Friday, 29 September 2017

Statistical knowledge and structural safety



American petroleum institute’s recent code for offshore oil and gas structures’ integrity management (APIRP 2SIM), came up with a concept that damage can be tolerable. This concept is based on looking towards structure as a system and not number of individual components (this is how a design engineer look at it while designing new structure). This is a fundamental change in concept of life extension of structures, previously it had to be demonstrated that every component satisfies the design criteria resulting in need of all damages to be repaired. Now with the concept of “damage can be tolerable” and looking into structure as a system, it can be very well shown that (by use of ultimate strength analysis) structure as whole (system) still satisfies the design criteria with a minimum repairs/ no repairs.
Further, risk based techniques can be used for development in inspection programs for damage detection and repair scheme.
Here risk is defined, as product of probability of failure and consequence of failure, for calculations of probability of failure.

We need strong background of statistical knowledge, as a minimum, we should be able to model the material and loads stochastically so that we can come up with area of overlap as probability of failure. Following figure shows a typical structural engineering problem where R is resistance (strength) of material and S is loads effect.

A typical design engineer does not have any knowledge about, how codes are developed or what is background theory about partial safety factors used? So he/ she takes help of structural engineering knowledge alone that too within framework of code requirements to save the structure. Sometimes he/she may succeed with help of advanced structural analyses. But most of the times the end result would be lot of repair suggestions or exhaustive inspection plans. Spending a lot of money to save the structure for its future use.

But a smart structural engineer should have a good statistical background and good domain knowledge so he can combine code ideas to apply for site specific things statistically and come up with optimum repair suggestions and risk based inspection plan.

Aalborg University has a requirement to complete PhD is that, we should complete at least 30 credits through various PhD courses planned. With every PhD course, I undertook I feel that I am getting my statistical knowledge building up. So I can say following applies rightly here :P

Half of being smart is knowing what you are dumb about.

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