Structural capacity of steel tubular cast-in-place piling

Steel tubular cast-in-place pilings are used throughout the country for many different project types. These piles are a closed-end pipe with varying wall thicknesses and outer diameters, that are driven to depth and then the core is filled with concrete. These piles are typically used for smaller bridges, or secondary structures. Mostly the piling is designed based on a resistance based method which is a function of the soil properties of which the pile is driven through, however there is a structural capacity of these members that is considered to be the upper bound on the loading of the member. This structural capacity is given by the AASHTO LRFD (2010), with two methods. These two methods are based on a composite or non-composite section. Many state agencies and corporations use the non-composite equation because it is requires much less computation and is known to be conservative. However with the trends of the time, more and more structural elements are being investigated to determine ways to better understand the mechanics of the members, which could lead to more efficient and safer designs. In this project, a set of these piling are investigated. The way the cross section reacts to several different loading conditions, along with a more detailed observation of the material properties is considered as part of this research. The evaluation consisted of testing stub sections of pile with varying sizes (10-¾”, 12-¾”), wall thicknesses (0.375”, 0.5”), and testing methods (whole compression, composite compression, push through, core sampling). These stub sections were chosen as they would represent a similar bracing length to many different soils. In addition, a finite element model was developed using ANSYS to predict the strains from the testing of the pile cross sections. This model was able to simulate the strains from most of the loading conditions and sizes that were tested. The bond between the steel shell and the concrete core, along with the concrete strength through the depth of the cross section were some of the material properties of these sections that were investigated.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.