Most numerical integration techniques consist of approximating the integrand by a polynomial in a region or regions and then integrating the polynomial exactly. Often a complicated integrand can be factored into a non-negative ''weight'' function and another function better approximated by a polynomial, thus $\int_{a}^{b} g(t)dt = \int_{a}^{b} \omega (t)f(t)dt \approx \sum_{i=1}^{N} w_i f(t_i)$. Hopefully, the quadrature rule ${\{w_j, t_j\}}_{j=1}^{N}$ corresponding to the weight function $\omega$(t) is available in tabulated form, but more likely it is not. We present here two algorithms for generating the Gaussian quadrature rule defined by the weight function when: a) the three term recurrence relation is known for the orthogonal polynomials generated by $\omega$(t), and b) the moments of the weight function are known or can be calculated.

Calculation of Gauss quadrature rules.

Structural systems often show nonlinear behavior under severe excitations generated by natural hazards. In that condition, the restoring force becomes highly nonlinear showing significant hysteresis. The hereditary nature of this nonlinear restoring force indicates that the force cannot be described as a function of the instantaneous displacement and velocity. Accordingly, many hysteretic restoring force models were developed to include the time dependent nature using a set of differential equations. This survey contains a review of the past, recent developments and implementations of the Bouc-Wen model which is used extensively in modeling the hysteresis phenomenon in the dynamically excited nonlinear structures.

The Hysteresis Bouc-Wen Model, a Survey

https://orbilu.uni.lu/bitstream/10993/14191/2/iga_final.pdf

Isogeometric analysis: an overview and computer implementation aspects

This paper is focused on reliable fuzzy H∞ controller design for active suspension systems with actuator delay and fault. The Takagi-Sugeno (T-S) fuzzy model approach is adapted in this study with the consideration of the sprung and the unsprung mass variation, the actuator delay and fault, and other suspension performances. By the utilization of the parallel-distributed compensation scheme, a reliable fuzzy H∞ performance analysis criterion is derived for the proposed T-S fuzzy model. Then, a reliable fuzzy H∞ controller is designed such that the resulting T-S fuzzy system is reliable in the sense that it is asymptotically stable and has the prescribed H∞ performance under given constraints. The existence condition of the reliable fuzzy H∞ controller is obtained in terms of linear matrix inequalities (LMIs) Finally, a quarter- vehicle suspension model is used to demonstrate the effectiveness and potential of the proposed design techniques.

/pdf/reliable-fuzzy-control-for-active-suspension-systems-with-1uo5wm4d8y.pdf

Reliable Fuzzy Control for Active Suspension Systems With Actuator Delay and Fault

In a developing organism, tissues emerge from coordinated sequences of cell renewal, differentiation, and assembly that are orchestrated by spatial and temporal gradients of multiple regulatory factors. The composition, architecture, signaling, and biomechanics of the cellular microenvironment act in concert to provide the necessary cues regulating cell function in the developing and adult organism. With recent major advances in stem cell biology, tissue engineering is becoming increasingly oriented toward biologically inspired in vitro cellular microenvironments designed to guide stem cell growth, differentiation, and functional assembly. The premise is that to unlock the full potential of stem cells, at least some aspects of the dynamic three-dimensional (3D) environments that are associated with their renewal, differentiation, and assembly in native tissues need to be reconstructed. In the general context of tissue engineering, we discuss the environments for guiding stem cell function by an interactive use of biomaterial scaffolds and bioreactors, and focus on the interplay between molecular and physical regulatory factors. We highlight some illustrative examples of controllable cell environments developed through the interaction of stem cell biology and tissue engineering at multiple levels.

/pdf/engineered-microenvironments-for-controlled-stem-cell-20yzq9bsvk.pdf

Engineered Microenvironments for Controlled Stem Cell Differentiation

http://hub.hku.hk/bitstream/10722/54269/2/92945.pdf?accept=1

Semi-active H∞ control of vehicle suspension with magneto-rheological dampers

Correcting power-law viscoelastic effects in elastic modulus measurement using depth-sensing indentation

The Incremental Harmonic Balance Method for Nonlinear Vibration of Axially Moving Beams

In the recent years, solid-shell finite element models which possess no rotational degrees of freedom and applicable to thin plate/shell analyses have attracted considerable attention. Development of these elements are not straightforward. Shear, membrane, trapezoidal, thickness and dilatational lockings must been visioned. In this part of this paper, a novel eight-node solid-shell element is proposed. To resolve the shear and trapezoidal lockings, the assumed natural strain (ANS) method is resorted to. The hybrid-stress formulation is employed to rectify the thickness and dilatational locking. The element is computationally more efficient than the conventional hybrid elements by adopting orthogonal-assumed stress modes and enforcing admissible sparsity in the flexibility matrix. Popular benchmark tests are exercised to illustrate the efficacy of the elements. In Part II of the paper, the element will be generalized for smart structure modelling by including the piezoelectric effect. Copyright © 2000 John Wiley & Sons, Ltd.

Kam Yim Sze

Papers

Popular benchmark problems for geometric nonlinear analysis of shells

Semi-active H∞ control of vehicle suspension with magneto-rheological dampers

Correcting power-law viscoelastic effects in elastic modulus measurement using depth-sensing indentation

The Incremental Harmonic Balance Method for Nonlinear Vibration of Axially Moving Beams

A hybrid stress ANS solid-shell element and its generalization for smart structure modelling. Part I—solid-shell element formulation