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Natural hazards such as hurricanes may cause extensive economic losses and social disruption for civil structures and infrastructures in coastal areas, implying the importance of understanding the construction performance subjected to hurricanes and assessing the hurricane damages properly. The intensity and frequency of hurricanes have been reported to change with time due to the potential impact of climate change. In this paper, a probability-based model of hurricane damage assessment for coastal constructions is proposed taking into account the non-stationarity in hurricane intensity and frequency. The non-homogeneous Poisson process is employed to model the non-stationarity in hurricane occurrence while the non-stationarity in hurricane intensity is reflected by the time-variant statistical parameters (e.g., mean value and/or standard deviation), with which the mean value and variation of the cumulative hurricane damage are evaluated explicitly. The Miami-Dade County, Florida, USA, is chosen to illustrate the hurricane damage assessment method proposed in this paper. The role of non-stationarity in hurricane intensity and occurrence rate due to climate change in hurricane damage is investigated using some representative changing patterns of hurricane parameters.

Effective length method is still widely used in engineering practice to evaluate the stability of compression members in frame structures. However, the conventional effective length method can be inaccurate in many cases as it considers columns in isolation from the stories above and below. This article proposes an improved method for simplified frame stability analysis that accounts for the vertical interaction effects of columns. The idealized sub-assemblage model includes the columns of all stories and their restraining beams. The stability matrix for a single-story unit is first derived, and then the system stability matrix is obtained by considering the compatibility of the story units. The governing equation for the elastic buckling load of the sub-assemblage is derived. The method is applicable to both sway-permitted and sway-prevented frames. The applicability and accuracy of the proposed method are demonstrated using a series of examples with a wide variation of parameters including numbers of story, boundary conditions, stiffness of beam-to-column connections, column length and stiffness, and axial force level.

Bridge resistance and reliability may deteriorate with time due to aggressive environmental conditions and increasing road freight volumes, resulting in an increase of potential economic loss. This is thus a great concern to decision-makers managing the bridges’ continued future service. Reasonable models of bridge resistance and applied loads are the fundamentals of accurate estimation/prediction of a bridge’s serviceability. In this paper, a new model for resistance deterioration is proposed, which enables the non-increasing property and auto-correlation in the stochastic deterioration process to be incorporated. To facilitate the practical application of the model, methods to determine its parameters using obtained data on structural resistance are developed and illustrated through simple numerical examples. Time-dependent reliability analysis is conducted using the proposed resistance deterioration model based on Monte Carlo simulation, and the effect of auto-correlation in the deterioration process on structural time-dependent reliability is investigated.