(1)Background: Early-age concrete shrinkage induces stress that impact the cost and service life of concrete pavements. (2)Methods: In this study, strain measurements of field slabs were conducted and a methodology was presented that independently derived autogenous, drying, and thermal shrinkages in the initial stages of concrete placement. Total strain was measured according to five different environmental conditions and shrinkage strain was calculated for each condition. (3)Results: By measuring the strain of the slab and the specimen, the drying shrinkage strain was measured to be approximately 54% better than that by the conventional non-stressed cylinder method because it was possible to measure the drying shrinkage strain at the surface rather than in the middle part of the slab along its depth direction. When the water-to-cement ratio increased (35→40%), there was a considerable reduction (317με→82με) of autogenous shrinkage strain for the concrete at 28 days of age. Furthermore, calculation of stress-dependent strain allowed the presentation of more intuitive and accurate results. (4)Conclusion: As the measurement of independent shrinkage occurrence is possible, the consequent calculated result of the stress-dependent strain acting on real slabs will facilitate improvement in the construction quality, reduction in the development of defects in the concrete structure, and increase in the service life.

The rapid growth of the aviation industry has progressively heightened the importance of airport maintenance management. There is an increasing need for a comprehensive system that considers the diverse requirements of various stakeholders. Existing research has primarily focused on the technological advancements of optimization models, with limited applicability in practice. In this study, we introduce the Condition Cases Optimization (CCO) to address these limitations while incorporating multi-facility and multi-year network optimization models. We developed condition index, Serviceability Level, integrated assessment indices and performance models for decision-making criteria. We categorize conditions into three classes and propose a practical decision-making strategy that can flexibly adapt to budget constraints. Sensitivity analysis highlights the impact of initial budget, maintenance methods, costs, and thresholds on decision outcomes. Through a case study we validate the effectiveness and practicality of the CCO method as an efficient decision-making tool.