Journal of Engineering Mechanics

The governing equations for the stability analysis of stochastic frame structures with small variations of the material and geometry parameters are established for the means and deviations of responses by including first-order terms. Taking advantage of the similarity between these equations and the governing equations for static analysis, a new Green’s function method based on the fundamental solutions for static problems is proposed for the stability analysis of stochastic structures in conjunction with multidomain techniques. The numerical examples presented show that there is good agreement between the results of the proposed method and those from Monte Carlo simulation for small variation situations, and that the new approach is more efficient than the perturbation stochastic FEM. Based on the numerical results, the effects of the covariance type, correlation scale parameter, coefficient of variation, and discretization of random fields, as well as the location of fictitious loads, are investigated.

The current study deals with the oblique wave trapping by bottom-standing and surface-piercing porous structures of finite width placed at a finite distance from a vertical rigid wall. Using the Sollitt and Cross model for wave motion within the porous structure, the problems are analyzed based on the small-amplitude water wave theory in water of finite depth. The solutions of the associated boundary value problems are obtained analytically using the eigenfunction expansion method and numerically using a multidomain boundary-element method. In the boundary-element method, the boundary value problems are converted into integral equations over the physical boundaries. The physical boundaries are discretized into a finite number of elements to obtain a system of linear algebraic equations. Various aspects of structural configurations, in trapping surface gravity waves, are analyzed from the computed results on the reflection coefficients and the hydrodynamic forces. Suitable arrangements of the rigid wall and partial porous structure of specific configurations can provide long-term and cost-effective solutions for protecting various marine facilities from wave attack.

Performance and reliability of structures will deteriorate with time as a result of the effects of various loads and the environment. This paper aims to develop a time-dependent reliability model of deteriorating structures that considers both aging effects and random shocks. First, a deteriorating model is proposed in which the aging effect is modeled as a gamma process while random shock is described by a Poisson process. The time-dependent reliability of the structural components is then evaluated based on the model. To incorporate the effects of model uncertainties, Bayesian inference methods are further integrated with the reliability model to update the uncertain parameters in the model using sampling data. Numerical examples demonstrate that the proposed model provides a reasonable method for evaluating the reliability of deteriorating structures containing model uncertainties.

Automotive and aerospace manufacturers are looking for ways to reduce the gross weight of vehicles to economize on fuel consumption as well as improve performance. Magnesium alloys, being the lightest among the metals, are highly attractive as potential structural materials. However, their use is quite limited, especially in structural applications. As of this writing, knowledge of the dynamic behavior of magnesium alloys is not sufficient to depict their true response under dynamic loadings, and has been a hindrance to their widespread use. In this research, an experimental study, followed by constitutive and microstructural analyses, was carried out to investigate the behavior of AZ31B magnesium alloy. The alloy has been tested at strain rates in the range between ${10}^{-4}\hspace{0.17em}{\text{s}}^{-1}$ and $1.5\times {10}^3\hspace{0.17em}{\text{s}}^{-1}$ under tension.

Nonlinear bending analysis of shear deformable anisotropic laminated composite beams with various kinds of distributed loads resting on a two-parameter elastic foundation is investigated. The material of each layer of the beam is assumed to be linearly elastic and fiber reinforced. A new nonlinear beam model involving the exact expression of the bending curvature is introduced. The governing equations are based on higher-order shear deformation beam theory with a von Kármán type of kinematic nonlinearity that includes bending-stretching, bending-twisting, and stretching-twisting couplings. Two kinds of end conditions, namely movable and immovable, are considered. The analysis uses a two-step perturbation technique combined with the Galerkin method to determine the relationship between distributed loads and deflections of a composite beam with or without initial loads. The numerical illustrations concern the static bending behavior of laminated beams with different geometric and material parameters, distributed loads, and end conditions, and its effect on the elastic foundation. The results based on the curvature model reveal that the geometric and physical properties, end conditions, axial force, distributed loads, and foundation stiffness have a significant influence on the large-amplitude bending behavior of anisotropic laminated composite beams.

A closed-form solution and finite-element formulation are developed for the dynamic analysis of thin-walled members with asymmetric open sections subjected to harmonic forces. The dynamic equations of motion and associated boundary conditions are derived from Hamilton’s principle. The formulation is based on a generalized Vlasov-Timoshenko beam theory and accounts for the effects of shear deformation caused by bending and warping and translational and rotary inertia effects. It also captures the effects of flexural-torsional coupling caused by cross-sectional asymmetry. From this a general closed-form solution is obtained. A family of shape functions is then developed based on the exact solution of the coupled field equations and is used to formulate a beam finite element. The new element has two nodes with six degrees of freedom per node and successfully captures the coupled bending-torsional static and steady-state responses of asymmetric thin-walled members under harmonic forces. Results based on the closed-form solution and finite-element formulation are assessed and validated against other well-established finite-element solutions.

Through particle image velocimetry, conical vortices were observed near the leading edge of a flat roof and two saddle roofs whose high points were windward. The influences of wind direction and roof curvature on the appearance of conical vortices are discussed in this paper. The results indicated that when the wind direction changed from along the diagonal to deviating from the diagonal of the roofs, the conical vortex close to the approaching flow changed, becoming more oblong. At the same wind direction, a greater roof curvature led to a larger angle between the vortex axis and the leading edge of the saddle roof. Based on velocities measured in conical vortices by flow visualization, a simplified two-dimensional vortex model was established by adding a transitional region between the vortex core and the potential flow region of the Rankine vortex. Through this flow model, the intensities of conical vortices on the two saddle roofs under different wind directions were deduced. The quasi-steady theory was corrected by including the effect of vortices. With this two-dimensional vortex model and the corrected quasi-steady theory, the mean and peak suctions beneath cores of conical vortices on the two saddle roofs were predicted, and these predictions were verified by measured pressures.

Traditional passive base-isolation systems provide an effective means to mitigate the responses of seismically excited structures. A challenge for these systems can be found in accommodating the large base displacements during severe earthquakes. Recently, active base-isolation systems, combining actively controlled actuators with passive isolation bearings, have been shown experimentally to produce reduced base displacements, while maintaining similar responses of the superstructure obtained by the passive base-isolation systems. The active control devices used in hybrid isolation systems are typically driven by an external power source, which may not be available during severe seismic events. Another class of isolation systems is smart base isolation, in which semiactive control devices are used in place of their active counterparts. This control strategy has been proven effective against a wide range of seismic excitation; however, there has been limited effort to experimentally validate smart base-isolation systems. In this study, the focus is on experimentally investigating and verifying a smart base-isolation system using real-time hybrid simulation (RTHS), which provides a cost-effective means to conduct such experiments because only the portion of the structure that is poorly understood needs to be represented experimentally, while the reminder of the structure can be modeled using a computer. In this paper, a prototype magnetorheological damper is physically tested, while the isolated building concurrently is simulated numerically. A model-based compensation strategy is used to carry out high-precision RTHS. The performance of the semiactive control strategies is evaluated using RTHS, and the efficacy of the smart base-isolation system is demonstrated. This smart base-isolation system is found to reduce base displacements and floor accelerations in a manner comparable with the active isolation system without the need for large external power sources.

Lowering production temperature in warm mix asphalt technology may lead to inadequate drying of aggregates, which results in moisture stripping of pavement. Because of the difficulty in direct observation of drying and heating aggregates inside the dryer, numerical analysis offers an alternative way to study heat transfer and aggregate temperature revolution. In this paper, coupled computational fluid dynamics (CFDs) and the discrete-element method (DEM) are used to simulate aggregate movement and heat transfer in a simple drum. The effects of aggregate size, drum rotation speed, flights, and fluid temperature on aggregate temperature evolution and heating efficiency are studied. The results show that a coupled CFD-DEM technique is an appropriate approach to study aggregate movement and temperature evolutions in the drum directly. Small particles can be heated more easily than large particles. Optimum drum rotation speed and inner flights could improve heating efficiency. In addition, higher fluid temperature could reduce the heating time of particles to reach a target mixing temperature. Preliminary results may provide useful guidelines for operating and designing the mixing drum efficiently.

Accurate estimation of the damping in a structure has remained an important but challenging problem for the structural engineering community. The relative difficulty of damping estimation can be compounded when the excitation is not uniformly broadband or ambient in nature, such as when car traffic or large trains travel over a bridge. A bridge model that consisted of a series of simply supported (SS) stringers resting atop a larger girder was constructed using finite elements, and several simulations were conducted in which cars and trains crossed the bridge model. The presence of the cars and trains led to the appearance of driving forcing frequencies in the response. Driving frequencies are inherent to moving loads and proportional to the velocity of the moving loads and the length of the beam or bridge being crossed. The moving loads produced a pulse-like response in the SS stringers on the bridge model, and the resulting power spectral density (PSD) of the stringers showed that its power was concentrated at the first driving frequency and its even multiples. The vertical component of the moving load and the SS stringer responses were transferred to the girder, and owing to the continuity within the girder, each of its nodes experienced all of the car crossings. The repeated nature of the car crossings led to a PSD of the girder responses that contained peaks at the even multiples of the driving frequency. Over the course of a full simulation, the peaks produced by the different car velocities merged to form shelves of elevated power; these shelves were repeated at each of the even multiples of the driving frequency, causing sustained regions of distortion in the frequency response spectra of the girder. Attempts were made to identify the modal damping ratios from the bridge acceleration responses using the frequency domain decomposition (FDD) and blind source separation (BSS) methods, but the driving frequencies interfered with the estimates. The regions of distortion compromised the spectra for the frequency-based methods and altered the estimated modal responses recovered from the BSS method, creating problems with identification in the time domain. The driving frequencies generated by the car and train traffic on a bridge negatively impacted both the reliability and accuracy of the damping estimates found using various operational modal analysis (OMA) techniques.

An arbitrarily laminated, anisotropic cantilever cylindrical shell of finite length, under uniform internal pressure, is analyzed using kinematic relations under the framework of classical lamination theory. Extensive numerical results are presented for two model problems, pertaining to two-layer, asymmetrically laminated, anisotropic cantilever cylindrical shells, illustrating the influence of layer anisotropy and lamination sequence on the beam-column/tie-bar effects, which, in turn, severely affect the free-end displacements and other response quantities of interest. Furthermore, because the beam-column effect can cause severe wrinkling in a thin asymmetrically laminated cylindrical shell, the possibility of its elimination through composite tailoring (a combination of stacking sequence and fiber orientation angle in a constituent lamina) has also been explored. Finally, the effect of length-to-radius ratio is also numerically investigated.

A new computational tool, referred to as the polynomial correlated function expansion (PCFE), has been developed for predicting response statistics of nonlinear stochastic dynamic problems. This method facilitates a systematic mapping between the input and output by expressing the output as a ranked order of component functions, with higher-order component functions representing higher-order cooperative effects. The component functions are expressed in terms of extended bases, and the unknown coefficients associated with the basis are determined by using a homotopy algorithm. This algorithm considers the hierarchical orthogonality of the component functions as a constraint and determines the coefficients associated with the basis. Implementation of the proposed approach for nonlinear stochastic dynamic problems has been demonstrated with three numerical problems. Results obtained certify the accuracy of the proposed method. Furthermore, the proposed approach significantly reduces the number of calls to the partial differential equation solver, as observed in the numerical problems.

This paper discusses self-supporting sandwich panels, which are used as wall and roof cladding. They consist of two external thin and flat facings and a thick soft core. The panels are subjected to mechanical and temperature actions. The aim of this paper was to find the optimal solution for supports of a multispan sandwich structure. The following support models were considered: rigid support and linear-elastic support, with or without an imposed limit of elastic deflection. The problem was formulated as a two-criterion optimization (i.e., the maximization of the load multiplier and the maximization of the allowable length of the span). The criteria were in mutual exclusion (i.e., the results of the optimization comprise a set of nondominated optimal solutions). It shows that the optimal choice of supporting conditions remarkably improves the capacity of thermally loaded sandwich panels used in civil engineering.

Bayesian updating is a powerful method to learn and calibrate models with data and observations. Because of the difficulties involved in computing the high-dimensional integrals necessary for Bayesian updating, Markov chain Monte Carlo (MCMC) sampling methods have been developed and successfully applied for this task. The disadvantage of MCMC methods is the difficulty of ensuring the stationarity of the Markov chain. We present an alternative to MCMC that is particularly effective for updating mechanical and other computational models, termed Bayesian updating with structural reliability methods (BUS). With BUS, structural reliability methods are applied to compute the posterior distribution of uncertain model parameters and model outputs in general. An algorithm for the implementation of BUS is proposed, which can be interpreted as an enhancement of the classic rejection sampling algorithm for Bayesian updating. This algorithm is based on the subset simulation, and its efficiency is not dependent on the number of random variables in the model. The method is demonstrated by application to parameter identification in a dynamic system, Bayesian updating of the material parameters of a structural system, and Bayesian updating of a random field–based finite-element model of a geotechnical site.

An in-house–built rheological device, made of assemblies of custom-made nickel titanium-Naval Ordnance Laboratory (Nitinol) strands, wires, and steel wire ropes, is experimentally tested in different configurations corresponding to three distinct constitutive behaviors: a strong hardening pinched hysteresis, a quasi-linear–softening behavior, and an intermediate behavior in the range of interest. The nonlinear features of the hysteretic rheological device are the result of geometric hardening of the ropes, interwire friction, and dissipation caused by the phase transformations of the Nitinol wires. These different mechanisms determine a pinching at the origin of the hysteresis force-displacement loops. A phenomenological representation of the experimentally acquired constitutive responses is obtained by an extension of the Bouc-Wen model incorporating a pinching function that depends on two parameters. The responses of the Nitinol wires and strands under uniaxial tension are instead well identified using the Ivshin-Pence model. Parameter identification of the phenomenological models, based on the experimental measurements, is carried out using an optimization method belonging to the family of differential evolutionary algorithms. A very good agreement is found between the experiments and the identified models.

Blowing and drifting of snow is a major concern for transportation efficiency and road safety in regions where their development is common. One common way to mitigate snow drifts on roadways is to install plastic snow fences. Of critical importance for road safety is protection against snow drifting in regions with narrow rights of way, where standard fences cannot be deployed at the recommended distance from the road. The current study proposes a joint experimental and numerical approach to monitor snow deposits around snow fences, and to quantitatively estimate snow deposits in the field, assess efficiency, and improve the design of snow fences. Snow deposit profiles were mapped using global positioning system–based real-time kinematic surveys conducted at the monitored field site during and after snow storms. The monitored site allowed testing various snow fence designs under close to identical conditions. A main goal of the current study was to assess the performance of lightweight plastic snow fences with a lower porosity than the typical 50% porosity used in standard designs of such fences. The field data, collected during the first winter, were used to identify the best design for snow fences with a porosity of 50%. The flow fields obtained from numerical simulations showed that the fence design that worked the best during the first winter induced the formation of an elongated area of small velocity magnitude close to the ground. This information was used to identify other candidates for optimum design of fences with a lower porosity. Two of the designs with a fence porosity of 30% that were found to perform well based on the results of the numerical simulations were tested in the field during the second winter along with the best performing design for fences with a porosity of 50%. The field data showed that the length of the snow deposit away from the fence was reduced by approximately 30% for the two proposed lower-porosity (30%) fence designs compared with the best design identified for fences with a porosity of 50%. Moreover, one of the lower-porosity designs tested in the field showed no significant snow deposition within the bottom gap region beneath the fence. It is expected that this design will continue to work well for even more severe snow events or for successive snow events occurring during the same winter. The approach advocated in the current study allowed making recommendations for optimizing the design of lower-porosity plastic snow fences. This approach can be extended to improve the design of other types of snow fences.