Structural optimization in steel structures, algorithms and applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Evaluation of NSP and MPA Methods to Optimize Special Truss Moment Frames (STMF) Using Island Genetic Algorithm

The purpose of the present study is to evaluate the Pushover (NSP) and Modal Pushover (MPA) analysis methods in optimizing Special Truss Moment Frames (STMF) using island genetic algorithm. For this purpose, the optimization program is written and developed in Matlab software, and OpenSees software is used for structural analysis. The design variables of truss arrangement, cross section of members, truss height values and length of special zone of truss moment frame are considered. The constraints of the optimization problem are based on the rules and restrictions of AISC341-16. Case studies were performed on five frames of 3, 6, 9, 12 and 15 stories with a story height of 3 meters and span length of 18 meters with the aim of minimizing weight and maximizing the response modification factor. The results of these analyses are compared with nonlinear dynamic time history analyses as the most accurate method available, which could be used to finally identify and introduce the most efficient method in these structures. The MPA method was able to show better performance than the NSP method in estimating the maximum response of the structure. Despite the excellent performance of this method, Evaluation of numerical results of this study indicates the non-economic nature of MPA method for low-rise structures, and the acceptable efficiency of this method for medium-height to high-rise structures

Clustering Elements of Truss Structures for Damage Identification by CBO

The number of structural elements plays a significant role in detecting damage location and severity; such methods have sometimes failed to provide correct solutions due to the entrapment of damage detection algorithms in the local optimum. To resolve this problem, this study proposed the simultaneous use of mathematical and statistical methods to narrow down the search space. To this end, a two-step damage detection method was proposed. In the first step, the structural elements were initially divided into different clusters using the k-means method. Subsequently, the possibly damaged elements of each cluster were identified. In the second step, the elements selected in the first step were placed in a new set, and a process was applied to identify their respective damage location and severity. Thus, the proposed method reduced the search space as well as the possibility of entrapment in the local optimum. Other advantages of the proposed method include the use of fewer dynamic properties. Accordingly, by narrowing down the search space and the dimensions of the system for governing equations, the proposed method could significantly increase the chance of obtaining favorable results in structures with many elements and those with few vibration modes. A meta-heuristic method, called the colliding bodies optimization (CBO), was used in the proposed damage detection optimization algorithm. The optimization problem was based on the modal strain energy equations. According to the results, the proposed method was able to detect the location and severity of damage, even at its slightest percentage

Damage identification in bridge structures : review of available methods and case studies

Bridges are integral parts of the infrastructure and play a major role in civil engineering. Bridge health monitoring is necessary to extend the life of a bridge and retain safety. Periodic monitoring contributes significantly in keeping these structures operational and extends structural integrity. Different researchers have proposed different methods for identifying bridge damages based on different theories and laboratory tests. Several review papers have been published in the literature on the identification of damage and crack in bridge structures in the last few decades. In this paper, a review of literature on damage identification in bridge structures based on different methods and theories is carried out. The aim of this paper is to critically evaluate different methods that have been proposed to detect damages in different bridges. Different papers have been carefully reviewed, and the gaps, limitations, and superiority of the methods used are identified. Furthermore, in most of the reviews, future applications and several sustainable methods which are necessary for bridge monitoring are covered. This study significantly contributes to the literature by critically examining different methods, giving guidelines on the methods that identify the damages in bridge structures more accurately, and serving as a good reference for other researchers and future works

Structural Health Monitoring and Application of Wireless Sensor Networks

Different elements of structural health monitoring (SHM) can benefit from the application of wireless sensor Networks (WSNs), as advanced sensing systems. While WSNs can significantly enhance the SHM by facilitating deployment of scalable and dense monitoring systems, challenges in the power consumption and data communication, and concerns regarding the possible impacts of their associated quality on the results have restricted their broad application. This research contributes in addressing the limitation associated with the prohibitive data communication delay and power consumption by introducing a novel time- and energy-efficient distributed algorithm for modal identification, and also addressing the concerns regarding the possible effects of their sensing quality by development of quality assessment approaches for modal identification and damage detection practices. The onboard processing techniques attempt to reduce the communication and power consumption by pushing the computation into the network. Efforts in developing onboard processing algorithms are restricted by the topology and algorithms, and their efficiency is not high enough to alleviate the challenge. A novel approach for modal identification of structural systems in a distributed scheme is developed which assigns the entire computational task of modal identification to remote nodes and limits the communication to transmission of only system\u27s parameters. The algorithm is based on estimation-updating steps at remote nodes and iterations by passing the results through the network for convergence of estimation. The algorithm is first developed for input-output scenarios and then is further expanded to address output-only systems as well. Development of approaches such as Cumulative System Formation for providing initial estimates of the system (as starting point of iteration) and also a novel AR-ARX approach for expediting the convergence also further enhanced the developed algorithm. Experiments and implementations have proved the functionality and performance of the algorithm. While the focus of the research is on development of algorithms for enhancing the application of wireless sensors in modal identification, other aspects of data-driven SHM such as damage detection, and performance evaluation through field-testing of real-life structures are also studied. A framework for damage detection algorithm including accuracy indicators and statistical approaches for change point detection is developed and validated through implementation on different experimental models. Moreover, the state of the art in structural monitoring and vibration evaluation is presented in two field deployments

Active thermography for the investigation of corrosion in steel surfaces

The present work aims at developing an experimental methodology for the analysis of corrosion phenomena of steel surfaces by means of Active Thermography (AT), in reflexion configuration (RC). The peculiarity of this AT approach consists in exciting by means of a laser source the sound surface of the specimens and acquiring the thermal signal on the same surface, instead of the corroded one: the thermal signal is then composed by the reflection of the thermal wave reflected by the corroded surface. This procedure aims at investigating internal corroded surfaces like in vessels, piping, carters etc. Thermal tests were performed in Step Heating and Lock-In conditions, by varying excitation parameters (power, time, number of pulse, ….) to improve the experimental set up. Surface thermal profiles were acquired by an IR thermocamera and means of salt spray testing; at set time intervals the specimens were investigated by means of AT. Each duration corresponded to a surface damage entity and to a variation in the thermal response. Thermal responses of corroded specimens were related to the corresponding corrosion level, referring to a reference specimen without corrosion. The entity of corrosion was also verified by a metallographic optical microscope to measure the thickness variation of the specimens

Model Validation and Simulation

The Bauhaus Summer School series provides an international forum for an exchange of methods and skills related to the interaction between different disciplines of modern engineering science. The 2012 civil engineering course was held in August over two weeks at Bauhaus-Universität Weimar. The overall aim was the exchange of research and modern scientific approaches in the field of model validation and simulation between well-known experts acting as lecturers and active students. Besides these educational intentions the social and cultural component of the meeting has been in the focus. 48 graduate and doctoral students from 20 different countries and 22 lecturers from 12 countries attended this summer school. Among other aspects, this activity can be considered successful as it raised the sensitivity towards both the significance of research in civil engineering and the role of intercultural exchange. This volume summarizes and publishes some of the results: abstracts of key note papers presented by the experts and selected student research works. The overview reflects the quality of this summer school. Furthermore the individual contributions confirm that for active students this event has been a research forum and a special opportunity to learn from the experiences of the researchers in terms of methodology and strategies for research implementation in their current work

Seismic retrofitting of substandard frame buildings using steel shear walls

The use of steel shear panels represents an effective strategy to enhance the seismic performance of substandard framed buildings not designed to resist earthquakes. The seismic response of framed structures equipped with steel walls can be predicted using finite element models with accurate shell elements for representing the steel panels. However, such a detailed numerical description requires significant computational resources, especially for nonlinear dynamic analysis of large retrofitted buildings with steel infill plates. Besides, the design of steel shear walls for seismic retrofitting has been addressed mainly by trial-and-error methods in previous research and practical applications. Therefore, there is a clear need for more simplified and efficient numerical models for accurate simulations of steel shear walls under earthquake loading and enhanced seismic retrofitting design procedures with automatic selection of the retrofitting components. In this research, an 8-noded macroelement formulation is first proposed incorporating six nonlinear springs with asymmetric constitutive relationships. To improve the macroelement performance, material parameters are calibrated via genetic algorithms (GAs) based on the numerical results from validated shell element models. Subsequently, simple functions for macroelement material parameters in terms of steel plate geometrical properties are determined using multiple linear regressions. Applications to numerical examples have confirmed the accuracy and computational efficiency of the proposed macroelement with calibrated material properties. An improved optimal seismic retrofitting design procedure utilising steel shear wall macroelements is developed based on the capacity spectrum method. The proposed approach regards the selection and design of infill plates as a multi-objective optimisation problem with constraints solved by GA procedures. Nonlinear regression for equivalent viscous damping of steel shear walls is also carried out to determine the hysteretic damping ratio as a function of plate dimensions and drift demand. Afterwards, the proposed optimal design strategy is applied to the seismic retrofitting of a deficient 4-storey RC frame building. Seismic assessment is finally conducted for the retrofitted structure, where a significant enhancement of the seismic performance is observed.Open Acces