Artificial Intelligence in Civil Engineering

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering

Conceptualizing the concept of disaster resilience: a hybrid approach in the context of earthquake hazard : case study of Tehran City, Iran

From the natural perspective, disaster resilience is defined as the ability of a system or community to resist, mitigate, respond, and recover from the effects of hazards in efficient and timely manner. How urban communities recover subsequent a disaster event is often conceptualized in terms of their disaster resilience level. While numerous studies have been carried out on the importance of disaster resilience measurement, a few of them suggest how and by which mechanism the concept can be quantified. Thus, the primary purpose of this thesis is to advance our understanding of the multifaceted nature of disaster resilience and answer to the general question of how the concept of disaster resilience can be operationalized in the context of earthquake hazard. The starting point for conceptualizing the concept of disaster resilience is performed through the development of measurement and benchmarking tools for better understanding of factors that contribute to resilience and the effectiveness of interventions to sustain it. Since constructing composite indicators has often been addressed to perform this task in literature, this research has proposed the new hybrid approach to develop a sound set of composite indicators in the context of earthquake hazard. The methodology has specially scrutinized data reduction and factor retention, and indicators weighting steps using a hybrid factor analysis and analytic network process (F’ANP). It replaces the hierarchical and deductive methods in the literature with an inductive method of factor analysis. The methodology also applies an unequal weighting method instead of an equal weighting in which the inter-dependencies and feedbacks among all indicators are considered. The 368 urban neighborhoods (within 22 urban regions and 116 sub-regions) of Tehran City were utilized as a case study and validation tool for developing a new set of composite indicators in this dissertation. The ability to measure disaster resilience and the issue of resilience building is important for a community such as Tehran in view of the fact that the urban areas within the city tend to be inherently vulnerable, partially because of the high population and building density, and partially due to their exposure to earthquake hazard. Visualization of the results (using Arc-GIS) provided a better understanding of resilience and its variation level at the scale of urban regions, sub-regions and urban neighborhoods. The results showed that the northern areas are relatively more disaster resilient while the regions located in the south or center of the city reflect lower level of disaster resilience. The reliability and validity of the proposed approach were assessed through comparing its results with the results of DROP and JICA studies using a scatter plot and Pearson’s correlation coefficient. The findings indicated that there is a strong positive relationship between the results of this study and the results of other two models.Wie sich Städte entwickeln, nachdem sie von einer Naturkatastrophe getroffen wurden ist abhängig von ihrem Grad der Resilienz gegenüber Katastrophen. Resilienz gegenüber Naturkatastrophen aber keine fest definierte Größe sondern fasst eine Reihe von Eigenschaften eines System, in dieser Arbeit einer Stadt zusammen, die negative Folgen solcher Ereignisse reduzieren und sich von dem Ereignis wieder zu erholen. Die Fähigkeit außer den Risiken und der Vulnerabilität auch die Resilienz von Städten zu messen, wird zunehmend als ein grundlegendes Ziel der Risikominderung und des Risikomanagements betrachtet. Zahlreiche Studien beschreiben das Konzept der Resilienz und heben die Bedeutung für die urbane Entwicklung heraus. Es wurden jedoch nur in wenigen Arbeiten tragfähige Ansätze entwickelt, wie und mit welcher Methodik die Resilienz gegenüber Katastrophen gemessen werden können. Das primäre Ziel dieser Dissertation ist, unser Verständnis der Resilienz zu erweitern und eine Operationalisierung des Begriffs zu entwickeln. Der Fokus der Arbeit ist dabei auf die Anwendung des Konzeptes der Resilienz im Zusammenhang mit Erdbebenrisiken gerichtet. Ausgehend von der Idee der Resilienzmessung über einen kompositen Index wird in dieser Arbeit ein neues Indikatorenset aufgebaut, welches die Resilienz gegenüber Erdbebenrisiken effektiv messen kann. Die Vorgehensweise, mit der die Relevanz der Indikatoren und Ihre Reliabilität innerhalb eines kompositen Index sichergestellt wird, ist entscheidend für die Güte des Messverfahrens. Die vorgeschlagene Methodik ermöglicht eine Reduktion der Indikatoren und deren Gewichtung unter Verwendung einer hybriden Faktoren-Analyse und des Analytischen Netzwerkprozesses (F'ANP). Dies ersetzt die aus der Literatur bekannte hierarchisch-deduktive Methode durch eine induktive Methode der Faktorenanalyse. Die Methodik verwendet an Stelle einer Gleichgewichtung der Indikatoren eine ungleiche Gewichtung, in dem die Wechselbeziehungen und das Feedback zwischen allen Indikatoren berücksichtigt werden. Anhand der Fallstudie Teheran wird der Ansatz validiert und der neu entwickelte Satz von Sammelindikatoren für 368 Wohnviertel in 22 städtischen Regionen im Stadtgebiet von Teheran angewendet. Die Möglichkeit der Beurteilung der Resilienz einer Stadt ist insbesondere für Teheran in Anbetracht der hohen Erdbebenrisikos, der hohen Bevölkerungs- und Bebauungsdichte von hoher Bedeutung. Die Ergebnisse werden mit Arc-GIS visualisiert und liefern ein besseres Verständnis der Resilienz und der Variationen innerhalb der Stadt. Die Ergebnisse zeigen, dass die nördlichen Regionen verhältnismäßig resilient gegenüber Erdbeben sind. Die Regionen im Süden und im Zentrum der Stadt weisen hingegen eine geringe Resilienz gegenüber Erdbeben auf. Die Zuverlässigkeit und die Validität des vorgeschlagenen Ansatzes wurden durch einen Vergleich mit den Ergebnissen bereits vorliegender Studien (DROP, JICA) beurteilt. Die Ergebnisse zeigen, dass es eine starke positive Korrelation zwischen des neu entwickelten Ansatzes und den vorliegenden Ansätzen gibt

Optimal sliding friction coefficients for isolated viaducts and bridges: A comparison study

The aim of this work is to evaluate the influence of the pier–abutment–deck interaction on the seismic response of bridges isolated by single concave sliding pendulum isolators (friction pendulum system [FPS]) through a comparison with the results of the seismic response of isolated bridges without considering the presence of the rigid abutment (i.e., isolated viaducts). Two different multidegree-of-freedom (mdof) models are properly defined to carry out this comparison. In the both mdof models, five vibrational modes are considered to describe the elastic behavior of the reinforced concrete pier, and an additional degree of freedom is adopted to analyze the response of the infinitely rigid deck isolated by the seismic devices. The FPS isolator behavior is described through a widespread velocity-dependent model. By means of a nondimensional formulation of the motion equations with respect to the seismic intensity, a parametric analysis for several structural properties is performed in order to investigate the differences between the two mdof models in relation to the relevant response parameters. The uncertainty in the seismic input is taken into account by means of a set of natural records with different characteristics. Finally, multivariate nonlinear regression relationships are provided to estimate the optimum values of the sliding friction coefficient able to minimize the pier displacements relative to the ground as a function of the structural properties considering or neglecting the presence of the abutment

Optimal sliding friction coefficient for isolated bridges in different soil conditions

The work evaluates the optimal properties of friction pendulum system (FPS) bearings for the seismic protection of bridge piers under earthquake excitations having different frequency characteristics representative of different soil conditions in order to reduce the seismic vulne-rability of infrastructures. A two-degree-of-freedom model is adopted to describe, respective-ly, the response of the infinitely rigid deck isolated by the FPS devices and the elastic behavior of the pier. By means of a non-dimensional formulation of the motion equations, a wide parametric analysis for several structural parameters is carried out. Seismic excitations, modelled as time-modulated filtered Gaussian white noise random processes having different intensities and frequency contents, are considered. Specifically, the filter parameters, which control the frequency contents, are properly calibrated to reproduce stiff, medium and soft soil conditions, respectively. Finally, the optimum values of the sliding friction coefficient able to minimize the pier displacements with respect to the ground are derived as a function of the structural properties, of the seismic input intensity and of the soil condition

Beurteilung der Resttragfähigkeit von Bauwerken mit Hilfe der Fuzzy-Logik und Entscheidungstheorie

Whereas the design of new structures is almost completely regulated by codes, there are no objective ways for the evaluation of existing facilities. Experts often are not familiar with the new tasks in system identification and try to retrieve at least some information from available documents. They therefore make compromises which, for many stakeholders, are not satisfying. Consequently, this publication presents a more objective and more realistic method for condition assessment. Necessary basics for this task are fracture mechanics combined with computational analysis, methods and techniques for geometry recording and material investigation, ductility and energy dissipation, risk analysis and uncertainty consideration. Present tools for evaluation perform research on how to analytically conceptualize a structure directly from given loads and measured response. Since defects are not necessarily visible or in a direct way detectable, several damage indices are combined and integrated in a model of the real system. Fuzzy-sets are ideally suited to illustrate parametric/data uncertainty and system- or model uncertainty. Trapezoidal membership functions may very well represent the condition state of structural components as function of damage extent or performance. Tthe residual load-bearing capacity can be determined by successively performing analyses in three steps. The "Screening assessment" shall eliminate a large majority of structures from detailed consideration and advise on immediate precautions to save lives and high economic values. Here, the defects have to be explicitly defined and located. If this is impossible, an "approximate evaluation" should follow describing system geometry, material properties and failure modes in detail. Here, a fault-tree helps investigate defaults in a systematic way avoiding random search or negligence of important features or damage indices. In order to inform about the structural system it is deemed essential not only due to its conceptual clarity, but also due to its applicational simplicity. It therefore represents an important prerequisite in condition assessment though special circumstances might require "fur-ther investigations" to consider the actual material parameters and unaccounted reserves due to spatial or other secondary contributions. Here, uncertainties with respect to geometry, material, loading or modeling should in no case be neglected, but explicitly quantified. Postulating a limited set of expected failure modes is not always sufficient, since detectable signature changes are seldom directly attributable and every defect might -together with other unforeseen situations- become decisive. So, a determination of all possible scenarios to consider every imaginable influence would be required. Risk is produced by a combination of various and ill-defined failure modes. Due to the interaction of many variables there is no simple and reliable way to predict which failure mode is dominant. Risk evaluation therefore comprises the estimation of the prognostic factor with respect to undesir-able events, component importance and the expected damage extent.Während die Bemessung von Tragwerken im allgemeinen durch Vorschriften geregelt ist, gibt es für die Zustandsbewertung bestehender Bauwerken noch keine objektiven Richtlinien. Viele Experten sind mit der neuen Problematik (Systemidentifikation anhand von Belastung und daraus entstehender Strukturantwort) noch nicht vertraut und begnügen sich daher mit Kompromißlösungen. Für viele Bauherren ist dies unbefriedigend, weshalb hier eine objektivere und wirklichkeitsnähere Zustandsbewertung vorgestellt wird. Wichtig hierfür sind theoretische Grundlagen der Schadensanalyse, Methoden und Techniken zur Geometrie- und Materialerkundung, Duktilität und Energieabsorption, Risikoanalyse und Beschreibung von Unsicherheiten. Da nicht alle Schäden offensichtlich sind, kombiniert man zur Zeit mehrere Zustandsindikatoren, bereitet die registrierten Daten gezielt auf, und integriert sie vor einer endgültigen Bewertung in ein validiertes Modell. Werden deterministische Nachweismethoden mit probabilstischen kombiniert, lassen sich nur zufällige Fehler problemlos minimieren. Systematische Fehler durch ungenaue Modellierung oder vagem Wissen bleiben jedoch bestehen. Daß Entscheidungsträger mit unsicheren, oft sogar widersprüchlichen Angaben subjektiv urteilen, ist also nicht zu vermeiden. In dieser Arbeit wird gezeigt, wie mit Hilfe eines dreistufigen Bewertungsverfahrens Tragglieder in Qualitätsklassen eingestuft werden können. Abhängig von ihrem mittleren Schadensausmaß, ihrer Strukturbedeutung I (wiederum von ihrem Stellenwert bzw. den Konsequenzen ihrer Schädigung abhängig) und ihrem Prognosefaktor L ergibt sich ihr Versagensrisiko mit. Das Risiko für eine Versagen der Gesamtstruktur wird aus der Topologie ermittelt. Wenn das mittlere Schadensausmaß nicht eindeutig festgelegt werden kann, oder wenn die Material-, Geometrie- oder Lastangaben vage sind, wird im Rahmen "Weitergehender Untersuchungen" ein mathematisches Verfahren basierend auf der Fuzzy-Logik vorgeschlagen. Es filtert auch bei komplexen Ursache-Wirkungsbeziehungen die dominierende Schadensursache heraus und vermeidet, daß mit Unsicherheiten behaftete Parameter für zuverlässige Absolutwerte gehalten werden. Um den mittleren Schadensindex und daraus das Risiko zu berechnen, werden die einzelnen Schadensindizes (je nach Fehlermodus) abhängig von ihrer Bedeutung mit Wichtungsfaktoren belegt,und zusätzlich je nach Art, Bedeutung und Zuverlässigkeit der erhaltenen Information durch Gamma dividiert. Hiermit wurde ein neues Verfahren zur Analyse komplexer Versagensmechanismen vorgestellt, welches nachvollziehbare Schlußfolgerungen ermöglicht

Modelling stakeholder perceptions to assess Green Infrastructures potential in agriculture through fuzzy logic: A tool for participatory governance

Abstract Solutions like Green Infrastructures can restore and maintain key regulative ecosystem services capable of mitigating disaster risk and contributing to climate change adaptation. Given the vulnerabilities that affect agriculture and its role in national economies, GI can play an important role in managing trade-offs between conflicting ecosystem services. However, their use is still lagging behind, and socio-economic dynamics in their uptake in the agricultural sector are partially disregarded. The uncertainty involved in the modelling of ecological processes can be reduced through the use of participatory processes and the involvement of relevant stakeholders to sustain decision-making processes. This article intends to assess stakeholders' perceptions on the implementation of Green Infrastructures in agriculture by capturing critical barriers and facilitators. The implementation of such Green Infrastructures policies is associated to different climate change trends in order to understand the effect of different scenarios on rural development. The study uses fuzzy logic to elicit the stakeholders' needs. The key results show that when there is uncertainty in the state of climate change trends, it is always more efficient to adopt progressive policies investing in the development and diffusion of Green Infrastructures

Towards a resilient community: A decision support framework for prioritizing stakeholders' interaction areas

Interactions among community stakeholders act as a buffer against disasters and present a way to build community resilience. Several decision support frameworks have been proposed in the literature to improve community resilience, but none focus on interactions among stakeholders. This paper presents a decision support framework to guide decision-makers in prioritizing areas of interaction based on their mutual impact. The framework is built on three components. The first involved conducting a literature review to identify areas of interaction among community stakeholders; resulting in identifying 27 factors that reflect the various interaction areas. The second was to implement a Delphi study to capture the dependency among the different areas. The third was to prioritize the identified areas of interaction through network analysis techniques to understand the propagating impacts of a change in one area on the others. The framework was applied to Spain, utilizing data provided by Spanish resilience experts. Our findings indicate a high degree of interdependence among all areas of interaction. Decentralization of the decision-making process and effective leading capabilities of emergency organizations have been identified as top priority areas. By utilizing this framework, decision-makers can systematically enhance interactions among diverse stakeholders, creating a roadmap to improve community resilience

Seismic Risk Management

Seismic risk management is a problem of many dimensions, involving multiple inputs, interactions within risk factors, criteria, alternatives and stakeholders. The deployment of this process is inherently fraught with the issues of complexity, ambiguity and uncertainty, posing extra challenges in the assessment, modelling and management stages. The complexity of earthquake impacts and the uncertain nature of information necessitate the establishment of a systematic approach to address the risk of many effects of seismic events in a reliable and realistic way. To fulfill this need, the study applies a systematic approach to the assessment and management of seismic risk and uses an integrated risk structure. The fuzzy set theory was used as a formal mathematical basis to handle uncertainties involved within risk parameters. Throughout the process, the potential impacts of an earthquake as the basic criteria for risk assessment were identified and relations between them were accommodated through a hierarchical structure. The various impacts of an earthquake are then aggregated through a composite fuzzy seismic risk index (FSRi) to screen and prioritize the retrofitting of a group of school buildings in Iran. Given the imprecise data which is the prime challenge for development of any risk model, the proposed model demonstrates a more reliable and robust methodology to handle vague and imprecise information. The significant feature of the model is its transparency and flexibility in aggregating, tracing and monitoring the risk impacts. The novelty of this study is that it serves as the first attempt of the process of a knowledge base risk-informed system for ranking and screening the retrofitting group of school buildings. The model is capable of integrating various forms of knowledge (quantitative and qualitative information) extracted from different sources (facts, algorithms, standards and experience). The outcomes of the research collectively demonstrate that the proposed system supports seismic risk management processes effectively and efficiently

Ecosystems And Engineering: A Working Synergy Towards City Resilience To Natural Disasters

Climate change, natural and human-induced risks always threat the precarious safety of contemporary societies. As a consequence, resilience represents a key issue for modern societies, as the capability to withstand and effectively recover from disasters. But resilience is also strictly related to sustainability. Any urban transformation has to ensure the safeguarding of communities’ assets and resources and human well-being, that is economic, environmental and social sustainability of the urban environment. The present PhD Thesis work has been developed to address issues related to resilience of urban systems to natural catastrophe risks. Resilience has been studied from multiple perspectives, trying to catch its high interdisciplinary nature. The most critical issues related to the quantification of resilience at the urban scale and to the development of mitigation instruments devoted at enhancing disaster resilience at the global scale are discussed and investigated. Primarily the origin of the concept of resilience are investigated, as well as the variability of its definition within various subject area, which resilience is applied in. A novel understanding of resilience is proposed, as the theoretical basis, which the thesis is based on. Resilience is defined as the engineering one in the sense of the ecosystems theory. In this view, it is the capability of a system to face an external stress and bounce back from it to an equilibrium condition, that can be the same but also different from the pre-event one. The deep link between resilience and sustainability is also highlight, according to a human-centric perspective. Resilience is, in fact, understood as one of the main factors contributing to sustainability. Accordingly, a city to be sustainable, has to be resilient too. Disaster resilience is first of all approached from a global, superurban perspective by developing methodologies for insurance-based products. Particularly, a methodology is presented for the modelling of an insurance model against seismic risk for private householders, which is based on the probabilistic assessment of seismic hazard. A real case study application is also developed for the Italian residential building stock. Expected seismic losses are evaluated for the entire national territory, being evaluated at the single municipality level. Seismic insurance premiums are also evaluated, according to the actual exposure and annual rate for each municipality, according to different models, considering diverse excess and maximum coverage levels. Furthermore, a performance-based earthquake engineering (PBEE) methodology is described for the development of curves enabling to forecast economic losses, given the magnitude of the expected seismic event. Curves are obtained through regression analysis, which are performed on scenario analysis’ results, based on seismic events collected in the Italian catalogue of historical earthquakes from the National Institute of Geophysics and Volcanology (INGV). According to a multi-scale approach, resilience is addressed from a global to a urban scale. A methodological framework for the quantification of urban resilience is then proposed. It shows the chance to model any urban environment as a hybrid social-physical network (HSPN) and to assess its performance level according to the complex network theory. The human component of the modelled HSPN is then further considered through the integration of social indicators, enabling to evaluate the life quality level and the happiness of citizens. Finally an integrated framework is described, which methodologies can be integrated in, in order to homogenize data and to compare them, to finally obtain a synthetic resilience index. A rigorous methodology for the quantification of resilience of HSPNs is also described. The trend of the scaling relationships between urban size and shape and the seismic resilience level is investigated. Furthermore, a real application is developed for case study of the Quartieri Spagnoli, the historical centre of the city of Naples (Campania, Italy). Here the connectivity level between couple of inhabitants and between inhabitants and school buildings is investigated, together with the global urban efficiency and the seismic resilience. Finally, also a probability-based methodology for the quantification of urban resilience to diverse event typology is presented, particularly earthquakes and flow-type landslide. Alternative resilience metrics are herein proposed, accounting for the initial state of damage level and the number of deallocated citizens. A further resilience measure is also proposed, begin totally independent on the simulated event typology. The robustness of the proposed metrics is then evaluated, through the implementation of seismic and landslide scenario analysis within a real case study for the city of Sarno (Campania, Italy)

Collaborative Networks, Decision Systems, Web Applications and Services for Supporting Engineering and Production Management

This book focused on fundamental and applied research on collaborative and intelligent networks and decision systems and services for supporting engineering and production management, along with other kinds of problems and services. The development and application of innovative collaborative approaches and systems are of primer importance currently, in Industry 4.0. Special attention is given to flexible and cyber-physical systems, and advanced design, manufacturing and management, based on artificial intelligence approaches and practices, among others, including social systems and services