Alex Fang

Analysis of Impact of Various Factors on Downwind Deposition Using a Simulation Method

The drift of aerially applied crop protection and production materials is studied using a novel simulation-based design of experiments approach. Many factors that can potentially contribute to downwind deposition from aerial spray application are considered. This new approach can provide valuable information about the significant level of the impact from all factors and interactions among them that affect drift using simulation software such as AGDISP. The application efficiency, the total downwind drift, the cumulative downwind deposition between 30.48 m (100 ft) and 45.72 m (150 ft), and the deposition at 30.48 m (100 ft), 76.2 m (250 ft), and 152.4 m (500 ft) are established as the performance metrics. The most significant factors will be identified using statistical analysis based on simulation results, and suggestions for improvement will be made. Through preliminary study, the new simulation-based method has shown the potential for statistic analysis without conducting time-consuming field experiments. The new method can be used to search for the optimal spray conditions, which could be used to generate guidelines for applicators to achieve an optimal spray result. The effective use of simulation tool through the identification of significant factors can greatly simplify the field study.

Modeling Material Removal in Lapping of Brittle Materials

Lapping of polycrystalline diamond compact (PDC) is a costly and time-consuming process that demands fundamental studies to improve its efficiency and quality. A series of experiments are conducted in this study to gain insights into the effects of the most influential factors on material removal rate (MRR). The well-known Preston’s equation is found to be insufficient for a satisfactory prediction of MRR associated with PDC lapping, and a new model is developed. The current approach treats MRR as the product of removal intensity and removal density, which are formulated as simple functions of pressure, velocity and grain concentration. The newly derived model is in good accordance with the analyzed experimental results. The decrease in MRR at higher pressure and the connections between applied pressure, grain concentration and MRR can all be well explained by the proposed model.Copyright

Lapping of Polycrystalline Diamond Compact (PDC)

This paper is aimed at developing an efficient process, in terms of the material removal rate (MRR), for the lapping of polycrystalline diamond compact (PDC). A carbomer based viscoelastic vehicle with a non-reversible shear-thinning property was first developed for the effective suspension of diamond grits used for lapping. The effects of key process parameters on the MRR such as lapping pressure, speed, vehicle concentration, diamond grit concentration, and vehicle flow rate have been investigated through experiments. To obtain an insight into what happened to the diamond grits during lapping, diamond abrasives were reclaimed and sieved after lapping. The grit size distributions of diamond abrasives before and after the lapping were then compared.

Technical Development and Applications of Soft Computing in Agricultural and Biological Engineering

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and applied in the last three decades for scientific research and engineering computing. In agricultural and biological engineering, researchers and engineers have developed methods of fuzzy logic, artificial neural networks, genetic algorithms, decision trees, and support vector machines to study soil and water regimes related to crop growth, analyze the operation of food processing, and support decision-making in precision farming. This paper will review the development of soft computing techniques, and a number of advanced soft computing techniques will be introduced. With these concepts and methods, applications of soft computing in the field of agricultural and biological engineering will be presented, especially in the soil and water context for crop management and decision support for precision agriculture. The future of development and application of soft computing in agricultural and biological engineering will be discussed.

Studies on the Lapping of Polycrystalline Diamond Compact (PDC)

Researching the effect that certain parameters have on the lapping process is crucial to understanding the fundamental material removal mechanisms and implementing a procedure that most efficiently produces desired results. This study examines the lapping procedure for polycrystalline diamond compacts (PDCs). Tests were conducted using different sample carriers, PDC arrangements, and abrasive size distributions. Previous studies have focused on the material removal rate (MRR), which is of interest, but this study also examines the MRR uniformity within a group of PDCs lapped together. The goal of this research was to determine the optimal lapping conditions and PDC arrangement required to achieve the highest productivity. Results indicate that a hard specimen carrier is necessary to produce PDCs with uniform MRRs, and the number of PDC samples in a carrier can be increased with certain design constraints kept in mind.