A smooth curve evolution approach to the feedrate planning on five-axis toolpath with geometric and kinematic constraints

Feedrate planning with geometric and kinematic constraints is crucial for sculptured surface machining. Due to the non-linear relationship between the Cartesian space and the joint space, the feedrate planning method for a given five-axis toolpath is very limited compared with that in three-axis machining. To achieve the exact control of the chord error and the kinematic characteristics of cutter and machine tool, this paper presents a new feedrate planning method for five-axis parametric path using a smooth curve evolution strategy. The constraints in feedrate planning are first classified as two types of neighbor-independent (NI) constraints and neighbor-dependent (ND) constraints. Then for constraint violated region, the detailed formulas of determining the update feedrates of violated sampling points are given using a decoupled manner. As a result, NI and ND constraints are satisfied respectively with one step and multi-step smooth curve evolution technique, which can smoothly deform the target feedrate profile to the desired update positions. Simulations and experiments are performed on the given tool path to validate the effectiveness of the proposed feed planning method. The results show that the proposed method is robust and effective in the exact control of constraints in the feedrate planning on complex five-axis toolpath.     

测井曲线标准化方法研究

由于长岭凹陷区经过近60年的勘探开发,再加上井场井眼条件的差异、测井系列、仪器刻度、测量时间及操作者不同等因素,使得各测井曲线存在系统误差。因此在开展储层参数研究和有效厚度划分时,为消除这些非地层因素对原始资料的影响,有必要对测井曲线进行标准化,以保证解释结果的合理性与可靠性。测井曲线标准化方法可以分为定性和定量两种类型。其中定性方法主要包括直方图法标准化校正、均值法标准化校正和重叠图法标准化校正;定量方法则为趋势面分析校正法。本论文利用Matlab软件,采用趋势面方法对研究区域内的井进行测井曲线标准化。结果表明经过趋势面法标准化校正能够消除不利因素,准确的提取出测井曲线中的各种有用地质信息。     

Predictions of frame compliance and apex morphology in sharp nanoindentations

If all components in a nanoindentation system are well calibrated and a reference material has unique hardness, H and reduced modulus, E_r independent of the indentation depths, the load, L and the penetration depth, h in the indentation loading curve of the reference material can be correlated by L=Kh². Here the constant K is expressed by H, E_r and indenter geometry constants. By using H and E_r of a fused silica and the Berkovich geometry, an analytical expression for the indentation loading curve could be derived. To compare with this analytical loading curve, experimental indentation data were measured with two commercial nanoindenters. The experimental loading curves shifted leftward or rightward from the analytical loading curve and this depth deviation was attributed to improper calibration of the nanoindenters. Quantitative calibrations of frame compliance and indenter bluntness were tried for the raw nanoindentation data and this resulted in consistent nanoindentation data regardless of the used nanoindenters.     

Damage accumulation modeling under uniaxial low cycle fatigue at elevated temperatures

The paper presents a fatigue damage accumulation model, which allows us to predict fatigue life under low cycle uniaxial loadings at elevated temperatures. The structure of the model has been based on the stress–strain curves obtained during the experimental study. The model has been verified experimentally by applying experimental studies carried out on ENAW-2024T3 aluminum alloy and 2Cr–2WVTa steel. Moreover, a comparison between the results of fatigue life prediction using the proposed damage accumulation model was done with the results obtained on the basis of various generally applied models, based on the Manson–Coffin dependency. Furthermore this paper presents the results of experimental studies carried out on the aluminum alloy ENAW 2024 T3 under uniaxial low cycle fatigue loadings in the conditions of elevated temperatures. In the course of the study, material constants and the parameters of the stress–strain curve in the range of low cycle fatigue for four levels of temperatures (20, 100, 200 and 300 °C) were set.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

Performance curve available for non-steady flow through Venturi-like reverse flow diverter

A reverse flow diverter (RFD) consists of a driving nozzle, a diffuser, and a suction gap that separates the nozzle and diffuser. Thus, the RFD is a Venturi-like fluidic component with three ports. The jet flow emanating from the driving nozzle exit can entrain the ambient fluid and transport it to a high elevation. During this time, the flow through the RFD is non-steady, which makes it difficult to measure the flow depending on the pressure drop. In this study, a series of tests was carried out to evaluate this fluid flow with different contraction ratios, suction gap lengths, fluid properties, inlet flow rates, and inlet pressures. A performance curve was formulated that can be expressed as an exponential equation correlating the non-dimensional Euler number, pressure ratio, and suction factor. The performance curve is not affected by the driving nozzle exit diameter and suction length of the RFD. The performance curve makes it possible to measure the flow out of a RFD depending on the pressure drop.     

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from ?0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.     

基于增强算子的污染土雷达图像特征提取仿真

针对雷达图像特征提取效率低、精度不高等问题,提出一种基于增强算子的污染土雷达图像特征提取方法。首先使用多尺度非均匀滤波把含有噪声与不含噪声的像素点灰度值、构成因素及像素加权灰度密度三个特征进行划分,完成雷达图像去噪。其次提出增强算子方法,将图像数据转变至图像的空间域,以此判断污染土雷达图像内是否存在对比度不高区域和细微区域。最后采用灰色关联分析计算超像素之间的相似度,运用MLS增强算子对曲面进行拟合,通过高斯曲率与平均曲率构建出特征判断准则,提高图像特征提取完整性,实现污染土雷达图像特征的精准提取。仿真结果表明,与传统方法相比所提方法计算速度较快,雷达特征提取效率较高,可大幅提升污染土雷达图像特征提取准确率。     

平板集热器(倾角)变化工况数值模拟

运用FLUENT数值模拟软件分析了平板集热器(倾角)变化对集热器传热特性的影响,保证其结构参数不变,通过对5组不同倾角(0°、30°、45°、60°、75°)的数值模型进行非稳态模拟,对模拟数据进行分析,得出了平板集热器不同倾角对集热器传热性能变化的影响。     

基于功能参数的渐进成形件表面质量表征研究

目的 以圆锥台成形件为例，基于粗糙表面的区域支承率曲线，进行了用功能参数表征表面几何形貌的研究，以全面、准确、定量地表征渐进成形件的表面质量，预测表面性能。方法 用渐进成形工艺加工成形角分别为35°、45°和55°的圆锥台件，将各圆锥台的成形面分为顶部、中部和底部三个区域，并使用三维表面轮廓仪，在上述三个区域中随机测量各4个样本。根据ISO 25178-2:2012，将各样本表面的区域支承率曲线分为峰区、核心区和谷区，选用部分功能参数——核心区高度Sk、峰区材料体积Vmp、核心区材料体积Vmc和谷区空隙体积Vvv表征表面，并与常用的高度表征参数——Sa、Sq、Ssk和Sku进行比较。结果 成形件表面的Ssk和Sku的计算值极不稳定，变异系数（标准偏差与均值之比）最高值分别可达127.67%和39.11%，Sa、Sq的最大变异系数分别为4.41%和4.26%，虽然它们的参数计算值较为稳定，但常无法体现表面形貌的实际差异。功能参数独立表征不同功能区，Sk和Vmc的最大变异系数分别为9.32%和7.73%，说明同一表面各处，在长期工作阶段具有较为一致的表面性能，Vmp和Vvv的最大变异系数分别为60.53%和31.25%，说明表面各处峰、谷区的形貌有所不同，因而在磨合时间、磨粒存储等方面会有不同的表现。结论 粗糙表面的三维本质要求用三维表征参数才能全面表征其几何形貌。高度参数虽然计算简单，但常难以解读它们的物理意义，无法定量评价表面性能；功能参数具有明确的物理意义，可为表征表面质量、预测表面性能提供定量、实用的方法。