Teos-based consolidants for stone conservation: evaluation of the effects and testing by x-ray imaging

Natural stones have been widely used in the construction field since antiquity. Building materials undergo decay processes due to mechanical,chemical, physical and biological causes that can act together. Therefore an interdisciplinary approach is required in order to understand the interaction between the stone and the surrounding environment. Utilization of buildings, inadequate restoration activities and in general anthropogenic weathering factors may contribute to this degradation process. For this reasons, in the last few decades new technologies and techniques have been developed and introduced in the restoration field. Consolidants are largely used in restoration and conservation of cultural heritage in order to improve the internal cohesion and to reduce the weathering rate of building materials. It is important to define the penetration depth of a consolidant for determining its efficacy. Impregnation mainly depends on the microstructure of the stone (i.e. porosity) and on the properties of the product itself. Throughout this study, tetraethoxysilane (TEOS) applied on globigerina limestone samples has been chosen as object of investigation. After hydrolysis and condensation, TEOS deposits silica gel inside the pores, improving the cohesion of the grains. X-ray computed tomography has been used to characterize the internal structure of the limestone samples,treated and untreated with a TEOS-based consolidant. The aim of this work is to investigate the penetration depth and the distribution of the TEOS inside the porosity, using both traditional approaches and advanced X-ray tomographic techniques, the latter allowing the internal visualization in three dimensions of the materials. Fluid transport properties and porosity have been studied both at macroscopic scale, by means of capillary uptake tests and radiography, and at microscopic scale,investigated with X-ray Tomographic Microscopy (XTM). This allows identifying changes in the porosity, by comparison of the images before and after the treatment, and locating the consolidant inside the stone. Tests were initially run at University of Bologna, where characterization of the stone was carried out. Then the research continued in Switzerland: X-ray tomography and radiography were performed at Empa, Swiss Federal Laboratories for Materials Science and Technology, while XTM measurements with synchrotron radiation were run at Paul Scherrer Institute in Villigen.

Preparazione di una resina epossidica bio-based e studio delle relative proprietà

Epoxy resins are very diffused materials due to their high added value deriving from high mechanical proprieties and thermal resistance; for this reason they are widely used both as metallic coatings in aerospace and in food packaging. However, their preparation uses dangerous reagents like bisphenol A and epichlorohydrin respectively classified as suspected of causing damage to fertility and to be carcinogen. Therefore, to satisfy the ever-growing attention to environmental problems and human safeness, we are considering alternative “green” processes through the use of reagents obtained as by-products from other processes and mild experimental conditions, and also economically sustainable and attractive for industries. Following previous results, we carried out the reaction leading to the formation of diphenolic acid (DPA), its allylation and the following epoxidation of the double bonds, all in aqueous solvent. In a second step the obtained product were cross-linked at high temperature with and without the use of hardeners. Then, on the obtained resin, some tests were performed like release in aqueous solution, scratch test and DSC analysis.

Modelling, simulation and optimization of maintenance considerations on condition based maintenance

Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.

Feasibility study and flow scheduling optimization of a multi-product pipeline system

The first goal of this study is to analyse a real-world multiproduct onshore pipeline system in order to verify its hydraulic configuration and operational feasibility by constructing a simulation model step by step from its elementary building blocks that permits to copy the operation of the real system as precisely as possible. The second goal is to develop this simulation model into a user-friendly tool that one could use to find an “optimal” or “best” product batch schedule for a one year time period. Such a batch schedule could change dynamically as perturbations occur during operation that influence the behaviour of the entire system. The result of the simulation, the ‘best’ batch schedule is the one that minimizes the operational costs in the system. The costs involved in the simulation are inventory costs, interface costs, pumping costs, and penalty costs assigned to any unforeseen situations. The key factor to determine the performance of the simulation model is the way time is represented. In our model an event based discrete time representation is selected as most appropriate for our purposes. This means that the time horizon is divided into intervals of unequal lengths based on events that change the state of the system. These events are the arrival/departure of the tanker ships, the openings and closures of loading/unloading valves of storage tanks at both terminals, and the arrivals/departures of trains/trucks at the Delivery Terminal. In the feasibility study we analyse the system’s operational performance with different Head Terminal storage capacity configurations. For these alternative configurations we evaluated the effect of different tanker ship delay magnitudes on the number of critical events and product interfaces generated, on the duration of pipeline stoppages, the satisfaction of the product demand and on the operative costs. Based on the results and the bottlenecks identified, we propose modifications in the original setup.

Development of a colorimetric indicator label for food oxidation based on hexanal detection

In this work, a colorimetric indicator for food oxidation based on the detection of hexanal in gas-phase, has been developed. In fact, in recent years, the food packaging industry has evolved towards new generation of packaging, like active and intelligent. According to literature (Pangloli P. et al. 2002), hexanal is the main product of a fatty acid oxidation: the linoleic acid. So, it was chosen to analyse two kinds of potato chips, fried in two different oils with high concentration of linoleic acid: olive oil and sunflower oil. Five different formulas were prepared and their colour change when exposed to hexanal in gas phase was evaluated. The formulas evaluations were first conducted on filter paper labels. The next step was to select the thickener to add to the formula, in order to coat a polypropylene film, more appropriate than the filter paper for a production at industrial scale. Three kinds of thickeners were tested: a cellulose derivative, an ethylene vinyl-alcohol and a polyvinyl alcohol. To obtain the final labels with the autoadhesive layer, the polypropylene film with the selected formula and thickener was coat with a water based adhesive. For both filter paper and polypropylene labels, with and without autoadhesive layer, the detection limit and the detection time were measured. For the selected formula on filter paper labels, the stability was evaluated, when conserved on the dark or on the light, in order to determine the storage time. Both potato chips samples, stocked at the same conditions, were analysed using an optimised Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) method, in order to determine the concentration of volatilized hexanal. With the aim to establish if the hexanal can be considered as an indicator of the end of potato chips shelf life, sensory evaluation was conducted each day of HS-SPME-GC-MS analysis.

Synthesis of KOH-based geopolymers for innovative applications

This study presents an evaluation on compressive strength of metakaolin-based geopolymers synthetized by using different activators, KOH and NaOH. The influence of NaOH/KOH concentration ratio together with curing temperature and time were investigated to find the best results from the compressive strength tests of metakaolin-based geopolymers, synthesized with a commercial metakaolin. Aggregates of small grain size referred as fillers, were added to reduce brittleness, and minimize the pore size and shrinkage of the final mixture creating a stronger network. In this work, silt recovered from industrial processes of wash water used for aggregates production was used as a filler in the production of KOH-based geopolymers, examining the possible influence on the mechanical strength of the final product. The curing temperatures chosen for the synthesis were 85°C, 60°C and 40°C. The samples were tested after 7 days and 28 days, according to the UNI EN 1015-11:2019 applied on Ca-based cements, analyzing the differences in mechanical strength comparing samples with similar and different compositions. The study presented in total 72 synthetized geopolymer specimens that were analyzed with unconfined compression test (UCT). The characterization of the starting materials metakaolin and silt was carried out using X- ray diffraction analysis (XRD). Whereas, the formed geopolymers were analyzed using X- ray diffraction (XRD), and scanning electron microscopy (SEM) with energy dispersive X- ray spectroscopy (EDS).

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

Graph-based Vision-Language Model for Multi-Modal Retrieval of Fashion Products

Artificial Intelligence is reshaping the field of fashion industry in different ways. E-commerce retailers exploit their data through AI to enhance their search engines, make outfit suggestions and forecast the success of a specific fashion product. However, it is a challenging endeavour as the data they possess is huge, complex and multi-modal. The most common way to search for fashion products online is by matching keywords with phrases in the product's description which are often cluttered, inadequate and differ across collections and sellers. A customer may also browse an online store's taxonomy, although this is time-consuming and doesn't guarantee relevant items. With the advent of Deep Learning architectures, particularly Vision-Language models, ad-hoc solutions have been proposed to model both the product image and description to solve this problems. However, the suggested solutions do not exploit effectively the semantic or syntactic information of these modalities, and the unique qualities and relations of clothing items. In this work of thesis, a novel approach is proposed to address this issues, which aims to model and process images and text descriptions as graphs in order to exploit the relations inside and between each modality and employs specific techniques to extract syntactic and semantic information. The results obtained show promising performances on different tasks when compared to the present state-of-the-art deep learning architectures.