Design of heterogeneous turbine blade

Constantly rising operating pressure and temperature in turbine drivers push the material capabilities of turbine blades to the limit. The recent development of heterogeneous objects by layered manufacturing offers new potentials for the turbine blades. In heterogeneous turbine blades, multiple materials can be synthesized to provide better properties than any single material. A critical task of such synthesis in turbine blade design is an effective design method that allows a designer to design geometry and material composition simultaneously.This paper presents a new approach for turbine blade design, which ties B-spline representation of a turbine blade to a physics (diffusion) process. In this approach, designers can control both geometry and material composition. Meanwhile, material properties are directly conceivable to the designers during the design process. The designer's role is enhanced from merely interpreting the optimization result to explicitly controlling both material composition and geometry according to the acquired experience (material property constraints).The mathematical formulation of the approach includes three steps: using B-spline to represent the turbine blade, using diffusion equation to generate material composition variation, using finite element method to solve the constrained diffusion equation. The implementation and examples are presented to validate the effectiveness of this approach for heterogeneous turbine blade design.     

Modeling complex heterogeneous objects with non-manifold heterogeneous cells

This paper presents a new approach to model complex heterogeneous objects with simultaneous geometry intricacies as well as complex material distributions. Different from most of the existing approaches, which utilize manifold B-Rep and the assembly representations, the proposed scheme takes advantage of the non-manifoldcellular representations to model the geometries of the heterogeneous objects. With the aid of the cell adjacency information and attribute based reasoning, complex, smooth and versatile material distributions can be defined upon the intricate geometries. Compared with other similar approaches, the proposed scheme (1) generates heterogeneous object models with higher data consistencies and lower redundancies; (2) naturally avoids unnecessary/repetitive computations and thus improves computation efficiencies; (3) represents versatile material variations/distributions using different heterogeneous feature tree (HFT) structures. The detailed representation, associated algorithms and a prototype software package are presented. Example heterogeneous objects modeled with the proposed approach are provided.     

Constructive sculpting of heterogeneous volumetric objects using trivariate B-splines

This paper deals with modeling heterogeneous volumetric objects as point sets with attributes using trivariate B-splines. In contrast to homogeneous volumes with uniform distribution of material and other properties, a heterogeneous volumetric object has a number of variable attributes assigned at each point. An attribute is a mathematical model of an object property of an arbitrary nature (material, photometric, physical, statistical, etc.). In our approach, the function representation (FRep) is used as the basic model for both object geometry and attributes represented independently using real-valued scalar functions of point coordinates. While FRep directly defines object geometry, for an attribute it specifies a space partition used to define the attribute function. We propose a volume sculpting scheme with multiresolution capability based on trivariate B-spline functions to define both object geometry and its attributes. A new trivariate B-spline primitive is proposed that can be used as a leaf in an FRep constructive tree. An interactive volume modeler based on trivariate B-splines and other simple primitives is described, with a real-time repolygonization of the surface during modeling. We illustrate that the space partition obtained in the modeling process can be applied to define attributes for the objects with an arbitrary geometry model such as BRep or homogeneous volume models.     

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.     

A B-spline based framework for volumetric object modeling

With the recent development of Iso-geometric Analysis (IGA) (Cottrell et al., 2009) and advanced manufacturing technologies employing heterogeneous materials, such as additive manufacturing (AM) of functionally graded material, there is a growing emerging need for a full volumetric representation of 3D objects, that prescribes the interior of the object in addition to its boundaries. In this paper, we propose a volumetric representation (V-rep) for geometric modeling that is based on trimmed B-spline trivariates and introduce its supporting volumetric modeling framework. The framework includes various volumetric model (V-model) construction methods from basic non-singular volumetric primitives to high level constructors, as well as Boolean operations’ support for V-models. A V-model is decomposed into and defined by a complex of volumetric cells (V-cells), each of which can also represent a variety of additional varying fields over it, and hence over the entire V-model. With these capabilities, the proposed framework is able of supporting volumetric IGA needs as well as represent and manage heterogeneous materials for AM. Further, this framework is also a seamless extension to existing boundary representations (B-reps) common in all contemporary geometric modeling systems, and allows a simple migration of existing B-rep data, tools and algorithms. Examples of volumetric models constructed using the proposed framework are presented.     

Computer-aided design of porous artifacts

Heterogeneous structures represent an important new frontier for 21st century engineering. Human tissues, composites, ‘smart’ and multi-material objects are all physically manifest in the world as three-dimensional (3D) objects with varying surface, internal and volumetric properties and geometries. For instance, a tissue engineered structure, such as bone scaffold for guided tissue regeneration, can be described as a heterogeneous structure consisting of 3D extra-cellular matrices (made from biodegradable material) and seeded donor cells and/or growth factors.The design and fabrication of such heterogeneous structures requires new techniques for solid models to represent 3D heterogeneous objects with complex material properties. This paper presents a representation of model density and porosity based on stochastic geometry. While density has been previously studied in the solid modeling literature, porosity is a relatively new problem. Modeling porosity of bio-materials is critical for developing replacement bone tissues. The paper uses this representation to develop an approach to modeling of porous, heterogeneous materials and provides experimental data to validate the approach. The authors believe that their approach introduces ideas from the stochastic geometry literature to a new set of engineering problems. It is hoped that this paper stimulates researchers to find new opportunities that extend these ideas to be more broadly applicable for other computational geometry, graphics and computer-aided design problems.     

Simultaneous Surface Approximation and Segmentation of Complex Objects

Deformable models represent a useful approach to approximate objects from collected data points. We propose to augment the basic approaches designed to handle mostly compact objects or objects of known topology.Our approach can fit simultaneously more than one curve or surface to approximate multiple topologically complex objects by using (1) the residual data points, (2) the badly fitting parts of the approximating surface, and (3) appropriate Boolean operations. In 2-D, B-snakes [3] are used to approximate each object (pattern). In 3-D, an analytical surface representation, based on the elements detected, is presented. The global representation of a 3-D object, in terms of elements and their connection, takes the form of B-spline and Bézier surfaces. A Bézier surface is used to connect different elements, and the connecting surface itself conforms to the data points nearby through energy minimization. This way, aG¹continuity surface is achieved for the underlying 3-D object.We present experiments on synthetic and real data in 2-D and 3-D. In these experiments, multiple complex patterns and objects with through holes are segmented. The system proceeds automatically without human interaction or any prior knowledge of the topology of the underlying object.     

Feature-based design and material blending for free-form heterogeneous object modeling

In this paper, a new feature-based method is proposed to represent and design heterogeneous objects. Material governing features are defined to control material composition inside the objects. Interrelations between the material governing features and material attributes are established in the design process and retained in the object model. Free-form B-spline functions are used to represent complex shapes of geometry and material features. A new material feature blending method is used to determine continuous material variation. To obtain the best material features, an optimization problem is constructed based on the object's functional requirements. Variant models are easily generated by changing the geometric and material features using the constraints between them. Implementation and examples are also presented in this paper.     

SplineLearner: Generative learning system of design constraints for models represented using B-spline surfaces

Product design involves a computer-aided design (CAD) model with its design (dimensional) parameters. A generative design (GD) system can then be utilized to generate new designs by modifying these parameters. There is a need for a GD system to determine the visual validity of a design that is obtained after parametric modification. In this context, this paper introduces an approach to learn visual (i.e., design) constraints of a CAD model (represented using B-spline surfaces) by means of user feedbacks. A deformation technique (utilizing modification and limit curves) for B-spline surfaces is first introduced, which involves a few design (deformation) parameters. Via a generative learning process, the proposed system, SplineLearner, generates random designs, which are shown to user(s) for visual validity classifications. In a machine learning step, a mathematical model is computed that can perform prediction for a design to be valid or not. The mathematical model is also integrated into SplineLearner (after some user interactions) to prevent imbalances between the numbers of valid and invalid designs. As a proof of concept, B-spline surface models of a car body parts (hood, roof, side and trunk) are utilized, and two user studies are conducted to demonstrate the efficacy of the proposed method.     

Direct extraction of surface meshes from implicitly represented heterogeneous volumes

This paper describes a novel algorithm to extract surface meshes directly from implicitly represented heterogeneous models made of different constituent materials. Our approach can directly convert implicitly represented heterogeneous objects into a surface model separating homogeneous material regions, where every homogeneous region in a heterogeneous structure is enclosed by a set of two-manifold surface meshes. Unlike other discretization techniques of implicitly represented heterogeneous objects, the intermediate surfaces between two constituent materials can be directly extracted by our algorithm. Therefore, it is more convenient to adopt the surface meshes from our approach in the boundary element method (BEM) or as a starting model to generate volumetric meshes preserving intermediate surfaces for the finite element method (FEM). The algorithm consists of three major steps: firstly, a set of assembled two-manifold surface patches coarsely approximating the interfaces between homogeneous regions are extracted and segmented; secondly, signed distance fields are constructed such that each field expresses the Euclidean distance from points to the surface of one homogeneous material region; and finally, coarse patches generated in the first step are dynamically optimized to give adaptive and high-quality surface meshes. The manifold topology is preserved on each surface patch.     

A hierarchical representation for heterogeneous object modeling

A hierarchical representation for heterogeneous object modeling is presented in this paper. To model a heterogeneous object, Boundary representation is used for geometry representation, and a novel Heterogeneous Feature Tree (HFT) structure is proposed to represent the material distributions. HFT structure hierarchically organizes the material variation dependency relationships and is intuitive in modeling different types of material gradations. Based on the HFT structure, a recursive material evaluation algorithm is proposed to dynamically evaluate the material compositions at a specific location. Such a hierarchical representation guarantees complex material gradations and the user's design intent can be intuitively represented. Example heterogeneous objects modeled with this scheme are provided and potential applications are discussed.     

Deformable models for laparoscopic surgery simulation

This paper introduces a method for handling deformation in interactive, real time computer graphics simulations which involve deformable objects and require a high degree of visual realism. Our proposal, the virtual structure, is a “divide and conquer” approach, which combines a novel physical model with a geometric modelling utilizes the theory of elasticity and Newtonian mechanics, applied by a numerical method, the finite element method. Using different levels of structural resolution for global and local or collision with other objects. The geometric modelling uses the physical structure as a set of control points and produces a fine polygonal mesh generated by a B-spline surface. In order to demonstrate the method we have modelled the gallbladder as a spherical membrane containing liquid, in an interactive simulated environment for laporoscopic cholecystectomy.     

Abstraction hierarchies in top-down design

This paper describes a program design discipline that has successfully produced well-modularized programs. The basic approach is to apply, in a uniform way, the concepts of data and procedural abstraction in a top-down decomposition during the initial programming-in-the-large phase of construction. This combination of data and procedural abstraction, called hybrid abstraction, views the system as composed almost entirely of abstract objects. The resulting structural design is partially expressed as a syntactic specification for a set of modules (a module being a set of objects) having no directly shared global data. In addition to the syntactic specification, the design expresses the abstract type decomposition and the structural relationships of the modules. Three relations on the set of modules define the hierarchies is called by, implements, and obtains resources from. These relations define the discipline and characterize the class of designs possible. Modules in practice are used in two different ways: single-instance use and multiple-instance use. Abstract objects can be of two different kinds: collection objects and singular objects. The relationships of these variations in module construction are illustrated. Three moderately large examples are shown. euclid is used to illustrate the discipline.     

Equal distance offset approach to representing and process planning for solid freeform fabrication of functionally graded materials

This paper deals with the representation and process planning for solid freeform fabrication (SFF) of 3D functionally graded material (FGM) objects. A novel approach of representation and process planning for SFF of FGM objects, termed as equal distance offset (EDO), is proposed. In EDO, a neutral arbitrary 3D CAD model is adaptively sliced into a series of 2D layers. Within each layer, 2D material gradients are designed and represented via dividing the 2D shape into several sub-regions enclosed by iso-composition contours. If needed, the material composition gradient within each of the sub-regions can be further specified by applying the equal distance offset algorithm to each sub-region. Using this approach, an arbitrary-shaped 3D FGM object with linear or non-linear composition gradients can be represented and fabricated via suitable SFF machines.     

Material-solid modeling of human body: A heterogeneous B-spline based approach

Human body is a natural heterogeneous object optimized in its structure and composition by natural processes over years of evolution. In this paper, B-spline solid representation method is extended to represent material composition to develop a heterogeneous model of the human body. Two different approaches, namely surface fairing and surface fit, are used to create a slice by slice model from CT scan data. Both the approaches are compared for different regression parameters. This methodology has the potential to represent internal body details accurately with fewer digital input data,with applications in FEM analysis, freeform-fabrication and tissue engineering.     

A novel CACD/CAD/CAE integrated design framework for fiber-reinforced plastic parts

This work presents a novel CACD/CAD/CAE integrated framework for design, modeling, and optimization of fiber-reinforced plastic parts, which can greatly enhance the current design practice by realizing partial automation and multi-stage optimization. To support this framework, a new heterogeneous feature model (HFM) has been developed to model the fiber-reinforced objects and to be transferred between engineering modules. To be specific, the CACD (computer-aided conceptual design) module employs the level-set structure and material optimization to produce the initial design with thickness control, and also the initial HFM; the CAD (computer-aided design) module allows manual editing on the HFM to reflect various design intents; then, the injection molding CAE (computer-aided engineering) simulates the manufacturing process, and the response surface method (RSM) is applied to optimize the process parameters of gate location, injection flow rate, mold temperature and melt temperature, to approach the manufactured fiber orientation distribution close to the optimized result produced by the CACD module; besides, the structural analysis CAE module generates the mechanical performance result to support the CACD module, as well as to validate the final design. By applying this framework, the final structural design including the fiber orientation distribution, will perform better in mechanical properties, and consume less matrix and fiber materials; besides, the design maturity can be approached in shorter time. To prove the effectiveness, a plastic gripper design will be comprehensively studied.     

A level-set based variational method for design and optimization of heterogeneous objects

A heterogeneous object is referred to as a solid object made of different constituent materials. The object is of a finite collection of regions of a set of prescribed material classes of continuously varying material properties. These properties have a discontinuous change across the interface of the material regions. In this paper, we propose a level-set based variational approach for the design of this class of heterogeneous objects. Central to the approach is a variational framework for a well-posed formulation of the design problem. In particular, we adapt the Mumford-Shah model which specifies that any point of the object belongs to either of two types: inside a material region of a well-defined gradient or on the boundary edges and surfaces of discontinuities. Furthermore, the set of discontinuities is represented implicitly, using a multi-phase level set model. This level-set based variational approach yields a computational system of coupled geometric evolution and diffusion partial differential equations. Promising features of the proposed method include strong regularity in the problem formulation and inherent capabilities of geometric and material modeling, yielding a common framework for optimization of the heterogeneous objects that incorporates dimension, shape, topology, and material properties. The proposed method is illustrated with several 2D examples of optimal design of multi-material structures and materials.     

NURBS surface fitting using orthogonal coordinate transform for rapid product development

Constructing a CAD model from a physical model plays a key role in some rapid product development processes. Presented in the paper is a method of fitting NURBS surfaces for rotational freeform shapes: (1) cloud-of-points data (COP-data) representing a rotational freeform shape are transformed into an orthogonal coordinate system, (2) a single-valued B-spline surface is fitted to the transformed data, and (3) the resulting B-spline surface is converted to a 3D NURBS surface by applying a symbolic product operation with a quadratic NURBS base-geometry. Compared to the existing ‘direct’ fitting methods, the proposed method has some distinctive advantages: it provides a natural means to parameterization, enables to recover exact NURBS geometry when the COP-data represent a true surface-of-revolution, and allows an easy point-membership classification for NURBS-bounded solid objects.     

An end-to-end neural network for detecting hidden people in images based on multiple attention network

Camouflaged people like soldiers on the battlefield or even camouflaged objects in the natural environments are hard to be detected because of the strong resemblances between the hidden target and the background. That’s why seeing these hidden objects is a challenging task. Due to the nature of hidden objects, identifying them require a significant level of visual perception. To overcome this problem, we present a new end-to-end framework via a multi-level attention network in this paper. We design a novel inception module to extract multi-scale receptive fields features aiming at enhancing feature representation. Furthermore, we use a dense feature pyramid taking advantage of multi-scale semantic features. At last, to locate and distinguish the camouflaged target better from the background, we develop a multi-attention module that generates more discriminative feature representation and combines semantic information with spatial information from different levels. Experiments on the camouflaged people dataset show that our approach outperformed all state-of-the-art methods.