Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

Three-dimensional modeling of biomass fuel flow in a circulating fluidized bed furnace

The reduction of greenhouse gas emissions in the European Union promotes the combustion of biomass rather than fossil fuels in energy production. Circulating fluidized bed (CFB) combustion offers a simple, flexible and efficient way to utilize untreated biomass in a large scale. CFB furnaces are modeled in order to understand their operation better and to help in the design of new furnaces. Therefore, physically accurate models are needed to describe the heavily coupled multiphase flow, reactions and heat transfer inside the furnace. This thesis presents a new model for the fuel flow inside the CFB furnace, which acknowledges the physical properties of the fuel and the multiphase flow phenomena inside the furnace. This model is applied with special interest in the firing of untreated biomass. An experimental method is utilized to characterize gas-fuel drag force relations. This characteristic drag force approach is developed into a gas-fuel drag force model suitable for irregular, non-spherical biomass particles and applied together with the new fuel flow model in the modeling of a large-scale CFB furnace. The model results are physically valid and achieve very good correspondence with the measurement results from large-scale CFB furnace firing biomass. With the methods and models presented in this work, the fuel flow field inside a circulating fluidized bed furnace can be modeled with better accuracy and more efficiently than in previous studies with a three-dimensional holistic model frame.

Modeling pulmonary fibrosis by abnormal expression of telomerase/apoptosis/collagen V in experimental usual interstitial pneumonia

Limitations on tissue proliferation capacity determined by telomerase/apoptosis balance have been implicated in pathogenesis of idiopathic pulmonary fibrosis. In addition, collagen V shows promise as an inductor of apoptosis. We evaluated the quantitative relationship between the telomerase/apoptosis index, collagen V synthesis, and epithelial/fibroblast replication in mice exposed to butylated hydroxytoluene (BHT) at high oxygen concentration. Two groups of mice were analyzed: 20 mice received BHT, and 10 control mice received corn oil. Telomerase expression, apoptosis, collagen I, III, and V fibers, and hydroxyproline were evaluated by immunohistochemistry, in situ detection of apoptosis, electron microscopy, immunofluorescence, and histomorphometry. Electron microscopy confirmed the presence of increased alveolar epithelial cells type 1 (AEC1) in apoptosis. Immunostaining showed increased nuclear expression of telomerase in AEC type 2 (AEC2) between normal and chronic scarring areas of usual interstitial pneumonia (UIP). Control lungs and normal areas from UIP lungs showed weak green birefringence of type I and III collagens in the alveolar wall and type V collagen in the basement membrane of alveolar capillaries. The increase in collagen V was greater than collagens I and III in scarring areas of UIP. A significant direct association was found between collagen V and AEC2 apoptosis. We concluded that telomerase, collagen V fiber density, and apoptosis evaluation in experimental UIP offers the potential to control reepithelization of alveolar septa and fibroblast proliferation. Strategies aimed at preventing high rates of collagen V synthesis, or local responses to high rates of cell apoptosis, may have a significant impact in pulmonary fibrosis.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Experimental results and modeling of poultry carcass cooling by water immersion

Poultry carcasses have to be chilled to reduce the central breast temperatures from approximately 40 to 4 °C, which is crucial to ensure safe products. This work investigated the cooling of poultry carcasses by water immersion. Poultry carcasses were taken directly from an industrial processing plant and cooled in a pilot chiller, which was built to investigate the influence of the method and the water stirring intensity on the carcasses cooling. A simplified empiric mathematical model was used to represent the experimental results. These results indicated clearly that the understanding and quantification of heat transfer between the carcass and the cooling water is crucial to improve processes and equipment. The proposed mathematical model is a useful tool to represent the dynamics of carcasses cooling, and it can be used to compare different chiller operational conditions in industrial plants. Therefore, this study reports data and a simple mathematical tool to handle an industrial problem with little information available in the literature.

Multicomponent diffusion during Prato cheese ripening: mathematical modeling using the finite element method

The partial replacement of NaCl by KCl is a promising alternative to produce a cheese with lower sodium content since KCl does not change the final quality of the cheese product. In order to assure proper salt proportions, mathematical models are employed to control the product process and simulate the multicomponent diffusion during the reduced salt cheese ripening period. The generalized Fick's Second Law is widely accepted as the primary mass transfer model within solid foods. The Finite Element Method (FEM) was used to solve the system of differential equations formed. Therefore, a NaCl and KCl multicomponent diffusion was simulated using a 20% (w/w) static brine with 70% NaCl and 30% KCl during Prato cheese (a Brazilian semi-hard cheese) salting and ripening. The theoretical results were compared with experimental data, and indicated that the deviation was 4.43% for NaCl and 4.72% for KCl validating the proposed model for the production of good quality, reduced-sodium cheeses.

Modeling the water uptake by chicken carcasses during cooling by immersion

In this study, water uptake by poultry carcasses during cooling by water immersion was modeled using artificial neural networks. Data from twenty-five independent variables and the final mass of the carcass were collected in an industrial plant to train and validate the model. Different network structures with one hidden layer were tested, and the Downhill Simplex method was used to optimize the synaptic weights. In order to accelerate the optimization calculus, Principal Component Analysis (PCA) was used to preprocess the input data. The obtained results were: i) PCA reduced the number of input variables from twenty-five to ten; ii) the neural network structure 4-6-1 was the one with the best result; iii) PCA gave the following order of importance: parameters of mass transfer, heat transfer, and initial characteristics of the carcass. The main contributions of this work were to provide an accurate model for predicting the final content of water in the carcasses and a better understanding of the variables involved.

Mathematical modeling of dehydration of 'Fuji' and 'Gala' apples slices using infrared

The objective of this work was to determine and model the infrared dehydration curves of apple slices - Fuji and Gala varieties. The slices were dehydrated until constant mass, in a prototype dryer with infrared heating source. The applied temperatures ranged from 50 to 100 °C. Due to the physical characteristics of the product, the dehydration curve was divided in two periods, constant and falling, separated by the critical moisture content. A linear model was used to describe the constant dehydration period. Empirical models traditionally used to model the drying behavior of agricultural products were fitted to the experimental data of the falling dehydration period. Critical moisture contents of 2.811 and 3.103 kgw kgs-1 were observed for the Fuji and Gala varieties, respectively. Based on the results, it was concluded that the constant dehydration rates presented a direct relationship with the temperature; thus, it was possible to fit a model that describes the moisture content variation in function of time and temperature. Among the tested models, which describe the falling dehydration period, the model proposed by Midilli presented the best fit for all studied conditions.

Mathematical modeling of microbial growth in milk

A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

Construction of 2D transparent micromodels in polyester resin with porosity similar to carrots

Microscopic visualization, especially in transparent micromodels, can provide valuable information to understand the transport phenomena at pore scale in different process occurring in porous materials (food, timber, soils, etc.). Micromodels studies focus mainly on the observation of multi-phase flow, which presents a greater proximity to reality. The aim of this study was to study the process of flexography and its application in the manufacture of polyester resin transparent micromodels and its application to carrots. Materials used to implement a flexo station for micromodels construction were thermoregulated water bath, exposure chamber to UV light, photosensitive substance (photopolymer), RTV silicone polyester resin, and glass plates. In this paper, data on size distribution of a particular kind of carrot we used, and a transparent micromodel with square cross-section as well as a Log-normal pore size distribution with pore radii ranging from 10 to 110 µm (average of 22 µm and micromodel size of 10 × 10 cm) were built. Finally, it stresses that it has successfully implemented the protocol processing 2D polyester resin transparent micromodels.

Modeling of allergen proteins found in sea food products

Shellfish are a source of food allergens, and their consumption is the cause of severe allergic reactions in humans. Tropomyosins, a family of muscle proteins, have been identified as the major allergens in shellfish and mollusks species. Nevertheless, few experimentally determined three-dimensional structures are available in the Protein Data Base (PDB). In this study, 3D models of several homologous of tropomyosins present in marine shellfish and mollusk species (Chaf 1, Met e1, Hom a1, Per v1, and Pen a1) were constructed, validated, and their immunoglobulin E binding epitopes were identified using bioinformatics tools. All protein models for these allergens consisted of long alpha-helices. Chaf 1, Met e1, and Hom a1 had six conserved regions with sequence similarities to known epitopes, whereas Per v1 and Pen a1 contained only one. Lipophilic potentials of identified epitopes revealed a high propensity of hydrophobic amino acids in the immunoglobulin E binding site. This information could be useful to design tropomyosin-specific immunotherapy for sea food allergies.

Mathematical modeling of microwave dried celery leaves and determination of the effective moisture diffusivities and activation energy

Celery (Apium graveolens L. var. secalinum Alef) leaves with 50±0.07 g weight and 91.75±0.15% humidity (~11.21 db) were dried using 8 different microwave power densities ranging between 1.8-20 W g-1, until the humidity fell down to 8.95±0.23% (~0.1 db). Microwave drying processes were completed between 5.5 and 77 min depending on the microwave power densities. In this study, measured values were compared with predicted values obtained from twenty thin layer drying theoretical, semi-empirical and empirical equations with a new thin layer drying equation. Within applied microwave power density; models whose coefficient and correlation (R²) values are highest were chosen as the best models. Weibull distribution model gave the most suitable predictions at all power density. At increasing microwave power densities, the effective moisture diffusivity values ranged from 1.595 10-10 to 6.377 10-12 m2 s-1. The activation energy was calculated using an exponential expression based on Arrhenius equation. The linear relationship between the drying rate constant and effective moisture diffusivity gave the best fit.

Coolability of porous core debris beds : Effects of bed geometry and multi-dimensional flooding

This thesis addresses the coolability of porous debris beds in the context of severe accident management of nuclear power reactors. In a hypothetical severe accident at a Nordic-type boiling water reactor, the lower drywell of the containment is flooded, for the purpose of cooling the core melt discharged from the reactor pressure vessel in a water pool. The melt is fragmented and solidified in the pool, ultimately forming a porous debris bed that generates decay heat. The properties of the bed determine the limiting value for the heat flux that can be removed from the debris to the surrounding water without the risk of re-melting. The coolability of porous debris beds has been investigated experimentally by measuring the dryout power in electrically heated test beds that have different geometries. The geometries represent the debris bed shapes that may form in an accident scenario. The focus is especially on heap-like, realistic geometries which facilitate the multi-dimensional infiltration (flooding) of coolant into the bed. Spherical and irregular particles have been used to simulate the debris. The experiments have been modeled using 2D and 3D simulation codes applicable to fluid flow and heat transfer in porous media. Based on the experimental and simulation results, an interpretation of the dryout behavior in complex debris bed geometries is presented, and the validity of the codes and models for dryout predictions is evaluated. According to the experimental and simulation results, the coolability of the debris bed depends on both the flooding mode and the height of the bed. In the experiments, it was found that multi-dimensional flooding increases the dryout heat flux and coolability in a heap-shaped debris bed by 47–58% compared to the dryout heat flux of a classical, top-flooded bed of the same height. However, heap-like beds are higher than flat, top-flooded beds, which results in the formation of larger steam flux at the top of the bed. This counteracts the effect of the multi-dimensional flooding. Based on the measured dryout heat fluxes, the maximum height of a heap-like bed can only be about 1.5 times the height of a top-flooded, cylindrical bed in order to preserve the direct benefit from the multi-dimensional flooding. In addition, studies were conducted to evaluate the hydrodynamically representative effective particle diameter, which is applied in simulation models to describe debris beds that consist of irregular particles with considerable size variation. The results suggest that the effective diameter is small, closest to the mean diameter based on the number or length of particles.

Modeling and kinetic study of bio-ethanol production from soy protein concentrate by-product

Abstract The aim of this work was to evaluate a non-agitated process of bioethanol production from soybean molasses and the kinetic parameters of fermentation using a strain of Saccharomyces cerevisiae (ATCC® 2345). Kinetic experiment was conducted in medium with 30% (w v-1) of soluble solids without supplementation or pH adjustment. The maximum ethanol concentration was in 44 hours, the ethanol productivity was 0.946 g L-1 h-1, the yield over total initial sugars (Y1) was 47.87%, over consumed sugars (Y2) was 88.08% and specific cells production rate was 0.006 h-1. The mathematical polynomial was adjusted to the experimental data and provided very similar parameters of yield and productivity. Based in this study, for one ton of soybean molasses can be produced 103 kg of anhydrous bioethanol.