Terje Haukaas
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Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
In this dissertation an object-oriented framework of models is developed and applied to study disaster recovery in communities in British Columbia, Canada. The impact of earthquakes on communities is quantified over months and years, and the focus is on identifying the factors that affect the recovery. Contrasting with the practice of investigating disaster impacts to infrastructure or societal systems in isolation, an integrated approach is used in this dissertation. Lifelines, buildings, and persons are modelled in the same computational environment. One contribution of this dissertation is the development of models for infrastructure and social systems of a community. Another contribution is the development of a new approach to simulate the transportation of goods through a network of models. This new approach allows great flexibility in the composition of the transported goods and facilitates the modelling of the competition for resources. Another innovation is the individual modelling of buildings and dwellings, in this work referred to as dwellings, in the community. The socioeconomic demographics of the dwellings determine their capacity to compete for limited resources, which affect their recovery capacity. The integration of socioeconomic demographics, infrastructure, and buildings in the same computational environment allows for a broad range of disaster mitigation actions to be compared. This dissertation assesses the benefits of improving resource management, retrofitting physically vulnerable infrastructure, improving access to funds for recovery, among other actions. The findings in this dissertation can inform pre-disaster plans and help identifying mitigation strategies that improve disaster recovery in communities in British Columbia.
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This dissertation presents models and methods for the lifecycle analysis of buildings. Detailed models are developed that are associated with constructing, operating, repairing, and demolishing buildings. These models address an array of direct and indirect concerns, including impacts from the repair of earthquake damage. In support of cost-based decision making, a host of cost models are implemented to translate lifecycle impacts into monetary costs. The significant uncertainty in predicting earthquake hazards, material behaviour, and future costs is addressed through probabilistic modelling.The models in this dissertation are underpinned by a new library of building components. The components contain finite elements, built-in functionality, and information required for lifecycle analysis. These information-rich building components are created from building information models, or BIMs, with algorithms that are implemented in this dissertation. Methods are presented for generating a structural model from the components, and a correlation structure is developed for random variables that are created within these components.A novelty of this work is a seismic loss estimation methodology that is based on visual damage. Models are developed that predict visual damage from the responses of high- fidelity finite element models. A new damage mesh discretizes building components into damage regions where the stresses and strains are expected to influence the damage at the surface. Resembling the approach of a repair estimator, arrays of repair actions are described for different types and extents of visual damage. The repair actions are paired with a construction database to provide enriched estimates of the repair cost and duration.The new models and methods are applied to a six-storey building in order to gain new insights into the repair of earthquake damage. The building is subjected to earthquake ground motions, where it is demonstrated that the ground shaking duration, and the damage accumulated during the initial part of the shaking, influence the subsequent repairs. Next, several lifecycle analyses are performed, and wood, concrete, and steel material options are compared for the structural system. Results show that wood is the better option from a broader societal perspective.
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The overarching objective in this work is to advance damage modelling for performance-based earthquake engineering. To achieve this objective, this thesis provides a new vision, technique, and software framework for the assessment of seismic damage and loss to building components. The advent of performance-based earthquake engineering placed a renewed emphasis on the assessment of damage and monetary loss in structural engineering. Assessment of seismic damage and loss for decision making entails two ingredients. First, models that predict the detailed damage to building components; second, a probabilistic framework that simulates damage and delivers the monetary loss for the reliability, risk, and optimization analysis. This motivates the contributions in this thesis, which are summarized in the following paragraphs. First, a literature review is conducted on models, techniques and experimental studies that address component damage due to earthquakes. The existing approaches for prediction of the seismic damage, repair actions, and costs are examined. The objective in this part is to establish a knowledge bank that facilitates the subsequent development of probabilistic models for seismic damage. Second, a logistic regression technique is employed for developing multivariate models that predict the probability of sustaining discrete damage states. It is demonstrated that the logistic regression remedies several shortcomings in univariate damage models, such as univariate fragility curves. The multivariate damage models are developed for reinforced concrete shear walls using experimental data. A search algorithm for model selection is included. It is found that inter-story drift and aspect ratio of walls are amongst the most influential parameters on the damage. Third, an object-oriented software framework for detailed simulation of visual damage is developed. The work builds on the existing software Rt. Emphasis is on the software framework, which facilitates detailed simulation of component behaviour, including visual damage. Information about visual damage allows the prediction of repair actions, which in turn improves our ability to predict the time and cost of repair.
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The fundamental objective in this thesis is to advance the state-of-the-art in the field of infrastructure risk analysis. To meet this objective, probabilistic models, methods, and software are developed and applied. The work is conducted within a new reliability-based approach, in which reliability methods are employed to compute risk. Risk, in this context, means the probability of exceeding monetary loss. Evaluating such probabilities requires probabilistic models for hazards, response, damage, and loss. This motivates the contributions in this thesis, which are summarized as follows: First, a new computer program, called Rt, is developed. It is tailored to conduct reliability analysis with many probabilistic models. It orchestrates the interaction of models by means of a new object-oriented software design. Each model and analysis algorithm is represented by an object. As a result, new models and algorithms are easily implemented without modifying existing code. Another novelty is the parameterization of uncertainties, decisions, and model responses. This has several implications; one being that, in each step of an analysis, only the models affected by new parameter realizations are evaluated. Another novelty is the computation of “direct differentiation” response sensitivities in a multi-model analysis. Second, a library of new probabilistic models are developed and implemented in Rt. The models are intended for use in regional seismic risk analysis. The library includes new models for location and magnitude of earthquakes, and response, damage, and loss of building. The library also features damage and loss models for entire regions. Third, the models are applied in a risk analysis for the Vancouver metropolitan region in Canada. The primary results are “loss curves” and “hazard curves,” which show the probability of exceeding loss and spectral acceleration, respectively. As another example of results, it is found that Richmond is the most vulnerable municipality. Finally, new sensitivity measures are developed to prioritize the allocation of resources to mitigate risk and to reduce model uncertainty. In particular, these measures identify the buildings whose retrofit yields the most reduction in regional risk. They also identify the models whose improvement yields the most reduction in uncertainty.
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This thesis presents the development, implementation, and application of response sensitivities in numerical simulation of composite manufacturing. The sensitivity results include both first- and second-order derivatives. Such results are useful in many applications. In this thesis, they are applied in reliability analysis, optimization analysis, model validation, model calibration, as well as stand-alone measures of parameter importance to gain physical insight into the curing and stress development process. In addition to novel derivations and implementations, this thesis is intended to facilitate and foster increased use of response sensitivities in engineering analysis. The work presented in this thesis constitutes an extension of the direct differentiation method (DDM). This is a method that produces response sensitivities in an efficient and accurate manner, at the one-time cost of deriving and implementing sensitivity equations alongside the ordinary response algorithm. In this thesis, novel extensions of the methodology are presented for the composite manufacturing problem. The derivations include all material, geometry, and processing parameters in both the thermochemical and the stress development algorithms. A state-of-the-art simulation software is developed to perform first-order sensitivity analysis for composite manufacturing problems using the DDM. In this software, several novel techniques are employed to minimize the computational cost associated with the response sensitivity computations. This sensitivity-enabled software is also used in reliability, optimization, and model calibration applications. All these applications are facilitated by the availability of efficient and accurate response sensitivities.The derivation and implementation of second-order sensitivity equations is a particular novelty in this thesis. It is demonstrated that it is computationally feasible to obtain second-order sensitivities (the “Hessian matrix”) by the DDM for inelastic finite element problems. It is demonstrated that the direct differentiation approach to the computation of first- and second-order response sensitivities becomes increasingly efficient as the problem size increases, compared with the less accurate and less efficient finite different approach.
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Performance-based earthquake engineering is an emerging field of study that complements the prescriptive methods that the design codes provide to ensure adequate seismic performance of structures. Accounting for uncertainties in the performance assessments forms an important component in this area. In this context, the present study focuses on two broad themes; first, treatment of uncertainties and the application of the first-order reliability method (FORM) in finite-element reliability analysis, and second, the seismic risk assessment of reinforced concrete structures for performance states such as, collapse and monetary loss. In the first area, the uncertainties arising from inherent randomness (“aleatory uncertainty”) and due to the lack of knowledge (“epistemic uncertainty”) are identified. A framework for the separation of these uncertainties is proposed. Following this, the applicability of FORM to the linear and nonlinear finite-element structural models under static and dynamic loading is investigated. The case studies indicate that FORM is applicable for linear and nonlinear static problems. Strategies are proposed to circumvent and remedy potential challenges to FORM. In the case of dynamic problems, the application of FORM is studied with an emphasis on cumulative response measures. The limit-state surface is shown to have a closed and nonlinear geometric shape. Solution methods are proposed to obtain probability bounds based on the FORM results. In the application-oriented second area of research, at first, the probability of collapse of a reinforced concrete frame is assessed with nonlinear static analysis. By modelling the post-failure behaviour of individual structural members, the global response of the structure is estimated beyond the component failures. The final application is the probabilistic assessment of monetary loss for a high-rise shear wall building due to the seismic hazard in the Cascadia subduction zone. A 3-dimensional finite-element model of the structure with nonlinear material models is subjected to stochastic ground motions in the reliability analysis. The parameters for the stochastic ground motion model are developed for Vancouver, Canada. Monetary losses due to the damage of structural and non-structural components are included.
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Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
This thesis presents and examines a database of structural failures, including bridges, buildings, and telecommunication towers. In addition to the database, a novelty of this work is the comparison of observed failure probabilities with target reliability index values in design codes. The study aims to improve the safety of future construction by exposing and understanding past structural failures. A labelling system is established to categorize and provide a basis for the future documentation of failures. The 275 failures in the database are collected from a search of newspaper articles, case studies, and the Imhof (2021) database of bridge failures. The scope of structural failures in this research considers partial and total collapse. The focus of the database is unexpected failures; therefore, failures due to vandalism, terrorism, or earthquakes are not considered. Earthquakes are excluded from the natural hazards considered because substantial damage is often expected during design-level ground shaking. Other natural hazards, such as ice accumulation, wind, and flooding, are considered. The majority of the failures that are considered in the database occurred in the United States; those account for 41% of the failures. Several insights are obtained from the total database. For instance, the most significant cause of failure for bridges is natural hazards, accounting for 29% of the failures. That is followed by 20% design errors and 15% failures caused by collisions. The most significant causes of failure for buildings are construction errors (24%), design errors (20%), and natural hazards (15%). The most significant failure causes for telecommunication towers are natural hazards (61%) and negligent maintenance errors (26%). The failures that occur during maintenance operations are primarily associated with the removal of structural members without adequate temporary support. The bridge superstructure type with the most failures is beam bridges. In the United States, truss bridges are apparently associated with the largest probability of failure. That failure probability corresponds to a reliability index of 3.1, which is inferior to the lifetime target reliability index of 3.5 from CSA S6.1.19.
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In this thesis, parametric studies are performed, to understand the effect of selected input parameters on the seismic response of a multi-span concrete bridge. An existing model of an archetype three-span concrete continuous bridge is analyzed with the Python interpreter of the finite element program OpenSees. Two stochastic ground motion models are employed in Python to generate accelerograms compatible with certain soil properties. An orchestrating algorithm in Python is established to analyze the seismic bridge response over a range of values of the selected input parameters. The parameters are the pier diameter of the bridge, the initial stiffness of the bridge, the stiffness of the deck, the dominant frequency of the soil, and the damping of the soil. The responses monitored in this study are the displacement of the pier, the plastic rotation of a section of the pier, the shear deformation of the bearing pad, and the cumulative energy dissipation. In addition, the effect of randomness in the ground motion generation and the effect of spectral nonstationarity in the ground motions are studied.Three findings stand out from the studies conducted in this thesis. First, amplification in the nonlinear response occurs at ground motion frequencies lower than the natural frequency of the bridge. Reduced post-yield stiffness and permanent deformations in the piers are found to govern this response amplification. Second, randomness in the ground motion generation results in substantial uncertainty in the peak responses. The coefficient of variation of the responses isobserved to be as high as 26%. Third, spectral nonstationarity in the ground motion is found to induce higher plastic deformations in the bridge, as compared to the stationary ground motions.
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Self-centring Cross-Laminated Timber (CLT) walls are a low damage seismic force resisting system, which can be used to construct tall wood buildings. This study examines two approaches to model self-centring CLT walls, one that uses lumped plasticity elements, and another that uses fibre-based elements. Finite element models of self-centring CLT walls are developed using the Python interpreter of Opensees, OpenSeesPy, and tested under monotonic and reverse cyclic loading conditions. Outputs from the analysis are compared with data from two existing experimental programs. Both models accurately predict the force displacement relationship of the wall in monotonic loading. For reverse cyclic loading, the lumped plasticity model could not capture cyclic deterioration due to crushing of CLT. Both models slightly overpredict the post-tension force. Sensitivity analyses were run on the fibre model, which show the wall studied is not sensitive to the shear stiffness of CLT. OpenSeesPy models are also created of a two-story structure, which is tested dynamically under a suite of ground motions. The structure is based on a building tested as part of the NHERI TallWood initiative. During testing the foundation of the building was found to be inadvertently flexible. To determine the appropriate model parameters for this foundation, calibrations were performed by running a sequence of OpenSeesPy analyses with an optimization algorithm. Outputs from the lumped plasticity and fibre models were compared to experimental results, which showed that both could capture the global behaviour of the system with reasonable accuracy. Both models overpredict peak post-tension forces. The suite of analyses is then run again on the building to predict the performance with a rigid foundation. Cyclic deterioration is more significant for the building with a rigid foundation, and as a result the fibre mode is more accurate.
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The goal of the research described in this thesis is to develop a program that assists designers in designing highly efficient buildings. Rts is a model framework software that performs holistic life-cycle analysis and contains algorithms and data used to calculate relevant costs. Compatibility with building information models allows Rts to interface with other design software, while model interchangeability allows for the application of new relevant research.Holistic life-cycle cost assessment is useful for quantifying various outcomes of a building design, such as construction cost and environmental impact. It allows for single-objective optimization by weighing these multiple outcomes objectively. Different costs have been categorized and are calculated in different models, with the existing models reviewed in this thesis. New models for construction cost, based off costing data, and concrete maintenance, using carbonation theory, have been developed.A parametric study was performed to make preliminary observations and verify the accuracy of the models. It was found that operating costs contribute a major portion, 33%, of the total direct cost of a building, in agreement with existing literature. Furthermore, environmental impacts, particularly those resulting from emissions during operation, also contribute a large portion of total cost, at 36%. Additionally, transporting construction materials from overseas results in a dramatic increase of the environmental cost of construction, and renewable energy sources lead to a much lower total life-cycle cost. Other variables studied include the depth of concrete cover, and the influence of the discounting rate and design building life.
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This thesis presents a collection of numerical models that predict the total lifetime cost of buildings. Different models are developed for different phases in the life of a building, i.e., extraction and manufacturing of materials, construction, operation, hazards, demolition, and recycling. Models forecast direct costs, environmental impact costs, and human health costs related to each such phase. The variability in the parameters that enter the cost models is addressed using random variables. The estimate of the total cost of a building can be used in future work to optimize the structural design.Despite powerful new optimization algorithms, the answer to what is holistically the optimal choice of materials, dimensions, and configurations is often unanswered in practice. One reason is that developers, architects, users, and societies may have different objectives, ranging from the cost of construction to aesthetic appeal and environmental impact. Another problem is the lack of unbiased models to predict the costs and benefits that matter to private and public stakeholders. Thus, concerns such as environmental impacts and cost of potential earthquakes are rarely quantified in an explicit and comprehensive manner. This issue is addressed in this thesis through the development of a collection of unified probabilistic cost models for a broad range of costs and benefits. The models proposed in this thesis are implemented in a computer program for simulation of building behaviour.
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Disasters can, and do lead to widespread disruption, often crippling transportation systems in complex ways. Transportation systems need to be designed not only to operate on an ordinary day; they need to be designed to respond to man-made and natural disasters. Proactive planning can allow transport to resume service, and deal with crises, as quickly as possible post-disaster. This thesis provides information to assist in the development of plans and protocols for emergency scenarios. Coastal communities throughout British Columbia (BC) are heavily dependent on maritime transportation for the supply of fuel, food, and other critical resources. Vancouver Island only has an estimated 3 days’ worth of food and fuel stored on the island. Without sufficient storage, or a means of producing these resources, coastal communities are highly vulnerable to maritime disruption. If transportation systems are disrupted for an extended period, communities can experience shortages to supply. This can lead to communities losing power, operations, and critical resources for survival. Through interviews and interactive workshops with industry stakeholders, this study brings forth issues and limitations within fuel transportation in BC. Current transportation systems are potentially ill equipped to deal with large-scale events with some response plans fragmented, and the decision-making infrastructure at times ad hoc. Improving a system’s preparedness through identification of hazards, and educating the industry could significantly aid the system’s response and revitalization post-disaster. Through review of current systems and plans, this thesis highlights persistent concerns within the system and begins to explore ways to improve the resilience of fuel distribution in BC. Through analyzing mitigation options, the validity of pro-active planning can be seen. The concerns and recommendations from this thesis could lay the foundation for building a more resilient system capable of executing effective emergency response.
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During an earthquake, shear walls can experience damage around corners of doors and windows due to development of stress concentration. Reinforcements provided to minimize this damage are designed for forces that develop at these corners known as transfer forces. In this thesis, the focus is on understanding the forces that develop around opening corners in cross laminated timber (CLT) shear walls and reinforcement requirements for the same.In the literature, four different analytical models are commonly considered to determine the transfer force for design of wood-frame shear walls. These models have been reviewed in this thesis. The Diekmann model is found to be the most suitable analytical model to determine the transfer force around a window-type opening.Numerical models are developed in ANSYS to analyse the forces around opening corners in CLT shear walls. CLT shear walls with cut-out openings are analysed using a three-dimensional brick element model and a frame model. These models highlight the increase in shear and torsion around opening corners due to stress concentration. The coupled-panel construction practice for CLT shear walls with openings is analysed using a continuum model calibrated to experimental data. The analysis shows the increase in strength and stiffness of walls, when tie-rods are used as reinforcement. Analysis results also indicate that the tie-rods should be designed to behave linearly for optimum performance of the wall.Finally, a linear regression model is developed to determine the stiffness of a simply-supported CLT shear wall with a window-type opening. This model provides insight into the effect of various geometrical and material parameters on the stiffness of the wall. The process of model development has been explained, which can be improved further to include the behaviour of anchors.
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Rts is a risk-based structural optimization, multi-platform computer program that incorporates uncertainty into structural analysis with the utilization of random variable parameters. The major contribution to this thesis is that Rts now has the capability to perform reliability-based design optimization using Finite Element Method (FEM) analytical sensitivities. Analytical gradients are exact, more efficient, and convergence is achieved more rapidly in gradient- based optimization methods when compared to finite difference sensitivity methods. For this thesis, I have derived and implemented both nodal and material analytical gradients throughout the Rts framework starting at the finite element level up through to the optimization level. The Reliability-Based Design Optimization (RBDO) model stream includes an FEM model, a COST model, a RISK model with built-in First-Order Reliability Model (FORM), and the orchestrating RBDO model. A program wide Direct Differentiation Method (DDM) framework was additionally established that provides efficient analytical gradient calculations throughout the model stream. The FEM elements implemented consist of the Bilinear-Mindlin four node and nine node plate elements. An academic COST model was created to showcase the multi-model capabilities of Rts and the ability to calculate DDM dependencies of downstream models. Additionally, a RISK model was implemented that incorporated a built-in FORM model with gradient-history capabilities and in-model DDM dependency calculations; the RISK measure used is the mean cost. The RBDO model was also built upon to include DDM capabilities and downstream model integration. Finally, two reliability-based design optimization examples were implemented using both nodal and material sensitivities. The thickness and width of a timber cantilever beam was optimized with respect to mean cost taking into account deflection damage and construction cost.
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Dynamic structural analysis in recent years has gained importance due to increasing need to design structures for seismic resistance and also meet different performance demands. Also, structures are becoming more complex and it is difficult to accurately simulate their dynamic behavior using static analyses. With the advent of better computational capacity, engineers have been adopting computer programs for design and analyses of buildings. Making use of the advancement in computation and the need for dynamic analyses, tools required for dynamic analyses are implemented in a software called Rts. Rts is the next version of Rt, a computer program for risk and reliability analysis. For dynamic analyses it is required to have a ground motion input which can either be selected from existing databases of ground motion records or be generated as synthetic ground motions. If using actual ground motions it is required to modify them so that they match the anticipated hazard level. To overcome the limitation of scarcity of ground motion records, synthetic ground motion models can be used. To accomplish this in Rts, a synthetic ground motion model is implemented. The dynamic analysis algorithm and the ground motion models are implemented using object oriented programming. These implementations can be seen as a stepping stone to develop a computer program that would be robust and closely simulate the behavior of structures. It also forms the platform for future research for performance based earthquake engineering design and reliability analysis.
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The risk posed to a structure from an earthquake may be minimized by changing the design characteristics of the structure to determine the optimal design. A risk measure, the mean value of the cost functions in this thesis, can be determined using reliability methods to construct a loss curve. This formulation includes the effect of uncertainty in all aspects of the cost, including construction and repair given an event. This risk model also requires no prior information to determine the mean cost and does not define a discrete “failure,” instead using a continuum of possible outcomes in determining the mean of the cost functions. The optimization model allows for different search directions and step sizes in the search for the minimum cost, with steepest descent and BFGS search directions currently implemented. These analyses are performed using the Rts software, which has the capability of performing the optimization, risk, and reliability analyses on input structural models.The functionality of risk minimization is demonstrated with two example structures, with the framework provided for a third. The first is an example previously solved in Rt, which confirms functionality of the implementations in Rts. The second model uses an analytical model of a single-storey timber-steel hybrid frame, which utilizes the novel structural “Finding the Forest Through the Trees” (FFTT) design concept that has been proposed in Vancouver and studied at UBC. The minimum mean cost of this structure, subject to the cost functions and structural simplification, was determined by optimizing two decision variables that represent the fundamental geometry of the frame. Optimization of this frame converged to one point throughout many analyses, utilizing both the steepest descent and BFGS search methods. Finally, the framework for a future 6-storey FFTT example was developed. This example is inspired from modern tall timber design concepts, which are discussed in a literature review and demonstrates unique features within Rts, including the deep parameterization and nested model structure.
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This thesis presents an investigation of the in-plane stiffness of wood-frame diaphragms. Studying the stiffness of the diaphragm is important since it affects the distribution of lateral loads to shear walls. In order to determine the force in each shear wall, it is common to classify a diaphragm as either flexible in engineering design. Wood-frame diaphragms have generally been treated as flexible, which distributes the lateral loads using the straightforward “tributary area” approach. The accuracy of this assumption is investigated in this study. A detailed numerical model is developed for the study of the in-plane behaviour of wood-frame diaphragms. The model is validated with full-scale diaphragm tests, which has not been done so far for other diaphragm models in previous studies. As such, the model can be used as a “virtual laboratory” to predict the in-plane behaviour of wood-frame diaphragms with various configurations. A simplified model is developed based on the detailed diaphragm model to be used in the building analysis. The simplified model consists of “truss units”, which can be calibrated using analytical methods. In previous studies, wood-frame diaphragms were generally simplified as beam or spring models, where individual calibration is required for diaphragms with various configurations. Compared with these models, the simplified model developed here is obtained as an assembly of truss units, thus the number of calibration times can be considerably reduced. A case study of a one-storey wood-frame building is conducted to investigate the distribution of lateral loads to shear walls under different diaphragm flexibility conditions. It is found that the wood-frame diaphragm in this work is rather rigid, but is found that the distribution of lateral loads to the shear walls is strongly dependent on the relative stiffness of the diaphragm and the shear walls.
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This study investigates the in-plane stiffness of CLT floor diaphragms and addresses the lateral load distribution within buildings containing CLT floors. In practice, it is common to assume the floor diaphragm as either flexible or rigid, and distribute the lateral load according to simple hand calculations methods. Here, the applicability of theses assumption to CLT floor diaphragms is investigated. There is limited number of studies on the subject of in-plane behaviour of CLT diaphragms in the literature. Many of these studies involve testing of the panels or the connections utilized in CLT diaphragms. This study employs numerical modeling as a tool to address the in-plane behaviour of CLT diaphragms. The approach taken to develop the numerical models in this thesis has not been applied so far to CLT floor diaphragms. Detailed 2D finite element models of selective CLT floor diaphragm configurations are generated and analysed in ANSYS. The models contain a smeared panel-to-panel connection model, which is calibrated with test data of a special type of CLT connection with self-tapping wood screws. The floor models are then extended to building models by adding shearwalls, and the lateral load distribution is studied for each building model. A design flowchart is also developed to aid engineers in finding the lateral load distribution for any type of building in a systematic approach. By a parametric study, the most influential parameters affecting the in-plane behaviour of CLT floor diaphragm and the lateral load distribution are identified. The main parameters include the response of the CLT panel-to-panel connections, the in-plane shear modulus of CLT panels, the stiffness of shearwalls, and the floor diaphragm configuration. It was found that the applicability of flexible or rigid diaphragm assumptions is primarily dependent on the relative stiffness of the CLT floor diaphragm and the shearwalls.
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To acknowledge and account for the uncertainties present in civil engineering applications is an area of major importance and of continuing research interest. This Thesis focuses on an application of Bayes' inference rule to evaluate the probability of damage in structures, using measured modal parameters and a set of possible damage states. The hypothesis is that observed changes in dynamic characteristics are due to damage accumulation over time. The main objective is to identify the most likely damage scenario from a set of previously defined damage states. These are characterized in terms of vectors, θi, the components of which are the parameters, θij, that are associated with the stiffness contribution, Kj, from each substructure undergoing damage. These stiffness matrices are uncertain as a result of random geometric and material properties. For different combinations of the damage parameters and realizations of the random variables, the modal parameters are calculated solving the basic eigenvalue problem. The results are used to calculate the statistics of the parameters given a specific damage state, the likelihood functions, as these are needed to calculate the probability of a given a set of measurements given a damage state. Each damage state Di is associated with a prior probability P(Di). In order to calculate its posterior probability, given a set of measurements, a Bayesian updating is implemented, in which the prior probability is updated by means of the likelihood functions, f(r|Di), which represent the probability density function of the modal parameter, r, given the damage state, Di. This Thesis discusses the effectiveness of the approach in identifying a particular damage state referred to as damage scenario. It is shown that measurement of multiple modal parameters is required to identify, quickly and with confidence, a given damage state. The discussion also considers the effect of error in the measurements, and the number of repeated measurements that are required to achieve a substantial confidence as to the presence of a particular damage state. Ranking of the estimated probabilities, after a set of measurements, offers guidance to the engineer as when and where to conduct a direct inspection of the structure.
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The context of this thesis is performance-based engineering, in which the prediction of damage is a central theme. In contrast with traditional structural engineering, which focuses on forces and displacements, performance-based engineering entails the consideration of seismic consequences in terms of direct and indirect cost of damage to structures. To account for unavoidable uncertainties in such predictions, a probabilistic approach is adopted in this thesis. Specifically, a methodology is proposed that is based on reliability analysis in conjunction with probabilistic models. The phrase “unified reliability analysis” is employed to describe the approach. Although the framework of models generally includes hazard, structure, and consequence models, it is the damage models that are of particular concern in this thesis. In a novel approach, the visual damage at the structural component level is predicted. Importantly, such models predict “physical quantities” of damage. This is done because it is recognized that repair action selection is the central link between the predicted damage and its associated direct and indirect costs. Hence, in order to predict the repair cost and time associated with seismic events, this study puts forward damage models that are directly utilized to predict the repair action. In turn, this leads to probabilistic estimates of seismic loss by summing contributions from the components in the structure. The probabilistic model development follows a Bayesian framework. This approach builds on linear regression theory and explicitly accounts for uncertainties. Specifically, the coefficients in the linear regression models are random variables. The probabilistic models developed in this thesis facilitate the unified reliability analysis that ultimately determines final loss probabilities. This thesis describes the overall methodology, which is generic and applicable to a wide range of structural components, and applies it to reinforced concrete components. This specific application includes the development of a probabilistic model of crack length in reinforced concrete shear walls.
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There is increased awareness and concern regarding human activities with high environmental impacts caused by the construction, operation, maintenance and decommissioning of the built environment. The work presented in this thesis helps predict holistically the environmental impact indicators of different building design options. A probabilistic framework, applicable to multiple building function types, is proposed to estimate the environmental metrics of energy, water and global warming potential. The environmental impact indicators are studied at varying resolutions of data quality. The proposed framework differs from alternate tools by explicitly accounting for uncertainty through the use of random variables in its models. The modeling approach emphasizes greater transparency of the environmental impact intensity values that relate known information about the building, such as material quantities, with respective environmental impacts. Explicit environmental impact models are presented for each of the building’s life cycle phases, including extraction, manufacture, on-site construction, operation, maintenance, and end of life. The methodology is then demonstrated by analyzing a sample residence in Ontario. The environmental impacts associated with the entire life cycle of the building are reported and possible improvements to the methodology are identified. The ability to analyze the probability of exceeding an environmental impact threshold is a feature of this work that is useful in the refinement of environmental performance rating systems. The general lack of public information about the environmental impact of the manufacturing of building components in North America, as well as uncertainty about component replacement frequency and the building service life continue to pose a challenge for environmental impact analysis. However, this thesis presents a new probabilistic framework in which this uncertainty is explicitly identified and addressed.
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