Digital technologies can enhance climate resilience of critical infrastructure

Climate Risk Management, Год журнала: 2021, Номер 35, С. 100387 - 100387

Опубликована: Дек. 22, 2021

Delivering infrastructure, resilient to multiple natural hazards and climate change, is fundamental continued economic prosperity social coherence. This a strategic priority of the United Nations Sustainable Development Goals (SDGs), World Bank, Organisation for Economic Co-operation (OECD), public policies global initiatives. The operability functionality critical infrastructure are continuously challenged by stressors, increasing demands ageing, whilst their interconnectedness dependencies pose additional challenges. Emerging disruptive digital technologies have potential enhance resilience providing rapid accurate assessment asset condition support decision-making adaptation. In this pursuit, it imperative adopt multidisciplinary roadmaps deploy computational, communication other technologies, tools monitoring systems. Nevertheless, these emerging remains largely unexploited, as there lack consensus, integrated approaches legislation in use. perspective paper, we discuss main challenges enablers climate-resilient identify how available roadmaps, e.g. Internet Things, twins, point clouds, Artificial Intelligence, Building Information Modelling, can be placed at service safer world. We show will lead enhanced resilience, delivering efficient reliable decision-making, proactive and/or reactive manner, prior, during after hazard occurrences. respect, significantly reduce uncertainties all phases evaluations. Thus, building aided underpin activities globally, contribute Net Zero target hence safeguard our societies economies. To achieve set an agenda, which aligned with relevant SDGs highlights urgent need deliver holistic inclusive standards legislation, supported coordinated alliances, fully utilise technologies.

Язык: Английский

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Resilience of aging structures and infrastructure systems with emphasis on seismic resilience of bridges and road networks: Review

Resilient Cities and Structures, Год журнала: 2022, Номер 1(2), С. 23 - 41

Опубликована: Июнь 1, 2022

Risk assessment and mitigation programs have been carried out over the last decades in attempt to reduce transportation infrastructure downtime post-disaster recovery costs. Recently, concept of resilience gained increasing importance design, assessment, maintenance, rehabilitation structures systems, particularly bridges networks, exposed natural man-made hazards. In field disaster mitigation, frameworks proposed provide a basis for development qualitative quantitative models quantifying functionality at various scales, including components, groups systems within networks communities. these frameworks, effects aging environmental aggressiveness must be explicitly considered, affecting structural performance civil systems. Significant efforts made incorporate risk into informed decision making decide how best use resources minimize impact hazards on This review paper is part efforts. It presents an overview main principles concepts, methods strategies, advances accomplishments life-cycle reliability, with emphasis seismic road networks.

Язык: Английский

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Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective

Reliability Engineering & System Safety, Год журнала: 2023, Номер 233, С. 109104 - 109104

Опубликована: Янв. 18, 2023

Язык: Английский

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A review of seismic resilience of shield tunnels

Tunnelling and Underground Space Technology, Год журнала: 2023, Номер 136, С. 105075 - 105075

Опубликована: Март 20, 2023

Язык: Английский

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Earthquake-based multi-hazard resilience assessment: a case study of Istanbul, Turkey (neighborhood level)

npj natural hazards., Год журнала: 2025, Номер 2(1)

Опубликована: Фев. 3, 2025

Язык: Английский

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A state-of-the-art decision-support environment for risk-sensitive and pro-poor urban planning and design in Tomorrow's cities

International Journal of Disaster Risk Reduction, Год журнала: 2022, Номер 85, С. 103400 - 103400

Опубликована: Дек. 29, 2022

In this Special Issue introductory paper, we present the Tomorrow's Cities Decision Support Environment (TCDSE). As negative impacts of natural hazards continue to escalate around world due increasing populations, climate change, and rapid urbanisation (among other factors processes), there is an urgent requirement develop structured operational approaches towards multi-hazard risk-informed decision making on urban planning design. This a particularly pressing issue for low-to-middle income countries, which are set be impacted ever more disproportionately during future natural-hazard events if "business as usual" urban-development approach continues unabated. Urban poor residents these countries will significantly suffer under risk-insensitive development trajectories. The proposed TCDSE addresses crucial challenge. It facilitates participatory, people-centred making, using state-of-the-art procedures physics-based hazard engineering impact modelling, integrating physical social vulnerability in unified framework, expressing consequences disasters across array stakeholder-weighted metrics that facilitate democratisation risk concept. purpose paper provide detailed description each component TCDSE, characterising related data inflows outflows between modules. We conclude with short end-to-end demonstration Tomorrowville virtual testbed. Individual components further dealt detail within subsequent papers Issue.

Язык: Английский

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Resilience of Critical Infrastructure Systems: A Systematic Literature Review of Measurement Frameworks

Infrastructures, Год журнала: 2022, Номер 7(5), С. 67 - 67

Опубликована: Май 2, 2022

Critical infrastructures such as transportation, power, telecommunication, water supply, and hospitals play a vital role in effectively managing post-disaster responses. The resilience of critical should be incorporated the planning designing phase based on risk assessment particular geographic area. However, framework to assess infrastructure (CIR) is variably conceptualised. Therefore, objective this study was critically appraise existing CIR frameworks developed since adoption Sendai Framework 2015 with hazard focus earthquakes. preferred reporting items for systematic reviews meta-analyses (PRISMA) method used selection 24 most relevant studies, these were analysed delineate frameworks, models, concepts. found that there are wide-ranging disparities among resilience, it has become key challenge prioritise resilience-based investment sector. Furthermore, attributes performance indicators, emergency aspects, damage need considered different disaster phases—ex-ante, during, ex-post—to improve long-term infrastructure. Subsequently, an integrated adaptable proposed proper decision making.

Язык: Английский

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Utilizing advanced machine learning approaches to assess the seismic fragility of non-engineered masonry structures

Results in Engineering, Год журнала: 2024, Номер 21, С. 101750 - 101750

Опубликована: Янв. 5, 2024

Seismic fragility assessment provides a substantial tool for assessing the seismic resilience of these buildings. However, using traditional numerical methods to derive curves poses significant challenges. These often overlook diverse range buildings found in different regions, as they rely on standardized assumptions and parameters. Consequently, may not accurately capture response various building types. Alternatively, extensive data collection becomes essential address this knowledge gap by understanding local construction techniques identifying relevant This is crucial developing reliable analytical approaches that can curves. To overcome challenges, research employs four Machine Learning (ML) techniques, namely Support Vector Regression (SVR), Stochastic Gradient Descent (SGD), Random Forest (RF), Linear (LR), probability collapse terms Peak Ground Acceleration (PGA). achieve objective, comprehensive input/output dataset consisting on-site collected from 646 masonry walls Malawi used. Adopted ML models are trained tested entire then again only most highly correlated features. The study includes comparative analysis efficiency accuracy each approach influence used analyses. (RF) technique emerges efficient deriving surveyed achieved lowest values evaluation metrics methods. scored Mean Absolute Percentage Error (MAPE) 16.8 %, Root Square (RMSE) 0.0547. results highlight potential particularly RF, derivation with proper levels accuracy.

Язык: Английский

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Pseudo‐dynamic testing, repairability, and resilience assessment of a large‐scale steel structure equipped with self‐centering column bases

Earthquake Engineering & Structural Dynamics, Год журнала: 2024, Номер 53(9), С. 2756 - 2781

Опубликована: Апрель 27, 2024

Abstract Recent destructive seismic events have underlined the need for increasing research efforts devoted to development of innovative seismic‐resilient structures able reduce seismic‐induced direct and indirect losses. Regarding steel Moment Resisting Frames (MRFs), inclusion Friction Devices (FDs) in Beam‐to‐Column Joints (BCJs) has emerged as an effective solution dissipate input energy while ensuring a damage‐free behavior. Additionally, recent studies demonstrated benefits implementing similar solutions Column Bases (CBs). In this context, authors recently experimentally investigated Self‐Centering CB (SC‐CB) aimed at residual drift reduction. Previous experimental tests only focused on response isolated SC‐CBs under cyclic loads. Conversely, present paper advances through campaign large‐scale structure equipped with proposed SC‐CBs, providing valuable insights into global structural improved repairability. A set eight Pseudo‐Dynamic (PsD) were conducted considering different records configurations structure. The results highlighted effectiveness minimizing interstory drifts protecting first‐story columns from damage, thus enhancing structure's resilience. Moreover, consecutive PsD allowed investigating reparation process restoring performance ‘undamaged’ An advanced numerical model was developed OpenSees validated against component‐level results. Incremental Dynamic Analyses finally performed investigate influence accounting record‐to‐record variability.

Язык: Английский

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Modeling Variability in Seismic Analysis of Concrete Gravity Dams: A Parametric Analysis of Koyna and Pine Flat Dams

Infrastructures, Год журнала: 2024, Номер 9(1), С. 10 - 10

Опубликована: Янв. 5, 2024

This study addresses the vital issue of variability associated with modeling decisions in dam seismic analysis. Traditionally, structural and simulations employ a progressive approach, where more complex models are gradually incorporated. For example, if previous levels indicate insufficient safety margins, advanced analysis is then undertaken. Recognizing constraints evaluating influence various methods essential for improving comprehension effectiveness assessments. To this end, an extensive parametric carried out to evaluate response Koyna Pine Flat dams using solution approaches model complexities. Numerical conducted 2D framework across three software programs, encompassing different system configurations. Additional complexity introduced by simulating reservoir dynamics Westergaard-added mass or acoustic elements. Linear nonlinear analyses performed, incorporating pertinent material properties, employing concrete damage plasticity latter. Modal parameters crest displacement time histories used highlight among selected procedures Finally, recommendations made regarding adequacy robustness each method, specifying scenarios which they most effectively applied.

Язык: Английский

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