双相区加速冷却处理对X80管线钢组织与性能的影响

采用双相区加速冷却法(加速冷却始冷温度为700 ℃)对X80管线钢进行热处理,获得了贝氏体和铁素体(B+F)双相组织。然后通过组织表征、力学性能测试以及在3.5wt%NaCl溶液中的耐蚀性进行研究。结果表明:热处理后获得的管线钢组织由板条状贝氏体、多边形铁素体及少量马氏体/奥氏体岛组成。与热处理前相比,(B+F)双相管线钢屈强比较低,为0.65,初始加工硬化指数为0.31,均匀伸长率达8.3%,塑性显著提升;双相组织中含有52.4%的铁素体,因而耐腐蚀性明显提高。通过双相区加速冷却法获得的(B+F)两相组织在塑变过程中发生协调变形,可以适应大变形的需求,同时耐蚀性优异,为大变形管线钢实际生产提供一定的借鉴。     

不确定环境下基于质量功能展开的电动汽车技术特性综合重要度确定

电动汽车技术特性重要度的确定是电动汽车研发的关键环节,能协助研发主体优化资源配置,更好地满足顾客需求。综合考虑顾客需求、竞品情况、技术可得性情况以及企业自身实力情况,提出一种不确定环境下基于质量功能展开的电动汽车技术特性综合重要度确定模型,为电动汽车制造企业提供了一种科学、有效的开发工具。该模型利用基本不确定语言信息刻画不确定评估信息,模型的基本过程为:识别顾客需求,并利用最佳—最差权重确定方法(BWM)确定顾客需求重要度;确定顾客需求与技术特性关联关系,基于顾客需求重要度确定技术特性基本重要度;利用BWM方法,确定基于竞品分析的修正重要度、基于技术可得性的修正重要度以及基于自身实力的修正重要度;综合基本重要度与修正重要度,确定技术特性综合重要度。最后,以某一企业的电动汽车研发案例为对象,论证了该模型的可行性与有效性。     

Approximate ODE models for population balance systems

We propose an approximate polynomial method of moments for a class of first-order linear PDEs (partial differential equations) of hyperbolic type, involving a filtering term with applications to population balance systems with fines removal terms. The resulting closed system of ODEs (ordinary differential equations) represents an extension to a recently published method of moments which utilizes least-square approximations of factors of the PDE over orthogonal polynomial bases. An extensive numerical analysis has been carried out for proof-of-concept purposes. The proposed modeling scheme is generally of interest for control and optimization of processes with distributed parameters.     

一种混合多边缘型LDPC码密度进化算法

在二进制输入加性高斯白噪声信道下，研究了基于多边缘型低密度奇偶校验码（Multi-edge Low Density Parity Check，MET-LDPC）的密度进化算法。针对高斯近似算法在前期迭代中的不准确问题，提出了一种改进算法。在分析MET-LDPC码的密度进化的基础上，将全密度进化与高斯近似算法结合，通过设置切换限制条件，弥补早期迭代的不准确，提高编码阈值估计的准确性。仿真结果表明,与MET-LDPC全密度进化算法相比，所提算法可以有效提高编码阈值估计的准确性，对LDPC编码的设计有一定的参考价值。     

Thermal imaging of time-varying longitudinal defects in the internal coating of a tube

We deal with the mathematical model of the incremental degradation of the internal coating (e.g. a polymeric material) of a metallic pipe in which a fluid flows relatively fast. The fluid drags solid impurities so that longitudinal scratches, inaccessible to any direct inspection procedure, are produced on the coating. Time evolution of this kind of defects can be reconstructed from the knowledge of a sequence of temperature maps of the external surface. The time-varying orthogonal section of this damaged interface is determined as a function of time and polar angle through the identification of a suitable effective heat transfer coefficient by means of Thin Plate Approximation.     

Unique hue judgments using saturated and desaturated Munsell samples under different light sources

Past studies investigating the unique hues only used samples with a relatively high saturation levels under standard illuminants. In this study, 10 observers selected the four samples with unique hues from 40 V6C8 (Value 6 Chroma 8) and 40 V8C4 (Value 8 Chroma 4) Munsell samples under six light sources, comprising three levels of D_uv (i.e., 0, ?0.02, and ?0.04) and two levels of correlated color temperature (i.e., 2700 and 3500 K). Significant differences were found between the two chroma levels for unique blue and yellow, with the hue angles of unique yellow and blue judged using the desaturated samples being significantly different from those defined in CIECAM02. The iso‐lines of unique yellow, blue, and green did not always go through the origin of the a*‐b* or a′‐b′ planes in CIELAB and CAM02‐UCS. Thus, the problems of CIECAM02, CIELAB, and CAM02‐UCS identified in this study need further investigations.     

Complete convergence of stochastic approximation algorithm in ℝd under random noises

In this article, we study a stochastic approximation algorithm that approximates the exact root θ of a function M defined in ?^d into ?^d. The function M cannot be known exactly, but only noisy measurements are available at each point x_n with the error ξ_n. The sequence of noise (_ξn)n is random; we treat both cases where it is independent and dependent and we establish the complete convergence of the approximated sequence of θ.     

A pure proactive scheduling algorithm for multiple earth observation satellites under uncertainties of clouds

Most earth observation satellites (EOSs) are equipped with optical sensors, which cannot see through clouds. Hence, observations are significantly affected and blocked by clouds. In this work, with the inspiration of the notion of a forbidden sequence, we propose a novel assignment formulation for EOS scheduling. Considering the uncertainties of clouds, we formulate the cloud coverage for observations as stochastic events, and extend the assignment formulation to a chance constraint programming (CCP) model. To solve the problem, we suggest a sample approximation (SA) method, which transforms the CCP model into an integer linear programming (ILP) model. Subsequently, a branch and cut (B&C) algorithm based on lazy constraint generation is developed to solve the ILP model. Finally, we conduct a lot of simulation experiments to verify the effectiveness and efficiency of our proposed formulation and algorithm.     

A reliable modifier-adaptation strategy for real-time optimization

In model-based real-time optimization, plant-model mismatch can be handled by applying bias- and gradient-corrections to the cost and constraint functions in an iterative optimization procedure. One of the major challenges in practice is the estimation of the plant gradients from noisy measurement data, in particular for several optimization variables. In this paper we propose a new real-time optimization scheme that explores the inherent smoothness of the plant mapping to enable a reliable optimization. The idea here is to combine the quadratic approximation approach used in derivative-free optimization techniques with the iterative gradient-modification optimization scheme. The convergence of the scheme is analyzed. Simulation studies for the optimization of a ten-variable synthetic example and a reactor benchmark problem with considerable plant-model mismatch show its promising performance.     

Approximation and relaxation of semantic web path queries

Given the heterogeneity of complex graph data on the web, such as RDF linked data, it is likely that a user wishing to query such data will lack full knowledge of the structure of the data and of its irregularities. Hence, providing flexible querying capabilities that assist users in formulating their information seeking requirements is highly desirable. In this paper we undertake a detailed theoretical investigation of query approximation, query relaxation, and their combination, for this purpose. The query language we adopt comprises conjunctions of regular path queries, thus encompassing recent extensions to SPARQL to allow for querying paths in graphs using regular expressions (SPARQL 1.1). To this language we add standard notions of query approximation based on edit distance, as well as query relaxation based on RDFS inference rules. We show how both of these notions can be integrated into a single theoretical framework and we provide incremental evaluation algorithms that run in polynomial time in the size of the query and the data, returning answers in ranked order of their ‘distance’ from the original query. We also combine for the first time these two disparate notions into a single ‘flex’ operation that simultaneously applies both approximation and relaxation to a query conjunct, providing even greater flexibility for users, but still retaining polynomial time evaluation complexity and the ability to return query answers in ranked order.