Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

The implementation of artificial intelligence (AI), together with robotics, sensors, sensor networks, Internet of Things (IoT), and machine/deep learning modeling, has reached the forefront of research activities, moving towards the goal of increasing the efficiency in a multitude of applications and purposes related to environmental sciences. The development and deployment of AI tools requires specific considerations, approaches, and methodologies for their effective and accurate applications. This Special Issue focused on the applications of AI to environmental systems related to hazard assessment in urban, agriculture, and forestry areas

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

Environmental risk assessment in the mediterranean region using artificial neural networks

Los mapas auto-organizados han demostrado ser una herramienta apropiada para la clasificación y visualización de grupos de datos complejos. Redes neuronales, como los mapas auto-organizados (SOM) o las redes difusas ARTMAP (FAM), se utilizan en este estudio para evaluar el impacto medioambiental acumulativo en diferentes medios (aguas subterráneas, aire y salud humana). Los SOMs también se utilizan para generar mapas de concentraciones de contaminantes en aguas subterráneas simulando las técnicas geostadísticas de interpolación como kriging y cokriging. Para evaluar la confiabilidad de las metodologías desarrolladas en esta tesis, se utilizan procedimientos de referencia como puntos de comparación: la metodología DRASTIC para el estudio de vulnerabilidad en aguas subterráneas y el método de interpolación espacio-temporal conocido como Bayesian Maximum Entropy (BME) para el análisis de calidad del aire. Esta tesis contribuye a demostrar las capacidades de las redes neuronales en el desarrollo de nuevas metodologías y modelos que explícitamente permiten evaluar las dimensiones temporales y espaciales de riesgos acumulativos

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University

Radioactive Waste

The safe management of nuclear and radioactive wastes is a subject that has recently received considerable recognition due to the huge volume of accumulative wastes and the increased public awareness of the hazards of these wastes. This book aims to cover the practice and research efforts that are currently conducted to deal with the technical difficulties in different radioactive waste management activities and to introduce to the non-technical factors that can affect the management practice. The collective contribution of esteem international experts has covered the science and technology of different management activities. The authors have introduced to the management system, illustrate how old management practices and radioactive accident can affect the environment and summarize the knowledge gained from current management practice and results of research efforts for using some innovative technologies in both pre-disposal and disposal activities

A Matlab-CONTAM Toolbox for contaminant event monitoring in intelligent buildings

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 412)An intelligent building should take all the necessary steps to provide protection against the dispersion of contaminants from sources (events) inside the building which can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. Multi-zone models and software, such as CONTAM, have been widely used in building environmental studies for predicting airflows and the resulting contaminant transport. This paper describes a developed Matlab Toolbox that allows the creation of data sets from running multiple scenarios using CONTAM by varying the different problem parameters. The Matlab-CONTAM Toolbox is an expandable research tool which facilitates the implementation of various algorithms related to contamination event monitoring. In particular, this paper describes the implementation of state-of-the-art algorithms for detecting and isolating a contaminant source. The use of the Toolbox is demonstrated through a building case-study. The Matlab-CONTAM Toolbox is released under an open-source licence, and is available at https://github.com/KIOS-Research/matlab-contam-toolbox

A Matlab-CONTAM Toolbox for contaminant event monitoring in intelligent buildings

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 412)An intelligent building should take all the necessary steps to provide protection against the dispersion of contaminants from sources (events) inside the building which can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. Multi-zone models and software, such as CONTAM, have been widely used in building environmental studies for predicting airflows and the resulting contaminant transport. This paper describes a developed Matlab Toolbox that allows the creation of data sets from running multiple scenarios using CONTAM by varying the different problem parameters. The Matlab-CONTAM Toolbox is an expandable research tool which facilitates the implementation of various algorithms related to contamination event monitoring. In particular, this paper describes the implementation of state-of-the-art algorithms for detecting and isolating a contaminant source. The use of the Toolbox is demonstrated through a building case-study. The Matlab-CONTAM Toolbox is released under an open-source licence, and is available at https://github.com/KIOS-Research/matlab-contam-toolbox

International Conference on Civil Infrastructure and Construction (CIC 2020)

This is the proceedings of the CIC 2020 Conference, which was held under the patronage of His Excellency Sheikh Khalid bin Khalifa bin Abdulaziz Al Thani in Doha, Qatar from 2 to 5 February 2020. The goal of the conference was to provide a platform to discuss next-generation infrastructure and its construction among key players such as researchers, industry professionals and leaders, local government agencies, clients, construction contractors and policymakers. The conference gathered industry and academia to disseminate their research and field experiences in multiple areas of civil engineering. It was also a unique opportunity for companies and organizations to show the most recent advances in the field of civil infrastructure and construction. The conference covered a wide range of timely topics that address the needs of the construction industry all over the world and particularly in Qatar. All papers were peer reviewed by experts in their field and edited for publication. The conference accepted a total number of 127 papers submitted by authors from five different continents under the following four themes: Theme 1: Construction Management and Process Theme 2: Materials and Transportation Engineering Theme 3: Geotechnical, Environmental, and Geo-environmental Engineering Theme 4: Sustainability, Renovation, and Monitoring of Civil InfrastructureThe list of the Sponsors are listed at page 1

Advanced Technology of Waste Treatment

The protection of human health and the environment (representing the main reason for waste management), as well as the sustainable use of natural resources, requires chemical, biological, physical and thermal treatment of wastes. This refers to the conditioning (e.g., drying, washing, comminution, rotting, stabilization, neutralization, agglomeration, homogenization), conversion (e.g., incineration, pyrolysis, gasification, dissolution, evaporation), and separation (classification, direct and indirect (i.e., sensor-based) sorting) of all types of wastes to follow the principles of the waste hierarchy (i.e., prevention (not addressed by this issue), preparation for re-use, recycling, other recovery, and disposal). Longstanding challenges include the increase of yield and purity of recyclable fractions and the sustainable removal or destruction of contaminants from the circular economy.This Special Issue on “Advanced Technology of Waste Treatment” of Processes collects high-quality research studies addressing challenges on the broad area of chemical, biological, physical and thermal treatment of wastes