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The present work is concerned with the development of finite element techniques for nonlinear transient dynamic analysis of reinforced concrete plates and shells. Computational models have been developed and coded, which are applied to various engineering problems under static and dynamic loading conditions. The first part of the thesis deals with some aspects of linear-elastic, geometric and material nonlinear finite element formulations of general thin and thick shell analysis under static or quasistatic loading. A generalized displacement method is proposed to overcome the 'shear locking' problem for the degenerated thick shell element when used in the context of thin shell structures. The basic concept and mathematical formulation of the generalized displacement method are detailed and its application is illustrated by numerical examples. The method is also extended to the geometrically nonlinear analysis of thin shells based on both Updated and Total Lagrangian formulation. An elasto-viscoplastic analysis of anisotropic plates and shells is developed by means of the finite element displacement method. A discrete layered approach is adopted to represent different material properties and gradual plastification through the thickness. Viscoplastic yielding is based on the Huber-Mixes criterion extended by Hill for anisotropic material and special consideration is given to the evaluation of the viscoplastic strain increment for anisotropic situations. The second part of this thesis is concerned with nonlinear dynamic transient analysis of reinforced concrete shell structures. Direct integration methods are reviewed and discussed. In particular, the general single step explicit, implicit and implicit-explicit algorithms with predictor - corrector forms are presented and corresponding stability conditions are deduced by invoking the energy method. The modelling of reinforced concrete behaviour in shell structures under fast loading conditions is considered. Both a strain rate sensitive elasto-viscoplastic model and a strain rate sensitive elasto-plastic model are presented for describing concrete nonlinearities due to multiaxial compressive or tensile yielding under dynamic loads. The models are used in conjuction with a tensile crack monitoring algorithm to trace concrete crack opening and closing. Various reinforced concrete plates and shells are analyzed and reported in detail, with the results obtained being compared with those from other sources.

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Experimental verification of a novel system identification technique that can detect defects at the element level is successfully accomplished. The method can be used for in-service health assessment of real structures without disrupting normal operations. This study conclusively verifies the method.Analytical verification of the proposed algorithm has been successfully completed by the research team at the University of Arizona. Vo and Haldar (2004) experimentally verified the method by conducting tests on fixed-ended and simply supported defect-free and defective beams. The purpose of this research was to validate the method by conducting experiments with more realistic structures. A three-story one-bay steel frame, built to 1/3 scale to fit the experimental facility, was considered. The frame was excited by harmonic or impulsive excitation forces. The transverse acceleration responses were collected using capacitive accelerometers. The angular displacement responses were measured using an autocollimator. The dynamic responses of the frames were collected by a data acquisition system with simultaneous sampling capability. Using only experimentally collected response information and completely ignoring the excitation information, the stiffness of all the structural elements were identified. The method identified the defect-free frame very accurately. Defects, in terms of removing a beam, reducing cross sectional area over a small segment of a beam, and cutting notches in a beam, were introduced. The method correctly identified the defect location in all cases. Additional sensors were placed around the location of the defect in an effort to identify the defect spot more accurately. The proposed method also successfully identified defect with improved accuracy. To increase the implementation potential of the proposed method, the defect-free and defective frames are then identified using limited response information. A two-stage Kalman filter-based approach is used. It is denoted as Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. A sub-structure approach is used for this purpose. The GILS-EKF-UI method also identified the state of the structure using only limited response information. As expected, in this case the error in the identification goes up as less information is used. However, the error is much smaller than other methods currently available in the literature, even when input excitation was used for the identification purpose. The method is very robust and can identify defects caused by different types of loadings. The method can be used as a nondestructive defect assessment technique for structures.

Dynamic Air Diffuser

The purpose of this research was to quantify feedstock supply risk over the lifetime of an agricultural residue-based (straw and chaff) biorefinery and to determine the range of delivered prices. The Peace River region of Alberta was used as a case study for analysis, with a geographic information system utilized for data analysis. Inter-year availability of crop residues was highly variable over the 20 year period under study, which created significant differences in the delivered price of feedstock between minimum, average, and maximum availability scenarios. At the four primary study sites (Fahler, Grimshaw, Peace River, and Sexsmith), the range was from double the average availability for the maximum scenario to zero biomass available for the minimum scenario. Biomass availability is a function of grain yield, the biomass to grain ratio, the cropping frequency, and residue retention rate used to ensure future crop productivity. Using minimum, average, and maximum supply scenarios, delivered price was determined using the dynamic (time-dependent) Integrated Biomass Supply Analysis and Logistics (IBSAL) simulation model. Five biorefinery capacities, ranging from 50,000 to 500,000 tonnes of feedstock per year, were analyzed. Since no biomass was available to model in true minimum years, a simulated minimum of half the average availability was used. Delivered cost, including harvest and transportation, for the 50,000 t plant ranged from $24.01 t-1 for the maximum availability scenario at the Sexsmith site to $42.63 t-1 for the simulated minimum scenario at the Fahler site. The range for the 500,000 t plant at the Sexsmith site was $41.78 for the maximum availability and $70.98 for the simulated minimum availability. As no biomass is available (and hence the true cost is unknown) in some years, storage strategies must be implemented and alternate feedstock sources identified to supply biorefineries in low-yield years. Since feedstock cost is a large component of total operating cost of a biorefinery, feedstock supply variability and delivered cost inconsistency should be primary decision criteria for any future biorefinery projects.

The performance of an electric utility vehicle is very dependent on how it is used. The range can decrease significantly if there are many uphill along the route and if the vehicle carry a heavy load. The most important is that the vehicle never stops because lack of energy or power. The purpose of this thesis was to study how performance of the electric utility vehicle Nimbell Trigo were affected, depending on route, drive pattern and load. To study the performance, the parameters: battery current, state of charge and speed were analyzed. To analyze these parameters, a dynamic model of the vehicle has been created with Simulink. The model is based on physical relations and vehicle data. With the specifications for the vehicle and the force acting on it, energy consumption, battery current and power demand have been calculated with the Simulink model for specific routes and drive patterns. To validate the mode, three different routes were driven with Nimbell Trigo in Gothenburg and a simulation of the same routes and drive patterns were made with the Simulink model. The result from the validation shows that the dynamic model can predict the parameters of interest well, particularly the state of charge. The Simulink model can in the future be a time and cost efficient way, to analyze the performance of Nimbell Trigo and thereby replace test drives in an initial phase. / Marknaden för elektriska arbetsfordon har ökat de senaste åren i takt med dels ökade krav på miljövänliga alternativ, dels framsteg inom batteritekniken. Akilleshälen för de elektriska fordonen som grupp har varit energilagringen i batterierna. Erfordrad batteri- och motorstorlek är starkt kopplat till användningen av fordonet. Vid körningar med långa uppförsbackar samt tung last, förkortas räckvidden markant. Vid för höga belastningar på fordonet minskar maximala hastigheten och i längden kan motorn överhettas. För användaren är det av stor vikt att fordonet inte blir stillastående för att effekten eller energin inte räcker till. Syftet med detta examensarbete var att utreda hur det elektriska arbetsfordonet Nimbell Trigo presterar för olika rutter och körmönster, med en given last. För att utreda prestandan av fordonet skapades därför en dynamisk modell av Nimbell Trigo i det dynamiska simuleringsverktyget Simulink. De parametrar som valdes att studera var batterinivå som är kopplat till energin, batteriströmmen som är relaterad till effekten och i sin tur påverkar batterinivån, samt hastigheten som kan indikera när effekten inte räcker till. Med den dynamiska modellen kan effektbehov och energikonsumtion för en given sträcka beräknas på förhand. Fordonets hastighet, acceleration samt backtagningsförmåga erhålls för olika situationer från simuleringen. Dessa parametrar kan därmed studeras med avseende på olika motoralternativ genom att ange moment- och verkningsgradskurvan för motorn. Den dynamiska modellen validerades med testkörningar där Nimbell Trigo kördes en viss rutt med ett givet körmönster och last. Motorfrekvens, batteriström och batterinivå uppmättes. Dessa parametrar simulerades i modellen för samma rutt och körmönster. Mätvärdena från testkörningarna plottades mot de värden som erhölls från simuleringen. Resultatet visar att den dynamiska modellen som skapades stämmer bra överens mot uppmätta testdata. Den dynamiska modellen kan i framtiden komma att användas, för att på ett kostnads- och tidseffektivt sätt ersätta testkörningar i initiala studier av olika drivlinor och batterier.

The main goal is to develop decision policies for individual forest stand management. It addresses three major areas of interest in the optimal management of individual forest stands: incorporating a two-species growth and yield model into a single stand management model, incorporating a comprehensive list of management options into a single stand management model, and incorporating uncertainty into a single stand management model. Dynamic programming (DP) is a natural framework to study forest management with uncertainty. The forest stand management problem, as modelled in this thesis, has a large dimensional state space with a mix of discrete and continuous state variables. The DP model used to study this problem is solved by value iteration with the objective of understanding infinite horizon policies. However, since some of the state variables are continuous, all states can’t be examined in an attempt to create the cost-to-go function. Therefore, the cost-to-go function value is calculated at a given stage of the algorithm at a finite set of state points and then the cost-to-go values are approximated on the continuous portion of the state space using a continuous function. All of this is done with random processes impacting state transitions. With the mixed-species growth model developed in this thesis, a comprehensive list of management options can be incorporated into the DP model and, with the addition of uncertainty from sources such as market prices and natural disasters, near optimal stand management policies are developed. Solving the DP model with the required level of detail lead to the development of insight into function fitting on continuous state spaces and to the development of cost-to-go function approximation bounds. Studying the policies shows that the addition of uncertainty to the model captures the dynamics between market prices and stand definitions, and leads to policies that are better suited to decision making in a stochastic environment, when compared with policies that are developed with a deterministic model. Enough precision is built into the DP model to give answers to typical questions forest managers would ask.

This thesis intends to utilize mathematical models for testing the development of sustainable urban neighbourhoods and analyze the impact of these developments at city level using dynamic and multiobjective optimization techniques. These techniques aim to monitor and lower urban carbon emission levels, while predicting the municipality’s projected tax revenues. This study shows how multiple decision making models can operate and re- late to help analyze the implementation of a sustainable neighbourhood design in a mid-size urban area.

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