Algorithm of J-spectral factorization of polynomial matrices

Numerical algorithms for the canonical J-factorization of polynomial matrices with respect to the imaginary axis are given. The factorization problems for the non-regular polynomial matrices and for polynomials, whose determinants have zero roots, are considered. The constructed algorithms are not connected to the finding of roots of the polynomial. The basic calculation procedure is the construction of the stabilizing solution of the matrix algebraic Riccati equation.     

A neural network approach for prediction of critical submergence of an intake in still water and open channel flow for permeable and impermeable bottom

Free air-core vortex occurring at a water-intake pipe is an important problem encountered in hydraulic engineering. When the submergence of the intake pipe is not sufficient, air enters the pipe and reduction in discharge occurs. The most common solution for avoiding air entrainment is to provide sufficient submergence to the intake. In this study, the critical submergence of intakes is investigated in still water and open channel flow for permeable and impermeable bottom. It is seen that the permeability of the bottom is effective on the critical submergence. The main aim of this study is to develop a suitable model for the critical submergence for intake pipe. Therefore, an artificial neural network (ANN) and multi-linear regression models are used. Results of these experimental studies are compared with those obtained by the ANN and MLR approaches. The ANN model results are found to be in good agreement with the experimental results.     

Degradation and Mineralization of Simazine in Aqueous Solution by Ozone/Hydrogen Peroxide Advanced Oxidation

Advanced oxidation of simazine in aqueous solution by the peroxone (hydrogen peroxide/ozone) treatment was investigated using Box-Behnken statistical experiment design and response surface methodology. Effects of pH, simazine and H2O2 concentrations on percent simazine and total organic carbon (TOC) removals were investigated. Ozone concentration was kept constant at 45?mg?L?1. The optimum conditions yielding the highest simazine and TOC removals were also determined. Both simazine and peroxide doses affected simazine removal while pH and pesticide dose had more pronounced effect on mineralization (TOC removal) of simazine. Nearly 95% removal of simazine was achieved within 5 min for simazine and peroxide concentrations of 2.0 and 75?mg?L?1, respectively at pH = 7. However, mineralization of simazine was not completed even after 60 min at simazine doses above 2?mg?L?1 indicating formation of some intermediate compounds. The optimum H2O2/pH/Simazine ratio resulting in maximum pesticide (94%) and TOC removal (82%) was found to be 75/11/0.5(mg?L?1).     

Microbial culture selection for bio-hydrogen production from waste ground wheat by dark fermentation

Hydrogen formation performances of different anaerobic bacteria were investigated in batch dark fermentation of waste wheat powder solution (WPS). Serum bottles containing wheat powder were inoculated with pure cultures of Clostridium acetobutylicum (CAB), Clostridium butyricum (CB), Enterobacter aerogenes (EA), heat-treated anaerobic sludge (ANS) and a mixture of those cultures (MIX). Cumulative hydrogen formation (CHF), hydrogen yield (HY) and specific hydrogen production rate (SHPR) were determined for every culture. The heat-treated anaerobic sludge was found to be the most effective culture with a cumulative hydrogen formation of 560 ml, hydrogen yield of 223 ml H₂ g⁻¹ starch and a specific hydrogen production rate of 32.1 ml H₂ g⁻¹ h⁻¹.     

Zinc (II) ion recovery by biosorption onto powdered waste sludge (PWS): effects of operating conditions

Powdered waste sludge (PWS) obtained from a paint industry wastewater treatment plant and pretreated with 1% H₂O₂ was used for biosorption of Zn(II) ions from aqueous solution. The effects of operating conditions, pH, temperature, agitation speed, PWS particle size, Zn ion and PWS concentrations on the extent of Zn ion biosorption were investigated in batch experiments. The optimum pH resulting in maximum Zn ion biosorption was found to be pH = 5, since Zn ions precipitated in the form of Zn(OH)₂ at pH levels above 5. The rate and extent of Zn ion biosorption increased with temperature between 25 and 50 °C, although biosorption was not strongly sensitive to temperature variations since the activation energy was low at 4.5 kcal mol^?1. Biosorbent particle size had a significant effect on Zn ion biosorption, yielding high percentage Zn removals at small particle sizes (D_p < 100 µm) or large surface areas of PWS. Agitation speed also considerably affected the extent of Zn ion removal, and should be above 150 rpm in order to obtain a high rate. The extent of Zn ion biosorption was also affected by the initial Zn ion and PWS concentrations. At constant biosorbent (PWS) concentration, percentage Zn ion removal decreased, but the biosorbed Zn concentration increased with increasing initial Zn ion concentrations. However, at constant initial Zn concentrations, percentage Zn removal increased, but the biosorbed Zn ion concentration decreased with increasing adsorbent (PWS) concentration. With a maximum Zn ion biosorption capacity of 168 mg g^?1 powdered waste sludge was proven to be an effective biosorbent compared to other biosorbents. Copyright © 2006 Society of Chemical Industry     

Prediction of swelling pressures of expansive soils using soft computing methods

Lateral and vertical swelling pressures associated with expansive soils cause damages on structures. These pressures must be predicted before the structures are constructed in order to prevent the damages. The magnitude of the stresses can decrease rapidly when volume changes are partly allowed. Therefore, a material, which has a high compressibility, must be placed between expansive soils and the structures in both horizontal and vertical directions in order to decrease transmitted swelling pressure on structures. There are numerous techniques recommended for estimating the swelling pressures. However, these techniques are very complex and time-consuming. In this study, a new estimation model to predict the pressures is developed using experimental data. The data were collected in the laboratory using a newly developed device and experimental setup also. In the experimental setup, a rigid steel box was designed to measure transmitted swelling pressures in lateral and vertical directions. In the estimation model, approaches of artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. In the first stage of the study, the lateral and vertical swelling pressures were measured with different thicknesses of expanded polystyrene geofoam placed between one of the vertical walls of the steel box and the expansive soil in the laboratory. Then, ANN and ANFIS approaches were trained using these results of the tests measured in the laboratory as input for the prediction of transmitted lateral and vertical swelling pressures. Results obtained showed that ANN-based prediction and ANFIS approaches could satisfactorily be used to estimate the transmitted lateral and vertical swelling pressures of expansive soils.     

Hydrogen gas production from waste anaerobic sludge by electrohydrolysis: Effects of applied DC voltage

Waste anaerobic sludge was subjected to different DC voltages (0.5-5 V) for hydrogen gas production by using aluminum electrodes and a DC power supply. Effects of applied DC voltage on the rate and extent of hydrogen gas production were investigated. The highest cumulative hydrogen production (2775 ml), daily hydrogen gas formation (686.7 ml d⁻¹), hydrogen yield (96 ml H₂ g⁻¹ COD) and percent hydrogen (94.3%) in the gas phase were obtained with 2 V DC voltage. Energy conversion efficiency (H₂ energy/electrical energy) also reached the highest level (74%) with 2 V DC voltage application. Control experiments with no voltage application to the sludge yielded almost the same level of COD removal, but no hydrogen gas production. Voltage application to water resulted in much lower hydrogen gas production as compared to sludge indicating negligible electrolysis of water. The results indicated that the sludge was naturally decomposed by the active cells removing COD and releasing hydrogen ions to the medium which reacted with the electrons provided by DC current to produce hydrogen gas. Hydrogen gas production from electrohydrolysis of waste sludge was found to be a fast and effective method with high energy efficiency.     

Comparison of artificial neural networks and general linear model approaches for the analysis of abrasive wear of concrete

This study aims to determine the influence of metallic aggregate content, cement content and different loads applied on the abrasive wear of concrete by using artificial neural networks (ANN) and general linear model (GLM) approaches. For this purpose, experimental studies are made and suitable models based on experimental results are developed to estimate the abrasive wear of concrete. In these models, 60 data set was used. For training set, 48 data (80%) were randomly selected and the residual data (12 data, 20%) were selected as test set. Root mean square error (RMSE) and determination coefficient (R²) statistics are used as evaluation criteria of the ANN and GLM models and the experimental results are compared with these models. The comparison results indicate that the ANN models are superior to the GLM models in modeling of the influence metallic aggregate content, cement content and different loads applied on the abrasive wear of concrete.     

Photo-fermentative hydrogen gas production from dark fermentation effluent of ground wheat solution: Effects of light source and light intensity

Dark fermentation effluent of wheat powder solution was subjected to light fermentation for bio-hydrogen production using different light sources and intensities. Tungsten, fluorescent, infrared (IR), halogen lamps were used as light sources with a light intensity of 270 Wm⁻² along with sunlight. Pure culture of Rhodobacter sphaeroides-RV was used in batch light fermentation experiments. Halogen lamp was found to be the most suitable light source yielding the highest cumulative hydrogen formation (CHF, 252 ml) and yield (781 ml H₂ g⁻¹ TVFA). In the second set of experiments, light fermentations were performed at different light intensities (1–10 klux) using halogen lamp. The optimum light intensity was found to be 5 klux (approx. 176 Wm⁻²) resulting in the highest CHF (88 ml) and hydrogen yield (1037 ml H₂ g⁻¹TVFA). Hydrogen formation was limited by the availability of light at low light intensities below 5 klux and was inhibited by the excess light above 5 klux.