An Overall Uniformity Optimization Method of the Spherical Icosahedral Grid Based on the Optimal Transformation Theory

The improvement of overall uniformity and smoothness of spherical icosahedral grids, the basic framework of atmospheric models, is a key to reducing simulation errors. However, most of the existing grid optimization methods have optimized grid from different aspects and not improved overall uniformity and smoothness of grid at the same time, directly affecting the accuracy and stability of numerical simulation. Although a well-defined grid with more than 12 points cannot be constructed on a sphere, the area uniformity and the interval uniformity of the spherical grid can be traded off to enhance extremely the overall grid uniformity and smoothness. To solve this problem, an overall uniformity and smoothness optimization method of the spherical icosahedral grid is proposed based on the optimal transformation theory. The spherical cell decomposition method has been introduced to iteratively update the grid to minimize the spherical transportation cost, achieving an overall optimization of the spherical icosahedral grid. Experiments on the four optimized grids (the spring dynamics optimized grid, the Heikes and Randall optimized grid, the spherical centroidal Voronoi tessellations optimized grid and XU optimized grid) demonstrate that the grid area uniformity of our method has been raised by 22.60% of SPRG grid, −1.30% of HR grid, 38.30% of SCVT grid and 38.20% of XU grid, and the grid interval uniformity has been improved by 2.50% of SPRG grid, 2.80% of HR grid, 11.10% of SCVT grid and 11.00% of XU grid. Although the grid uniformity of the proposed method is similar with the HR grid, the smoothness of grid deformation has been enhanced by 79.32% of grid area and 24.07% of grid length. To some extent, the proposed method may be viewed as a novel optimization approach of the spherical icosahedral grid which can improve grid overall uniformity and smoothness of grid deformation.

The Visual Measurement of Velocity Profile Distribution in Silt Carrying Flow by Using Ultrasound PIV and Iterative Multi-Grid Deformation Technique

Flow velocity in silt carrying flow is one key parameter to many river engineering problems. A visual measurement technique of velocity profile distribution in silt carrying flow is provided using a portable ultrasound imaging system and an improved iterative multi-grid deformation algorithm. A convex array probe in the system is used to obtain a series of ultrasonic images at different times. Window offset and an iterative computing scheme for reducing interrogation window size in the algorithm improve the accuracy and efficiency of flow velocity measurement in regions with velocity gradients. Results show that the measured profile velocities can be more acceptable after being compared with time-averaged stream-wise velocities of profiles at ten positions in the same silt carrying flow and subsequently verified by comparing the point-by-point standard value. The measured velocity is more in agreement with the theoretical value, with the minimum root mean square error in the ultrasound beam sweep effect calculated by using optimal interrogation size parameters. The system is a feasible alternative to the single-point measurement technique in silt carrying flow. The iterative multi-grid deformation algorithm can analyze velocity profile distribution with gradients simultaneously, which can help the real-time measurement of multiple spatial velocity distribution and turbulence.

Advanced Modeling of Drilling – Realistic Process Mechanics Leading to Helical Chip Formation

There is considerable interest in the “Industry 4.0 project”. Industry hopes that a general solution of the metal removal problem will be found through the use of highly automated manufacturing data. Scientists hope that the computer will provide better models based on artificial intelligence and machine learning. Initial attempts leveraging existing models did not result in satisfactory results yet — largely because of mathematical, physical and metallurgical reasons. This paper presents a new mathematical-physical model to describe the total process mechanics from volume conservation, to friction, to metal plasticity with self-hardening or softening effects and dynamic phenomena during metal plastic flow. The softening effects are created by high energy corresponding to high strain-rate resulting in high temperatures. Furthermore, the developed equations for strain-rate discontinuities as well as yield shear stress with body forces have an interdependent relationship and lead to plastic deformation with dynamic behavior in the total chip formation zone. This plastic deformation is the only parameter that will not disappear after completing the process. This leads to the opportunity to check the theoretically developed grid deformation and compare it with practical results of the same area. In this publication this new theory will be used to analyze the complex contact and friction conditions between the chip and tool edge of a twist drill during operation. It will be shown that the existing conditions are leading to high wear at the corner edge and flank wear at the tool cutting edge. In addition, the existing temperatures can be estimated and compared with practical measurements, and all these complex and difficult conditions create a helical spiral chip, which could be developed as it will be presented in this paper.

Usage of Digital D Chart Test as a Modification of Amsler Grid in Ophthalmology and Optometry

Aims: Metamorphopsia is important symptom of macular disease. The most common simple detection method of metamorphopsia is Amsler grid. Usually it is used monocularly with best correction for near. Patient should evaluate grid deformation and describe position of the deformity. This method is based on qualitative principle. For quantitative evaluation we can use Software D Chart (Thomson Software Solution). This instrument enables evaluate degree and position of the metamorphopsia in central visual field. Our goal was to establish M-score values in group of young healthy subjects without correction (M-score natural), with cylindrical spectacle lens (M-score SL) and in group of patients with age related degeneration (M-score ARMD). Objects and Methods: We had 33 probands divided into 2 samples. The first sample contains 15 young probands with average age 23 years without any eye pathology. The second sample contains 18 patients with ARMD (7 with dry form and 11 with wet form). In our study we used software D Chart (Thomson Software Solution). This software was use in Acer PC with touchable screen. We note total M-score in right eye of all probands. Level for statistic evaluation was set on p = 0.05. Results: Natural M-score values for young probands was: median 0, minimum 0, maximum 2.3. With cylindrical lens we got these values: median 25.2, minimum 3.6, maximum 41.6. In second sample with probands suffer from ARMD we got these values: median 0.8, minimum 0, maximum 29.4. Wilcoxon non-parametric test was used for statistical evaluation. We proved statistically significant difference between all variables. M-score natural vs. M-score SL showed p < 0.001, M-score natural vs. M-score ARMD showed p = 0.04 and M-score SL vs. M-score ARMD showed p < 0.001. Conclusion: Our study showed statistically significant differences between variable M-score natural, M-score SL and M-score ARMD. We found that printed Amsler grid as well as its digital modification D Chart are suitable for determining metamorphopsia in central visual field. The main advantage of D Chart is quantitative evaluation of the test with M-score and digital registration of retinal changes during patient´s follow up.

Fuel efficiency optimization of high-aspect-ratio aircraft via variable camber technology considering aeroelasticity

In this study, variable camber technology is applied to improve the fuel efficiency of high-aspect-ratio aircraft with aeroelasticity considered. The nonlinear static aeroelastic analyses are conducted for CFD/CSD (computational fluid dynamics/computational structural dynamics) numerical simulations. The RBF (radial basis function) method is adopted for the transmission of aerodynamic loads and structural displacements, the diffusion smoothing method is employed for grid deformation in each iteration of CFD/CSD coupling, and the FFD (free-form deformation) method is introduced for the parameterization of variable camber wing. Based on the aerodynamic characteristic curves under different cambers, the discrete variable camber control matrix for the high-aspect-ratio aircraft during the cruise phase is established. The Fibonacci method is employed to optimize the fuel efficiency by utilizing the control matrix. The results indicate that the drag during the cruise phase is reduced obviously and the fuel efficiency is improved evidently comparing to the original configuration.

Near-Optimal Weather Routing by Using Improved A* Algorithm

With soaring oil prices worldwide, determining the most optimal routes for economical ship operation has become an important issue. Optimizing ship routes is economically important for ship operation, but it is also essential to meet the standards of environmental regulations recently imposed by the International Maritime Organization. For this purpose, various algorithms for determining ship routes have been developed to ensure the economical operation of ships via utilization of marine climate data and Automatic Identification System (AIS) data. However, such algorithms require a large amount of computational time and do not provide optimal routes because they do not consider practical operating conditions, such as weather and ocean conditions. In this study, an improved A* algorithm using AIS and weather data is proposed to overcome the limitation of the original A* algorithm, one of the most widely used path-finding algorithms. The improved A* algorithm uses an adaptive grid system that efficiently explores nodes according to map grid deformation by latitude. It finds economical routes by minimizing the estimated time of arrival generated by machine learning through 16-way node exploration. For verification of the proposed method, the original A* algorithm and improved A* algorithm were compared through a case study.