Numerical Analysis of Drivability of Non-Uniform Piles

This paper presents a numerical analysis of pile driving for tapered piles using FLAC software. The approach involves idealization of pile-soil system in pile drivability. The pile is assumed to be vertical and have elastic and linear behaviour. The soil is assumed to be elasto-plastic material which obeys the Mohr-Coulomb failure criterion. To allow slip between the pile and the soil in pile driving, interface elements are used at the pile-soil borders along the shaft and the toe. Quiet boundaries are considered in the lateral and vertical directions for the soil to absorb traveling waves. The obtained numerical results are compared with experimental results, leading to a satisfactory agreement. It will be shown that with increasing the angle of taper, the driving stresses decrease and the permanent pile toe settlement increases. These are interesting phenomena in pile driving and are on the safe side for driven piles

Regression modeling of field emissions in wheat production using a life cycle assessment (LCA) approach

Field emissions of Irianian wheat production were investigated. Data were collected from 260 farms from the city of Fereydonshahr in the Esfahan province. Life cycle assessment (LCA) methodology was developed to assess environmental impacts associated with the production of wheat in the studied region. Global warming potential (GWP), eutrophication potential (EP), human toxicity potential (HTP), terrestrial eco-toxicity potential (TEP), oxidant formation potential (OFP) and acidification potential (AP) were calculated as 2620.86 kg CO2 eq.t-1 (tonne of grain), 14.25 kg PO4 -2 eq.t-1, 1111.7 kg 1,4-DCB eq.t-1, 10.59 kg 1,4-DCB eq.t-1, 0.0073 kg ethylene eq.t-1 and 19.07 kg SO2 eq.t-1, respectively. In order to specify a relationship between input materials and field emissions (direct and indirect emission), the Cobb-Douglass production function was applied. The impacts of farm area, N, P2O5, K2O, diesel fuel and biocides were entered as independent variables and different impact categories as dependent variables. RMSE of models for GWP, EP, HTP, TEP, OFP and AP was 0.07, 0.19, 0.17, 0.34, 0.49 and 0.26, respectively. Accordingly with a rise in farm size level, the emissions per tonne of grain produced decreased

Fuel consumption models of MF285 tractor under various field conditions

Due to the ascending importance of energy in the world, prediction and optimization of Fuel Consumption (FC) in agricultural tasks is merit to consideration. In this study a Massey Ferguson (MF285) tractor was implemented with a low cost and precise data acquisition system as a means to record and monitor the affectual parameters on FC such as forward speed and instant fuel flow rate during field operation. Field experiments were carried out in the experimental farm of Agricultural Engineering Department of Tehran University, Karaj province, Iran, which had loamy soil texture. A mouldboard plow was used as tillage toll during the experiments at various tillage depths, engine speeds, forward speeds, tire inflation pressures, moisture contents and cone indexes. Acquired data were used to elicit an accurate model for Temporal, Area-specific and Specific Fuel Consumption (TFC, AFC and SFC). Results showed considerable effect of all measured parameters on TFC, AFC and SFC. For instance the TFC, AFC and SFC decreased by 11%, 13% and 56% respectively when the cone index increased from 105 to 1161 kPa. And also augmenting tillage depth from 10 to 20 cm led to 44% increase of TFC while SFC decreased by 164% oppositely. AFC rate was 1.1 liter per cm of tillage depth. Increasing the engine speed from 1200 to 2000 r/min led to increase of TFC, AFC and SFC by 56%, 71% and 46%, respectively. The forward speed was the most influential parameter on TFC, AFC and SFC while the moisture content and tire inflation pressure effects were minor. Models validation was acceptable and the fuel consumption rate could be predicted with accuracy of about 95%

Artificial Neural Network Based Modeling of Tractor Performance at Different Field Conditions

Application of tractors in farming is undeniable as a power supply. Therefore, performance model for evolving parameters of tractors and implements are essential for farm machinery, operators and manufacturers alike. The objective of this study was to assess the predictive capability of several configurations of ANNs for performance evaluating of tractor in parameters of drawbar power, fuel consumption, rolling resistance and tractive efficiency. A conventional tillage system which included a moldboard plow with three furrows was used for collecting data from MF285 Massey Ferguson tractor. To predict performance parameters, ANN models with back-propagation algorithm were developed using a MATLAB software with different topologies and training algorithms. For drawbar power. The best result was obtained by the ANN with 6-7-1 topology and Bayesian regulation training algorithm with R2 of 0.995 and MSE of 0.00024. The ANN model with 6-7-1 structure and Levenberg-Marquardt training algorithm had the best performance with R2 of 0.969 and MSE of 0.13427 for TFC prediction. The 6-8-1 topology shows the best power for prediction of AFC with R2 and MSE of 0.885 and 0.01348, respectively. Also, the 6-10-1 structure yielded the best performance for prediction of SFC with R2 of 0.935 and MSE of 0.012756. The obtained result showed that the 6-7-1 structured ANN with Levenberg-Marquardt training algorithm represents a good prediction of TE with R2 equal to 0.989 and MSE of 0.001327. The obtained results confirmed that the neural network can be able to learn the relationships between the input variables and performance parameters of tractor, very well

Energy analysis and greenhouse gas emission in broiler farms: A case study in Alborz province, Iran

The goal of this study was to examine the energy flows for poultry breeding in broiler production farms in Alborz province of Iran. Data were obtained randomly from 30 poultry production farms using a face to face questionnaire method. The results indicated that the total input energy was 189805.48 MJ per 1000 birds, while the output energy was 28151.17 MJ/(1000 bird). Net energy was negative, -161654.31 MJ/(1000 bird), implying that energy had been lost. Energy use efficiency was calculated as 0.15, showing the inefficient use of energy in the broiler production farms. The fuel energy (energy content of the fuel) with a share of 58.35% had the highest share of input energy and the feed energy by 29.71% was the next. Greenhouse gas (GHG) emission of the studied farms was 10267.96 kg CO2-eq/(1000 bird). Among different inputs, feed with 48% had the highest share of GHG emissions. Cobb-Douglas frontier production function was adopted to specify the production technology of the farms. Econometric model evaluation showed that the effects of diesel fuel and feed on output energy was significant at 1% level. The marginal physical productivity (MPP) values of energy inputs based on sensitivity analysis were 0.04 and 0.51 for diesel fuel and feed, respectively. The variability results between poultry farms showed that the most variability comes from fuel consumption

A review of the most important native medicinal plants of Iran effective on gastric acid

Gastrointestinal diseases such as gastric acid hypersecretion are highly prevalent. Gastrointestinal diseases manifest frequently with gastric and duodendal ulcers, gastritis, and dyspepsia which are due to impaired gastric acid secretion. Given the frequency of developing gastrointestinal diseases such as gastric acid hypersecretion and consequently gastric ulcer, the aim of this review article is to report the native medicinal plants of Iran that are used to decrease or neutralize gastric acid. Ziziphora clinopodioidesl, Achillea wilhelmsii, Allium sativum, Amirkabiria odoratissim, Heracleum persicum L. and Medicago sativa are the most native medicinal plants of Iran used to treat gastric acid hypersecretion. Certain compounds such as pulegon, cisisopulegon, cineol, thymol, alpha and betapinene, piperitenone, terpenoids, flavonoids, allicin, tannin, terpenoids, saponin, sterol, and leucoanthocyanin, 3, 4, and 7-trihydroxy flavonol, caffeic acid, and fetalid existing in these plants may be the main agents for reducing gastric acid

L-2-Hydroxyglutaric Aciduria is a Diagnostic Indicator of Leukodystrophy: A Case Report

How to Cite this Article: Ashrafi MR, Nikkhah A, Houshmand M, Aryani O. L-2-Hydroxyglutaric Aciduria is a Diagnostic Indicator of Leukodystrophy: A CaseReport Iranian Journal of Child Neurology 2011;5(4):37-38. L-2-Hydroxyglutaric aciduria is a rare autosomal recessive inherited neurometabolic disorder.It is characterized by slow progressive neurological dysfunction with cerebellar ataxia, pyramidal and extrapyramidal signs, intellectual decline, and seizures. Herein, we report a case of a 7-year-old boy from Tehran whose symptoms and signs indicated leukoencephalopathy with macrocephaly and motor delay. References 1. Barth PG, Hoffmann GF, Jaeken J, Lehnert W, Hanefeld F, van Gennip AH, et al. L-2-hydroxyglutaric acidemia: a novel inherited neurometabolic disease. Ann Neurol 1992;32(1):66-71. 2. Duran M, Kamerling JP, Bakker HD, Van Gennip AH, Wadman S. L-2-Hydroxyglutaric aciduria: an inborn error of metabolism? J Inherit Metab Dis 1980;3(4):109-12. 3. Haliloglu G, Jobard F, Oguz KK, Anlar B, Akalan N, Coskun T, et al. L-2-hydroxyglutaric aciduria and brain tumors in children with mutations in the L2HGDH gene: neuroimaging findings. Neuropediatrics  2008;39(2):119-22. 4. De Klerk JB, Huijmans JG, Stroink H, Robben SG, Jakobs C, Duran M. L-2-hydroxyglutaric aciduria: clinical heterogeneity versus biochemical homogeneity in a sibship. Neuropediatrics 1997;28(6):314-7. 5. Fenichel GM. Clinical pediatric neurology: a signs and symptoms approach. Saunders:Elsevier, 2009. 6. Diogo L, Fineza I, Canha J, Borges L, Cardoso ML, Vilarinho L. Macrocephaly as the presenting feature of L-2-hydroxyglutaric aciduria in a 5-month-old boy. J Inherit Metab Dis 1996;19(3):369-70. 7. Rzem R, Van Schaftingen E, Veiga-da-Cunha M. The gene mutated in l-2-hydroxyglutaric aciduria encodes l-2-hydroxyglutarate dehydrogenase. Biochimie 2006;88(1):113-6. 8. Shafeghati Y, Vakili G, Entezari A. L-2-hydroxyglutaric aciduria: A report of six cases and Review of the Literature. Arch Iran Med 2006;9(2):165-9.

New methods for captive finance in project based companies using private sectors supply

Economic development in countries depends on implementing of infrastructural projects and services, furthermore, increasing efficiency and quality of offered services are of its purposes. Mention this fact that in developing countries finding the financial source is one of the main challenges that often faced up, cooperating with private sectors seems more important from day to day. The cooperative styles vary due to each project specific condition. In current research, the compilation of constructing types and financial recourse, briefly discussed in base of implementing and financing captive methods, then with mentioning the legal limitation and specific conditions in our country, the appropriate methods in different projects including oil and gas, petro chemistry and water resources are revealed. Finally, essential conditions and characteristics of these offered corporations were expanded on, for using them efficiently to provide the essential fundamental by private resources that lead to economic development and improvement

New methods for captive finance in project based companies using private sectors supply

Economic development in countries depends on implementing of infrastructural projects and services, furthermore, increasing efficiency and quality of offered services are of its purposes. Mention this fact that in developing countries finding the financial source is one of the main challenges that often faced up, cooperating with private sectors seems more important from day to day. The cooperative styles vary due to each project specific condition. In current research, the compilation of constructing types and financial recourse, briefly discussed in base of implementing and financing captive methods, then with mentioning the legal limitation and specific conditions in our country, the appropriate methods in different projects including oil and gas, petro chemistry and water resources are revealed. Finally, essential conditions and characteristics of these offered corporations were expanded on, for using them efficiently to provide the essential fundamental by private resources that lead to economic development and improvement

Vibration condition monitoring of planetary gears based on decision level data fusion using Dempster-Shafer theory of evidence

In recent years, due to increasing requirement for reliability of industrial machines, fault diagnosis using data fusion methods has become widely applied. To recognize crucial faults of mechanical systems with high confidence, indubitably decision level fusion techniques are the foremost procedure among other data fusion methods. Therefore, in this paper in order to improve the fault diagnosis accuracy of planetary gearbox, we proposed a representative data fusion approach which exploits Support Vector Machine (SVM) and Artificial Neural Network (ANN) classifiers and Dempster-Shafer (D-S) evidence theory for classifier fusion. We assumed the SVM and ANN classifiers as fault diagnosis subsystems as well. Then output values of the subsystems were regarded as input values of decision fusion level module. First, vibration signals of a planetary gearbox were captured for four different conditions of gear. Obtained signals were transmitted from time domain to time-frequency domain using wavelet transform. In next step, some statistical features of time-frequency domain signals were extracted which were used as classifiers input. The gained results of every fault diagnosis subsystem were considered as basic probability assignment (BPA) of D-S evidence theory. Classification accuracy for the SVM and ANN subsystems was determined as 80.5 % and 74.6 % respectively. Then, by using the D-S theory rules for classifier fusion, ultimate fault diagnosis accuracy was gained as 94.8 %. Results show that proposed method for vibration condition monitoring of planetary gearbox based on D-S theory provided a much better accuracy. Furthermore, an increase of more than 14 % accuracy demonstrates the strength of D-S theory method in decision fusion level fault diagnosis