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Adeli, H and Karim, A (1997) Scheduling/Cost Optimization and Neural Dynamics Model for Construction. Journal of Construction Engineering and Management, 123(04), 450–8.

Arditi, D, Kale, S and Tangkar, M (1997) Innovation in Construction Equipment and Its Flow into the Construction Industry. Journal of Construction Engineering and Management, 123(04), 371–8.

Hartman, F, Snelgrove, P and Ashrafi, R (1997) Effective Wording to Improve Risk Allocation in Lump Sum Contracts. Journal of Construction Engineering and Management, 123(04), 379–87.

Jaafari, A (1997) Concurrent Construction and Life Cycle Project Management. Journal of Construction Engineering and Management, 123(04), 427–36.

Kang, L S and Paulson, B C (1997) Adaptability of Information Classification Systems for Civil Works. Journal of Construction Engineering and Management, 123(04), 419–26.

Pocock, J B, Liu, L Y and Kim, M K (1997) Impact of Management Approach on Project Interaction and Performance. Journal of Construction Engineering and Management, 123(04), 411–8.

Portas, J and AbouRizk, S (1997) Neural Network Model for Estimating Construction Productivity. Journal of Construction Engineering and Management, 123(04), 399–410.

Schexnayder, C and Ohrn, L G (1997) Highway Specifications—Quality versus Pay. Journal of Construction Engineering and Management, 123(04), 437–43.

Touran, A (1997) Probabilistic Model for Tunneling Project Using Markov Chain. Journal of Construction Engineering and Management, 123(04), 444–9.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1997)123:4(444)
  • Abstract:
    Actual tunnel advance rates from the Outfall Tunnel of the Boston Harbor Cleanup Project are analyzed. It is shown that states of work and nonwork for the tunnel boring machine can be modeled with a Markov chain. A general probabilistic approach is proposed for developing the cumulative distribution function (CDF) of the total length that can be tunneled in a given time frame. Simulation models are developed to verify the results of the analytical model and also to simulate the distribution for the time necessary to tunnel a certain length (in this case the remainder of the tunnel). The validity of the predictive model is verified using the data from the completed project. The proposed approach may be used for relatively long tunnels with durations extending over several months where the tunneling has already begun and sufficient progress data have been collected. The data from progress up to a certain date may be used for forecasting the length of tunnel that can be constructed in a specified duration.

Venegas C., P and Alarcón C., L F (1997) Selecting Long-Term Strategies for Construction Firms. Journal of Construction Engineering and Management, 123(04), 388–98.

Walsh, K D, Houston, W N and Houston, S L (1997) Field Implications of Current Compaction Specification Design Practices. Journal of Construction Engineering and Management, 123(04), 363–70.