Optimization Based Partitioning Selection for Improved Contaminant Detection Performance

Indoor Air Quality monitoring is an essential ingredient of intelligent buildings. The release of various airborne contaminants into the buildings, compromises the health and safety of occupants. Therefore, early contaminant detection is of paramount importance for the timely activation of proper contingency plans in order to minimize the impact of contaminants on occupants health. The objective of this work is to enhance the performance of a distributed contaminant detection methodology, in terms of the minimum detectable contaminant release rates, by considering the joint problem of partitioning selection and observer gain design. Towards this direction, a detectability analysis is performed to derive appropriate conditions for the minimum guaranteed detectable contaminant release rate for specific partitioning configuration and observer gains. The derived detectability conditions are then exploited to formulate and solve an optimization problem for jointly selecting the partitioning configuration and observer gains that yield the best contaminant detection performance

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

Innovative accessible sunken floor systems for multi-story steel buildings

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 1987.Includes bibliographical references (leaves 154-160).With the demands of telecommunications and computer equipment, building owners and designers are facing an increasingly difficult problem for wire management in today's electronic workplace. This thesis is to investigate and design the accessible sunken floor systems for multi-story steel buildings with proliferating data cables and mechanical equipment. The terminology of an accessible sunken floor system or a dropped floor system is not new. Sunken floor has been used in reinforced concrete buildings with flat slabs and multi-story steel-framed construction with solid wide-flange beams. However, the design of an accessible sunken floor system with open-web steel joists and joist girders is an innovation, by leading steel design and construction industry into a new era. Sunken floors are sirniliar to raised floors, which are composed of removable square floor panels on metal pedestals to provide space for electrical or mechanical equipment or both. The removable panels provide easy access to the equipment below. These floors are commonly used in computer rooms, clean rooms and new office buildings which require extensive mechanical and electrical service. A clean room environment with air return through accessible plenums is essential in microelectronics and pharmaceutical facilities, in hospital operating rooms, in bio-genetic research laboratories and production areas, and in assembly plants for items such as computer disk drives and compact disks. Accessible sunken floor systems are used to avoid ramps or stairs as opposite to raised floor systems. Also, the finished floor-to-floor height in multi-story construction is less than the acceptable height for a raised floor, with subsequent savings on other more expensive building materials. Moreover, the construction cycle for steel buildings with open-web steel joists and joist girders is faster if the finished floor is composed of removable floor panels. One of the proposed systems is to substitute conventional concrete metal decks for fire-rated acoustical ceilings and horizontal bracings to cut down the construction cycle and costs. A second variation of the proposed systems permits economies in concrete slab finish by using lightweight concrete poured on corrugated metal decks, or by using pour- in -place or precast slabs below the finished floor panels, and the floor system is suspended 4 inches below the top chord of the steel joists as a horizontal diaphragm and fire barrier. This thesis will explore the building system integration and forecast the construction cycle and costs. An evaluation of the proposed systems will be presented with matrix diagrams to summarize the conclusion of this paper.by Henry K. Kwan.S.M

Simulation methods for reliability-based design optimization and model updating of civil engineering structures and systems

This thesis presents a collection of original contributions pertaining to the subjects of reliability-based design optimization (RBDO) and model updating of civil engineering structures and systems. In this regard, probability theory concepts and tools are instrumental in the formulation of the herein reported developments. Firstly, two approaches are devised for the RBDO of structural dynamical systems under stochastic excitation. Namely, a stochastic search technique is proposed for constrained and unconstrained RBDO problems involving continuous, discrete and mixed discrete-continuous design spaces, whereas an efficient sensitivity assessment framework for linear stochastic structures is implemented to identify optimal designs and evaluate their sensitivities. Moreover, two classes of model updating problems are considered. In this context, the Bayesian interpretation of probability theory plays a key role in the proposed solution schemes. Specifically, contaminant source detection in water distribution networks is addressed by resorting to a sampling-based Bayesian model class selection framework. Furthermore, an effective strategy for Bayesian model updating with structural reliability methods is presented to treat identification problems involving structural dynamical systems, measured response data, and high-dimensional parameter spaces. The approaches proposed in this thesis integrate stochastic simulation techniques as an essential part of their formulation, which allows obtaining non-trivial information about the systems of interest as a byproduct of the solution processes. Overall, the findings presented in this thesis suggest that the reported methods can be potentially adopted as supportive tools for a number of practical decision-making processes in civil engineering.Diese Arbeit stellt eine Sammlung von Beiträgen vor, die sich mit der Reliability-based-Design-Optimization (RBDO) und dem Model updating von Strukturen und Systemen im Bauwesen befassen. In diesem Zusammenhang sind wahrscheinlichkeitstheoretische Konzepte für die Formulierung der hier vorgestellten Entwicklungen von entscheidender Bedeutung. Zunächst werden zwei Ansätze für eine RBDO von strukturdynamischen Systemen unter stochastischer Anregung entwickelt. Es wird eine stochastische Suchtechnik für beschränkte und unbeschränkte RBDO-Probleme vorgeschlagen. Diese beziehen kontinuierliche, diskrete und gemischt diskret-kontinuierliche Designräume ein. Gleichzeitig wird ein effizientes Framework zur Bewertung der Sensitivität lineare stochastische Strukturen implementiert, um optimale Designs zu identifizieren und ihre Sensitivitäten zu bewerten. Darüber hinaus werden zwei Klassen von Problem aus dem Model updating betrachtet. Der Fokus wird hierbei auf die Erkennung von Kontaminationsquellen in Wasserverteilungsnetzen mithilfe eines auf Stichproben basierenden Bayesian-Model-Class-selection-Framework gelegt. Ferner wird eine effektive Strategie zur Bearbeitung von Problemen des Bayesian-Model-updating, die strukturdynamischen Systeme, gemessene Systemantwortdaten und hochdimensionale Parameterräume umfassen, vorgestellt. Die beschriebenen Ansätze verwenden stochastische Simulationstechniken als wesentlicher Bestandteil ihrer Formulierung, wodurch nicht-triviale Informationen über betrachtete Systeme als Nebenprodukt der Lösungsprozesse gewonnen werden können. Insgesamt deuten die vorgestellten Ergebnisse dieser Arbeit darauf hin, dass die beschriebenen Methoden potenziell als unterstützende Elemente in praktischen Entscheidungsproblemen im Zusammenhang mit Strukturen und Systemen im Bauwesen eingesetzt werden können

Wireless Sensor Network Virtualization: A Survey

Wireless Sensor Networks (WSNs) are the key components of the emerging Internet-of-Things (IoT) paradigm. They are now ubiquitous and used in a plurality of application domains. WSNs are still domain specific and usually deployed to support a specific application. However, as WSN nodes are becoming more and more powerful, it is getting more and more pertinent to research how multiple applications could share a very same WSN infrastructure. Virtualization is a technology that can potentially enable this sharing. This paper is a survey on WSN virtualization. It provides a comprehensive review of the state-of-the-art and an in-depth discussion of the research issues. We introduce the basics of WSN virtualization and motivate its pertinence with carefully selected scenarios. Existing works are presented in detail and critically evaluated using a set of requirements derived from the scenarios. The pertinent research projects are also reviewed. Several research issues are also discussed with hints on how they could be tackled.Comment: Accepted for publication on 3rd March 2015 in forthcoming issue of IEEE Communication Surveys and Tutorials. This version has NOT been proof-read and may have some some inconsistencies. Please refer to final version published in IEEE Xplor

The Development of a Web-based Decision Support System for the Sustainable Management of Contaminated Land

Land is a finite natural resource that is increasingly getting exhausted as a result of land contamination. Land is made up of soil and groundwater, both of which have many functions for which we depend on, including provision of food and water, supporting shelter, natural flood defence, carbon sequestration, etc. Contaminants in land also pose a number of threats to public health and the environment; other natural resources; and have detrimental effects on property such as buildings, crops and livestock. The most effective method of dealing with these contaminants is to cleanup and return the sites to beneficial use. The cleanup process involves making a choice from amongst competing remediation technologies, where the wrong choice may have disastrous economic, environmental and/or social impacts. Contaminated land management is therefore much broader than the selection and implementation of remedial solutions, and requires extensive data collection and analysis at huge costs and effort. The need for decision support in contaminated land management decision-making has long been widely recognised, and in recent years a large number of Decision Support Systems (DSS) have been developed. This thesis presents the development of a Web-based knowledge-based DSS as an integrated management framework for the risk assessment of human health from, and sustainable management of, contaminated land. The developed DSS is based on the current UK contaminated land regime, published guidelines and technical reports from the UK Environment Agency (EA) and Department for Environment, Food and Rural Affairs (DEFRA) and other Government agencies and departments. The decision-making process of the developed DSS comprises of key stages in the risk assessment and management of contaminated land: (i) preliminary qualitative risk assessment; (ii) generic quantitative risk assessment; and (iii) options appraisal of remediation technologies and remediation design. The developed DSS requires site specific details and measured contaminant concentrations from site samples as input and produces a site specific report as output. The DSS output is intended to be used as information to support with contaminated land management decision-making.Great Western Researc