scholarly journals DESIGN AND OPERATION PARAMETERS OPTIMIZATION OF 4SGMS-220 PLOUGH LAYER RESIDUAL FILM RECOVERY MACHINE

2021 ◽  
pp. 317-326
Author(s):  
Jianfei Xing ◽  
Xufeng Wang ◽  
Can Hu ◽  
Xiaowei He ◽  
Wensong Guo ◽  
...  
Keyword(s):  
Recovery Rate ◽  
Travel Speed ◽  
Optimal Operation ◽  
Parameters Optimization ◽  
Movement Trajectory ◽  
Residual Film ◽  
The Difference ◽  
Predicted Values ◽  
Primary Focus ◽  
Plough Layer

In view of the harm of residual film retention to soil environment in Xinjiang which even affected the germination of seeds and hindered the growth of crop roots in severe cases, in this paper, a 4SGMS-220 plough layer residual film recovery machine with a ground preparation device is designed. The main part of the machine is composed of a filming mechanism, a conveying mechanism, a soil crushing roller, and a film collecting box. The machine can achieve simultaneous film lifting, film stripping, collecting membrane and suppression operations. In this paper, primary focus is placed on the design of the filming mechanism, while the movement trajectory of the comb teeth and the filming condition are analysed in detail. In order to obtain the optimal combination of equipment and operating parameters, the equipment traveling speed, the filming device rotational speed, and the comb teeth depth are used as the influencing factors. Furthermore, the residual film recovery rate and impurity rates are employed as test indicators for three-factor three-level response surface experiment and optimization via Design-Expert software. The results indicate that optimal operation is achieved for the machine travel speed of 4.1 km/h, the filming device speed of 106 min-1, and the comb tooth soil penetration depth of 139.2 mm. The residual film recovery rate is equal to 74.32%, while the residual film impurity rate is equal to 7.11%. The difference between the test results and the predicted values is relatively small. Thus, it can be concluded that the optimized model is reliable.

Performance of Three DifferentSpades for Residual Plastic Film Recycling Machine

2020 ◽  
Vol 36 (2) ◽  
pp. 187-195
Author(s):  
Songmei Yang ◽  
Xuegeng Chen ◽  
Limin Yan ◽  
Deli Jiang
Keyword(s):  
Recovery Rate ◽  
Northwest China ◽  
Travel Speed ◽  
Soil Disturbance ◽  
Cotton Field ◽  
Plastic Film ◽  
Mechanical Recycling ◽  
The Sustainable Development ◽  
Residual Film ◽  
Draft Force

HighlightsEffectively separating the “white pollution” from agricultural soil.Three different spades for mechanical recycling residual film were tested.All spades had a similar draft requirement and soil disturbance trend.Spade A provided a higher residual film recovery rate.Abstract. Plastic film mulching cultivation provides important support for increasing the crop yield and ensuring food security, but residual plastic film pollution has become a prominent problem affecting the sustainable development of agriculture especially in northwest China. Recovery of thicker film by residual plastic film recycling machines may represent an effective way to solve this problem. In this study, a combined implement comprising three different spades (spades A, B, and C) were tested in a cotton field to compare their performance. All three types of spades were tested at a travel speed of 4.5 kmh-1 and a working depth of 40 mm. The residual plastic film recovery rate, soil draft force, soil disturbance characteristics (furrow profile), and cotton stubble uprooting were measured. Spade B had a higher draft force than the other spades. This trend was also observed for the soil disturbance area. Spades A and C produced stubble uprooting of approximately 5%, and spade B resulted in an approximately 5.7% larger degree of uprooting. Spade A had the largest recovery rate of residual film, while spade C had the smallest one. Overall, considering both recovery rate of residual film and draft force requirement, spade A showed better performance compared to spades B and C. Keywords: Draft force, Residual plastic film, Recovery rate, Soil disturbance, Spade.

Thermoelectric Power of the Liquid Sn—Te Alloy

1982 ◽  
Vol 37 (10) ◽  
pp. 1127-1131 ◽  
Author(s):  
D. H. Kurlat ◽  
M. Rosen
Keyword(s):  
Thermoelectric Power ◽  
Hard Sphere ◽  
Stoichiometric Composition ◽  
Band Model ◽  
Liquid Alloys ◽  
Sphere Approximation ◽  
The Difference ◽  
Predicted Values ◽  
Experimental Values ◽  
Two Band Model

The Seebeck coefficient (S) of Sni1-x- Tex liquid alloys was measured as a function of concentration and temperature. For 0 ≦ x <0.45 the behaviour is metallic; S values are small and negative, rising linearly with temperature. The predicted values of Ziman's theory when using the hard sphere approximation disagree with the experimental ones. The change in sign occurs for 0.45. For x = 0.5 (stoichiometric composition) the thermoelectric power decreases linearly with temperature. This fact is explained assuming a two-band model. For x ≧ 0.6 the liquid alloy becomes more semiconducting and presents a maximum in the isotherms of S for x = 0.65. For the excess tellurium concentration range we have calculated the difference EF - EV and γ/kB, assuming a S(1/T) law. The experimental values are compared with those of Dancy and Glazov.

TRUE AND APPARENT METABOLIZABLE ENERGY VALUES FOR POULTRY OF CANADIAN WHEATS AND OATS MEASURED BY BIOASSAY AND PREDICTED FROM PHYSICAL AND CHEMICAL DATA

1977 ◽  
Vol 57 (2) ◽  
pp. 365-374 ◽  
Author(s):  
I. R. SIBBALD ◽  
K. PRICE
Keyword(s):  
Metabolizable Energy ◽  
Chemical Data ◽  
Accuracy And Precision ◽  
Apparent Metabolizable Energy ◽  
The Difference ◽  
Variation Explained ◽  
Predicted Values ◽  
Naked Oats ◽  
Physical And Chemical ◽  
Better Than

Thirty samples of wheat and 28 samples of oats were assayed for true and apparent metabolizable energy (TME, AME). Within grains, the difference TME−AME increased with decreasing AME values; there is evidence that this trend is associated with reduced voluntary consumption of AME assay diets containing low energy grains. The TME and AME data were compared with ME values predicted from physical and chemical data describing the grains. Previously published prediction equations were tested and new equations were derived. Comparisons between predicted and observed data suggested that both the TME and AME values of wheat were predicted with insufficient accuracy and precision for practical use. Similar comparisons using the oat data showed high correlations between observed and predicted values, although the predictions were no more accurate than for wheat; however, when data describing four samples of naked oats were removed, the correlations were reduced substantially. Comparisons involving data for the hulled oats indicated that most equations were able to predict AME better than TME. Multiple regression analysis was used to identify those combinations of variables best able to predict TME data. No combination of variables was best for both wheat and oats. The combinations of variables used in published equations performed quite well. With four variables, the percentage of the TME variation explained was as high as 52 for wheat, 82 for oats and 64 for hulled oats. Predictions based on air-dry data are associated with higher correlations than those based on dry matter data, but the air-dry predictions are the less useful in practice. The reason for this is discussed.

scholarly journals Analysis and Development of Seawater Density Measurement Algorithms Using Arduino Uno and YL-69 Sensor

2020 ◽  
Vol 4 (5) ◽  
pp. 951-956
Author(s):  
Miftahul Walid ◽  
Hozairi ◽  
Madukil Makruf
Keyword(s):  
Sea Water ◽  
Density Measurement ◽  
Absolute Error ◽  
Error Level ◽  
Value Range ◽  
Density Values ◽  
The Mean ◽  
Arduino Uno ◽  
The Difference ◽  
Predicted Values

In this research, an analysis was carried out to develop a measuring instrument for seawater density in salt production using a microcontroller (Arduino Uno) and YL-69 sensor, this sensor was commonly used to measure soil moisture. The experimental method was used in this research to produce initial data in the form of resistance and seawater density values, then calculations are carried out using statistical methods to find equations and produce a constant variable that connects the resistance and seawater density values. The equation was used to compile the algorithm into Arduino Uno. As for the results of this research,  From six experiments conducted, two experiments produced the same sea water density value between the actual and the predicted, namely the 2nd and 5th experiments, while for other experiments there was a difference between the actual and predicted values, however, it was not too significant, the difference occurs between the value range 0 ~ 1, to determine the level of error, use the Mean Square Error (MSE) with an error level of = 0.5 and Mean Absolute Error (MAE) with an error level of = 0.6. The contribution of this research is an algorithm that can predict the density value (baume) based on the resistance value obtained from the YL 69 sensor.

Construction and Experimental Study of an Elevation Linear Fresnel Reflector

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
J. D. Nixon ◽  
P. A. Davies
Keyword(s):  
Heat Loss ◽  
Thermal Efficiency ◽  
Theoretical Models ◽  
Loss Coefficient ◽  
Heat Transfer Fluid ◽  
Stagnation Temperature ◽  
Model Predictions ◽  
The Difference ◽  
Predicted Values ◽  
Linear Fresnel Reflector

This paper outlines a novel elevation linear Fresnel reflector (ELFR) and presents and validates theoretical models defining its thermal performance. To validate the models, a series of experiments were carried out for receiver temperatures in the range of 30–100 °C to measure the heat loss coefficient, gain in heat transfer fluid (HTF) temperature, thermal efficiency, and stagnation temperature. The heat loss coefficient was underestimated due to the model exclusion of collector end heat losses. The measured HTF temperature gains were found to have a good correlation to the model predictions—less than a 5% difference. In comparison to model predictions for the thermal efficiency and stagnation temperature, measured values had a difference of −39% to +31% and 22–38%, respectively. The difference between the measured and predicted values was attributed to the low-temperature region for the experiments. It was concluded that the theoretical models are suitable for examining linear Fresnel reflector (LFR) systems and can be adopted by other researchers.

Numerical Study on Mechanism and Parameters Optimization of Temporary Plugging by Particles in Wellbore

2021 ◽  
pp. 1-16
Author(s):  
Tao Zhang ◽  
Ming Li ◽  
Jianchun Guo ◽  
Haoran Gou ◽  
Kefan Mu
Keyword(s):  
Particle Size ◽  
Numerical Study ◽  
Optimal Operation ◽  
Parameters Optimization ◽  
Mass Ratio ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Pump Rate ◽  
Single Well ◽  
Operation Parameters

Summary The temporary plugging by particles in the wellbore can open new perforation clusters and increase stimulated reservoir volume, but the temporary plugging process of particles is not clear. Therefore, in this paper, we take an ultradeep well in the Tarim Basin as the research object and establish a numerical model based on the coupled computational fluid dynamics-discrete element technology (CFD-DEM) approach, which accurately describes the movement process and mechanism of the temporary plugging particles in the wellbore. Furthermore, the influence of flow rate, concentration of injected particles, and the injected mass ratio of particle size on the temporary plugging effect were studied, respectively. In addition, based on the results of the orthogonal experimental analysis, we obtained the pump rate as the primary factor affecting the effect of temporary plugging, and we recommended the optimal operation parameters for temporary plugging by particles in the field: The pump rate is 2 m3/min, the concentration of the injected temporary plugging particles is 20%, and the ratio of the mass of the injected temporary plugging particles with particle size 1 to 5 mm to the mass of the temporary plugging particles with particle size 5 to 10 mm is 3:1. Finally, a single well that had implemented temporary plugging by particles was used to verify the recommended optimal temporary plugging operation parameters. The research results of this paper provide important guidance and suggestions for the design of temporary plugging schemes on the field.

scholarly journals 1 Assessing the predictive adequacy of simple and complex mathematical models

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 24-24
Author(s):  
Luis O Tedeschi
Keyword(s):  
Model Development ◽  
Predictive Ability ◽  
Random Variable ◽  
Coefficient Of Determination ◽  
Skewed Data ◽  
Future Performance ◽  
Evaluation Phase ◽  
The Difference ◽  
Predicted Values ◽  
Analytical Approaches

Abstract The establishment of credibility for a mathematical model’s (MM) predictive ability is an essential component for improving the MM because it stimulates the evolutionary thinking (i.e., the next generation of the model) of mental conceptualizations, assumptions, and boundaries of the MM. Its predictive adequacy is commonly assessed through its ability to precisely or accurately predict observed (real) values. The precision component measures how closely the model predicted values are of each other or whether a defined pattern of predictions exists. The accuracy component, on the other hand, measures how closely the average of the model predicted values are to the actual (true) average. Many statistics exist to determine precision and accuracy of MM such as mean bias, resistant coefficient of determination, coefficient of determination, modeling efficiency, concordance correlation coefficient (CCC), the mean square error of prediction, Kleijnen’s statistic (regression of the difference between predicted and observed on their sum), and Altman and Bland’s limits of agreement statistics among many more. However, for complex models that use skewed data or repeated data in which the data is not independent (e.g., multiple measurements on the same subject), simple statistics may not suffice. For instance, four methods to compute CCC exist (moment, variance components, U-statistics, and generalized estimating equations—GEE), but only the last two methods are resilient to lightly skewed data. Another type of complexity arises when meta-analytical approaches are used at the model development phase or the model evaluation phase. In general, meta-analytical approaches remove errors (i.e., variation) associated with random variables that are believed to be known. Under these circumstances, MM tends to overperform (i.e., they have greater predictive adequacy) and their future performance may be deceitful when trying to forecast at scenarios in which the random variable(s) is(are) indeterminable or unquantifiable.

General Correlation of Building Energy Use Via Hybrid Genetic Programming/Genetic Algorithm

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Mohammed A. Altarakma ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Programming ◽  
Closed Form ◽  
Hybrid Algorithm ◽  
Energy Use ◽  
Building Energy ◽  
Simulation Engine ◽  
Building Energy Use ◽  
The Difference ◽  
Predicted Values ◽  
Specific Number

A hybrid algorithm that combines genetic programming (GP) and genetic algorithms (GAs) that deduce a closed-form correlation of building energy use is presented. Throughout the evolution, the terms, functions, and form of the correlation are evolved via the genetic program. Whenever the fitness of the best correlation stagnates for a specific number of GP generations, the GA optimizes the real-valued coefficients of each correlation in the population. When the GA, in turn, stagnates, correlations with optimized coefficients and powers are passed back to the GP for further search. The hybrid algorithm is applied to the problem of predicting energy use of a U-shape building. More than 800 buildings with various foot-print areas, relative compactness (RC), window-to-wall ratio (WWR), and projection factor (PF) values were simulated using the VisualDOETM energy simulation engine. The algorithm tries to minimize the difference between simulated and predicted values by maximizing the R2 value. The algorithm was able to arrive at a closed-form correlation that combines the four building parameters, accurate to within 4%. The methodology can be easily used to model any type of data behavior in any engineering or nonengineering application.

scholarly journals Creativity Versus Innovativeness: Exploring the Differences between the Two Constructs May Lead to Greater Innovation in Large Firms

2015 ◽  
Vol 10 (11) ◽  
pp. 83 ◽  
Author(s):  
John Cocco ◽  
Majdi Quttainah
Keyword(s):  
Motivational Orientation ◽  
Individual Level ◽  
Sustained Competitive Advantage ◽  
Starting Point ◽  
Seeking Behavior ◽  
Study Support ◽  
The Difference ◽  
Primary Focus ◽  
The Individual ◽  
The Right

<p>Several individuals from top management seem to be confused about the difference between creativity and innovativeness. Amabile (1997) suggests that while innovation begins with creative ideas, creativity by individuals and teams is only a starting point for innovation. Individual creativity is necessary but not sufficient to yield breakthrough innovation in organizations. This can sometimes cause confusion in employee development efforts and actions taken by management. Companies often look for ways to hire and retain creative employees and at the same time they are also interested in establishing a creative environment for knowledge workers… but should creativity be the primary focus? These firms hope that creativity enhancing steps will eventually lead to greater innovation and therefore help it to achieve sustained competitive advantage. This paper attempts to demonstrate that there are potentially other dimensions beyond creativity related to innovativeness, which should be considered at the individual level in order to foster innovation in firms. Empirical results in this study support the idea that intrinsic motivational orientation, sociability and political astuteness are enhancers to employee innovativeness while perfection seeking behavior detracts employee innovativeness. These findings may serve to extend Amabile’s (1997) componential framework to center on the “innovativeness” construct versus creativity to help explain how firms need to hire, cultivate and retain the right talent.</p>

scholarly journals Modulus and Strength of Concretes with Alternative Materials

Materials ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 4378
Author(s):  
Ana Elisabete Paganelli Guimarães de Avila Jacintho ◽  
Ivanny Soares Gomes Cavaliere ◽  
Lia Lorena Pimentel ◽  
Nádia Cazarim Silva Forti
Keyword(s):  
Recycled Concrete ◽  
Recycled Aggregates ◽  
Concrete Aggregates ◽  
Recycled Concrete Aggregates ◽  
Model Code ◽  
Alternative Materials ◽  
Model Code 2010 ◽  
The Difference ◽  
Natural Aggregates ◽  
Predicted Values

This paper presents a study with concretes produced with natural aggregates, recycled concrete aggregates (RCA) and waste porcelain aggregates (WPA). The study analyzed the influence of recycled aggregates in the mechanical properties of conventional concretes and evaluated the difference between measured and predicted values of elasticity modulus. The incorporation of WPA in concrete showed better mechanical results compared to the concretes produced with RCA. Measured elasticity moduli were lower than moduli predicted by NBR 6118:2014 and fib Model Code 2010, while measured results were greater than values predicted by Eurocode 2:2004 and ACI 318:2014, as expected, which indicated the safety of the latter two standards.

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