Sustainability of Bridges:Risk Mitigation for Natural Hazards

Bridges serve as essential parts of transportation infrastructure,facilitating the movement of people and goods across rivers,valleys,and other obstacles.However,they are also susceptible to a wide range of natural hazards,including floods,earthquakes,and landslides,which can damage or even collapse these structures,leading to severe economic and human losses.A risk index has been developed to address this issue,which quantifies the likelihood and severity of natural hazards occurring in a specific location.The application of risk indices for natural hazards in bridge management involves a data collection process and mathematical modelling.The data collection process gathers information on bridges’location,condition,and vulnerability,while mathematical modelling uses the data to assess the risk of natural hazards.Overall,risk indices provide a quantitative measure of the vulnerability of bridges to natural hazards and help to prioritize maintenance and repair activities.Mitigation measures are then evaluated and implemented based on the risk assessment results.By using this tool,the UBMS research group has developed an algorithm for risk assessment which will be essential in the decision-making process,specifically focused on enhancing Fund Optimization,Deterioration Modelling,and Risk Analysis.These developments effectively fulfill the primary objectives associated with addressing and mitigating hazards.This development also helps bridge managers understand the potential threats posed by natural hazards and allocate resources more efficiently to ensure the safety and longevity of critical transportation infrastructure.

Predicting the excavation damaged zone within brittle surrounding rock masses of deep underground caverns using a comprehensive approach integrating in situ measurements and numerical analysis

Excavation Damaged Zone(EDZ)scope is important for optimizing excavation and support schemes in deep underground caverns.However,accurately predicting the full EDZ scope within the surrounding rock masses of deep underground caverns during excavation remains a pressing problem.This study presents a comprehensive EDZ scope prediction approach(CESPA)for the brittle surrounding rock masses of deep underground caverns by coupling numerical simulation with quantitative analysis of borehole wall images and ultrasonic test results.First,the changes in both P-velocity(V_(p))and joint distribution of the surrounding rock masses before and after excavation damage are captured using ultrasonic tests and borehole digital cameras.Second,the quality Q-parameters of the surrounding rock mass before and after excavation damage are preliminarily rated with the rock mass descriptions provided by borehole wall images,and the rock mass V_(p)-parameter values are determined according to the V_(p)-borehole depth curves.Third,the Q-parameter ratings are further finely adjusted by updating the related Q-values to be similar with the Q-values estimated by V_(p)-parameter values.Fourth,the initial and residual mechanical parameters for the rock mass deterioration model(RDM)are estimated by the adjusted Q-parameter ratings based on the modified Q-based relations,and the elastic modulus deterioration index(EDI)threshold to describe the EDZ boundary is determined with the V_(p)-parameter values.Finally,EDZ scope is predicted using the elastoplastic numerical simulation with RDM and EDI based on the mechanical parameter estimates and EDI threshold.Analyses of applications in Sub-lab D1 in Jinping II project show that CESPA can provide a reliable and operable solution for predicting full EDZ scopes within the brittle surrounding rock masses of deep underground caverns.

An Approach for Quantifying the Influence of Seepage Dissolution on Seismic Performance of Concrete Dams

Many concrete dams seriously suffer from long-term seepage dissolution,and the induced mechanical property deterioration of concrete may significantly affect the structural performance,especially the seismic safety.An approach is presented in this paper to quantify the influence of seepage dissolution on seismic performance of concrete dams.To connect laboratory test with numerical simulation,dissolution tests are conducted for concrete specimens and using the cumulative relative leached calcium as an aging index,a deterioration model is established to predict the mechanical property of leached concrete in the first step.A coupled seepage-calcium dissolutionmigrationmodel containing two calculation modes is proposed to simulate the spatially non-uniformdeterioration of concrete dams.Based on the simulated state of a roller compacted concrete dam subjected to 100 years of seepage dissolution,seismic responses of the damare subsequently analyzed.During which the nonlinear cracking of concrete,the radiation damping of the far-field foundation is considered.Research results show that seepage dissolution will seriously weaken the seismic safety of concrete dams because of the dissolution-induced decrease of effective thickness of the dam body.The upstream surface,dam toe and gallery wall suffer from a large degree of dissolution,whereas it is minimal and basically the same inside the dam body,at a degree of 0.19%within 100 years.The horizontal displacements of dam crest under the design static load and fortification against earthquake increase by 6.9%and 21.9%,respectively,and the dissolution-induced seismic cracking leads to the failure of dam anti-seepage system.This study can provide engineers with a reference basis for reinforcement decision of old concrete dams.

A combined risk-based and condition monitoring approach:developing a dynamic model for the case of marine engine lubrication

This paper focuses on the creation of a dynamic probabilistic model which simulates deterioration trends of a marine engine lubricationsystem. The approach is based on risk and the implementation is achieved through a dynamic Bayesian network (dBN).Risk can be useful for decision making, while dBNs are a powerful tool for risk modelling and prediction models. The model takesinto account deterioration of engine components, oil degradation and the off-line condition monitoring technique of oil analysis, inthe context of predictive maintenance. The paper aims to efficiently predict probability evolution for main engine lubrication failureand to decide upon the most beneficial schemes from a variety of lubrication oil analysis interval schemes by introducing monetarycosts and producing the risk model. Real data and respective analysis, along with expert elicitation, are utilized for achieving modelquantification, while themodel is materialized through a code in the Matlab environment. Results from the probabilistic model showa realistic simulation for the system and indicate the obvious, that with more frequent oil analyses and respective maintenance orrepairs, the probability of failure drops significantly. However, the results from the risk model highlight that the costs can redefinescheme suggestions, as they can correspond to low probabilities of failure but also to higher costs. A two-month interval scheme issuggested, in contrast to the most preferred practice among shipping companies of a three-month interval. The developed model isin general identified as a failure prediction tool focusing on marine engine lubrication failure.