Periodic Reporting for period 1 - READMODE (REliability and risk Assessment of flexible MOdular structures with vibration control DEvices in multi-hazard environments)
Berichtszeitraum: 2023-10-01 bis 2025-10-31
Across Europe, buildings and infrastructure are increasingly exposed to earthquakes, strong winds, and climate-driven extreme events. At the same time, there is a growing demand for rapid, sustainable, and modular construction solutions that reduce costs, material use, and environmental impact. Modular buildings—constructed from prefabricated units assembled on-site—offer major advantages in speed and sustainability. However, because these systems are often lighter and more flexible than conventional structures, they can be more sensitive to dynamic loads such as seismic shaking and wind-induced vibrations. In parallel, Europe is accelerating the deployment of renewable energy systems, including offshore wind turbines, which must operate safely under combined environmental hazards such as wind, waves, and seismic loading. Ensuring the reliability and resilience of these systems is critical for achieving climate neutrality and strengthening energy security. The project addressed these challenges by developing advanced methods to evaluate and improve the safety, reliability, and resilience of modular buildings and renewable energy structures under multiple hazards. Instead of relying only on traditional deterministic safety factors, the project adopted a probabilistic approach. This means explicitly accounting for uncertainties in material properties, geometry, connections, and loading conditions in order to compute failure probabilities and quantify risk in a transparent and scientifically rigorous way. The overall objectives were:
To compute the probability of structural failure of modular systems under dynamic loading within a comprehensive probabilistic framework.
To evaluate joint failure probabilities under multiple hazards (e.g. earthquake and wind), enabling more realistic risk assessment.
To quantify resilience and robustness, and to design optimized vibration control systems that enhance structural performance under extreme events.
By integrating structural dynamics, uncertainty quantification, and adaptive vibration control, the project provides a new pathway toward safer and more sustainable infrastructure systems. The expected impact includes improved design guidelines for modular construction, enhanced safety of renewable energy infrastructure, and reduced lifecycle environmental costs through risk-informed optimization. The project directly contributes to European priorities on climate adaptation, resilient infrastructure, and sustainable construction under the European Green Deal.
To compute the probability of structural failure of modular systems under dynamic loading within a comprehensive probabilistic framework.
To evaluate joint failure probabilities under multiple hazards (e.g. earthquake and wind), enabling more realistic risk assessment.
To quantify resilience and robustness, and to design optimized vibration control systems that enhance structural performance under extreme events.
By integrating structural dynamics, uncertainty quantification, and adaptive vibration control, the project provides a new pathway toward safer and more sustainable infrastructure systems. The expected impact includes improved design guidelines for modular construction, enhanced safety of renewable energy infrastructure, and reduced lifecycle environmental costs through risk-informed optimization. The project directly contributes to European priorities on climate adaptation, resilient infrastructure, and sustainable construction under the European Green Deal.
The project developed a comprehensive scientific framework to assess and enhance the reliability and resilience of modular buildings and renewable energy structures under dynamic and multi-hazard loading. The work combined structural dynamics, probabilistic modelling, uncertainty quantification, and vibration control engineering.
A first major activity consisted of developing high-fidelity numerical models of modular structural systems. These models explicitly represented the mechanical behavior of prefabricated modules, their interconnections, and floor-level degrees of freedom. Unlike conventional simplified approaches, the models captured the specific dynamic characteristics of modular assemblies, including flexibility at joints and possible torsional effects. This modelling effort provided the basis for accurate simulation of structural response under seismic and wind excitation. The second core activity focused on uncertainty quantification. Instead of treating material properties, geometric parameters, and loading conditions as fixed values, the project represented them as random variables. Monte Carlo simulation and advanced surrogate modelling techniques were used to propagate these uncertainties through the structural models. This enabled the computation of failure probabilities and the construction of fragility curves, which describe the likelihood of reaching damage states under increasing hazard intensity. A key achievement was the development of an efficient surrogate-based reliability framework. Because direct probabilistic simulations of complex structural models are computationally demanding, surrogate models were trained to approximate the structural response with high accuracy but significantly reduced computational cost. This approach allowed large numbers of simulations to be performed, making multi-hazard reliability assessment feasible in practical engineering contexts. The project then extended the analysis to multi-hazard scenarios, where structures are subjected to combined effects such as earthquake and wind loading. A joint probabilistic framework was formulated to compute combined failure probabilities, taking into account the interaction between hazards and structural uncertainties. This represents an advancement over traditional single-hazard assessments and provides a more realistic estimate of structural risk. Beyond reliability assessment, the project introduced resilience-oriented performance metrics. Instead of evaluating only whether a structure fails, the developed framework quantifies robustness and the ability to maintain functionality under extreme events. Reliability curves were interpreted as resilience indicators, enabling comparison between different design configurations and control strategies. Another major component of the work involved the design and optimization of vibration control systems. Novel adaptive control concepts were proposed to mitigate structural vibrations under both seismic and wind loading. Optimization algorithms were developed to determine optimal device parameters that maximize resilience under multi-hazard conditions. In addition, innovative concepts integrating energy harvesting with vibration control were formulated, allowing structural components to simultaneously dissipate energy and contribute to renewable power generation.
The final outcomes of the project include:
A validated probabilistic framework for computing failure probability and fragility of modular structures.
A joint multi-hazard reliability model capable of evaluating combined risk scenarios.
A resilience assessment methodology linking reliability to performance-based design.
Optimized vibration control strategies tailored for modular buildings and renewable energy structures.
Computational tools and modelling procedures that can be integrated into engineering practice.
Overall, the project advanced the state of the art in risk-informed structural design by combining uncertainty quantification, multi-hazard modelling, and adaptive control within a unified framework. These scientific achievements contribute to safer modular construction systems and more reliable renewable energy infrastructure, supporting the long-term goal of resilient and sustainable built environments.
A first major activity consisted of developing high-fidelity numerical models of modular structural systems. These models explicitly represented the mechanical behavior of prefabricated modules, their interconnections, and floor-level degrees of freedom. Unlike conventional simplified approaches, the models captured the specific dynamic characteristics of modular assemblies, including flexibility at joints and possible torsional effects. This modelling effort provided the basis for accurate simulation of structural response under seismic and wind excitation. The second core activity focused on uncertainty quantification. Instead of treating material properties, geometric parameters, and loading conditions as fixed values, the project represented them as random variables. Monte Carlo simulation and advanced surrogate modelling techniques were used to propagate these uncertainties through the structural models. This enabled the computation of failure probabilities and the construction of fragility curves, which describe the likelihood of reaching damage states under increasing hazard intensity. A key achievement was the development of an efficient surrogate-based reliability framework. Because direct probabilistic simulations of complex structural models are computationally demanding, surrogate models were trained to approximate the structural response with high accuracy but significantly reduced computational cost. This approach allowed large numbers of simulations to be performed, making multi-hazard reliability assessment feasible in practical engineering contexts. The project then extended the analysis to multi-hazard scenarios, where structures are subjected to combined effects such as earthquake and wind loading. A joint probabilistic framework was formulated to compute combined failure probabilities, taking into account the interaction between hazards and structural uncertainties. This represents an advancement over traditional single-hazard assessments and provides a more realistic estimate of structural risk. Beyond reliability assessment, the project introduced resilience-oriented performance metrics. Instead of evaluating only whether a structure fails, the developed framework quantifies robustness and the ability to maintain functionality under extreme events. Reliability curves were interpreted as resilience indicators, enabling comparison between different design configurations and control strategies. Another major component of the work involved the design and optimization of vibration control systems. Novel adaptive control concepts were proposed to mitigate structural vibrations under both seismic and wind loading. Optimization algorithms were developed to determine optimal device parameters that maximize resilience under multi-hazard conditions. In addition, innovative concepts integrating energy harvesting with vibration control were formulated, allowing structural components to simultaneously dissipate energy and contribute to renewable power generation.
The final outcomes of the project include:
A validated probabilistic framework for computing failure probability and fragility of modular structures.
A joint multi-hazard reliability model capable of evaluating combined risk scenarios.
A resilience assessment methodology linking reliability to performance-based design.
Optimized vibration control strategies tailored for modular buildings and renewable energy structures.
Computational tools and modelling procedures that can be integrated into engineering practice.
Overall, the project advanced the state of the art in risk-informed structural design by combining uncertainty quantification, multi-hazard modelling, and adaptive control within a unified framework. These scientific achievements contribute to safer modular construction systems and more reliable renewable energy infrastructure, supporting the long-term goal of resilient and sustainable built environments.
The project delivers several advances beyond the current state of the art in structural reliability, multi-hazard assessment, and vibration control of modular and renewable energy structures. Traditional structural design methods typically rely on deterministic safety factors and single-hazard analysis. In contrast, this project introduced an integrated probabilistic framework that explicitly quantifies uncertainties in materials, geometry, connections, and loading. By computing failure probabilities rather than relying solely on fixed safety margins, the project enables more transparent and risk-informed decision-making. This represents a conceptual shift from conservative design assumptions toward scientifically quantified reliability. A major scientific advance is the development of an efficient surrogate-based reliability framework tailored for modular structures. Modular systems possess distinct dynamic characteristics due to prefabricated units and inter-module connections, which are often simplified in conventional analyses. The project combined high-fidelity dynamic modelling with surrogate modelling techniques to significantly reduce computational demand while maintaining accuracy. This makes large-scale probabilistic simulations feasible for real engineering applications and multi-hazard scenarios. Another key advancement is the formulation of a joint multi-hazard reliability framework. Infrastructure systems are increasingly exposed to interacting hazards such as earthquake and wind, or wind and wave loading in offshore environments. Existing design approaches often treat these hazards separately. The project developed a methodology to compute joint failure probabilities, accounting for hazard interaction and structural uncertainty. This provides a more realistic assessment of structural risk and supports climate-adaptive engineering strategies. Beyond reliability, the project advanced resilience-oriented structural assessment. Instead of focusing only on whether a structure fails, the developed framework quantifies robustness and performance degradation under extreme events. By linking reliability curves with resilience metrics, the project enables comparison of alternative design configurations and control strategies based on their ability to maintain functionality. In the field of structural control, the project proposed innovative adaptive vibration mitigation concepts, including devices capable of operating effectively under different types of dynamic excitation. Furthermore, novel concepts integrating vibration control with energy harvesting were developed. These multifunctional systems aim to enhance structural safety while contributing to renewable energy generation, thereby supporting sustainable infrastructure development.
Overview of Results: The main results achieved include: i) A probabilistic computational framework for modular structures capable of calculating failure probability and fragility under dynamic loading, ii) A surrogate-based modelling approach enabling efficient large-scale uncertainty propagation, iii) A joint multi-hazard reliability assessment methodology, iv) A resilience quantification framework suitable for performance-based design, v) Optimized adaptive vibration control concepts, including integrated energy harvesting solutions, vi) Prototype-level innovation concepts supported by analytical and numerical validation.
Potential Impact and Conditions for Further Uptake
The results have significant potential impact in several domains:
Engineering Practice and Design Guidelines: The probabilistic and resilience-based frameworks can inform future updates of structural design methodologies, particularly for modular construction and lightweight systems. For widespread adoption, further collaboration with standardization bodies and engineering associations would be beneficial.
Demonstration and Pilot Projects: To accelerate uptake, demonstration projects involving real modular buildings or renewable energy installations would be valuable. Experimental validation and field implementation would help bridge the gap between research and industry practice.
Commercialization and Intellectual Property Support: The vibration control and energy-harvesting concepts provide opportunities for patent protection and technology transfer. Support for prototype development, testing, and industrial partnerships will be essential to bring these innovations closer to market readiness.
Access to Finance and Industrial Partnerships: Collaboration with modular construction companies, offshore wind developers, and engineering consultancies will be crucial to translate computational frameworks into commercial software tools and deployable hardware solutions.
Further Research and Internationalization: Additional research can extend the framework to other hazard combinations and infrastructure types. International collaboration will enhance validation across different regulatory environments and hazard conditions.
Supportive Regulatory and Standardization Frameworks: The transition toward resilience-based and probabilistic design approaches requires gradual integration into building codes and engineering standards. Engagement with regulatory bodies will be important to support this evolution.
Overall, the project moves beyond incremental improvement by integrating uncertainty quantification, multi-hazard assessment, and adaptive control into a unified framework for resilient infrastructure. Its results provide a scientifically robust foundation for next-generation design methodologies, supporting Europe’s long-term objectives in climate adaptation, sustainable construction, and renewable energy reliability.
Overview of Results: The main results achieved include: i) A probabilistic computational framework for modular structures capable of calculating failure probability and fragility under dynamic loading, ii) A surrogate-based modelling approach enabling efficient large-scale uncertainty propagation, iii) A joint multi-hazard reliability assessment methodology, iv) A resilience quantification framework suitable for performance-based design, v) Optimized adaptive vibration control concepts, including integrated energy harvesting solutions, vi) Prototype-level innovation concepts supported by analytical and numerical validation.
Potential Impact and Conditions for Further Uptake
The results have significant potential impact in several domains:
Engineering Practice and Design Guidelines: The probabilistic and resilience-based frameworks can inform future updates of structural design methodologies, particularly for modular construction and lightweight systems. For widespread adoption, further collaboration with standardization bodies and engineering associations would be beneficial.
Demonstration and Pilot Projects: To accelerate uptake, demonstration projects involving real modular buildings or renewable energy installations would be valuable. Experimental validation and field implementation would help bridge the gap between research and industry practice.
Commercialization and Intellectual Property Support: The vibration control and energy-harvesting concepts provide opportunities for patent protection and technology transfer. Support for prototype development, testing, and industrial partnerships will be essential to bring these innovations closer to market readiness.
Access to Finance and Industrial Partnerships: Collaboration with modular construction companies, offshore wind developers, and engineering consultancies will be crucial to translate computational frameworks into commercial software tools and deployable hardware solutions.
Further Research and Internationalization: Additional research can extend the framework to other hazard combinations and infrastructure types. International collaboration will enhance validation across different regulatory environments and hazard conditions.
Supportive Regulatory and Standardization Frameworks: The transition toward resilience-based and probabilistic design approaches requires gradual integration into building codes and engineering standards. Engagement with regulatory bodies will be important to support this evolution.
Overall, the project moves beyond incremental improvement by integrating uncertainty quantification, multi-hazard assessment, and adaptive control into a unified framework for resilient infrastructure. Its results provide a scientifically robust foundation for next-generation design methodologies, supporting Europe’s long-term objectives in climate adaptation, sustainable construction, and renewable energy reliability.