Temporal variation of dynamical modal properties of a base-isolated building is investigated using earthquake records in the building. A batch processing least-squares estimation method is applied to segment-wise time-series data. To construct an input-output system, an auto-regressive model with exogenous input (ARX) of second-order including a forgetting coefficient as a weighting coefficient is used for the estimation of modal parameters. The fundamental and second natural frequencies and the damping ratios of the fundamental and second natural modes of the base-isolated building are identified in the time domain. The identified results are consistent with the results obtained from the micro-tremor vibration data, forced-vibration test data and earthquake records in the present base-isolated building in the case of taking into account the amplitude-dependency of the isolators and viscous dampers. It is finally pointed out that several factors, e.g., amplitude dependency of the isolator and damper system and special characteristics of the series-type viscous damper system, may be related complicatedly with the temporal variation in modal properties of the above-mentioned system.

This paper deals with the problem of tunneling effects on existing buildings. The direct solution, using the condensation method, is presented. This method allows the structural and geotechnical engineers to treat the problem separately and then assemble a relatively small matrix that can be solved directly, even within a spreadsheet. There are certain concerns that the resultant matrix may be ill-conditioned when the structure is very stiff. This paper suggests an alternative method that essentially relaxes the system from an infinitely rigid structure solution. As such, it does not encounter the problems associated with stiff systems. The two methods are evaluated for an example problem of tunneling below a framed structure. It is found that while the direct method may fail to predict reasonable values when the structure is extremely rigid, the alternative method is stable. The relaxation method can therefore be used in cases where there are concerns about the reliability of a direct solution.

Randomness plays a major role in the interpretation of many interesting traffic flow phenomena, such as hysteresis, capacity drop and spontaneous breakdown. The analysis of the uncertainty and reliability of traffic systems is directly associated with their random characteristics. Therefore, it is beneficial to understand the distributional properties of traffic variables. This paper focuses on the dependence relation between traffic flow density and traffic speed, which constitute the fundamental diagram (FD). The traditional model of the FD is obtained essentially through curve fitting. We use the copula function as the basic toolkit and provide a novel approach for identifying the distributional patterns associated with the FD. In particular, we construct a rule-of-thumb nonparametric copula function, which in general avoids the mis-specification risk of parametric approaches and is more efficient in practice. By applying our construction to loop detector data on a freeway, we identify the dependence patterns existing in traffic data. We find that similar modes exist among traffic states of low, moderate or high traffic densities. Our findings also suggest that highway traffic speed and traffic flow density as a bivariate distribution is skewed and highly heterogeneous.

In this paper, an experimental study of an air inflated membrane was carried out based on the China National Stadium (the Bird’s Nest). After the 2008 Olympic Games, it was apparent that the future use of the Bird’s Nest would be enhanced if rainfall could be prevented from entering the stadium. The installation of an air inflated membrane across the opening of the steel structure was proposed as a solution to this problem. To verify the scheme, a theoretical analysis and experimental study of an air inflated membrane was carried out. Experimental and computational models were developed, form-finding was carried out using both experimental and theoretical methods, and the results from the two approaches, including the deflection of the air inflated membrane and deformation of the support structure, were analyzed and compared. The force-transfer path and deformation of the air inflated membrane under loads was studied. Conclusions and suggestions are presented.

The transverse free vibration of nanobeams subjected to an initial axial tension based on nonlocal stress theory is presented. It considers the effects of nonlocal stress field on the natural frequencies and vibration modes. The effects of a small scale parameter at molecular level unavailable in classical macro-beams are investigated for three different types of boundary conditions: simple supports, clamped supports and elastically-constrained supports. Analytical solutions for transverse deformation and vibration modes are derived. Through numerical examples, effects of the dimensionless nanoscale parameter and pre-tension on natural frequencies are presented and discussed.

Given the definition of the reference Knudsen number for micro gas journal bearings, the range in the number is related to the viscosity of air at different temperatures. A modified Reynolds equation for micro gas journal bearings based on Burgdorfer’s first-order slip boundary condition is proposed that takes into account the gas rarefaction effect. The finite difference method (FDM) is adopted to solve the modified Reynolds equation to obtain the pressure profiles, load capacities and attitude angles for micro gas journal bearings at different reference Knudsen numbers, bearing numbers and journal eccentricity ratios. Numerical analysis shows that pressure profiles and non-dimensional load capacities decrease markedly as gas rarefaction increases. Attitude angles change conversely, and when the eccentricity ratio is less than 0.6, the attitude angles rise slightly and the influence of the reference Knudsen number is not marked. In addition, the effect of gas rarefaction on the non-dimensional load capacity and attitude angle decreases with smaller bearing numbers.

The flow in a finite diverging channel opening into a large space and resembling the experimental prototype of Putkaradze and Vorobieff (2006) was numerically investigated. The effects of the Reynolds number, initial condition, intersection angle, length of the wedge edges, and the outer boundary condition were examined. The numerical results showed that the flow in the wedge undergoes a change from symmetrical flow to unsymmetrical flow with a weak backflow, then a vortical (circulation) flow and finally an unsteady jet flow as the Reynolds number is increased for an intersection angle of 32( and a wedge edge of length 30 times the width of the inlet slit. For the unsteady flow, the jet attached to one side of the wedge constantly loses stability and rolls up into a mushroom-shaped vortex-pair near the outlet of the wedge. As the intersection angle is increased to 50(, a stable jet flow is observed as a new regime between the vortex and unsteady regimes. Both the intersection angle and the wedge length have negative effects on the stability of the flow, although the effect of the wedge length on the critical Reynolds number for the symmetry-breaking instability is not pronounced. The outer boundary condition was found not to affect the flow patterns inside the wedge significantly. At a certain Re regime above the onset of symmetry-breaking instability, the flows evolve into steady state very slowly except for the initial stage in the case of decreasing flow flux. Two different solutions can be observed within the normal observation time for the experiment, providing a possible explanation for the hysteresis phenomenon in the experiment.

In this paper, an application of a nonlinear predictive controller based on a self recurrent wavelet network (SRWN) model for a direct internal reforming solid oxide fuel cell (DIR-SOFC) is presented. As operating temperature and fuel utilization are two important parameters, the SOFC is identified using an SRWN with inlet fuel flow rate, inlet air flow rate and current as inputs, and temperature and fuel utilization as outputs. To improve the operating performance of the DIR-SOFC and guarantee proper operating conditions, the nonlinear predictive control is implemented using the off-line trained and on-line modified SRWN model, to manipulate the inlet flow rates to keep the temperature and the fuel utilization at desired levels. Simulation results show satisfactory predictive accuracy of the SRWN model, and demonstrate the excellence of the SRWN-based predictive controller for the DIR-SOFC.