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.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.

In this study, robust and defect-free thin film composite (TFC) forward osmosis (FO) membranes have been successfully fabricated using ceramic hollow fibers as the substrate. Polydopamine (PDA) coating under controlled conditions is effective in reducing the surface pores of the substrate and making the substrate smooth enough for interfacial polymerization. The pure water permeability (A), solute permeability (B), and structural parameter (S) of the resultant FO membrane are 0.854 L·m^–2·h⁻¹·bar⁻¹ (LMH/Bar), 0.186 L·m^–2·h⁻¹ (LMH), and 1720 µm, respectively. The water flux and reverse draw solute flux are measured using NaCl and proprietary ferric sodium citrate (FeNaCA) draw solutions at low and high osmotic pressure ranges. As the osmotic pressure increases, a higher water flux is obtained, but its increase is not directly proportional to the increase in the osmotic pressure. At the membrane surface, the effect of dilutive concentration polarization is much less serious for FeNaCA-draw solutions. At an osmotic pressure of 89.6 bar, the developed TFC membrane generates water fluxes of 11.5 and 30.0 LMH using NaCl and synthesized FeNaCA draw solutions. The corresponding reverse draw solute flux is 7.0 g·m^–2·h⁻¹ (gMH) for NaCl draw solution, but it is not detectable for FeNaCA draw solution. This means that the developed TFC FO membranes are defect-free and their surface pores are at the molecular level. The performance of the developed TFC FO membranes is also demonstrated for the enrichment of BSA protein.

This problem is a solar hut photovoltaic cell in the attached and overhead two installation methods, the type of photovoltaic cells and array mode and inverter type optimization design issues. In question 1, since the photovoltaic cells are attached to the roof and exterior surfaces, the direction and angle of the battery are uniquely determined by the direction and angle of the attached surface. The problem is translated to optimize the installation of a certain type on a single surface area (array) of photovoltaic cells, so that the total amount of solar photovoltaic power generation as much as possible, and the unit power generation costs as small as possible, which is a multi-objective optimization problem. The problem can be discussed in the ideal environment in a single surface area of the battery installation optimization program, and then the actual environment of the multi-surface optimization. In the solution to Problem 1, the unit on the south of the roof of the battery at the moment to accept the solar energy formula is generated. The definition of and is the moment of direct radiation intensity, for the moment the sun and the south of the roof of the plane where the angle, for the level of horizontal radiation intensity, for the south of the roof and the horizontal angle, the planefor the plane, the center of the heart, the vertical upward direction is the axis of the positive coordinate system, obtained with the sun height angle , the sun azimuth , red angle, angle and the sun when the relationship is generated. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of electricity generation is 77126 degrees, the economic benefits of 16,488 yuan, the recovery period of 21.3 years. In question 2, because the photovoltaic cells in the roof and the external wall surface can be installed overhead, the panel orientation and tilt will affect the efficiency of photovoltaic cells. Therefore, in the optimization scheme of Problem 1, the orientation and inclination of the panel on each surface are further adjusted to calculate the optimum orientation and inclination of the panel on each surface. The problem can be in the ideal weather environment to establish the sun running and the battery board efficiency model, and then the measured environment test. The optimal orientation of the panel is southward, and the optimal angle with the ground plane is 39.89 degrees. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of generating capacity of 82165.2 degrees, the economic benefits of 18,998 yuan, the recovery period of 13 years. In question 3, by the optimization of the above two issues, in the building to meet the requirements of the hut under the design of the various aspects of the cabin and battery installation, and further optimize the total power generation of the hut, economic benefits. The whole model solver is run in MATLAB7.0.

Numerical study of subcooled and saturated flow boiling in the curved and helically  coiled tubes in presence of phase change is one of the challenging area of CFD studies. In this paper, the CFD modeling of the nucleate and convective flow boiling in the small helically coiled tube at low vapor quality (up to the 18.93 percent) region is studied. A proper Eulerian-based mathematical model is used for interphase exchange forces and heat transfer between two phases in CFD modeling using Bulk boiling model. The results show that, the inner and the bottom wall of the helically coiled tube have the lowest and the highest heat transfer coefficient, respectively. The effect of change in coil diameter, helical pitch and tube diameter is investigated on the counters of vapor volume fraction. It is seen that at low vapor quality flows, the heat transfer coefficient is enhanced by decreasing in coil diameter, tube diameter and increasing in coil pitch of helically coiled tube.