Search

For any building project, the project management triangle QCT (Quality, Cost, Time) are decisive in the decision-making process. Indeed, better, faster and cheaper remain very important goals in the design of new industrial products in a competitive environment. In this paper, we propose a reference framework to formalize the quality criterion that characterizes a building made during a project. A quality measurement is then defined based on the performance levels of the functions actually provided by a building and the requirements originally formulated by its owner. In addition, a modeling of the building production process is proposed to observe the effects of technical or managerial choices on the expected quality of a new or renovated building. Finally, a representation of the level of performance of each building technical attribute over its life cycle is proposed in order to represent the performance recovery allowed by a renovation operation as a resilience process. In the end of this paper, a section is dedicated to a computational experiment for illustrating the theoretical approach.

Many studies, using various modeling approaches and simulation tools have been made in the field of urban growth. A multitude of models, with common or specific features, has been developed to reconstruct the spatial occupation and changes in land use. However, today most of urban growth techniques just use the historical geographic data such as urban, road and excluded maps to simulate the prospective urban maps. In this paper, adding buildings and population data as urban fabric factors, we define different urban growth simulation scenarios. Each simulation corresponds to policies that are more or less restrictive of space considering what these territories can accommodate as a type of building and as a global population.Among the urban growth modeling techniques, dynamic models, those based on Cellular Automata (CA) are the most common for their applications in urban areas. CA can be integrated with Geographical Information Systems (GIS) to have a high spatial resolution model with computational efficiency. The SLEUTH model is one of the cellular automata models, which match the dynamic simulation of urban expansion and could be adapted to morphological model of the urban configuration and fabric.Using the SLEUTH model, this paper provides different simulations that correspond to different land priorities and constraints. We used common data (such as topographic, buildings and demography data) to improve the realism of each simulation and their adequacy with the real world. The findings allow having different images of the city of tomorrow to choose and reflect on urban policies.

Urbanization induces almost irreversible changes and leads to the phenomenon of urban sprawl and, therefore an increase in artificial lands that affects biodiversity, ecosystems and climate impacts. SLEUTH as a Cellular Automaton (CA) simulation model is widely used by the researchers and urban planners in order to simulate the urban sprawl as a dynamic system. However, SLEUTH, like many other urban simulation models, only considers historical data, and the growth of urban population and urban tissue is not explicitly contemplated and does not have much effect on the simulation results. In this research, we have added these two parameters to SLEUTH and simulated a 3D city model in order to see the impacts of population growth and types of construction on urban sprawl, and to improve the results of simulations. The 3D representation of urban forecasting is based on the results of 2D urban growth simulation while respecting some restrictions on urbanization such as the direction of the footprints, and the distances to urban entities and geographic features. The aim of this research is not only to produce a 3D city model, but also to use the potential of the third dimension to provide different urban future scenarios that can inform prospective strategies for sustainable urban development. The findings allow proposing a set of different simulations that correspond to the different land priorities and constraints, and provide disparate images of city of tomorrow for its application in urban policy as well as smart city modelling and management.

Purpose: This paper aims to develop an efficient model able to reduce catastrophic consequences and the significant number of victims resulting from fires at construction sites. The paper proposes probabilistic modeling aimed to minimize the probability of failure of a construction site. Methodology: The developed model in this paper consists of modeling fire hazards, the vulnerability of the potential targets, and the risk within construction sites. The optimization algorithm called &ldquo, differential evolution&rdquo, is used in order to determine the optimal site layout, which is characterized by having the smallest overall probability of failure. A numerical simulation is performed to delineate an appropriate probability density function of the failure of the site. In addition, a geographic information system (GIS) is used to display the spatial variability of fire risk on a construction site. Findings: The paper provides an efficient model to enhance site layout planning and assign locations for supporting temporary facilities at appropriate positions within a construction site. The model is examined through applying it on a simple case study containing numerous facilities. All these facilities are considered vulnerable targets and some of them are potential fire hazards, with different intensity values. Value: Most of the previous research focuses on travel cost distance in developing site layout planning models. This paper fulfills the development of a valuable model able to generate an optimized construction site layout by minimizing the probability of failure of the whole site. It will assist the decision makers and the risk managers in identifying the riskiest zones on a construction site.

BIM (Building Information Modeling) is a new concept in construction industry and becomes popular worldwide in recent years. BIM is widely used by individuals, businesses and government agencies. It is applied in all phases of construction lifecycle from planning and designing to constructing and maintaining. It contains different structure types of buildings and infrastructures including water, refuse, electricity, gas, communication utilities, roads, railways, bridges, ports and tunnels. The application of BIM in the building industry is relatively widespread while the development of BIM method in the domain of infrastructure is yet in infancy. In this research, we would like to study the compatibility of BIM in modeling the bridge by using Autodesk Revit.

This paper uses a case study approach to explore the extent to which the municipalities in Palestinian cities are ready to adopt GIS in their business procedures to improve service delivery and planning activities. For this purpose the business needs and data requirements of Bidya municipality which represent Palestine case were researched by adapting Tomlinson’s approach for planning GIS. The research provide a list of Information Products (IPs) which are cases of how GIS will benefit the municipality and support the various work processes, whereas these (IPs) were used to extract a Master Input Data List (MIDL) and a database schema which reflect the actual and comprehensive data requirements to operate the needed GIS. The research concluded that in general most Palestinian municipalities do have other priorities which are considered prerequisites for adopting the GIS and getting the maximum benefits out of it, such as; land registration, addressing system and activating the property tax collection system. اعتمدت هذه المقالة على منهج الحالة الدراسية لاستكشاف مدى جاهزية البلديات الفلسطينية لتبني انظمة المعلومات الجغرافية في اجراءات العمل وذلك لتحسين تزويد الخدمات للمواطنين وتحسين الانشطة التخطيطية. ولهذا الغرض تم بحث متطلبات العمل ومتطلبات البيانات في بلدية بديا كحالة دراسية تمثل مدى واسع من البلديات الفلسطينية وذلك باتباع منهجية روجر توملنسون لتخطيط انظمة المعلومات الجغرافية، وقد قدم البحث قائمة من "منتجات المعلومات" وهي عبارة عن حالات تطويع انظمة المعلومات الجغرافية لمنفعة البلديات ودعم العمليات المختلفة، كما تم استخدام "وصف منتجات المعلومات" لتطوير مصفوفة البيانات الرئيسية للبلدية ومخطط اساسي لقاعدة بيانات شاملة تعكس المتطلبات الحقيقية من المعلومات التي تلزم لتشغيل نظام معلومات جغرافي فعال يشمل كافة الدوائر والاقسام. وقد خلص البحث الى ان البلديات الفلسطينية بشكل عام لديها اولويات أخرى يجب تحقيقها وهي عبارة عن متطلبات سابقة واساسية لتبني نظام معلومات جغرافي والحصول على الفائدة القصوى منه، وامثلة هذه الاولويات: تسوية وتسجيل الاراضي، تسمية وترقيم الشوارع والمباني بغرض العنونة والترميز اضافة الى تفعيل نظام جباية ضريبة الاملاك حيث تمثل هذه البيانات مدخلات اساسية للنظام كما تتم ادارتها بفعالية من خلاله.

Public construction projects in countries with economic difficulties are funded by donor organizations. These types of projects in low-income countries have been negatively influenced by the communication gap between the among, consultant and the construction contractor, which emerges because of unclear definitions of responsibilities and problems in exchange of information. All stakeholders face significant problems as a result of this gap. The main objective of this paper is to identify and map the processes of donor-funded construction projects to facilitate clear definition of tasks and roles, and support sustainable communication in donor-funded projects. Following a literature review, the paper provides an analysis of the current processes in donor-funded projects and presents a process map for donor funded projects which is developed based on expert interviews and five case studies. Finally, the process map is validated by a set of semi-structured interviews.

Risk studies are very important to avoid human and economic losses. However the study cost becomes very expensive in some case when the site scale is very large. That's why; using a numerical simulation with a small-scale model is considered as a suitable solution. In order to have accurate results on which we can rely to assess the risk, it is necessary to use sophisticated means to simulate with a high efficiency the study area. One of the very accurate means able to do that is based on laser scanning techniques. This article describes how a 3D laser scanning can provide quickly and accurately a 3D model of the study area reduced model for the risk simulation step. Moreover, the necessary processing steps in the laser software named Geomagic v12, are highlighted to achieve a neat 3-D model. The article also describes the preparation of the model for the numerical simulation step.

To preserve the urban fabric or characteristics in specific quarters, there is often a need to either strengthen or lessen the homogeneity of the urban fabric when inserting new buildings. Evaluating the form of urban fabric is fundamentally important for urban design practice and relevant policy making. However, the quantitative methods and attempts are rare due to the lack of available methods. To address this deficiency, this article presents a GIS-based method to measure the homogeneity of urban fabric by extracting attributes directly from the geometry of 2D building footprints, including the angles between buildings, areas of building footprints, and distances between buildings. These attributes are calculated for separate overlaid grids in the open space between buildings, where each grid holds the measured values for one attribute. We test the method on a prototype, which we applied on four real sites using OpenStreetMap data. The results show how to categorize different kinds of urban fabric based on the new measure of homogeneity. The method can be used to interactively inform urban planners how new design proposals would affect the homogeneity of a neighborhood. Furthermore, the measure can be used to synthesize new design variants with a defined homogeneity.

International audience; Urban flooding due to climate changes, dam breaking and drainage systems being overwhelmed by rainfall causes a huge loss to mankind civilization every year all over the world. This work aims to minimize the flooding damage by optimally design the building location and interspace. The velocity, water pressure and the height of water are considered as the main factors to reduce the flooding damage. The multi-objective optimization is implemented by combing several techniques, including Design of Experiment (DOE), Response Surface Method (RSM) and the Genetic Algorithm (GA). The proposed methodology is validated with a case study on the topography of ESTP Cachan.

Construction sites contain several supporting facilities that are required to complete construction activities. These facilities are susceptible to damage due to the occurrence of natural or technological hazards such as fire, explosion, blast wave, and so on. These may cause adverse consequences for the whole construction process, which in turn lead to fatal accidents that have a major impact on worker and employee productivity, project completion time, project quality and project budget. Therefore, project planners must adopt and develop innovative approaches able to face the occurrence of potential hazards, minimize their consequences, and facilitate the evacuation of the site in case of their occurrence. One of these approaches is optimizing construction site layout. In general, generating construction site layout able minimizing risk resulting from natural or technological hazards is still a scientific challenge.In the present research, two proposed model (deterministic and probabilistic) are developed to minimize the risks within a construction site. The common methodology adopted to develop these two models consists of:• Modeling construction site components, for instance; electric generator, offices and material storages, in a 2D layout, to act as either hazardous source or potential target or both at the same time.• Modeling hazard: it shows the hazard interaction among site components and the attenuation of hazard.• Modeling vulnerability: it represents the potential weakness of whole targets to the hazard generated from each source.• Defining the utility function: it aims to afford an optimized site layout with minimum total risk in the construction site. The differential evolution algorithm is adopted to run optimization process.Particularly, in the deterministic model, we use space syntax principle in order to realize the impact of space configurations in evaluating the risk in the construction site. Therefore, as the evacuation process is considered in estimating the risk, the actual risk is amplified by utilizing penalty factor called mean depth. Furthermore, Dijkstra’s algorithm is run on deterministic model to find the safest paths (least risk paths) for evacuating sites from any position on the construction site towards the safe places in order to diminish losses and fatalities. On the other hand, the framework utilized to develop a probabilistic model assumed that the risk is combined of the individual failure of each facility within a construction site. Moreover, the numerical simulation is performed to find the probabilistic distribution of failure for the whole site.Geographic information system (GIS) capabilities were exploited, in this research, to present data in maps format, generate the spatial risk map in the construction site, and implement the Dijkstra’s algorithm and least-cost path analysis.For illustration purposes, the proposed models are employed in a case study consisting of several facilities. In the deterministic model, all of these facilities act as hazardous sources and potential targets, at the same time, while, in a probabilistic model, only three of these facilities act as fire hazardous sources, whereas, all of them are potential targets. The results revealed that the proposed models are efficient due to their capability of generating site layout with the safer work environment. In addition, the model is capable of highlighting the riskiest areas within a construction site. Moreover, the proposed models are able to generate paths through least-risk zones, which will minimize the serious injuries and victims in cases of emergencies; Les chantiers de construction contiennent plusieurs installations. Celles-ci sont susceptibles d’être endommagées par des incidents liés aux risques naturels ou technologiques comme les incendies, les explosions, les ondes de souffles, etc. Ces incidents peuvent avoir des conséquences néfastes sur l’ensemble du processus de construction, ce qui pourrait entrainer des accidents graves ayant un impact majeur sur la productivité des employés, le temps global du projet, sa qualité et son budget. Par conséquent les gestionnaires et les planificateurs du projet doivent adopter et développer des approches novatrices capables de faire face aux risques naturels potentiels, de minimiser leurs conséquences et de faciliter l’évacuation du site en cas de danger. Une de ces approches consiste à optimiser l’aménagement des chantiers de construction. En général, la réduction des dommages résultants de risques naturels ou technologiques est encore un défi scientifique.Dans cette thèse, deux modèles (déterministe et probabiliste) sont développés pour minimiser les risques au sein d’un chantier. La méthode adoptée pour le développement de ces deux modèles consiste en :• La modélisation des éléments du chantier, par exemple : le générateur électrique, les bureaux et les entrepôts de matériaux, sont modélisés en 2D, pour agir en tant que source d’aléa et/ou cible vulnérable potentielle.• La modélisation de l’aléa : elle montre l’interaction des aléas entre les composants du chantier.• La modélisation de la vulnérabilité : elle représente la faiblesse potentielle des cibles sur l’aléa généré par chaque source.• La définition de la fonction d’utilité : elle vise à offrir une disposition optimisée avec un minimum de risque total sur le chantier. L’algorithme à évolution différentielle est adopté pour exécuter le processus d’optimisation.D’une part, dans le modèle déterministe, nous utilisons le principe de la syntaxe spatiale pour étudier l’impact des configurations spatiales dans l’évaluation du risque sur le chantier. Par conséquent, comme le processus d’évacuation est pris en compte dans l’estimation du risque, le risque réel est amplifié en utilisant le facteur de pénalité appelé « profondeur moyenne ». L’algorithme de Dijkstra est appliqué sur un modèle déterministe afin de trouver les chemins les plus sûrs (chemins de moindre risque) pour évacuer les sites à partir de chaque position sur le chantier vers les lieux sûrs afin de diminuer les pertes humaines et matérielles.D’autre part, le modèle probabiliste suppose que le risque est composé de la défaillance individuelle de chaque installation sur le chantier de construction. La simulation numérique est utilisée pour trouver la distribution de probabilités des défaillances pour l’ensemble du site.Les fonctionnalités d’un SIG (Système d’Information Géographique) ont été utilisées pour présenter les données sous forme de cartes, pour produire des cartes spatiales de risque sur le chantier de construction, pour mettre en œuvre l’algorithme de Dijkastra et pour l’analyse du coût le plus faible.A titre indicatif, les modèles proposés sont utilisés dans un cas d’étude comprenant plusieurs installations. Dans le modèle déterministe, toutes ces installations agissent comme des sources d’aléa et des cibles vulnérables, en même temps, dans le modèle probabiliste, quelques-unes de ces installations agissent comme des sources d’aléa et toutes comme des cibles vulnérables. Les résultats obtenus montrent que les modèles proposés sont efficaces en raison de leur capacité à générer une disposition optimale du site avec un environnement de travail plus sûr. En outre, les modèles obtenus sont capables de mettre en évidence les zones les plus risquées d’un chantier, de générer les chemins d’évacuation les moins risqués, ce qui permettra de minimiser les blessures graves et les victimes en cas d’urgence