loadfactors
So I'm going to start with one of the most basic steps in SE.
This is a copy from the McCormack book in Load and Resistance Factor Design and Allowable Strength Design, LRFD and ASD, respectively.
It comments on how the AISC Specifications provides the two methods as acceptable, notes information about load combinations and how the term limit state defines lots of what we do.
The term limit state is used to describe a condition at which a structure or part of it ceases to perform its intendeted function. There are two categories of it: strength and serviceability.
Where strength relates to basic analysis regarding stress and serviciabilty gets more into deformations, and strains.
As the book notes, the strength limit states define load-carrying capacity, including excessive yielding, fracture, buckling, fatigue and gross rigid body motion. Serviceability, defines performance, deflection, cracking, slipping, vibration and deterioration.
All those limit states must be prevented.
Why is this important?
Because it is an estimate.
As the book states, Structural engineers have long recognized the inherent uncertainty of both the magnitude of the loads acting on a structure and the ability of the structure to safely carry it, as well as the effects of multiple loads being additive, as for example, it can happen for a beam column, where one load can magnify the effect of another load.
So... shouldn't this be accounted in Structural Analysis?
It is part of what we do kids.
It is important to note that for the combined effect of multiple loads, related to a particular limit state or failure mode, we can describe them with a mathematical probability density function (MPDF).
For the ideal case, two probability density functions yield a mathematical relation for either the difference between or the ratio of the two means, and the possibility that the load wille xceed the resistance.
So the margin established between resistance and load in real cases is intended to reduce the probability of failure, pending on other factors.
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