Moisture-dependent physical and mechanical properties of hawthorn (Crataegus aronia)

 In this study, some important physical and mechanical properties of the hawthorn and the effect of moisture on them were investigated.  The effect of moisture at two levels (64.01% and 70.1%, w.b.) on the geometric dimensions (length, width, thickness, arithmetic mean diameter, geometric mean diameter, degree of sphericity, surface area, projected area, criteria projected area, mass, volume and the apparent), true density, porosity, coefficient of static friction and coefficient of rolling on three levels (wood, glass and galvanized) and mechanical properties obtained by impact testing machine using a randomized factorial design was evaluated by software SPSS18.  Results indicate that moisture has an effect on the physical properties of the hawthorn.  The moisture content of 70.1% of all physical properties except the true density and porosity values​​ is greater than 64.01% moisture there.  Coefficient of static friction with increasing moisture increased and coefficient of rolling decreased.  Moisture has an effect on the mechanical properties of hawthorn also.  With increasing moisture, all the mechanical properties except dL in Fmax decreased (dL is changing the shape of the force and Fmax is the maximum force).   Keywords: hawthorn, physical properties, maximum force at impact, mechanical properties, moisture conten

Evaluation of the performance and emissions of a single cylinder diesel engine fueled by biodiesel and using EGR

In this study, the effect of using biodiesel – derived from waste cooking oil – and exhaust gas recirculation (EGR) on engine performance and emissions of a single cylinder 4-stroke engine has been investigated. Three engine speeds (1800, 2100 and 2400 rpm), three engine loads (25, 50 and 75 %), four biodiesel/diesel blend (B0, B5, B10 and B15) and four EGR rates (0, 10, 20 and 30 %) have been applied to the engine. The considered emissions of the engine, measured at exhaust, were , CO, CO2, HC and smoke. The considered performance parameters were engine power, exhaust gas temperature and brake specific fuel consumption. The results of the study show that the addition of the biodiesel to the diesel fuel increases emission of the engine. The highest decrease in emissions while using the biodiesel and EGR has been 63.76% with B10 fuel blend and 30% EGR rate. Therefore, it can be stated that, using EGR, the increase in emissions of the engine due to biodiesel can be reduced. The simultaneous usage of EGR and biodiesel reduced CO emission of the engine of 4.04, 12 and 1.73% for low, medium and high engine speed. The biodiesel decreased the HC emission of the engine and so it compensated the increase of HC due to EGR. The highest reduction in HC emission levels while using EGR and biodiesel simultaneously, has been 54.05%. It is noticeable that the total amount of the smoke emission levels while using EGR and biodiesel did not change considerably

Determination of physical and mechanical properties of Zucchini (summer squash)

Abstract: Several physical and mechanical properties of Zucchini from Kermanshah province of Iran were determined.  The physical and mechanical properties of the zucchini are necessary for the design of automatic equipment for harvesting, processing, transporting, sorting and separating of samples.  At the average moisture content of 94.65% w.b., average of mass, volume, dimensions (big, medium and small diameters), geometric mean diameter, projected area (big, medium and small area), criteria areas, arithmetic means diameter, sphericity, density and surface area were 80.81 g, 85 cm3, 111.7 mm, 34.58 mm, 33.87 mm, 51.74 mm, 3892.52 mm2, 3792.07 mm2, 1126.44 mm2, 2937.02 mm2, 60.05 mm, 45.49%, 0.96 g/cm3 and 8268.20 mm2, respectively, and ratio of weight of rind per weight of fruit was 0.25.  Mechanical properties that measured including elasticity modulus, maximum force which fruit can be supported, work which performed to this force under compression loading, deformation at maximum force and penetration force, their averages were found 0.73 GPa, 167 N, 762.82 N.mm, 8.81 mm and 1.26 N, respectively. Keywords: Zucchini, physical and mechanical properties, compression loading, penetration force

Prediction of lithium-ion battery temperature in different operating conditions equipped with passive battery thermal management system by artificial neural networks

Lithium-ion batteries generate an enormous amount of heat during constant operation or rapid charge and discharge, which can result in a substantial increase in temperature, affecting the battery performance, reducing its cycle life, and potentially posing a safety issue. As a result, phase change materials (PCMs) based battery thermal management system (BTMS) can be used to control temperature of the battery and improve its performance. Moreover, with the increasing usage of artificial intelligence in a variety of disciplines, it appears to be worthwhile to investigate artificial intelligence approaches to evaluate various types of battery thermal management systems. The main aim of this study is to develop an artificial neural network (ANN) model for prediction of lithium-ion battery temperature equipped with a BTMS. The inputs of the model are discharge rate (1,2 ,3 and 4C), PCM thicknesses (0, 3, 6, 9, and 12 mm), Time (s) and PCM (with and without paraffin/ graphene PCM composite). The output of the model is temperature of the battery (C). Totally, 2012 data points were used to train, validation and test the model. The results of the study revealed capability of ANN to predict battery temperature in various operating conditions of BTMS. The R2, MSE, MAD and MAPE of the model were 0.99, 0.0173, 3.84 and 0.331, respectively. The results of the study have approved suitability of the ANN to predict performance of the passive BTMS

Latent heat prediction of nano enhanced phase change material by ann method

Thermal characteristics of phase change material (PCM) are important in design and utilization of thermal energy storage or other applications. PCMs have great latent heat but suffer from low thermal conductivity. Then, in recent years, nano particles have been added to PCM to improve their thermophysical properties such as thermal conductivity. Effect of this nano particles on thermophysical properties of PCM has been a question and many experimental and numerical studies have been done to investigate them. Artificial intelligence-based approach can be a good candidate to predict thermophysical properties of nano enhance PCM (NEPCM). Then, in this study an artificial neural network (ANN) has been developed to predict the latent heat of the NEPCM. A comprehensive literature search was conducted to acquire thermal characteristics data from various NEPCM to train and test this artificial neural network model. Twenty different types of Nano particle and paraffin based PCMs were used in ANN development. The most important properties which are used as the input for the developed ANN model are NP size, density of NP, latent heat of PCM, density of PCM, concentration and latent heat of NEPCM in the range of 1–60 nm, 100–8960 kg/m3, 89.69–311 kJ/kg, 760 to 1520 kg/m3, 0.02–20 wt% and 60.72–338.6 kJ/kg, respectively. The output variable was latent heat of NEPCM. The result indicates that the ANN model can be applied to predict the latent heat of nano enhanced PCM satisfactory. The correlation coefficient of the created model was 0.97. This result shows ability of ANN to predict the latent heat of NEPCM

Mass modeling of caper (Capparis spinosa) with some engineering properties

Nomenclature M = fruit mass, g; V = fruit Volume, cm 3 ; Dg = geometric mean diameter, mm; S = surface area, mm 2 ; L = length of fruits, mm; W = width of fruit, mm; T = thickness of fruit, mm; PA1 = first projected area which perpendicular to L direction, mm 2 ; PA2 = second projected area which perpendicular to W direction, mm 2 ; PA3 = third projected area which perpendicular to T direction, mm 2 ; CPA = criteria projected area, mm 2 ; SD = standard deviation; b0, b1, b2 = curve fitting parameters; X = independent parameter. Abstract Introduction Horticultural crops used as food with a similar weight and uniform shape are in high demand in terms of marketing value. Objectives Therefore, an awareness of methods for grading fruits and vegetables based on weight is crucial. A part of this research was aimed at presenting some physical properties of caper. Methods In addition, in this study, the mass of caper was predicted using different physical characteristics in four models that include linear, quadratic, S-curve and power. Results According to the results, all properties considered in the current study were found to be statistically significant at the 1% probability level for the best and the worst models for prediction; the mass of caper was based on volume and second projected area of the caper with determination coefficients of 0.984 and 0.323, respectively. Conclusion Mass model based on first projected area from an economical standpoint is recommended. Lorestani AN, Jaliliantabar F, Gholami R (2012) Mass modeling of caper (Capparis spinosa) with some engineering properties. Quality Assurance and Safety of Crops & Foods, 4

Comparative analysis of exhaust gases from MF285 and U650 tractors under field conditions

Agricultural machinery is an important source of emission of air pollutant in rural locations.  This work deals with the effects of types of tractors and operation conditions on engine emission.  The values of some exhaust gases (HC, CO, CO2, O2 and NO) from two common tractors (MF285 and U650) at three situations (use of ditcher, plowing and cultivator) were evaluated in the West of IRAN (Kermanshah).  In addition, engine oil temperature at operation conditions was measured.  Also results showed the values of exhaust HC and O2 of MF285 are lower than U650, while the other exhausts gases (CO, CO2, and NO) of MF285 are higher than U650.  Value of NO emission increased as engine oil temperature increased.  All of exhaust gases except CO have a significant relationship with type of tractors, while all of measured gases have a significant relationship with installed instruments at 1%.   Keywords: environmental pollution, exhaust gases, tracto

Experimental investigation of temperature-dependent thermal stability of eicosane-based nano-enhanced phase change materials

Recently, studying phase change materials (PCMs) has brought many researchers' attentiveness to be applied in thermal energy storage and battery thermal management (BTM) applications. According to this fact that PCM requires to be thermally stable. Hence, the principal aim of this study is to analyze the thermal stability of PCMs composites by loading different mass fractions of CuO nano-particles. Results demonstrated that 0.5 wt% is the best value of additive nano-particle which showed a remarkable increment in thermal stability. Therefore, all the presented results indicate the importance of selecting an optimal PCM nanocomposite for various applications including NePCM-based thermal energy storage and BTM systems. The brand and model of the device used in this study are Hitachi and STA7000 respectively

Artificial neural network modeling and sensitivity analysis of performance and emissions in a compression ignition engine using biodiesel fuel

In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine

Biofuel combustion generated particles analysis

Soot emission or carbon black is considered as a major challenge recently. Generally, internal combustion engines have been introduced as the main source of these materials specially in urban areas. Different methods are proposed to control soot emission of diesel engine such as DPF (Diesel Particulate Filter) which is attached to the engine exhaust line and the microstructure and size of NPs were introduced as important parameters on its efficiency. In addition, biodiesel has become widely accepted as an appropriate substitution for diesel fuel, however, the using of biodiesel fuel may change the structural characteristics of soot emission. It is observed that biofuel has higher soot oxidative reactivity, and it is more reactive than diesel fuel, which is an advantage for DPF regeneration. Smaller size of particles in biodiesel fuel soot compared to diesel fuel is mentioned as a reason for this phenomenon. For instance, it is reported that the fractal dimension of micro algae, cotton seed, waste cooking oil, eucalyptus oil, tea tree oil and diesel fuel is 2.02, 1.97, 1.85, 1.75, 1.80, 1.73, 1.69 (nm) respectively. Filtration efficiency which is a crucial characteristic of the DPFs for biodiesel fuel and diesel fuel was found to be much different. These differences are attributed to the morphology of the produced soot of the fuel burning. The source of the biodiesel fuel is introduced as an impactful parameter on engine NPs morphology and size. For example, the primary diameter of the soot emission from the above fuels is 20.1, 14.8, 14.8, 15.5, 14.5, 15, 17.5 and 20.75 nm, respectively. The result of these study reveals that structure and morphology of soot emission come from biofuel combustion is different from diesel fuel and these properties should be investigated for any unique biofuel resource individually. However, the smaller size of the biofuel combustion generated soot is an advantage of these fuels to enhance their oxidation reactivity