Electrodialytic recovery of phosphorus and organic contaminants removal from sewage sludge

Phosphorus is a macronutrient essential to life which comes from phosphate rock, a non-renewable resource. Sewage sludge from wastewater treatment plants (WWTP) is a secondary resource rich in phosphorus that can be valorized. However, organic compounds are detected in sewage sludge, due to its non-polar and hydrophobic character, being considered an environmental risk. The present dissertation aims to study the efficiency of the electrodialytic process (ED) when applied to sewage sludge aiming phosphorus recovery and organic contaminants removal. Four organic compounds were analyzed: 17α-ethynylestradiol (EE2), bisphenol A (BPA), caffeine (Caf) and oxybenzone (MBPh). The experiments took place in an ED cell with two compartments and an anion exchange membrane, with the sludge in the cathode compartment. The experiments were carried out for three days with spiked sewage sludge (six assays). One control experiment was done without current, three experiments were carried out applying a constant current of 50, 75, and 100 mA and two experiments were carried out applying sequential currents: 50 mA, 75 mA and 100 mA and the opposite (100-75-50 mA). A qualitative and quantitative analysis of microorganisms existing in the samples was also done. At the end, the pH increased in the sewage sludge favoring phosphorus recovery. In terms of phosphorus, the highest recovery was achieved in the experiment run with 100 mA, where 70.3±2.0% of total phosphorus was recovered in the electrolyte. Generally, compounds degradation was favored by the current. Caf and MBPh achieved degradation percentages of 96.2±0.2% and 84.8±1.3%, respectively, in 100 mA assay. EE2 (83.1±1.7%) and BPA (91.8±4.6%) degradations were favored by 50 mA current. A total of 35 taxa from four different groups were identified, totalizing between 81,600-273,000 individuals per gram of initial sludges. After ED, microbial community population decreased between 47-98%. Arcella gibbosa represented 61% of the total observed organisms and revealed to be more tolerant to medium changes.

Removal of organic contaminants from wastewater using the electrodialytic process

Pharmaceuticals and personal care products (PPCPs) are widely used on a daily basis. After their usage they reach the wastewater treatment plants (WWTPs). These compounds have different physico-chemical characteristics, which makes them difficult to completely remove in the WWTPs, througth conventional treatments. Currently, there is no legislation regarding PPCPs thresholds in effluent discharge. But, even at vestigial concentrations, these compounds enclose environmental risks due to, e.g., endocrine disruption potential. There is a need of alternative techniques for their removal in WWTPs. The main goal of this work was to assess the use of electrodialytic (ED) process to remove PPCPs from the effluent to be discharged. A two-compartment ED cell was used testing (i) the effluent position in the cell (anode and cathode compartment); (ii) the use of anion (AEM) and cation exchange membrane (CEM); (iii) the treatment period (6, 12 and 24 hours); (iv) effluent recirculation and current steps; (v) the feasibility of sequential treatments. Phosphorus (P) removal from effluent and energetic costs associated to the process were also evaluated. Five PPCPs were studied – caffeine (CAF), bisphenol A (BPA), 17 β-estradiol (E2), ethinyl estradiol (EE2) and oxybenzone (MBPh). The ED process showed to be effective in the removal when effluent is in the anode compartment. Oxidation is suggested to be the main removal process, which was between 88 and 96%, for all the compounds, in 6 hours. Nevertheless, the presence of intermediates and/or by-products was also observed in some cases. Effluent recirculation should have a retention time in the ED cell big enough to promote removal whereas the current steps (effluent in anode compartment) slightly increased removal efficiencies (higher than 80% for all PPCPs). The sequential set of ED treatment (effluent in anode compartment) showed to be effective during both periods with a removal percentage between 80 and 95% and 73 to 88% in the case of AEM and CEM, respectively. Again, the main removal process is strongly suggested to be oxidation in the anode compartment. However, there was an increase of BOD5 and COD, which might be explained by effluent spiking, these parameters limiting the effluent discharge. From these treatments, the use of AEM, enhanced the P removal from effluent to minimize risk of eutrophication. Energetic costs of the best set-up (6 hours) are approximately 0,8€/m3 of wastewater, a value considered low, attending to the prices of other treatment processes.

Organic-inorganic nanostructured multilayers for calcium phosphate biomineralization

The weak fixation of biomaterials within the bone structure is one of the major reasons of implants failures. Calcium phosphate (CaP) coatings are used in bone tissue engineering to improve implant osseointegration by enhancing cellular adhesion, proliferation and differentiation, leading to a tight and stable junction between implant and host bone. It has also been observed that materials compatible with bone tissue either have a CaP coating or develop such a calcified surface upon implantation. Thus, the development of bioactive coatings becomes essential for further improvement of integration with the surrounding tissue. However, most of current applied CaP coatings methods (e.g. physical vapor deposition), cannot be applied to complex shapes and porous implants, provide poor structural control over the coating and prevent incorporation of bioactive organic compounds (e.g. antibiotics, growth factors) because of the used harsh processing conditions. Layer-by-layer (LbL) is a versatile technology that permits the building-up of multilayered polyelectrolyte films in mild conditions based on the alternate adsorption of cationic and anionic elements that can integrate bioactive compounds. As it is recognized in natureâ s biomineralization process the presence of an organic template to induce mineral deposition, this work investigate a ion based biomimetic method where all the process is based on LbL methodology made of weak natural-origin polyelectrolytes. A nanostructured multilayer component, with 5 or 10 bilayers, was produced initially using chitosan and chondroitin sulphate polyelectrolyte biopolymers, which possess similarities with the extracellular matrix and good biocompatibility. The multilayers are then rinsed with a sequential passing of solutions containing Ca2+ and PO43- ions. The formation of CaP over the polyelectrolyte multilayers was confirmed by QCM-D, SEM and EDX. The outcomes show that 10 polyelectrolyte bilayer condition behaved as a  better site for initiating the formation of CaP as the precipitation occur at earlier stages than in 5 polyelectrolyte bilayers one. This denotes that higher number of bilayers could hold the CaP crystals more efficiently. This work achieved uniform coatings that can be applied to any surface with access to the liquid media in a low-temperature method, which potentiates the manufacture of effective bioactive biomaterials with great potential in orthopedic applications.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Portuguese strengths and fragilities on safety and health practices

Despite improvements over the years, accidents continue to be a scourge in the construction sector, leading to an increase in the number of journal articles addressing the issue, in an attempt to help construction industry to increase safety performance [1]. This paper aims to, helping construction industry and particulary tunneling community, describe the Portuguese approach to most typical health and safety problems in underground excavations performed with the Sequential Excavation Method (SEM). The article will address various topics, from safety management and organizational practices, to collective and personal protection equipment, to emergency planning. nt problems in safety and health matters are similar to several other countries, the paper will expose a compilation of Portuguese best practices used to solve that problems. This enunciation of best practices describes experience from most important and recognized Project Owners and Contractors in Portugal. In a second phase it will be analysed Portuguese weaknesses, identifying preventive measures, and their comparative importance, that should be adopted in Portugal in order to reduce accidents and health diseases.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Dispersion and re-agglomeration of graphite nanoplates in polypropylene melts under controlled flow conditions

The kinetics of GnP dispersion in polypropylene melt was studied using a prototype small scale modular extensional mixer. Its modular nature enabled the sequential application of a mixing step, melt relaxation, and a second mixing step. The latter could reproduce the flow conditions on the first mixing step, or generate milder flow conditions. The effect of these sequences of flow constraints upon GnP dispersion along the mixer length was studied for composites with 2 and 10 wt.% GnP. The samples collected along the first mixing zone showed a gradual decrease of number and size of GnP agglomerates, at a rate that was independent of the flow conditions imposed to the melt, but dependent on composition. The relaxation zone induced GnP re-agglomeration, and the application of a second mixing step caused variable dispersion results that were largely dependent on the hydrodynamic stresses generated.

Analysis of integrated management systems from various perspectives

This article compiles the main topics addressed by management systems (MSs) literature concerningMSs integration by performing a systematic literature review. In this paper, it is intended to present themain limitations of non-integratedmanagement systems (IMSs), the main motivations driving an IMS implementation, the major resistances faced, the most common resultant benefits, the suitable guidelines and standards and the critical success factors. In addition, this paper addresses the issues concerning integration strategies and models, the integration levels or degrees achieved by an IMS and the audit function in an integrated context. The motivations that drive companies to integrate their management subsystems, the obstacles faced and the benefits collected may have internal or external origins. The publishing of standards guiding companies on how to integrate their management subsystems has been done mainly at a national level. There are several models that could be used in order to support companies in their management subsystems integration processes, and a sequential or an all-in strategy may be adopted. Four audit typologies can be distinguished, and the adoption of any of these typologies should consider resource availability and audit team know-how, among other features.

Ilustração de livros de literatura infantojuvenil em Portugal [2000-2009]: tipificação, tendências e padrões de recetividade do público-alvo

Tese de Doutoramento em Estudos da Criança (área de especialização em Comunicação Visual e Expressão Plástica)

Otimização com restrições de complementaridade: algoritmos e aplicações

Tese de Doutoramento em Engenharia Industrial e de Sistemas (PDEIS)

A search for high-mass resonances decaying to τ+τ− in pp collisions at s√=8 TeV with the ATLAS detector

A search for high-mass resonances decaying into τ+τ− final states using proton-proton collisions at s√=8 TeV produced by the Large Hadron Collider is presented. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 19.5-20.3 fb−1. No statistically significant excess above the Standard Model expectation is observed; 95% credibility upper limits are set on the cross section times branching fraction of Z′ resonances decaying into τ+τ− pairs as a function of the resonance mass. As a result, Z′ bosons of the Sequential Standard Model with masses less than 2.02 TeV are excluded at 95% credibility. The impact of the fermionic couplings on the Z′ acceptance is investigated and limits are also placed on a Z′ model that exhibits enhanced couplings to third-generation fermions.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Aplicação de técnicas e procedimentos Lean Production numa empresa da indústria automóvel

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Estudo, desenvolvimento de manuais de utilização e colocação em funcionamento da bancada SIMATIC da Siemens

Dissertação de mestrado em Engenharia Mecatrónica