Tropical cyclones (TCs) evolve over time and space and can cause substantial damage to building portfolios. Therefore, timely and accurate TC damage assessment is essential for effective risk management. One practical approach is to establish a relationship between hazard intensity (e.g., wind speeds) and regional damage. However, when the study area is large, spatial heterogeneity, such as clustered building distributions, terrain variability, and spatial variations in wind speeds, can hinder accurate modelling of the hazard-damage relationship. To address this challenge, the present study employs a spatial clustering algorithm to divide the entire area into multiple sub-regions with relatively homogeneous characteristics. For each sub-region, a TC loss model is developed as a function of wind speed at the sub-regional centroid and the corresponding building portfolio loss ratio. In practice, losses in all sub-regions are first assessed individually and then aggregated to estimate the total regional loss. This divide-and-aggregate approach significantly improves the accuracy and applicability of TC loss modelling and can be readily applied to various contexts, such as long-term risk management in large-scale communities.

This paper proposes a method to value the target reliability index of the main girder of a concrete cable-stayed bridge considering the resistance decay and cost optimization in the whole life cycle of the girder. The initial cost during the construction period, the maintenance cost during the service period, and the failure cost of the main girder structure are comprehensively considered, and the calculation model and objective function of the whole life-cycle cost are established. For maintenance costing, a hybrid strategy model (corrective + preventive) is adopted, and the time-variant reliability index is approximated from the recession law of the initial flexural capacity with resistance decay. On this basis, a bridge case with a 100-year design life is analyzed in detail to compute cost-optimized initial resistances and the corresponding initial reliability indices. In addition, to reflect that a target reliability index is defined for a class of structures, we further generate a set of feasible designs (ribbed-deck cable-stayed girders) and construct the class-level E[CT]-beta scatter envelope. The minimum of the envelope yields a rational class target reliability, beta T=5.865, which exceeds the code lower bound of 4.7. A brief parametric study indicates that increasing the failure consequence cost CF shifts the envelope leftward and slightly raises beta T, while a higher discount rate gamma moves the envelope downward and tends to reduce beta T. The proposed procedure provides a balanced, economics-and-safety-oriented basis for selecting beta T of ribbed-deck cable-stayed bridge girders and can support life-cycle design and operation and maintenance decision-making.

This paper proposes a Bayesian network (BN) framework for the probabilistic assessment of regional building losses induced by hurricanes. To explicitly capture the spatial heterogeneity of damage, the study area is partitioned into geographic subdivisions, with the model formulated as a BN-based multi-output regression framework. This framework utilises key hurricane parameters, including translation speed, heading angle, location, and central pressure, as inputs to generate probabilistic loss statistics for each subdivision as outputs. This study introduces new schemes for the discretisation of the input and output variables of the BN. For hurricane variables, a supervised discretisation method is developed that integrates weighted principal component analysis with decision tree algorithms, while also considering the relative importance of each subdivision (e.g., building density) to improve accuracy in high-priority areas. For loss variables, a clustering-based discretisation method is applied to capture the characteristics of regional building losses. The proposed framework enables efficient assessment of the spatial distribution of hurricane-induced building losses in a community, accounting for uncertainties and spatial correlation in hurricane hazard predictions and structural performance. Its effectiveness is demonstrated through a numerical example.

The pressure-resistant shell plays a critical role in determining the submerged depth of underwater vehicles. Traditional pressure-resistant shell designs are confronted with challenges such as high sensitivity to defects, poor space utilization, and limited load-carrying capacity. The proposed ring-stiffened sandwich cylindrical shell redistributes the load between inner and outer shell plates, significantly reducing the plate thickness and enhancing stealth potential. New strength and stability criteria are provided, and a parametric geometric model is developed. Additionally, a rapid optimization design method based on the MIGA surrogate model and the radial basis function neural network (RBFNN) surrogate model is utilized to improve effective design efficiency. Numerical analyses of underwater vibration and acoustic radiation demonstrate the superior acoustic stealth performance of the proposed structure, thereby contributing to addressing key challenges in the development of deep-diving underwater vehicles.

This paper proposes a framework for mixed uncertainty quantification in the remaining service life assessment of existing deteriorated reinforced concrete (RC) bridges under temperature climate changes. The probability bound analysis (PBA) is deployed for quantifying mixed uncertainty. The epistemic uncertainty in climate change is modelled using a distribution-free p-box in the PBA framework. An extension of Chebyshev’s inequality is proposed to construct a parametric distribution-free probability-box (p-box) under a specific confidence interval. This ensures consistency with the distributional p-box, constructed based on the uncertainty in distribution parameters. The proposed method can account for parametric uncertainties for variables with known or unknown distribution types with a specified confidence level and provides narrower bounds than other approaches. The types and sources of uncertainty associated with assessing an existing bridge are thoroughly investigated as an application example. An insight into how epistemic uncertainty governs corrosion initiation and propagation in service life prediction is provided. Results show that the epistemic uncertainty in the diffusion coefficient is most critical in the probabilities of corrosion initiation and damage, followed by the epistemic uncertainty in temperature projections.

To enhance the safety performance and lightweight design level of the B-pillar assembly, this article proposes the collaborative design concept and processing method of variable-thickness high-strength steel-carbon fiber composite B-pillar assembly design, optimization and process molding. Established the finite element analysis models of the B-pillar and the body-in-white, and conducted verification. Determined the structural scheme of the B-pillar reinforcement plate, through the experimental tests of the basic performance parameters of the T700/WP-R2300 composite, and the lay-up design and multi-level optimization of the Carbon Fiber Reinforced Plastic (CFRP) B-pillar reinforcement plate. Designed the composition of low-cost micro-alloyed high-strength steel and the forming process parameters, and conducted mechanical property verification. Combined with the previously proposed improved PSO-BFO (Particle Swarm optimization algorithm-bacterial foraging algorithm) hybrid optimization algorithm and its multi-objective optimization method, the multi-objective optimization of the outer plate of the Variable thickness Rolled Blanks (VRB) high-strength steel B-pillar was carried out under multiple working conditions to obtain the Pareto solution set. The simulation comparison of the B-pillar assembly performance before and after optimization shows that the weight of the B-pillar assembly is reduced by 13.52 %, while the tensile stiffness, side-bending stiffness, rear-bending stiffness and three-point bending stiffness are increased by 18.93 %, 6.40 %, 9.66 % and 49.66 % respectively. Additionally, the first-order bending-torsion mode is increased by 46.82 % and 11.90 % respectively. These results validate the effectiveness of the proposed design scheme and the multi-level multi-objective optimization methodology. The B-pillar reinforcement plate was manufactured by using the improved vacuum-assisted resin transfer molding (VARTM) process, while the B-pillar VRB high-strength steel outer plate was manufactured through a combined hot stamping and carbon partitioning process. The outer plate and reinforcement plate were connected by adhesive bonding technology, followed by comparative modal testing and experimental verification. The discrepancy between simulation and experimental results was maintained within 6 %. The displacements under the bending and torsional conditions of the body-in-white were reduced by 24.80 % and 1.97 %, respectively, significantly enhancing the stiffness of both the body-in-white and the B-pillar assembly. These results confirm the validity and effectiveness of the proposed methodology and technical solution.

In existing probabilistic durability design for marine reinforced concrete (RC) structures, the material-level deterioration behavior is modelled, and corrosion onset at a point on the rebar is taken as the limit state. However, the owners may more concern the risk of the structural member's surface damage or the potential maintenance demands. To bridge the gap, a member-level durability design method is developed in this paper. It treats the target reliability index as a function of member-level target performance, and incorporates the existing design method into the proposed framework. Its differences and relations with the existing material-level method are addressed. By improving the effective tools from existing studies, the general procedures of performing a member-level durability design are proposed. Taking the HZM project as the examples, member-level durability designs are performed for its beams, columns and immerged tube tunnels under various exposure conditions with various design targets being considered. Accuracy of the design outputs are checked by assessing the corresponding member-level performance and comparing it to the design targets. In addition, the proposed method is also validated with the in-situ data from an in-service high-pile RC wharf.

The paper describes the main outcomes of a recently completed project on built-up cold-formed steel structures, including experimental, analytical and numerical advances. The project covers columns failing by distortional buckling or interactive global-local or global-distortional buckling, and laterally restrained and unrestrained beams. The cross-sections studied feature two, three or four component sections, arranged to produce singly or doubly cross-sections, including open sections and sections with closed loops.The paper first summarises the main experimental observations and results, then presents analytical solutions for determining the flexural, torsional and warping rigidities of built-up sections, followed by recent finite strip analyses to determine the local and distortional buckling loads of built-up sections accounting for discrete fasteners, including the Compound Strip Method and the modal Finite Strip Method, the latter for determining the pure modes of built-up sections. The development of fully nonlinear shell finite element models is outlined next, as specific for built-up sections. Lastly, the paper summarises proposed provisions for the design of built-up sections with two or more component cross-sections, covering columns and beams failing by local, distortional and/or global modes as well as combinations of these modes.

The crushing tool is the pivotal component of the medical waste treatment equipment and is prone to wear and fracture. To improve its performance, the medical waste crushing process was numerically studied with the coupling method of DEM-FEM under various cutting angle designs of the crushing tool. The effects of different cutting angles on the elastic deformation and impact wear of the horizontal blade in the crushing tool were analyzed. To achieve the best deformation and wear, a multi-objective optimization method that combined AHP and EWM was proposed to determine the optimal cutting angle of the horizontal blade in the crushing tool based on the DEM-FEM results. A specific cutting angle of B80° was finally revealed to be the optimal design.

Abstract The safety and serviceability of in-service structures and infrastructure systems are often threatened by natural hazards. Asset owners/decision makers are thus concerned about the resilience of an object of interest (structure or infrastructure), that is, its ability to be in readiness for, to absorb, recover from, and adapt to disruptive events. This is particularly the case when considering the potential impacts of climate change, which may lead to nonstationary natural hazards in the future (e.g., increasing wind hazard in a changing climate). Moreover, in many occasions, the presence of concurrent multiple hazards may result in more severe performance reduction to structures/infrastructures, compared with the occurrence of single hazards. This paper proposes an innovative method for the time-dependent resilience assessment of structures and infrastructure systems exposed to the impacts of concurrent multiple hazards in a changing climate. The interaction between different types of hazards is reflected through the mutual dependency between the performance functions associated with these hazards. New insights into the time-dependent resilience problem are also provided through a new concept of the performance concern index (PCI). It is shown that the mean nonresilience (i.e., 1 minus the mean value of resilience), if small enough, can be approximated by the mean value of the average PCI over the time domain of interest. Two examples are presented to demonstrate the applicability of the proposed method, and to investigate the sensitivity of resilience to key factors such as the interaction between multiple hazards and the climate change scenario.

Data-driven material models have shown advantages in recent studies since they can directly use the existing data and improve the model performances further when additional data is available. However, few data-driven material models in the previous studies considered the uncertainty and stochastic correlations of the material properties. In this work, the hybrid Proper Orthogonal Decomposition-Heteroscedastic Sparse Gaussian Process Regression (POD-HSGPR) framework is proposed for predicting stochastic material behaviors and their correlation. The two material behaviors case studies on the metal strength and the rock joint behavior have demonstrated that the proposed POD-HSGPR-based stochastic material model can effectively capture the material properties, material uncertainty, and stochastic correlation between the material behaviors directly from the experimental dataset. The proposed POD-HSGPR model is then applied to a rock slope structure problem to investigate the influence of the correlation of material properties on structural behavior. The results indicate that the proposed POD-HSGPR model could effectively quantify the correlation effect in a non-parametric format and avoid the overestimation of structural reliability.

This paper develops a new generalized component method (GCM) model for bolted bearing type connections to capture the full‐range response and all relevant limit states, including the bolt shear, bearing, shear‐out, net section fracture, and block shear limit states. The proposed model divides a bolted bearing type joint into components that significantly contribute to its deformation and/or strength limit states. For each component, the force‐deformation curve is derived including the post‐ultimate behavior. The new component model is developed in the context of the generalized component method to predict the full‐range joint moment‐rotation response. The proposed GCM can consider the interaction of adjacent bolts in modelling multi‐bolt connections. The new GCM is validated through experimental tests and fully nonlinear finite element analyses, and compared with predictions by the Eurocode 3 component method.

This paper investigates the lateral‐torsional buckling of built‐up cold‐formed steel beams featuring two or three component C‐ or sigma‐sections arranged to have a closed loop. Several thicknesses of each cross‐section with nominal yield stress values of 450 MPa and 550 MPa were tested to obtain lateral buckling strength data for a range of cross‐section slenderness values. Complementary reference tests were conducted on the same built‐up sections braced laterally to obtain the in‐plane section capacities, precluding the effect of lateral‐torsional buckling. Coupon tests were also conducted to determine the mechanical properties of the steel material. The test rig featured a dual‐actuator set‐up, with one actuator (applying vertical load) mounted on a trolley that was moved horizontally by the second actuator in response to the signal from a transducer measuring the lateral buckling displacement at the mid‐length of the beam, thus ensuring vertical loading throughout the experiments. The rig also featured specialized end bearings allowing free flexural rotations and warping, while restraining lateral displacements and twist rotations. The paper describes the test rig and the results of the in‐plane and lateral‐torsional buckling experiments. Particular attention is paid to the use of closed parts to enhance the torsional rigidity of the built‐up sections and thereby their lateral‐torsional buckling capacity.

This paper proposes a new method for time-variant reliability analysis of existing ageing structures under epistemic uncertainty from limited recurrent field measurement data. A growth model and a noise factor are introduced to account for the ageing changes of distribution parameters that take place while the reliability interval is sequentially updated using inspection data acquired over the service period. The method is applied to quantify the reliability of deteriorating concrete bridges under routine inspections of reinforcement steel corrosion. The interval estimation of corrosion and reliability shows narrower uncertainty bounds than a traditional frequentist approach, particularly when relatively sparse inspection datasets are available. In the case study presented, the relative variation of reliability bounds could be reduced by at least half when compared to a frequentist estimation.

Risk assessment of spatially distributed infrastructure systems under natural hazards shall treat the performance of individual components as stochastically correlated due to the common engineering practice in the community including similarities in building design code, regulatory practices, construction materials, construction technologies, and the practices of local contractors. Modelling the spatially correlated damages of an infrastructure system with many components can be computationally expensive. This study addresses the scalability issue of risk analysis of large-scale systems by developing an interpolation technique. The basic idea is to sample a portion of components in the systems and evaluate their correlated damages accurately, while the damages of remaining components are interpolated from the sampled components. The new method can handle not only linear systems, but also systems with complex connectivity such as utility networks. Two examples are presented to demonstrate the proposed method, including cyclone loss assessment of the building portfolios in a virtual community, and connectivity analysis of an electric power system under a scenario cyclone event.

Stainless steel, known for its exceptional corrosion resistance and durability, has emerged as a promising material in the field of structural engineering. This research article presents a comparative study that evaluates the cost efficiency and longevity of stainless steel in structural applications, contrasting it with conventional construction materials. Through comprehensive analysis and case studies, we aim to provide valuable insights into the feasibility and advantages of utilizing stainless steel in structural engineering projects.

For marine reinforced concrete (RC) structures under chloride-attack, the risks of member surface damage can be evaluated using random field analysis method, considering the spatial variations of durability parameters. However, the random field analysis method requires high computational cost and advanced skills, and is not feasible for engineering practice. Recognizing this difficulty, a simplified method is proposed in this paper based on the statistical characteristics of time to corrosion initiation and surface damage. The new method establishes the mappings between the probabilities of member surface damage and the probability (or reliability index) of corrosion initiation at the same age. Thus, engineers and decision-makers can estimate the risk of surface damage through reliability index of corrosion initiation, with the latter can be obtained relatively easily. Probabilistic analysis for the durability performance of a RC slab serviced in marine environment is performed to demonstrate the method. The accuracy of the proposed method is examined through the comparison with the random field simulation method and experimental results in literature.