Heatwaves in Southern Europe are intensifying in frequency, duration and severity, with heat-related mortality concentrated among elderly residents in poorly insulated homes without access to cooling. A key driver is indoor overheating in post-war social housing. Assessing thermal resilience of such dwellings requires future weather data capable of representing extreme heat, yet no consensus exists on which generation method is most reliable — and resilience assessments are typically evaluated against comfort criteria developed for healthy adults rather than thresholds reflecting elderly physiological stress.

This thesis develops a building performance simulation workflow to assess the thermal resilience of a post-war Mediterranean social housing block in Rome (Laurentino 38) under future extreme heat, using Standard Effective Temperature (SET) evaluated against health-based thresholds for elderly and vulnerable occupants. Two state-of-the-art datasets are compared across three climate periods under RCP8.5: dynamically downscaled RCM-based Heatwave Years and morphed future Typical Meteorological Years, both from the same CORDEX CMIP5 model chain.

The results show that weather data choice has a fundamental and growing impact on resilience conclusions. Both datasets remain within acceptable limits in the current climate. By 2050, the RCM dataset already shows 35.7% of occupied hours exceeding the elderly limited-adaptation threshold (26.7°C SET), while the morphing dataset remains at zero. By 2080, this divergence is extreme: 60.7% exceedance under RCM versus near-zero under morphing — a false-negative resilience assessment for the same building under identical simulation conditions. Threshold choice proved equally decisive: the same simulation produces near-zero exceedance against a healthy-adult standard but 60.7% against the elderly threshold. Passive measures substantially reduced thermal stress but proved insufficient under long-term RCM conditions, pointing to active cooling as a necessary complement. A solar radiation misassignment error was also identified and corrected in the published Annex 80 Rome files. ... Read more

Urban neighbourhoods face climate risks from pluvial flooding and heatwaves which can be tackled using blue green infrastructure (BGI) interventions, yet existing BGI design tools lack the capacity to evaluate multi-hazard performance parametrically at the design stage.

This study develops and deploys an integrated parametric workflow combining FastFlood flood simulation and ENVI-met microclimate modelling within a Grasshopper environment, enabling systematic variation of BGI design parameters and simultaneous assessment of flood depth, flow velocity, and daytime and evening outdoor thermal comfort assess PET across four BGI feature types: trees, shrubs, surfaces, and water bodies. Performance assessment is structured around the IPCC risk framework covering sensitivity to flood, sensitivity to heat, and multi-hazard adaptive capacity. This identifies
which BGI design parameters most influence multi-hazard performance and under what conditions. Results show that surface roughness is the dominant flood parameter, trees are the dominant daytime heat mitigation feature, and trade-offs exist between hazard domains. These trade-offs confirm that BGI design decisions cannot be reduced to single-hazard optimization. A TOPSIS-based multicriteria strategy ranking framework is applied to translate performance evidence into comparative design guidance, demonstrating that strategy preferences are sensitive to criterion weights, particularly when adaptive capacity indicators are introduced.

The research concludes that a parametric BGI workflow is both necessary and feasible for evidence-informed neighbourhood-scale design, and that the integration of a digital workflow, multi-hazard performance analysis, and multi-criteria decision analysis constitutes a replicable methodological foundation for climate-adaptive urban design. ... Read more

The ever increasing frequence and destructiveness of wildfires across the globe calls for accurate interpretation of the underlying conditions to enhance data-driven mitigation strategies. While deep learning techniques have produced valuable results in both prediction of wildfire ignition as well as its spread, the abstraction of data into the interpretation of a generalized risk of occurrence remains largely uninvestigated. This thesis represents a novel approach directed at solving this challenge by leveraging a spatio-temporal transformer network. By combining multi-modal satellite imagery in an early-fusion attention arcitecture, along with the explicit temporal and spatial embedding of spatial and dynamic datasets, the here proposed transformer architecture STViT (Spatio-temporal Vision Transformer) abstracts probabilistic risk of fire occurrence from deterministic burn records. A progressive resolution-scaling decoder transfers embedded variables into a continuous risk map, optimized by a Weighted Binary Cross-Entropy loss function, referencing historical burn records of the MODIS instrument.

Results validate the STViT architecture's capacity to successfully suppress noise and capture both seasonal wildfire trends as well as an understanding of natural fire barriers in waterbody regions. Investigations into the best applicable context window reveal a 3-day sample extent to provide the best accuracy in forecasting a 14-day prediction window, managing to contain $70 percent$ of fire events in $20 percent$ of its most risk-prone predicted area. A horizon stress test into the error produced by enhancing lead-time proves the model to retain a high predictive skill for up to 5 days after which sharp accuracy degradation is shown. A comprehensive discussion of ablation studies demonstrates the model to be exercising balanced feature reliance without mathematical shortcuts. By investigating seasonal reliance on features, results indicate dominant reliance during fire-prone months on land surface temperature and a combination of terrain data. NDWI proves to be a more reliable proxy of fuel moisture as compared to NDVI. Finally, this work illustrates high-dimensional spatio-temporal embedding spaces to successfully capture a wide array of climate conditions, making it a valuable asset for wildfire management. ... Read more

Driven by climate change, the increasing frequency and intensity of flood events impose growing risks on urban infrastructure. To quantify these projected risks, conventional flood risk assessments rely on generic, univariate depth-damage curves that assume a pristine building stock. As a result, these methods systemically underestimate the vulnerability of historic unreinforced masonry dwellings that exhibit pre-existing structural degradation, exposing a critical scale gap between mesoscale risk modelling and microscale structural engineering physics. To bridge this gap, this thesis develops a multivariate, state-dependent probabilistic vulnerability framework that integrates component-level structural capacities with sociotechnical recovery timelines. The framework is applied to two residential case study locations, which reveals that initial degradation shifts damage onset to lower flood depths. Mean repair costs yield a 5 to 8 percentage point divergence in median repair costs. Crucially, crossing into extensive structural damage triggers compounding procurement and permitting delays that severely elevate re-occupancy downtime, extending community displacement from two months to over a year. While component adaptation mitigates direct interior losses, preflood structural restoration is more effective in reducing median re-occupancy downtime by up to 40.7%. This framework establishes a scalable tool to improve current flood risk assessments and enable targeted climate adaptation and heritage preservation investments within ageing urban environments. ... Read more

Climate change is increasing the frequency and severity of heatwaves and windstorms, shifting the focus of façade design from energy efficiency and sustainability towards climate resilience. Façades sit at the boundary between the indoor environment and an increasingly hostile climate, and they are now expected to deliver thermal comfort under extreme heat and to retain structural integrity under extreme wind in a single, coherent design. Current façade design workflows, however, lack the computational efficiency and the multi-hazard framework necessary to systematically balance the non-linear trade-offs between thermal and wind resilience.

Three gaps in current practice motivate this work. First, thermal and wind hazards are typically evaluated separately and combined only after the design has been fixed, which prevents trade-offs from being navigated generatively. Second, the dynamic simulations required for both hazards (EnergyPlus and CFD) are too computationally expensive to be embedded inside a design exploration loop, forcing designers to rely on a few pre-selected variants. Third, the literature offers resilience indicators for each hazard but provides little guidance on how to recast them into a single, simulation-ready, comparable form that can drive an optimisation.

To address these gaps, this thesis develops and tests a data-driven workflow that links eleven façade design parameters to thermal and wind resilience metrics. The parameters comprise four aperture ratios, four shading depths, two window-subdivision ratios, and the outer-pane glass thickness. Hazard-specific simulations are coupled with a resilience quantification framework that translates literature-based indicators into simulation-ready, normalised resilience scores on [0, 1] for both hazards. A Latin Hypercube Sampling dataset is generated across the eleven-variable design space and explored through correlation, feature-importance, and Sobol sensitivity analyses to identify the drivers of each hazard. Because the underlying simulations are too expensive to evaluate inside an optimisation loop, a random forest surrogate model is trained on this dataset to predict the two resilience scores in near-real time, and the surrogate is embedded inside an NSGA-II multi-objective optimisation routine that generates Pareto-optimal façade designs making cross-hazard conflicts and synergies explicit.

The workflow is illustrated on De Centrale IJburg, a residential case study located in the IJburg district of Amsterdam, the Netherlands. The building has a footprint of approximately 32 × 20 m and a height of approximately 20 m, and the analysis uses climate data and building-code references relevant to the Dutch context. The results show that thermal and wind resilience engage disjoint subsets of the design space: thermal performance is governed primarily by the orientation-specific apertures and the South shading depth, while wind performance is governed almost entirely by the window subdivision parameters. This separation produces a Pareto front with a clear knee region in which both objectives can be jointly maximised. The top-ranked Pareto solutions share a coherent geometric signature combining moderate apertures across all four orientations, deeper shading on the North and East orientations, and the thicker outer-pane glass option.

By translating high-level EU climate adaptation targets into a practical, Grasshopper-based design tool, this thesis contributes to resilience-based design practice and demonstrates how multi-hazard resilience can be treated as a generative design objective embedded within the optimisation process, rather than as a separate evaluation step applied only after the design is fixed. ... Read more

As populations continue to grow, cities also continue to densify and expand. In this process, natural surfaces are increasingly replaced by impervious surfaces, which reduce the ability of rainwater to infiltrate into the ground. This increases pluvial flood risk and shows the need to rethink how urban areas are built. One way to do this is by making room for more natural areas within the urban fabric. However, in dense cities where space is limited, these areas also need to perform multiple functions. Blue-Green Infrastructure (BGI) offers this form of spatial adaptation by combining rainwater regulation with other urban benefits. While some BGI strategies are applied at the building scale, this research focuses on ground-based BGI adaptation: strategies applied to open spaces and ground surfaces at the urban scale.

Ground-based BGI adaptation is often evaluated through its ability to reduce flood hazard in general. However, when adaptation resources and available urban space are limited, it becomes important to ask where adaptation can create the most meaningful improvement. This is why a more targeted receptor-based perspective is needed. Among the many urban receptors affected by flooding, this research focuses on buildings and examines how building flood-resilience improvement can be understood through an urban adaptation lens.

Drawing on the idea of ‘Grounded Resilience’, the study explores how building flood-resilience assessment can be used to ground the spatial design of ground-based BGI adaptation strategies. To achieve this, the research develops a Grasshopper-based simulation workflow that integrates rainwater simulation, BGI design evaluation, and building-level resilience assessment based on building attribute data. This enables area-level evaluation based on data-driven differences between buildings within a single design environment.

The workflow is tested in the Lijnbaan area in Rotterdam. The results show that the workflow enables the comparison of ground-based BGI adaptation scenarios through indicators including absorbed runoff volume, changes in flood depth, differences in building resilience scores, and runoff path visualisation. By linking site runoff behaviour with building resilience outcomes, the workflow supports early-stage design decision-making by helping designers identify where ground-based BGI adaptation can deliver the greatest local resilience improvements and where adaptation efforts should be prioritised. ... Read more

Türkiye faces a dual challenge: high seismic vulnerability and large-scale construction and demolition waste. In cities such as Istanbul, ageing reinforced concrete residential buildings remain exposed to significant seismic risk. While ongoing urban transformation continues to generate large quantities of concrete and brick rubble. Seismic assessment and retrofit procedures are typically carried out building-by-building, making this process time-intensive and difficult to scale across the many vulnerable structures. Additionally, construction and demolition waste is still mostly directed to landfills, despite its potential as a material resource for structural strengthening.

This thesis develops a design framework in which seismic retrofitting is approached as both a structural assessment problem and a material supply problem. This framework is positioned behind the logic that the vulnerable building stock is assessed as the target of seismic strengthening, while demolition waste from the same urban transformation context is investigated as a potential resource for producing the retrofit components. In this way, the retrofit demand is defined by the structural workflow, while the material workflow explores how this demand could be supplied through locally available recycled concrete and brick aggregates, making this vulnerable building stock part of the material cycle that can support renewed seismic resilience

The research focuses on a representative Turkish building typology: mid-rise reinforced concrete moment-resisting frame apartment buildings. A survey-based workflow is proposed in which on-site building data is collected through a structured assessment form and translated into a parametric Grasshopper model. This model generates a simplified building geometry, calculates seismic loads using an equivalent static approach, and supports structural evaluation through Karamba3D analysis combined with analytical capacity checks in accordance with the relevant Turkish and European structural codes. These checks identify key vulnerability parameters, including excessive inter-storey drift and insufficient member capacity.

The identified vulnerabilities guide the choice of retrofit intervention, which is supported through a designer-led selection of suitable strategies, such as column jacketing or shear wall interventions. These types of interventions create the link between the two research tracks: the structural workflow defines the retrofit need while the material workflow explores how this need could be met through modular components made from recycled construction and demolition waste.

For this purpose, concrete and brick aggregates are processed into recycled aggregate inputs for modular retrofit components for column jacketing and shear wall interventions. Supported by a designed recycling process aimed at reducing impurities in the waste stream. The material investigation therefore supports the structural workflow by translating the selected retrofit strategies into a more resource-efficient and accessible supply system.

The result is a design-driven proof of concept for a faster, typology-based, and resource-aware retrofit workflow. In which the structural parametric workflow generates a retrofit demand by identifying what fails, where, by how much, directly informing which interventions are needed where to prevent collapse, while the material track designs the whole system of supplying locally sourced retrofit elements derived from demolition waste. ... Read more

With climate change increasing the frequency and severity of heat waves in the Netherlands, the risk of buildings overheating poses a critical challenge to occupant health, energy efficiency, and sustainability goals. Despite regulatory progress on reducing energy-related emissions, current renovation practices often overlook overheating issues.
This study addresses this gap by integrating heat hazard loss as cost into a probabilistic cost-benefit analysis to assess the long-term benefits of improving resilience. The method can assist in decision-making when retrofitting by informing about the financial feasibility of mitigation, including the impact of recurring extreme events.
In a case study, renovation alternatives were tested on a housing unit in Rotterdam. The performance was evaluated considering energy efficiency, heat resilience, and carbon footprint. Using the developed framework, the distribution of costs and cost recovery under climate uncertainty were investigated.
The findings show that while passive cooling measures can significantly reduce overheating, their cost recovery is limited under current climate conditions. Still, the financial analysis shows that resilience improvements prevent operational cost from overshooting in the worst-case scenarios. Finally, integrating heating with cooling in a cost-benefit analysis can disclose counteracting measures that reduce the net benefit.
The study demonstrates that further investigation into cost-effective climate adaption is crucial to building future-proof environments. ... Read more

For a long time, timber has taken the backseat to steel and concrete for largescale structures, but due to sustainability interests many developments have been made to improve its less desirable qualities. With the introduction of engineered wood products, large timber sections required for fire resistant design became economical and the timber structural behavior became more reliable. However, there are still many challenges when it comes to the seismic design of tall timber structures. Current modelling strategies are time-consuming to implement, provide inconsistent results, and do not account for the passive parameters which impact the seismic behavior of the structure throughout its lifetime. Since timber is a natural material, it is subject to varying levels of moisture content which impacts its stiffness. Furthermore, given the lightweightedness of timber structures (compared to concrete or steel alternatives), any changes to the mass distribution of the structure drastically changes its dynamic response.
This research project develops a computational workflow for the seismic analysis of tall timber structures which integrates the seismic analysis model seamlessly into the main design workflow, simplifies the process for setting the parameters in a semi component-level model for seismic analysis, includes a lifetime analysis option which considers the variables which impact the structural performance of the structure over time, and provides the engineer with component-level data over time. Python class objects are used to develop this computational workflow inside of the Grasshopper environment for Rhino, using the OpenSeesPy library for analysis. It follows the analysis standards provided by the (recent drafts of the) Eurocodes and supporting research papers. It has been developed to align with the most prominent tall timber construction types, as defined through the literature review. The analysis script utilizes the modelling strategy put forth by Rinaldi et al. (2021) to determine the effective stiffness of a cross-laminated timber wall, and its implementation was validated with a comparative analysis to the results of that research. The implementation of the full workflow and its impact on the design process is demonstrated through a case study, with results confirming the importance of including lifetime variables for analysis. This research increases the timeframe of analysis that the engineer can perform on tall timber structures such that the initial structural design can be informed by future predicted events, allowing for more resistant designs. ... Read more

This thesis focuses on using MARL as a decision tool for post-earthquake repair scheduling of interdependent infrastructure. MARL is a multi-agent ML paradigm which combines traditional ML research and game-theoretical approaches. Given the relative increase in natural disaster frequency and the lack of available post-disaster tools such tools are crucial in increasing the climate resilience of cities. Given the stochastic nature of earthquake events and subsequent losses, MARL can be helpful in navigating this uncertainty and finding preferable joint policies.The methodology involves multi-scenario-based seismic hazard assessment, stochastic fragility modelling and prediction of several direct and indirect losses to aggregate them into a holistic community resilience metric. This is then used to compute the instantaneous and cumulative recovery resilience loss values. The tested approach uses two custom built test-beds of 4 and 30 components, and MARL is compared against baseline solvers, including random and importance-based policies. Value Decomposition Network with Parameter Sharing (𝑉𝐷𝑁 − 𝑃𝑆), Q-Learning with Mixer Network and Parameter Sharing (𝑄𝑀𝐼𝑋 − 𝑃𝑆), Deep Centralised Multi-Agent Actor Critic (𝐷𝐶𝑀𝐴𝐶) are the algorithms tested. 𝑉𝐷𝑁 and 𝑄𝑀𝐼𝑋 are shown to perform similarly to each other and sub-optimally relative to 𝐷𝐶𝑀𝐴𝐶. 𝐷𝐶𝑀𝐴𝐶 is shown to match importance-based policies when considering full recovery, but convincingly outperforms all other 𝐷𝑅𝐿 methods and importance-based policies when considering partial recovery. This shows that 𝐷𝐶𝑀𝐴𝐶 and 𝐷𝑅𝐿 more generally is effective at swift early recovery by prioritising components that contribute most to community functionality. ii ... Read more

The growing complexity of modern façade systems and the increasing use of combustible materials highlight a pressing need to evaluate not only fire resistance but also fire resilience in façade design. This study addresses critical gaps in façade fire resilience assessment, particularly the absence of methodologies that incorporate both damage progression and post-fire recovery potential. To fill this gap, the research formulates a central question: How can the fire resilience of façade systems be assessed to evaluate their ability to maintain structural integrity and recover functionality after fire exposure?
A two-phase methodology was adopted. First, a quantitative damage assessment was performed using a one-dimensional heat transfer simulation. This model, governed by the standard fire and implemented via the finite difference method, simulates temperature evolution in multi-layered façade assemblies. Damage states were classified based on critical temperature thresholds, enabling the computation of vulnerability scores over different fire durations. This method was selected due to its computational efficiency and its solid foundation in fire engineering literature, making it well-suited for early-stage design comparisons. In the second phase, resilience was evaluated through a qualitative expert survey focusing on repairability and recoverability, as the lack of empirical post-fire data necessitated expert-based evaluation. Experts assessed post-fire conditions of façade materials and components in terms of ease of repair, repair duration, cost, and likelihood of restoring performance.
The integration of these two methods provides a holistic framework for evaluating façade fire resilience by linking thermal vulnerability with practical recovery insights. The framework is further developing through a preparation phase, which also serves as its validation by comparison with existing research results. This study contributes a novel perspective to façade design, enabling stakeholders to identify fire-resilient systems that balance thermal performance, structural robustness, and post-fire recoverability.
... Read more

Disasters, both natural and man-made, displace millions of people worldwide every year, necessitating an urgent need for shelter that should not only be safe and habitable but also adaptable to the diverse needs of displaced communities.

The design and deployment of disaster relief shelters face numerous challenges, including rapid deployment needs, environmental and cultural adaptability, sustainability, and the psychological well-being of the occupants. Traditional approaches often result in shelters that are slow to deploy, inadequately adapted to local conditions, or environmentally unsustainable. Furthermore, they frequently overlook the potential of involving affected communities in the shelter design process, missing opportunities for empowerment and better alignment with user needs.

Hence, why this thesis aimed to create an environment for people to design and manufacture their own customizable shelters with local products and culture in mind and without the need for expert intervention. Central to this approach is the design of a modular lightweight structure made with Plywood able to be set up by just two individuals without requiring large machinery. A structural analysis is conducted using the plugin Karamba 3D in Grasshopper, while verification is done through custom Python scripts within the same environment adhering to the Eurocode EN-1995.

To enhance user autonomy in shelter design, this thesis also explored the potential computational design offers as an approach to the optimization of shelter for specific environmental and contextual conditions as well as user requirements. Such as the ability to with a parametric model of the structure to iterate between numerous different options quite quickly. Giving the user the freedom to make it fit with their wishes without compromising structural integrity. In combination with digital fabrication technologies such as CNC-routing that enable the rapid production of each custom component as well as the addition to make use of the concept of Makerspaces, or similar environments where these tools like these are made available to anyone it can further democratize shelter design and production.

To further empower communities an online environment is developed to bring all of this together. Build using Viktor in combination with Grasshopper and Rhino the platform allows users to customize their shelter in both layout and materials and the rest is handled by the application, the structural analysis, optimization and generation of a digital 3D model. Which is then translated into the necessary fabrication files and information they need to set up their shelter using local materials and production. Fostering a sense of ownership while ensuring sustainability, adaptability and structural integrity.
... Read more

The escalating challenges caused by the climate change, notably floods and heatwaves, highlights the urgent need for robust resilience strategies in infrastructure and urban ecosystems. this research identifies critical gaps in existing methodologies and tools for assessing resilience, particularly during extreme events. Key issues include the absence of specialized tool for facade resilience quantification, limited multi-hazard assessment methodologies and a scarcity of quantitative methods in existing literature. In order to fill these gaps, this study formulates a research question: How can we identify the optimal facade combination that is resilient against heatwaves and floods?

A quantitative approach is employed, integrating an interdisciplinary perspective that encompasses structural design, facade design, climate design and hazard engineering. The methodology involves an extensive literature review, computational simulations, machine learning models, sensitivity analysis and resilience matrix for quantification of flood and heatwaves resilient facade system.

This study fills crucial gaps by offering a framework to assess facade resilience against these hazards. It identifies influential facade parameters and primary hazard stressors, crucial for informed decision-making by designers and engineers. The study culminates in a resilience quantification for multi-hazard assessment, empowering stakeholders to design resilient facade systems tailored to specific environmental contexts. The research findings contribute to advancing knowledge in building facade resilience, offering practical guidance for enhancing resilience in the face of evolving environmental challenges. ... Read more

In response to global climate change and the increasing frequency of extreme natural hazards, an early intervention flood risk assessment methodology has been developed to assess damage at the building component level. This approach allows for the precise identification of vulnerable structural components and localized redesigns, leading to more cost-effective and safer structural solutions. The focus of this paper is on quantifying flood damage to components and visualizing the results, with two main objectives: 1) quantifying the damage and 2) interactive visualization.
Hydrodynamic simulations of compound floods under future climate scenarios are performed to apply the quantitative results at the micro level. Using future climate scenarios obtained by perturbing atmospheric data with a regional climate model, the top 24 hours of flood-driven data are selected to create inundation maps. Vulnerability curves for each material are plotted, taking into account the sensitivity of the component materials to water. Based on the water depth at each point, the failure probability is determined. This method of quantifying component vulnerability provides new insights into micro-level flood damage.
Finally, an integrated BIM-GIS model is constructed, and the damage level and distribution are displayed on the ArcGIS Pro platform. This allows different stakeholders to intuitively obtain damage level information. Users can customize their view, for example, by focusing solely on the damage to first-floor exterior windows or by examining the damage levels of components and buildings under different intensity flood ratings. ... Read more

This master thesis rigorously explores the integration of a genetic algorithm-based workflow in the design and optimization of a passive fixed shading system utilizing ETFE cushion panels, with the objective of enhancing the thermal resilience of an existing building envelope. The case study focuses on a mid-rise office building located in the port of Athens, Greece. The central research question addressed is: "How can a genetic algorithm-based workflow be effectively employed in the multi-objective optimization of a shading system to improve the energy efficiency of an existing building envelope?"

To answer this question, the research investigates four interconnected domains: ETFE double skin structures, resilience quantification, multi-criteria decision-making approaches with genetic algorithms, and the analysis of the case study building facade system. The study centers on the preliminary design phase of the shading system, highlighting its potential as a retrofit solution for existing infrastructures challenged by rising temperatures.

The outcomes of this research include the development of a versatile workflow for evaluating the energy performance of existing buildings, facilitating interdisciplinary feedback within a design team, and applying multi-objective optimization to design problems. This work provides a comprehensive framework for integrating advanced computational methods in architectural design, thereby contributing to the improvement of building energy efficiency and thermal resilience. ... Read more

Curtain-wall systems have become increasingly common in present-day architecture.
They can be produced with high-efficiency qualities selected by the architect or façade
engineer, the most essential of which are excellent strength-to-weight ratio, functionality
requirements, component material recyclability, transparency, and comprehensive
aesthetic attributes.(Baniotopoulos et al., 2016) Over the last decade, much research has
been conducted to produce performance-based earthquake resilient structures and
façades. This research aims to explore the integration of timber and aluminium suspended
façade systems within environments characterized by these extreme conditions. On
the first part of the research thesis, the focus will be on developing a comprehensive
understanding of the performance of this façade system under wind, earthquake forces and
implementing automation techniques to streamline the calculations by creating a smart
grid in Grassshopper and Python. Additionally, once structural integrity has been met, an
optimal structural design of the bracket using steel and glass as a material is presented by
using advanced finite-element analysis schemes and structural design criteria. ... Read more

The thesis focuses on creating a solution aimed at reducing suffering in earthquake prone regions. The research done resulted in the development of Embrace, a wearable communication device designed to alleviate human suffering during seismic events in seismically active regions like Zagreb. Commencing with an exploration of challenges faced by people living in these quake affected regions, the research aimed to devise a cost-effective, visually appealing solution to these issues.
Methodologies encompassed literature reviews, interviews, cause-effect analysis, and Inside out Design approach, offering crucial insights into user needs and preferences. Following an evaluation of various design concepts, Embrace emerged as the preferred solution, aligning with project requirements.
Embrace integrates LoRa technology for long-range communication, empowering individuals to request aid during earthquakes. Its design process involved modeling with Fusion 360, 3D printing, and utilizing liquid rubber for silicone shells. Sizing considerations, ergonomic enhancements with fillets, and a hierarchy of requirements guided its development.
Future research pathways should include testing Embrace's functionality, exploring diverse shapes and materials, and investigating additional features like smartwatch integration. The thesis resulted in development of Embrace as a significant contribution to wearable technology, enhancing safety and well-being during seismic events. ... Read more

With the increasing number and diversity of disruptive events imposed on the built environment, it is becoming more important to identify a system's resilience. Quantifying resilience is crucial because it enables effective preparation, recovery, and adaptation to the uncertainties that lie ahead. This study focuses on the resilience of building facades, which play an integral role in a building's various functions, including environmental, structural, and operational performance. Facades contribute significantly to the total building damage, yet their resilience is not sufficiently addressed in current discourse. This research aims to bridge this research gap by addressing the question: How can the integrated resilience of a facade system to multiple hazards be identified? A methodology was developed with two objectives: 1) evaluating facade resilience, and 2) integrating this methodology into the facade design process.

The Resilience-based Facade Design Framework assesses the impact of multiple hazards on a building facade, taking into account its fragility. The framework provides a quantitative approach to decision-making regarding facades, both in the early design stage and in retrofitting. Users can input project location, building geometry, and existing facade specifications to create a facade package. This package is then assessed for resilience under different hazards, including seismic and heat hazards. The resilience performance, defined in terms of resilience loss and economic loss, is integrated into a multi-attribute decision-making tool. This tool allows users to select a facade package based on its integrated resilience performance value, or to configure a facade package based on individual enhancements to resilience attributes. ... Read more

Climate change and extreme heat are critical issues which have been faced all over the world. Consequently, designers strive to monitor and assess the performance of facades by developing environmental assessments at the early design stages, since design changes do not require many resources. Rapid urban expansion in many parts of the world is leading to increased exposure to extreme natural hazards, exacerbated by climate change. It is essential to come up with strategies for mitigating the vulnerability of the built environment. The concept of thermal resilience and adaptation to climate change have gained ground and international attention in the Architecture, Engineering and Construction (AEC) industry. Resilience is a multi-facet property which defines the vulnerability of the built environment. Although the qualitative assessment of resilience value, the quantification of urban resilience is not yet representative enough and there is a lack of calculating the resilience in the built environment. However, designers are called to develop building and planning proposals with taking into consideration the thermal resilience of buildings against extreme hazards. This thesis aims to fill the gap between the qualitative and quantitative evaluation of thermal resilience in buildings by considering the operational building performance and the thermal performance of the building envelope in case of extreme heat waves. Towards this direction, the most influential parameters of thermal resilience are identified by implementing a sensitivity analysis process, in the first part. Secondly, a quantification method is presented and the thermal resilience performance for buildings in Amsterdam is calculated. Last, this thesis attempts to develop a computational workflow in order to assist designers and engineers in defining the thermal resilience index from the early design stage. Defining a less computational cost and time-consuming workflow is also a goal. Due to time limitations, the multi-facet aspect of resilience and the difficulty of quantification of its indicators, this research focuses on the ex-ante evaluation of the building envelope by identifying its vulnerability to extreme heat waves. ... Read more

Due to global warming, the Netherlands is experiencing a variety of climatic changes, including temperature rise, increased solar radiation and condensation, low pressure, high humidity, wildfires, drought, subsidence, changes in groundwater levels, an increased risk of flooding, and downbursts, thunder, wind gusts, and hail. Building materials, including steel, concrete, and timber, are affected directly or indirectly by these climatic events.

When it comes to resilience, increasing moisture, temperature, subsidence, and flood damage affect structural materials most. Investigating the impact of temperature and flood damage on construction materials was the main goal of the thesis.

For flood assessment, flood loads based on the FEMA Coastal Construction Handbook are used to simulate flooding damage and evaluate the impact on structures. Hand calculations are used to calculate the deflection. Damage evaluation involves calculations from reference cases and utilizes databases such as Hazus, the REDi rating system, and FEMA to determine recovery and repair times. The script for the assessment tool incorporates these calculations, formulas, and numbers, eventually resulting in a graph based on the dimension of the column and the material; the deflection, damage, recovery time, and repair time are returned. The current flood assessment is limited to deflection in terms of structural assessment, but it can easily be expanded to contain stress calculations or other similar formulas.

Regarding the temperature impact, an empirical concrete corrosion formula calculates mass loss, while the Arrhenius equation assesses the deterioration of wood and steel. A specific formula for concrete corrosion considering the concrete layer is required. Using Faraday's equation, corrosion ratios or material degradation ratios can be converted into mm/year, determining the new cross-section size and assessing its impact on structural deflection by anticipating the mass loss. This loss is also directly linked to the structure's performance in a flood, effectively integrating both investigated events.

Both flood assessment and temperature effect approaches are translated into a Python script using packages like open-meteo for climate data, klimaateffectatlas for flood depths, and ifcopenshell for data extraction from IFC models. ... Read more