A self-tuning ANN model for simulation and forecasting of surface flows

Artificial neural networks (ANN) are applicable for and forecasting without the need to calculate complex nonlinear functions. This paper evaluates the effectiveness of temperature, evapotranspiration, precipitation and inflow factors, and the lag time of those factors, as variables for simulating and forecasting of runoff. The genetic algorithm (GA) is coupled with ANN to determine the optimal set of variables for streamflow forecasting. The minimization of the total mean square error (MSE) is considered as the objective function of the ANN-GA method in this paper. Our results show the effectiveness of the ANN-GA for simulating and forecasting runoff with consistent accuracy compared with using pure ANN for runoff simulation and forecasting.     

Pressure Fluctuation Analysis of Laboratory Scale Air/Polyethylene Fluidized Beds

Differential pressure fluctuations were studied along the wall of a laboratory scale column filled with a polyethylene resin. Air flow rates to the column were varied in order to examine the changes in wall pressure with respect to superficial gas velocity. Statistical and spectral analysis was used to study the periodic features of column wall pressure measurements in the dense region of a fluidized bed. From the analysis, it is evident that multiple flow regimes exist in the column. These flow regimes are dependent upon the height above the distributor. Results also show a significant peak developing at 1 Hz as superficial gas velocity increases.     

Calculation of pure saturation properties using cubic equations of state

A robust algorithm is outlined for the solution of the classical non-linear isofugacity problem by using equations of state (EOS). The procedure suggested is free of numerical pitfalls from the triple point to the critical point. The combination of differential stability (spinodal curve) and zero pressure reference concepts yields an automatic initialization of the calculations inside a region of convergence where the EOS can always predict pure compound vapor pressures at a given temperature.     

Methodology to Optimize Rainwater Tank-sizing and Cluster Configuration for a Group of Buildings

Water Resources Management - The behavior of a rainwater harvesting system depends on some variables that cannot be controlled, such as rainfall, building roof size and water consumption. The...     

Developing Strategies for Agricultural Water Management of Large Irrigation and Drainage Networks with Fuzzy MCDM

Sustainable water resources management aims at increasing the efficient use of water and achieving food security. This work proposes a generalized novel spatial fuzzy strategic planning (SFSP) in combination with multi-criteria decision making (MCDM) and a conceptual agricultural water use model for determining sustainable agricultural water management strategies. The proposed framework is applied to an irrigation and drainage network in Iran, which constitutes a large-scale water resource system. A spatial strength, weakness, opportunity, and threat (SWOT) analysis of internal and external factors related to agricultural water management is applied in this work. Possible water management strategies were ranked with the MCDM approach that combines the Analytic Hierarchy Process (AHP) and the Fuzzy technique for order-preference by similarity to ideal solution (TOPSIS). The AHP estimates the criteria weights and the TOPSIS model prioritizes the agricultural water management strategies. The results of SWOT analysis show that the final scores of the internal and external factors are equal to 2.9 and 2.73, respectively. Accordingly, the most attractive strategic type is a SO (aggressive) strategy, and a combination of structural and non-structural strategies (SO, ST, and WO strategies) are the top-ranked ones. Proposed strategies for water supply and demand management are the development and rehabilitation of the physical structure of water resources system of irrigation network, improvement of operation management and maintenance of water resources system, wastewater management, and inter-basin water transfer within the irrigation network. The results indicate that the total annual volume of agricultural water under normal conditions is about 1.8 billion cubic meters, of which about 1707 million cubic meters (95%) issue from surface water sources and 90 million cubic meters (5%) from groundwater sources. The proposed model and the calculated results provide viable and effective solutions for the implementation of sustainable management of water resources and consumption in large-scale water resources systems.

     

A simple low-cost approach for transport parameter determination in mountain rivers

A simplified low-cost approach to experimentally determine transport parameters in mountain rivers is described, with an emphasis on the longitudinal dispersion coefficient (D_L). The approach is based on a slug injection of table salt (NaCl) as a tracer and specific conductance readings at different locations downstream of the injection spot. Observed specific conductance readings are fit using the advection-dispersion equation with OTIS-P, yielding estimates of cross-sectional area and longitudinal dispersion coefficient for various stream reaches. Estimates of the D_L are used to assess the accuracy of several empirical equations reported in the literature. This allowed the determination of complementary transport parameters related to transient storage zones. The empirical equations yielded rather high D_L values, with some reaching up an order of magnitude higher to those obtained from tracer additions and OTIS-P. Overall, the proposed approach seems reliable and pertinent for river reaches of ca. 150 m in length.     

The steryl ester and phospholipid fatty acids of the spongeAgelas conifera from the Colombian Caribbean

The steryl ester and phospholipid fractions of the marine spongeAgelas conifera were isolated and analyzed. The fatty acyl components of the steryl ester and phospholipid fractions as determined by gas chromatography and gas chromatography/mass spectrometry were very similar and consisted of 56.8 and 62.7% of C₁₄−C₂₀ acids (normal; branched, especiallyiso andanteiso; and monounsaturated, particularly Δ⁹ and Δ¹¹ acids) and of 43.1 and 35.5% of C₂₄−C₂₆ acids (Δ^5,9 diunsaturated acids), respectively. The major constituent fatty acids detected were 13-methyltetradecanoic,n-hexadecanoic, 10-methylhexadecanoic, 11-octadecenoic, 12-methyloctadecanoic, 5,9-pentacosadienoic and 5,9-hexacosadienoic acids. The phospholipids isolated were identified as phosphatidylcholine (37%), phosphatidylserine (34%), phosphatidylethanolamine (16%) and phosphatidylinositol (11%). The distribution of fatty acids within the phospholipid classes was also determined.     

Comparison of the effects of dietary sunflower oil and virgin olive oil on rat exocrine pancreatic secretion <Emphasis Type="Italic">in vivo</Emphasis>

The aim of this study was to investigate the functional consequences in vivo of adapting the rat exocrine pancreas to different dietary fats. Weanling rats were fed diets containing 10 wt% virgin olive oil or sunflower oil for 8 wk. We then examined resting and cholecystokinin-octapeptide (CCK-8)-stimulated pancreatic secretion in the anesthetized animals. To confirm a direct influence of the type of fat upon the gland, the FA composition of pancreatic membranes as well as tissue protein and amylase content were determined in separate rats. The membrane FA profile was profoundly altered by the diets, reflecting the type of dietary fat given, although this was not paralleled by variations in the pancreatic content of protein or amylase. Nevertheless, dietary intake of oils evoked different effects on in vivo secretory activity. Resting flow rate and amylase output were significantly (P<0.05) enhanced by sunflower oil feeding. Time course changes in response to CCK-8 infusion also showed a different pattern in each group. Secretion of fluid, protein, and amylase increased markedly in all animals, reaching a maximum within 20–40 min of infusion that was followed by a dramatic decline in both groups. In the sunflower oil group, this resulted in values reaching the resting level as soon as 60 min after CCK-8 infusion was begun. However, after the initial decline, olive oil group values showed a prolonged plateau elevation above the baseline (P<0.05) that was maintained for at least the infusion time. In addition, a positive correlation between flow rate and both protein concentration and amylase activity existed in the olive oil group, but not in the sunflower oil group. The precise mechanism by which these effects are produced remains to be elucidated.     

Photoluminescence Decay and Hydrogen Desorption of n-Type Porous Silicon

The decay under illumination of the photoluminescence (PL) intensity ofn-type porous silicon (PS) samples prepared by electrochemical etching has been investigated. We have found that the PL evolution with illumination time presents two different stages: an initial very fast decay which lasts 300 s, followedby a second one, much slower, which extends for times longer than 10⁴ s. Thisevolution suggests that two different mechanisms could be responsible for the PLintensity decay. Samples subjected to different illumination times were studied byThermal Desorption Spectroscopy (TDS). The desorption rate of H₂ and SiH_x species was monitored during linear heating of the samples. A qualitative correlationbetween the decay of the PL intensity under illumination and the amount of H₂ and SiH_x species evolved from the illuminated samples has been observed. Experimentaldata suggest that H₂ could be desorbed from the sample during the illuminationtime through a photoinduced H₂ desorption process, inducing the decrease of the PLintensity.