蒸发器泄漏原因分析及处理

对锦州石化分公司第三套催化裂化装置系统蒸发器泄漏原因进行了分析,并提出处理措施。收到较好的效果。     

Protein binding study of isoflavone, perillyl alcohol and S-ibuprofen by high-performance frontal analysis

High-performance frontal analysis (HPFA) was used for a protein binding study of isoflavones (daidzein, genistin, and genistein), enantiomers of perillyl alcohol and S-ibuprofen to human serum albumin (HSA). The analyses were performed on a Develosil and Inertsil 100-Diol-5 column (10 cm×4.6mm). Sodium phosphate solution (pH 7.4, ionic strength 0.17) was used as the mobile phase at a flow rate of 1 ml/min. To ensure the drug to be eluted as a trapezoidal peak with a plateau, injection volumes were each fixed up the zonal profile with an evident plateau appears. The unbound drug concentration was determined from a plateau height of the plateau region after that experimental data were fitted by Scatchard equation. The binding constants (K) and total binding affinities (nK) of drugs to HSA were calculated, respectively.     

Drag coefficient of flow around a sphere: Matching asymptotically the wide trend

An empirical relationship of drag coefficient of flow around a sphere is developed for the entire range of Particle Reynolds numbers reported in the literature from Stokes regime to the condition when turbulent boundary layer prevails. The relationship is obtained using an approach to match asymptotically the wide trend of drag coefficient. The matching approach, which relies on dividing the wide trend into smaller segments that can be combined into an overall relationship, employs regression techniques and thus warrants the best-fit accuracy results. The relationship is calibrated with experimental data available in the literature covering the entire range for Reynolds numbers up to ~ 10⁶. For Reynolds values greater than 10⁶, the relationship renders a drag coefficient of 0.2. The performance of the relationship is tested and compared with other suitable models found in the literature. This relationship is also transformed into an explicit expression for settling velocity calculations.     

冰蓄冷系统运行经济性分析

建筑物的空调制冷系统采用蓄冷方式，可以节约运行费用，减少设备容量，转移用电高峰。蓄冷空调系统与常规空调系统相比，在运行的经济性方面有很多优点。因此开发了冰蓄冷系统运行经济性分析计算机软件，应用这套软件对实际工程项目进行分析，计算出各种冰蓄冷系统与相应常规系统的逐时耗电量、电费、全年运行费用和设备容量减少率等，并以图表的方式对两种系统的经济性作出综合的比较，能全面、直观的显示冰蓄冷系统的优点。     

Cycle detection using a stack

We present an algorithm for detecting periodicity in sequences produced by repeated application of a given function. Our algorithm uses logarithmic memory with high probability, runs in linear time, and is guaranteed to stop within the second loop through the cycle. We also present a partitioning technique that offers a time/memory tradeoff. Our algorithm is especially well suited for sequences where the cycle length is typically small compared to the length of the acyclic prefix.     

基于回归方法的移动通信话务量预测

针对移动通信话务量与市场用户和相应资费政策相关的特点，采用回归预测方法，建立了基于市场用户数及每用户收入的话务量预测模型，并对模型进行了经济学意义上的检验。根据此模型，对话务量进行了初步的预测分析。     

A simple approximation algorithm for the weighted matching problem

We present a linear time approximation algorithm with a performance ratio of 1/2 for finding a maximum weight matching in an arbitrary graph. Such a result is already known and is due to Preis [STACS'99, Lecture Notes in Comput. Sci., Vol. 1563, 1999, pp. 259-269]. Our algorithm uses a new approach which is much simpler than the one given by Preis and needs no amortized analysis for its running time.     

核电站中椭圆柱形屏蔽体辐射衰减率的仿真研究

为了预测核电站中椭圆柱形屏蔽体的辐射衰减率，该文用数值解析法对放射线源到评价点的放射线所穿透椭圆柱形屏蔽物体的交点进行了研究。首先用空间解析法建立了椭圆柱形物体的数学模型。然后解曲面方程求出交点。在判断放射线是否穿透此椭圆柱体时，该文又提出了椭圆柱形屏蔽体的假想外接长方体的建模方法，将曲面方程联立解的复杂计算简化为一次代数方程的简单计算，大幅度地缩短了计算时间。     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

Makespan estimation and order acceptance in batch process industries when processing times are uncertain

Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times. Correspondence to: C.V. Ivanescu