Optimization of the extraction process of polyphenols from cashew apple agro-industrial residues

The goal of this study was to determine the chemical composition of cashew apples agro-industrial residue and optimize the process of polyphenols extraction in this residue. The extraction process conditions were defined using a 24-1 fractional factorial experimental design using acetone and methanol as solvents. The independent variables were: time (30 to 90 min), temperature (30 to 50 °C), solvent concentrations (50% to 90%), agitation speed (100 to 300 rpm); the dependent variables were: total phenolic content and DPPH scavenging capacity. The optimized process was carried out by applying the Central Composite Rotational Design (CCRD) considering the results obtained with the 24-1 fractional factorial experimental design. The residue presented bioactive compounds in its composition, with emphasis on the content of total phenolic compounds (1975.64 mg/ 100 g). The extraction process was not affected by methanol; however, acetone affected the amounts of extracted phytochemicals. Extracts with high levels of polyphenols and strong DPPH scavenging capacity (> 80%) were obtained using 55% acetone, 30 minutes, 30 °C, and 150 rpm. The results showed that cashew apple residue is a potential natural source of bioactive compounds with strong antioxidant capacity. These compounds could be used partially or totally to replace synthetic antioxidants.

Optimization of Lignin Peroxidase, Manganese Peroxidase, and Lac Production from Ganoderma lucidum Under Solid State Fermentation of Pineapple Leaf

This study was undertaken to isolate ligninase-producing white-rot fungi for use in the extraction of fibre from pineapple leaf agriwaste. Fifteen fungal strains were isolated from dead tree trunks and leaf litter. Ligninolytic enzymes (lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac)), were produced by solid-state fermentation (SSF) using pineapple leaves as the substrate. Of the isolated strains, the one showing maximum production of ligninolytic enzymes was identified to be Ganoderma lucidum by 18S ribotyping. Single parameter optimization and response surface methodology of different process variables were carried out for enzyme production. Incubation period, agitation, and Tween-80 were identified to be the most significant variables through Plackett-Burman design. These variables were further optimized by Box-Behnken design. The overall maximum yield of ligninolytic enzymes was achieved by experimental analysis under these optimal conditions. Quantitative lignin analysis of pineapple leaves by Klason lignin method showed significant degradation of lignin by Ganoderma lucidum under SSF

Optimization Strategies Based on Sequential Quadratic Programming Applied for a Fermentation Process for Butanol Production

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

Efficient robust optimization based on polynomial chaos and tabu search algorithm

The study of robust design methodologies and techniques has become a new topical area in design optimizations in nearly all engineering and applied science disciplines in the last 10 years due to inevitable and unavoidable imprecision or uncertainty which is existed in real word design problems. To develop a fast optimizer for robust designs, a methodology based on polynomial chaos and tabu search algorithm is proposed. In the methodology, the polynomial chaos is employed as a stochastic response surface model of the objective function to efficiently evaluate the robust performance parameter while a mechanism to assign expected fitness only to promising solutions is introduced in tabu search algorithm to minimize the requirement for determining robust metrics of intermediate solutions. The proposed methodology is applied to the robust design of a practical inverse problem with satisfactory results.

Optimization of xylanase production by Bacillus circulans D1 in submerged fermentation using response surface methodology

In this work, a 3(3) factorial design was performed with the aim of optimizing the culture conditions for xylanase production by an alkalophilic thermophilic strain of Bacillus circulans, using response surface methodology. The variables involved in this study were xylan concentration (X-1), pH (X-2) and cultivation time (X-3). The optimal response region was approached without using paths of steepest ascent. Statistical analysis of results showed that, in the range studied, only pH did not have a significant effect on xylanase production. A second-order model was proposed to represent the enzymic activity as a function of xylan concentration (X-1) and cultivation time (X-3). The optimum xylan concentration and cultivation time were 5 g/l and 48 h, respectively. Under these conditions, the model predicted a xylanase activity of 19.1 U/ml. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Optimization of an amperometric biosensor for the detection of hepatitis C virus using fractional factorial designs

Fractional factorial design and factorial with center point design were applied to the development of an amperometric biosensor for the detection of the hepatitis C virus. Biomolecules were immobilized by adsorption on graphite electrodes modified with siloxane-poly(propyleneoxide) hybrid matrix prepared using the sol-gel method. Several parameters were optimized, such as the streptavidin concentration at 0.01 mg mL(-1) and 1.0% bovine serum albumin, the incubation time of the electrodes in the complementary DNA solution for 30 minutes and a 1: 1500 dilution of the avidin-peroxidase conjugate, among others. The application of chemometric studies has been efficient, since the best conditions have been established with a restricted number of experiments, indicating the influence of different factors on the system.

A modified ant colony optimization algorithm modeled on tabu-search methods

An earlier model underlying the foraging strategy of a pachycodyla apicalis ant is modified. The proposed algorithm incorporates key features of the tabu-search method in the development of a relatively simple but robust global ant colony optimization algorithm. Numerical results are reported to validate and demonstrate the feasibility and effectiveness of the proposed algorithm in solving electromagnetic (EM) design problems.

Optimum design of experiments for statistical inference

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

A comparison of deterministic, reliability-based and risk-based structural optimization under uncertainty

In this paper, the effects of uncertainty and expected costs of failure on optimum structural design are investigated, by comparing three distinct formulations of structural optimization problems. Deterministic Design Optimization (DDO) allows one the find the shape or configuration of a structure that is optimum in terms of mechanics, but the formulation grossly neglects parameter uncertainty and its effects on structural safety. Reliability-based Design Optimization (RBDO) has emerged as an alternative to properly model the safety-under-uncertainty part of the problem. With RBDO, one can ensure that a minimum (and measurable) level of safety is achieved by the optimum structure. However, results are dependent on the failure probabilities used as constraints in the analysis. Risk optimization (RO) increases the scope of the problem by addressing the compromising goals of economy and safety. This is accomplished by quantifying the monetary consequences of failure, as well as the costs associated with construction, operation and maintenance. RO yields the optimum topology and the optimum point of balance between economy and safety. Results are compared for some example problems. The broader RO solution is found first, and optimum results are used as constraints in DDO and RBDO. Results show that even when optimum safety coefficients are used as constraints in DDO, the formulation leads to configurations which respect these design constraints, reduce manufacturing costs but increase total expected costs (including expected costs of failure). When (optimum) system failure probability is used as a constraint in RBDO, this solution also reduces manufacturing costs but by increasing total expected costs. This happens when the costs associated with different failure modes are distinct. Hence, a general equivalence between the formulations cannot be established. Optimum structural design considering expected costs of failure cannot be controlled solely by safety factors nor by failure probability constraints, but will depend on actual structural configuration. (c) 2011 Elsevier Ltd. All rights reserved.

A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Nonlinear / electromagnetic co-simulation and co-design of microwave links in highly polluted and / or strongly inhomogeneous environments

The objective of the Ph.D. thesis is to put the basis of an all-embracing link analysis procedure that may form a general reference scheme for the future state-of-the-art of RF/microwave link design: it is basically meant as a circuit-level simulation of an entire radio link, with – generally multiple – transmitting and receiving antennas examined by EM analysis. In this way the influence of mutual couplings on the frequency-dependent near-field and far-field performance of each element is fully accounted for. The set of transmitters is treated as a unique nonlinear system loaded by the multiport antenna, and is analyzed by nonlinear circuit techniques. In order to establish the connection between transmitters and receivers, the far-fields incident onto the receivers are evaluated by EM analysis and are combined by extending an available Ray Tracing technique to the link study. EM theory is used to describe the receiving array as a linear active multiport network. Link performances in terms of bit error rate (BER) are eventually verified a posteriori by a fast system-level algorithm. In order to validate the proposed approach, four heterogeneous application contexts are provided. A complete MIMO link design in a realistic propagation scenario is meant to constitute the reference case study. The second one regards the design, optimization and testing of various typologies of rectennas for power generation by common RF sources. Finally, the project and implementation of two typologies of radio identification tags, at X-band and V-band respectively. In all the cases the importance of an exhaustive nonlinear/electromagnetic co-simulation and co-design is demonstrated to be essential for any accurate system performance prediction.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

Dynamic Response Optimization of Vehicles through Efficient Multibody Formulations and Automatic Differentiation Techniques

El diseño y desarrollo de sistemas de suspensión para vehículos se basa cada día más en el diseño por ordenador y en herramientas de análisis por ordenador, las cuales permiten anticipar problemas y resolverlos por adelantado. El comportamiento y las características dinámicas se calculan con precisión, bajo coste, y recursos y tiempos de cálculo reducidos. Sin embargo, existe una componente iterativa en el proceso, que requiere la definición manual de diseños a través de técnicas “prueba y error”. Esta Tesis da un paso hacia el desarrollo de un entorno de simulación eficiente capaz de simular, analizar y evaluar diseños de suspensiones vehiculares, y de mejorarlos hacia la solución optima mediante la modificación de los parámetros de diseño. La modelización mediante sistemas multicuerpo se utiliza aquí para desarrollar un modelo de autocar con 18 grados de libertad, de manera detallada y eficiente. La geometría y demás características de la suspensión se ajustan a las del vehículo real, así como los demás parámetros del modelo. Para simular la dinámica vehicular, se utiliza una formulación multicuerpo moderna y eficiente basada en las ecuaciones de Maggi, a la que se ha incorporado un visor 3D. Así, se consigue simular maniobras vehiculares en tiempos inferiores al tiempo real. Una vez que la dinámica está disponible, los análisis de sensibilidad son cruciales para una optimización robusta y eficiente. Para ello, se presenta una técnica matemática que permite derivar las variables dinámicas dentro de la formulación, de forma algorítmica, general, con la precisión de la maquina, y razonablemente eficiente: la diferenciación automática. Este método propaga las derivadas con respecto a las variables de diseño a través del código informático y con poca intervención del usuario. En contraste con otros enfoques en la bibliografía, generalmente particulares y limitados, se realiza una comparación de librerías, se desarrolla una formulación híbrida directa-automática para el cálculo de sensibilidades, y se presentan varios ejemplos reales. Finalmente, se lleva a cabo la optimización de la respuesta dinámica del vehículo citado. Se analizan cuatro tipos distintos de optimización: identificación de parámetros, optimización de la maniobrabilidad, optimización del confort y optimización multi-objetivo, todos ellos aplicados al diseño del autocar. Además de resultados analíticos y gráficos, se incluyen algunas consideraciones acerca de la eficiencia. En resumen, se mejora el comportamiento dinámico de vehículos por medio de modelos multicuerpo y de técnicas de diferenciación automática y optimización avanzadas, posibilitando un ajuste automático, preciso y eficiente de los parámetros de diseño. ABSTRACT Each day, the design and development of vehicle suspension systems relies more on computer-aided design and computer-aided engineering tools, which allow anticipating the problems and solving them ahead of time. Dynamic behavior and characteristics are thus simulated accurately and inexpensively with moderate computational times and resources. There is, however, an iterative component in the process, which involves the manual definition of designs in a trialand-error manner. This Thesis takes a step towards the development of an efficient simulation framework capable of simulating, analyzing and evaluating vehicle suspension designs, and automatically improving them by varying the design parameters towards the optimal solution. The multibody systems approach is hereby used to model a three-dimensional 18-degrees-of-freedom coach in a comprehensive yet efficient way. The suspension geometry and characteristics resemble the ones from the real vehicle, as do the rest of vehicle parameters. In order to simulate vehicle dynamics, an efficient, state-of-the-art multibody formulation based on Maggi’s equations is employed, and a three-dimensional graphics viewer is developed. As a result, vehicle maneuvers can be simulated faster than real-time. Once the dynamics are ready, a sensitivity analysis is crucial for a robust optimization. To that end, a mathematical technique is introduced, which allows differentiating the dynamic variables within the multibody formulation in a general, algorithmic, accurate to machine precision, and reasonably efficient way: automatic differentiation. This method propagates the derivatives with respect to the design parameters throughout the computer code, with little user interaction. In contrast with other attempts in the literature, mostly not generalpurpose, a benchmarking of libraries is carried out, a hybrid direct-automatic differentiation approach for the computation of sensitivities is developed, and several real-life examples are analyzed. Finally, a design optimization process of the aforementioned vehicle is carried out. Four different types of dynamic response optimization are presented: parameter identification, handling optimization, ride comfort optimization and multi-objective optimization; all of which are applied to the design of the coach example. Together with analytical and visual proof of the results, efficiency considerations are made. In summary, the dynamic behavior of vehicles is improved by using the multibody systems approach, along with advanced differentiation and optimization techniques, enabling an automatic, accurate and efficient tuning of design parameters.

Multi-objective Aerodynamic Optimization of High-speed Trains in Tunnels

A genetic algorithm (GA) is employed for the multi-objective shape optimization of the nose of a high-speed train. Aerodynamic problems observed at high speeds become still more relevant when traveling along a tunnel. The objective is to minimize both the aerodynamic drag and the amplitude of the pressure gradient of the compression wave when a train enters a tunnel. The main drawback of GA is the large number of evaluations need in the optimization process. Metamodels-based optimization is considered to overcome such problem. As a result, an explicit relationship between pressure gradient and geometrical parameters is obtained.

Guidelines for the design of efficient sono-microreactors

Possible drawbacks of microreactors are inefficient reactant mixing and the clogging of microchannels when solid-forming reactions are carried out or solid (catalysts) suspensions are used. Ultrasonic irradiation has been successfully implemented for solving these problems in microreactor configurations ranging from capillaries immersed in ultrasonic baths to devices with miniaturized piezoelectric transducers. Moving forward in process intensification and sustainable development, the acoustic energy implementation requires a strategy to optimize the microreactor from an ultrasound viewpoint during its design. In this work, we present a simple analytical model that can be used as a guide to achieving a proper acoustic design of stacked microreactors. An example of this methodology was demonstrated through finite element analysis and it was compared with an experimental study found in the literature.