Produção de beta-glucanases por Trichoderma harzianum Rifai para obtenção gluco-oligossacarídeos a partir de botriosferana

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

Production of β-(1,3)-glucanases by Trichoderma harzianum Rifai: Optimization and Application to Produce Gluco-oligosaccharides from Paramylon and Pustulan

β-(1→3)-Glucanases were produced by Trichoderma harzianum Rifai PAMB-86 cultivated on botryosphaeran in a bench-fermenter and optimised by the response surface method. Maximal enzyme titres occurred at 5 days, initial pH 5.5 and aeration of 1.5vvm. β-(1→3)-The β-glucanolytic enzyme complex produced by T. harzianum Rifai PAMB- 86 was fractionated by gel filtration into 2 fractions (F-I, F-II), and employed to produce gluco-oligosaccharides from algal paramylon ((1→3)-β-D-glucan) and lichen pustulan ((1→6)-β-D-glucan). Both enzymes attacked paramylon to the extent of ~15-20% in 30 min releasing glucose and laminaribiose as major end-products, and laminarioligosaccharides of degree of polymerization (DP) ≥3. Only F-I degraded pustulan resulting in ~2% degradation at 30 min, with glucose, gentiobiose and gentio-oligosaccharides of DP ≥4 as major products. The difference in the nature of the hydrolysis products can be explained by the substrate specificities of each enzyme fraction, and the structural differences of the β-D-glucans attacked.

Probabilistic crack growth analyses using a boundary element model: Applications in linear elastic fracture and fatigue problems

This paper addresses the numerical solution of random crack propagation problems using the coupling boundary element method (BEM) and reliability algorithms. Crack propagation phenomenon is efficiently modelled using BEM, due to its mesh reduction features. The BEM model is based on the dual BEM formulation, in which singular and hyper-singular integral equations are adopted to construct the system of algebraic equations. Two reliability algorithms are coupled with BEM model. The first is the well known response surface method, in which local, adaptive polynomial approximations of the mechanical response are constructed in search of the design point. Different experiment designs and adaptive schemes are considered. The alternative approach direct coupling, in which the limit state function remains implicit and its gradients are calculated directly from the numerical mechanical response, is also considered. The performance of both coupling methods is compared in application to some crack propagation problems. The investigation shows that direct coupling scheme converged for all problems studied, irrespective of the problem nonlinearity. The computational cost of direct coupling has shown to be a fraction of the cost of response surface solutions, regardless of experiment design or adaptive scheme considered. (C) 2012 Elsevier Ltd. All rights reserved.

Development of instrumental and sensory analytical methods of food obtained by traditional and emerging technologies

The consumer demand for natural, minimally processed, fresh like and functional food has lead to an increasing interest in emerging technologies. The aim of this PhD project was to study three innovative food processing technologies currently used in the food sector. Ultrasound-assisted freezing, vacuum impregnation and pulsed electric field have been investigated through laboratory scale systems and semi-industrial pilot plants. Furthermore, analytical and sensory techniques have been developed to evaluate the quality of food and vegetable matrix obtained by traditional and emerging processes. Ultrasound was found to be a valuable technique to improve the freezing process of potatoes, anticipating the beginning of the nucleation process, mainly when applied during the supercooling phase. A study of the effects of pulsed electric fields on phenol and enzymatic profile of melon juice has been realized and the statistical treatment of data was carried out through a response surface method. Next, flavour enrichment of apple sticks has been realized applying different techniques, as atmospheric, vacuum, ultrasound technologies and their combinations. The second section of the thesis deals with the development of analytical methods for the discrimination and quantification of phenol compounds in vegetable matrix, as chestnut bark extracts and olive mill waste water. The management of waste disposal in mill sector has been approached with the aim of reducing the amount of waste, and at the same time recovering valuable by-products, to be used in different industrial sectors. Finally, the sensory analysis of boiled potatoes has been carried out through the development of a quantitative descriptive procedure for the study of Italian and Mexican potato varieties. An update on flavour development in fresh and cooked potatoes has been realized and a sensory glossary, including general and specific definitions related to organic products, used in the European project Ecropolis, has been drafted.

Propagation of nuclear data uncertainties in fuel cycle calculations using MONTE-CARLO Technique

The uncertainty propagation in fuel cycle calculations due to Nuclear Data (ND) is a important important issue for : issue for : • Present fuel cycles (e.g. high burnup fuel programme) • New fuel cycles designs (e.g. fast breeder reactors and ADS) Different error propagation techniques can be used: • Sensitivity analysis • Response Response Surface Method Surface Method • Monte Carlo technique Then, p p , , in this paper, it is assessed the imp y pact of ND uncertainties on the decay heat and radiotoxicity in two applications: • Fission Pulse Decay ( y Heat calculation (FPDH) • Conceptual design of European Facility for Industrial Transmutation (EFIT)

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Selective Laser Melting of the Eutectic Silver-Copper Alloy Ag 28 wt % Cu

The aim of this work was to perform a detailed investigation of the use of Selective Laser Melting (SLM) technology to process eutectic silver-copper alloy Ag 28 wt. % Cu (also called AgCu28). The processing occurred with a Realizer SLM 50 desktop machine. The powder analysis (SEM-topography, EDX, particle distribution) was reported as well as the absorption rates for the near-infrared (NIR) spectrum. Microscope imaging showed the surface topography of the manufactured parts. Furthermore, microsections were conducted for the analysis of porosity. The Design of Experiments approach used the response surface method in order to model the statistical relationship between laser power, spot distance and pulse time.

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

A prognostic assessment method for power electronics modules

This paper describes a prognostic method which combines the physics of failure models with probability reasoning algorithm. The measured real time data (temperature vs. time) was used as the loading profile for the PoF simulations. The response surface equation of the accumulated plastic strain in the solder interconnect in terms of two variables (average temperature, and temperature amplitude) was constructed. This response surface equation was incorporated into the lifetime model of solder interconnect, and therefore the remaining life time of the solder component under current loading condition was predicted. The predictions from PoF models were also used to calculate the conditional probability table for a Bayesian Network, which was used to take into account of the impacts of the health observations of each product in lifetime prediction. The prognostic prediction in the end was expressed as the probability for the product to survive the expected future usage. As a demonstration, this method was applied to an IGBT power module used for aircraft applications.

Investigation of Utilizing Single Surface Depressions in Optimization of NLF Aerofoil Design

An environment has been created for the optimisation of aerofoil profiles with inclusion of small surface features. For TS wave dominated flows, the paper examines the consequences of the addition of a depression on the aerodynamic optimisation of an NLF aerofoil, and describes the geometry definition fidelity and optimisation algorithm employed in the development process. The variables that define the depression for this optimisation investigation have been fixed, however a preliminary study is presented demonstrating the sensitivity of the flow to the depression characteristics. Solutions to the optimisation problem are then presented using both gradient-based and genetic algorithm techniques, and for accurate representation of the inclusion of small surface perturbations it is concluded that a global optimisation method is required for this type of aerofoil optimisation task due to the nature of the response surface generated. When dealing with surface features, changes in the transition onset are likely to be of a non-linear nature so it is highly critical to have an optimisation algorithm that is robust, suggesting that for this framework, gradient-based methods alone are not suited.

Integration of design of experiment, surface response methodology and multi-layer validation to predict the effect of blanching on colour of tomato juice

Response surface methodology was used to develop models to predict the effect of tomato cultivar, juice pH, blanching temperature and time on colour change of tomato juice after blanching. The juice from three tomato cultivars with adjusted pH levels ranging from 3.9 to 4.6 were blanched at temperatures from 60-100 °C for 1-5 min using the central composite design (CCD). The colour change was assessed by calculating the redness (a/b) and total colour change (∆E) after measuring the Hunter L, a and b values. Developed models for both redness and ∆E were significant (p<0.0001) with satisfactory coefficient of determination (R2 = 0.99 and 0.97) and low coefficient of variation (CV% = 1.89 and 7.23), respectively. Multilevel validation that was implemented revealed that the variation between the predicted and experimental values obtained for redness and ∆E were within the acceptable error range of 7.3 and 22.4%, respectively

A Simple and Green Analytical Method for the Determination of Formaldehyde

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate Development and Validation of a Stability-Indicating HPLC Method for the Determination of Glimepiride in Tablets

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

Optimisation of a sample preparation method for the determination of fumonisin B-1 in rice

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Laser shock peening without absorbent coating (LSPwC) effect on 3D surface topography and mechanical properties of 6082-T651 Al alloy

The influence of nanosecond laser pulses applied by laser shock peening without absorbent coating (LSPwC) with a Q-switched Nd:YAG laser operating at a wavelength of λ = 1064 nm on 6082-T651 Al alloy has been investigated. The first portion of the present study assesses laser shock peening effect at two pulse densities on three-dimensional (3D) surface topography characteristics. In the second part of the study, the peening effect on surface texture orientation and micro-structure modification, i.e. the effect of surface craters due to plasma and shock waves, were investigated in both longitudinal (L) and transverse (T) directions of the laser-beam movement. In the final portion of the study, the changes of mechanical properties were evaluated with a residual stress profile and Vickers micro-hardness through depth variation in the near surface layer, whereas factorial design with a response surface methodology (RSM) was applied. The surface topographic and micro-structural effect of laser shock peening were characterised with optical microscopy, InfiniteFocus® microscopy and scanning electron microscopy (SEM). Residual stress evaluation based on a hole-drilling integral method confirmed higher compression at the near surface layer (33 μm) in the transverse direction (σmin) of laser-beam movement, i.e. − 407 ± 81 MPa and − 346 ± 124 MPa, after 900 and 2500 pulses/cm2, respectively. Moreover, RSM analysis of micro-hardness through depth distribution confirmed an increase at both pulse densities, whereas LSPwC-generated shock waves showed the impact effect of up to 800 μm below the surface. Furthermore, ANOVA results confirmed the insignificant influence of LSPwC treatment direction on micro-hardness distribution indicating essentially homogeneous conditions, in both L and T directions.