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Wind turbine efficiency typically focuses on the shape, orientation, or stiffness of the turbine blades. In this thesis, the focus is instead on using static fixed airfoils in proximity to the wind turbine to control the airflow coming out of the turbine. These control devices have three beneficial effects. (1) They gather air from “higher up” where the air is moving faster on average (and therefore has more kinetic energy in it). (2) They throw the used (and slowed down air) downwards. This means that any turbines in the wind farm behind the lead turbines do not get “stale” air. (3) These control devices provide a large stabilizing lifting force for floating off-shore turbines. In this study, Reynolds-Averaged Navier-Stokes (RANS) simulations of an aligned array of two wind turbines along with various designs of these control devices is studied. The recovery in the velocity at the inlet plane of downstream turbine due to the controlled flow facilitated by these devices is measured with respect to the average streamwise wind velocity at the inlet plane of upstream turbine. A customized numerical solver was written in C++ using Opensource Field Operation And Manipulation (OpenFOAM) to model the turbines as actuator discs with axial induction and to generate an inlet velocity field similar to a turbulent atmospheric boundary layer (ABL). All the design configurations use a streamlined (airfoil shaped) structure, at an angle of attack carefully selected to prevent flow separation depending upon its location around the turbine. For strong wake displacement, the devices are placed in proximity to the upstream wind turbine so as to facilitate a substantial downwash of the faster wind from upper layers of the ABL and at the same time deflect the wake out of the way of the downstream turbine. Also, the pressure coefficient across the upstream turbine augmented with these devices can sometimes become more negative than a bare turbine, which in turn increases the mass flow rate of air passing through it, thereby also increasing the leading turbine’s efficiency slightly.

This thesis has investigated the application of CFRP and GFRP bars as longitudinal reinforcement for continuously supported concrete beams. Two series of simply and continuously supported CFRP and GFRP reinforced concrete beams were tested in flexure. In addition, a continuously supported steel reinforced concrete beam was tested for comparison purposes. The FRP reinforced concrete continuous beams were reinforced in a way to accomplish three possible reinforcement combinations at the top and bottom layers of such continuous beams. The experimental results revealed that over-reinforcing the bottom layer of either the simply or continuously supported FRP beams is a key factor in controlling the width and propagation of cracks, enhancing the load capacity, and reducing the deflection of such beams. However, continuous concrete beams reinforced with CFRP bars exhibited a remarkable wide crack over the middle support that significantly influenced their behaviour. The ACI 440.1R-06 equations have been validated against experimental results of beams tested. Comparisons between experimental results and those obtained from simplified methods proposed by the ACI 440 Committee show that ACI 440.1R-06 equations can reasonably predict the load capacity and deflection of the simply and continuously supported GFRP reinforced concrete beams tested. However, The potential capabilities of these equations for predicting the load capacity and deflection of continuous CFRP reinforced concrete beams have, however, been adversely affected by the de-bonding of top CFRP bars from concrete. An analytical technique, which presents an iterative procedure based on satisfying force equilibrium and deformation compatibility conditions, has been introduced in this research. This technique developed a computer program to investigate flexural behaviour in particular the flexural strength and deflection of simple and continuously supported FRP reinforced concrete beams. The analytical modelling program has been compared against different prediction methods, namely ACI 440, the bilinear method, mean moment inertia method and Benmokrane¿s method. This comparison revealed the reliability of this programme in producing more enhanced results in predicting the behaviour of the FRP reinforced beams more than the above stated methods.

The mechanical and thermal properties of natural short latania fiber (SLF)-reinforced poly(propylene)/ethylene-propylene-diene-monomer (SLF/PP/EPDM) bio-composites reinforced with nano-clays (NCs), pistachio shell powders (PSPs), and/or date seed particles (DSPs) were studied using experiments and machine learning (ML) predictions. This dissertation embraces three related investigations: (1) an assessment of maleated polypropylene (MAPP) coupling agent on mechanical and thermal behavior of SLF/PP/EPDM composites, (2) heat deflection temperature (HDT) of bio-nano-composites using experiments and ML predictions, and (3) fracture toughness ML predictions of short fiber, nano- and micro-particle reinforced composites. The first project (Chapter 2) investigates the influence of MAPP on tensile, bending, Charpy impact and HDT of SLF/PP/EPDM composites containing various SLF contents. The second project (Chapter 3) introduces two new bio-powderditives (DSP and PSP) and characterizes the HDT of PP/EPDM composites using experiments and K-Nearest Neighbor Regressor (KNNR) ML predictions. The composites contain various contents of SLF (0, 5, 10, 20, and 30wt%), NCs (0, 1, 3, 5wt%), micro-sized PSPs (0, 1, 3, 5wt%) and micro-sized DSPs (0, 1, 3, 5wt%). The third project (Chapter 4) characterizes the fracture toughness of the same composite series used in the second project, by applying Charpy impact tests, finite element analysis, and a ML approach using the Decision Tree Regressor (DTR) and Adaptive Boosting Regressor (ABR). 2wt% MAPP addition enhanced the composite tensile/flexural moduli and strength up to 9% compared with the composites with zero MAPP. In addition, energy impact absorption was profoundly increased (up to78%) and HDT (up to 4 Co) was improved upon MAPP addition to the composites. SLF, NC, DSP and PSP could separately and conjointly increase HDT and fracture toughness values. The KNNR ML approach could accurately predict the composite’s HDT values and, Decision Tree Regressor (DTR) and Adaptive Boosting Regressor ML algorithms worked well with fracture toughness predictions. Pictures taken through a transmission electron microscope, scanning electron microscope and X-Ray proved the NC dispersion and exfoliation as one of the factors in HDT and fracture toughness improvements.

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Yes / The impact behavior of deflection-hardening High Performance Fiber Reinforced Cementitious Concretes (HPFRCs) was evaluated herein. During the preparation of HPFRCs, fiber type and amount, fly ash to Portland cement ratio and aggregate to binder ratio were taken into consideration. HPFRC beams were tested for impact resistance using free-fall drop-weight test. Acceleration, displacement and impact load vs. time graphs were constructed and their relationship to the proposed mixture parameters were evaluated. The paper also aims to present and verify a nonlinear finite element analysis, employing the incremental nonlinear dynamic analysis, concrete damage plasticity model and contact surface between the dropped hammer and test specimen available in ABAQUS. The proposed modelling provides extensive and accurate data on structural behavior, including acceleration, displacement profiles and residual displacement results. Experimental results which are further confirmed by numerical studies show that impact resistance of HPFRC mixtures can be significantly improved by a proper mixture proportioning. In the presence of high amounts of coarse aggregates, fly ash and increased volume of hybrid fibers, impact resistance of fiberless reference specimens can be modified in a way to exhibit relatively smaller displacement results after impact loading without risking the basic mechanical properties and deflection-hardening response with multiple cracking.