Bin Facility Research Articles

Working speed optimisation of the fully automated vegetable seedling transplanter

The purpose of this study was to determine the optimal operating speeds for a modified linkage cum hopper type planting unit that was used in low-speed automated vegetable transplanters. The transplanter utilizes a biodegradable seedling plug-tray feeding mechanism. The movement of the planter unit was simulated at different operating conditions using kinematic simulation software, and the resulting trajectories were compared based on factors such as plant spacing, soil intrusion area, soil intrusion perimeter, and horizontal displacement of the hopper in soil and found optimal result at 200, 250 and 300 mm/s and 40, 50 and 60 rpm combinations. The optimal operating speeds were then tested in a soil bin facility and found to perform well when transplanting pepper seedlings, with measured plant spacing that was close to the theoretical spacing. The planting depth in each case was not significantly different and the planting angle in different speed combinations was found to be significantly different, but within permissible limits. The mulch film damage was low for the selected optimised speed combinations. This study resulted in the determination of the optimal speeds for the transplanter, which can be used as a basis for optimising the other mechanisms within the transplanter.

ANALISIS PENGETAHUAN MITIGASI BANJIR PADA MASYARAKAT KABUPATEN BANJAR DENGAN PENDEKATAN METODE REGRESI LOGISTIK BINER

The largest flood condition in South Kalimantan Province occurred in 2021. The worst flooded area is Banjar Regency with 27,249 fatalities. Floods also affected the agriculture and fisheries sectors, causing agricultural land productivity to decrease to 87,598 tons from 2021 to 2020. A total of 1,838 aquaculture businesses suffered losses of up to 70 billion rupiah. The causes of flooding do not only come from natural factors but can come from other factors such as a lack of knowledge of flood mitigation, resulting in huge losses for the community. Previous research states that the factors that influence flood disaster mitigation are the level of education and income. This study aims to determine the factors that influence flood mitigation knowledge in Banjar Regency communities using the binary logistic regression method. The results of the study provide differences from previous studies, namely the environmental factor with category 1, the implementation of environmental management by the community affects flood mitigation knowledge with a p value (0.027) < α (0.05) and a value of W (2.2198) > Z_table (1.960). The odds ratio value shows that the probability of the Banjar Regency community having flood mitigation knowledge is 2.79 times greater than other variable categories. The model explains an influence of 31.6% with an AIC value of 125. The respondents flood mitigation knowledge in managing the environment includes all types and stages of flood disaster mitigation related to local wisdom in the respondents location, namely several terms such as "Apar-Apar, Jukung Terpal, Galangan, Kelambu Kolam". There are still some things that need to be maximized for flood mitigation knowledge, namely the formation of disaster resilient villages in Martapura City, East and West Sub-districts. Dissemination of information on climate-smart agriculture training to farmers. Realization of temporary waste bin facilities in Banjar Regency.

A Study of the Energy Component of X-Ray Radiation from an X-Pinch Hot Spot at the BIN Facility

—A technique for studying the spatial structure of hybrid X-pinch plasma objects in the X-ray range is described, and main experimental results are presented. The spectral characteristics of X-ray sources of plasma objects have been measured. The investigations have been carried out using thermoluminescent detectors based on lithium fluorides LiF(Mg, Ti).

Compliance on existing WASH facilities in community clinics of Bangladesh: A comparative study

Provisions of water sanitation and hygiene (WASH) facilities are essential to make accessible and sustainable through Community Clinics (CCs) to control infection in primary health care service. However, there is scarcity of literature to observe the scenario. This cross-sectional study with mix-method approach conducted a comparative analysis with a focus on compliance with WASH facilities between two categories of CCs in Meherpur and Kustia District in Bangladesh. There were total 420 respondents out of which 400 were selected purposively from the 20 renovated and non-renovated CCs for quantitative approach and 20 respondents for qualitative approach. Data were collected using face-to-face interview method. The study revealed that all of the renovated CCs had safe drinking water source, functioning toilet, hand washing and dust bin facilities except for a few cases with technical problem in water supply. But the reverse scenario was observed in non-renovated CCs. Compliance on WASH facilities in renovated CCs was two times higher than the non-renovated CCs. Clients aged ≤40 years (AOR = 0.41, renovated CCs), and married (AOR = 4.03, non-renovated CCs) did not comply the use of safe drinking water in CCs. Noncompliance of toilet use (AOR = 12.15, renovated CCs and AOR = 8.96, non-renovated CCs) and hand washing facility use (AOR = 8.46, renovated CCs and AOR = 16.8, non-renovated CCs) significantly found higher among respondents who had no formal education. Non-renovated CCs need to develop their WASH facilities as well as ensure maintenance whereas the renovated CCs need dedicated human resource as well as effective policies to maintain the sustainability.

Prediction of energy dissipation of off-road vehicles using smoothed-particle hydrodynamics techniques

This paper studies the energy dissipated during experimental and simulated procedures for the pressure-sinkage and shear-strength test. These tests are performed using a clayey-loam soil and modelled as smoothed-particle hydrodynamics (SPH) technique in Visual Environment's Pam-Crash software. The hydrodynamic elastic plastic material is used to define the equation of state for the clayey-loam soil. The soil is modelled at five different levels of compaction to represent multi-pass of a tyre over soil. The soil calibration is performed using the pressure-sinkage and direct shear-strength test and validated using experimental data from a soil bin facility. The energy dissipation is calculated using the soil sinkage values at every pass of wheel. Finally, the results of experimental and simulation dissipation energy are discussed and the effect of the tyre multi-pass on dissipated energy is investigated and presented. This research will further continue to model an agricultural FEA tyre over the clayey-loam soil to compute tyre performance and interaction characteristics.

Development of a Single Wheel Test Rig for Measuring Motion Resistance

Research on soil-wheel interaction is essential in studies of motion resistance of narrow wheels of agricultural machines. The aim of this research was to study the effects of soil moisture content and tyre inflation pressure on motion resistance of narrow wheels using a locally developed single wheel test rig. A single wheel Test Rig facility was developed at Federal University of Technology, Akure. It consists of a soil bin, carriage, single narrow wheel tester, trolley and drive system. An existing indoor soil bin facility was equipped with a soil bin which dimension was 9.76 m length x 1.98 m width x 0.92 m high. The single-wheel test facility was utilized to investigate the effect of tyre inflation pressure and vertical load on motion resistance of wheel. Two narrow wheels of 90/10-10 in width, IRC MB90 tyre were used as the test wheels on clay soil and were separately installed on a carriage that traversed the length of soil bin. Two inflation pressures of 274 kPa and 380 kPa and four levels of vertical load applied on wheel (i.e. 15, 20, 30, and 40 kg) were examined at two different soil moisture conditions (bulk density of 1.58 g/cm3 and 1.55 g/cm3, soil moisture content of 8% and 10% dry basis and soil penetration resistance of 1.02 MPa and 1.5 MPa). Exponential regression was obtained for the two wheels to check for linearity at different moisture content, R2 value for test wheel 1 with inflation pressure of 270 kPa at 8% moisture content was 0.9974 while that of inflation pressure of 380 kPa at 10% moisture content was 0.9952; also for test wheel two (2) R2 value was 0.9977 and 0.9914 at moisture content of 8% and 10% respectively, this shows for test wheel 1 with inflation pressure of 270 kPa at 8% moisture content showed more motion resistance compared to motion resistance of test wheel 1 at inflation pressure of 380 kPa and 10% moisture content, while for test wheel 2 with inflation pressure of 270 kPa showed low motion resistance at 8% motion content. The effect of different inflation pressures and vertical loads on the motion resistance of the narrow wheels has been investigated under different moisture content (8% and 10%). The contact area for all tests was in the range of 309-330 cm2, average contact pressure increased nearly linearly with increase in vertical load and increase in inflation pressure The research provides data that are relevant in the study of soil-wheel interaction.

Appraisal of numerical based finite element method to synthesise the wheel-obstacle collision dynamics using a single-wheel tester

As a very substantial aspect of vehicle dynamics and vibrational controlling, it is essential to ascertain the role of tyre-obstacle collision kinetics. Ride comfort assessments are pivotal in predicting the non-linear deformation, particularly when traversing large road obstacles. The present study focuses on the assessment of tyres travelling over different obstacles using a well-equipped soil bin facility and a single-wheel tester. The vertically and longitudinally oriented load cells were responsible for measuring the vertical and longitudinal force variations. Additionally, a finite element tyre model was developed specially for this purpose using explicit integration in ABAQUS ™. It was found that with the increase of the resonant amplitude of spindle force response as well as the tyre deformation becomes greater in both longitudinal and vertical directions. It was revealed that the new proposed model can serve as a functional alternative to classical modelling tools for the prediction of nonlinear wheel dynamics.

Prediction effect of farmyard manure, multiple passes and moisture content on clay soil compaction using adaptive neuro-fuzzy inference system

Soil compaction by machine traffic is a complex process with many interacting factors. The strength of adaptive neuro-fuzzy inference system (ANFIS) is the ability to handle linguistic concepts and find nonlinear relationships between inputs and outputs parameters. In this research, the effect of farmyard manure, the number of tire passes, soil moisture contents and three average depths on clay soil compaction is predicted using ANFIS and Regression. For the prediction of soil compaction, an agricultural tractor tire was used and the experiments were carried out in the controlled condition of soil bin facility utilizing a well-equipped single-wheel tester. To measure soil compaction, cylindrical cores in groups of three were inserted into the three different depths. Various member function ANFIS were tested to discover the supervised ANFIS-based models for the soil compaction. On the basis of statistical performance criteria of MAPE and R2, Gaussian curve built-in membership function (gaussmf) was found as a proper model. In addition, the ANFIS model with ‘Gaussian mf’ is recommended considering the higher prediction performance values of MAPE = 0.2957%. The regression analyses of ANFI and Multiple Linear Regression (MLR) revealed a high correlation with farmyard manure, the number of tire passes, soil moisture, and depth. Also, it showed a higher performance compared to the regression model for predicting soil compaction. Thus, it can be concluded that ANFIS-based methodology is a soft computing approach that provides excellent nonlinear systems such as soil compaction.

A mobile, in-situ soil bin test facility to investigate the performance of maresha plough

Ethiopia is well known for its use of an ard plough dating from antiquity – maresha – which fractures and disturbs the soil. However, hardly any notable progress of experimental research on this animal drawn tillage tool in the field has been made. The attendant problems in current practise are soil- maresha interaction, viz., uneven oxen strength along with different pace of walking, uncontrolled implement behaviour, and field conditions. Taking stock of the experimental research on animal drawn tillage tools in general, most of the documented works on the dynamics of the interaction between soil and animal drawn tillage tools tend to rely on trial-and-error based on factors mainly based on experience and cultural context. As such, no research tailored to systematically handle the link between maresha plough and soil bin experiments exists. To this aim, this study developed a mobile in-situ soil bin facility in which the system was calibrated, tested, and evaluated under outdoor experimental conditions, wherein online measurements of draught, speed, and depth of tillage were carried out. The insights and observations gained from the experimentation were discussed and reported in terms of smooth run, overload, cyclic forces, zero speed with minimal force, stoppage, speed measurement with no force, force measurement with no speed, and low speed with low force.

APPRAISAL OF TAKAGI–SUGENO TYPE NEURO-FUZZY NETWORK SYSTEM WITH A MODIFIED DIFFERENTIAL EVOLUTION METHOD TO PREDICT NONLINEAR WHEEL DYNAMICS CAUSED BY ROAD IRREGULARITIES

Wheel dynamics play a substantial role in traversing and controlling the vehicle, braking, ride comfort, steering, and maneuvering. The transient wheel dynamics are difficult to be ascertained in tire–obstacle contact condition. To this end, a single-wheel testing rig was utilized in a soil bin facility for provision of a controlled experimental medium. Differently manufactured obstacles (triangular and Gaussian shaped geometries) were employed at different obstacle heights, wheel loads, tire slippages and forward speeds to measure the forces induced at vertical and horizontal directions at tire–obstacle contact interface. A new Takagi–Sugeno type neuro-fuzzy network system with a modified Differential Evolution (DE) method was used to model wheel dynamics caused by road irregularities. DE is a robust optimization technique for complex and stochastic algorithms with ever expanding applications in real-world problems. It was revealed that the new proposed model can be served as a functional alternative to classical modeling tools for the prediction of nonlinear wheel dynamics.

The induced shock and impact force as affected by the obstacle geometric factors during tire-obstacle collision dynamics

The knowledge on vehicle stability, ride comfort and performance is critically significant on off-road vehicle traversing over irregular terrains. The subject of off-road vehicle analysis from the terrain–tire interaction perspective has always been from complex domains of engineering owing to the elasto-plastic behavior of deformable terrain and nonlinear vehicle dynamics. This paper is dedicated to synthesize the induced shock and impact force as affected by the obstacle geometric factors during tire-obstacle collision dynamics. To this end, various obstacle shapes were included at different depths to determine at which geometric configuration, the greatest and lowest impact forces are induced. Aiming this, the soil bin facility equipped with a single-wheel tester of Urmia University was adopted to carry out the needed experimental tests while the operational condition of the wheel traversing was absolutely controllable (i.e. slip, forward speed, wheel load, etc.). The developed model also was verified by the experimental data and the obtained results showed that the greatest impact force both at the longitudinally and vertically oriented directions were obtained by the triangular shaped obstacle at the greatest height while in contradictory to the expectations, the lowest values were obtained for the trapezoidal obstacle when compared with the Gaussian shaped obstacle. The findings will serve future studies as a functional source to develop improved vehicle designs to interact with differently shaped obstacles and various operational conditions for run-off-road vehicles traversing over irregularities.

Appraisal of artificial neural network-genetic algorithm based model for prediction of the power provided by the agricultural tractors

The knowledge of the available power provided by the driving wheel of agricultural tractors is required to gain a correct insight into the energy management of agricultural tractors. The design of the tractors is pivotal on the maximization of the traction efficiency and simultaneous minimization of energy dissipation. This paper spearheads the synthesis of the power provided by the agricultural tractors as affected by wheel load, slip and speed by use of the potential of a soil bin facility and a single-wheel test rig. The hybridized artificial neural network-genetic algorithm method was adopted to model the provided power of the driving wheel under the effect of the aforementioned tire parameters. The common drawback of the back-propagation algorithm known as the low speed of convergence and the possibility of being trapped in a local minimum was solved by the use of genetic algorithm. The mean square error equal to 0.02242 was obtained as the most optimal artificial neural network-genetic algorithm configuration using Levenberg–Marquardt training algorithm. Therefore, a 3-9-1 feed-forward with back propagation learning algorithm was selected as the modeling structure. The computed coefficient of determination for the training and test phases of the best artificial neural network-genetic algorithm model was obtained at 0.9696 and 0.9672, respectively. The present study spearheads the required power estimation for the driving wheels of off-road vehicles while the experimental test conduction in a controlled soil bin facility using single-wheel tester and adoption of soft computing tools are of the highlights and added values of the paper.

Experimental analysis of the dissipated energy through tire-obstacle collision dynamics

Wheeled vehicles are responsible for a substantial portion of dissipated energy while the share of tire-ground interface is among the most role playing elements in this regard. The vibrations and kinetics of a traversing wheel over an obstacle is a paradigm that can serve as a functional example for energy dissipation of wheeled vehicles. This paper communicates the analysis of the dissipated energy for a traveling wheel at collision time with obstacles while a controlled laboratory condition of the soil bin facility equipped with a single wheel-tester rig was utilized to carry out the experiments. The tests were conducted as affected by wheel load, obstacle height, obstacle geometry, slippage and speed. It was inferred that the increment of collision speed, obstacle height and tire slippage lead to the increase of the dissipated energy; however, the complexity lies in the contradictory effect of wheel load. This can be attributed to the nonlinear wheel dynamics and the vibration attenuation process. It has to be emphasized that the outcome of this study would serve as a functional catalyst for the extensive researches concerned with the machine design industry and the heavy vehicle trafficking management.

A comparative study between artificial neural networks and support vector regression for modeling of the dissipated energy through tire-obstacle collision dynamics

Energy dissipation control has long been synthesized addressing the trafficking of wheeled vehicles. Wheel-obstacle collision has attracted the studies more on ride comfort, stability, maneuvering, and suspension purposes. This paper communicates, for the first time, the energy dissipation analysis through tire-obstacle collision that frequently occurs for the wheeled vehicles particularly those of off-road vehicles. To this aim, a soil bin facility equipped with a single wheel-tester is employed considering input parameters of wheel load, speed, slippage, and obstacle height each at three different levels. In the next step, the potential of classic artificial neural networks was appraised against support vector regression with the two kernels of radial basis function and polynomial function. On account of performance metrics, it was revealed that radial basis function based support vector regression is outperforming the other tested methods for the prediction of dissipated energy through tire-obstacle collision dynamics. The details are documented in the paper.

X-ray absorption spectroscopy on the basis of hybrid X-pinch radiation

Results of experiments on X-ray absorption spectroscopy carried out at the BIN (270 kA, 100 ns) and XP (450 kA, 45 ns) facilities are presented. Continuum radiation of a Mo hybrid X-pinch was used as probing radiation, against which absorption lines of the plasma of exploded Al wires placed in the return current circuit of a hybrid X-pinch, as well as in a two- and four-wire array, were observed. The experiments have demonstrated that the radiation of a hybrid X-pinch hot spot can be used as probing radiation for X-ray absorption spectroscopy and that, in many parameters, such a source surpasses those on the basis of laser-produced plasma. The plasma parameters in arrays made of two and four Al wires were studied experimentally.

Relationships among the contact patch length and width, the tire deflection and the rolling resistance of a free-running wheel in a soil bin facility

Qualitative and quantitative analysis of contact patch length-rolling resistance, contact patch width-rolling resistance and tire deflection-rolling resistance at different wheel load and inflation pressure levels is presented. The experiments were planned in a randomized block design and were conducted in the controlled conditions provided by a soil bin environment utilizing a well-equipped single wheel-tester of Urmia University, Iran. The image processing technique was used for determination of the contact patch length and contact patch width. Analysis of covariance was used to evaluate the correlations. The highest values of contact length and width and tire deflection occurred at the highest wheel load and lowest tire inflation pressure. Contact patch width is a polynomial (order 2) function of wheel load while there is a linear relationship between tire contact length and wheel load as well as between tire deflection and wheel load. Correlations were developed for the evaluation of contact patch length-rolling resistance, contact patch width-rolling resistance and tire deflection-rolling resistance. It is concluded that the variables studied have a significant effect on rolling resistance.

Synthesis of the Resultant Force Position on a Radial Ply Tire of Off-Road Vehicle with a Comparative Trend Between Some Soft Computing Techniques

To obtain a qualitative understanding of tractive performance parameters, ride comfort, vibration control and the design of an off-road vehicle suspension system, it is essential to find the resultant force position on the wheel. To this aim, a soil bin facility assisted with a single-wheel tester was used for the synthesis of the objective parameter. Four levels of slip were induced to the wheel along with three levels of velocity and two wheel loads. The stochastic characteristic of soil---wheel interactions promoted the authors to apply two promising artificial intelligence approaches of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) and compare the results with the statistical approach of multiple linear regression (MLR). Various structures of ANN and ANFIS tools were constructed to obtain the best representations. Two statistical performance criteria of mean squared error (MSE) and coefficient of determination $$(R^{2})$$(R2) were employed to assess the potential of the constructed models. In view of the employed criteria, it was divulged that the supervised ANN outperformed the ANFIS model with MSE and $$R^{2}$$R2 values of 0.02615 and 0.93628, respectfully, where ANFIS model yielded MSE and $$R^{2}$$R2 values equal to 0.0439 and 0.8494, respectfully.

Evaluating the effect of tire parameters on required drawbar pull energy model using adaptive neuro-fuzzy inference system

Determination of the required energy for drawbar pull of agricultural tractors plays a significant role in the characterization of the quality of tractors during different operations. Assessment of the effect of some tire parameters on drawbar pull energy was performed utilizing a single-wheel tester in a soil bin facility. To this aim, the potential of a global searching soft computing approach (i.e. adaptive neuro-fuzzy inference system) with various membership functions was evaluated. The tire parameters of velocity at three levels of 0.8, 1 and 1.2 m/s, wheel load at three levels of 2, 3 and 4 kN and slippage at three levels of 8, 12 and 15% were applied to single-wheel tester while four installed load cells were responsible for the measurement of drawbar pull. It was concluded that drawbar pull energy is a direct function of wheel load, velocity and slippage. Hence, the greatest value of 1.056 kJ corresponded to the wheel load of kN, slippage of 15% and velocity of 1.2 m/s. The outperforming model yielded mean square error and coefficient of determination values of 0.00236 and 0.995, respectively.

On-The-Move Monitoring of Tire Rut Depth on Deformable Soil Using an Instrumented Inclinometer

Abstract. This study examined online measurement of tire-induced rut depth on a soft soil using an instrumented inclinometer. The experiments were carried out in a soil bin facility equipped with a single-wheel tester. Three levels of wheel load (2, 3, and 4 kN), velocity (0.4, 0.8, and 1.2 m s -1 ), and slippage (8%, 10%, and 15%) were considered for implementation of the tests. The experiments were planned as a complete randomized block design with three replicates on clay loam soil. The potential of the instrumented inclinometer for online monitoring of the imposed rut depth was assessed when the obtained data were statistically analyzed at the 1% significance level. The results showed that increase in wheel load as well as slippage led to increased rut depth (p

Multi-criteria optimization model to investigate the energy waste of off-road vehicles utilizing soil bin facility

The main objective of the present study was to determine the energy use efficiency of soil-wheel interaction in a soil bin testing facility. Input parameters were velocity at three levels (i.e. 0.7, 1.4 and 2 m/s), tire inflation pressure at three levels (i.e. 100, 200 and 300 kPa) and wheel load at five levels (i.e. 1, 2, 3, 4, and 5 kN) where the output was the energy waste of soil-tire interface. The potential of nonparametric technique of DEA (data envelopment analysis) and hybrid statistical-mathematical modeling approach of RSM (response surface methodology) were assessed in the present investigation. Response surface contours were constructed to determine the optimum conditions for the objective parameter. The present investigation spearheads the practice of DEA and RSM approaches in the optimization of energy waste of off-road vehicles. The findings revealed that RSM with optimized value of 5.7175 J, which corresponds to wheel load of 1 kN, velocity of 0.7 m/s, and tire inflation pressure of 150 kPa, is achievable. Additionally, input-oriented option of DEA resulted in the mean efficiency of 0.4379. Moreover, contribution of each input factor for energy saving was assessed by DEA approach.