah 21589 Saudi Arabia Univ Murcia Dept Dermatol Stomatol Radiol & Phys Med Murcia Spain Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon

The design of integrated intelligent computing solver with Morlet wavelet neural networks (MW-NNs) is presented for solving the mathematical predator-prey model by exploiting the strength of MW-NNs modeling, optimization ability of global search with genetic algorithms (GAs) and rapid local search eminence of sequential quadratic programming (SQP), i.e., MW-NNs-GA-SQP. The proposed MW-NNs-GA-SQP scheme is used to analyze the predator-prey dynamics for six different variables coefficient values. The validation, correctness and reliability of the presented MW-NNs-GA-SQP technique is attained through the consistent matched outcomes with the reference Adams numerical results. Moreover, statistics investigations have been accomplished to verify the precision and accuracy of the outcomes with proposed MW-NNs-GA-SQP solver via the performances of Theil's inequality coefficient, Nash Sutcliffe efficiency and mean absolute error.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Predator-prey model Morlet wavelet neural networks sequential quadratic programming Genetic algorithm Intelligent computing Numerical computing

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Design of moth flame optimization heuristics for integrated power plant system containing stochastic wind

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APPLIED SOFT COMPUTING 2021年 104卷 107193-107193页

作者： Khan, Babar Sattar Raja, Muhammad Asif Zahoor Qamar, Affaq Chaudhary, Naveed Ishtiaq Univ Engn & Technol Peshawar Dept Elect Energy Syst Engn USPCAS E Peshawar Khyber Pakhtunk Pakistan COMSATS Univ Islamabad Dept Elect & Comp Engn Campus Attock Attock Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Int Islamic Univ Dept Elect Engn Islamabad Pakistan

In this investigation, nature-inspired heuristic strategy exploiting moth flame optimization (MFO) algorithm combined with active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) are presented to take care of the enhancement issues of economic load dispatch (ELD) problem involving valve point loading effect (VPLE) and stochastic wind (SW). The strength of MFO algorithm is used as a global search mechanism that explore and exploit the entire search space while ASA, IPA and SQP are responsible for refinement of local optimum. The performance of the design system is based on 40 generating units including 37 thermal and 3 wind power units and is evaluated to verify the effectiveness of the scheme. The worth of the design integrated heuristic of MFO algorithm is endorsed through outcomes of the state of the art counterpart solvers in case of ELD problems integrated with wind power units in terms of cost minimization and computational complexity parameters. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Moth flame optimization algorithm sequential quadratic programming Active-set algorithm Interior-point algorithm Economic load dispatch Integrated power systems

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Deterministic and reliability-based optimization of composite laminates for cryogenic environments

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AIAA JOURNAL 2003年第10期41卷 2029-2036页

作者： Qu, XY Haftka, RT Venkataraman, S Johnson, TF Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA San Diego State Univ Dept Aerosp Engn & Engn Mech San Diego CA 92182 USA NASA Langley Res Ctr Mech & Durabil Branch Hampton VA 23681 USA

Designs of composite laminates are investigated for hydrogen tanks in cryogenic environments. Large residual strains, which can develop due to thermal mismatch between matrix and fibers, result in matrix cracking at cryogenic temperatures and increase hydrogen leakage through the tank wall. To reduce thermal mismatch, ply angles need to be close to each other, but this leads to a substantial weight increase under biaxial loading. First deterministic optimization is used to investigate possible weight reduction measures. Reducing axial loads on walls by auxiliary stiffening mechanisms led to significant weight reduction. Reliability-based optimizations were performed to identify the uncertainties in composite material properties with the largest influences on the optimum design. Then measures for reducing uncertainty in important parameters are examined. The results indicate that the most effective measure for reducing thickness is quality control.

关键词： Composite Laminates Material Properties Thermal Expansion Residual Strain Cryogenic Temperature Elastic Properties Statistical Distributions Monte Carlo Simulation Central Composite Designs sequential quadratic programming

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Meyer wavelet neural networks to solve a novel design of fractional order pantograph Lane-Emden differential model

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CHAOS SOLITONS & FRACTALS 2021年 152卷

作者： Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Guirao, Juan L. G. Saeed, Tareq Hazara Univ Dept Math & Stat Mansehra Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Tech Univ Cartagena Hosp Marina Dept Appl Math & Stat Cartagena 30203 Spain King Abdulaziz Univ Fac Sci Dept Math Nonlinear Anal & Appl Math NAAM Res Grp POB 80203 Jeddah 21589 Saudi Arabia

The aim of this study is to design a singular fractional order pantograph differential model by using the typical form of the Lane-Emden model. The necessary details of the singular-point, fractional order and shape factor of the designed model are also provided. The numerical solutions of the designed model have been presented using the combination of the fractional Meyer wavelet (FMW) neural networks (NNs) modeling and optimization of global search with genetic algorithm (GA) supported with local search of sequential quadratic programming (SQP), i.e., FMWNN-GASQP. The strength of FMWNN is employed to design an objective function using the differential model along with its initial conditions of the singular fractional order pantograph model. The optimization of this objective function is performed using the integrated competence of GA-SQP. The verification, perfection and authentication of the singular fractional order pantograph model using fractional Meyer computing solver is observed for different cases through comparative studies from the available exact solutions which endorsed its robustness, convergence and stability. Moreover, the statistics observation with necessary explanations further authenticate the performance of the FMWNN-GASQP in terms of accuracy and reliability. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Singular fractional order pantograph model Shape factors Meyer wavelet neural models sequential quadratic programming Genetic algorithm Statistical analysis

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Optimal control of thermal and mechanical loads in activation processes of mechanical components

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APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING 2024年第1期32卷

作者： Friedlich, Nicolai Gottschalk, Hanno Vossen, Georg Niederrhein Univ Appl Sci Inst Modelling & High Performance Comp Krefeld Germany Tech Univ Berlin Inst Math Berlin Germany

This paper develops a mathematical framework that aims to control the temperature and rotational speed in the activation process of a gas turbine in an optimal way. These controls influence the deformation and the stress in the component due to centripetal loads and transient thermal stress. An optimal control problem is formulated as the minimization of maximal von Mises stress over a given time and over the whole component. To find a solution for this, we need to solve the linear thermoelasticity and the heat equations using the finite element method. The results for the optimal control as functions of the rotation speed and external gas temperature over time are computed by sequential quadratic programming, where gradients are computed using finite differences. The overall outcome reveals a significant reduction of approximately 10%, from $ 830\,\frac {{\rm N}}{{\rm mm}<^>2} $ 830Nmm2 to $ 750\,\frac {{\rm N}}{{\rm mm}<^>2} $ 750Nmm2, in von Mises stress by controlling two parameters, along with the temporal separation of physical control phenomena.

关键词： Activation of mechanical components optimal control finite element method sequential quadratic programming

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Selecting probabilistic approaches for reliability-based design optimization

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AIAA JOURNAL 2004年第1期42卷 124-131页

作者： Youn, BD Choi, KK Univ Iowa Ctr Comp Aided Design Coll Engn Iowa City IA 52241 USA Univ Iowa Dept Mech Engn Coll Engn Iowa City IA 52241 USA

During the past decade, numerous endeavors have been made to develop effective reliability-based design optimization (RBDO) methods. Because the evaluation of probabilistic constraints defined in the RBDO formulation is the most difficult part to deal with, a number of different probabilistic design approaches have been proposed to evaluate probabilistic constraints in RBDO In the first approach, statistical moments are approximated to evaluate the probabilistic constraint. Thus, this is referred to as the approximate moment approach (AMA). The second approach, called the reliability index approach (RIA), describes the probabilistic constraint as a reliability index. Last, the performance measure approach (PMA) was proposed by converting the probability measure to a performance measure. A guide for selecting an appropriate method in RBDO is provided by comparing probabilistic design approaches for RBDO from the perspective of various numerical considerations. It has been found in the literature that PMA is more efficient and stable than RIA in the RBDO process. It is found that PMA is accurate enough and stable at an allowable efficiency, whereas AMA has some difficulties in RBDO process such as a second-order design sensitivity required for design optimization, an inaccuracy to measure a probability of failure, and numerical instability due to its inaccuracy. Consequently, PMA has several major advantages over AMA, in terms of numerical accuracy, simplicity, and stability. Some numerical examples are shown to demonstrate several numerical observations on the three different RBDO approaches.

关键词： Cumulative Distribution Function sequential quadratic programming Sensitivity Analysis Monte Carlo Simulation Iterative Algorithm Crashworthiness Design of Experiments Search Algorithm Structural Modeling Computing Power

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Solving a novel designed second order nonlinear Lane-Emden delay differential model using the heuristic techniques

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APPLIED SOFT COMPUTING 2021年 102卷 107105-107105页

作者： Sabir, Zulqurnain Guirao, Juan L. G. Saeed, Tareq Hazara Univ Dept Math & Stat Mansehra Pakistan Tech Univ Cartagena Hosp Marina Dept Appl Math & Stat Cartagena 30203 Spain King Abdulaziz Univ Fac Sci Dept Math Nonlinear Anal & Appl Math NAAM Res Grp POB 80203 Jeddah 21589 Saudi Arabia

The aim of the present study is to present a new model based on the nonlinear singular second order delay differential equation of Lane-Emden type and numerically solved by using the heuristic technique. Four different examples are presented based on the designed model and numerically solved by using artificial neural networks optimized by the global search, local search methods and their hybrid combinations, respectively, named as genetic algorithm (GA), sequential quadratic programming (SQP) and GA-SQP. The numerical results of the designed model are compared for the proposed heuristic technique with the exact/explicit results that demonstrate the performance and correctness. Moreover, statistical investigations/assessments are presented for the accuracy and performance of the designed model implemented with heuristic methodology. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Delay differential equations Lane-Emden Artificial neural networks Nonlinear Genetic algorithm Statistical analysis sequential quadratic programming

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Optimal Design of Bubble Deck Concrete Slabs: Serviceability Limit State

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MATERIALS 2023年第14期16卷 4897-4897页

作者： Gajewski, Tomasz Staszak, Natalia Garbowski, Tomasz Poznan Univ Tech Inst Struct Anal Piotrowo 5 PL-60965 Poznan Poland Poznan Univ Life Sci Doctoral Sch Wojska Polskiego 28 PL-60637 Poznan Poland Poznan Univ Life Sci Dept Biosyst Engn Wojska Polskiego 50 PL-60627 Poznan Poland

In engineering practice, one can often encounter issues related to optimization, where the goal is to minimize material consumption and minimize stresses or deflections of the structure. In most cases, these issues are addressed with finite element analysis software and simple optimization algorithms. However, in the case of optimization of certain structures, it is not so straightforward. An example of such constructions are bubble deck ceilings, where, in order to reduce the dead weight, air cavities are used, which are regularly arranged over the entire surface of the ceiling. In the case of these slabs, the flexural stiffness is not constant in all its cross-sections, which means that the use of structural finite elements (plate or shell) for static calculations is not possible, and therefore, the optimization process becomes more difficult. This paper presents a minimization procedure of the weight of bubble deck slabs using numerical homogenization and sequential quadratic programming with constraints. Homogenization allows for determining the effective stiffnesses of the floor, which in the next step are sequentially corrected by changing the geometrical parameters of the floor and voids in order to achieve the assumed deflection. The presented procedure allows for minimizing the use of material in a quick and effective way by automatically determining the optimal parameters describing the geometry of the bubble deck floor cross-section. For the optimal solution, the concrete weight of the bubble deck slab was reduced by about 23% in reference to the initial design, and the serviceability limit state was met.

关键词： lightweight structures bubble deck concrete slabs numerical homogenization weight minimization sequential quadratic programming

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A velocity tracking approach for the data assimilation problem in blood flow simulations

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2017年第10期33卷 2017 Oct;33(10)页

作者： Tiago, J. Guerra, T. Sequeira, A. ULisboa Dept Math Lisbon Portugal ULisboa CEMAT IST Lisbon Portugal Inst Politecnico Setubal ESTBarreiro Setubal Portugal

Several advances have been made in data assimilation techniques applied to blood flow modeling. Typically, idealized boundary conditions, only verified in straight parts of the vessel, are assumed. We present a general approach, on the basis of a Dirichlet boundary control problem, that may potentially be used in different parts of the arterial system. The relevance of this method appears when computational reconstructions of the 3D domains, prone to be considered sufficiently extended, are either not possible, or desirable, because of computational costs. On the basis of taking a fully unknown velocity profile as the control, the approach uses a discretize then optimize methodology to solve the control problem numerically. The methodology is applied to a realistic 3D geometry representing a brain aneurysm. The results show that this data assimilation approach may be preferable to a pressure control strategy and that it can significantly improve the accuracy associated to typical solutions obtained using idealized velocity profiles.

关键词： blood flow boundary control data assimilation sequential quadratic programming

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