Terje Haukaas

Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion

In this paper, probabilistic drift and shear force capacity models are developed for corroding reinforced concrete (RC) columns. The developments represent a merger between a probabilistic model for chloride-induced corrosion, a time-dependent corrosion rate, and previously developed probabilistic models for drift and shear force capacity of pristine (undamaged) RC columns. Fragility estimates are obtained for an example corroding column by applying the developed models at given shear and drift demands. Model uncertainties in both the capacity and corrosion models are considered in the fragility estimation, in addition to uncertainties in environmental conditions, material properties, and structural geometry. Sensitivity analyses of the corroding RC column are carried out to identify the parameters to which the reliability of the example column is most sensitive. The developed models consider different combinations of chloride exposure condition, environmental oxygen availability, water-to-cement ratios, and curing conditions. They are applicable to both existing and new RC columns and may be employed for the prediction of service-life and life-cycle cost analysis of RC structures.

Reliability-based optimal design of electrical transmission towers using multi-objective genetic algorithms

A hybrid methodology for performing reliability-based structural optimization of three-dimensional trusses is presented. This hybrid methodology links the search and optimization capabilities of multi-objective genetic algorithms (MOGA) with structural performance information provided by finite element reliability analysis. To highlight the strengths of the proposed methodology, a practical example is presented that concerns optimizing the topology, geometry, and member sizes of electrical transmission towers. The weight and reliability index of a tower are defined as the two objectives used by MOGA to perform Pareto ranking of tower designs. The truss deformation and the member stresses are compared to threshold values to assess the reliability of each tower under wind loading. Importance sampling is used for the reliability analysis. Both the wind pressure and the wind direction are considered as random variables in the analysis. The research results presented demonstrate the benefit of implementing MOGA optimization as an integral part of a reliability-based optimization procedure for three-dimensional trusses.

Computer Program for Multimodel Reliability and Optimization Analysis

AbstractA computer program is developed to carry out reliability and optimization analysis with many interconnected probabilistic models. The program is freely available online and it contains a library of versatile models. The user can also implement new models—without any recompilation of the program—by several means, including a powerful scripting option. Other novel features include a comprehensive parameterization that facilitates flexible and effective model communication and the computation of direct-differentiation response sensitivities in multimodel analysis. The new program has already been successfully employed for regional risk analysis with thousands of model objects and hundreds of random variables. This paper presents the software architecture and a multimodel example of a structure that is modeled in an external finite-element program and subjected to multiple hazards, damage, and long-term deterioration.

Optimal inspection planning for onshore pipelines subject to external corrosion

Continuous operation of pipeline systems involves significant expenditures in inspection and maintenance activities. The cost-effective safety management of such systems involves allocating the optimal amount of resources to inspection and maintenance activities, in order to control risks (expected costs of failure). In this context, this article addresses the optimal inspection planning for onshore pipelines subject to external corrosion. The investigation addresses a challenging problem of practical relevance, and strives for using the best available models to describe random corrosion growth and the relevant limit state functions. A single pipeline segment is considered in this paper. Expected numbers of failures and repairs are evaluated by Monte Carlo sampling, and a novel procedure is employed to evaluate sensitivities of the objective function with respect to design parameters. This procedure is shown to be accurate and more efficient than finite differences. The optimum inspection interval is found for an example problem, and the robustness of this optimum to the assumed inspection and failure costs is investigated. It is shown that optimum total expected costs found herein are not highly sensitive to the assumed costs of inspection and failure.

Model Uncertainty in Finite-Element Analysis: Bayesian Finite Elements

In this paper, probabilistic models for structural analysis are put forward, with particular emphasis on model uncertainty. Context is provided by the finite-element method and the need for probabilistic prediction of structural performance in contemporary engineering. Sources of model uncertainty are identified and modeled. A Bayesian approach is suggested for the assessment of new model parameters within the element formulations. The expressions are formulated by means of numerical “sensors” that influence the model uncertainty, such as element distortion and degree of nonlinearity. An assessment procedure is proposed to identify the sensors that are most suitable to capture model uncertainty. This paper presents the general methodology and specific implementations for a general-purpose structural element. Two numerical examples are presented to demonstrate the methodology and its implications for probabilistic prediction of structural response.

Probabilistic Seismic Loss Assessment of a Vancouver High-Rise Building

A seismic loss curve of a real-world building is obtained by means of state-of-the-art models for the impending ground motion, the structure, the damage of structural and nonstructural components, and the ensuing losses. In particular, the seismic hazard at the building’s location (Vancouver, Canada) is described by a comprehensive probabilistic model. It is argued that this ground motion model is particularly appropriate in reliability analysis compared with the more common utilization of a limited set of scaled ground motions. In this paper the probabilistic integrals are carried out by means of a reliability formulation, in which a series of probabilistic models enter. This is referred to as unified reliability analysis to contrast the unified format of the probabilistic models with alternatives, such as suites of ground motions and fragility curves that themselves are created by reliability analysis. A key contribution in this paper is the comprehensive numerical example, which entails an inelastic dy...

Sensitivity measures for optimal mitigation of risk and reduction of model uncertainty

This paper presents a new set of reliability sensitivity measures. The purpose is to identify the optimal manner in which to mitigate risk to civil infrastructure, and reduce model uncertainty in order to improve risk estimates. Three measures are presented. One identifies the infrastructure components that should be prioritized for retrofit. Another measure identifies the infrastructure that should be prioritized for more refined modeling. The third measure identifies the models that should be prioritized in research to improve models, for example by gathering new data. The developments are presented in the context of a region with 622 buildings that are subjected to seismicity from several sources. A comprehensive seismic risk analysis of this region is conducted, with over 300 random variables, 30 model types, and 4000 model instances. All models are probabilistic and emphasis is placed on the explicit characterization of epistemic uncertainty. For the considered region, the buildings that should first be retrofitted are found to be pre-code unreinforced masonry buildings. Conversely, concrete shear wall buildings rank highest on the list of buildings that should be subjected to more detailed modeling. The ground shaking intensity model for shallow crustal earthquakes and the concrete shear wall structural response model rank highest on the list of models that should be prioritized by research to improve engineering analysis models.

Probabilistic Models for Structural Performance of Rounded Dovetail Joints

AbstractThis paper presents probabilistic models for the structural performance of rounded dovetail joints. The models are developed with a Bayesian technique, which implies that the model uncertainty is explicitly characterized by random variables. The Bayesian approach also promotes model updating when new test results become available in the future. Practical insight is gained from the modeling process, which includes a novel search for influential parameters, and from the subsequent probabilistic analysis with the models. The models are based on 80 tests of single and double dovetail joints with varying geometric parameters, specifically the flange angle and the dovetail height. A significant effort was made to record variables that conceivably influence the performance of this type of joint, including a series of material parameters: tension strength perpendicular to grain, shear strength parallel to grain, moisture content, density, growth ring density, and growth ring orientation. This paper explor...

Application of Response Sensitivity in Composite Processing

This article demonstrates the use of response sensitivities in numerical simulation of composite processing via four different application examples: real-time result validation, model calibration, reliability analysis, and optimization. The analyses are carried out with integrated simulation software with new response sensitivity capabilities. Notably, the response sensitivities are computed by the direct differentiation method. This is an efficient and accurate alternative to the finite difference approaches. A brief review of the derivation and implementation of sensitivity equations is provided. The primary objective of this article is to demonstrate and promote a suite of techniques to incorporate uncertainties into the simulation of the composite manufacturing process, facilitated by efficient sensitivity computations.

Hybrid Simulation of the Gravity Load Collapse of Reinforced Concrete Frames

A hybrid simulation test setup is developed to investigate and validate the application of hybrid simulation to the gravity load collapse of reinforced concrete frames. The OpenFresco software framework for hybrid simulation is used in combination with an event-driven real-time predictor/corrector ensuring continuous hybrid testing. A shear-critical reinforced concrete column loaded through three dynamic actuators constitutes the physical substructure while a nonlinear ductile reinforced concrete frame makes up the numerical substructure within the OpenSees environment. This paper presents a nonlinear transformation method designed to allow for an accurate application of the loading on the specimen, and an iterative algorithm with mode-switch to enable the use of force control for the actuators in combination with the displacement-based software, OpenSees. Validation of this hybrid simulation setup will be achieved through a comparison with a shaking table test of the same reinforced concrete frame.