994 resultados para Illinois Building Commission


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The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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This paper investigates the response of multi-storey structures under simulated earthquake loads with friction dampers, viscoelastic dampers and combined friction-viscoelastic damping devices strategically located within shear walls. Consequently, evaluations are made as to how the damping systems affect the seismic response of these structures with respect to deflections and accelerations. In particular, this paper concentrates on the effects of damper types, configurations and their locations within the cut-outs of shear walls. The initial stiffness of the cut out section of the shear wall is removed and replaced by the stiffness and damping of the device. Influence of parameters of damper properties such as stiffness, damping coefficient, location, configuration and size are studied and evaluated using results obtained under several different earthquake scenarios. Structural models with cut outs at different heights are treated in order to establish the effectiveness of the dampers and their optimal placement. This conceptual study has demonstrated the feasibility of mitigating the seismic response of building structures by using embedded dampers.

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Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.

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This paper analyses the profits from 221 construction projects undertaken by an Australian building firm in the period 1910–1938 and examines the factors that influence the firm's profit levels. This involves a series of multiple regression analyses with three dependent variables representing profit and 26 independent variables representing economic conditions and project characteristics. From these, 11 models are derived of which two are chosen as having the best explanatory power in explaining approximately 72% of the variability in profit levels movements. The results show that unemployment, interest rates, level of construction activity in the state, change of wage level, inflation rate of building material and project value significantly influenced the firm's profit level during the period.

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The role of Information and Communications Technology (ICT) has been identified as an important factor by the United Nations in achieving the millennium development goals (UNAPCICT, 2012)1. The potential for ICT has been identified as a means to reducing poverty, creating global communities by providing access to the internet and mobile networks to rural communities, improving education services, medical services, and information availability. As of today, significant amounts of funds have been invested by the governments and donor organizations in ‘Information and Communication Technologies for Development (ICT4D)’projects by establishing telecenters, e-villages, e-health, electronic and mobile banking, and egovernment systems for citizens in general, and more specifically, rural communities to bridge the digital divide (Heeks & Molla, 2009).

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A fundamental proposition is that the accuracy of the designer's tender price forecasts is positively correlated with the amount of information available for that project. The paper describes an empirical study of the effects of the quantity of information available on practicing Quantity Surveyors' forecasting accuracy. The methodology involved the surveyors repeatedly revising tender price forecasts on receipt of chunks of project information. Each of twelve surveyors undertook two projects and selected information chunks from a total of sixteen information types. The analysis indicated marked differences in accuracy between different project types and experts/non-experts. The expert surveyors' forecasts were not found to be significantly improved by information other than that of basic building type and size, even after eliminating project type effects. The expert surveyors' forecasts based on the knowledge of building type and size alone were, however, found to be of similar accuracy to that of average practitioners pricing full bills of quantities.

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Concern that poor image of UK construction industry is restricting recruitment has lead to call for action. This paper gives the results of a recent comparative analysis of the image of both UK and Hungarian industries which indicates the UK image to be relatively good. The perceived cause of Hungarian problems is the poor level of organisation and management.

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The construction industry contains two types of estimators the contractors' estimator and the designers' price forecaster. Each has two models of the building in which to systemize his procedures - the production model and the design model. The use of these models is discussed in the light of the industry's particular problems of complexity and uncertainty together with the pressures of the market. It is argued that estimators and forecasters, in order to function effectively in these conditions, are forced to exercise a high degree of subjective judgment. Means of eliciting good heuristics involved in judgment making are considered by reference to the artificial intelligence and construction literature and a methodology is proposed based on these findings. The results of two early trials of the method with students are given, indicating the usefulness of the approach.

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This paper describes the instigation and development of an expert system to aid in the strategic planning of construction projects. The paper consists of four parts - the origin of the project, the development of the concepts needed for the proposed system, the building of the system itself, and assessment of its performance. The origin of the project is outlined starting with the Japanese commitment to 5th generation computing together with the increasing local reaction to theory based prescriptive research in the field. The subsequent development of activities via the Alvey Commission and the RICS in conjunction with Salford University are traced culminating in the proposal and execution of the first major expert system to be built for the UK construction industry, subsequently recognised as one of the most successful of the expert system projects commissioned under the Alvey programme

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Growing community concerns about the ecological, social, cultural and economic impact of housing and urban projects poses new challenges for those who have to deliver them. It is important that these concerns are addressed as part of the community engagement processes on projects. Community engagement is traditionally perceived as the purview of planners and disconnected from the building construction process. This is despite most project approval processes mandating on-going community engagement over the project’s entire lifetime. There is evidence that point to a culture of ambiguity and ambivalence among building professionals about their roles, responsibilities and expectations of community engagement during the construction phase of projects. This has contributed to a culture of distrust between communities and the construction industry. There is a clear need to build capacity among building professionals to empower them as active participants in community engagement processes which can promote better project outcomes and minimise delays and conflicts. This paper describes a process that utilises the Theory of Planned Behaviour as a framework to equip building professionals with the skills they need to engage effectively with local communities during the construction phase of projects.

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The green building trend has increased rapidly worldwide in recent decades as a means of addressing growing concerns over climate change and global warming and to reduce the impact of the building industry on the environment. A significant contribution in Australia is the use of a series of rating tools by the Green Building Council Australia (GBCA) for the certification of various types of buildings. This paper reviews the use of the Green Star system in Australian building construction, and investigates the potential challenges involved in acquiring the certification of Australian buildings by critically analysing a database of most recently certified GBCA projects. The results show that management-related credits and innovation-related credits are the easiest and most difficult respectively to obtain. Additionally, 6-Star green buildings achieve significantly higher points than other certified buildings in the Energy category. In contrast, 4 Star green buildings achieve more points in the Material category than 5 and 6 Star buildings. The study offers a useful reference for both property developers and project teams to obtain a better understanding of the rating scheme and consequently the effective preparation of certification documentation.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.