Reasoning Boolean operation based modeling for heterogeneous objects

A reasoning Boolean operation based CAD modeling approach applied to construct heterogeneous material objects is presented. This reasoning Boolean operation consists of a merging operation and an extracting operation, and it is executed according to the material-dominant information defined in the designed heterogeneous object database. In addition to the material-dominant Boolean union, subtraction, and intersection, a new Boolean complex_union operation is defined and introduced to the set of the reasoning Boolean operation. The Boolean complex_union ‘assembles’ the results of the material-dominant Boolean intersection and subtraction to form a new modeling assembly for the heterogeneous object. Due to the CAD-based nature, the thus formed heterogeneous model can be readily implemented with advanced CAD/CAE/CAM software for integrated design, analysis, and simulation. An example of such an application, its hierarchy of the model database, and the major steps of the model construction are described.     

Feature-based design for heterogeneous objects

Heterogeneous objects are objects composed of different constituent materials. In these objects, multiple desirable properties from different constituent materials can be synthesized into one part. In order to obtain mass applications of such heterogeneous objects, efficient and effective design methodologies for heterogeneous objects are crucial.In this paper, we present a feature based design methodology to facilitate heterogeneous object design. Under this methodology, designers design heterogeneous objects using high-level design components that have engineering significance. These high level components are form features and material features. In this paper, we first examine the relationships between form features and material features in heterogeneous objects. We then propose three synthesized material features in accordance with our examination of these features. Based on these proposed features, we develop a feature based design methodology for heterogeneous objects. Two enabling methods for this design methodology, material heterogeneity specification within each feature and combination of these material features, are developed. A physics (diffusion) based B-spline method is developed to (1) allow design intent of material variation be explicitly captured by boundary conditions, (2) ensure smooth material variation across the feature volume. A novel method, direct face neighborhood alteration, is developed to increase the efficiency of combining heterogeneous material features.Examples of using this feature based design methodology for heterogeneous object design, such as a prosthesis design, are presented.     

语义特征建模系统中布尔算法的研究

为了提高语义特征建模系统中布尔操作的运行效率,提出了一种基于语义表示法的布尔操作算法.该算法用语义表示法表示特征模型,用细胞元模型组织和管理特征元素,用语义面替代几何面来提高特征的交互检测效率,通过细胞分裂和语义面分解来生成新实体.该算法不仅可以快速准确地生成布尔实体,还可以避免几何面的丢失及“孔洞”等错误的发生.实验证明,该算法具有广泛的使用前景和实用价值.     

Modeling the material grading and structures of heterogeneous objects for layered manufacturing

The emphasis of this work is to discuss a scheme for modeling the material grading and structures of heterogeneous objects. To model the material grading of a heterogeneous object, a termed ‘grading source’ is defined. The grading sources are reference features, which specify the type and position of grading, and a material grading function for controlling the material variation within the geometric boundary of the objects. Within the proposed modeling scheme, a concept on representing objects, which are both heterogeneous in material and structure (e.g. composite laminates), will also be elaborated. For downstream layered manufacturing purposes, a contour sub-division algorithm on each layer arising from slicing a heterogeneous object is proposed. Within each slice, the material grading is decomposed into sub-contours according to the different grading variation. A parameter called ‘grading step-width’ is defined to control the number of sub-contours and resolution of the grading. With such discretization, it is, therefore, possible to build a heterogeneous object on layered manufacturing machines of different fabricating precision specification.     

A B-spline-based approach to heterogeneous objects design and analysis

The recent advancement of solid freeform fabrication, design techniques and fundamental understanding of material properties in functionally graded materials has made it possible to design and fabricate multifunctional heterogeneous objects. In this paper, we present an integrated design and analysis approach for heterogeneous object realization, which employs a unified design and analysis model based on B-spline representation and allows for direct interaction between the design and analysis model without laborious meshing operation. In the design module, a new approach for intuitively modelling of multi-material objects, termed heterogeneous lofting, is presented. In the analysis module, a novel graded B-spline finite element solution procedure is described, which gives orders of magnitude of better convergence rate in comparison with current methods, as demonstrated in several case studies. Further advantages of this approach include simplified mesh construction, exact geometry/material composition representation and easy extraction of an isomaterial surface for manufacturing process planning.     

Dealing with heterogeneous information in engineering evaluation processes

Before selecting a design for a large engineering system several design proposals are evaluated studying different key aspects. In such a design assessment process, different criteria need to be evaluated, which can be of both of a quantitative and qualitative nature, and the knowledge provided by experts may be vague and/or incomplete. Consequently, the assessment problems may include different types of information (numerical, linguistic, interval-valued). Experts are usually forced to provide knowledge in the same domain and scale, resulting in higher levels of uncertainty. In this paper, we propose a flexible framework that can be used to model the assessment problems in different domains and scales. A fuzzy evaluation process in the proposed framework is investigated to deal with uncertainty and manage heterogeneous information in engineering evaluation processes.     

基于案例推理的层流冷却过程建模

针对具有非线性,参数时变,分布参数等综合复杂特性的热轧层流冷却过程,将机理建模方法与案例推理技术相结合,通过使用层流冷却过程中带钢的运行工况构造案例,在案例库中检索与其匹配的历史案例,利用实际工况的特征与匹配工况的特征经过推理给出当前工况的模型参数,从而确定层流冷却过程的动态模型.利用这一模型可以预测整个冷却过程中带钢的温度变化过程.通过某钢铁公司热轧层流冷却过程实际数据的实验比较表明所提出的建模方法是有效的.     

Complex Probabilistic Modeling with Recursive Relational Bayesian Networks

A number of representation systems have been proposed that extend the purely propositional Bayesian network paradigm with representation tools for some types of first-order probabilistic dependencies. Examples of such systems are dynamic Bayesian networks and systems for knowledge based model construction. We can identify the representation of probabilistic relational models as a common well-defined semantic core of such systems.Recursive relational Bayesian networks (RRBNs) are a framework for the representation of probabilistic relational models. A main design goal for RRBNs is to achieve greatest possible expressiveness with as few elementary syntactic constructs as possible. The advantage of such an approach is that a system based on a small number of elementary constructs will be much more amenable to a thorough mathematical investigation of its semantic and algorithmic properties than a system based on a larger number of high-level constructs. In this paper we show that with RRBNs we have achieved our goal, by showing, first, how to solve within that framework a number of non-trivial representation problems. In the second part of the paper we show how to construct from a RRBN and a specific query, a standard Bayesian network in which the answer to the query can be computed with standard inference algorithms. Here the simplicity of the underlying representation framework greatly facilitates the development of simple algorithms and correctness proofs. As a result we obtain a construction algorithm that even for RRBNs that represent models for complex first-order and statistical dependencies generates standard Bayesian networks of size polynomial in the size of the domain given in a specific application instance.     

Modeling Ontological Concepts of Locations with a Heterogeneous Cardinal Direction Model

Modeling human concepts of object locations is essential for the development of the systems and machines that collaborate with ordinary people on spatial tasks. This paper applies a heterogeneous cardinal direction model, called HCDM, to model human concepts of object locations with both directional and topological information in a 2D space. Using its ability we illustrate where and how an object is located as seen from another even if they have different spatial extensions. For generality, we adopt a set of formal spatial concepts defined in an existing spatial ontology called GUM and associate these concepts with the patterns identified by HCDM. We also discuss the converse and composition operations on HCDM patterns for qualitative spatial reasoning and compare it with other cardinal direction models.     

PSO并行优化LSSVR非线性黑箱模型辨识

针对非线性黑箱系统辨识中存在不确定性、高阶次,采用常规辨识方法建立其精确数学模型十分困难等问题,提出一种基于自适应粒子群算法的最小二乘支持向量机回归(PSO-LSSVR)非线性系统辨识方法.该方法采用2组自适应粒子群算法并行计算模型,分别利用自适应粒子群算法对LSSVR中的参数进行自动选取和矩阵迭代求解,既克服了传统LSSVR参数难以确定的缺点,提高了辨识精度,同时避免了复杂矩阵求逆运算,加快了计算速度.将该方法应用于船舶操纵性模型非线性系统辨识,仿真结果表明,由该方法得到的LSSVR能够有效地对系统进行建模,仿真精度高,结构简单,具有一定的理论推广意义.