Modeling of the Fluid-Structure Interaction in Inelastic Piping Systems

In many engineering applications, compliant piping systems conveying liquids are subjected to inelastic deformations due to severe pressure surges such as plastic tubes in modern water supply transmission lines and metallic pipings in nuclear power plants. In these cases the design of such systems may require an adequate modeling of the interactions between the fluid dynamics and the inelastic structural pipe motions. The reliability of the prediction of fluid-pipe behavior depends mainly on the adequacy of the constitutive equations employed in the analysis. In this paper it is proposed a systematic and general approach to consistently incorporate different kinds of inelastic behaviors of the pipe material in a fluid-structure interaction analysis. The main feature of the constitutive equations considered in this work is that a very simple numerical technique can be used for solving the coupled equations describing the dynamics of the fluid and pipe wall. Numerical examples concerning the analysis of polyethylene and stainless steel pipe networks are presented to illustrate the versatility of the proposed approach.

Substitution-Newton-Raphson method applied to the modeling of a vapour compression refrigeration system using different representations of the thermodynamic properties of R-134a

This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.

Modeling of weeds interference periods in bean

The research objective was to determine the effects of spacing and seeding density of common bean to the period prior to weed interference (PPI) and weed period prior to economic loss (WEEPPEL). The treatments consisted of periods of coexistence between culture and the weeds, with 0 to 10, 0 to 20, 0 to 30, 0 to 40, 0 to 50, 0 to 60, 0 to 70, and 0 to 80 days and a control maintained without weeds. In addition to the periods of coexistence, there were still studies with an inter-row of 0.45 and 0.60 m, 10 and 15 plants m-1. The experimental delineation used was randomized blocks with four repetitions per treatment. The grain productivity of the culture had a reduction of 63, 50, 42 and 57% when the coexistence with the weed plants was during the entire cycle of the culture for a row spacing of 0.45 m and a seeding density of 10 and 15 plants per meter; and a row spacing of 0.60m and a seeding density of 10 and 15 plants per meter, respectively. The PPI occurred in 23, 27, 13, and 19 days after crop emergence and WEEPPEL in 10, 9, 8, and 8 days, respectively.

Mathematical modeling of electro-rotation spectra of small particles in liquid solutions: Application to human erythrocyte aggregates

Electro-rotation can be used to determine the dielectric properties of cells, as well as to observe dynamic changes in both dielectric and morphological properties. Suspended biological cells and particles respond to alternating-field polarization by moving, deforming or rotating. While in linearly polarized alternating fields the particles are oriented along their axis of highest polarizability, in circularly polarized fields the axis of lowest polarizability aligns perpendicular to the plane of field rotation. Ellipsoidal models for cells are frequently applied, which include, beside sphere-shaped cells, also the limiting cases of rods and disks. Human erythrocyte cells, due to their particular shape, hardly resemble an ellipsoid. The additional effect of rouleaux formation with different numbers of aggregations suggests a model of circular cylinders of variable length. In the present study, the induced dipole moment of short cylinders was calculated and applied to rouleaux of human erythrocytes, which move freely in a suspending conductive medium under the effect of a rotating external field. Electro-rotation torque spectra are calculated for such aggregations of different length. Both the maximum rotation speeds and the peak frequencies of the torque are found to depend clearly on the size of the rouleaux. While the rotation speed grows with rouleaux length, the field frequency nup is lowest for the largest cell aggregations where the torque shows a maximum.

Thermodynamic evaluation and modeling of proton and water exchange associated with benzamidine and berenil binding to ß-trypsin

Serine-proteases are involved in vital processes in virtually all species. They are important targets for researchers studying the relationships between protein structure and activity, for the rational design of new pharmaceuticals. Trypsin was used as a model to assess a possible differential contribution of hydration water to the binding of two synthetic inhibitors. Thermodynamic parameters for the association of bovine ß-trypsin (homogeneous material, observed 23,294.4 ± 0.2 Da, theoretical 23,292.5 Da) with the inhibitors benzamidine and berenil at pH 8.0, 25ºC and with 25 mM CaCl2, were determined using isothermal titration calorimetry and the osmotic stress method. The association constant for berenil was about 12 times higher compared to the one for benzamidine (binding constants are K = 596,599 ± 25,057 and 49,513 ± 2,732 M-1, respectively; the number of binding sites is the same for both ligands, N = 0.99 ± 0.05). Apparently the driving force responsible for this large difference of affinity is not due to hydrophobic interactions because the variation in heat capacity (DCp), a characteristic signature of these interactions, was similar in both systems tested (-464.7 ± 23.9 and -477.1 ± 86.8 J K-1 mol-1 for berenil and benzamidine, respectively). The results also indicated that the enzyme has a net gain of about 21 water molecules regardless of the inhibitor tested. It was shown that the difference in affinity could be due to a larger number of interactions between berenil and the enzyme based on computational modeling. The data support the view that pharmaceuticals derived from benzamidine that enable hydrogen bond formation outside the catalytic binding pocket of ß-trypsin may result in more effective inhibitors.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

RNAi-mediated knockdown of pituitary tumor- transforming gene-1 (PTTG1) suppresses the proliferation and invasive potential of PC3 human prostate cancer cells

Pituitary tumor-transforming gene-1 (PTTG1) is a proto-oncogene that promotes tumorigenesis and metastasis in numerous cell types and is overexpressed in a variety of human tumors. We have demonstrated that PTTG1 expression was up-regulated in both human prostate cancer specimens and prostate cancer cell lines. For a more direct assessment of the function of PTTG1 in prostate tumorigenesis, RNAi-mediated knockdown was used to selectively decrease PTTG1 expression in PC3 human prostate tumor cells. After three weeks of selection, colonies stably transfected with PTTG1-targeted RNAi (the knockdown PC3 cell line) or empty vector (the control PC3 cell line) were selected and expanded to investigate the role of PTTG1 expression in PC3 cell growth and invasion. Cell proliferation rate was significantly slower (28%) in the PTTG1 knockdown line after 6 days of growth as indicated by an MTT cell viability assay (P < 0.05). Similarly, a soft agar colony formation assay revealed significantly fewer (66.7%) PTTG1 knockdown PC3 cell colonies than control colonies after three weeks of growth. In addition, PTTG1 knockdown resulted in cell cycle arrest at G1 as indicated by fluorescence-activated cell sorting. The PTTG1 knockdown PC3 cell line also exhibited significantly reduced migration through Matrigel in a transwell assay of invasive potential, and down-regulation of PTTG1 could lead to increased sensitivity of these prostate cancer cells to a commonly used anticancer drug, taxol. Thus, PTTG1 expression is crucial for PC3 cell proliferation and invasion, and could be a promising new target for prostate cancer therapy.

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.

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.

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.

Software for interpolation of vegetative growth of yerba mate plants in 3D

The objective of this work was to build mock-ups of complete yerba mate plants in several stages of development, using the InterpolMate software, and to compute photosynthesis on the interpolated structure. The mock-ups of yerba-mate were first built in the VPlants software for three growth stages. Male and female plants grown in two contrasting environments (monoculture and forest understory) were considered. To model the dynamic 3D architecture of yerba-mate plants during the biennial growth interval between two subsequent prunings, data sets of branch development collected in 38 dates were used. The estimated values obtained from the mock-ups, including leaf photosynthesis and sexual dimorphism, are very close to those observed in the field. However, this similarity was limited to reconstructions that included growth units from original data sets. The modeling of growth dynamics enables the estimation of photosynthesis for the entire yerba mate plant, which is not easily measurable in the field. The InterpolMate software is efficient for building yerba mate mock-ups.

The inhibitory effect of photodynamic therapy and of an anti-VCAM-1 monoclonal antibody on the in vivo growth of C6 glioma xenografts

We investigated the effect of photodynamic therapy (PDT) and of an anti-vascular cell adhesion molecule-1 (VCAM-1) monoclonal antibody on the in vivo growth of C6 glioma. Seven days after inoculation with C6 cells, adult male Wistar rats weighing 280-300 g with MRI-confirmed glioma were randomly assigned to 4 groups (N = 15 per group): PDT + VCAM-1 antibody group; PDT group; VCAM-1 antibody group; control group. Eight days after inoculation, hematoporphyrin monomethyl ether (HMME) was administered as a photosensitizer and PDT was performed at 630 nm (illumination intensity: 360 J/cm²) for 10 min. VCAM-1 antibody (50 µg/mL) was then administered (0.5 mL) through the tail vein every other day from day 8 to day 16. At day 21, 5 rats in each group were sacrificed and cancers were harvested for immunohistochemistry and Western blot assay for the detection of VCAM-1, and TUNEL assay was used to detect apoptosis. Survival and tumor volume were recorded in the remaining 10 rats in each group. In the PDT group, tumor growth was significantly suppressed (67.2%) and survival prolonged (89.3%), accompanied by an increase in apoptosis (369.5%), when compared to control. Furthermore, these changes were more pronounced in the PDT + VCAM-1 antibody group. After PDT, VCAM-1 expression was markedly increased (121.8%) and after VCAM-1 monoclonal antibody treatment, VCAM-1 expression was significantly reduced (58.2%). PDT in combination with VCAM-1 antibody can significantly inhibit the growth of C6 glioma and prolong survival. This approach may represent a promising strategy in the treatment of glioma.