Development and Application of a High-Performance Triangular Shell Element and an Explicit Algorithm in OpenSees for Strongly Nonlinear Analysis

The open-source finite element software,OpenSees,is widely used in the earthquake engineering community.However,the shell elements and explicit algorithm in OpenSees still require further improvements.Therefore,in this work,a triangular shell element,NLDKGT,and an explicit algorithm are proposed and implemented in OpenSees.Specifically,based on the generalized conforming theory and the updated Lagrangian formulation,the proposed NLDKGT element is suitable for problems with complicated boundary conditions and strong nonlinearity.The accuracy and reliability of the NLDKGT element are validated through typical cases.Furthermore,by adopting the leapfrog integration method,an explicit algorithm in OpenSees and a modal damping model are developed.Finally,the stability and efficiency of the proposed shell element and explicit algorithm are validated through the nonlinear time-history analysis of a highrise building.

Suitable triggering algorithms for detecting strong ground motions using MEMS accelerometers

With the recent development of digital Micro Electro Mechanical System （MEMS） sensors, the cost of monitoring and detecting seismic events in real time can be greatly reduced. Ability of MEMS accelerograph to record a seismic event depends upon the efficiency of triggering algorithm, apart from the sensor＇s sensitivity. There are several classic triggering algorithms developed to detect seismic events, ranging from basic amplitude threshold to more sophisticated pattern recognition. Algorithms based on STA/LTA are reported to be computationally efficient for real time monitoring. In this paper, we analyzed several STA/LTA algorithms to check their efficiency and suitability using data obtained from the Quake Catcher Network （network of MEMS accelerometer stations）. We found that most of the STA/LTA algorithms are suitable for use with MEMS accelerometer data to accurately detect seismic events. However, the efficiency of any particular algorithm is found to be dependent on the parameter set used （i.e., window width of STA, LTA and threshold level）.

Shaping the Wavefront of Incident Light with a Strong Robustness Particle Swarm Optimization Algorithm

We demonstrate a modified particle swarm optimization(PSO) algorithm to effectively shape the incident light with strong robustness and short optimization time. The performance of the modified PSO algorithm and genetic algorithm(GA) is numerically simulated. Then, using a high speed digital micromirror device, we carry out light focusing experiments with the modified PSO algorithm and GA. The experimental results show that the modified PSO algorithm has greater robustness and faster convergence speed than GA. This modified PSO algorithm has great application prospects in optical focusing and imaging inside in vivo biological tissue, which possesses a complicated background.

PROXIMAL POINT ALGORITHM WITH ERRORS FOR GENERALIZED STRONGLY NONLINEARQUASIVARIATIONAL INCLUSIONS

In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an existence theorem of solutions for generalized strongly nonlinear quasivariational inclusion is established and a new proximal point algorithm with errors is suggested for finding approximate solutions which strongly converge to the exact solution of the generalized strongly, nonlinear quasivariational inclusion. As special cases, some known results in this field are also discussed.

Algorithm Selection Method Based on Coupling Strength for Partitioned Analysis of Structure-Piezoelectric-Circuit Coupling

In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis ofstructure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct piezoelectriccoupling and direct piezoelectric and circuit coupling. In the proposed method, implicit and explicit formulationsare used for strong and weak coupling, respectively. Three feasible partitioned algorithms are generated, namely(1) a strongly coupled algorithm that uses a fully implicit formulation for both types of coupling, (2) a weaklycoupled algorithm that uses a fully explicit formulation for both types of coupling, and (3) a partially stronglycoupled and partially weakly coupled algorithm that uses an implicit formulation and an explicit formulation forthe two types of coupling, respectively.Numerical examples using a piezoelectric energy harvester,which is a typicalstructure-piezoelectric-circuit coupling problem, demonstrate that the proposed method selects the most costeffectivealgorithm.

A New Hybrid Algorithm and Its Numerical Realization for a Quasi-nonexpansive Mapping

The purpose of this article is to propose a new hybrid projection method for a quasi-nonexpansive mapping. The strong convergence of the algorithm is proved in real Hilbert spaces. A numerical experiment is also included to explain the effectiveness of the proposed methods. The results of this paper are interesting extensions of those known results.

Stable Perturbed Algorithms for a New Class of Generalized Nonlinear Implicit Quasi Variational Inclusions in Banach Spaces

In this work, a new class of variational inclusion involving T-accretive operators in Banach spaces is introduced and studied. New iterative algorithms for stability for their class of variational inclusions and its convergence results are established.

SINGLE PROJECTION ALGORITHM FOR VARIATIONAL INEQUALITIES IN BANACH SPACES WITH APPLICATION TO CONTACT PROBLEM

We study the single projection algorithm of Tseng for solving a variational inequality problem in a 2-uniformly convex Banach space.The underline cost function of the variational inequality is assumed to be monotone and Lipschitz continuous.A weak convergence result is obtained under reasonable assumptions on the variable step-sizes.We also give the strong convergence result for when the underline cost function is strongly monotone and Lipchitz continuous.For this strong convergence case,the proposed method does not require prior knowledge of the modulus of strong monotonicity and the Lipschitz constant of the cost function as input parameters,rather,the variable step-sizes are diminishing and non-summable.The asymptotic estimate of the convergence rate for the strong convergence case is also given.For completeness,we give another strong convergence result using the idea of Halpern iteration when the cost function is monotone and Lipschitz continuous and the variable step-sizes are bounded by the inverse of the Lipschitz constant of the cost function.Finally,we give an example of a contact problem where our proposed method can be applied.

Strong-form framework for solving boundary value problems with geometric nonlinearity

In this paper, we present a strong-form framework for solving the boundary value problems with geometric nonlinearity, in which an incremental theory is developed for the problem based on the Newton-Raphson scheme. Conventionally, the finite ele- ment methods （FEMs） or weak-form based meshfree methods have often been adopted to solve geometric nonlinear problems. However, issues, such as the mesh dependency, the numerical integration, and the boundary imposition, make these approaches com- putationally inefficient. Recently, strong-form collocation methods have been called on to solve the boundary value problems. The feasibility of the collocation method with the nodal discretization such as the radial basis collocation method （RBCM） motivates the present study. Due to the limited application to the nonlinear analysis in a strong form, we formulate the equation of equilibrium, along with the boundary conditions, in an incremental-iterative sense using the RBCM. The efficacy of the proposed framework is numerically demonstrated with the solution of two benchmark problems involving the geometric nonlinearity. Compared with the conventional weak-form formulation, the pro- posed framework is advantageous as no quadrature rule is needed in constructing the governing equation, and no mesh limitation exists with the deformed geometry in the increment al-it erative process.

Development and application of the mo-ment-ratio imaging algorithm

In the moment-ratio imaging algorithm, which is based on the theory of healing of a wound, the energy of each strong earthquake is distributed around the epicenter according to certain rules, and the features of the Moment-ratio value R are analyzed as the space and time change, so that the relationships between the moment-ration value R and strong earthquakes can be found. In the present paper, regions divided, hypocenter depths and events completed magnitude analyses were carried out in the Chinese catalogue. By applying the moment-ratio imaging algorithm in which the parameters are adjusted, the processes of anomaly evolution which correspond to the epicenter and the surrounding value R before earthquakes of M≥7.0 since 1966 in different areas of China were analyzed. It was found that the range area and imminent time of a coming earthquake could be confirmed quantita- tively by analyzing the abnormal temporal and spatial variation of the value R The results showed that the temporal and spatial variation of the value R could quantitatively reflect the temporal and spatial factors of a coming strong earthquake as well as the rule of medium rupture.

PREDICTOR-CORRECTOR ALGORITHMS FOR SOLVING GENERALIZED MIXED IMPLICIT QUASI-EQUILIBRIUM PROBLEMS

A new class of generalized mixed implicit quasi-equilibrium problems （GMIQEP） with four-functions is introduced and studied. The new class of equilibrium problems includes many known generalized equilibrium problems and generalized mixed implicit quasi-variational inequality problems as many special cases. By employing the auxiliary principle technique, some predictor-corrector iterative algorithms for solving the GMIQEP are suggested and analyzed. The convergence of the suggested algorithm only requires the continuity and the partially relaxed implicit strong monotonicity of the mappings

The Properties Analysis for Generalized Abstract Evolutionary Algorithm

There has been a growing interest in mathematical models to character the evolutionary algorithms. The best-known one of such models is the axiomatic model called the abstract evolutionary algorithm （AEA）, which unifies most of the currently known evolutionary algorithms and describes the evolution as an abstract stochastic process composed of two fundamental abstract operators： abstract selection and evolution operators. In this paper, we first introduce the definitions of the generalized abstract selection and evolution operators. Then we discuss the characterization of some parameters related to generalized abstract selection and evolution operators. Based on these operators, we finally give the strong convergence of the generalized abstract evolutionary algorithm. The present work provides a big step toward the establishment of a unified theory of evolutionary computation.

Realization of Strongly Connected Direction of a Graph

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Instantaneous phase inversion based on an unwrapping algorithm

The full-waveform inversion method is a high-precision inversion method based on the minimization of the misfit between the synthetic seismograms and the observed data.However,this method suffers from cycle skipping in the time domain or phase wrapping in the frequency because of the inaccurate initial velocity or the lack of low-frequency information.furthermore,the object scale of inversion is affected by the observation system and wavelet bandwidth,the inversion for large-scale structures is a strongly nonlinear problem that is considerably difficult to solve.In this study,we modify the unwrapping algorithm to obtain accurate unwrapped instantaneous phase,then using this phase conducts the inversion for reducing the strong nonlinearity.The normal instantaneous phases are measured as modulo 2π,leading the loss of true phase information.The path integral algorithm can be used to unwrap the instantaneous phase of the seismograms having time series and onedimensional(1 D)signal characteristics.However,the unwrapped phase is easily affected by the numerical simulation and phase calculations,resulting in the low resolution of inversion parameters.To increase the noise resistance and ensure the inversion accuracy,we present an improved unwrapping method by adding an envelope into the path integral unwrapping algorithm for restricting the phase mutation points,getting accurate instantaneous phase.The objective function constructed by unwrapping instantaneous phase is less affected by the local minimum,thereby making it suitable for full-waveform inversion.Further,the corresponding instantaneous phase inversion formulas are provided.Using the improved algorithm,we can invert the low-wavenumber components of the underneath structure and ensure the accuracy of the inverted velocity.Finally,the numerical tests of the 2 D Marmousi model and 3 D SEG/EAGE salt model prove the accuracy of the proposed algorithm and the ability to restore largescale low-wavenumber structures,respectively.

Auto-optimization of production-injection rate for reservoirs with strong natural aquifer at ultra-high water cut stage

Based on the optimal control theory and taking the production law of reservoirs with strong natural aquifer as the basic constraint, a mathematical model of liquid production for such reservoirs in the later stage of development is established. The model is solved by improved simultaneous perturbation stochastic approximation algorithm(SPSA), and an automatic optimization software for liquid production is developed. This model avoids the disadvantage of traditional optimization methods that only focus on the maximum value of mathematics but ignore the production law of oilfield. It has the advantages of high efficiency of calculation, short period and automatic optimization. It can satisfy the automatic optimization of liquid production in later stage of oilfield development. The software was applied in the oilfield development of D oilfield, Ecuador in South America, and realized the automatic optimization of liquid production in the later stage of oilfield development.

A STRONG CONVERGENCE THEOREM FOR QUASI-EQUILIBRIUM PROBLEMS IN BANACH SPACES

In this paper,we study an extragradient algorithm for approximating solutions of quasi-equilibrium problems in Banach spaces.We prove strong convergence of the sequence generated by the extragradient method to a solution of the quasi-equilibrium problem.

A Practical Parallel Algorithm for Propositional Knowledge Base Revision

Different methods for revising propositional knowledge base have been proposed recently by several researchers, but all methods are intractable in the general case. For practical application, this paper presents a revision method in special case, and gives a corresponding polynomial algorithm as well as its parallel version on CREW PRAM.

仓库多机器人拣选任务的强繁殖遗传算法规划

为了减小智能仓库拣选机器人的行驶路径,提出了基于强繁殖遗传算法的多机器人拣选任务规划方法。介绍了多机器人系统的混合式控制与智能仓库运行流程,建立了智能仓库的栅格环境模型。以减小机器人行驶路径长度为目标,建立了拣选任务规划的优化模型。在遗传算法中定义了染色体的繁殖能力,根据繁殖能力将染色体分为传统群和加强群;传统群使用传统提出操作方式,维持其较强的繁殖能力;提出了强繁殖交叉和变异方式,从而强制提高加强群的繁殖能力。将强繁殖遗传算法应用于智能仓库拣选任务规划,传统遗传算法任务规划的机器人路径长度为63.0103,强繁殖遗传算法任务规划的路径长度为55.9496,比传统算法减少了11.21%,且强繁殖遗传算法的收敛速度高于传统遗传算法。仿真结果验证了强繁殖遗传算法在智能仓库拣选任务规划中的优越性。

基于关联规则的互联网医疗服务平台在肿瘤患者诊疗管理中的应用

目的探讨基于FP-Growth算法的有效强关联规则分析在肿瘤患者诊疗管理中的应用。方法在现有互联网医疗服务平台和电子病历系统基础上增加FP-Growth算法功能,通过FP-Growth算法挖掘2017年12月-2021年12月样本医院肿瘤放射治疗中心2075例患者和其中高危群体患者基线资料间的有效强关联规则,并将之用于肿瘤放射治疗中心。结果FP-Growth算法共反馈有效强关联规则15条,其中全部患者10条、高危群体患者5条,根据反馈结果调整了肿瘤放射治疗中心患者的治疗方案。结论增加了FP-Growth算法功能的互联网医疗服务平台具有临床应用价值。

具有限族半压缩映射的修正惯性同步算法的强收敛性

研究一个新的具有限族半压缩映射的修正惯性同步算法。在希尔伯特空间框架下,结合压缩映射,在适当的条件下建立一些强收敛定理。同时,给出了一个数值例子来说明所建议的算法的有效性。