A Framework for Sustainable Lightweight Concrete Mix Design Optimization

Thesis Abstract

The increasing demand for sustainable construction materials necessitates the development of optimized lightweight concrete (LWC) mixes that balance environmental impact, structural performance, and economic viability. This study addresses the challenge of achieving sustainable LWC design by establishing a comprehensive framework that integrates material properties, environmental considerations, and mechanical performance through a systematic optimization approach. The primary aim is to develop an evidence-based, practical model that guides the formulation of lightweight concrete mixes with minimized environmental footprints while maintaining structural integrity. The specific objectives include (1) identifying key material variables influencing sustainability and performance of LWC; (2) analyzing existing mix design practices and their limitations in sustainability contexts; (3) formulating a multi-criteria optimization framework utilizing statistical and computational techniques; and (4) validating the proposed framework through experimental testing and parametric analysis. Employing a mixed-methods research design, the study combines quantitative laboratory experiments with qualitative assessments to ensures robustness and applicability of the framework. The target population comprises lightweight aggregate producers, concrete mix designers, and construction practitioners within the regional building industry. A stratified random sampling technique selects 150 concrete mix samples for laboratory testing, representing a variety of aggregate types, cement sources, and admixture combinations. Data collection instruments include standardized ASTM testing procedures for compressive strength, durability, and thermal performance; life cycle assessment (LCA) metrics for environmental impact; and structured interviews and questionnaires to gather expert insights on practical constraints and preferences. The data analysis involves both descriptive and inferential statistical techniques. Multiple regression analysis explores the influence of mix design variables on performance indicators, while analysis of variance (ANOVA) tests differences across various mix formulations. A multi-objective optimization model based on Pareto efficiency principles is developed using MATLAB's optimization toolbox, integrating environmental impact scores from LCA, the mechanical performance metrics, and cost data. Structural equation modeling (SEM) is employed to examine relationships among variables and validate the conceptual model underpinning the framework. The analysis aims to identify optimal mix proportions that satisfy sustainability criteria without compromising structural standards. Anticipated findings include a set of empirically derived relationships linking material selection, mix proportions, and environmental impacts, alongside a calibrated optimization model capable of generating tailored lightweight concrete mixes for different structural applications. The results are expected to demonstrate that targeted adjustments in aggregate grading, binder type, and admixture use can significantly reduce embodied energy and carbon footprint by at least 20% while retaining or improving key mechanical properties such as compressive strength and durability. Furthermore, the study is projected to produce a practical decision-support tool that readily integrates into existing mix design procedures, fostering more sustainable construction practices. This research contributes novel insights to the domain by operationalizing an integrated sustainability-performance optimization framework that synthesizes theoretical principles, empirical data, and computational modeling. It advances existing knowledge by providing a structured methodology for eco-efficient lightweight concrete design that can be adapted across diverse regional contexts. The main conclusion posits that sustainable lightweight concrete mix design can be achieved through a systematic, data-driven approach that balances environmental, structural, and economic factors. Recommendations include adopting the framework within standard design protocols, promoting further research into nano-materials and alternative binders, and expanding the model to incorporate lifecycle cost analysis. Future studies could explore real-time monitoring of mix performance in construction settings and extend the framework to incorporate emerging sustainable materials and innovative construction techniques.