The global construction sector has witnessed exponential growth in concrete utilization over the past seven decades, with annual consumption over 9.42 billion m³ in 2021. This surge, driven by rapid urbanization, has positioned concrete as the dominant construction material while creating critical environmental burden. In response to these challenges, the Swedish concrete industry has committed to making all concrete climate-neutral by 2045, with market-ready climate-neutral concrete available by 2030. To reduce the negative environmental impact of the concrete, transitioning from linear to circular economic models presents a viable approach, particularly through integrating wastes and industrial by-products (e.g., fly ash, slag) as supplementary cementitious materials (SCM) into concrete formulations. However, this eco-friendly construction practice faces severe challenges at establishing and executing SCM concrete configurations (including concrete mixes and site construction methods). During plan establishment, the systemic environmental and economic impacts of SCM concrete—spanning cradle-to-practical-completion phases—remain insufficiently examined. 

The complex interactions between SCM concrete’s mechanical properties (e.g., prolonged hydration and decreased early strength) and site construction methods (e.g., formwork duration, occupancy of labour and equipment) increase the difficulty in quantification. For example, while SCM concrete reduces embodied carbon in production, its delayed strength gain may necessitate prolonged formwork use or require energy-intensive methods (e.g., thermal treatment) to meet project timelines. To mitigate this, engineers might opt for a higher concrete grade to accelerate early strength development—though this risks offsetting sustainability gains of SCM concrete. Such adaptations often erode projected emission reductions and inflate costs, shifting burdens across stages. These cross-stage trade-offs underscore the need for integrated, cradle-to-practical-completion evaluations of the environmental and economic impacts of SCM concrete to avoid suboptimal overall performance.

Furthermore, optimising SCM concrete configurations based on quantified performance metrics presents a significant computational challenge. This is due to the exponentially growing solution space resulting from the numerous combinations of SCM concrete mix designs and site-specific construction methods. As a result, exhaustive exploration of the solution space becomes computationally intensive, often leading to incomplete identification of optimal trade-offs between environmental benefits (e.g., reduced GHG emissions) and economic constraints (e.g., labour costs, construction time). Even after obtaining optimal SCM concrete configurations, real-world variability—such as fluctuating temperatures affecting curing rates —introduces uncertainty into project outcomes during site execution. For example, warmer weather than predicted will make former planed thermal curing measures become over-protection, leading to unnecessary expenses and energy consumption. To address this, robust optimisation frameworks are needed to simultaneously account for cross-stage interdependencies and operational uncertainties. 

Despite the critical need for integrated solutions, existing research on SCM concrete construction has largely remained discipline-specific—a divide rooted in the fragmented nature of the construction industry and its supply chain. Studies on SCM material properties are primarily limited to construction materials research, while on-site optimisation is explored within construction management. This fragmentation has prevented the integration of these two critical dimensions into a unified framework, limiting a comprehensive understanding of their collective impacts on a project’s economic and environmental performance. Based on gaps in previous studies, three research questions are formulated: 

RQ1: What systemic interdependencies exist between SCM concrete’s mechanical properties and site construction methods, and how do these interactions influence the cradle-to-practical-completion performance of SCM concrete?

RQ2: What critical trade-offs arise when optimizing SCM concrete configurations across environmental benefits and economic constraints, and how can these trade-offs be systematically prioritized to avoid sub-optimisation?

RQ3: What influence do weather-induced uncertainties have on the trade-offs between environmental benefits and economic constraints of SCM concrete construction practice across cradle to practical completion, and how should site construction methods be dynamically adapted to optimize these objectives under variable conditions?

To address the formulated research questions, the research underlying this thesis was conducted in three following procedures: (1) Problem identification, which investigated both the operational demands of SCM concrete construction practice and existing theoretical limitations hindering the realization of full eco-friendly potentials of SCM concrete; (2) Method development, which constructed a holistic approach to overcome the identified theoretical gaps; (3) Method validation, which built three according prototypes as practical solutions to the identified problems and applied them to actual construction case projects to examine the effectiveness of the proposed methods. Each research question is addressed by a purpose-built model tailored to the specific technical and decision-making challenges associated with the use of SCM concrete. These models offer targeted solutions across life cycle analysis, optimisation, and uncertainty management:

CSCD (Collection–Simulation–Calculation–Decision) for RQ1: This model integrates Discrete Event Simulation (DES), environmental impact assessment, and concrete maturity analysis to evaluate the environmental and economic performance of SCM concrete across the cradle-to-practical-completion span. It explicitly captures the interdependencies between SCM concrete’s mechanical properties (e.g., strength development) and construction practices (e.g., formwork duration), supporting holistic performance quantification.

ESO (Ensemble learning–Simulation–Optimisation) for RQ2: This model combines ensemble machine learning techniques with simulation-based optimisation to efficiently navigate the expanded solution space of SCM concrete mixes and site construction methods. It enables comprehensive multi-objective trade-off analysis between environmental benefits (e.g., GHG emissions reduction) and economic constraints (e.g., cost, time), while minimising computational demand and the risk of sub-optimal outcomes.

MADS (Modelling–Automation–Decision Support) for RQ3: This model integrates dynamic weather data, concrete maturity modelling, and automated decision rules to support the dynamic adaptation of construction practices—such as curing duration and protection measures—in response to temperature fluctuations. It enhances the reliability and responsiveness of SCM concrete implementation under weather-related uncertainties.

This research directly supports the strategic goals of the Swedish roadmap for climate-neutral concrete through a systematic and holistic approach to the use of SCMs. The roadmap emphasizes several key strategies, including: optimising the composition of concrete, replacing parts of the cement with alternative binders; contributing towards ensuring that the right concrete is used in the right place, i.e. avoiding higher concrete quality than necessary for the bearing capacity and durability of the building. The proposed research approach contributes to each of these areas in the following ways:

(1) Optimizing Concrete Composition. In alignment with the roadmap’s focus on reducing cement content, this research provides a structured method for evaluating and selecting SCMs as partial cement replacements. The CSCD model, developed in response to RQ1, enables a comprehensive environmental and economic assessment of different SCM concrete mixes, considering their mechanical behavior and performance during construction.

(2) Ensuring the Right Concrete is Used in the Right Place. Overdesign of concrete—using unnecessarily high-grade concrete mixes—leads to avoidable emissions and costs. The research supports decision-makers in selecting concrete grades that match structural needs without overdesign. The CSCD model quantifies performance relative to functional demand, minimizing unnecessary environmental burdens and ensuring practical suitability on-site.

(3) Lifecycle-Based Environmental and Economic Assessment. Avoiding impact shifting across project stages requires integrated evaluation from material selection to project delivery. This research embeds a cradle-to-practical-completion perspective throughout all phases of assessment. While the CSCD model forms the backbone of this life cycle analysis (per RQ1), the ESO and MADS models (developed under RQ2 and RQ3) extend this thinking into planning and execution, capturing downstream impacts and variability.

(4) Multi-Objective Optimization for SCM Usage Planning. Identifying optimal SCM configurations under multiple, often conflicting objectives—such as reducing emissions while controlling costs and timelines—is critical. This research introduces the ESO model, developed for RQ2, which combines simulation with ensemble learning to explore a vast solution space efficiently. It reveals optimal trade-offs while managing computational complexity.

(5) Managing Construction Uncertainties and Climate Variability. Real-world variability, especially weather-induced fluctuations, can disrupt curing rates and lead to mismatches between planned and actual outcomes. To address this, the MADS model, developed for RQ3, enables dynamic adaptation of construction measures such as curing protocols. It enhances the reliability and environmental performance of SCM concrete application under uncertain site conditions.