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This paper presents an efficient methodology to calculate fuzzy eigenvalues and eigenvectors of finite element structures defined by imprecise parameters. The material and geometric parameters are then described by fuzzy numbers. The proposed methodology, based on α‐cut discretization of fuzzy numbers and Taylor's expansion, determines the extreme eigensolutions for each α‐cut. The study of a finite element model and the comparison of results with a combinatorial approach, based on Zadeh's extension principle, show the efficiency of this methodology.

This paper presents a new framework to predict a structure’s effective properties and sensitivities to multiple simultaneous uncertain endogenous parameters. The methodology is based on the use of fuzzy sets and this paper extends the fuzzy set theory to a dynamic finite element analysis of engineering systems containing uncertainty on material properties. A general algorithm, which can resolve the uncertain eigenvalue problem by using a Neumann expansion, is studied. This algorithm is applied to the study of the modal behavior of structures presenting uncertain material properties. Finally, the entropy and the specificity of fuzzy responses lead to the identification of a plate structure’s most sensitive eigenvalue to uncertain sources.

The purpose of this paper is to present a new way to solve numerically a mechanical frictionless contact problem within a context of multiple sampling, frequently used to design robust structures.

This paper proposes to integrate a control-based approach, currently used in automation domain, for the solving of non-linear mechanical problem. More precisely, a fuzzy logic controller is designed to create a link between the normal gaps identified between the bodies and the normal contact pressures applied at the interface.

With this new strategy, the initial non-linear problem can be decomposed into a set of reduced linear problems solved using the finite element method. A projection built from the modal bases of each component in contact is considered to reduce computational time. Moreover, the proposed numerical applications highlight an interesting compromise between computation time and precision of contact data.

Currently, the proposed Fuzzy Logic Controller for Contact method has been developed for a frictionless contact problem in the case of 2D numerical applications. Therefore, as obtained results are very interesting, it will be possible to expand on these works in a future works for more complex problems including friction, 3D model and transient dynamic responses by adding other controllers.

In conclusion, this paper highlights the interest of studying a contact problem by considering automation approaches and defines the basis of future multidisciplinary works.

This paper aims to to simulate the flow and heat transfer during free convection in a square cavity using double-multi-relaxation time (MRT) lattice Boltzmann method.

The double-MRT lattice Boltzmann method is used, and the natural convection fluid flow and heat transfer under influence of different parameters are analyzed. The D2Q5 model and D2Q9 model are used for simulation of temperature field and flow field, respectively. The cavity is filled with CuO-water nanofluid; in addition, the thermo-physical properties of nanofluid and the effect of nanoparticles’ shapes are considered using Koo–Kleinstreuer–Li (KKL) model. On the other hand, the cavity is included with an internal active hollow with constant thermal boundary conditions at its walls and variable dimensions. It should be noted that the dimensions of the internal hollow will be determined by as aspect ratio.

The Rayleigh number, nanoparticle concentration and the aspect ratio are the governing parameters. The heat transfer performance of the cavity has direct relationship with the Rayleigh number and solid volume fraction of CuO-water nanofluid. Moreover, the configuration of the cavity is good controlling factor for changing the heat transfer performance and entropy generation.

The originality of this work is using double-MRT lattice Boltzmann method in simulating the free convection fluid flow and heat transfer.

Many analysis and design problems in engineering and science involve uncertainty to varying degrees. This paper is concerned with the structural vibration problem involving uncertain material or geometric parameters, specified as fuzzy parameters. The requirement is to propagate the parameter uncertainty to the eigenvalues of the structure, specified as fuzzy eigenvalues. However, the usual approach is to transform the fuzzy problem into several interval eigenvalue problems by using the α-cuts method. Solving the interval problem as a generalized interval eigenvalue problem in interval mathematics will produce conservative bounds on the eigenvalues. The purpose of this paper is to investigate strategies to efficiently solve the fuzzy eigenvalue problem.

Based on the fundamental perturbation principle and vertex theory, an efficient perturbation method is proposed, that gives the exact extrema of the first-order deviation of the structural eigenvalue. The fuzzy eigenvalue approach has also been improved by reusing the interval analysis results from previous α-cuts.

The proposed method was demonstrated on a simple cantilever beam with a pinned support, and produced very accurate fuzzy eigenvalues. The approach was also demonstrated on the model of a highway bridge with a large number of degrees of freedom.

This proposed Vertex-Perturbation method is more efficient than the standard perturbation method, and more general than interval arithmetic methods requiring the non-negative decomposition of the mass and stiffness matrices. The new increment method produces highly accurate solutions, even when the membership function for the fuzzy eigenvalues is complex.

The paper's aim is to explore the impact of statistical arbitrage and high-frequency trading as hedge fund investment strategies that have a significant impact on the environment of corporations.

The paper is a meta-analysis of the role of investment strategies within complex systems.

The growth of hedge fund investment activity based on statistical arbitrage tends to produce a vulnerability; more funds using the strategy helps to create the profitable outcomes that the strategy relies upon. However, the growth also reduces the time lines of profitability and produces an underlying instability based on overlapping holdings and the use of leverage. The shortened timelines also create a further impetus towards technological competition and promotes high frequency trading, which then introduces further vulnerabilities based on “stop-loss cascades”.

Much of the trading creates a superficial form of liquidity, which gives a limited sense of market vulnerabilities. The basis of complex interactions between high frequency traders is also not clearly understood. Researchers and agents of policy ought to pay greater attention to the issues than is currently the case.

The area is one that is under-researched.

Companies deal with many decision‐making processes whose impact on the global performance can be very strong. As a consequence, the role of the decision support systems (DSSs) within the organization is critical. Considering the imprecise or fuzzy nature of the data in real‐world problems, it becomes obvious that the ability to manage uncertainty turns out to be a crucial issue for a DSS. In this framework, this paper discusses the key role of fuzzy logic (FL) in the DSSs, presents new applications of FL in DSSs in various sectors and identifies new challenges and new directions for further research.

Natural convection heat transfer during free convection phenomenon in a cavity included with active fins and pipes is investigated. The influence of the orientation of fins on the heat transfer between heat source (i.e. hot fins) and heat sink (i.e. cold pipes) is investigated by using numerical and experimental techniques.

For the numerical simulations, the multiple relaxation time (MRT) thermal lattice Boltzmann method (LBM) is used. In this numerical approach, two separated distribution functions are used to solve the flow and temperature distributions within the computational domain. Furthermore, the local/volumetric second law analysis is used to show the impact of evaluated parameters on the heat transfer irreversibility. In addition, the dynamic viscosity and thermal conductivity of TiO2-water nanofluid are measured by using Brookfield viscometer and KD2 pro conductmeter, respectively.

The examined range of Rayleigh number is from 103 to 106, and the nanofluid samples are provided in 0, 20, 40, 60, 80 and 100 ppm.

The originality of this work is use of dual-MRT thermal LBM and experimental measurements of rheological/thermal properties of nanofluid for investigation of free convection problem for the considered application.

The purpose of this paper is to expand the previously published fuzzy logic controller for contact method to normal frictionless contact for solving mechanical frictional contact problems. The secondary aim is to integrate a reduction model for each component in contact to decrease the size of the global finite element contact problem.

The proposed strategy relies on the design of two fuzzy logic controllers currently used in the automation domain. These controllers are considered to link normal and tangential gaps (for sticking conditions) with normal and tangential contact loads. A direct consequence of integrating a control-based approach into the numerical solving approach is the decomposition of the non-linear problem into a set of linear problems.

With this new strategy, no tangent or coupling matrix is defined for the contact problem that allows to consider a projection matrix to reduce the size of each component in contact and subsequently to decrease the associated computational time. As in condensation techniques, this matrix is composed of both modal bases of each component in contact and static modes that capture behaviors at the contact interface. Moreover, the proposed numerical application highlights the efficiency of the proposal in terms of computation time and precision of contact data.

The developments are currently implemented in Matlab only for 2D static numerical applications. Therefore, as obtained results are very promising in terms of precision and computational time, the objective is to complete the proposed method in future research to manage frictional contact for 3D finite element models in a dynamic context.

In conclusion, this paper highlights the interest of studying mechanical frictional contact problems by considering fuzzy logic control approaches.

The paper targets on providing new experimental data for validation of the well-established mathematical models within the framework of the lattice Boltzmann method (LBM), which are applied to problems of casting processes in complex mould cavities.

An experimental campaign aiming at the free-surface flow within a system of narrow channels is designed and executed under well-controlled laboratory conditions. An in-house lattice Boltzmann solver is implemented. Its algorithm is described in detail and its performance is tested thoroughly using both the newly recorded experimental data and well-known analytical benchmark tests.

The benchmark tests prove the ability of the implemented algorithm to provide a reliable solution when the surface tension effects become dominant. The convergence of the implemented method is assessed. The two new experimentally studied problems are resolved well by simulations using a coarse computational grid.

A detailed set of original experimental data for validation of computational schemes for simulations of free-surface gravity-driven flow within a system of narrow channels is presented.