• Energy Research
• Open Access close
• Restricted close
• Embargo close
• other engineering and technologies close
• Persian close

The main objective of this study is to design and construct the new, spouted bed dryer, for food drying sensitive foods specially. For this purpose, firstly a new design of dryer was planned to achieve the maximum efficiency and flexibility for liquids and solids drying. After constructing and initial setup of spouted bed, basic experiments such as investigation of an inert particles motion, pressure drop, energy consumption were conducted and optimal system requirements for two particle size (5.8 & 7.8 mm) were determined. The results indicated that changes in pressure drop in the dryer chamber containing inert particles are followed from the Ergun equation. Energy consumption in this system is variable in the range of 3-8 kW per hour. Also results reveals that the energy consumption of the new design of spouted bed dryer is less than the spray dryer for liquid foods drying.

Customer Relationship Management (CRM) is a productive tool for monitoring the customer and recognizing their characteristics, behaviors, and his/her requirements and anticipating his/her reactions in order to establish a long term and strong relation with customer. CRM is a business strategy selecting and managing the most valuable customer relationships. CRM includes different parts and dimensions that covers the whole stages of business from marketing to conclusion of contract, R&D, product/service design, sale and period after that. One of the important tools applied in CRM is Customer Lifetime Value (CLV). CLV allocates a quantitative value to each customer or a specific group and ranks them with this quantity. Different methods have been introduced to calculate this quantitative value. This paper tries to analyze all mentioned methods and presents the weakness and strength of each method. The most weakness of the typical method is not to concentrate on the future value of the customer. In order to rectify the weakness, in this paper an innovative model which combines two methods of RFM (which considers qualitative factors) and ROI (which considers financial factors) has been introduced. The validation of the model has been accomplished based upon real case study of one of the Iranian Insurance Companies.

For structural reliability assessment or risk analysis of aging offshore steel structures, it is essential to have a probabilistic model, which contains specific statistical parameters, and predicts long term corrosion loss as a function of time. The aim of this study is to propose such model for offshore jacket platforms in the Persian Gulf. Field measurements for material loss due to uniform corrosion for submerged members in seawater have been collected and statistically analyzed to identify the probability density distribution function for dispersion and variation of corrosion loss value according to the passage of time. To predict the corrosion loss, two probabilistic models with different approaches and time dependent parameters are suggested, based on the statistical analysis results. For a comparative study, the application of aforementioned models on the reliability analysis of a simple plate structure is investigated. Prediction results, obtained from the proposed probabilistic models, are consistent well with filed measurements.

In the present study, alkali roasting and oxalic acid leaching were used to extract titanium dioxide from ilmenite, and the effect of ethanol and ascorbic acid on the purity and recovery of titanium dioxide was investigated. In this research, ilmenite was alkali roasted with sodium carbonate for 4 hours at 900˚C. Then, the roasted ilmenite was leached with distilled water for 1 hour at room temperature. Finally, leaching with a mixture of 0.47M oxalic acid and different amounts of ascorbic acid and ethanol was performed at 65˚C. The results showed that using ethanol caused an increase in the amount of recovery and ascorbic acid increased the purity of the extracted titanium dioxide; also, the presence of these two factors at the same time simultaneously increased the amount of purity and recovery of the final product. Eventually, by choosing 0.47M oxalic acid, 0.005M ascorbic acid, and 48% ethanol as the appropriate conditions for leaching media and increasing the leaching time and temperature to 16 hours and 80˚C, it was possible to get titanium dioxide purities which were as high as 93.3% and 90.9%, respectively.

Background and Objectives: Cadmium can enter water resources through the industrial wastewater. It could cause intensivly damages to the liver and kidney of humans. Magnetic iron nanoparticles are used to control and eliminate heavy metals from industrial effluents through the mechanisms of adsorption, ion exchange and electrostatic forces. The aim of this study was to evaluate the efficiency of magnetic nanoparticles for adsorption of cadmium. Methods: The magnetite nanoparticles were prepared by co-precipitation method through the addition of bivalent and trivalent iron chloride under alkaline conditions. Characteristics of nanoparticles including particles structure, composition and size were determined using analytical devices such as XRD, SEM, and FT-IR. For optimization of adsorption process of cadmium, some parameters such as pH, contact time, initial concentration of cadmium, nanoparticles concentration, and temperature were studied under different conditions. Results: It was found that 95% of cadmium could be removedAt pH ≥ 5.6, 10 mg/L initial cadmium concentration, a dose of 1 mg synthesized magnetite nanoparticles, 10 minutes contact time, and 200 rpm mixing rate at 25 °C. The isotherm of adsorption follows the Langmuir model (R2 < 0.995). Maximum capacity of cadmium adsorption was found to be 20.41 mg/g. Conclusion: Magnetite nanoparticles exhibit high capability for removal of cadmium. The nanoparticles synthesized could be used at industrial scale because of having the magnetic property, which make them easily recovered from aqueous solution through applying a magnetic field.

Introduction: Organization culture explains the characteristic of any organization. Organization culture includes values, standards and portrays behavior of members of that organization. Considering the pivotal role which is played by human resources and also the cost borne by these human sources, any kind of neglection on part of management can be drastic. Methods: This cross-sectional study included 95 employees of Yazd health care institutions. Data collection was through a questionnaire based on 10 dimensions and 44 indicators about organizational culture in EFQM environment. Results: The situation regarding organizational culture dimensions was not appropriate from viewpoint of EFQM in any of the health care institutions. Conclusions: Spurred by impressive results in other industries, this compelling and logical approach has begun to penetrate the thinking of health care accrediting agencies, business coalitions, private foundations and leading health care organizations. In this case, making some potential situations and using the study results of improvement of organizational culture can develop environmental situations for employee’s promotion and firm growth.

Thunder and storm fluctuations as consequences of climate change were studied in the Caspian region over the last half century. In this study, whole forest areas in southern part of Caspian sea were monitored by study on vegetation map and field visit. Three points representing the major part of the Hyrcanian forests were selected from wet part in the west to drier part in the east. Four meteorological stations data used for investigation. Most of climatic factors including maximum, minimum and mean annual temperature; daily, monthly and annual precipitations were investigated. Numbers of days with thunder and storm as well as wind speed were used for conclusion. During last half century, as consequence of climate change by means of increasing temperature and changing precipitation trends, number of Days With Thunder and Storms (DWTS) increased in forest area in the Caspian region. In Rasht and Gorgan stations, the number of days with thunder and storm in last half century, especially in last 25 years showed a sharp increase. This is in the same line of increasing mean annual temperature about 1.28°C and minimum temperature about 2.45°C in Rasht station. In addition, it is against the decrease of precipitation for the period of last 53 years in Gorgan station which is about 55.6 mm. Anzali and Baboulsar stations which are under coastal climate condition have a fluctuating trend of DWTS but also showed a mild increase in the trend of DWTS during last fifty years. This is in favor of increasing the mean annual temperature in Baboulsar station in last 54 years, about 1.44°C and its minimum temperature about 1.80°C. Also again, it is against the decrease of annual precipitation in Anzali station during last 54 years of records, which is about 409.4 mm and amount of the decreas of precipitation for the period of last 53 years in Gorgan station is about 55.6 mm.

Nowadays in some manufacturing processes, the quality of a product or process is well expressed by both correlated attribute and variable quality characteristics. To best of our knowledge, there is no method for monitoring the covariance matrix of multivariate-attribute quality characteristics. In this paper, we propose a multi-layer perception artificial neural network to monitor multivariate-attribute processes as well as to diagnose the quality characteristic(s) responsible for out-of-control signals. The performance of the proposed method is evaluated through a numerical example from both detection and diagnosis perspectives. In addition, the performance of the proposed neural network in detecting shifts in the variance of quality characteristics is compared with two statistical methods first proposed for monitoring the variability of multivariate quality characteristics and developed in this paper for our problem. The results of numerical example show that the proposed artificial neural network outperforms the extended statistical methods in detecting different out-of-control shifts. The results also confirm that the performance of the proposed neural network in identifying the quality characteristic(s) responsible for out-of-control signal is satisfactory

The industry of Dried Fruit Export is one of undeveloped industries regarding E-Commerce in Iran. This research is an attempt to investigate E-commerce admission obstacles in the industry of Dried Fruit Export of Iran and present its solutions. To achieve this purpose, we have identified the most important admission obstacles of E-commerce through reviewing the research literature and have classified them in the form of Tri-category (3C) Model in three co-structural, content and context dimensions as three research hypotheses. After distributing and collecting questionnaires among 61 randomly selected Dried Fruit Exporting companies of East Azerbaijan province and analyzing the data, all three dimensions of obstacles were supported and co-structural obstacles were recognized as the most important factors in the non-admission of E-commerce in the Industry of Dried Fruit Export. The government and related commercial organizations can consider the recommendations presented in this paper in order to help the private sector to implement E-commerce and remove the found obstacles for developing export.

Caspian Sea is one of the most low-lying areas of the region which is located between latitudes 36.34 and 47.13 degrees north. Its considerable vast area and depth have provided an opportunity to gain renewable energy by different methods. This paper analyzes the performance and mechanism of a floating wave energy converter known as WaveStar, in the above-mentioned sea. Different parts of mechanism are examined under hydrodynamic forces of waves with certain periods and amplitudes. By using the frequency parameters, profile and velocity of the waves; and solving the governing dynamic equations for the model, the vibration response of system has been derived. The main part of this study is the investigation of the effect of changing the arm length, float diameter, wave period and wave amplitude on the structure using regular wave with Froude-Krylov force.