20 resultados para 0905 Civil Engineering


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This paper discusses the development of the Virtual Construction Simulator (VCS) 3 - a simulation game-based educational tool for teaching construction schedule planning and management. The VCS3 simulation game engages students in learning the concepts of planning and managing construction schedules through goal driven exploration, employed strategies, and immediate feedback. Through the planning and simulation mode, students learn the difference between the as-planned and as-built schedules resulting from varying factors such as resource availability, weather and labor productivity. This paper focuses on the development of the VCS3 and its construction physics model. Challenges inherent in the process of identifying variables and their relationships to reliably represent and simulate the dynamic nature of planning and managing of construction projects are also addressed.

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One of the most significant sources of greenhouse gas (GHG) emissions in Canada is the buildings sector, with over 30% of national energy end-use occurring in buildings. Energy use must be addressed to reduce emissions from the buildings sector, as nearly 70% of all Canada’s energy used in the residential sector comes from fossil sources. An analysis of GHG emissions from the existing residential building stock for the year 2010 has been conducted for six Canadian cities with different climates and development histories: Vancouver, Edmonton, Winnipeg, Toronto, Montreal, and Halifax. Variation across these cities is seen in their 2010 GHG emissions, due to climate, characteristics of the building stock, and energy conversion technologies, with Halifax having the highest per capita emissions at 5.55 tCO2e/capita and Montreal having the lowest at 0.32 tCO2e/capita. The importance of the provincial electricity grid’s carbon intensity is emphasized, along with era of construction, occupancy, floor area, and climate. Approaches to achieving deep emissions reductions include innovative retrofit financing and city level residential energy conservation by-laws; each region should seek location-appropriate measures to reduce energy demand within its residential housing stock, as well as associated GHG emissions.

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Research in Bid Tender Forecasting Models (BTFM) has been in progress since the 1950s. None of the developed models were easy-to-use tools for effective use by bidding practitioners because the advanced mathematical apparatus and massive data inputs required. This scenario began to change in 2012 with the development of the Smartbid BTFM, a quite simple model that presents a series of graphs that enables any project manager to study competitors using a relatively short historical tender dataset. However, despite the advantages of this new model, so far, it is still necessary to study all the auction participants as an indivisible group; that is, the original BTFM was not devised for analyzing the behavior of a single bidding competitor or a subgroup of them. The present paper tries to solve that flaw and presents a stand-alone methodology useful for estimating future competitors’ bidding behaviors separately.