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A feasibility study on construction methods of high voltage transmission towers’ foundations

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Civil engineering projects deal with different risks over their life-cycle. Generally, risk sources are categorized into three types of cost, time, and project quality. The Modified Advanced Programmatic Risk Analysis Model (MAPRAM) is one of the leading approaches in this field that can assess the risks of the project on its whole life cycle. Electricity transmission lines have always been one of the most costly and time-consuming infrastructure projects. The costs of these projects play a significant role in a country's development budget. Given the considerable time and cost of constructing the foundations for power transmission towers, providing an economical design will significantly help in reducing duration and budget of these projects. In this study, using MAPRAM, first, different types of foundations of power transmission lines were studied; then the optimal foundations were introduced for a specific place as a case study, shaping a general framework to appoint the optimal foundation for power transmission lines in different areas. The foundations studied in this study included: pad & chimney foundation, auger foundation, steel grillage foundation, concrete piles, and helical piles. Initially, different types of foundations were designed, and then, the costs of each foundation in a whole life-cycle were estimated. Next, the risks and probability of their occurrence were identified for each type of foundation. Finally, the appropriate foundation was determined for the studied soil samples by performing an optimization process.
Rocznik
Strony
40--54
Opis fizyczny
Bibliogr. 36 poz., fot., rys., wykr.
Twórcy
autor
  • Department of Civil Engineering, University of Isfahan, Isfahan, Iran
  • Department of Civil Engineering, University of Isfahan, Isfahan, Iran
  • Department of Civil Engineering, University of Isfahan, Isfahan, Iran
Bibliografia
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  • [4] Halpin DW, Lucko G, Senior BA (2017) Construction management. John Wiley & Sons.
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  • [9] Thomopoulos NT (2013) Generating continuous random variates, In: Essentials of Monte Carlo Simulation: Springer, pp 27–44.
  • [10] Allahi F, Cassettari L, Mosca M (2017) Stochastic risk analysis and cost contingency allocation approach for construction projects applying Monte Carlo simulation. In: Proceedings of the World Congress on Engineering, vol. 1.
  • [11] Baig MMHA, Prasanthi SG (2013) Failure modes and effect analysis of a mechanical assembly by Using Mil-Std 1629a Method," the moon 13(13).
  • [12] Willmer G Time and cost risk analysis, Computers & Structures 41(6):1149–1155, 1991/01 1991.
  • [13] Cooper KG (1994) The $2,000 h: How managers influence project performance through the rework cycle, Project Management Institute.
  • [14] Mulholland B, Christian J. Risk assessment in construction schedules. J Construction Eng Manag. 1999;125(1):8–15.
  • [15] Mak S, Picken D. Using risk analysis to determine construction project contingencies. J Construction Eng Manag. 2000;126(2):130–6.
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  • [17] Dillon RL, Pate-Cornell ME. APRAM: an advanced programmatic risk analysis method. Int J Technol Policy Manage. 2001;1(1):47–65.
  • [18] Dillon RL, Paté-Cornell ME, Guikema SD. Programmatic risk analysis for critical engineering systems under tight resource constraints. Oper Res. 2003;51(3):354–70.
  • [19] Imbeah W, Guikema S. Managing construction projects using the advanced programmatic risk analysis and management model. J Construction Eng Manag. 2009;135(8):772–81.
  • [20] Zeynalian M, Trigunarsyah B, Ronagh HR. Modification of advanced programmatic risk analysis and management model for the whole project life cycle’s risks. J Construction Eng Manag. 2013;139(1):51–9.
  • [21] Gamble KB, Lightsey EG. Decision analysis tool for small satel-lite risk management. J Spacecraft Rockets. 2016;53(3):420–32.
  • [22] Zeynalian M, Dehaghi IK. Choice of optimum combination of construction machinery using modified advanced programmatic risk analysis and management model. Scientia Iranica. 2018;25(3):1015–24.
  • [23] Ali AA, Faruq I, Ahmad A, Gandu Y. Exploring the awareness of advanced programmatic risk analysis and management model in managing construction projects in Nigeria. African J Earth Environ Sci. 2020;2(1):465–75.
  • [24] Bayliss CR, Bayliss C, Hardy B (2012) Transmission and distribution electrical engineering. Elsevier.
  • [25] Mohajerani A, Bosnjak D, Bromwich D. Analysis and design methods of screw piles: a review. Soils Found. 2016;56(1):115–28.
  • [26] Perko HA (2009) Helical piles: a practical guide to design and installation. John Wiley & Sons.
  • [27] A. Services, "AMS-Victorian Electricity Transmission Network-Risk Management (PUBLIC VERSION) " in "AMS 10–22 " 2015, Available: https ://www.aer.gov.au/syste m/files /AusNe t%20Ser vices %20-%20AMS %2010-22%20-%20Ris k%20Manageme nt%20-%20Pub lic%20-%20Oct ober%20201 5.pdf.
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  • [29] ASCE 7-16 Minimum Design Loads and Associated Criteria for Buildings and Other Structures, 2016.
  • [30] ASTM E917 - 05 - Standard practice for measuring life-cycle costs of buildings and building systems, 2005.
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  • [33] Griffin J (2003) Life cycle cost analysis: a decision aid, in Life cycle costing for construction: Routledge, pp 147–158.
  • [34] Paté-Cornell ME. Fault trees vs. event trees in reliability analysis. Risk Anal. 1984;4(3):177–86.
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  • [36] Wolfram S (1999) The MATHEMATICA® book, version 4. Cambridge university Press.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a4a90d01-9d9e-43d6-87c7-a1f4c118966b
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