A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

Challenges in the Management of Geriatric Obesity in High Risk Populations.

The global prevalence of obesity in the older adult population is growing, an increasing concern in both the developed and developing countries of the world. The study of geriatric obesity and its management is a relatively new area of research, especially pertaining to those with elevated health risks. This review characterizes the state of science for this "fat and frail" population and identifies the many gaps in knowledge where future study is urgently needed. In community dwelling older adults, opportunities to improve both body weight and nutritional status are hampered by inadequate programs to identify and treat obesity, but where support programs exist, there are proven benefits. Nutritional status of the hospitalized older adult should be optimized to overcome the stressors of chronic disease, acute illness, and/or surgery. The least restrictive diets tailored to individual preferences while meeting each patient's nutritional needs will facilitate the energy required for mobility, respiratory sufficiency, immunocompentence, and wound healing. Complications of care due to obesity in the nursing home setting, especially in those with advanced physical and mental disabilities, are becoming more ubiquitous; in almost all of these situations, weight stability is advocated, as some evidence links weight loss with increased mortality. High quality interdisciplinary studies in a variety of settings are needed to identify standards of care and effective treatments for the most vulnerable obese older adults.

Active Surface Deformation Technology for Management of Marine Biofouling

Biofouling, the accumulation of biomolecules, cells, organisms and their deposits on submerged and implanted surfaces, is a ubiquitous problem across various human endeavors including maritime operations, medicine, food industries and biotechnology. Since several decades, there have been substantial research efforts towards developing various types of antifouling and fouling release approaches to control bioaccumulation on man-made surfaces. In this work we hypothesized, investigated and developed dynamic change of the surface area and topology of elastomers as a general approach for biofouling management. Further, we combined dynamic surface deformation of elastomers with other existing antifouling and fouling-release approaches to develop multifunctional, pro-active biofouling control strategies.

This research work was focused on developing fundamental, new and environment-friendly approaches for biofouling management with emphasis on marine model systems and applications, but which also provided fundamental insights into the control of infectious biofilms on biomedical devices. We used different methods (mechanical stretching, electrical-actuation and pneumatic-actuation) to generate dynamic deformation of elastomer surfaces. Our initial studies showed that dynamic surface deformation methods are effective in detaching laboratory grown bacterial biofilms and barnacles. Further systematic studies revealed that a threshold critical surface strain is required to debond a biofilm from the surface, and this critical strain is dependent on the biofilm mechanical properties including adhesion energy, thickness and modulus. To test the dynamic surface deformation approach in natural environment, we conducted field studies (at Beaufort, NC) in natural seawater using pneumatic-actuation of silicone elastomer. The field studies also confirmed that a critical substrate strain is needed to detach natural biofilm accumulated in seawater. Additionally, the results from the field studies suggested that substrate modulus also affect the critical strain needed to debond biofilms. To sum up, both the laboratory and the field studies proved that dynamic surface deformation approach can effectively detach various biofilms and barnacles, and therefore offers a non-toxic and environmental friendly approach for biofouling management.

Deformable elastomer systems used in our studies are easy to fabricate and can be used as complementary approach for existing commercial strategies for biofouling control. To this end, we aimed towards developed proactive multifunctional surfaces and proposed two different approaches: (i) modification of elastomers with antifouling polymers to produce multifunctional, and (ii) incorporation of silicone-oil additives into the elastomer to enhance fouling-release performance.

In approach (i), we modified poly(vinylmethylsiloxane) elastomer surfaces with zwitterionic polymers using thiol-ene click chemistry and controlled free radical polymerization. These surfaces exhibited both fouling resistance and triggered fouling-release functionalities. The zwitterionic polymers exhibited fouling resistance over short-term (∼hours) exposure to bacteria and barnacle cyprids. The biofilms that eventually accumulated over prolonged-exposure (∼days) were easily detached by applying mechanical strain to the elastomer substrate. In approach (ii), we incorporated silicone-oil additives in deformable elastomer and studied synergistic effect of silicone-oils and surface strain on barnacle detachment. We hypothesized that incorporation of silicone-oil additive reduces the amount of surface strain needed to detach barnacles. Our experimental results supported the above hypothesis and suggested that surface-action of silicone-oils plays a major role in decreasing the strain needed to detach barnacles. Further, we also examined the effect of change in substrate modulus and showed that stiffer substrates require lower amount of strain to detach barnacles.

In summary, this study shows that (1) dynamic surface deformation can be used as an effective, environmental friendly approach for biofouling control (2) stretchable elastomer surfaces modified with anti-fouling polymers provides a pro-active, dual-mode approach for biofouling control, and (3) incorporation of silicone-oils additives into stretchable elastomers improves the fouling-release performance of dynamic surface deformation technology. Dynamic surface deformation by itself and as a supplementary approach can be utilized biofouling management in biomedical, industrial and marine applications.

Vibration based health monitoring of civil infrastructure using energy harvesting techniques

The use of structural health monitoring of civil structures is ever expanding and by assessing the dynamical condition of structures, informed maintenance management can be conducted at both individual and network levels. With the continued growth of information age technology, the potential arises for smart monitoring systems to be integrated with civil infrastructure to provide efficient information on the condition of a structure. The focus of this thesis is the integration of smart technology with civil infrastructure for the purposes of structural health monitoring. The technology considered in this regard are devices based on energy harvesting materials. While there has been considerable focus on the development and optimisation of such devices using steady state loading conditions, their applications for civil infrastructure are less known. Although research is still in initial stages, studies into the uses associated with such applications are very promising. Through the use of the dynamical response of structures to a variety of loading conditions, the energy harvesting outputs from such devices is established and the potential power output determined. Through a power variance output approach, damage detection of deteriorating structures using the energy harvesting devices is investigated. Further applications of the integration of energy harvesting devices with civil infrastructure investigated by this research includes the use of the power output as a indicator for control. Four approaches are undertaken to determine the potential applications arising from integrating smart technology with civil infrastructure, namely • Theoretical analysis to determine the applications of energy harvesting devices for vibration based health monitoring of civil infrastructure. • Laboratory experimentation to verify the performance of different energy harvesting configurations for civil infrastructure applications. • Scaled model testing as a method to experimentally validate the integration of the energy harvesting devices with civil infrastructure. • Full scale deployment of energy harvesting device with a bridge structure. These four approaches validate the application of energy harvesting technology with civil infrastructure from a theoretical, experimental and practical perspective.

Ocean sprawl: challenges and opportunities for biodiversity management in a changing world.

The last few decades have seen rapid proliferation of hard artificial structures (e.g., energy infra-structure, aquaculture, coastal defences) in the marine environment: ocean sprawl. The replacement of natural, often sedimentary, substrata with hard substrata has altered the distribution of species, particularly non-indigenous species, and can facilitate the assisted migration of native species at risk from climate change. This has been likened to urbanization as a driver of global biotic homogenization in the marine environment—the process by which species invasions and extinctions increase the genetic, taxonomic, or functional similarity of communities at local, regional, and global scales. Ecological engineering research showed that small-scale engineering interventions can have a significant positive effect on the biodiversity of artificial structures, promoting more diverse and resilient communities on local scales. This knowledge can be applied to the design of multifunctional structures that provide a range of ecosystem services. In coastal regions, hybrid designs can work with nature to combine hard and soft approaches to coastal defence in a more environmentally sensitive manner. The challenge now is to manage ocean sprawl with the dual goal of supporting human populations and activities, simultaneously strengthening ecosystem resilience using an ecosystem- based approach.

Control Strategues for Automatic Generation Control over MTDC Grid

Increasingly in power systems, there is a trend towards the sharing of reserves and integration of markets over wide areas in order to enable increased penetration of renewable sources in interconnected power systems. In this paper, a number of simple PI and gain based Model Predictive Control algorithms are proposed for Automatic Generation Control in AC areas connected to Multi-Terminal Direct Current grids. The paper discusses how this approach improves the sharing of secondary reserves and could assist in achieving EU energy targets for 2030 and beyond.

Review of virtual power plant applications for the power system management and V2G market development

Utilization of renewable energy sources and energy storage systems is increasing with fostering new policies on energy industries. However, the increase of distributed generation hinders the reliability of power systems. In order to stabilize them, a virtual power plant emerges as a novel power grid management system. The VPP has a role to make a participation of different distributed energy resources and energy storage systems. This paper defines core technology of the VPP which are demand response and ancillary service concerning about Korea, America and Europe cases. It also suggests application solutions of the VPP to V2G market for restructuring national power industries in Korea.

What kind of expertise is needed for low energy construction

The construction industry is responsible for 40% of European Union (EU) end-use emissions but addressing this is problematic, as evident from the performance gap between design intention and on-site energy performance. There is a lack of the expertise needed for low energy construction (LEC) in the UK as the complex work processes involved require ‘energy literacy’ of all construction occupations, high qualification levels, broad occupational profiles, integrated teamworking, and good communication . This research identifies the obstacles to meeting these requirements, the nature of the expertise needed to break down occupational divisions and bridge those interfaces where the main heat losses occur, and the transition pathway implied. Obstacles include a decline in the level, breadth and quality of construction vocational education and training (VET), the lack of a learning infrastructure on sites, and a fragmented employment structure. To overcome these and develop enhanced understanding of LEC requires a transformation of the existing structure of VET provision and construction employment and a new curriculum based on a broader concept of agency and backed by rigorous enforcement of standards. This can be achieved through a radical transition pathway rather than market-based solutions to a low carbon future for the construction sector.

Utilizing “Big Data” to Improve the Hotel Sector’s Energy Efficiency: Lessons from Recent Economics Research

Hotel chains have access to a treasure trove of “big data” on individual hotels’ monthly electricity and water consumption. Benchmarked comparisons of hotels within a specific chain create the opportunity to cost-effectively improve the environmental performance of specific hotels. This paper describes a simple approach for using such data to achieve the joint goals of reducing operating expenditure and achieving broad sustainability goals. In recent years, energy economists have used such “big data” to generate insights about the energy consumption of the residential, commercial, and industrial sectors. Lessons from these studies are directly applicable for the hotel sector. A hotel’s administrative data provide a “laboratory” for conducting random control trials to establish what works in enhancing hotel energy efficiency.

Hotel Sustainability Benchmarking Index 2016: Energy, Water, and Carbon

Several studies have been undertaken or attempted by industry and academe to address the need for lodging industry carbon benchmarking. However, these studies have focused on normalizing resource use with the goal of rating or comparing all properties based on multivariate regression according to an industry-wide set of variables, with the result that data sets for analysis were limited. This approach is backward, because practical hotel industry benchmarking must first be undertaken within a specific location and segment.1 Therefore, the CHSB study’s goal is to build a representative database providing raw benchmarks as a base for industry comparisons.2 These results are presented in the CHSB2016 Index, through which a user can obtain the range of benchmarks for energy consumption, water consumption, and greenhouse gas emissions for hotels within specific segments and geographic locations.

Application of battery energy storage in the Québec interconnection

Le Système Stockage de l’Énergie par Batterie ou Batterie de Stockage d’Énergie (BSE) offre de formidables atouts dans les domaines de la production, du transport, de la distribution et de la consommation d’énergie électrique. Cette technologie est notamment considérée par plusieurs opérateurs à travers le monde entier, comme un nouveau dispositif permettant d’injecter d’importantes quantités d’énergie renouvelable d’une part et d’autre part, en tant que composante essentielle aux grands réseaux électriques. De plus, d’énormes avantages peuvent être associés au déploiement de la technologie du BSE aussi bien dans les réseaux intelligents que pour la réduction de l’émission des gaz à effet de serre, la réduction des pertes marginales, l’alimentation de certains consommateurs en source d’énergie d’urgence, l’amélioration de la gestion de l’énergie, et l’accroissement de l’efficacité énergétique dans les réseaux. Cette présente thèse comprend trois étapes à savoir : l’Étape 1 - est relative à l’utilisation de la BSE en guise de réduction des pertes électriques ; l’Étape 2 - utilise la BSE comme élément de réserve tournante en vue de l’atténuation de la vulnérabilité du réseau ; et l’Étape 3 - introduit une nouvelle méthode d’amélioration des oscillations de fréquence par modulation de la puissance réactive, et l’utilisation de la BSE pour satisfaire la réserve primaire de fréquence. La première Étape, relative à l’utilisation de la BSE en vue de la réduction des pertes, est elle-même subdivisée en deux sous-étapes dont la première est consacrée à l’allocation optimale et le seconde, à l’utilisation optimale. Dans la première sous-étape, l’Algorithme génétique NSGA-II (Non-dominated Sorting Genetic Algorithm II) a été programmé dans CASIR, le Super-Ordinateur de l’IREQ, en tant qu’algorithme évolutionniste multiobjectifs, permettant d’extraire un ensemble de solutions pour un dimensionnement optimal et un emplacement adéquat des multiple unités de BSE, tout en minimisant les pertes de puissance, et en considérant en même temps la capacité totale des puissances des unités de BSE installées comme des fonctions objectives. La première sous-étape donne une réponse satisfaisante à l’allocation et résout aussi la question de la programmation/scheduling dans l’interconnexion du Québec. Dans le but de réaliser l’objectif de la seconde sous-étape, un certain nombre de solutions ont été retenues et développées/implantées durant un intervalle de temps d’une année, tout en tenant compte des paramètres (heure, capacité, rendement/efficacité, facteur de puissance) associés aux cycles de charge et de décharge de la BSE, alors que la réduction des pertes marginales et l’efficacité énergétique constituent les principaux objectifs. Quant à la seconde Étape, un nouvel indice de vulnérabilité a été introduit, formalisé et étudié ; indice qui est bien adapté aux réseaux modernes équipés de BES. L’algorithme génétique NSGA-II est de nouveau exécuté (ré-exécuté) alors que la minimisation de l’indice de vulnérabilité proposé et l’efficacité énergétique représentent les principaux objectifs. Les résultats obtenus prouvent que l’utilisation de la BSE peut, dans certains cas, éviter des pannes majeures du réseau. La troisième Étape expose un nouveau concept d’ajout d’une inertie virtuelle aux réseaux électriques, par le procédé de modulation de la puissance réactive. Il a ensuite été présenté l’utilisation de la BSE en guise de réserve primaire de fréquence. Un modèle générique de BSE, associé à l’interconnexion du Québec, a enfin été proposé dans un environnement MATLAB. Les résultats de simulations confirment la possibilité de l’utilisation des puissances active et réactive du système de la BSE en vue de la régulation de fréquence.

Adapting the social-ecological system framework for urban stormwater management: the case of green infrastructure adoption

Stormwater management has long been a critical societal and environmental challenge for communities. An increasing number of municipalities are turning to novel approaches such as green infrastructure to develop more sustainable stormwater management systems. However, there is a need to better understand the technological decision-making processes that lead to specific outcomes within urban stormwater governance systems. We used the social-ecological system (SES) framework to build a classification system for identifying significant variables that influence urban stormwater governance decisions related to green infrastructure adoption. To adapt the framework, we relied on findings from observations at national stormwater meetings in combination with a systematic literature review on influential factors related to green infrastructure adoption. We discuss our revisions to the framework that helped us understand the decision by municipal governments to adopt green infrastructure. Remaining research needs and challenges are discussed regarding the development of an urban stormwater SES framework as a classification tool for knowledge accumulation and synthesis.

A long-term energy efficiency prediction model for the Brazilian automotive industry

According to law number 12.715/2012, Brazilian government instituted guidelines for a program named Inovar-Auto. In this context, energy efficiency is a survival requirement for Brazilian automotive industry from September 2016. As proposed by law, energy efficiency is not going to be calculated by models only. It is going to be calculated by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in market will be a key factor on profits of each automaker. Energy efficiency and its consequences should be taken into consideration in all of its aspects. In this scenario, emerges the following question: which is the efficiency curve of one automaker for long term, allowing them to adequate to rules, keep balancing on investment in technologies, increasing energy efficiency without affecting competitiveness of product lineup? Among several variables to be considered, one can highlight the analysis of manufacturing costs, customer value perception and market share, which characterizes this problem as a multi-criteria decision-making. To tackle the energy efficiency problem required by legislation, this paper proposes a framework of multi-criteria decision-making. The proposed framework combines Delphi group and Analytic Hierarchy Process to identify suitable alternatives for automakers to incorporate in main Brazilian vehicle segments. A forecast model based on artificial neural networks was used to estimate vehicle sales demand to validate expected results. This approach is demonstrated with a real case study using public vehicles sales data of Brazilian automakers and public energy efficiency data.

IoT Based Pain Management using Physiological Parameters

The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.

Microturbinas em redes de abastecimento de água

Nos dias de hoje a sociedade exige níveis qualitativos de vida cada vez mais elevados, o que torna prioritária a conceção de sistemas eficientes, não poluidores, económicos e diversificados que permitam uma gestão integrada e racionalizada de recursos tão escasso como é o da água e da energia. Em sistemas de abastecimento de água, o uso de válvulas redutoras de pressão (VRP) visa a uniformização e controlo de pressões, promovendo uma perda de carga localizada que dissipa a energia hidráulica presente através da redução dos valores de pressão a jusante. Estas são fundamentais no controlo e redução de pressão. A utilização de microturbinas é uma alternativa sustentável para o controle de pressão e, simultaneamente, para a produção de energia elétrica. Trata-se de um método de mitigação para controlar as perdas referidas convergindo no âmbito da eficiência energética. Na perspetiva de promover um aproveitamento de energia nas redes de abastecimento de água, o presente trabalho sugere a substituição de válvulas redutoras de pressão (VRP) por microturbinas. Desse modo, apresenta-se um método automático de seleção de (i) local para implementação e (ii) projeto de microturbinas para sistemas de abastecimento de água. Para a modelação do funcionamento dos sistemas hidráulicos recorre-se ao simulador hidráulico EPANET. Esta ferramenta possibilita avaliação de caudais e pressões em todos os pontos da rede durante um determinado intervalo de tempo. A metodologia desenvolvida permite selecionar o local ideal no sistema hidráulico através de uma análise de cada secção conduta-nó escolhendo-se a melhor opção baseada na produção de energia. Depois da localização procede-se à seleção do tipo de turbina (Kaplan, Francis, Pelton e Cross-flow) que vai depender das características do sistema hidráulico. Na etapa seguinte apresenta-se os resultados obtidos pela turbina nomeadamente a produção de energia elétrica anual, o investimento necessário, o tempo de retorno e a rentabilização ao final de um período de 25 anos. Na última etapa da metodologia, de forma avaliar o comportamento do sistema final, realiza-se uma nova simulação da rede mas tendo em conta a introdução da microturbina no local. Apresentam-se alguns casos de estudo que validam a ferramenta desenvolvida. A metodologia desenvolvida é comparada com um caso de estudo real. Em ambos os exemplos simulados a metodologia aplicada permite obter soluções com ganhos energéticos significativos associados ao sistema. Apenas num dos exemplos se observaram que a implementação da microturbina no sistema hidráulico não seria economicamente rentável.