Asset management of wastewater networks

Asset Management (AM) is a set of procedures operable at the strategic-tacticaloperational level, for the management of the physical asset’s performance, associated risks and costs within its whole life-cycle. AM combines the engineering, managerial and informatics points of view. In addition to internal drivers, AM is driven by the demands of customers (social pull) and regulators (environmental mandates and economic considerations). AM can follow either a top-down or a bottom-up approach. Considering rehabilitation planning at the bottom-up level, the main issue would be to rehabilitate the right pipe at the right time with the right technique. Finding the right pipe may be possible and practicable, but determining the timeliness of the rehabilitation and the choice of the techniques adopted to rehabilitate is a bit abstruse. It is a truism that rehabilitating an asset too early is unwise, just as doing it late may have entailed extra expenses en route, in addition to the cost of the exercise of rehabilitation per se. One is confronted with a typical ‘Hamlet-isque dilemma’ – ‘to repair or not to repair’; or put in another way, ‘to replace or not to replace’. The decision in this case is governed by three factors, not necessarily interrelated – quality of customer service, costs and budget in the life cycle of the asset in question. The goal of replacement planning is to find the juncture in the asset’s life cycle where the cost of replacement is balanced by the rising maintenance costs and the declining level of service. System maintenance aims at improving performance and maintaining the asset in good working condition for as long as possible. Effective planning is used to target maintenance activities to meet these goals and minimize costly exigencies. The main objective of this dissertation is to develop a process-model for asset replacement planning. The aim of the model is to determine the optimal pipe replacement year by comparing, temporally, the annual operating and maintenance costs of the existing asset and the annuity of the investment in a new equivalent pipe, at the best market price. It is proposed that risk cost provide an appropriate framework to decide the balance between investment for replacing or operational expenditures for maintaining an asset. The model describes a practical approach to estimate when an asset should be replaced. A comprehensive list of criteria to be considered is outlined, the main criteria being a visà- vis between maintenance and replacement expenditures. The costs to maintain the assets should be described by a cost function related to the asset type, the risks to the safety of people and property owing to declining condition of asset, and the predicted frequency of failures. The cost functions reflect the condition of the existing asset at the time the decision to maintain or replace is taken: age, level of deterioration, risk of failure. The process model is applied in the wastewater network of Oslo, the capital city of Norway, and uses available real-world information to forecast life-cycle costs of maintenance and rehabilitation strategies and support infrastructure management decisions. The case study provides an insight into the various definitions of ‘asset lifetime’ – service life, economic life and physical life. The results recommend that one common value for lifetime should not be applied to the all the pipelines in the stock for investment planning in the long-term period; rather it would be wiser to define different values for different cohorts of pipelines to reduce the uncertainties associated with generalisations for simplification. It is envisaged that more criteria the municipality is able to include, to estimate maintenance costs for the existing assets, the more precise will the estimation of the expected service life be. The ability to include social costs enables to compute the asset life, not only based on its physical characterisation, but also on the sensitivity of network areas to social impact of failures. The type of economic analysis is very sensitive to model parameters that are difficult to determine accurately. The main value of this approach is the effort to demonstrate that it is possible to include, in decision-making, factors as the cost of the risk associated with a decline in level of performance, the level of this deterioration and the asset’s depreciation rate, without looking at age as the sole criterion for making decisions regarding replacements.

Soil enzyme activities and biochemical indexes to assess soil quality in agronomic and forested ecosystems

The soil carries out a wide range of functions and it is important study the effects of land use on soil quality in order to provide most sustainable practices. Three fields trial have been considered to assess soil quality and functionality after human alteration, and to determine the power of soil enzymatic activities, biochemical indexes and mathematical model in the evaluation of soil status. The first field was characterized by conventional and organic management in which were tested also tillage effects. The second was characterized by conventional, organic and agro-ecological management. Finally, the third was a beech forest where was tested the effects of N deposition on soil organic carbon sequestration. Results highlight that both enzyme activities and biochemical indexes could be valid parameters for soil quality evaluation. Conventional management and plowing negatively affected soil quality and functionality with intensive tillage that lead to the downturn of microbial biomass and activity. Both organic and agro-ecological management revealed to be good practices for the maintenance of soil functionality with better microbial activity and metabolic efficiency. This positively affected also soil organic carbon content. At the eutrophic forest, enzyme activities and biochemical indexes positively respond to the treatments but one year of experimentation resulted to be not enough to observe variation in soil organic carbon content. Mathematical models and biochemical indicators resulted to be valid tools for assess soil quality, nonetheless it would be better including the microbial component in the mathematical model and consider more than one index if the aim of the work is to evaluate the overall soil quality and functionality. Concluding, the forest site is the richest one in terms of organic carbon, microbial biomass and activity while, the organic and the agro-ecological management seem to be the more sustainable but without taking in consideration the yield.

Integrating Machine Learning Paradigms for Predictive Maintenance in the Fourth Industrial Revolution era

In the last decade, manufacturing companies have been facing two significant challenges. First, digitalization imposes adopting Industry 4.0 technologies and allows creating smart, connected, self-aware, and self-predictive factories. Second, the attention on sustainability imposes to evaluate and reduce the impact of the implemented solutions from economic and social points of view. In manufacturing companies, the maintenance of physical assets assumes a critical role. Increasing the reliability and the availability of production systems leads to the minimization of systems’ downtimes; In addition, the proper system functioning avoids production wastes and potentially catastrophic accidents. Digitalization and new ICT technologies have assumed a relevant role in maintenance strategies. They allow assessing the health condition of machinery at any point in time. Moreover, they allow predicting the future behavior of machinery so that maintenance interventions can be planned, and the useful life of components can be exploited until the time instant before their fault. This dissertation provides insights on Predictive Maintenance goals and tools in Industry 4.0 and proposes a novel data acquisition, processing, sharing, and storage framework that addresses typical issues machine producers and users encounter. The research elaborates on two research questions that narrow down the potential approaches to data acquisition, processing, and analysis for fault diagnostics in evolving environments. The research activity is developed according to a research framework, where the research questions are addressed by research levers that are explored according to research topics. Each topic requires a specific set of methods and approaches; however, the overarching methodological approach presented in this dissertation includes three fundamental aspects: the maximization of the quality level of input data, the use of Machine Learning methods for data analysis, and the use of case studies deriving from both controlled environments (laboratory) and real-world instances.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.

Embedded systems and advanced signal processing for Acousto- Ultrasonic Inspections

Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) are becoming essential in many application contexts, e.g. civil, industrial, aerospace etc., to reduce structures maintenance costs and improve safety. Conventional inspection methods typically exploit bulky and expensive instruments and rely on highly demanding signal processing techniques. The pressing need to overcome these limitations is the common thread that guided the work presented in this Thesis. In the first part, a scalable, low-cost and multi-sensors smart sensor network is introduced. The capability of this technology to carry out accurate modal analysis on structures undergoing flexural vibrations has been validated by means of two experimental campaigns. Then, the suitability of low-cost piezoelectric disks in modal analysis has been demonstrated. To enable the use of this kind of sensing technology in such non conventional applications, ad hoc data merging algorithms have been developed. In the second part, instead, imaging algorithms for Lamb waves inspection (namely DMAS and DS-DMAS) have been implemented and validated. Results show that DMAS outperforms the canonical Delay and Sum (DAS) approach in terms of image resolution and contrast. Similarly, DS-DMAS can achieve better results than both DMAS and DAS by suppressing artefacts and noise. To exploit the full potential of these procedures, accurate group velocity estimations are required. Thus, novel wavefield analysis tools that can address the estimation of the dispersion curves from SLDV acquisitions have been investigated. An image segmentation technique (called DRLSE) was exploited in the k-space to draw out the wavenumber profile. The DRLSE method was compared with compressive sensing methods to extract the group and phase velocity information. The validation, performed on three different carbon fibre plates, showed that the proposed solutions can accurately determine the wavenumber and velocities in polar coordinates at multiple excitation frequencies.

Waste prevention: policy instruments and business model innovation

Waste prevention (WP) is a strategy which helps societies and individuals to strive for sufficiency in resource consumption within planetary boundaries alongside sustainable and equitable well-being and to decouple the concepts of well-being and life satisfaction from materialism. Within this dissertation, some instruments to promote WP are analysed, by adopting two perspectives: firstly, the one of policymakers, at different governance levels, and secondly, the one of business in the electrical and electronic equipment (EEE) sector. At a national level, the role of WP programmes and market-based instruments (extended producer responsibility, pay-as-you-throw schemes, deposit-refund systems, environmental taxes) in boosting prevention of municipal solid waste is investigated. Then, focusing on the Emilia-Romagna Region (Italy), the performances of the waste management system are assessed over a long period, including some years before and after an institutional reform of the waste management governance regime. The impact of a centralisation (at a regional level) of both planning and economic regulation of the waste services on waste generation and WP is analysed. Finally, to support the regional decision-makers in the prioritisation of publicly funded projects for WP, a framework for the sustainability assessment, the evaluation of success, and the prioritisation of WP measures was applied to some projects implemented by Municipalities in the Region. Trying to close the research gap between engineering and business, WP strategies are discussed as drivers for business model (BM) innovation in EEE sector. Firstly, an innovative approach to a digital tracking solution for professional EEE management is analysed. New BMs which facilitate repair, reuse, remanufacturing, and recycling are created and discussed. Secondly, the impact of BMs based on servitisation and on producer ownership on the extension of equipment lifetime is analysed, by performing a review of real cases of organizations in the EEE sector applying result- and use-oriented BMs.

Integración de sistemas para la documentación, gestión y puesta en valor del patrimonio arquitectónico: el parque arqueológico de las tumbas de la Vía Latina en Roma

En la civilización de la antigua Roma, tres de los aspectos más importantes de la vida cotidiana estaban vinculados a la arquitectura: las termas, los acueductos y las tumbas. Esta investigación propone el estudio de la integración de sistemas avanzados para la documentación, gestión y valorización del patrimonio arquitectónico funerario de la Vie Latina y la Appia Antica, en estrecha relación con el tema del Paisaje Cultural. De hecho, el Parque de las Tumbas Latinas alberga uno de los complejos funerarios más importantes, que en la actualidad conserva el aspecto tradicional del antiguo paisaje romano. A lo largo de una vía empedrada, como todas las vías consulares, la Vía Latina (al igual que la Vía Appia Antica), que, como recordaba Tito Livio, conectaba en su día las ciudades de Roma con Capua, sigue manteniendo "congelado" el antiguo trazado urbano/paisajístico. El sistema multiforme del Ager Romanus y del sitio cultural Via Latina/Appia Antica estudiado en esta investigación es, por tanto, comparable a una estructura viva y dinámica y, como tal, debe ser analizada. Por lo tanto, para diseñar una herramienta de protección y gestión tan "potente" y adecuada para un sitio histórico de enorme importancia, fue necesario utilizar las técnicas de levantamiento arquitectónico más avanzadas que se utilizan actualmente (como el escaneo láser y la fotogrametría, junto con un software de análisis específico), acompañadas de un estudio en profundidad de las técnicas de construcción antiguas. El último aspecto clave que pretende abordar la investigación es la catalogación. De hecho, los sitios y monumentos históricos no se pueden mantener sólo mediante su uso y utilización pasiva, sino activando todas las operaciones de protección y conservación mediante intervenciones directas (mantenimiento/restauración) e indirectas, como la catalogación constante de las obras históricas y la consiguiente "catalogación dinámica".

Late onset spinal cord ischemia after thoracoabdominal aortic aneurysm open repair

The aim of this study is to evaluate if spinal cord ischemia (SCI), especially its late presentation, and can be correlated to the results of intraoperative evoked potential monitoring (IOM). Methods. This study is a physician-initiated, retrospective, single-center, non-randomized study. Data from all patients undergoing a thoracoabdominal aortic aneurysm surgical repair (TAAA SR) between January 2016 and March 2020 IOM was collected and analyzed. Results. During the study period, 261 patients underwent TAAA SR with MEP/SSEPs monitoring [190 males, 73%; median age 65 (57-71)]. Thirty-seven patients suffered from SCI, for an overall rate of 14% (permanent 9%). When stratifying patients according to the SCI onset, 18 patients presented with an early (11 permanent) and 19 with a late SCI (<24h) (11 permanent). Of 261 patients undergoing TAAA SR with IOM, 15 were excluded due to changes in the upper extremity motor evoked potentials. For the remaining 246, the association between SCI and IOM was investigated: only irreversible IOM loss without peripheral changes have been found to be a risk factor for late onset SCI (p=.006). Furthermore, given that no statistical differences were found between the two groups when no IOM changes were recorded (p=.679), this situation cannot reliably rule out any SCI in our cohort. Independent risk factors for late spinal cord ischemia onset found at multivariate analysis were smoking history (p=.008), BMI>28 (p=.048) and TAAA extent II (p=.009). The irreversible MEP change without peripheral showed a trend of significance (p=.052). Conclusions. Evoked potential intraoperative monitoring is an important adjunct during thoracoabdominal aortic open repair to predict and possibly prevent spinal cord ischemia. Irreversible IOM loss without peripheral changes was predictive of late SCI, therefore more attention should be paid to the postoperative management of this subgroup of patients.

Sensor networks optimization and software development for Structural Health Monitoring based on ultrasonic guided waves

The Structural Health Monitoring (SHM) research area is increasingly investigated due to its high potential in reducing the maintenance costs and in ensuring the systems safety in several industrial application fields. A growing demand of new SHM systems, permanently embedded into the structures, for savings in weight and cabling, comes from the aeronautical and aerospace application fields. As consequence, the embedded electronic devices are to be wirelessly connected and battery powered. As result, a low power consumption is requested. At the same time, high performance in defects or impacts detection and localization are to be ensured to assess the structural integrity. To achieve these goals, the design paradigms can be changed together with the associate signal processing. The present thesis proposes design strategies and unconventional solutions, suitable both for real-time monitoring and periodic inspections, relying on piezo-transducers and Ultrasonic Guided Waves. In the first context, arrays of closely located sensors were designed, according to appropriate optimality criteria, by exploiting sensors re-shaping and optimal positioning, to achieve improved damages/impacts localisation performance in noisy environments. An additional sensor re-shaping procedure was developed to tackle another well-known issue which arises in realistic scenario, namely the reverberation. A novel sensor, able to filter undesired mechanical boundaries reflections, was validated via simulations based on the Green's functions formalism and FEM. In the active SHM context, a novel design methodology was used to develop a single transducer, called Spectrum-Scanning Acoustic Transducer, to actively inspect a structure. It can estimate the number of defects and their distances with an accuracy of 2[cm]. It can also estimate the damage angular coordinate with an equivalent mainlobe aperture of 8[deg], when a 24[cm] radial gap between two defects is ensured. A suitable signal processing was developed in order to limit the computational cost, allowing its use with embedded electronic devices.