Modeling
M. Sadeghi-Delooee; R. Alimardani; H. Mousazadeh
Abstract
IntroductionThere are two types of hydropower harvesting methods: conventional and unconventional. In the conventional method, the potential energy of water is harvested using a dam or barrage. However, in the unconventional method, the kinetic energy of flowing water is extracted using hydrokinetic ...
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IntroductionThere are two types of hydropower harvesting methods: conventional and unconventional. In the conventional method, the potential energy of water is harvested using a dam or barrage. However, in the unconventional method, the kinetic energy of flowing water is extracted using hydrokinetic turbines. Resource assessment is a pivotal step in developing hydrokinetic energy sites. Power density (power per unit area) is used to estimate the theoretical hydrokinetic power of a site. Flow velocity and cross-sectional area are the two variables that constitute the power density. Researchers use various methods such as numerical simulation, direct velocity measurement, or indirect velocity calculation using discharge data to conduct resource assessment. In the latter method, the Manning equation is used to convert the discharge data into velocity values. While this method is straightforward for canals, given their fixed and known geometry, it is cumbersome to calculate the hydraulic radius in rivers. To overcome this challenge, numerous researchers have proposed the utilization of hydraulic geometry (HG) to estimate the width and depth of a river reach, and then calculate the hydraulic radius based on these estimated values. The main objective of this study is to present and implement a fast method for assessing theoretical hydrokinetic power using the HG and the Manning equation.Materials and MethodsIn the present study, two hydrometry stations (Gachsar and Siera-Karaj) were selected in the Karaj dam watershed in Iran to implement resource assessment based on HG. A computer code comprising the following four steps was developed in Python using the Google COLAB environment.Data Preparation: The monthly-averaged discharge, Manning roughness coefficient, and slope were collected and imported into the code. The roughness coefficient could be determined directly or indirectly. In the present study, it was considered to be 0.045 for the Karaj River according to the literature review. ArcGIS software and the Digital Elevation Model (DEM) were used to extract the local slope of each hydrometry station. For this purpose, the stream network of Alborz province was first extracted, and then the longitudinal elevation profile was measured using the 3D Analyst tools. Discharge Data Processing: The flow duration curve (FDC) is one of the computational tools used by engineers to describe the hydrological regime of watersheds. FDC is a graphical representation of the cumulative distribution of flows. In the present study, an all-time record FDC for each station was constructed, and fitted with five different probability distribution functions (PDF). The results of PDF fittings were evaluated by different goodness-of-fit indices, and the best PDF was selected. Calculations of HG and the Manning Equation: The HG formulas were used to calculate the width and depth of flow using the reconstructed FDC from the previous step. These values, along with the roughness coefficient and slope, were used to calculate flow velocity using the Manning equation. After obtaining the flow velocity values, the power density was easily computed. Generating Outputs: In the final step, two categories of outputs are generated: (1) duration curves for width, depth, flow velocity, and power density, and (2) theoretical and turbine-extracted energy diagrams.Results and DiscussionThe goodness-of-fit indices for PDF fitting indicated that the log-normal PDF is the most suitable distribution to describe the FDC with a coefficient of determination of 0.99. The calculated average discharge (Q50) for the Gachsar and Siera stations was 2.34 and 7.68 m3s-1, respectively. These values are consistent with findings from previous studies. The results of the Manning equation calculations revealed that the flow velocity does not differ significantly between these stations (8% higher at Siera). The base flow depth at the Gachsar and Siera stations is less than 1 m. Therefore, as indicated in the literature review, axial flow (propeller) turbines are not suitable for installation in these rivers because they need to be fully submerged and require at least 1 m of depth. Overall, the use of wide and short turbines, such as Savonius turbines, is suggested in the Karaj River. The energy analysis results show that the maximum monthly theoretical energy at Gachsar and Siera equals 38,500 and 125,500 kWh, respectively. However, considering a turbine with a 1 m2 swept area and a power coefficient of 0.2, the maximum monthly extracted energy is limited to 940 and 1,142 kWh at these two stations.ConclusionThis study presents a fast method for the theoretical assessment of hydrokinetic power, which was applied to two hydrometry stations in the Karaj dam watershed. The results of HG calculations revealed that the base velocity (V90) of 1.34 and 1.49 m/s is present at the Gachsar and Siera stations, respectively. According to the available depths at these stations, the use of wide and short turbines such as Savonius turbines is suggested. Each individual Savonius turbine with a unit swept area at Gachsar and Siera is estimated to extract a maximum monthly energy of 940 and 1,142 kWh, respectively.
Precision Farming
B. Besharati; A. Jafari; H. Mousazadeh; H. Navid
Abstract
IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control ...
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IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control weeds, but due to the high cost are not economical. Electromagnetic waves transfer energy into weeds and finally destroy them. The effect of radiation on plant mutation, high consumption of energy, and human health are problems for this approach. Unlike other methods, electrical energy is an ideal and non-chemical method for weeds. This method applies high voltage to weeds, their roots, and soil so that electric currents pass through them, and the vaporization of the liquid content of weeds kills the weeds. To increase the severity of damage to weeds, the development of a feedback mechanism is required. The ultrasonic sensor measuring physical parameters like plant height is a simple method. Some complex sensing systems include optical sensors such as infrared, and machine vision that require high-speed processors and expensive equipment. In this project, as a simple method, the monitoring of the electrical current passing through weeds was used for developing the feedback mechanism and increasing electric damage to weeds.Materials and MethodsIn this study, the system consisted of a high-voltage device that generated a 15 kV AC voltage to kill weeds, as well as a feedback mechanism that included a sensor to measure the electric current on the input of the weed killer and identify the presence of weeds and their annihilation. All parts were installed on a robotic platform, and an application on a laptop was connected to it via an access point for navigation and data reception. The system was tested in a greenhouse lab with various weeds. Initially, a test was performed to investigate the effect of high voltage on the weeds and establish relationships between the electric currents passing through weeds and their presence (before and after annihilation). During the test, the system was guided along a path and applied high voltage to kill the weeds. The feedback mechanism was then calibrated based on the extracted data on electric current relations. This allowed the system to detect weeds and their annihilation, enabling it to move to the next target once a weed had been eliminated. After calibration, a comparative test was conducted to evaluate the weed-killing efficiency of the two methods (with and without the feedback mechanism), and the results were analyzed using a t-test with p ≤ 0.01.Results and DiscussionThe observations indicated that the input electric current on the weed killer was dependent on the electric current passing through weeds. When the high-voltage electrode touched a weed, the electric current passed through it increased, and simultaneously, the high electrical energy destroyed the weed. After the removal of the weed, the electric current rapidly decreased. The average energy consumption per weed plant was estimated to be 250 joules, which can be compared with other methods. The final test comparing the use and non-use of the feedback mechanism revealed significant differences (P < 0.01) between the results obtained with and without the mechanism, demonstrating that the feedback mechanism increased the efficiency of weed annihilation. The sensing system used in the developed feedback mechanism is a simple method that is affected by the electrical resistivity of weeds. As such, it did not mistakenly detect other objects as weeds, unlike an ultrasonic mechanism. Based on these results, monitoring the electrical current passing through weeds proved to be a suitable method for developing a feedback mechanism for the weed killer to identify the presence of weeds and their annihilation.ConclusionThe use of high voltage as a non-chemical and alternative method for weed control has shown promising results. The study revealed that measuring the electric current applied to the weed killer was an effective and straightforward approach to developing a feedback mechanism. This mechanism aids in identifying the presence of weeds and ensuring their elimination by intensifying the damage inflicted on them through the application of high electrical energy. To further enhance the efficiency and speed of weed control, future research should consider integrating an automatic guidance mechanism with the weed killer.
Design and Construction
S. Naderi Parizi; R. Alimardani; M. Soleimani; H. Mousazadeh
Abstract
IntroductionActivated carbon has a wide range of applications as a porous material in the liquid or gas phase adsorption process. The physical process of activated carbon production is divided into two stages thermal decomposition and activation. In this study, only the activation stage has been studied ...
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IntroductionActivated carbon has a wide range of applications as a porous material in the liquid or gas phase adsorption process. The physical process of activated carbon production is divided into two stages thermal decomposition and activation. In this study, only the activation stage has been studied because it is very important in the properties of activated carbon being produced.The production of activated carbon from horticultural waste not only leads to cheap production and supply of many industrial and environmental necessities but also reduces the amount of the produced solid waste. Iran produces about 94,000 tons of pistachio husk annually, which is a good raw material for the production of activated carbon. The profitability index of activated carbon production in Iran is equal to 3.63, which in the case of export, the profitability index will be tripled.Studies have shown that temperature, period, and activation gas flow are the key factors affecting burn-off and iodine number during activated carbon production. Among the various activators tested, steam was found to be the most efficient, with the fastest activation time. For pistachio crops, the minimum iodine number required for economic efficiency is 600 mg g-1, while the highest specific surface area according to the BET test is 1062.2 m2 g-1.Materials and MethodsA Mannesmann tube made of 10 mm thick steel was used to construct the rotating reactor. To minimize heat loss during operation, the kiln body was insulated with a ceramic blanket capable of withstanding temperatures up to 1400°C. The kiln had a length and diameter of 190 cm and 48 cm, respectively, and operated at a temperature of 600°C, requiring approximately 25 kWh of energy for heating. CATIA V5 R21 software was employed to design the device, while ANSYS R20 software was used for thermal and mechanical analysis. The rotary reactor was identified as a critical component due to the high levels of thermal and mechanical stress it experiences. To address these issues, a thermal and fluid analysis was conducted, followed by a mechanical analysis using the results from the prior step. Subsequently, experimental tests were performed on the actual model, and the results were analyzed using statistical methods, including the T-student test in IBM SPSS software.The central heating unit and its surroundings were modeled using ANSYS CFX to obtain valuable information on fluid velocity, radiant properties, and heat transfer within the kiln and surrounding area at an operating temperature of 650°C. The analysis revealed uniform steam flow velocity between the kiln and the heating unit. To accommodate longitudinal expansion resulting from heat stress, taller rollers were employed to allow freedom of movement in that direction, while the lateral movement was unrestricted. This arrangement allows the reactor length to increase under varying temperatures. The reactor's end was designed with grooves and pressure plates, incorporating abrasion and compression plates made from refractory fibers to effectively seal the device. Furthermore, telescopic movement of the parts compensates for expansion effects.Results and DiscussionThe operating temperature of the system was gradually increased to reduce thermal stresses in the reactor shell. This led to a maximum increment in a longitudinal increase of 11.75 mm. Results from five sets of experimental tests and five software analyses demonstrated no significant differences between the experimental and analytical results at a significance level of 5%. Based on the thermal contour analysis, the thickness of the insulation layer was determined to be 5 cm. To control the operating temperature of the device, two methods were employed: adjusting the flame length of the burner and using different types of exhaust outlets. These measures effectively reduced thermal stress on the device.ConclusionThermal and mechanical analysis were useful methods for predicting heat distribution, thermal stresses, and potential dimensional changes in the activated carbon reactor. To compensate for possible alterations in the reactor's length and diameter, abrasive plates and friction washers were implemented. Careful control of fuel input to the burner and regulation of exhaust gas flow helped effectively reduce thermal stresses on the device.
H. Abdolmaleki; A. Jafari; H. Mousazadeh; A. Hajiahmad
Abstract
IntroductionAs the world population grows up, the quantity and quality of human food must be improved. The production yield of marine aquaculture and farming of aquatic organisms, as a valuable source of food, will be increased. Regular and online monitoring of the physical, chemical, and biological ...
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IntroductionAs the world population grows up, the quantity and quality of human food must be improved. The production yield of marine aquaculture and farming of aquatic organisms, as a valuable source of food, will be increased. Regular and online monitoring of the physical, chemical, and biological qualities of water and environmental parameters in such these controlled environments can be achieved by using advanced world technologies, such as autonomous boats. In this study, simulation of an autonomous boat has been done to help better understanding and control of this type of vessel in various environments such as dams, ports, rivers, aquatic ecosystems, and aquaculture. Hence, the main goal of this paper is to simulate and evaluate the guidance and navigation system of an autonomous boat based on the Fourth order of Runge-Kutta for determining the changes of water quality indices in a fish farming ponds.Materials and Methods In order to achieve the main goal of this study, an autonomous boat was designed and built. This boat as a general-purpose robotic trimaran boat has dimensions of 110 cm x 37 cm x40 cm and is made of Plexiglas 2 mm thick. Maximum forward speed of the boat is 125 cm s-1 (at 6850 rpm of brushless motors) and the turning radius is less than 61 cm. The environmental data can be transferred using Internet of Things (IOT), smartphones, SMS, and mini PC. The position and heading of the boat are determined using GPS and IMU data. The hydrodynamic and aerodynamic forces, moments, and coefficients of the boat model are determined and then applied in the mathematical simulation as the input of classic Runge-Kutta (RK4). The performance of the robotic boat navigational and control systems evaluated in a rectangular track with a length of 20 m and a width of 15 m in a fish farming pond in Karaj and 4 waypoints. The local coordinates of four corner of the mentioned rectangular in the pond was (0, 0), (0, 20), (15, 20), and (15, 0). The purpose of control system was to conduct the actuators in such way that boat be able to go to the next point. When the boat reaches the target distance of one m of the desired point, the next point will be introduced as a new target. The set point of boat speed was 0.4 m s-1 and zero state vector was [0, 0, 0, 0, 0, 0]. Results and DiscussionThe maximum error of position and heading of the autonomous boat is 135 cm and 11 degrees, respectively. Also, in the speed PID controller test (40 cm s-1), the average and standard deviation of the speed calculated as 40 cm s-1 and 2 cm s-1, respectively. Maximum difference between the heading obtained from the Kalman filter and received from the GPS is 11 degrees. In some situations that high precision of heading angle is not required, the GPS data can provide such accuracy of the heading. Among the variables of longitudinal, latitude, time to reach the target area, yaw rate, heading, and forward speed the minimum and maximum of percentage error are related to forward speed and yaw rate, respectively. These values show good performance of the simulated model and PID controllers.Conclusion In this study, motion simulation and evaluation of a robotic boat was carried out using a model boat and MATLAB software. The mathematical model simulated the real boat behavior correctly and the boat can be used safely in fish farming ponds to monitor environmental conditions and water quality.
Design and Construction
S. I. Saedi; R. Alimardani; H. Mousazadeh; R. Salehi
Abstract
Introduction Global increase in the food demand and challenges regarding the water, energy and fertile soil has made it clear that current strategies are no longer efficient for maintaining food safety. Therefore, attention to novel, science-based, seasonal and climate-independent farming methods which ...
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Introduction Global increase in the food demand and challenges regarding the water, energy and fertile soil has made it clear that current strategies are no longer efficient for maintaining food safety. Therefore, attention to novel, science-based, seasonal and climate-independent farming methods which could result in the higher crop quality and quantity is an inescapable decision. Among all agricultural practices and technologies, intensive culture and hydroponic methods in controlled environments play an important role. Materials and Methods To address these challenges, an indoor solar-powered auto-irrigate rotary cropping system (SARCS) was designed and implemented. Arrangement of plants in the surface area of an open-ended drum makes it possible to use space rather than area to maximize the acreage. An embedded fuzzy control system managed the irrigation process based on the plant water requirement predictions, and photovoltaic panels (PVs) was responsible for system electrical energy provision. The drum rotates around its horizontal axis where LED lamps are positioned to provide light to plants. This structure causes the plants gain the light illumination efficiently while getting access to water accumulated in the secondary tank positioned beneath the drum. Fertigation fuzzy control was based on plant evapotranspiration (ET) estimations with temperature, humidity, and light as its inputs. The instantaneous estimated ETs which were measures for root substrate moisture were summed until reaching its critical value which is equivalent to plant readily available water (RAW). This tends to trigger a pump submerged in a primary tank to fill the secondary one up to a predefined height ruled by a level sensor. The solar energy system consisted of PVs, MPPT, inverter, and battery bank. The SARCS evaluation procedure included two valid lettuce cultivation in grow bags filled with the same proportions of perlite and coco peat as a root substrate. The first cultivation used water level sensors to rule the irrigation process (non-fuzzy) while the second one (fuzzy) were governed by fertigation cycle fuzzy control. Results and Discussion The results showed that employing these two modes increased lettuce planting density to about 12 times in the field culture and 4 times in the greenhouse. The energy consumption evaluation revealed that in fuzzy and non-fuzzy approaches the same amounts of energy were needed. But in fuzzy mode the amount of energy consumed per kilogram of marketable lettuce was 74.33% less than in non-fuzzy mode. Fuzzy and non-fuzzy modes utilized 58.81% and 48.41% of the total energy requirements from PVs, respectively. It was calculated that the solar system is able to supply 51.16 % of SARCS total annual energy requirements in Karaj Province. The results of water consumption evaluations revealed that the fuzzy approach could cut the needed water to 24%, and improved the marketable product to 74.47%. For producing one kilogram dry and fresh biomass, fuzzy mode used 50.41% and 55.53% less water than non-fuzzy, respectively. Furthermore, one kilogram marketable product in fuzzy approach needed 56.46% less water than in non-fuzzy. The averaged water needed for growing one lettuce plant in non-fuzzy and fuzzy modes were 15 times less than in field lettuce. The comparison of growth parameters of harvested lettuce in the two studied approaches revealed that fuzzy mode would have significantly higher results in all parameters. Conclusion The results suggested that the development of intensive culture strategies would play an important role in the sustainable agricultural production and food safety. Also, the solar energy utilization in farming practices could save fossil resources and decrease air pollutions. Finally, purposeful irrigation approaches which are based on plant water requirement predictions can significantly reduce the total water consumption and improve products quality. This strategy, therefore can be introduced to other farming practices such as field and greenhouse methods.
S. I. Saedi; R. Alimardani; H. Mousazadeh
Abstract
Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable ...
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Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable and clean energy which can be used in numerous applications to get rid of environmental impacts of non-renewable fossil fuels. Therefore, easy and fast estimation of daily global solar radiation would play an effective role is these affairs. Materials and Methods This study aimed at predicting the daily global solar radiation by means of artificial neural network (ANN) method, based on easy-to-gain weather data i.e. daily mean, minimum and maximum temperatures. Having a variety of climates with long-term valid weather data, Washington State, located at the northwestern part of USA was chosen for this purpose. It has a total number of 19 weather stations to cover all the State climates. First, a station with the largest number of valid historical weather data (Lind) was chosen to develop, validate, and test different ANN models. Three training algorithms i.e. Levenberg – Marquardt (LM), Scaled Conjugate Gradient (SCG), and Bayesian regularization (BR) were tested in one and two hidden layer networks each with up to 20 neurons to derive six best architectures. R, RMSE, MAPE, and scatter plots were considered to evaluate each network in all steps. In order to investigate the generalizability of the best six models, they were tested in other Washington State weather stations. The most accurate and general models was evaluated in an Iran sample weather station which was chosen to be Mashhad. Results and Discussion The variation of MSE for the three training functions in one hidden layer models for Lind station indicated that SCG converged weights and biases in shorter time than LM, and LM did that faster than BR. It means that SCG provided the fastest performance. However, the story for accuracies was different i.e. the BR, LM, and SCG algorithms provided the most accurate performances, respectively, both among one or two hidden layers. According to the evaluation criteria, six most accurate derived models out of 1260 tested ones for Lind station was 3-14-1 and 3-11-19-1 with LM, 3-20-1 and 3-20-19-1 with BR, and 3-9-1 and 3-20-17-1 with SCG training algorithm, and 3-20-19-1 topology with BR showed the best performance out of all architectures. Results of the evaluation of the six accurate models in the remaining 18 stations of Washington State proved that regardless of the climate, in each weather station, BR with its inherent automatic regularization, provided the most accurate models (0.87 67.41 %), and then SCG (0.90>R>0.83, 3.91>RMSEMAPE > 77.28 %). Therefore, the Bayesian neural networks, which showed the best performance among all Washington State weather stations, were evaluated for Mashhad station, as an Iran sample climate. The results proved the ability of the said networks for this climate (R=0.82, RMSE=3.92 MJm-2, MAPE=79.92%). Conclusion The results indicated that the Bayesian neural networks are capable of predicting global solar radiation with minimum inputs in different climates. This was concluded both in Washington State weather stations, which has a variety of climates, and also in Mashhad as an Iran sample weather station. These models would eliminate the need for complex climate-dependent mathematical relations or other models which are mostly dependent on many inputs. So, this algorithm would be a good means first in weather forecast practices, also in the design and development of solar assisted equipment, as well as in managerial practices in agriculture when monitoring crop solar-dependent processes like photosynthesis and evapotranspiration.
N. Tarabi; H. Mousazadeh; A. Jafari; J. Taghizadeh Tameh
Abstract
Introduction
Calotropis is an evergreen and perennial shrub that grows in tropical areas of Iran and has valuable fibers in the bark of its stem. Fibers obtained from Calotropis stem have 75% cellulose. Tensile strength and modulus of the fibers is more than Cotton and elongation of the fibers is higher ...
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Introduction
Calotropis is an evergreen and perennial shrub that grows in tropical areas of Iran and has valuable fibers in the bark of its stem. Fibers obtained from Calotropis stem have 75% cellulose. Tensile strength and modulus of the fibers is more than Cotton and elongation of the fibers is higher than Linen fibers. Calotropis stem fibers are researched for paper pulp applications and also has been evaluated for some applications such as their fiber characteristics for cloth making.
However, there are no more studies on Calotropis bark fibers and very limited information is available about fibers extraction methods. In traditional methods of extraction, the stems were wetted for a period of 8 days and then the fibers were separated manually. In another method that was common in south region of Iran, the dried stems were threshed by hand and the fibers were separated from the crushed stems manually. These methods need cumbersome works, and require long times for processing. Therefore the aim of this study is to develop an extraction method for Calotropis bark fibers based on mechanical ways. Investigation of some importance characteristics, e.g. moisture content and rotational speed on the performance of extraction machine is another objective of this study.
Materials and Methods
Considering that the fibers are in the bark of the stems, extracting principle is based on bark separation by pushing of stems against some pairs of sharp blades. Since diameter of stems is variable, it is essential that the designed system to be capable of auto-adjusting for different diameters. So the stems were fed through the blades, via two serrated rollers. The roller, blade and other parts of a separated unit were tightened to a yoke, so when thick stems are inserted, the roller compresses the spring and moves up, as a result, the blade was pulled up. The Yoke was connected to the frame through two long screws. For complete debarking and fibers extraction, three separation units were arranged in series at the final design. For complete debarking from all sides, the second unit was attached while 90o rotated in relation to the first unit.
To evaluate the machine performance, the test specimens were provided from the south region of Iran, Kerman. Approximated length of test specimens was 150 cm. Firstly, petioles and leaves were removed at the nodes of the stems. Extraction efficiency of the machine was evaluated with three moisture contents (75% w.b., 65% w.b. and 55% w.b.) and six rotational speeds (30, 35, 40, 45, 50 and 50 rpm). Stems with a moisture content higher than 75% w.b. and lower than 55% w.b. were not suitable for fiber extraction by the machine. Because latex flows from the stem at moisture content of higher than 75% w.b. and also the bark was being stuck on the stem at moisture content of lower than 55% w.b. The stem feeding capacity was evaluated at different moisture content and speeds as well. In order to investigate the power consumption due to moisture content and rotational speed, the consumed power per stem mass unit was calculated at three moisture contents and three speeds (35, 45 and 55 rpm).
Analysis of variance (ANOVA) technique was used to evaluate effect of different speeds and moisture contents. The study was planned as factorial experiments based on a completely randomized design and each treatment was replicated five times.
Results and Discussion
Based on the analysis of variance for extraction efficiency at different three moisture contents and six rotational speeds, it is obtained that the effect of moisture contents (at P≤0.01) and rotational speeds (at P≤0.05) were significant on the extraction efficiency. Comparison extraction efficiency at six speeds and three moisture content levels showed that the maximum extracting efficiency occurs at rotational speed of 40 rpm with the moisture content of 75% w.b. The average efficiency in this case was 95% approximately. Extraction efficiency at moisture contents of 65 and 55 % w.b. were 78-90% and 60-82% respectively. As the moisture content decreased, the bark was being bonded and stuck on the stem so the fibers were torn while debarking. It is found that the effect of speeds on the capacity was not significant. Average stem feeding capacity into the machine at rotational speed of 45 rpm and at three moisture contents of 75% w.b., 65% w.b. and 55%w.b. were respectively 46, 37 and 28 kg hr-1.
The effect of moisture content and rotational speed on the consumed power per stem mass unit was significant at 0.01 probability level. However, the consumed power per mass unit increased with decrease in moisture content and increase in rotational speed. The average of maximum consumed power per unit mass at moisture contents of 75%, 65% and 55% w.b. were 1.46, 1.70 and 1.85w g-1, respectively. Also 1 kg fibers were obtained from 22kg stems at a moisture content of 75% w.b. Finally, it is concluded that the fiber length varied from 10 cm to 80 cm by the mechanical method.
Conclusions
In this study, a machine that would be capable to extract fibers from stems of Calotropis was developed. Comparison of extracting efficiency at six speed levels and three moisture contents indicated that the maximum extracting efficiency (95%) is at rotational speed of 40 rpm with the moisture content of 75% w.b. Average stem feeding capacity into the machine at three moisture contents of 75% w.b., 65% w.b. and 55% w.b. were 46, 37 and 28 kg hr-1, respectively. Results showed that consumed power per unit mass is increased when moisture decreased. Also 1 kg fiber was obtained by 22kg stems at moisture content of 75% w.b.
