Localized identification of shear building with embedded foundation in frequency domain

For studying the behavior of structure in an earthquake, it is advisable to model the structure as a multi‐degrees of freedom system, consisting of numerous single‐degree of freedom substructures and pay attention to soil–structure interaction. System identification is divided into two categories: namely time domain method and frequency domain approach. In this paper, a localized substructure identification of shear building considering the soil–structure interaction is presented using a frequency domain approach. In order to deal with noise‐corrupted data, a spectral smoothing technique with Parzen's window reduction method is adapted. It is shown that better convergence and accuracy can be achieved by the present technique. As a result, it is shown that by taking into account the soil–structure interaction more realistic results can be obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Online detection of the breathing crack using an adaptive tracking technique

Summary Early detection of structural damage is an important goal of any structural health monitoring system. Among numerous data analysis techniques, those which are used for online damage detection have received considerable attention recently, although the problem of online detection in continuous structures, for example beams, is quite challenging. In this paper, it is shown how the type, the size and the location of breathing cracks are identified online with the use of the records which are gathered from a continuous beam. For determining the existence of a breathing crack in a beam, its vibrating behavior is simulated. The algorithm of the least square estimation with the use of adaptive tracking is employed for identification purposes. This algorithm is capable of detecting the abrupt changes in problem parameters and traces its variations. With the use of reducing domain algorithm, this identification method shows better results and can detect the breathing crack in beams more efficiently. Finally, it is shown that with the use of sufficient mode shapes the method is capable of identifying the breathing crack in beams and frames. The efficiency of the proposed algorithm is shown through some case studies.     

An investigation on the effect of SBS+Vacuum bottoms residue modification on rheological characteristics of asphalt binder

In this research, the effect of adding SBS and vacuum bottoms residue on 60/70 neat asphalt binder have been carried out using classic and superpave testing methods. Adding SBS led to increase of softening point, elastic recovery and viscosity of asphalt binder. Besides, SBS reduced the penetration and ductility of specimens. Results of dynamic shear rheometer indicated that G^* and G^*sinδ reduced by adding the SBS content before and after aging while δ and G^*/sinδ parameters increased. Therefore, adding SBS improves the permanent deformation and fatigue resistance of neat asphalt binder.     

Approximate dynamic programming for two-player zero-sum game related to <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control of unknown nonlinear continuous-time systems

This paper develops a concurrent learning-based approximate dynamic programming (ADP) algorithm for solving the two-player zero-sum (ZS) game arising in H _∞ control of continuous-time (CT) systems with unknown nonlinear dynamics. First, the H _∞ control is formulated as a ZS game and then, an online algorithm is developed that learns the solution to the Hamilton-Jacobi-Isaacs (HJI) equation without using any knowledge on the system dynamics. This is achieved by using a neural network (NN) identifier to approximate the uncertain system dynamics. The algorithm is implemented on actor-critic-disturbance NN structure along with the NN identifier to approximate the optimal value function and the corresponding Nash solution of the game. All NNs are tuned at the same time. By using the idea of concurrent learning the need to check for the persistency of excitation condition is relaxed to simplified condition. The stability of the overall system is guaranteed and the convergence to the Nash solution of the game is shown. Simulation results show the effectiveness of the algorithm.     

Ozone treatment for improving the solubility of cellulose extracted from palm fiber

We investigated effects of ozone treatment on solubility of cellulose and chemical composition in cellulose extracted from palm fiber. The initial holocellulose, α-cellulose, and lignin contents of the extracted cellulose were 88.0, 81.9, and 8.75%, respectively. The extracted cellulose was treated with ozone and NaOH solution. Ozone treatment for 5 hr at 40°C using 3% citric acid decreased the lignin content from 8.75 to 2.71%. Under these conditions, the degree of polymerization (DP) of the cellulose decreased to 29 from 160 and the carboxyl content increased to 2.05 mmol/g. When the solid phase was treated with NaOH after ozone treatment, the mass of the solid phase decreased as the ozone treatment time increased. The lowest mass was 0.43 g. Additionally, the mass of cellulose regenerated from the liquid phase increased with increasing treatment time. The highest mass of regenerated cellulose was 0.54 g. The masses of the solid phase and regenerated cellulose obtained without ozone treatment under the same conditions were 0.76 and 0.18 g, respectively. These results suggest that ozone treatment improves the solubility of cellulose by converting hydroxyl groups in the cellulose to carboxyl groups and reducing the DP.     

Fabrication of chitosan nanoparticles incorporated with Pistacia atlantica subsp. kurdica hulls’ essential oil as a potential antifungal preservative against strawberry grey mould

Essential oil was extracted from Pistacia atlantica subsp. kurdica hulls and encapsulated in chitosan nanoparticles (NPs) by an emulsion-ionic gelation method. A desirable retention rate (43.3–61.5%) of P. atlantica subsp. kurdica hulls’ essential oil (PAHEO) encapsulated in chitosan NPs was confirmed. In addition, the Fourier transform infrared spectroscopy and X-ray diffraction analysis results revealed the success of PAHEO encapsulation. The formed NPs illustrated a shrunk and spherical shape with a size range of 187.2–632.5 nm as indicated by scanning electron microscopy and dynamic light scattering. The encapsulated PAHEO had a high antifungal activity against Botrytis cinerea under both the in vitro and in vivo conditions. It also significantly decreased the incidence and disease severity of grey mould on strawberries during storage. The spoilage process was postponed by the 8th days of storage at 4 °C in the strawberry fruit treated by PAHEO-incorporated chitosan NPs. These findings imply that NP-encapsulated PAHEO will have promising novel applications in food industries.     

Online concurrent reinforcement learning algorithm to solve two‐player zero‐sum games for partially unknown nonlinear continuous‐time systems

Online adaptive optimal control methods based on reinforcement learning algorithms typically need to check for the persistence of excitation condition, which is necessary to be known a priori for convergence of the algorithm. However, this condition is often infeasible to implement or monitor online. This paper proposes an online concurrent reinforcement learning algorithm (CRLA) based on neural networks (NNs) to solve the H _∞ control problem of partially unknown continuous‐time systems, in which the need for persistence of excitation condition is relaxed by using the idea of concurrent learning. First, H _∞ control problem is formulated as a two‐player zero‐sum game, and then, online CRLA is employed to obtain the approximation of the optimal value and the Nash equilibrium of the game. The proposed algorithm is implemented on actor–critic–disturbance NN approximator structure to obtain the solution of the Hamilton–Jacobi–Isaacs equation online forward in time. During the implementation of the algorithm, the control input that acts as one player attempts to make the optimal control while the other player, that is, disturbance, tries to make the worst‐case possible disturbance. Novel update laws are derived for adaptation of the critic and actor NN weights. The stability of the closed‐loop system is guaranteed using Lyapunov technique, and the convergence to the Nash solution of the game is obtained. Simulation results show the effectiveness of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.