Quality assurance (QA) during construction often relies on inspection records and laboratory test results that become available days or weeks after work is completed. On large highway and bridge projects, this delay limits early intervention and increases the risk of rework, schedule impacts, and fragmented documentation. This study presents a construction-phase digital twin framework designed to support element-level QA and readiness-based decision making during active construction. The framework links inspection records, material production and placement data, early-age sensing, and predictive strength models to individual construction elements. By integrating these data streams, the system represents the evolving quality state of each element and supports structured release or hold decisions before standard-age test results are available. The approach does not replace established inspection and testing procedures. Instead, it supplements existing workflows by improving traceability and enabling earlier, data-informed quality assessments. Practical considerations related to data integration, contractual constraints, and implementation challenges are also discussed. The proposed framework provides a structured pathway for transitioning construction QA from delayed, document-driven review toward proactive, element-level decision support during construction.

翻译：施工过程中的质量保证通常依赖于工作完成后数日乃至数周才能获取的检查记录与实验室测试结果。在大型公路与桥梁项目中，这种延迟限制了早期干预，增加了返工风险、进度影响及文档碎片化问题。本研究提出一种施工阶段数字孪生框架，旨在支持施工活动期间基于构件层级的质量保证与就绪状态的决策制定。该框架将检查记录、材料生产与浇筑数据、早期监测以及强度预测模型关联至各个施工构件。通过集成这些数据流，系统能够表征每个构件不断演化的质量状态，并在标准龄期测试结果获得前，支持结构化的放行或暂缓决策。该方法并非取代既有的检查与测试流程，而是通过提升可追溯性、实现更早期的数据驱动质量评估，对现有工作流进行补充。本文亦讨论了与数据集成、合同约束及实施挑战相关的实际考量。所提出的框架为将施工质量保证从滞后的、文档驱动的审查模式，转向施工期间主动的、构件层级的决策支持，提供了一条结构化路径。