Synthesis of National and International Methodologies Used for Bridge Health Indices

Chapter 2. Ratio-Based Condition Index

COMPUTATIONAL APPROACH OVERVIEW

A ratio-based condition index is frequently used in the United States, Canada, Italy, Japan, and other parts of the world.^(4–6) It assigns a condition index based on the ratio of the current condition to the condition of structure when it was new.

These indices are mostly adapted from the California BHI, which is a concept originally developed by the California Department of Transportation to generate a single-number measure of the structural performance of a bridge or a network of bridges. The index assesses the current condition of a bridge by aggregating the current condition value of all the elements of the bridge and comparing it to the total value of the bridge elements when they were in their best possible state. The value of each element is proportional to the quantity of elements in the present condition and the economic consequence of the element’s failure. The element’s failure cost (FC) can be seen as a weight emphasizing the importance of the element to the overall health of the bridge.

DATA INVENTORY AND CONDITION RATINGS

The development of most ratio-based condition indices is based on the following two primary sources of data:

• Element-level bridge condition data.
  
  
• Element failure or replacement cost data.

Element-Level Condition Data

Element-level inspections capture the conditions of more detailed components compared with the NBI database used by the Federal Highway Administration (FHWA). For instance, instead of rating the condition of the whole superstructure (NBI case), an element-level inspection looks at the condition of the individual components of the superstructure, such as girders, floor beams, pins, hangers, bearings, etc.

Inspectors rate the condition of elements according to the following states and descriptions: “Good” (1), “Fair” (2), “Poor” (3), and “Severe” (4). The number of states and descriptions used was standardized by the AASHTO Manual for Bridge Element Inspection, which was published and adopted in 2013.⁽⁷⁾

One of the key strengths of element-level inspection is its ability to simultaneously capture the severity and extent of deterioration of an element. For example, an inspection of a girder reports the percentage, or extent, of the girder that is in the different condition states (e.g., 10 percent in condition 1, 25 percent in condition 2, and 65 percent in condition 3).

Element Failure or Replacement Cost Data

The cost associated with the failure of an element is estimated from one of the following two main sources:

• Agency and User Cost Estimates—The cost to the agency may include operating costs, cost of inspection, cost of maintenance, rehabilitation, etc. Examples of user costs include estimated costs associated with delays when traffic flow is restricted or diverted, increases in vehicle operating costs due to bridge inadequacies, upkeep of detours, etc. Also, note that the costs are only for one element. The current BHI method does not consider the effect of subordinate elements.
  
  
• Element Replacement Cost—This cost is estimated by expert bridge engineers.

Calculating the California BHI

BHI is based on the premise that a bridge has an initial asset value when it is commissioned. This value depreciates due to deterioration caused by traffic loading and environmental effects. Interventions through maintenance or rehabilitation improves the value and corresponding condition of the bridge asset.⁽⁴⁾ The BHI is calculated as the ratio of the aggregate remaining value of the bridge elements to the total initial value of the element. The following steps are used to calculate BHI.

Step 1

Obtain element-level inspection data from BrM (table 2), with the understanding that an element can have portions of it in more than one condition state.

Q_n = Quantity of each element in each condition state.

n = Number of condition state for each element.

ea = Each.

Step 2

Calculate a weighting factor (WF) for each of the condition states (figure 1). Table 3 shows an example of WFs for various number of condition states.

Figure 1. Equation. Condition state WF.

Step 3

Based on current element conditions in step 1, estimate the FC of each element (table 2). The two approaches for calculating FC are as follows:

• Element agency FC plus element user FC.
  
  
• Element replacement cost multiplied by element WF.

These cost values are established through expert solicitation.

Step 4

Calculate the total element value (TEV) (figure 2) and the current element value(CEV) (figure 3).

Figure 2. Equation. TEV.

Figure 3. Equation. CEV.

Step 5

Calculate the BHI as the ratio of the TEV to the CEV (figure 4).

Figure 4. Equation. BHI.

STRENGTHS AND LIMITATIONS

Strengths

The use of element-level inspection data provides a thorough and objective assessment of the condition of the bridge. Inspectors are able to capture both the severity and extent of any problems that may influence the integrity of the structure. Such information is valuable for planning maintenance, repair, and rehabilitation programs.

The health index is also useful for structural health comparisons and resource allocation for a network of bridges. Some State agencies are mostly interested in fixing bridges with the most severe deficiencies rather than those with clearance and geometric (functional) issues. In such cases, the health index can be incorporated into prioritization models used for allocating funds for the repair and rehabilitation of bridges with a low health index.

Limitations

Availability of Element-Level Data

Many agencies, especially at the county level, do not collect element-level data required for computing the health index. The recently adopted AASHTO Manual for Bridge Element Inspection provides standard guidelines for assessing how good or poor the bridge condition is, resulting in a more uniform basis for the computed health index.⁽⁷⁾

FC Data

In estimating the FC of an element, since the true cost of an element’s failure is unknown, several assumptions and estimations have to be made. This makes the FC uncertain. FCs are sometimes related to agency and user costs, which are very difficult to estimate. Different agencies will have different FCs. Anything outside the true FC is an estimate and therefore uncertain. The variability of FC estimates also increases the difficulty of standardizing the BHI across agencies and countries. A replacement cost of one element varies from State to State and project to project. Since the replacement cost varies, the health index also becomes variable and uncertain. Equal health indices from two different regions might not necessarily mean that the two bridges have similar structural condition. Relative structural health comparisons between bridges is therefore challenging.

The Universal Bridge Health Index (UBHI), developed by Sivakumar et al., was intended to standardize the use of the index across different States and countries.⁽⁹⁾ The UBHI does not consider economic value of elements; rather, their physical conditions are used. This helps reduce the uncertainties associated with estimating the significance of bridge elements. In place of the economic worth or FCs, the UBHI calculates a structural significance factor and material vulnerability factor. These two factors, although less uncertain compared with economic cost, are still very subjective. The structure significance is found by comparing the role of one element to the role of other elements with a range of 1 (least significant) to 4 (most significant).

Computational Issues

In calculating the health index, only conditions of structural elements of the bridge are considered. The bridge’s functional adequacies (service provided by the bridge) such as capacity, traffic volume, and clearance issues are ignored. Corporate bridge risk factors such as scour, seismic, and fatigue are also not incorporated. Therefore, although the health index provides management with an indicator of the overall condition of the bridge, it is not a complete measure of the value of the agency’s investments.