The article aims at developing an efficient and stable catalysts for simultaneous hydrogenation of o-chloronitrobenzene to o-chloroaniline and 1,4-butanediol dehydrogenation to γ-butyrolactone. A series of CoO-Cu-MgO catalysts, composed of 10 wt% of copper, various amount of cobalt loadings (1, 5 and 10 wt%) and remaining of MgO were developed by co-precipitation followed by thermal treatment. o-Chloroaniline and γ-butyrolactone were the main products with high yield of 85% and 90%, respectively. The advantage of the coupling process is that the hydrogenation reaction was conducted without external hydrogen, demonstrating minimize the hydrogen consumption known as hydrogen economy route. From N₂O characterization results, the high activity of 5CoO-10Cu-MgO was found that it has high amount of Cu species (Cu⁰/Cu⁺¹) which govern the stable activity and selectivity on time on stream study in presence of cobalt in Cu-MgO.

Afforestation is a main tool for preventing desertification and soil erosion in arid and semiarid regions of Iran. Large-scale afforestation, however, has poorly understood consequences for the future ecosystems in the term of ecosystems protection. The objective of the present study is to identify changes in soil properties following different intervals of planting of Ailanthus altissima (tree of heaven) in semiarid afforestation of Iran (Chitgar Forest Park, Tehran). For this purpose, sand, silt and clay ratios, bulk density, soil moisture, pH, electrical conductivity, phosphorus, potassium, magnesium, calcium, sodium, total soil N, and total carbon was measured. Our study highlighted the potential of the invasive trees by A. altissima, to alter soil properties along chronosequence. Almost all soil quality attributes showed a declining trend with stand age. A continuous decline in soil quality indicated that the present land management may not be sustainable. Therefore, an improved management practice is imperative to sustain soil quality and maintain long-term productivity of plantation forests. Thinning activity will be required to reduce the number of trees competing for the same nutrients especially in a older stand to protect forest soils.

This paper is concerned with the numerical solution of the mixed Volterra-Fredholm integral equations by using a version of the block by block method. This method efficient for linear and nonlinear equations and it avoids the need for spacial starting values. The convergence is proved and finally performance of the method is illustrated by means of some significative examples.

The regulation of compressor extraction and energy storage can improve the performance of gas turbine energy system. In order to make the gas turbine system match the external load more flexibly and efficiently, a gas turbine cogeneration system with solar energy coupling compressor outlet extraction and energy storage is proposed. By establishing the variable condition mathematical model of air turbine, waste heat boiler and solar collector, we use Thermoflex software to establish the variable condition model of gas turbine compressor outlet extraction, and analyze the variable condition of the coupling system to study the changes of thermal parameters of the system in the energy storage, energy release and operation cycle. Taking the hourly load of a hotel in South China as an example, this paper analyzes the case of the cogeneration system of solar energy coupling compressor outlet extraction and energy storage, and compares it with the benchmark cogeneration system. The results show that taking a typical day as a cycle, the primary energy utilization rate of the system designed in this paper is 3.2% higher than that of the traditional cogeneration system, and the efficiency is 2.4% higher.

Helical deep hole drilling is a process frequently used in industrial applications to produce bores with a large length to diameter ratio. For better cooling and lubrication, the deep drilling oil is fed directly into the bore hole via two internal cooling channels. Due to the inaccessibility of the cutting area, experimental investigations that provide information on the actual machining and cooling behavior are difficult to carry out. In this paper, the distribution of the deep drilling oil is investigated both experimentally and simulatively and the results are evaluated. For the Computational Fluid Dynamics (CFD) simulation, two different turbulence models, i.e. the RANS k-ω-SST and hybrid SAS-SST model, are used and compared. Thereby, the actual used deep drilling oil is modelled instead of using fluid dynamic parameters of water, as is often the case. With the hybrid SAS-SST model, the flow could be analyzed much better than with the RANS k-ω-SST model and thus the processes that take place during helical deep drilling could be  simulated with realistic details. Both the experimental and the simulative results show that the deep drilling oil movement is almost exclusively generated by the tool rotation. At the tool’s cutting edges and in the flute, the flow velocity drops to zero for the most part, so that no efficient cooling and lubrication could take place there. In addition, cavitation bubbles form and implode, concluding in the assumption that the process heat is not adequately dissipated and the removal of chips is adversely affected, which in turn can affect the service life of the tool and the bore quality. The carried out investigations show that the application of CFD simulation is an important research instrument in machining technology and that there is still great potential in the area of tool and process optimization.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.