New Methods for ferrous raw materials characterization in electric steelmaking

425 p.In the siderurgical sector, the steel scrap is the most important raw material in electric steelmaking,contributing between 70% of the total production costs. It is well-known how the degree of which thescrap mix can be optimized, and also the degree of which the melting operation can be controlled andautomated, is limited by the knowledge of the properties of the scrap and other raw-materials in thecharge mix.Therefore, it is of strategic importance having accurate information about the scrap composition of thedifferent steel scrap types. In other words, knowing scrap characteristics is a key point in order to managethe steel-shop resources, optimize the scrap charge mix/composition at the electric arc furnace (EAF),increase the plant productivity, minimize the environmental footprint of steelmaking activities and tohave the lowest total cost of ownership of the plant.As a main objective of present doctoral thesis, the doctorate will provide new tools and methods of scrapcharacterization to increase the current recycling ration, through better knowledge of the quality of thescrap, and thus go in the direction of a 100% recycling ratio. In order to achieve it, two main workinglines were developed in present research. Firstly, it was analysed not only the different existingmethodologies for scrap characterization and EAF process optimization, but also to develop new methodsor combination of existing, Secondly, it was defined a general recommendations guide for implementingthese methods based on the specifics of each plant

Value of Mineralogical Monitoring for the Mining and Minerals Industry In memory of Prof. Dr. Herbert Pöllmann

This Special Issue, focusing on the value of mineralogical monitoring for the mining and minerals industry, should include detailed investigations and characterizations of minerals and ores of the following fields for ore and process control: Lithium ores—determination of lithium contents by XRD methods; Copper ores and their different mineralogy; Nickel lateritic ores; Iron ores and sinter; Bauxite and bauxite overburden; Heavy mineral sands. The value of quantitative mineralogical analysis, mainly by XRD methods, combined with other techniques for the evaluation of typical metal ores and other important minerals, will be shown and demonstrated for different minerals. The different steps of mineral processing and metal contents bound to different minerals will be included. Additionally, some processing steps, mineral enrichments, and optimization of mineral determinations using XRD will be demonstrated. Statistical methods for the treatment of a large set of XRD patterns of ores and mineral concentrates, as well as their value for the characterization of mineral concentrates and ores, will be demonstrated. Determinations of metal concentrations in minerals by different methods will be included, as well as the direct prediction of process parameters from raw XRD data

Affinity between bitumen and aggregate in hot mix asphalt by hyperspectral imaging and digital picture analysis

This study investigated the viability of quantifying the affinity between aggregate and bitumen by means of different imaging techniques. Experiments were arranged in accordance with the rolling-bottle test, as indicated in UNI EN 12697-11, “Test methods for hot bituminous conglomerates—Part 11”. Digital image processing (DIP) techniques have only recently been used for such quantification. The data gathered with a multi-sensor optical platform equipped with VIS–NIR and SWIR spectrometers were compared with DIP outcomes. Data were processed using the unsupervised ISODATA and the supervised parallelepiped algorithms. The exposed aggregate index (EAI) and the bitumen index (BIT) were calculated to retrieve the bitumen percentage coverage of different mixtures. The comparison with the results obtained employing the traditional 6, 24, 48 and 72 testing hours reveals the possibility to implement a standardized analysis methodology combining digital and hyperspectral imagery to highlight potential inaccuracies deriving from the visual interpretation

Magnetic field-based arc stability sensor for electric arc furnaces

During the last decades the strategy to define the optimal Electric Arc Furnaces (EAF) electrical operational parameters has been constantly evolving. Foaming slag practice is currently used to allow high power factors that ensures higher energy efficiency. However, this performance depends on strict electric arc stability control. Control strategies for these are normally defined for alternating current furnaces (AC EAF) and are based on intrusive and highly expensive systems. In this work we analyze the variation of the magnetic field vector around the direct current EAF (DC EAF) and its relationship with arc stability. We propose a cheap stability control system with no installation or integration requirements and thus, easily implementable to both AC and DC EAFs. To this end we have built a non-intrusive and low-cost 3-axis Hall-effect sensor that can be mounted neighboring the furnace’s electrical bars. The sensor allows acquiring the magnetic field magnitude and orientation that provides a newly defined arc stability factor metric. This proposed Arc Stability Index has been compared with three different alternative well established and more expensive measurement methodologies obtaining with similar results. The proposed index serves as a closed loop signal to the electrical regulation for controlling the arc voltage, ensuring the most convenient arc length that guaranties non-instabilities. The new system was developed and industrially validated at two different DC EAF’s in ArcelorMittal demonstrating an improvement of 6.7 kWh per Liquid steel ton during the evaluated period and a time reduction of 1.1 min per heat over the current standard procedure. Additional validation tests were also carried out also in ArcelorMittal AC EAF proving the capability of this technology for both AC and DC of furnaces.Partial financial support of this work by the Basque Govern-ment (Hazitek AURRERAB ZE-2017/00009 and FASIN ZE-2016/0016 Projects) is gratefully acknowledged

END OF LIFE MANAGEMENT OF ELECTRONIC WASTE

Electronic products are becoming obsolete at a very high rate due to rapid changes in consumer demand and technological advancements. However, on other hand End-of-Life (EOL) management of electronic products is not effectively approached while these products offer huge opportunities for effective recycling. In this context, this thesis has highlighted the current practices and issues related to EOL management of electronic products focusing on their different material compositions, the uses of their raw materials in the circular economy perspective. The thesis proposes the introduction of digital technologies into the recycling process to improve efficiency. More specifically, this thesis has focused on the corona electrostatic separation process and the improvement of efficiency based on the simulation of the particle trajectories to identify the most effective parameters. Thus, in this frame, a numerical model to predict the particle trajectories in a corona electrostatic separator is developed using COMSOL Multiphysics and MATLAB software and validated with experimental trials. The recycling of electronic waste is becoming challenging due to its diverse and constantly changing material composition. In this regard, this thesis illustrates the use of non-destructive visible near-infrared hyperspectral imaging (VNIR-HSI) technique to identify material accurately; the effectiveness of VNIR-HSI is demonstrated through an experimental campaign combined with machine learning models, such as Support Vector Machine, K-Nearest Neighbors and Neural Network.Nonostante i prodotti elettronici diventino obsoleti ad un ritmo molto elevato, a causa dei rapidi cambiamenti nella domanda dei consumatori e dei progressi tecnologici, la gestione del loro fine vita (End-of-Life (EOL)) non viene affrontata in modo efficace benché offra, invece, grandi opportunità di riciclo. In questo contesto, questa tesi ha evidenziato le attuali pratiche e problematiche relative alla gestione del fine vita dei prodotti elettronici concentrandosi sulla loro diversa composizione, l’utilizzo delle materie prime seconde ricavabili in una prospettiva di economia circolare. La tesi propone l’introduzione di tecnologie digitali nel processo di riciclo per migliorarne l'efficienza. In particolare, questa tesi si è concentrata sul processo di separazione elettrostatica a corona e sul miglioramento dell'efficienza grazie alla simulazione delle traiettorie delle particelle per identificare i parametri più efficaci. Pertanto, in questo studio, utilizzando i software COMSOL Multiphysics e MATLAB, è stato sviluppato un modello numerico per prevedere le traiettorie delle particelle in un separatore elettrostatico a corona; il modello è stato poi validato con prove sperimentali. Il riciclo dei rifiuti elettronici sta diventando sempre più complesso a causa della presenza di mix di materiali diversificati e in continua evoluzione. A questo proposito, la tecnologia di visione iperspettrale non distruttiva basata su lunghezze d’onda nel visibile e nel vicino infrarosso (VNIR-HSI) è stata utilizzata in questo lavoro di tesi per identificare il materiale in modo preciso; l'efficacia di VNIR-HSI, combinato con modelli di apprendimento automatico, come la Support Vector Machine, K-Nearest Neighbors e Neural Network, viene dimostrata attraverso una campagna sperimentale

APPLICATIONS OF INNOVATIVE BUILDING MATERIAL AND COMPUTER VISION METHODS IN GEOTECHNICAL ENGINEERING

Ph.D

Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas

In recent decades, remote sensing technology has been incorporated in numerous mineral exploration projects in metallogenic provinces around the world. Multispectral and hyperspectral sensors play a significant role in affording unique data for mineral exploration and environmental hazard monitoring. This book covers the advances of remote sensing data processing algorithms in mineral exploration, and the technology can be used in monitoring and decision-making in relation to environmental mining hazard. This book presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling, offering excellent information to professional earth scientists, researchers, mineral exploration communities and mining companies

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

Quantifying the physical composition of urban morphology throughout Wales based on the time series (1989-2011) analysis of Landsat TM/ETM+ images and supporting GIS data

Knowledge of impervious surface areas (ISA) and on their changes in magnitude, location, geometry and morphology over time is significant for a range of practical applications and research alike from local to global scales. Despite this, use of Earth Observation (EO) technology in mapping ISAs within some European Union (EU) countries, such as the United Kingdom (UK), is to some extent scarce. In the present study, a combination of methods is proposed for mapping ISA based on freely distributed EO imagery from Landsat TM/ETM+ sensors. The proposed technique combines a traditional classifier and a linear spectral mixture analysis (LSMA) with a series of Landsat TM/ETM+ images to extract ISA. Selected sites located in Wales, UK, are used for demonstrating the capability of the proposed method. The Welsh study areas provided a unique setting in detecting largely dispersed urban morphology within an urban-rural frontier context. In addition, an innovative method for detecting clouds and cloud shadow layers for the full area estimation of ISA is also presented herein. The removal and replacement of clouds and cloud shadows, with underlying materials is further explained. Aerial photography with a spatial resolution of 0.4 m, acquired over the summer period in 2005 was used for validation purposes. Validation of the derived products indicated an overall ISA detection accuracy in the order of ~97%. The latter was considered as very satisfactory and at least comparative, if not somehow better, to existing ISA products provided on a national level. The hybrid method for ISA extraction proposed here is important on a local scale in terms of moving forward into a biennial program for the Welsh Government. It offers a much less subjectively static and more objectively dynamic estimation of ISA cover in comparison to existing operational products already available, improving the current estimations of international urbanization and soil sealing. Findings of our study provide important assistance towards the development of relevant EO-based products not only inaugurate to Wales alone, but potentially allowing a cost-effective and consistent long term monitoring of ISA at different scales based on EO technology