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The harvested walnut has a relatively high moisture content of 30% compared with the safe storage moisture content of 8%. One of the common means of reducing the moisture content is by drying. For design of drying and other aeration systems for agricultural products including walnuts, the relationship between the drop in pressure and airflow velocity must be known. An airflow resistance apparatus was designed and manufatured to measure the airflow resistance of walnuts. This apparatus consisted of an air compressor, a rotameter, a cylindrical bin and an inclined U-tube manometer. The pressure, drops at airflow velocities of 0.085 to 0.55 (m3/s)/m2, were measured at a constant depth of the nuts. Airflow resistance equations were fitted to the measured data. The results showed that, by increasing airflow rates, an increased drop in pressure was achieved through out walnut column. To study the effect of walnut moisture content on airflow resistance, the drop in pressure was measured at different moisture contents levels of 8.6%, 15.5%, 21.3% and 27%. Results indicated that the drop in pressure decreased with increasing moisture content, especially for high airflow rates.

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Vibration generated by vehicles during road transport has an important effect on the agricultural products damage process, particularly vegetable and fruit. Modulus of elasticity is one of the most important mechanical properties of fruits and its variation can be described as one of the damage criteria during transportation. This research was conducted to evaluate the effects of vibration parameters (frequency, acceleration and duration) and fruit position in the bin, on watermelon damage. At first, vibration frequency and acceleration were measured on the different points of a truck-bed in order to obtain the range of vibration frequency and acceleration distribution during transportation. Second, a laboratory vibrator was used to obtain some factors influencing damage during watermelons transportation. The damage was described as a difference in the modulus of elasticity of the watermelon (flesh and hull) before and after the test. According to the results measured on the truck-bed, the vibration frequency mean values were 7.50 Hz and 13.0 Hz for 5-10 Hz and 10-15 Hz frequency intervals, respectively. Furthermore, vibration acceleration mean values were 0.30 g and 0.70 g for 0.25-0.50 g and 0.50-0.75 g intervals, respectively. Vibration frequency and acceleration mean values were used for vibration simulation. Vibration durations were 30 and 60 minutes and damage was measured for watermelons at the top, middle and bottom positions in the bin. Laboratory studies indicated that, vibration frequency, vibration acceleration, vibration duration, and fruit position, which were taken into consideration as controlled variable parameters, significantly affected the damage (P< 0.01). Damage to the watermelon flesh was higher than watermelon hull. Vibration with a frequency of 7.5 Hz, acceleration of 0.70 g, and duration of 60 minutes caused higher damage levels. Fruits located at the top of the bin showed more damage than those in middle and bottom positions (P< 0.05).

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To increase agricultural crops’ quality and to minimize losses in the final product and used energy during the drying process, major drying system parameters should be continuously controlled. Precise control of such parameters is attained by using automatic control systems. To optimize the overall dryer efficiency in a forced convective solar dryer, a controller was designed, constructed and evaluated. The dryer fan speed was chosen to be the controlled variable. Based upon the mathematical relations and a monitoring of the air inlet temperature to the collector, the air outlet temperature from the collector and the air outlet temperature from the drying chamber, the dryer efficiency was determined. Using the dryer control program the current and the optimized dryer efficiencies were calculated, compared and the fan speed changed accordingly to maintain the optimized efficiency. Experiments were carried out in three replications (in three days) with the results showing that the system was capable of controlling the fan speed to obtain the optimum efficiency. The dryer equipped with the designed control system worked with its highest efficiency throughout the day. Statistical analysis showed that the control system highly improved the dryer efficiency throughout its operation at a 1% probability level.

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The scope of the current investigation incorporates the entire process involved in design and development of a Shape Memory Alloy (SMA) actuated wing intended to fulfill morphing missions. At the design step, a two Degree-of-Freedom (DOF) mechanism is designed that is appropriate for morphing wing applications. The mechanism is developed in such a way that it can undergo different two DOF, i.e. gull and sweep, so that the wing can have maneuvers that are more efficient. Smart materials commonly are selected as the actuators due to their suitable thermo-mechanical characteristics. Shape Memory Alloy (SMA) actuators are capable of providing more efficient mechanisms in comparison to the conventional actuators due to their large force/stroke generation, smaller size with high capabilities in limited spaces, and lower weight. As SMA wires have nonlinear hysteresis behavior, their modeling should be implemented in a meticulous way. In this work, after proposing a two DOF morphing wing, an aerodynamic analysis of the whole wing for unmorphed and morphed wings is presented. The results show that the performance of the morphed wing in special flight regimes is improved.

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Due to the importance of autopilot systems in Micro Aerial Vehicles (MAVs), in this paper first, parametric guidance and control systems are designed, and then they are implemented on a simulated nonlinear six-DOF MAV. The control system is fuzzy-supervisory which its gains are optimized using genetic algorithm. For designing the guidance system, first, two-dimensional (constant height) path following algorithms of vector field and carrot-chasing are developed to 3D algorithms. Then, an optimized 3D fuzzy carrot-chasing guidance system is presented using a combination of the carrot-chasing geometric algorithm, fuzzy logic, and genetic algorithm. Augmentation of the fuzzy logic to the carrot-chasing algorithm, improves its performance significantly. In any autonomous flight maneuver, guidance and control systems affect the performance of the aircraft, simultaneously. So, using a similar control system, the performance of the 3D carrot-chasing algorithm, 3D vector field method, and the proposed 3D fuzzy carrot chasing algorithms are compared with and without applying the wind external disturbance. Results have shown significant superiority of the proposed 3D fuzzy carrot-chasing approach in the horizontal plane of motion and the 3D vector field method in the vertical plane of motion.

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Precise modeling has great importance in systems which are designed to work in transonic regions. The scope of current investigation includes numerical simulation of static aeroelastic phenomena of deformable structures in transonic regimes. Transonic flow brings lots of instabilities for aerodynamic systems. These instabilities bring nonlinearity in flow and structure solvers. Due to improvements in numerical methods and also enhancement in computing technologies, computational costs reduced and high-fidelity simulations are more applicable. Simulations in this paper are done in transonic flow (M = 0.96) on the benchmark wing AGARD 445.6. The procedure includes modal analysis, steady flow simulation and investigation of structure’s elastic behavior. At the first phase, the geometry model is validated by modal analysis with regards to comparison of first four natural frequencies and corresponding mode shapes. Then, a loose or staggered coupling is used to analyze aeroelastic behavior of the wing. In each simulation step, imposed pressure on the surfaces of the wing caused by transonic flow regime, deforms the structure. In the results section, a comparison between imposed pressure coefficients in each step with the existing literature and experimental results are reported. Also, pressure coefficients in each steps are calculated and reported. In this investigation by using multiple steps in one-way fluid-structure analysis, deformations are reduced in each step and as a result, the structure reached its static stability point.

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In this study, an intelligent diagnosis systems have been developed and applied for classifying six types of cooling radiator conditions by means of infrared thermal images; namely, radiator tube blockage, radiator fin blockage, loose connections between fins and tubes, radiator door failure, coolant leakage and normal. The proposed system is consisted of several subsequent procedures including thermal image acquisition, preprocessing, of images via two dimensional discrete wavelet transform (2D-DWT), feature extraction, feature selection, and classification. The 2D-DWT was implemented to decompose the thermal images. Subsequently, statistical texture features were extracted from the original and decomposed thermal images. Consequently, statistical texture features are extracted from the original and decomposed thermal images to develop ANFIS classifiers. In this paper, the significant and relevant features are selected based on genetic algorithm (GA) in order to enhance the performance of ANFIS classifier. For evaluating ANFIS classifier performance, the values of the confusion matrix, such as specificity, sensitivity, precision and accuracy were computed. The overall accuracy of the classifier was 94.11 %. The results demonstrated that this system can be employed satisfactorily as an intelligent condition monitoring and fault diagnosis for a class of cooling radiator.

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Rotor dynamics is known as the study of vibrational behavior in axially symmetric linear rotating structures. Devices such as engines, turbines, compressors and generators are located in this category. Study of vibrational behavior of these structures in different rotational velocities yields to recognition of critical points and preventing failures, especially high cycle fatigue. The case study of the present paper is a bladed disk used in the first stage of compressor of a gas turbine engine. The material of machined integrated bladed disk is aluminum alloy. The simulations have been done by ANSYS finite element software. By using the cyclic symmetry module of ANSYS the nodal diameter mode shapes of structure have been obtained. In the next step, experimental modal analysis test has been done by measuring 58 points on the bladed disk and the nodal diameters have been obtained experimentally. Finally, experimental and simulation results have been compared to each other. The novelty of this paper is the experimental procedure of obtaining nodal diameter of a bladed disk, which is so useful in verification of numerical simulation.

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Research on atmospheric boundary layers in wind farms is an important task. Especially, wind effect on wind turbines installed in mountainous area with complex terrain is complicated. In this research, the wake of a wind turbine and wind flow in complex terrain have studied with computational fluid dynamic (CFD) method in OpenFOAM software. Actuator-disk model with introducing forces, based on Blade Element Momentum Theory, on the disk are used. For simulation of wind turbine in wind farm, Reynolds averaged Navier Stokes equation with k-ɛ turbulence model has been used. Structured mesh was used for simulation domain. Also, main wind direction has been determined from North toward south considering wind rose of area. One of wind turbines is studied by detail. The numerical results show an extended wake effect around 5d (five times the rotor diameter). Wind speed deficit is 26% at this distance. Captured wind power from the simulation is close to real data. Also, wind regime has been studied and analyzed for different seasons. For November, December and January, the time period that wind blows in effective speed, is decreased less than %50 which is important in wind farm design and operation.

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This paper proposes a two phase strategy for proportional myoelectric control of Surena 3 humanoid robot which benefits from strength of two common myoelectric control methods, Pattern recognition base and simultaneous proportional control, for improving joint angle estimation. The aim of this research is to present a human-robot interface to create a mapping between electrical activities of muscles known as electromyogram (EMG) signals and kinematics of corresponding motion. First phase concerns with motion classification using Quadratic Discriminant Analysis (QDA) and Majority Voting (MV). Several common motion classification algorithms and feature vectors including time domain and frequency domain futures were investigated which lead to QDA and a superior feature vector with more than 97% classification accuracy. The second phase concerns with continuous angle estimation of shoulder joint motion classes using Time Delayed Artificial Neural Network (TDANN) with overall accuracy of 90% R2. QDA serves as a high level controller which decides between four TDANN correspond to each shoulder motion classes. QDA and TDANN models trained with several sets of offline data and were tested with online dataset. Online and offline data estimation accuracy and model robustness against disturbances show a significant improvement compared to similar methods in this field.