•Framework for optimising sustainability, resilience, and cost (SRC) metrics is described and applied.•Traditional and low-carbon restoration strategies are compared on a bridge.•Fragility and ...restoration models are employed toward actionable SRC metrics.•Practical starting point for evaluating climate projections in adaptation strategies.
Climate change exacerbates natural hazards and continuously challenges the performance of critical infrastructure. Thus, climate resilience and sustainable adaptation of infrastructure are of paramount importance. This paper puts forward a novel framework and metrics for optimising sustainability (Greenhouse Gas emissions - GHG), climate resilience (restoration time), and cost. The framework aims to facilitate decision-making by operators and stakeholders and communicate actionable trade-offs between these principles. It describes approaches for quantifying ex-ante adaptation and ex-post recovery from the lenses of sustainability and resilience using relevant metrics. This paper concludes with an application of the framework on a bridge, where normalised metrics are integrated into one unique index (ISRC), which can be used in the recovery prioritisation for portfolios of similar assets. The optimisation program includes a bridge recovery, while reducing GHG emissions. The impact of climate change on the sustainability and resilience indexes is examined and the results show how the optimum solutions are adversely affected by different climate projections. In all scenarios examined, more sustainable solutions leading to reduced GHG emissions (tCO2e) are the optimum solutions when weighing resilience and cost. Based on the case study analysed in this paper, the low carbon restoration strategy resulted in up to 50% higher ISRC, which can justify investments for low GHG adaptation strategies in transport assets.
Delivering infrastructure, resilient to multiple natural hazards and climate change, is fundamental to continued economic prosperity and social coherence. This is a strategic priority of the United ...Nations Sustainable Development Goals (SDGs), the World Bank, the Organisation for Economic Co-operation and Development (OECD), public policies and global initiatives. The operability and functionality of critical infrastructure are continuously challenged by multiple stressors, increasing demands and ageing, whilst their interconnectedness and dependencies pose additional challenges. Emerging and disruptive digital technologies have the potential to enhance climate resilience of critical infrastructure, by providing rapid and accurate assessment of asset condition and support decision-making and adaptation. In this pursuit, it is imperative to adopt multidisciplinary roadmaps and deploy computational, communication and other digital technologies, tools and monitoring systems. Nevertheless, the potential of these emerging technologies remains largely unexploited, as there is a lack of consensus, integrated approaches and legislation in support of their use. In this perspective paper, we discuss the main challenges and enablers of climate-resilient infrastructure and we identify how available roadmaps, tools and emerging digital technologies, e.g. Internet of Things, digital twins, point clouds, Artificial Intelligence, Building Information Modelling, can be placed at the service of a safer world. We show how digital technologies will lead to infrastructure of enhanced resilience, by delivering efficient and reliable decision-making, in a proactive and/or reactive manner, prior, during and after hazard occurrences. In this respect, we discuss how emerging technologies significantly reduce the uncertainties in all phases of infrastructure resilience evaluations. Thus, building climate-resilient infrastructure, aided by digital technologies, will underpin critical activities globally, contribute to Net Zero target and hence safeguard our societies and economies. To achieve this we set an agenda, which is aligned with the relevant SDGs and highlights the urgent need to deliver holistic and inclusive standards and legislation, supported by coordinated alliances, to fully utilise emerging digital technologies.
We live in the era of large data analysis, where processing vast datasets has become essential for uncovering valuable insights across various domains of our lives. Machine learning (ML) algorithms ...offer powerful tools for processing and analyzing this abundance of information. However, the considerable time and computational resources needed for training ML models pose significant challenges, especially within cascade schemes, due to the iterative nature of training algorithms, the complexity of feature extraction and transformation processes, and the large sizes of the datasets involved. This paper proposes a modification to the existing ML-based cascade scheme for analyzing large biomedical datasets by incorporating principal component analysis (PCA) at each level of the cascade. We selected the number of principal components to replace the initial inputs so that it ensured 95% variance retention. Furthermore, we enhanced the training and application algorithms and demonstrated the effectiveness of the modified cascade scheme through comparative analysis, which showcased a significant reduction in training time while improving the generalization properties of the method and the accuracy of the large data analysis. The improved enhanced generalization properties of the scheme stemmed from the reduction in nonsignificant independent attributes in the dataset, which further enhanced its performance in intelligent large data analysis.
•Novel resilience framework to support infrastructure recovery prioritisation in war-torn countries.•Resilience by assessment based on standoff observations from disparate data ...sources.•Reconstruction prioritisation using cost-based resilience for the benefit of the society.
Apart from security issues, war-torn societies and countries face immense challenges in rebuilding damaged critical infrastructure. Existing post-conflict recovery frameworks mainly focus on social impacts and mitigation. Also, existing frameworks for resilience to natural hazards are mainly based on design and intervention, yet, they are not fit for post-conflict infrastructure recovery for a number of reasons explained in this paper. Post-conflict peacebuilding can be enhanced when resilience by assessment (RBA) is employed, using standoff observations that include data from disparate remote-sensing sources, e.g. public satellite imagery, forensics and crowdsourcing, collected during the conflict. This paper discusses why conflicts and warfare require a new framework for achieving post-conflict infrastructure resilience. It then introduces a novel post-conflict framework that includes different scales of resilience with a focus on asset and regional resilience. It considers different levels of knowledge, with a focus on standoff observations and data-driven assessments to facilitate prioritisation during reconstruction. The framework is then applied to the transport network of the area west of Kyiv, Ukraine to demonstrate how resilience by assessment can support decision-makers, such as governments and multilateral financial institutions, to address infrastructure needs and accelerate financial and humanitarian assistance, absorb shocks and maximise infrastructure recovery after conflict.
The purpose of this survey is to define the restoration tasks after hydraulic-induced damage and/or loss of functionality of bridges. This includes the duration and sequence of restoration tasks, ...idle times, cost, and traffic/functionality loss for specified damage levels of given bridge components. The potential use of this data is the generation of sets of restoration and reinstatements functions for quantifying the resilience of bridges exposed to hydraulic hazards, i.e. scour, debris accumulation and hydraulic forces (Mitoulis et al. 2021). The data are expected to inform boroughs, county councils, road and rail owners and stakeholders by providing valuable information for managing efficiently their assets prior to and after catastrophic events on the basis of resilience. The survey was based on a questionnaire answered by experts on bridge and infrastructure engineering.
•Novel fragility models for scoured-critical bridges exposed to multiple hazards were generated•Rigorous FEM included the water-soil-bridge interaction under flooding and earthquakes•Failure modes ...for bridge components exposed to floods were described•Insights on the flood vulnerability of integral and bridges with bearings are provided•Consideration of uncertainties in scour formation enhance the reliability of risk assessment
Building resilient bridges, that are able to withstand multiple natural stressors with minimal damage and quickly restore their functionality is paramount to delivering climate-resilient transport infrastructure. Nevertheless, bridges are proven to be vulnerable to natural hazards, with floods and earthquakes being the main causes of failure. The available research and practice for assessing the vulnerability of river-crossing bridges is predominantly qualitative and therefore relies heavily on visual inspections, while ignoring important characteristics of the complex water-soil-bridge interaction. This is a knowledge gap that this paper aims to fill. This work provides novel fragility models for hydraulically induced stressors and/or combinations of hydraulic and seismic hazards. To achieve this, unique detailed two- and three- dimensional numerical models are employed, for a typical three-span prestressed box-girder river-crossing bridge. This paper is a primer on the vulnerability of flood-critical bridges as it models the entire water-soil-bridge system, taking into account critical hydraulic stressors (scour, debris accumulation, hydraulic forces), the uncertainty in scour hole formation, and all components of integral and isolated bridges: deck, bearings, piers and abutments, backfill, and the foundation soil. A detailed description of the damage modes for each component is given and sets of fragility curves for floods and combinations of hydraulic stressors and earthquakes are developed. The study concludes that integral bridges are in most cases more vulnerable to local scour than bridges with bearings, since the latter are more flexible and can therefore adapt to changes in their geometry. The opposite is true for global scour and/or seismic earthquake excitations. The generated fragility models are useful tools for quantitative risk assessment of transport systems and provide practical means in resilience-based asset management by owners and operators of transport infrastructure.
This dataset is related to the research paper entitled “Bridge-specific flood risk assessment of transport networks using GIS and remotely sensed data” published in the Science of the Total ...Environment. It provides the information necessary for the reproduction of the case study that was used for the demonstration and validation of the proposed risk assessment framework. The latter integrates indicators for the assessment of hydraulic hazards and bridge vulnerability with a simple and operationally flexible protocol for the interpretation of bridge damage consequences on the serviceability of the transport network and on the affected socio-economic environment. The dataset encompasses (i) inventory data for the 117 bridges of the Karditsa Prefecture, in Central Greece, which were affected by a historic flood that followed the Mediterranean Hurricane (Medicane) Ianos, in September 2020; (ii) results of the risk assessment analysis, including the geospatial distribution of hazard, vulnerability, bridge damage, and associated consequences for the area's transport network; (iii) an extensive damage inspection record, compiled shortly after the Medicane, involving a sample of 16 (out of the 117) bridges of varying characteristics and damage levels, ranging from minimal damage to complete failure, which was used as a reference for validation of the proposed framework. The dataset is complemented by photos of the inspected bridges which facilitate the understanding of the observed bridge damage patterns. This information is intended to provide insights into the response of riverine bridges to severe floods and a thorough base for comparison and validation of flood hazard and risk mapping tools, potentially useful for engineers, asset managers, network operators and stakeholders involved in decision-making for climate adaptation of the road sector.
The 2030 Sustainable Development Goals (SDGs) offer a blueprint for global peace and prosperity, while conserving natural ecosystems and resources for the planet. However, factors such as ...climate-induced weather extremes and other High-Impact Low-Probability (HILP) events on their own can devastate lives and livelihoods. When a pandemic affects us, as COVID-19 has, any concurrent hazards interacting with it highlight additional challenges to disaster and emergency management worldwide. Such amplified effects contribute to greater societal and environmental risks, with cross-cutting impacts and exposing inequities. Hence, understanding how a pandemic affects the management of concurrent hazards and HILP is vital in disaster risk reduction practice. This study reviews the contemporary literature and utilizes data from the Emergency Events Database (EM-DAT) to unpack how multiple extreme events have interacted with the coronavirus pandemic and affected the progress in achieving the SDGs. This study is especially urgent, given the multidimensional societal impacts of the COVID-19 pandemic amidst climate change. Results indicate that mainstreaming risk management into development planning can mitigate the adverse effects of disasters. Successes in addressing compound risks have helped us understand the value of new technologies, such as the use of drones and robots to limit human exposure. Enhancing data collection efforts to enable inclusive sentinel systems can improve surveillance and effective response to future risk challenges. Stay-at-home policies put in place during the pandemic for virus containment have highlighted the need to holistically consider the built environment and socio-economic exigencies when addressing the pandemic’s physical and mental health impacts, and could also aid in the context of increasing climate-induced extreme events. As we have seen, such policies, services, and technologies, along with good nutrition, can significantly help safeguard health and well-being in pandemic times, especially when simultaneously faced with ubiquitous climate-induced extreme events. In the final decade of SDG actions, these measures may help in efforts to “Leave No One Behind”, enhance human–environment relations, and propel society to embrace sustainable policies and lifestyles that facilitate building back better in a post-pandemic world. Concerted actions that directly target the compounding effects of different interacting hazards should be a critical priority of the Sendai Framework by 2030.
Harnessing vibrations in multifunctional nanostructured plates is pivotal to next-gen microsystems but necessitates understanding scale effects under multifield loading. Investigated in this work are ...the forced and unforced vibrations of multilayered piezoelectric nanoplates supported on a variable viscoelastic medium and loaded hygrothermo-electromechanically with functionally graded porous (FGP) cores. The viscoelastic foundation is supposed to demonstrate non-linear changes in both stiffness and damping characteristics in the x-coordinate direction. The goal is to improve the accuracy of the results by using the nonlocal strain gradient theory (NSGT) and the third-order shear deformation assumption (TSDA), which include the effects of hardening and softening materials. The FGP core layer considers four states of porosity distribution patterns. These porosity distributions are expected to change in both the in-plane and thickness directions. The governing partial differential equations resulting from Hamilton's principle can be reduced to a system of algebraic equations by applying the Galerkin method. The parametric studies evaluate the effects of several factors, such as the initial electric voltage, viscoelastic medium parameters, moisture rise, temperature changes, porosity distributions, FG index, nonlocal and strain gradient features, and boundary conditions, on the vibration response. The novelty lies in the incorporation of advanced theories, such as the NSGT and TSDT, which capture size-dependent effects and material hardening/softening phenomena. Additionally, the consideration of four distinct porosity distribution patterns in the FGP core layer provides insights into the influence of porosity gradients on the dynamic response. The proposed model can guide the design and optimization of multifunctional nanostructured plates for applications in next-generation microsystems, energy harvesting devices, and smart structures.
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•Novel traffic reinstatement and capacity restoration models for scour-damaged bridges.•Standardisation of damage per bridge component and functionality of scoured bridges.•High ...uncertainty in restoration task duration, dependencies and overlaps.•Duration of restoration tasks is twice the duration of functionality reinstatement.•Recovery models validated based on documented cases of scoured bridges.
Bridges are the most vulnerable assets of our transport networks. They are disproportionately exposed to and hit by multiple natural hazards, with flooding being the leading cause of bridge failures in the world. Their performance is constantly challenged by the combined effects of natural hazard stressors, e.g. flash floods, exacerbated by climate change, ageing, increasing traffic volumes and loads. Bridges are vulnerable to scour and other flood-related impacts, such as hydraulic forces and debris accumulation. In order to assess and quantify the resilience of flood-critical bridges and subsequently deploy bridge resilience models aiming at building resilience into transport networks, it is essential to use reliable fragility, capacity restoration and traffic reinstatement metrics and models. It is surprising that, despite the importance of bridges and their high vulnerability to hydraulic actions, there are no available recovery models. The latter can help quantify the pace of post-flood capacity and functionality gain for facilitating well-informed decision making for reliable prioritisation and efficient allocation of resources in transport networks. The main barrier is the nature and complexity of recovery actions, which encompass engineering, operational, owner resources and organisational challenges, among others. This paper, for the first time in the international literature, aims at filling this gap by generating a set of reliable recovery models that include both bridge reinstatement (traffic capacity) and restoration (structural capacity) models based on a detailed questionnaire that elicits knowledge from experts. Recovery models are then presented and validated for spread and deep foundations for a typical reinforced concrete bridge, including restoration task prioritisation and scheduling, inter-task dependencies, idle times, durations and cost ratios for different damage levels, as well as the evolution of traffic capacity after floods.
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