Field Investigation of Straw Length, Stubble Height and Rotary Speed Effect on the Dispersion and Burying of Residue

High-yielding agriculture leads to plenty of residues left in the field after harvest, which not only makes seeding operations difficult, but also decreases residue decomposition rate. Thus, it is necessary to incorporate some residue into the soil by tillage operations. Providing the relation between tillage operations and residue incorporation, and establishing a mathematical model plays an important role in residue management and the design of tillage machinery. In order to obtain detailed data on the interaction between crop residue and tillage operations, an electric and multi-functional field testing bench with precise parameter control was developed to perform residue incorporation characteristics of rotary tillage, and investigated straw length, rotary speed and stubble height effect on the dispersion and burying of residue. Three experimental factors affecting residue incorporation performance were studied, i.e. six lengths of straw (30-150 mm), four heights of stubble (50-200 mm), and three rotary speeds (240-320 rpm). Chopped straw and stubble with certain sizes were prepared for the test, and measure the dispersion uniformity and burying rate of residue after rotary tillage. The results indicated that straw length, stubble height, and rotary speed all impact residue incorporation quality. The dispersion uniformity and burying rate of residue decreased with the increase of straw length and stubble height; Lower rotary speed parameter buried lesser residue and dispersed worse uniformity than higher one; It is suggested that farmers determine the straw length and stubble height at the stage of harvest according to the burying rate and dispersion uniformity of residue.

Safety and Efficacy of a Novel Centrifugal Pump and Driving Devices of the OASSIST ECMO System: A Preclinical Evaluation in the Ovine Model

Background: Extracorporeal membrane oxygenation (ECMO) provides cardiopulmonary support for critically ill patients. Portable ECMO devices can be applied in both in-hospital and out-of-hospital emergency conditions. We evaluated the safety and biocompatibility of a novel centrifugal pump and ECMO device of the OASSIST ECMO System (Jiangsu STMed Technologies Co., Suzhou, China) in a 168-h ovine ECMO model.Methods: The portable OASSIST ECMO system consists of the control console, the pump drive, and the disposable centrifugal pump. Ten healthy sheep were used to evaluate the OASSIST ECMO system. Five were supported on veno-venous ECMO and five on veno-arterial ECMO, each for 168 h. The systemic anticoagulation was achieved by continuous heparin infusion to maintain the activated clotting time (ACT) between 220 and 250 s. The rotary speed was set at 3,200–3,500 rpm. The ECMO configurations and ACT were recorded every 6 hours (h). The free hemoglobin (fHb), complete blood count, and coagulation action test were monitored, at the 6th h and every 24 h after the initiation of the ECMO. The dissection of the pump head and oxygenator were conducted to explore thrombosis.Results: Ten sheep successfully completed the study duration without device-related accidents. The pumps ran stably, and the ECMO flow ranged from 1.6 ± 0.1 to 2.0 ± 0.11 L/min in the V-V group, and from 1.8 ± 0.1 to 2.4 ± 0.14 L/min in the V-A group. The anticoagulation was well-performed. The ACT was maintained at 239.78 ± 36.31 s, no major bleeding or thrombosis was observed during the ECMO run or in the autopsy. 3/5 in the V-A group and 4/5 in the V-V group developed small thrombus in the bearing pedestal. No obvious thrombus formed in the oxygenator was observed. The hemolytic blood damage was not significant. The average fHb was 0.17 ± 0.12 g/L. Considering hemodilution, the hemoglobin, white blood cell, and platelets didn't reduce during the ECMO runs.Conclusions: The OASSIST ECMO system shows satisfactory safety and biocompatibility for the 168-h preclinical evaluation in the ovine model. The OASSIST ECMO system is promising to be applied in clinical conditions in the future.

Biomimetic Rotary Tillage Blade Design for Reduced Torque and Energy Requirement

A rotary cultivator is a primary cultivating machine in many countries. However, it is always challenged by high operating torque and power requirement. To address this issue, biomimetic rotary tillage blades were designed in this study for reduced torque and energy requirement based on the geometric characteristics (GC) of five fore claws of mole rats, including the contour curves of the five claw tips (GC-1) and the structural characteristics of the multiclaw combination (GC-2). Herein, the optimal blade was selected by considering three factors: (1) the ratio ( r ) of claw width to lateral spacing, (2) the inclined angle ( θ ) of the multiclaw combination, and (3) the rotary speed ( n ) through the soil bin tests. The results showed that the order of influence of factors on torque was n , r , and θ ; the optimal combination of factors with the minimal torque was r = 1.25 , θ = 60 ° , and n = 240 rpm . Furthermore, the torque of the optimal blade (BB-1) was studied by comparing with a conventional (CB) and a reported optimal biomimetic blade (BB-2) in the soil bin at the rotary speed from 160 to 320 rpm. Results showed that BB-1 and BB-2 averagely reduced the torque by 13.99% and 3.74% compared with CB, respectively. The field experiment results also showed the excellent soil-cutting performance of BB-1 whose average torques were largely reduced by 17.00%, 16.88%, and 21.80% compared with CB at different rotary speeds, forward velocities, and tillage depths, respectively. It was found that the geometric structure of the five claws of mole rats could not only enhance the penetrating and sliding cutting performance of the cutting edge of BB-1 but also diminish the soil failure wedge for minimizing soil shear resistance of BB-1. Therefore, the GC of five fore claws of mole rats could inspire the development of efficient tillage or digging tools for reducing soil resistance and energy consumption.

Evaluation of the Performance of a Combined Tillage Implement with Plough and Rotary Tiller by Experiment and DEM Simulation

In order to improve the performance of tillage tool for straw incorporation in silty clay loam, a combined tillage implement with plough and rotary tiller was designed. Its performance on straw incorporation and power consumption was investigated, and the combined tillage types (CTSR and CTDR) were compared with traditional tillage types including a sole plough type (SP and DP), a sole rotary tiller (RT), and a two-pass tillage type (SP+RT and DP+RT) in a rice field experiment. The effect of the forward speed and rotary speed for RT and CTSR were studied by DEM simulation. The ratio of straw coverage by CTSR and CTDR increased nearly 20% compared with RT, and the stability coefficient of tillage depth and CV of the surface evenness after tillage also improved in the field experiment. The total power of CTSR and CTDR was less than that of RT and two-pass tillage types by measurement. DEM simulation indicated that the total power of CTSR increased with the increase of the forward speed and rotary speed, and the reduction of the rotary power for the combined tillage implement can be obtained at a relatively high rotary speed. The combined tillage implement improved the performance on straw incorporation and had an advantage on power consumption at some operational conditions.

Experimental Research on the Process Parameters of a Novel Low-Load Drill Bit Used for 7000 m Bedrock Sampling Base on Manned Submersible

Due to the need for accurate exploration of deep-sea scientific research, drilling techniques by combining the operational advantages of the Jiaolong manned submersible is considered one of the most feasible methods for deep-sea bedrock drilling. Based on deep sea bedrock cutting model and discrete element simulation, as well as efficient drilling as the design criterion, the development of a deep sea 7000 m electromechanical coring apparatus was carried out. The outstanding feature of this technology is that the bit load produced by the drill pressure is usually within the range 100–400 N while the recommended load for diamond drilling is 1–3 KN or even more. Therefore, searching for the drilling bits that can drill in extremely hard formations with minimal load and acceptable rates of penetration and rotary speed is the necessary step to prove the feasibility of electromechanical deep-sea drilling technology. A test has been designed and constructed to examine three types of drill bits. The results of experiments show that the new low-load polycrystalline diamond compact (PDC) bit has the highest penetration length of 138 mm/15 min under a 300 N load and 250 rpm rotary speed. Finally, field tests with the Jiaolong submersible were used to conduct deep sea experiments and verify the load model, which provides theoretical and technical data on the use of a low-load core sampling drill developed specifically for a deep sea submersible.

Optimization Studies on Biological Desulfurization of Sulfide Ore Using Response Surface Methodology

This research aimed to optimize the experimental conditions of biodesulfurization of sulfide ore and to evaluate the flame-retardant effect after desulfurization under optimal conditions. Six experimental factors were determined: particle size of ore sample, ambient temperature, rotary speed of the shaking table, volume of bacteria liquid, concentration of leaching aid (Tween80), and pH value of acidizing ore sample. Desulfurization efficiency was used as the main characterization index of the desulfurization effect in optimization studies. Particle size of ore sample, rotary speed of the shaking table, and volume of bacteria liquid inoculated were selected as significant factors by a Plackett–Burman experiment. Modeling, optimization, and analysis of the interactive effects of these factors, notably between particle size and bacteria liquid, were performed using a Box–Behnken design with response surface methodology. The optimum operating conditions were found to be: particle size of 120 to 140 mesh, rotary speed of 175 rpm, and bacteria liquid of 111 mL. Under these conditions, a significant rise of 8.1% was seen in 5-day average desulfurization efficiency. The 5-day oxidation weight gain rate of desulfurized ore was 2.73%, while that of the control group was 4.78%. The results show that, after optimized desulfurization, the surface oxidizability and spontaneous combustion tendency of the ore are reduced.

Drilling Vibration Modes and Penetration Rate Modeling using Artificial Neural Network and Multiple Linear Regression Analysis in Khoman Formation at the Egyptian Western Desert

Drill string vibrations are one of the most serious problems encountered while drilling as the bit and drill string interaction with formations under certain drilling conditions usually induces complex shocks and vibrations into the drill string components resulting in premature failure of the equipment and reduced drilling penetration rate. In severe cases where shocks and vibrations accumulated into drill string till exceeded its maximum yield or torsional strength, fatigue will occur and thereby increase the field development costs associated with replacing damaged components, fishing jobs, lost-in-hole situations, and sidetracks. Thus, real-time monitoring for downhole generated vibrations and accordingly adjusting drilling parameters including weight on bit, rotary speed, and circulation rate play a vital role in reducing the severity of these undesirable conditions. Vibration optimization must be done incorporation with the penetration rate, as a minimum economical penetration rate is required by the operator. In this study, three penetration rate and vibration level models were developed for axial, lateral, and stick-slip drilling modes using both MATLAB™ Software neural network and multiple regression analysis. It is found that the three models' results for vibration level and penetration rate; as compared with those recorded drilling data; showed an excellent match within an acceptable error of average correlation coefficient (R) over 0.95. The prediction of penetration rate and vibration level is thoroughly investigated in different axial, lateral, and stick-slip vibration drilling modes to be able to best select the optimum safe drilling zone. It is found that the axial vibration could be dampened by gradually increasing the weight on bit and increasing rotary speed while both the lateral and torsional vibrations are enhanced by increasing the rotary speed and decreasing the weight on bit.

Drilling in the Digital Age: Machine Learning Assisted Bit Selection and Optimization

Conventionally, a bit is selected from offset well bit run summaries. This method of selection is not always accurate since each bit is run under different conditions which might not be reflected in an offset study analysis. The large quantities of data generated from real time measurements in offset wells makes machine learning the ideal tool for analysis and comparison. Artificial Neural Network (ANN) is a relatively simple machine learning tool that combines inputs and calculation layers to compute a specified output layer. The ANN is fed over thousands of data points from 17-1/2 in hole sections across multiple wells. A specific model is then trained for every bit with weight on bit (WOB), rotary speed (RPM), bit hydraulics, and lithological properties as inputs and rate of penetration (ROP) as output. The model is finalized when a satisfactory statistical set of KPI's are achieved. Using a combination of Monte-Carlo analysis and sensitivity analysis, different bits are compared by varying parameters for the same bit and varying the bit under the same parameters. A bit and its optimized parameters are proposed, resulting in an average instantaneous ROP improvement of 32%. Performance benchmarked with individual drilling parameters shows improved ROP response to WOB, RPM, and bit hydraulics in the optimized run. This project solidifies machine learning as a powerful tool for bit selection and parameter optimization to improve drilling performance. Machine learning will become a significant part of well planning, design, and operations in the future. This study demonstrates how ANN's can be used to learn from previous operations and influence planning decisions to improve bit performance.

Establishing Predictive Friction Factor Ranges in the Permian and Appalachia: Frac Plug Drill Outs

Completions operations, especially in modern day extended laterals, presents challenges related to tripping to total depth, applying weight down and pull up, and rotating. As dozens of stages in laterals exceeding 10,000 ft stepout have become frequent, numerous technologies have risen to assist with pushing the envelope for reliable completions operations in these long laterals. This paper examines a combination of three technologies that are more commonly being applied when drilling out frac plugs in long horizontals in the USA: hydraulic completion units, torque and drag software, and data acquisition systems. Coiled tubing units (CTU) have historically been used to drill out frac plugs in shorter horizontal shale wells for the last two decades, and where coil has mechanical limitations, Hydraulic Completion Units (HCU) have taken over drilling out frac plugs in the longer laterals of >10,000 ft. As the limits of drilling out frac plugs have been tested for HCUs, accurate real time data has enabled the crews to make the most of their equipment to reliably complete wells with longer and longer lateral sections. Torque and drag software modeling is a tool commonly used to predict axial force and torsional values during completions that result in the available hook load and the rotary torque requirements. The largest unknown in the planning phase is the appropriate friction factor to use for the upcoming well, with accurate friction factor prediction therefore the key to accurate prejob analysis. As of 2019 remote telemetry data acquisition systems (DAS) have been used on the HCUs, which has allowed key performance indicators (KPIs) to be automatically calculated. The program provides live feed to the service company and operator so that real time changes can be made if necessary. In addition to tracking KPIs in real time to provide the field crew positive or negative feedback, friction factors can be matched to predictive torque plots to identify trends prior to problems arising. Post-job analysis is needed to produce accurate predictive friction factors for future offset wells. The two main components to a successful post-job analysis are a software model that correctly represents the prior wellbore operations and accurate field data to compare with that model. Unfortunately, the software models in use are commonly limited by necessary assumptions with input data, such as rotary speed and tripping speed, and field data collected for comparison is often rudimentary. Experienced field personnel using engineering best practices can make use of current tools in combination to overcome the limitations commonly inhibiting accurate performance planning and predictive modeling. The inclusion of the DAS present on the HCU has greatly enhanced the accuracy and amount of rig data gathered, which can then be used in conjunction with operational procedures and torque and drag software to accurately plan and execute completions operations in the wellbore. Using data acquisition software, a constant stream of data was collected in one-second intervals in over two dozen wells. This system has the ability to measure both rotary speed and rotary torque, which are critical parameters when drilling out frac plugs. By removing these assumptions in the post-job analysis over a number of wells, a range of friction factors have been established for the Appalachian Basin in the Utica and Marcellus plays. The authors will present field data from two wells as representative case studies, along with the range of predictive friction factors established from 13 wells for the particular completions operations evaluated in the Permian and Appalachia plays. It is the goal of the authors to disseminate technical information on the methodology and practice of modeling wells post-job, calibrating friction factors, and establishing predictive ranges for successful use in future projects.

Simultaneous Effect of Tool Rotation and Dwell Time on Quality of Dissimilar AA5052-Copper Joints Fabricated by Friction Stir Spot Welding

In the present study, lap joints of dissimilar 5052 aluminum alloy and pure copper were fabricated by friction stir spot welding process. The work was aimed to find effect of parameters such as tool rotary speed (1000, 1400 and 2000 RPM) and dwell time (5, 10 and 15s) on microstructure and strength properties of lap joints. Also, statistical models of the quality characteristics were developed to understand which interaction has dominant effect on quality characteristics. Research findings showed that to obtain sound joints with high lap shear strength tool rotary speed of 2000 rpm and dwell time of 5s should be selected. It provides sufficient heat input and prevents the excessive material softening. On the other hand, to achieve maximum hardness, 2000 rpm tool rotary speed should be chosen to provide enough heat for formation of intermetallic compound and 10s dwell time should be used prevent enough time for microstructure refining. Moreover, from the statistical analyses, it was found that dwell time and tool speed are the significant factor for lap shear strength and hardness, respectively. In order to attain simultaneous maximum strength and hardness, tool speed of 2000 rpm and dwell time of 8 s should be used. In such condition lap shear strength of 1755 N and hardness of 77 V are achieved with desirability of 85%.