Probabilistic Approach in Breakwater Design

Design of breakwater is not plugging numbers into Hudson's or Vandermeer's formulae instead it is a systematic assessment of failure probability based on the newly evolved design philosophy by PIANC ( Report No196: 2016). The report is the outcome of research after a considerable number of large breakwaters had failed globally or suffered severe damage. One of the primary requirements to breakwater design process is to achieve an acceptable low probability of failure throughout the design life as recommended in all design codes and guidelines. All components of the breakwater such as main and leeside armour, toe and crest wall etc should have adequate partial safety so that the entire system behave consistently on a low possibility of failure during its design life. Therefore every design should be based on a low probability of failure for both ultimate limit state and repair limit states throughout the intended design life of the breakwater.

The new system of design for rubble mound breakwaters has been developed by PIANC whereby partial coefficients can be derived for any chosen probability of failure within the specified service life of the proposed structure. Strength (R) of the structure and loading (S) are usually functions of many variables. The load variable normally includes wave height, period and direction and water level. The geometry and material of the structure are typical strength variables. When no damage or excess is allowed then the condition R>=S is applied, which is refers as the limit state condition. The probability of failure is the probability that the loading exceeds the strength (R>S).Depends on the complexity of analysis it is classified into three levels, level III design involves large number of computations using many combinations of the possible values of the variables in order to determine the failure probably. This can be done using Monte Carlo methods.

Monte Carlo Simulation Method

Level III methods are the most general of the reliability techniques, the complexity of the integral can be dealt with numerical rather than analytical methods. In this method a set of values of the basic variables are generated with the appropriate probability distribution and the values of the reliability function determined. By repeating this process many times and storing, the integral may be estimated as the proportion of the results for which the reliability function is negative.

Following is an example of computation using MathCAD functions (This article is posted intending to share knowledge/experience to the people those who are new to this industry)