To express information on construction project risks comprehensively and precisely and to improve the accuracy of the results of the ranking of construction project risk factors, we use the interval grey degree to express grey characteristics of information. The membership degree is used to express fuzzy characteristics of information. An uncertain linguistic variable is used to express linguistic descriptive characteristics of information. A ranking model for construction project risk factorsis proposed to identify the main risk factors on the basis of the interval grey fuzzy uncertain linguistic set and the continuous interval argument ordered weighted averaging (C-OWA) operator. We take the Weft Three-Road Cross-River Tunnel in Nanjing as a case to verify the feasibility of the proposed model.. Research results show that compared with fuzzy sets that can only use membership degree to express fuzziness, the interval grey fuzzy uncertain linguistic set can express the grey, fuzzy, and linguistic descriptive characteristics of practical construction project risk information simultaneously. The proposed model based on the theory helps to improve the comprehensiveness and authenticity of risk information expression, as well as the accuracy of risk factor rankings. The results of this work could assist project managers in determining main risk factors and thereby provide a theoretical basis for taking pre-control measures.

To effectively address the efficiency bottlenecks in the application of digital twin technology in the water conservancy sector, it is imperative to conduct a systematic analysis of the influencing factors and their underlying connections during the technology promotion process. Based on the fundamental connotations of new quality productive forces, this paper constructs a four-dimensional indicator system encompassing laborers, means of labor, objects of labor, and optimized combinations for enhancement using the qualitative comprehensive integration method. Subsequently, the fuzzy DEMATEL model is employed to quantify the interactive relationships and influence intensity among factors, precisely identifying key driving factors. An ISM model is utilized to generate a hierarchical topology diagram, revealing the critical driving pathways for technology promotion. This paper finds that the factors affecting the promotion of digital twin technology can be divided into surface factors, intermediate factors, and root factors. Among them, ten factors such as water conservancy policy guidance and incentives, water conservancy market demand and competition, and the application benefits of digital twin technology are the key influencing factors for technology promotion; the key influencing factors, with the help of the transmission of intermediate factors, affects the surface factors, forming a core driving path that starts with the guidance of water conservancy policies and market demand and ends with the benefits of technical application. It should be given priority when formulating technology promotion strategies.