Young Joo Lee

The flow capacity of a transportation network can be reduced significantly if its constituent bridges are damaged by natural or man-made hazards. For rapid risk-informed decision making on hazard mitigation and response, it is therefore essential to have a capability to predict the post-hazard flow capacity of the network efficiently and accurately. However, this is a challenging task due to the uncertainty in hazards and structural damage, and the complex nature of the network flow analysis. Mo

Bridges are one of the most important infrastructure systems that provide public and economic bases for humankind. It is also widely known that bridges are exposed to a variety of flood-related risk factors such as bridge scour, structural deterioration, and debris accumulation, which can cause structural damage and even failure of bridges through a variety of failure modes. However, flood fragility has not received as much attention as seismic fragility despite the significant amount of damage

Long-term displacement measurements provide important information about the structural safety of civil engineering structures and the associated maintenance necessary. Most approaches developed for measuring displacement, such as direct measurements using the linear variable differential transformer and computer vision-based sensing, relate to campaign-type sensor deployment. However, these methods have critical limitations when used to accurately measure long-term displacement, because it is di

Various types of structural systems are often subjected to the risk of fatigue-induced failures. If a structure does not have an adequate level of structural redundancy, local failures may initiate sequential failures and cause exceedingly large damage. For the risk-informed design and maintenance of such structural systems, it is thus essential to quantify the risk of fatigue-induced sequential failure. However, such risk analysis is often computationally intractable because one needs to explor

Because significant damages to structures having structural irregularity in their plans were repeatedly observed during many past earthquakes, there have been great research efforts to evaluate their seismic vulnerability. Although most of the previous studies used simplified structural representations such as one-dimensional or two-dimensional models in the fragility analysis of plan-irregular structures, simple analytical models could not represent true seismic behavior from the complicated no

There are continuous efforts to mitigate structural losses from earthquakes and manage risk through seismic risk assessment; seismic fragility curves are widely accepted as an essential tool of such efforts. Seismic fragility curves can be classified into four groups based on how they are derived: empirical, judgmental, analytical, and hybrid. Analytical fragility curves are the most widely used and can be further categorized into two subgroups, depending on whether an analytical function or sim

Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and

In this study, an artificial neural network (ANN)-based surrogate model is proposed to evaluate the system-level seismic risk of bridge transportation networks efficiently. To estimate the performance of a network, total system travel time (TSTT) was introduced as a performance index, and an ANN-based surrogate model was incorporated to evaluate a high-dimensional network with probabilistic seismic hazard analysis (PSHA) efficiently. To generate training data, the damage states of bridge compone

Earthquakes can have significant impacts on transportation networks because of the physical damage they can cause to bridges. Hence, it is essential to assess the seismic risk of a bridge transportation network accurately. However, this is a challenging task because it requires estimating the performance of a bridge transportation network at the system level. Moreover, it is necessary to deal with various possible earthquake scenarios and the associated damage states of component bridges conside

To complete a successful and aesthetic breast reconstruction for breast cancer survivors, tissue reinforcing acellular dermal matrices (ADMs) are widely utilized to create slings/pockets to keep breast implants or autologous tissue transfer secured against the chest wall in the desired location. However, ADM sheets are 2D and cannot completely cover the entire implant without wrinkles. Here, guided by finite element modeling, a kirigami strategy is presented to cut the ADM sheets with locally an

Management of the vertical long-term deflection of a high-speed railway bridge is a crucial factor to guarantee traffic safety and passenger comfort. Therefore, there have been efforts to predict the vertical deflection of a railway bridge based on physics-based models representing various influential factors to vertical deflection such as concrete creep and shrinkage. However, it is not an easy task because the vertical deflection of a railway bridge generally involves several sources of uncert

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, t