Probabilistic Modeling of Creep and Stress–Strain Diagram

• Published in: Probability Based High Temperature Engineering pp. 459 - 516
• Main Author: Razdolsky, Leo
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Subjects: Building construction & materials; Deterministic method; Fire protection; Limit state design; Mechanical engineering; Performance function; Probability-based structural design; Thermal loading
• ISBN: 9783319419077; 3319419072
• DOI: 10.1007/978-3-319-41909-1_7

Creep, probabilistic modeling of of structural Stress–strain diagram, probabilistic modeling of. During the first phase, stresses, and strains caused by external loads are calculated. These problems are addressed using methods of the theory of elasticity, theory of plasticity, and other like disciplines. The second phase of the calculation involves the comparison of the calculated stresses, strains, deflections, or other like parameters with values permitted under the applicable standard. The latter phase, albeit rather simple in the current computing procedures, is the most important one as it is one when the safety and cost-effectiveness of the structure are being assessed. Probabilistic analysis methods, unlike traditional Deterministic methods, provide a means to quantify the inherent risk of a structural design and to quantify the sensitivities of most important parts of the design in the overall reliability of a structural system as a whole. This chapter is intended to introduce the subject of probabilistic analysis (also known as probabilistic design) to engineers in the structural fire resistance design as well as act as a reference to guide those applying these methods to other branches of the Fire protection industry, such as (but not limited to) reliability of engineering systems. The level of mathematical complexity is aimed at those with limited statistical training; numerous references are given throughout that point to more elaborate details of the probabilistic methods.