| Summary: | A civil engineering structure is faced with many hazardous conditions such as blasts, earthquakes, hurricanes, tornadoes, floods, and fires during its lifetime. Even though structures are designed for credible events that can happen during a lifetime of the structure, extreme events do happen and cause catastrophic failures. Understanding the causes and effects of structural collapse is now at the core of critical areas of national need. One factor that makes studying
structural collapse difficult is the lack of full-scale structural collapse experimental test results against which researchers could validate their proposed collapse modeling approaches. The goal of this work is the creation of an element deletion strategy based on fracture models for use in validated prediction of collapse of steel structures. The current work reviews the state-of-the-art of finite element deletion strategies for use in collapse modeling of structures. It is shown
that current approaches to element deletion in collapse modeling do not take into account stress triaxiality in vulnerable areas of the structure, which is important for proper fracture and element deletion modeling. The report then reviews triaxiality and its role in fracture prediction. It is shown that fracture in ductile materials is a function of triaxiality. It is also shown that, depending on the triaxiality range, different fracture mechanisms are active and should be accounted
for. An approach using semi-empirical fracture models as a function of triaxiality are employed. The models to determine fracture initiation, softening and subsequent finite element deletion are outlined. This procedure allows for stress-displacement softening at an integration point of a finite element in order to subsequently remove the element. This approach avoids abrupt changes in the stress that would create dynamic instabilities, thus making the results more reliable and
accurate. The calibration and validation of these models are shown. The calibration is performed using a particle swarm optimization algorithm to establish accurate parameters when calibrated to circumferentially notched tensile coupons. It is shown that consistent, accurate predictions are attained using the chosen models. The variation of triaxiality in steel material during plastic hardening and softening is reported. The range of triaxiality in steel structures undergoing collapse
is investigated in detail and the accuracy of the chosen finite element deletion approaches is discussed. This is done through validation of different structural components and structural frames undergoing severe fracture and collapse.
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