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Large-scale electrification of heavy-duty road freight faces challenges including scarcity of charging infrastructure and high battery costs. Dynamic charging could help overcome these challenges by enabling trucks to charge while driving. Important additional benefits for carriers related to lower required sizes and longer lifetimes of batteries could justify the required investments. The study investigates the optimal configuration of network sections to be electrified so that the balance between costs and benefits turns out positive. A case study for a highway network spanning 4 countries in Europe suggests that dynamic charging can lead to a significant reduction in overall transport system costs, up to very large network sizes. The study supports the decision-making of policymakers and road authorities by providing new insights into the costs and benefits of dynamic charging networks, and simultaneously considering the perspectives of investors and users., Transport and Planning, Integral Design & Management, Transport and Logistics

The authors regret the acknowledgments in the published article are incomplete. The complete acknowledgments are as follows: “This research was supported by the Mexican National Council for Science and Technology (CONACYT) under project number 2019-000021-01EXTF-00564 CVU 784544. The authors would like to thank Dr. Andrés Antonio Torres Acosta, Research Professor at the Department of Sustainable and Civil Technologies, School of Engineering and Sciences, Tecnológico de Monterrey for his contributions to this research.” The authors would like to apologise for any inconvenience caused. ____________________________., Hydraulic Structures and Flood Risk, Integral Design & Management

Around the world, an increasing amount of bridge infrastructure is ageing. The resources involved in the reassessment of existing assets often exceed available resources and many bridges lack a minimum structural assessment. Therefore, there is a need for comprehensive and quantitative approaches to assess all the assets in the bridge network to reduce the risk of collapsing, damage to infrastructure, and economic losses. This paper proposes a methodology to quantify the structural criticality of bridges at a network level. To accomplish this, long-run site-specific simulations are conducted using Bayesian Networks and bivariate copulas, utilizing recorded traffic data obtained from permanent counting stations. To enhance the dataset, information from Weigh-in-Motion systems from different regions was integrated through a matching process. Subsequently, the structural response resulting from the simulated traffic is assessed, and the extreme values of the traffic load effects are obtained for selected return periods. Site-specific bridge criticality as a performance indicator for traffic load effects is derived by comparing the extreme load effects with the design load effects. The outcomes are mapped to facilitate visualization employing an open-source geographic information system application. To illustrate the application of the methodology, a total of 576 bridges within a national highway network are investigated, and a comparison with a popular simplified method is shown. The methodology herein presented can be used to assist in assessing the condition of a bridge network and prioritizing maintenance and repair activities by identifying potential bridges subjected to major load stress., Hydraulic Structures and Flood Risk, Integral Design & Management

This paper presents a two-stage simheuristics-based framework for optimizing bridge maintenance scheduling strategies in a highway transportation network under uncertainty considering bridge life-cycle reliability and the effects of different maintenance interventions. The design variables of the optimal bridge maintenance scheduling problem are the preventive maintenance schedules for all bridges in the network, with the conflicting objectives of minimizing total maintenance cost and total travel time over the life cycle of bridges. The outcome of the first stage of the framework is a Pareto front of deterministic optimal solutions, which are then tested in the second stage to measure their performance under uncertainty., Integral Design & Management, Transport and Planning

The Digital Twin (DT) concept, as understood nowadays, appeared in the early 2000s as an attempt to create virtual replicas of physical assets, such as bridges, that can be used to examine, monitor and manage their performance. Up to this day, it has been successfully applied in the fields of aeronautics, manufacturing, medicine, and more recently, in the architecture, engineering, and construction industry. The DT of a bridge requires the creation of a virtual replica of the real-life asset, along with the connection and feedback of information channel between the two of them. This connection is currently achieved through the generation of real-time data by the placement of sensors in the real bridge and the application of structural health monitoring techniques to analyze such data. This connection could result in a complex, time-consuming, and expensive process which would hinder the creation of DT prototypes for development purposes in the bridge engineering field. This paper aims at exploring the currently available synthetic data generation methodologies and tools, which could be used as a faster and a more economically feasible alternative to real monitoring, for the creation and development of DT prototypes of bridges, for both industry and research-oriented purposes. A synthetic data generation framework is proposed that can produce FAIR benchmark databases that are based on Findability, Accessibility, Interoperability, and Reuse, which could be used in the prototyping of bridge DTs. Finally, tentative future improvements in this topic are discussed., This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 101066739., Integral Design & Management

Digital twins (DTs) are virtual replicas of physical assets that can be used to monitor and manage their performance. To date, the DT concept has been effectively implemented in various industries, including aeronautics, manufacturing, medicine, and more recently, in the architecture, engineering, and construction sector. In the latter, these assets can be related to buildings, bridges, or other important infrastructures of the built environment. Although the creation of synthetic benchmark datasets for the validation of novel damage detection approaches has been attempted in the past, such alternatives are not easily findable or accessible. Thus, a new synthetic data generation framework is proposed within the DT paradigm context, that can produce FAIR benchmark databases that are characterized by Findability, Accessibility, Interoperability, and Reuse. This paper aims at exploring the uncertainty types, sources, and quantification approaches involved in the synthetic data generation methodologies and tools of the intended framework which could be used as a faster and cheaper alternative to real monitoring, for the creation and development of DT prototypes of bridges for both industry and research-oriented purposes. This work also highlights the benefits and drawbacks of implementing synthetic data for these purposes and points out tentative future improvements in the field., Integral Design & Management

The use of sensitivity analysis is essential in model development for the purposes of calibration, verification, factor prioritization, and mechanism reduction. While most contributions to sensitivity methods focus on the average model response, this paper proposes a new sensitivity method focusing on the extreme response and structural limit states, which combines an extreme-oriented sensitivity method with polynomial chaos expansion. This enables engineers to perform sensitivity analysis near given limit states and visualize the relevance of input factors to different design criteria and corresponding thresholds. The polynomial chaos expansion is used to approximate the model output and alleviate the computational cost in sensitivity analysis, which features sparsity and adaptivity to enhance efficiency. The accuracy and efficiency of the method are verified in a truss structure, which is then illustrated on a dynamic train–track–bridge system. The role of the input factors in response variability is clarified, which differs in terms of the design criteria chosen for sensitivity analysis. The method incorporates multi-scenarios and can thus be useful to support decision-making in design and management of engineering structures., Integral Design & Management, Engineering Structures

The severe effects of extreme wildfire events in recent years have shown that the fire suppression approach is not enough to solve the problem. An alternative to dealing with this issue is to accept the impossibility of eliminating wildfire hazards and focus on preparing systems to be more resilient. However, existing decision-making tools based on resilience present important drawbacks that make them inadequate for this task. This paper proposes a new approach and methodology for the resilience assessment of road traffic networks to wildfires that overcomes the main drawbacks, paying attention to the different functions of the system and the acceptance of a specific loss of performance. The latter is done through the introduction of dynamic thresholds that reflect the different requirements of the system under different wildfire conditions, including normal and extreme fires. The methodology is exemplified for five traffic networks. The results support the relevance of appropriate wildfire management through the adaptation of the natural and built environment to increase the capacity of the traffic networks to cope with wildfires., Integral Design & Management, Safety and Security Science

Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently evidenced by the collapse of several bridges worldwide. The objective of this systematic review is to collect and synthesize state-of-the-art knowledge and information about how bridge information modeling, finite element modeling, and bridge health monitoring are combined and used in the creation of digital twins (DT) of bridges, and how these models could generate damage scenarios to be used by anomaly detection algorithms for damage detection on bridges, especially in bridges with cultural heritage value. A total of 76 relevant studies from 2017 up to 2022 have been taken into account in this review. The synthesis results show a consensus toward the future adoption of DT for bridge design, management, and operation among the scientific community and bridge practitioners. The main gaps identified are related to the lack of software interoperability, the required improvement of the performance of anomaly-detection algorithms, and the approach definition to be adopted for the integration of DT at the macro scale. Other potential developments are related to the implementation of Industry 5.0 concepts and ideas within DT frameworks., Integral Design & Management

Transition zones such as level crossing and bridge approaches are critical links in railway networks due to higher degradation rates and maintenance needs. In this context, parametric optimization has been applied to improve the design in transition zones; however, it requires a more computationally efficient tool to support repetitive function evaluations, since the involved vehicle–track dynamic simulations are becoming more expensive to evaluate. For this purpose, a surrogate-based simulation methodology is proposed to search for an optimal combination of parameters relevant to the geometry and elasticity of track structures. Specifically, the presented methodology integrates finite element (FE)-based modeling with surrogate-assisted optimization: (1) the FE model is developed to characterize the dynamic behavior of a level crossing under a moving vehicle; (2) the optimization problem is formulated upon this mechanical model by extending the expensive FE simulations to an adaptive surrogate modeling scheme. This integration facilitates efficient exploration of the track design space (thereby reducing the computational cost), and a reasonable balance can be achieved between solution quality and computational effort. The methodology is applied to a Dutch railway case. Results show that compared to a reference design, the optimized design significantly improves performance indicators relevant to wheel–rail contact forces and energy dissipation in the ballast layer. The solution brings great potential in achieving a more desirable vehicle–track interaction and improving the connecting performance between level crossings and transitions. The methodology is applicable to other railway structures and may also contribute to improvements in current track design practices., Integral Design & Management, Engineering Structures

Wildfires have become a source of concern for society due to the increase in frequency, intensity, and unpredictability. This has caused serious impacts all over the world, even in areas where this type of problem did not occur before. Studies on the adaptation of critical infrastructure have been conducted to reduce the impacts of this type of hazard influenced by climate change. However, there are currently no tools to evaluate adaptation measures and their influence on the resilience of transport infrastructure to wildfires. Therefore, this paper proposes the application of a simplified methodology to assess the priority level in interventions on bridge networks and the effectiveness of different adaptation measures. The methodology is applied to a case study in Portugal. In that sense, the results show that adaptation measures such as changing vegetation management policy and implementing wildfire spread barriers effectively reduce the exposure of bridges. Therefore, this tool can be very useful for stakeholders and practitioners supporting wildfire management in terms of adaptation measures., Integral Design & Management, Safety and Security Science

Different emerging threats highlighted the relevance of recovery and adaptation modelling in the functioning of societal systems. However, as modelling of systems becomes more complex, its effort increases challenging the practicality of the engineering analyses required for efficient recovery and adaptation. In the present work, metamodels are researched as a tool to enable these analyses in traffic networks. One of the main advantages of metamodeling is their synergy with the short decision times required in recovery and adaptation. A sequential global metamodeling technique is proposed and applied to three macroscopic day-to-day user-equilibrium models. Two reference contexts of application are researched: optimal recovery to a perturbation (with response times reduced by 98% with loss of accuracy lower than 1%) and adaptation under uncertainty with perturbation-dependent optimality. Results show that metamodeling-based metaheuristics enable fast resource-intensive engineering analyses of traffic recovery and adaptation, which may change the paradigm of decision-making in this field., Integral Design and Management

Changes in a construction project schedule can impact the project's planned duration, resulting in penalties. A manual trial-and-error probabilistic approach is usually conducted to find an appropriate set of corrective measures to mitigate delays of the overall project. However, this approach does not capture the actual goal-oriented behavior of project managers who react to the actual scenarios causing delays, leading to a fundamental modeling error. Moreover, it does not employ control and automation concepts when finding the optimal mitigation strategy. To remove this modeling error and to automate the mitigation process, the Mitigation Controller (MitC) software is developed. The MitC searches for the most cost-effective set of mitigation measures considering risk events and durations uncertainties of activities. Moreover, the MitC captures activity correlations and enables contractual penalty/reward schemes in the simulation. As a result, it returns the most effective mitigation strategy that minimizes the mitigation cost and penalty and maximizes the reward potential. The Mitigation Controller introduced here constitutes an open-source code written in Matlab, R&D / Innovation, Integral Design and Management, Real Estate Management

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 Engineering, Integral Design and Management, Real Estate Management

A co-simulation solution based on direct equilibrium of contact forces is proposed to simulate vehicle-track interaction (VTI) dynamics. It is developed in two platforms, which presents an iterative feedback loop that exchanges contact force files and structure response field in real-time. The load vector acting on the structure is described by a moving Gaussian pulse, which approximates the Dirac-delta function. Through this approach, system matrices are not exported and the additional identification of the correspondence between structure nodes and vehicle positions is avoided, which is contrary to the typical scheme in existing co-simulation methods for VTI problems. The direct information exchange in the current solution simplifies the VTI model development, making it easier for the application in track design and maintenance phase. The solution is demonstrated by a general beam model subject to a quarter car and has been calibrated and verified by benchmark cases coded in MATLAB. The example presented is a baseline model for demonstration purposes. And the proposed scheme allows for flexibility in incorporating more complex structure configurations and vehicle motions for further study., 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 & Management, Engineering Structures

In traffic networks, some elements are more prone to suffer or to create disruptive situations, and the identification of these elements becomes a challenge due to the large number of possible threats. The following paper presents two new methodologies to identify and rank vulnerable and critical links of traffic networks. These methodologies use the Fisher Information Matrix, and the analysis of eigenvalues and eigenvectors, to systematically rank the links of a network. The identification is done by using traffic variables, such as the demand, the travel time, and the network's flow. For the ranking of the links, disruptions are considered in all the possible locations of the network, and the effects are systematically evaluated. In addition, the evaluation of traffic resilience is included in the process to validate the results. Finally, both methodologies are tested in a real network to infer on the validity of the results., 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 & Management

Assessing flood risks on road infrastructures is critical for the definition of mitigation strategies and adaptation processes. Some efforts have been made to conduct a regional flood risk assessment to support the decision-making process of exposed areas. However, these approaches focus on the physical damage of civil infrastructures without considering indirect impacts resulting from social aspects or traffic delays due to the functionality loss of transportation infrastructures. Moreover, existing methodologies do not include a proper assessment of the uncertainties involved in the risk quantification. This work aims to provide a consistent quantitative flood risk estimation and influence factor modelling for road infrastructures. To this end, a Flood Risk Factor (FRF) is computed as a function of hazard, vulnerability, and infrastructure importance factors. A Bayesian Network (BN) is constructed for considering the interdependencies among the selected input factors, as well as accounting for the uncertainties involved in the modelling process. The proposed approach allows weighting the relevant factors differently to compute the FRF and improves the understanding of the causal relations between them. The suggested method is applied to a case study located in the region of Santarem Portugal, allowing the identification of the sub-basins where the road network has the highest risks and illustrating the potential of Bayesian inference techniques for updating the model when new information becomes available., 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 & Management

Significant research has been conducted in identifying optimal recovery and adaptation decisions in disruptive scenarios using engineering models. In this context, an aspect that has been target of limited research is that of response times. Modelling is expected to grow progressively more complex as it becomes more accurate. Such complexity increases modelling efforts, and the promise of optimal adaptation and recovery may become hindered. The present work discusses the role of modelling fidelities in adaptation and recovery of systems, and in particular that of using a lower fidelity model that enables zero-time analyses of a system. A framework is proposed for using different fidelities in adaptation and recovery, considering system's decision time requirements. The relevance of this analysis is researched in two traffic networks and results show that multi-fidelity models should be expected to play a key role in increasing the efficiency of optimal adaptation and recovery decisions., Integral Design & Management

The built environment is already facing severe consequences related to climate change. Considering the durability of structures, the increase of carbon-dioxide (CO2) concentration and changes on temperature and relative humidity may accelerate carbonation-induced corrosion, thus affecting the service life of reinforced concrete structures. Several studies have assessed the potential effects of climate change on concrete carbonation for specific locations, and this requires to convert climate databases, which come in various spatial resolutions, to scales that are suitable for the purpose of the study. However, there is not a consistent methodology for using climate projections databases at various spatial scales (e.g., city, district, region, country, etc.). Hence, the main goal of this research is to propose an approach allowing for multi-region assessment of carbonation of reinforced concrete structures, under changing climate. The proposed methodology is based on a carbonation model that takes into account the effects of climate change over time. Moreover, procedures and recommendations are provided to reduce errors in lifetime assessment, such as selection of climate change scenarios, choice of simulation chains, and bias correction. The use of the proposed approach is illustrated by computing carbonation depths for several places located in three districts in Portugal: Porto (north), Lisboa (Middle), and Faro (South). The overall results allow to conclude that: (i) specific climate conditions inside a district, namely temperature and relative humidity, modify the carbonation depths (e.g.: a variation of 19 % was obtained for the carbonation depth in the district of Lisbon); (ii) bias-correction should be systematically carried out to avoid errors in the assessments (for example, in the district of Faro, the time to initiate corrosion was over estimated by about 7 years without bias correction); and (iii) climate change could accelerate concrete ca, Integral Design & Management

In smart cities, unmanned aerial vehicles and self-driving vehicles are gaining increased concern. These vehicles might utilize ultra-reliable telecommunication systems, Internet-based technologies, and navigation satellite services to locate their customers and other team vehicles to plan their routes. Furthermore, the team of vehicles should serve their customers by specified due date efficiently. Coordination between the vehicles might be needed to be accomplished in real-time in exceptional cases, such as after a traffic accident or extreme weather conditions. This paper presents the planning of vehicle routes as a team orienteering problem. In addition, an ‘agile’ optimization algorithm is presented to plan these routes for drones and other autonomous vehicles. This algorithm combines an extremely fast biased-randomized heuristic and a parallel computing approach., Integral Design and Management

The first Irish public Bike Sharing Scheme (BSS) was launched in Dublin in 2009. Dublinbikes has been internationally recognised as one of the most successful bike-sharing rental schemes in the world. For this reason, among others, the cities of Cork, Limerick and Galway launched their own BSSs at the end of 2014. The objective of this paper is to compare the performance of the four BSSs during the first two years of implementation in each Irish city according to endogenous factors, such as the physical design of the schemes, and exogenous factors, such as city size and population density. In terms of population, Limerick and Galway are small cities, Cork is a medium-sized city and Dublin is a large city. In consequence, the results cover the main relevant aspects of BSSs according to the size of the scheme, pointing out similarities and differences among BSS of different sizes. The main findings indicate that the number of daily rentals per bike is a good metric from the point of view of the transport operator. However, a higher density of bikes, stations and docking points does not imply greater usage, whereas the size of the deployment area could be a key factor in improving bike usage. Finally, a synopsis of the essential aspects to consider when designing a BSS deployment based on types of users in small cities is provided., 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 Management

The present paper discusses the application principles of value of information theory in adaptive metamodeling for reliability analysis. Metamodeling for reliability purposes has become particularly relevant in recent years. The usage of metamodels allows surrogating the, costly to evaluate, performance functions of engineering structures. Adaptive Kriging procedures are examples of the successful application of metamodel- ing in reliability analysis. Efficient adaptive Kriging involves the usage of some notion of improvement in what ultimately is an unsupervised decision making scheme that selects points to enrich the model. Therefore, the decision to select a point to enrich the experimental design should consider the utility of each candidate in the expectation of improvement of the metamodeling accuracy. Within this context, a comprehensive discussion on the application of value of information for reliability metamodeling is presented. Since the candidate points and surrogate are jointly built in a virtually costless model, it is possible to know the virtual outcome of the enrich- ment decisions. In many circumstances, points in the experimental design may provide redundant information. Furthermore, a priori knowledge on the performance function may be applied to weight the expected outcome of exploration and exploitation. Value of information considerations adds value to reliability metamodeling that uses adaptive methods, and is of interest for efficient design and optimization of complex structures, such as bridge structures., 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 Management

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 Management, Real Estate Management

The first Irish public Bike Sharing Scheme (BSS) was launched in Dublin in 2009. Dublinbikes has been internationally recognised as one of the most successful bike-sharing rental schemes in the world. For this reason, among others, the cities of Cork, Limerick and Galway launched their own BSSs at the end of 2014. The objective of this paper is to compare the performance of the four BSSs during the first two years of implementation in each Irish city according to endogenous factors, such as the physical design of the schemes, and exogenous factors, such as city size and population density. In terms of population, Limerick and Galway are small cities, Cork is a medium-sized city and Dublin is a large city. In consequence, the results cover the main relevant aspects of BSSs according to the size of the scheme, pointing out similarities and differences among BSS of different sizes. The main findings indicate that the number of daily rentals per bike is a good metric from the point of view of the transport operator. However, a higher density of bikes, stations and docking points does not imply greater usage, whereas the size of the deployment area could be a key factor in improving bike usage. Finally, a synopsis of the essential aspects to consider when designing a BSS deployment based on types of users in small cities is provided., Integral Design and Management

The impact of climate change on ambient temperature and relative humidity along with the present CO2 levels are speeding the corrosion process of reinforced concrete structures. The alarming cost of the associated reduction of the service life of structures, which is estimated to cost 3% to 4% of the Gross Domestic Product (GDP) of industrialized countries, has put the spotlight on the importance of introducing the issue of climate change on the new generation of Eurocodes. Amongst the strategies to tackle the problem, design-phase measures seem not to be always cost- effective, nevertheless, measures during service-life are generally the most expensive. This paper discusses the potential strategies to be addressed by structural codes to tackle the problem of climate change-induced corrosion, considering aspects such as the cost-benefit analysis, viability, and the large uncertainty involved in climate change evolution., 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 Management

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread., Integral Design and Management

Over the Earth’s history, the climate has changed considerably due to natural processes affecting directly the earth. In the last century, these changes have perpetrated global warming. Carbon dioxide is the main trigger for climate change as it represents approximately up to 80% of the total greenhouse gas emissions. Climate change and concrete carbonation accelerate the corrosion process increasing the infrastructure maintenance and repair costs of hundreds of billions of dollars annually. The concrete carbonation process is based on the presence of carbon dioxide and moisture, which lowers the pH value to around 9, in which the protective oxide layer surrounding the reinforcing steel bars is penetrated and corrosion takes place. Predicting the effective retained service life and the need for repairs of the concrete structure subjected to carbonation requires carbon dioxide forecasting in order to increase the lifespan of the bridge. In this paper, short term memory process models were used to analyze a historical carbon dioxide database, and specifically to fill in the missing database values and perform predictions. Various models were used and the accuracy of the models was compared. We found that the proposed Stochastic Markovian Seasonal Autoregressive Integrated Moving Average (MSARIMA) model provides R2 value of 98.8%, accuracy in forecasting value of 89.7% and a variance in the value of the individual errors of 0.12. When compared with the CO2 database values, the proposed MSARIMA model provides a variance value of −0.1 and a coefficient of variation value of −8.0e−4., 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 Management

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 Management

Engineering models are becoming increasingly complex, involving a larger number of variables. As a result, engineers struggle to deeply understand the models and therefore validate and properly use them. Sensitivity analyses (SA) are usually conducted to help with this task. Nonetheless, the knowledge and computational efforts required to conduct SA increases with the complexity of the model. This paper presents a conceptually simple method to conduct the SA of extreme-based engineering problems, that is, those problems whose outcome of interest is their maximum or minimum values. This type of problems is of relevance for reliability-based design. The method requires to iteratively maximize or minimize the model by fixing one input factor at each time. Then, the variation of the optimal surface is evaluated. The method permits the visualization and measure of the input factors’ influence on the extreme model response, with no need of defining the probability distribution of the input factors. Both the easiness of application and interpretation, along with a low computational cost for problems dealing with extreme values, make the proposed method very convenient to practitioners., Integral Design and Management

Performance evaluation and maintenance planning are gaining importance with ageing rail infrastructure and increasing demand on track safety and continuous availability. The discrete/point railway assets (e.g. bridges, level crossings) together with extended track sections constitute the main railway network infrastructure. The former has important implications in train safety, riding comfort and operating expenditures due to local intensified degradation and plays a role in effective network capacity due to their large quantity. The heterogeneity in asset features and operating environment also adds difficulties to efficient maintenance planning of multiple discrete assets. The current review screens the issue to level crossings, as little concern has been engaged to this asset type, and draws together different perspectives related to their maintenance management. The systems thinking approach is integrated and two levels of asset management (i.e. micro- and macro-level) are used to structure the synthesis, which are interdependent and synergistic. Two major approaches, namely, the mechanistic and data-driven modelling are synthesised. Both contribute to the maintenance knowledge and their comparisons are elaborated. Limitations in existing studies are identified and directions for future research are provided, aiming to contribute to a more refined ‘inspection and diagnosis’ process to properly capture the local track issues and move towards system-level maintenance approach for multiple level crossings., Integral Design and Management, Mechanics and Physics of Structures

Structural identification using dynamical parameters (such as the natural vibration frequencies and mode shapes) is an important issue, especially in bridges or high-rise buildings. However, incorrect decisions could happen on the Structural Health Monitoring (SHM) strategy and the Structural System Identification (SSI) analysis that makes the sometimes expensive and time-consuming process useless due to the large uncertainty of the resulting estimations. This paper discusses the role of the SHM strategy and the SSI analysis based on the constrained observability method (COM) and decision trees (DT) in reducing the estimation error. Here, the COM uses subsets of natural frequencies and/or modal-shapes to deal with the nonlinearity of the SSI derived from the operational aspects of the methods, and combines the unknown items including frequencies and mode shapes into an optimization process. Next, a decision-support tool based on decision trees is applied to help engineers to establish the best SHM + SSI strategy yielding the most accurate estimations. The principle and steps of this new method, the combination of constrained observability m,ethod and decision trees, are presented for the first time. After that, a numerical model of a bridge case is used to show how to choose the optimal strategy, when factors such as the structure layout, span length, measurement set, and parameters of the COM are included as decision variables. The importance ranking of these four factors is the layout, measurement set, parameters of the COM, and length through the sensitivity analysis of the COM estimated. Last, a real bridge is used to validate this methodology under the undamaged and damaged scenarios by comparing an Error Index, which shows the optimal SHM + SSI strategy works well no matter the bridge is damaged or not. The presented analysis leads to significant insights that can help the decision-making of the optimal SHM + SSI strategy, avoiding erroneous decisions if th, Integral Design and Management

The inverse problem of structural system identification is prone to ill‐conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part., Integral Design and Management

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 Management, Real Estate Management

The present work discusses an innovative approach to metamodeling in reliability that uses a field-transversal rationale. Adaptive metamodeling in reliability is characterized by its large spectra of models and techniques with different assumptions. As a result, the reliability engineer is frequently faced with the highly challenging task of selecting an appropriate model or technique with limited a priori knowledge about the performance function that defines the problem of reliability. To tackle this challenge, a complement-basis is proposed for adaptive metamodeling. It consists in using a batch of multiple metamodels or techniques that, accordingly to an activation criterion, are selected to solve the reliability analysis. This activation is set to depend on the model synergy with the problem in-hand. In the present work the leave-one-out loss is applied as evaluator of compatibility, and results show that the absolute loss successfully performs as an activator. A metamodel-independent learning approach and stopping criterion are implemented to study the proposed approach in five representative examples. Results show that the complement-basis allows to increase the efficiency of the reliability analysis through the selection of adequate metamodels, which is indicative of the untapped potential that further transversal research may add to metamodeling in reliability analysis., Integral Design and Management

The present work reviews the implementation of adaptive metamodeling for reliability analysis with emphasis in four main types of metamodels: response surfaces, polynomial chaos expansions, support vector machines, and Kriging models. The discussion presented is motivated by the identified spread and little interaction between metamodeling techniques in reliability, which makes it challenging for practitioners to decide which one to consider in a context of implementation. The conceptual problem of reliability analysis and the theoretical description of the four models is presented, and complemented by a comparative discussion of applications with identification of new areas of interest. The different considerations that influence the efficiency of adaptive metamodeling are reviewed, with extension to applicability discussions for the four models researched. Despite all adaptive techniques contributing to achieve significant gains in the amount of effort required for reliability analysis, and with minimal trade-off in accuracy, they should not be expected to perform equally in regard to the dependence on the reliability problem being addressed. Cross application of methodologies, bridging the gap between methodology and application, and ensembles are some of new areas of research interest identified. One of the major critical considerations for adaptive metamodeling, and that has been target of limited research, is the need for comprehensive techniques that allow a blind selection of the most adequate model with relation to the problem in–hand. To conclude, the extensive and comprehensive discussion presented aims to be a first step for the unification of the field of adaptive metamodeling in reliability; so that future implementations do not exclusively follow individual lines of research that progressively become more narrow in scope, but also seek transversal developments in the field of adaptive metamodeling for reliability analysis., Integral Design and Management

Despite widespread attention for the governance of infrastructures and improvements of the way infrastructure assets are maintained, the interdependency of infrastructures is not often considered from a systemic maintenance and renovation perspective. In this context, the issue of unforeseen intervention delays is of particular relevance because its impact on cost and hindrance might be too costly for infrastructure operators. Building upon the 3C concept (Centralize, Cluster, and Calculate) for intervention scheduling and optimization, this paper investigates the effect of unforeseen intervention delays on the intervention costs and the corresponding closure cost of the affected interdependent systems. A stochastic approach has been proposed to deal with the uncertainty of such delays. Uncertain intervention times are combined by Monte Carlo simulations to obtain the probabilistic distribution of the total cost at the end of the timeline of an intervention program affecting multiple interdependent infrastructures. Also, the change in the statistical deviation over time of the total cost with respect to the planned (optimal) cost during the entire program is obtained. This analysis yields interesting conclusions, such as the need for specific mitigation plans conducted during the course of the program to reduce the cost generated by the cumulative delays, and the need for enhanced communication between infrastructure managers, which could bring significant (economic) benefits to all stakeholders by jointly planning their intervention activities., Integral Design and Management, Organisation and Governance, Real Estate Management

The report presents the work of the Joint Research Centre (JRC) scientific network on adaptation of structural design to climate change addressing the expected implications of a changing climate on the corrosion of structures. The work first outlines recent EU policies supporting the sustainability and climate resilience of infrastructure and buildings. It is highlighted how the construction sector is encouraged to adopt more sustainable and circular economic practices, extend the lifetime of buildings and strive for better performance of buildings and infrastructure throughout their life cycle. The ongoing action plan to adapt European standards to a changing climate is emphasised. The report evaluates the expected variations in climatic factors causing corrosion, provides a state-of-the-art review on climate change induced corrosion of reinforced concrete and steel structures, and presents recent works on the corrosion impact, the costs and effectiveness of adaptation strategies. The effects of corrosion on the seismic performance of structures is addressed as well. In conclusion, this report presents the scientific and technical background to study the expected implications of climate change on the corrosion of structures. The work intends to stimulate debate on the subject, identify further research needs, and serve as a basis for the development of further work relevant to the adaptation to climate change of European standards and policies., Integral Design and Management

The new generation of structural Eurocodes will include climate change adaption measures in order to enhance the climate resilience of infrastructures across Europe. This paper discusses the impact that climate change might have on reinforced concrete structures subjected to corrosion, and the associated challenges of the standardisation of adaptation measures. A resilience-based framework is proposed for the adaptation of structural codes to climate change-induced actions. Such an approach aims to provide the required adaptive capacity to the new structures in order to be able to respond to the uncertain future minimising the investment under unlikely scenarios. In that way, the strategy can be summarised as a climate change-adapted design plus an in-design maintenance plan. Future actions, such as mapping the future climate-related drivers of corrosion, the determination of the design values of these drivers, and the prescription of maintenance activities, should be further investigated. Although this paper focuses on the new structures that will be designed with the new codes, some of the insights can be extrapolated to the existing structures., Integral Design and Management

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 Management, Integral Design and Management