Geothermal energy stands out as an exceptional renewable resource for power generation, offering a consistent power production without the intermittency issues. Despite its potential to deliver a consistent supply of electricity on demand, geothermal adoption is hindered due to substantial costs. Utilising the most effective drilling method can alleviate this challenge by boosting efficiency and reducing operational costs. The primary goal of this study is to identify the best drilling method for extracting heat from geothermal reservoirs. This optimised approach facilitates better access to geothermal reservoirs, leading to increased heat recovery rates and improved project viability. Traditional methods often fall short in evaluating optimal drilling alternatives due to uncertainties. To address this, our research introduces an innovative paradigm that integrates novel T-Spherical Hesitant Fuzzy Rough (T−SHFR) set, method for the removal effects of criteria with a geometric mean and ranking alternatives with weights of criterion hybrid Multiple Criteria Decision-Making (MCDM) techniques. By leveraging the novel T−SHFR concept, our approach allows for a comprehensive assessment of various factors. This holistic evaluation ensures an exhaustive comprehension of the decision-making environment. The study reveals that reservoir characteristics play a significant role in selecting a sustainable drilling alternative. Furthermore, directional drilling appears as the most promising method with higher energy yields followed by slim hole drilling. The robustness and credibility of these findings are established through sensitivity and comparative analyses, indicating the potential applicability of this MCDM method to analogous challenges in different contexts. The findings of the ranking techniques were validated using Spearman's rank correlation coefficient, which revealed a positive and notable correlation. This research will empower stakeholders to make informed decisions, thereby enhancing the overall efficiency and sustainability of geothermal energy projects.

In recent times, the world has been dealing with multiple environmental crises, including rising global temperatures, excessive energy consumption, elevated urban temperatures, and increasing carbon emissions from the building industry. As buildings have a significant impact on energy use, it is essential to address these challenges. In particular, window glass plays a significant role in controlling heat transfer, regulating indoor temperatures and reducing the dependence on artificial cooling. Therefore, selecting the most suitable energy-efficient glass has become crucial for sustainable development. Construction technology has introduced specialized glass materials for windows, including smart window technologies that automatically regulate heat and light. This study aims to identify the most suitable energy-efficient glass using a fuzzy multi-criteria decision-making method. Here, eight different alternatives are evaluated against eleven conflicting criteria classified as performance enhancing criteria (PEC) and performance reducing criteria (PRC). The Simultaneous Evaluation of Criteria and Alternative (SECA) method is employed for determining criteria weights, and the COmbinative Distance-based ASsessment (CODAS) approach is utilized to evaluate ranks of the alternatives. To ensure reliability and robustness, the study performed comparative and sensitivity analyses. The results indicate that electrochromic (EC) windows (A4) are the most suitable smart glazing technology among the considered alternatives. The results help urban planners and architects select energy-efficient glass for smart windows.