Mapping building functionality and community relationships through a dynamic model, informing post-event building operations

Danial Mohabat Doost, Mamak Pourabdollahtootkaboni

Mapping building functionality and community relationships through a dynamic model, informing post-event building operations.

Rel. Gian Paolo Cimellaro, P. Gordon Warn. Politecnico di Torino, Corso di laurea magistrale in Architettura Per Il Progetto Sostenibile, 2017

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Abstract:	INTRODUCTION Sometimes resilience is considered as one of the indicators of sustainability. Some other recent studies suggested that resilience could put an end to sustainability, as a way of development for future cities. However, the correlation between these two is more complicated. It is possible to have sustainable cities -which can reduce resource and energy consumption, optimize waste management and be economically efficient- but not necessarily operative in the case of shocks and major turbulences, so that they are not resilient. Such cities are not truly sustainable. It is also possible to have resilient cities that are not sustainable according to energy consumption, social equity, economic efficiency, and so on. They are not even resilient, but rather resistant, as they resist the hazardous situations. As an example, on September 2004, more than one century of deforestation and soil erosion provoked landslide and flood in Gonaives (a commune in northern Haiti). Absence of a mitigation plan left the homeless people hungry and worsened the situation. In the city, people were living on roofs, as their homes have become uninhabitable. This catastrophic event showed how an unsustainable way of development might increase the vulnerability of communities. The first purpose of this study is to clarify the correspondence of sustainability and resilience in order to demonstrate the importance of considering both concepts simultaneously. In addition, it is important to assess and evaluate any project from both points of view to have a sustainable and resilient community. Rating and Evaluation determine where we are on the road to sustainability and resilience, and identify new opportunities and assessment methods to the organizational practices. In sustainability, different credit weighting tools are adopted by the most popular rating systems around the world. Most of them are developed for the assessment of buildings as nationally and globally, buildings contribute significantly to energy consumption, as well as to other environmental impacts, such as air emissions and solid waste generation. For example, 38% of US primary energy consumption is related to building operations and 65% of all 1997 Municipal Solid Wastes. In this case, green procurement in construction section plays a key role in sustainable development. Leadership in Energy and Environmental Design (LEED) is an example of green building certification programs used worldwide. LEED (Leadership in Energy & Environmental Design) which developed by USGBC (US green building council), attempts to wed elements of two primary methods of communicating environmental attributes that relate to buildings, Eco-labeling and Life Cycle Assessment (LCA). The LEED rating system is not the first green building program. However, it is the only program with national scope and the only one that has been adopted by many private organizations (Herman Miller, Ford Motor Co., Natural Resources Defense Council) as well as local (Portland OR, Seattle WA, San Jose CA) federal (GSA, Department of State) ,and government bodies in U.S. One of the critical issues in developing a rating system for assessment is the distribution of points and weights across the different areas and indicators. LEED is a credit-based system. The last version of LEED contains 110 credit points, which are divided among 7 impact areas: Sustainable Sites (SS), Water Efficiency (WE), Energy and Atmosphere (EA), Materials and Resources (MR), Indoor Environmental Quality (IEQ), Location and transportation, Innovation in design and regional priority (ID). In resilience, the vagueness of the concept makes it difficult to define, but it becomes even more problematic when trying to measure it. Measuring community resilience is still in the primary stages of development. There are different quantities for evaluating the level of resilience of a system including loss and downtime. Downtime -as the time necessary to restore a system's functionality- is the critical parameter of the recovery process after an abrupt event. The importance of the concept, leads us to review and postulate factors affecting downtime with a particular focus on those external to the building. Relevant literature on loss and downtime estimation are reviewed, from which a list of external factors affecting downtime is developed and categorized. This quantity is usually underestimated to the repair time, while the recovery process also includes the "recovery initiation delay". This study focuses on downtime estimation and tries to use a dynamic model to estimate the time needed to start the building repair after the hazard occurrence. Among several factors affecting downtime, those external to the building play a key role in determining this duration. Such factors are strongly dependent on community relationships. External factors - including transportation access, building inspection, utility disruption, financing, etc. - from Loma Prieta and Chile 2010 earthquakes are compiled and analyzed in order to investigate the relative effect of community dependent factors on building recovery initiation delay. A sensitivity analysis is done, as different factors do not have the same influence on recovery path. In addition, a general building functionality curve is presented to illustrate how community services and external factors affect recovery/downtime. This general recovery curve serves as an initial attempt to better understand the phases of recovery affected by various factors. Preliminary definitions related to functionality are reviewed and ideas are posed related to the relationship of these factors to the design of resilient-sustainable buildings.
Relatori:	Gian Paolo Cimellaro, P. Gordon Warn
Tipo di pubblicazione:	A stampa
Soggetti:	A Architettura > AO Progettazione A Architettura > AQ Spazi funzionali dell'abitazione
Corso di laurea:	Corso di laurea magistrale in Architettura Per Il Progetto Sostenibile
Classe di laurea:	Nuovo ordinamento > Laurea magistrale > LM-04 - ARCHITETTURA E INGEGNERIA EDILE-ARCHITETTURA
Aziende collaboratrici:	NON SPECIFICATO
URI:	http://webthesis.biblio.polito.it/id/eprint/5898
Capitoli:	INDEXES 1.Chapter I: Overview 1.1.Introduction 1.2.Clarifying the critical concepts -such as resilience, resistance and sustainability- and analyzing the correlation between them 2.Chapter II: Downtime and External Factors 2.1.What is downtime? 2.2.Literature review on downtime modeling focusing on the community relationships 2.3.Synthesis of factors affecting downtime 3.Chapter III: External Factors Effect on Recovery Phases 3.1.Definitions: functionality, capacity, downtime and vulnerability 3.2.Parameterizing the functionality-time curve and analyzing the effect of external factors on each recovery phase 3.3.Examples of external factors affecting building recovery and downtime 3.3.1.Building Occupancy Resumption Program (BORP) 3.3.2.San Francisco Bay Area Planning and Urban Research Association (SPUR) 4.Chapter IV: Methodology 4.1 .Motivations and a brief explanation about the proposed model 4.2.CPM (critical path method) 4.3.PERT (Program Evaluation Review Technique) 4.3.1.Probability distribution of the project completion time 5.Chapter V: Case Studies 5.1.Brief explanation about case studies 5.2.Loma Prieta earthquake 5.2.1.Transportation 5.2.2.Building Inspection 5.2.3.Obtaining Permits 5.2.4.Utilities 5.2.5.Financing 5.2.6.Result analysis 5.3.Chile 2010 earthquake 5.3.1.Transportation 5.3.2.Building inspection 5.3.3.Demand estimation 5.3.4.Financing 5.3.5.Mobilization of contractor, workforce and ordering/receiving materials 5.3.6.Engineering mobilization and redesigning 5.3.7.Utilities 5.3.8.Result analysis 6.Chapter VI: 6.1.Conclusions 7.List of Figures 8.List of Tables 9.References
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