Studio e ottimizzazione del processo di fabbricazione additiva (SLM) per applicazioni in ambito biomedicale: produzione di protesi e strutture reticolari

Il progetto di dottorato che verrà presentato in questa tesi è focalizzato sullo sviluppo di un metodo sperimentale per la produzione di protesi personalizzate utilizzando il processo di fabbricazione additiva di Selective Laser Melting (SLM). L’obiettivo è quello di definire una condizione di processo ottimizzata per applicazioni in ambito chirurgico che possa essere generalizzabile, ovvero che ne garantisca la riproducibilità al variare dell’anatomia del paziente e che rappresenti la base per estendere il metodo ad altre componenti protesiche. Il lavoro si è sviluppato lungo due linee principali, la cui convergenza ha permesso di realizzare prototipi di protesi complete utilizzando un solo processo: da una parte la produzione di componenti a massima densità per il raggiungimento di elevate resistenze meccaniche, buona resistenza ad usura e corrosione e controllo di tensioni residue e deformazione delle parti stampate. Dall’altra si sono studiate strutture reticolari a geometria e porosità controllata per favorire l’osteointegrazione della componente protesica post impianto. In questo studio sono stati messe a confronto le possibili combinazioni tra parametri di processo e sono state individuate le correlazioni con le proprietà finali dei componenti stampati. Partendo da queste relazioni si sono sviluppate le strategie tecnologiche per la progettazione e la produzione dei componenti. I test sperimentali svolti e i risultati ottenuti hanno dimostrato la fattibilità dell’utilizzo del processo SLM per la produzione di protesi personalizzate e sono stati fabbricati i primi prototipi funzionali. La fabbricazione di protesi personalizzate richiede, però, anche la progettazione e la produzione di strumentario chirurgico ad hoc. Per questo motivo, parallelamente allo studio della lega di Cromo Cobalto, sono stati eseguiti i test anche su campioni in INOX 316L. Anche in questo caso è stato possibile individuare una finestra operativa di processo che garantisse proprietà meccaniche comparabili, e in alcuni casi superiori, a quelle ottenute con processi convenzionali.

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Tool Condition Monitoring of Single-Point Dresser Using Acoustic Emission and Neural Networks Models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-level visualisation using Gaussian process latent variable models

Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.

A reference business process for ecological niche modelling

Ecological niche modelling combines species occurrence points with environmental raster layers in order to obtain models for describing the probabilistic distribution of species. The process to generate an ecological niche model is complex. It requires dealing with a large amount of data, use of different software packages for data conversion, for model generation and for different types of processing and analyses, among other functionalities. A software platform that integrates all requirements under a single and seamless interface would be very helpful for users. Furthermore, since biodiversity modelling is constantly evolving, new requirements are constantly being added in terms of functions, algorithms and data formats. This evolution must be accompanied by any software intended to be used in this area. In this scenario, a Service-Oriented Architecture (SOA) is an appropriate choice for designing such systems. According to SOA best practices and methodologies, the design of a reference business process must be performed prior to the architecture definition. The purpose is to understand the complexities of the process (business process in this context refers to the ecological niche modelling problem) and to design an architecture able to offer a comprehensive solution, called a reference architecture, that can be further detailed when implementing specific systems. This paper presents a reference business process for ecological niche modelling, as part of a major work focused on the definition of a reference architecture based on SOA concepts that will be used to evolve the openModeller software package for species modelling. The basic steps that are performed while developing a model are described, highlighting important aspects, based on the knowledge of modelling experts. In order to illustrate the steps defined for the process, an experiment was developed, modelling the distribution of Ouratea spectabilis (Mart.) Engl. (Ochnaceae) using openModeller. As a consequence of the knowledge gained with this work, many desirable improvements on the modelling software packages have been identified and are presented. Also, a discussion on the potential for large-scale experimentation in ecological niche modelling is provided, highlighting opportunities for research. The results obtained are very important for those involved in the development of modelling tools and systems, for requirement analysis and to provide insight on new features and trends for this category of systems. They can also be very helpful for beginners in modelling research, who can use the process and the experiment example as a guide to this complex activity. (c) 2008 Elsevier B.V. All rights reserved.

Single step process for particles surface modification or thin film composite production

Adsorbent materials and composites are quite useful for sensor development. Therefore, the aim of this work is the surface modification of particulates and/or composite formation. The material was produced by plasma polymerization of HMDS (hexamethyldisilazane) in a single step. SEM analysis shows good surface coverage of particulates with a plasma polymerized film formed by several clusters that might increase adsorption. Particles (starch. 5 5 mu m) recovered with HMDS films show good properties for retention of medium-size Organic molecules, such as dye. Thin films formed by a mixture of particles and plasma polymerized thin film HMDS species were obtained in a single step and can be used for retention of organic compounds, in liquid or gaseous phase. (C) 2009 Elsevier B.V. All rights reserved.

Adsorption of Ni(2+), Zn(2+) and Pb(2+) onto dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris. I. Single metal systems

Adsorption of Ni(2+), Zn(2+) or Pb(2+) by dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris was studied as a function of contact time and initial metal concentration. The zero point of charge calculated for these biosorbents (pH(zpc) 4.0 and 3.4, respectively) and additional pH tests suggested the use of pH in the range 5.0-5.5 for the experiments. The equilibrium isotherms were evaluated in terms of maximum sorption capacity and sorption affinity. The pseudo first and second order kinetic models were considered to interpret the experimental data, and the latter best described the adsorption system. Both the Freundlich and Langmuir models were shown to well describe the sorption isotherms, thus suggesting an intermediate mono/multilayer sorption mechanism. Compared to A. platensis (q(e) = 0.354, 0.495 and 0.508 mmol g(-1) for Ni(2+), Pb(2)+ and Zn(2+), respectively), C. vulgaris behaved as a better biosorbent because of higher equilibrium sorption capacity (q(e) = 0.499, 0.634 and 0.664 mmol g(-1), respectively). The removal efficiency decreased with increasing metal concentration, pointing out a passive adsorption process involving the active sites on the surface of the biomasses. The FT-IR spectroscopy evidenced that ions removal occurred mainly by interaction between metal and carboxylate groups present on both the cell walls. (C) 2011 Elsevier B.V. All rights reserved.

Single Intranasal Administration of 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine in C57BL/6 Mice Models Early Preclinical Phase of Parkinson`s Disease

Many studies have shown that deficits in olfactory and cognitive functions precede the classical motor symptoms seen in Parkinson`s disease (PD) and that olfactory testing may contribute to the early diagnosis of this disorder. Although the primary cause of PD is still unknown, epidemiological studies have revealed that its incidence is increased in consequence of exposure to certain environmental toxins. In this study, most of the impairments presented by C57BL/6 mice infused with a single intranasal (i.n.) administration of the proneurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) (1 mg/nostril) were similar to those observed during the early phase of PD, when a moderate loss of nigral dopamine neurons results in olfactory and memory deficits with no major motor impairments. Such infusion decreased the levels of the enzyme tyrosine hydroxylase in the olfactory bulb, striatum, and substantia nigra by means of apoptotic mechanisms, reducing dopamine concentration in different brain structures such as olfactory bulb, striatum, and prefrontal cortex, but not in the hippocampus. These findings reinforce the notion that the olfactory system represents a particularly sensitive route for the transport of neurotoxins into the central nervous system that may be related to the etiology of PD. These results also provide new insights in experimental models of PD, indicating that the i.n. administration of MPTP represents a valuable mouse model for the study of the early stages of PD and for testing new therapeutic strategies to restore sensorial and cognitive processes in PD.

Structure-hepatic disposition relationships for cationic drugs in isolated perfused rat livers: Transmembrane exchange and cytoplasmic binding process

This work studied the structure-hepatic disposition relationships for cationic drugs of varying lipophilicity using a single-pass, in situ rat liver preparation. The lipophilicity among the cationic drugs studied in this work is in the following order: diltiazem. propranolol. labetalol. prazosin. antipyrine. atenolol. Parameters characterizing the hepatic distribution and elimination kinetics of the drugs were estimated using the multiple indicator dilution method. The kinetic model used to describe drug transport (the two-phase stochastic model) integrated cytoplasmic binding kinetics and belongs to the class of barrier-limited and space-distributed liver models. Hepatic extraction ratio (E) (0.30-0.92) increased with lipophilicity. The intracellular binding rate constant (k(on)) and the equilibrium amount ratios characterizing the slowly and rapidly equilibrating binding sites (K-S and K-R) increase with the lipophilicity of drug (k(on) : 0.05-0.35 s(-1); K-S : 0.61-16.67; K-R : 0.36-0.95), whereas the intracellular unbinding rate constant (k(off)) decreases with the lipophilicity of drug (0.081-0.021 s(-1)). The partition ratio of influx (k(in)) and efflux rate constant (k(out)), k(in)/k(out), increases with increasing pK(a) value of the drug [from 1.72 for antipyrine (pK(a) = 1.45) to 9.76 for propranolol (pK(a) = 9.45)], the differences in k(in/kout) for the different drugs mainly arising from ion trapping in the mitochondria and lysosomes. The value of intrinsic elimination clearance (CLint), permeation clearance (CLpT), and permeability-surface area product (PS) all increase with the lipophilicity of drug [CLint (ml . min(-1) . g(-1) of liver): 10.08-67.41; CLpT (ml . min(-1) . g(-1) of liver): 10.80-5.35; PS (ml . min(-1) . g(-1) of liver): 14.59-90.54]. It is concluded that cationic drug kinetics in the liver can be modeled using models that integrate the presence of cytoplasmic binding, a hepatocyte barrier, and a vascular transit density function.

Full-scale demonstration of biological nutrient removal in a single tank SBR process

Complete biological nutrient removal (BNR) in a single tank, sequencing batch reactor (SBR) process, is demonstrated here at full-scale on a typical domestic wastewater. The unique feature of the UniFed process is the introduction of the influent into the settled sludge blanket during the settling and decant periods of the SBR operation. This achieves suitable conditions for denitrification and anaerobic phosphate release which is critical to successful biological phosphorus removal, It also achieves a selector effect, which helps in generating a compact, well settling biomass in the reactor. The results of this demonstration show that it is possible to achieve well over 90% removal of GOD, nitrogen and phosphorus in such a process. Effluent quality achieved over a six-month operating period directly after commissioning was: 29 mg/l GOD, 0.5 mg/l NH4-N, 1.5 mg/l NOx-N and 1.5 mg/l PO4-P (50%-iles of daily samples). During an 8-day, intensive sampling period, the effluent BOD5 was

Charged higgs bosons in single top production at the LHC

We show that a light charged Higgs boson signal via tau(+/-)nu decay can be established at the Large Hadron Collider (LHC) also in the case of single top production. This process complements searches for the same signal in the case of charged Higgs bosons emerging from t (t) over bar production. The models accessible include the Minimal Supersymmetric Standard Model (MSSM) as well a variety of 2-Higgs Doublet Models (2HDMs). High energies and luminosities are however required, thereby restricting interest on this mode to the case of the LHC running at 14TeV with design configuration.

Strength and damage analysis of composite-aluminium adhesively-bonded single-lap joints

With the need to find an alternative way to mechanical and welding joints, and at the same time to overcome some limitations linked to these traditional techniques, adhesive bonds can be used. Adhesive bonding is a permanent joining process that uses an adhesive to bond the components of a structure. Composite materials reinforced with fibres are becoming increasingly popular in many applications as a result of a number of competitive advantages. In the manufacture of composite structures, although the fabrication techniques reduce to the minimum by means of advanced manufacturing techniques, the use of connections is still required due to the typical size limitations and design, technological and logistical aspects. Moreover, it is known that in many high performance structures, unions between composite materials with other light metals such as aluminium are required, for purposes of structural optimization. This work deals with the experimental and numerical study of single lap joints (SLJ), bonded with a brittle (Nagase Chemtex Denatite XNRH6823) and a ductile adhesive (Nagase Chemtex Denatite XNR6852). These are applied to hybrid joints between aluminium (AL6082-T651) and carbon fibre reinforced plastic (CFRP; Texipreg HS 160 RM) adherends in joints with different overlap lengths (LO) under a tensile loading. The Finite Element (FE) Method is used to perform detailed stress and damage analyses allowing to explain the joints’ behaviour and the use of cohesive zone models (CZM) enables predicting the joint strength and creating a simple and rapid design methodology. The use of numerical methods to simulate the behaviour of the joints can lead to savings of time and resources by optimizing the geometry and material parameters of the joints. The joints’ strength and failure modes were highly dependent on the adhesive, and this behaviour was successfully modelled numerically. Using a brittle adhesive resulted in a negligible maximum load (Pm) improvement with LO. The joints bonded with the ductile adhesive showed a nearly linear improvement of Pm with LO.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.