122 resultados para Sequential optimization
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Optimization of photo-Fenton degradation of copper phthalocyanine blue was achieved by response surface methodology (RSM) constructed with the aid of a sequential injection analysis (SIA) system coupled to a homemade photo-reactor. Highest degradation percentage was obtained at the following conditions [H(2)O(2)]/[phthalocyanine] = 7, [H(2)O(2)]/[FeSO(4)] = 10, pH = 2.5, and stopped flow time in the photo reactor = 30 s. The SIA system was designed to prepare a monosegment containing the reagents and sample, to pump it toward the photo-reactor for the specified time and send the products to a flow-through spectrophotometer for monitoring the color reduction of the dye. Changes in parameters such as reagent molar ratios. residence time and pH were made by modifications in the software commanding the SI system, without the need for physical reconfiguration of reagents around the selection valve. The proposed procedure and system fed the statistical program with degradation data for fast construction of response surface plots. After optimization, 97% of the dye was degraded. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
This work presents the use of sequential injection analysis (SIA) and the response surface methodology as a tool for optimization of Fenton-based processes. Alizarin red S dye (C.I. 58005) was used as a model compound for the anthraquinones family. whose pigments have a large use in coatings industry. The following factors were considered: [H(2)O(2)]:[Alizarin] and [H(2)O(2)]:[FeSO(4)] ratios and pH. The SIA system was designed to add reagents to the reactor and to perform on-line sampling of the reaction medium, sending the samples to a flow-through spectrophotometer for monitoring the color reduction of the dye. The proposed system fed the statistical program with degradation data for fast construction of response surface plots. After optimization, 99.7% of the dye was degraded and the TOC content was reduced to 35% of the original value. Low reagents consumption and high sampling throughput were the remarkable features of the SIA system. (C) 2008 Published by Elsevier B.V.
Resumo:
Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid-pumping applications and transducers for novel energy-harvesting devices. This project involves the development of a topology optimization formulation for dynamic design of piezoelectric laminated plates aiming at piezoelectric sensors, actuators and energy-harvesting applications. It distributes piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified resonance frequencies, modes, and enhanced electromechanical coupling factor (EMCC). The finite element employs a piezoelectric plate based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model combined with the RAMP model, where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element and its polarization sign. The design problem formulated aims at designing simultaneously an eigenshape, i.e., maximizing and minimizing vibration amplitudes at certain points of the structure in a given eigenmode, while tuning the eigenvalue to a desired value and also maximizing its EMCC, so that the energy conversion is maximized for that mode. The optimization problem is solved by using sequential linear programming. Through this formulation, a design with enhancing energy conversion in the low-frequency spectrum is obtained, by minimizing a set of first eigenvalues, enhancing their corresponding eigenshapes while maximizing their EMCCs, which can be considered an approach to the design of energy-harvesting devices. The implementation of the topology optimization algorithm and some results are presented to illustrate the method.
Resumo:
Tailoring specified vibration modes is a requirement for designing piezoelectric devices aimed at dynamic-type applications. A technique for designing the shape of specified vibration modes is the topology optimization method (TOM) which finds an optimum material distribution inside a design domain to obtain a structure that vibrates according to specified eigenfrequencies and eigenmodes. Nevertheless, when the TOM is applied to dynamic problems, the well-known grayscale or intermediate material problem arises which can invalidate the post-processing of the optimal result. Thus, a more natural way for solving dynamic problems using TOM is to allow intermediate material values. This idea leads to the functionally graded material (FGM) concept. In fact, FGMs are materials whose properties and microstructure continuously change along a specific direction. Therefore, in this paper, an approach is presented for tailoring user-defined vibration modes, by applying the TOM and FGM concepts to design functionally graded piezoelectric transducers (FGPT) and non-piezoelectric structures (functionally graded structures-FGS) in order to achieve maximum and/or minimum vibration amplitudes at certain points of the structure, by simultaneously finding the topology and material gradation function. The optimization problem is solved by using sequential linear programming. Two-dimensional results are presented to illustrate the method.
Resumo:
The NMR spin coupling parameters, (1)J(N,H) and (2)J(H,H), and the chemical shielding, sigma((15)N), of liquid ammonia are studied from a combined and sequential QM/MM methodology. Monte Carlo simulations are performed to generate statistically uncorrelated configurations that are submitted to density functional theory calculations. Two different Lennard-Jones potentials are used in the liquid simulations. Electronic polarization is included in these two potentials via an iterative procedure with and without geometry relaxation, and the influence on the calculated properties are analyzed. B3LYP/aug-cc-pVTZ-J calculations were used to compute the V(N,H) constants in the interval of -67.8 to -63.9 Hz, depending on the theoretical model used. These can be compared with the experimental results of -61.6 Hz. For the (2)J(H,H) coupling the theoretical results vary between -10.6 to -13.01 Hz. The indirect experimental result derived from partially deuterated liquid is -11.1 Hz. Inclusion of explicit hydrogen bonded molecules gives a small but important contribution. The vapor-to-liquid shifts are also considered. This shift is calculated to be negligible for (1)J(N,H) in agreement with experiment. This is rationalized as a cancellation of the geometry relaxation and pure solvent effects. For the chemical shielding, U(15 N) Calculations at the B3LYP/aug-pcS-3 show that the vapor-to-liquid chemical shift requires the explicit use of solvent molecules. Considering only one ammonia molecule in an electrostatic embedding gives a wrong sign for the chemical shift that is corrected only with the use of explicit additional molecules. The best result calculated for the vapor to liquid chemical shift Delta sigma((15)N) is -25.2 ppm, in good agreement with the experimental value of -22.6 ppm.
Resumo:
This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
This work describes the development and optimization of a sequential injection method to automate the determination of paraquat by square-wave voltammetry employing a hanging mercury drop electrode. Automation by sequential injection enhanced the sampling throughput, improving the sensitivity and precision of the measurements as a consequence of the highly reproducible and efficient conditions of mass transport of the analyte toward the electrode surface. For instance, 212 analyses can be made per hour if the sample/standard solution is prepared off-line and the sequential injection system is used just to inject the solution towards the flow cell. In-line sample conditioning reduces the sampling frequency to 44 h(-1). Experiments were performed in 0.10 M NaCl, which was the carrier solution, using a frequency of 200 Hz, a pulse height of 25 mV, a potential step of 2 mV, and a flow rate of 100 mu L s(-1). For a concentration range between 0.010 and 0.25 mg L(-1), the current (i(p), mu A) read at the potential corresponding to the peak maximum fitted the following linear equation with the paraquat concentration (mg L(-1)): ip = (-20.5 +/- 0.3) Cparaquat -(0.02 +/- 0.03). The limits of detection and quantification were 2.0 and 7.0 mu g L(-1), respectively. The accuracy of the method was evaluated by recovery studies using spiked water samples that were also analyzed by molecular absorption spectrophotometry after reduction of paraquat with sodium dithionite in an alkaline medium. No evidence of statistically significant differences between the two methods was observed at the 95% confidence level.
Resumo:
This paper describes the optimization and use of a Sequential Injection Analysis (SIA) procedure for ammonium determination in waters. Response Surface Methodology (RSM) was used as a tool for optimization of a procedure based on the modified Berthelot reaction. The SIA system was designed to (i) prepare the reaction media by injecting an air-segmented zone containing the reagents in a mixing chamber, (ii) to aspirate the mixture back to the holding coil after homogenization, (iii) drive it to a thermostated reaction coil, where the flow is stopped for a previously established time, and (iv) to pump the mixture toward the detector flow cell for the spectrophotometric measurements. Using a 100 mu mol L(-1) ammonium solution, the following factors were considered for optimization: reaction temperature (25 - 45 degrees C), reaction time (30 - 90 s), hypochlorite concentration (20 - 40 mmol L(-1)) nitroprusside concentration (10 - 40 mmol L(-1)) and salicylate concentration (0.1 - 0.3 mol L(-1)). The proposed system fed the statistical program with absorbance data for fast construction of response surface plots. After optimization of the method, figures of merit were evaluated, as well as the ammonium concentration in some water samples. No evidence of statistical difference was observed in the results obtained by the proposed method in comparison to those obtained by a reference method based on the phenol reaction. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.
Resumo:
This paper describes a sequential injection chromatography procedure for determination of picloram in waters exploring the low backpressure of a 2.5 cm long monolithic C18 column. Separation of the analyte from the matrix was achieved in less than 60 s using a mobile phase composed by 20:80 (v v-1) acetonitrile:5.0 mmol L-1 H3PO4 and flow rate of 30 μL s-1. Detection was made at 223 nm with a 40 mm optical path length cell. The limits of detection and quantification were 33 and 137 μg L-1, respectively. The proposed method is sensitive enough to monitor the maximum concentration level for picloram in drinking water (500 μg L-1). The sampling frequency is 60 analyses per hour, consuming only 300 μL of acetonitrile per analysis. The proposed methodology was applied to spiked river water samples and no statistically significant differences were observed in comparison to a conventional HPLC-UV method.
Resumo:
This work describes a photo-reactor to perform in line degradation of organic compounds by photo-Fenton reaction using Sequential Injection Analysis (SIA) system. A copper phthalocyanine-3,4',4²,4²¢-tetrasulfonic acid tetrasodium salt dye solution was used as a model compound for the phthalocyanine family, whose pigments have a large use in automotive coatings industry. Based on preliminary tests, 97% of color removal was obtained from a solution containing 20 µmol L-1 of this dye.
Resumo:
Objective: The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. Background: Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. Methods: Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. Results: Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. Conclusions: The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.
Resumo:
Blends of milk fat and canola oil (MF:CNO) were enzymatically interesterified (EIE) by Rhizopus oryzne lipase immobilized on polysiloxane-polyvinyl alcohol (SiO(2)-PVA) composite, in a solvent-free system. A central composite design (CCD) was used to optimize the reaction, considering the effects of different mass fractions of binary blends of MF:CNO (50:50, 65:35 and 80:20) and temperatures (45, 55 and 65 degrees C) on the composition and texture properties of the interesterified products, taking the interesterification degree (ID) and consistency (at 10 degrees C) as response variables. For the ID variable both mass fraction of milk fat in the blend and temperature were found to be significant, while for the consistency only mass fraction of milk fat was significant. Empiric models for ID and consistency were obtained that allowed establishing the best interesterification conditions: blend with 65 % of milk fat and 35 %, of canola oil, and temperature of 45 degrees C. Under these conditions, the ID was 19.77 %) and the consistency at 10 degrees C was 56 290 Pa. The potential of this eco-friendly process demonstrated that a product could be obtained with the desirable milk fat flavour and better spreadability under refrigerated conditions.
Resumo:
The structural engineering community in Brazil faces new challenges with the recent occurrence of high intensity tornados. Satellite surveillance data shows that the area covering the south-east of Brazil, Uruguay and some of Argentina is one of the world most tornado-prone areas, second only to the infamous tornado alley in central United States. The design of structures subject to tornado winds is a typical example of decision making in the presence of uncertainty. Structural design involves finding a good balance between the competing goals of safety and economy. This paper presents a methodology to find the optimum balance between these goals in the presence of uncertainty. In this paper, reliability-based risk optimization is used to find the optimal safety coefficient that minimizes the total expected cost of a steel frame communications tower, subject to extreme storm and tornado wind loads. The technique is not new, but it is applied to a practical problem of increasing interest to Brazilian structural engineers. The problem is formulated in the partial safety factor format used in current design codes, with all additional partial factor introduced to serve as optimization variable. The expected cost of failure (or risk) is defined as the product of a. limit state exceedance probability by a limit state exceedance cost. These costs include costs of repairing, rebuilding, and paying compensation for injury and loss of life. The total expected failure cost is the sum of individual expected costs over all failure modes. The steel frame communications, tower subject of this study has become very common in Brazil due to increasing mobile phone coverage. The study shows that optimum reliability is strongly dependent on the cost (or consequences) of failure. Since failure consequences depend oil actual tower location, it turn,,; out that different optimum designs should be used in different locations. Failure consequences are also different for the different parties involved in the design, construction and operation of the tower. Hence, it is important that risk is well understood by the parties involved, so that proper contracts call be made. The investigation shows that when non-structural terms dominate design costs (e.g, in residential or office buildings) it is not too costly to over-design; this observation is in agreement with the observed practice for non-optimized structural systems. In this situation, is much easier to loose money by under-design. When by under-design. When structural material cost is a significant part of design cost (e.g. concrete dam or bridge), one is likely to lose significantmoney by over-design. In this situation, a cost-risk-benefit optimization analysis is highly recommended. Finally, the study also shows that under time-varying loads like tornados, the optimum reliability is strongly dependent on the selected design life.
Resumo:
This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.