Combating Infrastructure Complexity: Developing a Comprehensive Set of Wellbeing and Resilience Indicators for the Transport Infrastructure System

As modern societies become increasingly dependent on infrastructure systems, ensuring their functionality is paramount. Current simulation-based approaches for evaluating infrastructure wellbeing and resilience are known to be complex and time-consuming, making them unfeasible for practical applications. Indicators-based methods have been proposed as a promising alternative to simulations. However, a comprehensive set of indicators that cover all aspects of infrastructure systems has yet to be established. In this study, we performed an extensive literature review on wellbeing and resilience indicators specific to the transport infrastructure system. We filtered out duplications among the indicators and categorized them under distinct components and dimensions. These indicators can be tailored to fit specific circumstances and employed for/alongside advanced techniques such as Machine Learning, Bayesian Networks, and Fuzzy Logic. Acquiring a comprehensive set of wellbeing and resilience indicators can significantly improve stakeholder communication, empower communities in decision-making processes and adaptive management, and support resilience-strengthening strategies.System Engineerin

Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks

Resilience indicators are a convenient tool to assess the resilience of engineering systems. They are often used in preliminary designs or in the assessment of complex systems. This paper introduces a novel approach to assess the time-dependent resilience of engineering systems using resilience indicators. A Bayesian network (BN) approach is employed to handle the relationships among the indicators. BN is known for its capability of handling causal dependencies between different variables in probabilistic terms. However, the use of BN is limited to static systems that are in a state of equilibrium. Being at equilibrium is often not the case because most engineering systems are dynamic in nature as their performance fluctuates with time, especially after disturbing events (e.g. natural disasters). Therefore, the temporal dimension is tackled in this work using the Dynamic Bayesian Network (DBN). DBN extends the classical BN by adding the time dimension. It permits the interaction among variables at different time steps. It can be used to track the evolution of a system's performance given an evidence recorded at a previous time step. This allows predicting the resilience state of a system given its initial condition. A mathematical probabilistic framework based on the DBN is developed to model the resilience of dynamic engineering systems. Two illustrative examples are presented in the paper to demonstrate the applicability of the introduced framework. One example evaluates the resilience of Brazil. The other one evaluates the resilience of a transportation system.Accepted Author ManuscriptIntegral Design and Managemen

Resourcefulness quantification approach for resilient communities and countries

Availability of resources is one of the primary criteria for communities to attain a high resilience level during disaster events. This paper introduces a new approach to evaluate resourcefulness at the community and national scales. Resourcefulness is calculated using a proposed composite resourcefulness index, which is a combination of several resourcefulness indicators. To build the resourcefulness index, resourcefulness indicators representing the different aspects of resourcefulness are collected from renowned literary publications. Every indicator is assigned a measure to make it quantifiable. Time-history data for the measures are needed to perform the analysis. While these data could be obtained from different sources, acquiring a full set of data is quite challenging. Hence, to account for missing data, the Multiple Imputation (MI) and the Markov Chain Monte Carlo (MCMC) data imputation methods are adopted. The data are then normalized, assigned weights, and aggregated to obtain the resourcefulness index. A case study is performed to demonstrate the applicability of the approach. The resourcefulness indexes of two countries, namely the United States and Italy, are evaluated. Results show that resourceful communities/countries are more resilient during disaster events as they have more tools to come up with solutions. It is also shown that knowing the current resourcefulness level helps in better identifying what aspects should be improved.Accepted Author ManuscriptIntegral Design and Managemen

Resilience Assessment at the State Level Using the Sendai Framework

The multitude of uncertainties of both natural and man-made disasters have prompted an increased attention in resilience engineering and disaster management. To overcome the effects of disastrous events, such as economic and social effects, modern communities need to be resilient. Natural disasters are unpredictable and unavoidable. While it is not possible to prevent them and protect individuals and societies against such disasters, modern communities should be prepared by incorporating both pre-event (preparedness and mitigation) and post-event (response and recovery) resilience activities to minimize the negative effects after a severe event. Resilience indicators may be fundamental to help the planners and decision-makers to develop strategies and action plans for making communities more resilient. This chapter presents a quantitative approach to estimate the resilience and resilience-based risk at the state level. In the proposed method, the resilience-based risk is a function of resilience, hazard, and exposure. To evaluate the resilience parameter, data provided by the Sendai Framework for Disaster Risk Reduction (SFDRR) are used. The framework is developed using resilience indicators with the primary goal of achieving disaster risk reduction. To use those indicators in the resilience assessment, it is necessary to define the impact and the contribution of each indicator towards resilience. To do that, two possible methods to combine and weight the different SFDRR indicators are presented: Dependence Tree Analysis (DTA) and Spider Plot Weighted Area Analysis (SPA). The proposed approach allows the decision-makers and governments to evaluate the resilience and the related resilience-based risk (RBR) of their countries using available information.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.System Engineerin

Measuring and improving community resilience: A fuzzy logic approach

Due to the increasing frequency of natural and man-made disasters, the scientific community has paid considerable attention to the concept of resilience engineering. On the other hand, authorities and decision-makers have been focusing their efforts on developing strategies that can help increase community resilience to different types of extreme events. Since it is often impossible to prevent every risk, the focus is on adapting and managing risks in ways that minimize impacts to communities (e.g., humans and other systems). Several resilience strategies have been proposed in the literature to reduce disaster risk and improve community resilience. Generally, resilience assessment is challenging due to uncertainty and the unavailability of data necessary for the estimation process. This paper proposes a Fuzzy Logic method for quantifying community resilience. The methodology is based on the PEOPLES framework, an indicator-based hierarchical framework that defines all aspects of a community. A fuzzy-based approach is implemented to quantify the PEOPLES indicators using descriptive knowledge instead of complex data, accounting for the uncertainties involved in the analysis. To demonstrate the applicability of the methodology, three cases with different levels of data availability are performed to obtain a resilience curve and resilience index of two out of seven dimensions of the PEOPLES framework. When numerical data does not exist, descriptive data based on expert knowledge is used as input. Results show that the proposed methodology can cope with both numerical and descriptive input data with different uncertainty levels providing good estimates of resilience. The methodology can be used as a decision-support tool to assist decision-makers and stakeholders in assessing and improving their communities' resilience for future events, focusing on specific indicators that suffer from resilience deficiencies and need improvements.System Engineerin

The open design education approach: An integrative teaching and learning concept for management and engineering

Construction Management and Engineering students need to acquire managing skills for solving real-world problems that are complex, rarely straightforward and lack 'one right answer'. For this, they need to become 'open designers', capable to be reflective, integrative and creative in- and on action with dynamic and new situations. In this paper, the so-called Open Design Learning Circle (ODLC) will be proposed as an innovative educational concept in which engineering-, management- and pedagogic sciences are integrated. Within this concept the students 'dialogue' with: 1) an objective open glass box model covering engineering products and management processes (outer) and, 2) their subjective open human threefold, reflecting their personal learning (inner). The integration of both human and model dialogues is essential for the emergence of new knowledge and creative insights for open designs, which is essentially distinct from more traditional learning concepts. To enable this emergence, a self-chosen system of interest is the 'experiential vehicle' that forms the basis for a self-created textbook and model. Thereby, the ODLC forms the fundamental basis for creating 'open and persistent learners'. In this paper, it also will be shown how the ODLC can be operationalized into a learning cycle and how it has been implemented in an example course on systems engineering management within the MSc Construction Management Engineering curriculum at the TU Delft. Finally, some preliminary student findings and next steps for further research are discussed.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Real Estate ManagementIntegral Design and Managemen

Multi-system intervention optimization for interdependent infrastructure

The wellbeing of modern societies is dependent upon the functioning of their infrastructure networks. This paper introduces the 3C concept, an integrative multi-system and multi-stakeholder optimization approach for managing infrastructure interventions (e.g., maintenance, renovation, etc.). The proposed approach takes advantage of the benefits achieved by grouping (i.e., optimizing) intervention activities. Intervention optimization leads to substantial savings on both direct intervention costs (operator) and indirect unavailability costs (society) by reducing the number of system interruptions. The proposed optimization approach is formalized into a structured mathematical model that can account for the interactions between multiple infrastructure networks and the impact on multiple stakeholders (e.g., society and infrastructure operators), and it can accommodate different types of intervention, such as maintenance, removal, and upgrading. The different types of interdependencies, within and across infrastructures, are modeled using a proposed interaction matrix (IM). The IM allows integrating the interventions of different infrastructure networks whose interventions are normally planned independently. Moreover, the introduced 3C concept accounts for central interventions, which are those that must occur at a pre-established time moment, where neither delay nor advance is permitted. To demonstrate the applicability of the proposed approach, an illustrative example of a multi-system and multi-actor intervention planning is introduced. Results show a substantial reduction in the operator and societal costs. In addition, the optimal intervention program obtained in the analysis shows no predictable patterns, which indicates it is a useful managerial decision support tool.Integral Design and ManagementReal Estate Managemen

Mitigation Controller: Adaptive Simulation Approach for Planning Control Measures in Large Construction Projects

Probabilistic Monte Carlo simulations are often used to determine a project's completion time given a required probability level. During project execution, schedule changes negatively affect the probability of meeting the project's completion time. A manual trial and error approach is then conducted to find a set of mitigation measures to again arrive at the required probability level. These are then implemented as scheduled activities. The mitigation controller (MitC) proposed in this paper automates the search for finding the most cost-effective set of mitigation measures using multiobjective linear optimization so that the probability of timely completion remains at the required level. It considers different types of uncertainties and risk events in the probabilistic simulation. Moreover, it removes the fundamental modeling error that exists in the traditional probabilistic approach by incorporating human control and adaptive behavior in the simulation. Its usefulness is demonstrated using an illustrative example derived from a recent Dutch construction project in which delay is not permitted. It is shown that the MitC is capable of identifying the most effective mitigation strategies allowing for substantial cost savings. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Integral Design and ManagementReal Estate Managemen

Quantifying restoration time of pipelines after earthquakes: Comparison of Bayesian belief networks and fuzzy models

Critical infrastructures are an integral part of our society and economy. Services like gas supply or water networks are expected to be available at all times since a service failure may incur catastrophic consequences to the public health, safety, and financial capacity of the society. Several resilience strategies have been examined to reduce disaster risk and evaluate the downtime of infrastructures following destructive events. This paper introduces an indicator-based downtime estimation model for buried infrastructures (i.e., water and gas networks). The model distinguishes the important aspects that contribute to determining the downtime of buried infrastructure following a hazardous event. The proposed downtime model relies on two inference methods for its computation, Fuzzy Logic (FL) and Bayesian Network (BN), which are adapted for the current application. Finally, through a case scenario, a comparison of the two inference methods, in terms of results and limitations, is presented. Results show that both methods incorporate intuitive knowledge and/or historical data for defining fuzzy rules (in FL) and estimating conditional probabilities (in BN). The difference stands in the interpretation of the outcome. The output of the FL is a membership that defines how well the downtime fits the fuzzy levels while the BN output is a probability distribution that represents how likely the downtime is in a certain state. Nevertheless, both approaches can be utilized by decision-makers to easily estimate the time to restore the functionality of buried infrastructures and plan preventive safety measures accordingly.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Integral Design & Managemen

Dynamic control for construction project scheduling on-the-run

Construction project management requires dynamic mitigation control to ensure a project's timely completion. Current mitigation approaches are usually performed by an iterative Monte Carlo (MC) analysis which does not reflect (1) the project manager's goal-oriented behavior, (2) contractual project completion performance schemes, and (3) stochastic dependence between construction activities. Therefore, the development statement within this paper is to design a method and implementation tool that properly dissolves all of the aforementioned shortcomings ensuring the project's completion date by finding the most effective and efficient mitigation strategy. For this purpose, the Mitigation Controller (MitC) has been developed using an integrative approach of nonlinear stochastic optimization techniques and probabilistic Monte Carlo analysis. MitC's applicability is demonstrated using a recent Dutch large infrastructure construction project showing its added value for dynamic control on-the-run. It is shown that the MitC is a state-of-the-art decision support tool that a-priori automates and optimizes the search for the best set of mitigation strategies on-the-run rather than a-posteriori evaluating the potentially sub-optimal and over-designed mitigation strategies (as commonly done with modern software such as Primavera P6).System EngineeringIntegral Design and ManagementReal Estate Managemen