Corrugated wood composite panels for structural decking

High flexural strength and stiffness can be achieved by forming a thin panel into a wave shape perpendicular to the bending direction. The use of corrugated shapes to gain flexural strength and stiffness is common in metal and reinforced plastic products. However, there is no commercial production of corrugated wood composite panels. This research focuses on the application of corrugated shapes to wood strand composite panels. Beam theory, classical plate theory and finite element models were used to analyze the bending behavior of corrugated panels. The most promising shallow corrugated panel configuration was identified based on structural performance and compatibility with construction practices. The corrugation profile selected has a wavelength equal to 8”, a channel depth equal to ¾”, a sidewall angle equal to 45 degrees and a panel thickness equal to 3/8”. 16”x16” panels were produced using random mats and 3-layer aligned mats with surface flakes parallel to the channels. Strong axis and weak axis bending tests were conducted. The test results indicate that flake orientation has little effect on the strong axis bending stiffness. The 3/8” thick random mat corrugated panels exhibit bending stiffness (400,000 lbs-in2/ft) and bending strength (3,000 in-lbs/ft) higher than 23/32” or 3/4” thick APA Rated Sturd-I-Floor with a 24” o.c. span rating. Shear and bearing test results show that the corrugated panel can withstand more than 50 psf of uniform load at 48” joist spacings. Molding trials on 16”x16” panels provided data for full size panel production. Full size 4’x8’ shallow corrugated panels were produced with only minor changes to the current oriented strandboard manufacturing process. Panel testing was done to simulate floor loading during construction, without a top underlayment layer, and during occupancy, with an underlayment over the panel to form a composite deck. Flexural tests were performed in single-span and two-span bending with line loads applied at mid-span. The average strong axis bending stiffness and bending strength of the full size corrugated panels (without the underlayment) were over 400,000 lbs-in2/ft and 3,000 in-lbs/ft, respectively. The composite deck system, which consisted of an OSB sheathing (15/32” thick) nailed-glued (using 3d ringshank nails and AFG-01 subfloor adhesive) to the corrugated subfloor achieved about 60% of the full composite stiffness resulting in about 3 times the bending stiffness of the corrugated subfloor (1,250,000 lbs-in2/ft). Based on the LRFD design criteria, the corrugated composite floor system can carry 40 psf of unfactored uniform loads, limited by the L/480 deflection limit state, at 48” joist spacings. Four 10-ft long composite T-beam specimens were built and tested for the composite action and the load sharing between a 24” wide corrugated deck system and the supporting I-joist. The average bending stiffness of the composite T-beam was 1.6 times higher than the bending stiffness of the I-joist. A 8-ft x 12-ft mock up floor was built to evaluate construction procedures. The assembly of the composite floor system is relatively simple. The corrugated composite floor system might be able to offset the cheaper labor costs of the single-layer Sturd-IFloor through the material savings. However, no conclusive result can be drawn, in terms of the construction costs, at this point without an in depth cost analysis of the two systems. The shallow corrugated composite floor system might be a potential alternative to the Sturd-I-Floor in the near future because of the excellent flexural stiffness provided.

Inductive-Capacitive Resonant Circuit Sensors for Structural Health and Environmental Monitoring

Inductive-capacitive (LC) resonant circuit sensors are low-cost, wireless, durable, simple to fabricate and battery-less. Consequently, they are well suited to sensing applications in harsh environments or in situations where large numbers of sensors are needed. They are also advantageous in applications where access to the sensor is limited or impossible or when sensors are needed on a disposable basis. Due to their many advantages, LC sensors have been used for sensing a variety of parameters including humidity, temperature, chemical concentrations, pH, stress/pressure, strain, food quality and even biological growth. However, current versions of the LC sensor technology are limited to sensing only one parameter. The purpose of this work is to develop new types of LC sensor systems that are simpler to fabricate (hence lower cost) or capable of monitoring multiple parameters simultaneously. One design presented in this work, referred to as the multi-element LC sensor, is able to measure multiple parameters simultaneously using a second capacitive element. Compared to conventional LC sensors, this design can sense multiple parameters with a higher detection range than two independent sensors while maintaining the same overall sensor footprint. In addition, the two-element sensor does not suffer from interference issues normally encountered while implementing two LC sensors in close proximity. Another design, the single-spiral inductive-capacitive sensor, utilizes the parasitic capacitance of a coil or spring structure to form a single layer LC resonant circuit. Unlike conventional LC sensors, this design is truly planar, thus simplifying its fabrication process and reducing sensor cost. Due to the simplicity of this sensor layout it will be easier and more cost-effective for embedding in common building or packaging materials during manufacturing processes, thereby adding functionality to current products (such as drywall sheets) while having a minor impact on overall unit cost. These modifications to the LC sensor design significantly improve the functionality and commercial feasibility of this technology, especially for applications where a large array of sensors or multiple sensing parameters are required.

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.