Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind,wave, and seismic excitations

The main intention of the present study is to reduce wind, wave, and seismic induced vibrations of jackettype offshore wind turbines (JOWTs) through a newly developed vibration absorber, called tuned liquid column gas damper (TLCGD). Using a Simulink-based model, an analytical model is developed to simulate global behavior of JOWTs under different dynamic excitations. The study is followed by a parametric study to explore efficiency of the TLCGD in terms of nacelle acceleration reduction under wind, wave, and earthquake loads. Study results indicate that optimum frequency of the TLCGD is rather insensitive to excitation type. In addition, while the gain in vibration control from TLCGDs with higher mass ratios is generally more pronounced, heavy TLCGDs are more sensitive to their tuned frequency such that ill-regulated TLCGD with high mass ratio can lead to destructive results. It is revealed that a well regulated TLCGD has noticeable contribution to the dynamic response of the JOWT under any excitation.     

Dependence of correlations between spectral accelerations at multiple periods on magnitude and distance

In this paper, the dependence of correlations between spectral accelerations at multiple periods on magnitude (M) and distance (R) has been investigated. For this purpose, a relatively large dataset of ground motion records (GMRs), containing 1551 records with a wide range of seismic characteristics, was selected. It is shown that the difference in the correlation coefficient is statistically meaningful when the general GMR dataset is divided into two subsets based on an arbitrary M or R. The observed difference is more meaningful in the case of magnitude when compared with distance. The general dataset of GMRs was then divided into four separate subsets based on optimum values of M and R, so that the four obtained subsets were given the greatest dissimilarity in terms of the correlation coefficients. The correlation coefficients between spectral accelerations at multiple periods were calculated in the case of the four subsets and compared with the available correlations in the literature. The conditional mean spectrum was also calculated by means of the conventional correlation coefficients, as well as by using the proposed M and R dependent correlation coefficients. The results show that, despite the commonly available findings in the literature, this dependence is significant and should not be neglected in the conditional spectra calculation process. Copyright © 2013 John Wiley & Sons, Ltd.     

Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study

In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M₅₃₁ and M₇₄₁, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models.     

Nettle ash as a low cost adsorbent for the removal of nickel and cadmium from wastewater

This study was focused on nettle ash as an alternative adsorbent for the removal of nickel (II) and cadmium (II) from wastewater. Batch experiments were conducted to determine the factors affecting adsorption of nickel (II) and cadmium (II). The adsorption process is affected by various parameters such as contact time, solution pH and adsorbent dose. The optimum pH required for maximum adsorption was found to be 6. The experimental data were tested using Langmuir, Freundlich and Tempkin equations. The data were fitted well to the Langmuir isotherm with monolayer adsorption capacity of 192.3 and 142.8 mg/g for nickel and cadmium, respectively. The adsorption kinetics were best described by the pseudo second order model. The cost of removal is expected to be quite low, as the adsorbent is cheap and easily available in large quantities. The present study showed that nettle ash was capable of removing nickel and cadmium ions from aqueous solution.     

Evaluation of scraping treatments to restore initial infiltration capacity of three artificial recharge projects in central Iran

 A limiting factor in developing artificial recharge of groundwater is clogging of the soil surface and consequent reduction of infiltration rates. In order to evaluate the degree of improving infiltration rates by scraping away various amounts of the upper soil materials, a study was conducted at three artificial recharge sites (Kohrouyeh, Bagh-Sorkh, and Kachak) in Isfahan Province, central Iran. Five treatments (T1–T5) were considered. Infiltration was measured: T1, on deposited sediment layer; T2, after removing the sediments; T3, scraping of sediments and 5 cm of soil; T4, scraping of sediments and 10 cm of soil; and T5, removing sediments and 15 cm of soil. Initial soil-moisture content of the sites ranged from 1.0–2.87% for Kohrouyeh, 1.18–3.47% for Bagh-Sorkh, and 1.89–3.93% for Kachak. The main texture of the soils was sandy loam. Clay particles have penetrated to a depth of more than 40 cm in some of the recharge basins. A significant increase in final infiltration rate of T5 as compared to T1 treatment was observed for all recharge sites. The final infiltration rates of T1 and T5 treatments for Kohrouyeh, Bagh-Sorkh, and Kachak sites were 0.35, 7.9; 1.22, 12.3; and 0.93, 6.2 cm/h, respectively. The differences between infiltration rates of T2, T3, and T4 treatments were not statistically significant. It is concluded that on average, the infiltration capacity of the untreated recharge facilities have reached 20.3% of the original values, and that scraping the top sediment layer and 15 cm of topsoil could restore 68.3% of the initial infiltration capacity. Received, July 1998 / Revised, April 1999, May 1999 / Accepted, June 1999     

Study of syntrophic anaerobic digestion of volatile fatty acids using enriched cultures at mesophilic conditions

Volatile fatty acids are the most important intermediates in anaerobic digestion, and their degradations are extremely complicated thermodynamically. In this research, syntrophic anaerobic digestion of volatile fatty acids using enriched acetogenic and methanogenic cultures in a batch reactor at mesophilic conditions was investigated. Interactive effects of key microbiological and operating variables (propionic, butyric and acetic acids, retention time and methanogen to acetogen populations ratio) on the anaerobic degradation of volatile fatty acids were analyzed. Acetogenic and methanogenic anaerobes in the granular sludge from an up-flow anaerobic sludge blanket reactor were enriched at mesophilic conditions within a period of four weeks, separately. Enriched cultures were mixed with known proportions and then used in the bioreactor. Experiments were carried out based on central composite design and analyzed using response surface methodology. Four parameters (final concentrations of propionic, butyric and acetic acids and biogas production) were directly measured as response. Also, the optimum conditions for volatile fatty acid degradation were found to be 937.5 mg/L, 3275.5 mg/L, 2319.5 mg/L, 45 h and 2.2 proportions for propionic acid, butyric acid, acetic acid, retention time and methanogen to acetogen populations ratio, respectively (corresponding to maximum volatile fatty acid removal efficiencies and biogas production). The results of the verification experiment and the predicted values from the fitted correlations at the optimum conditions were in close agreement at a 95% confidence interval. The present study provides valuable information about the interrelations of quality and process parameters at different values of microbiological and operating variables.     

Storage-yield analysis of surface water reservoirs: the role of reliability constraints and operating policies

Stochastic optimization methods are used for optimal design and operation of surface water reservoir systems under uncertainty. Chance-constrained (CC) optimization with linear decision rules (LDRs) is an old approach for determining the minimum reservoir capacity required to meet a specific yield at a target level of reliability. However, this approach has been found to overestimate the reservoir capacity. In this paper, we propose the reason for this overestimation to be the fact that the reliability constraints considered in standard CC LDR models do not have the same meaning as in other models such as reservoir operation simulation models. The simulation models have fulfilled a target reliability level in an average sense (i.e., annually), whereas the standard CC LDR models have met the target reliability level every season of the year. Mixed integer nonlinear programs are presented to clarify the distinction between the two types of reliability constraints and demonstrate that the use of seasonal reliability constraints, rather than an average reliability constraint, leads to 80–150 % and 0–32 % excess capacity for SQ-type and S-type CC LDR models, respectively. Additionally, a modified CC LDR model with an average reliability constraint is proposed to overcome the reservoir capacity overestimation problem. In the second stage, we evaluate different operating policies and show that for the seasonal (average) reliability constraints, open-loop, S-type, standard operating policy, SQ-type, and general SQ-type policies compared to a model not using any operation rule lead to 190–460 % (200–550 %), 100–200 % (80–300 %), 0–90 % (0–60 %), 30–90 % (0–20 %), and 10–90 % (0–10 %) excess capacity, respectively.     

A comparative study of kriging and simulation-based methods in classifying ore and waste blocks

Ore grade is the most important source of uncertainty in a mining operation which plays an important role to classify run-of-mine (ROM) material into ore and waste parcels. As a widely used method, kriging estimator is used to estimate the grade of ore blocks. In conventional mining practices, if the estimated grade of a parcel is above the cut-off grade, this parcel is classified as ore, otherwise, is labelled as a waste parcel. An alternative approach is to simultaneously consider the grade of parcels and the economic consequences of sending parcels to destinations by applying simulation-based methods. In this study, kriging and simulation-based methods including loss and profit functions are applied on a real-world case study to classify ore/waste material based on the initial exploration data. Then, the actual known data, collected from blast holes samples, are compared with the estimated results in order to validate the performance of the presented methods. Outcomes show that simulation-based methods can perform better and show more adjustability with real data.     

Stochastic finite element modelling of water flow in variably saturated heterogeneous soils

Water flow is greatly influenced by the characteristics of the domain through which the process occurs. It is generally accepted that earth materials have extreme variations from point to point in space. Consequently, this heterogeneity results in high variation in hydraulic properties of soil. In order to develop an accurate predictive model for transport processes in soil, the effects of this variability should be considered. In this study a two‐dimensional stochastic finite element flow model was developed for simulation of water flow through unsaturated soils. In this model, the stochastic partial differential governing equation of water flow, obtained from implementation of the perturbation‐spectral stochastic method on classical Richard's equation, was solved using a finite element method in the space domain and a finite difference scheme in the time domain. The effective hydrological parameters embedded in the mathematical model depend on time derivatives of capillary tension head; this makes possible to consider the hysteresis due to large‐scale variability of soil hydrological properties. The model is also capable of simulating infiltration and evaporation events and rapid change in the land surface boundary condition from one type event to another, based on a scheme used in the model for implementation of land surface boundary condition. The model was validated with the data obtained from a layered lysimeter test. The model was also used to simulate water flow under a long irrigation furrow. The results obtained with this model show better agreement with experimental measurements in comparison with a deterministic model. The possible reason for this agreement is that in the developed model, the influence of the variability of the properties of soil and effects of parameter hysteresis on water flow and water content redistribution are considered. Copyright © 2010 John Wiley & Sons, Ltd.