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In the early stages of a construction project, the reliability and accuracy of conceptual cost estimates are major concerns for clients and cost engineers. Previous studies applied scoring methods and established common rules or mathematical methods to assess the quality of cost estimates. However, those approaches have some limitations in adapting to real-world projects or require understanding of sophisticated statistical techniques. We propose a Conceptual Cost Estimate Reliability Index (CCERI), a simple, easy-to-use, and easy-to-understand tool that incorporates weights for 20 factors influencing the quality of conceptual cost estimates. The weights were obtained by eliciting experts’ experience and knowledge. Cost data from 71 building projects were used in the analysis and validation of the CCERI. The analysis reveals that a conceptual cost estimate with a CCERI score of less than 3000 has a high probability of exceeding 10% error, and such conceptual cost estimates are unlikely to be reliable. With the CCERI score, a decision maker or a client can recognize the reliability of the conceptual cost estimates and the score can thus support decision making using conceptual cost estimates. In addition, with the CCERI and the relative importance weights of factors affecting the conceptual cost estimates, the estimator can find ways to modify a conceptual cost estimate and reestimate it. These alternatives can decrease the risk in the conceptual estimated cost and assist in the successful management of a construction project.

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In this study digital image correlation (DIC) technique combined with a high speed video system was used to predict movement of particles in a water model. Comparing with Particle-image velocimetry (PIV) technique, it provides a low cost alternative approach to visualize flow fields and was successfully employed to predict the movement of particles in a water model at different submergence depth using gas injection. As the submergence depth increases, the number of the exposed eye is reduced accordingly. At 26.4 cm submergence depth, an exposed eye was found at 1/3 of the submergence depth, whereas two exposed eyes were observed at 1/2 depth and near the bottom wall at 24 cm submergence depth.