Patent Application
20110040542
In industrial design, e.g. automotive design, the aesthetic styling (aesthetic design) has to be coupled with functional requirements (functional design) and performance measures from CAE (Computer Aided Engineering) systems, e.g. dynamic stability, aerodynamics, computational fluid dynamics (CFD), structural stability, etc. In the overall design process, functional constraints are often used to define the initial conceptual design which is then shaped by the designer according to some aesthetic requirements, e.g. based on the designer's artistic taste and/or on the overall brand design requirements. Traditionally, the aesthetic design phase involves clay models, which are nowadays augmented by CAD models, interactive immersive displays [1] and virtual clay systems [2]. After the aesthetic design phase, again functional requirements can alter the final design and shape.
However, both processes (aesthetic and functional design) are largely decoupled and handled by different groups of people (i.e. designers and engineers).
In general, the representations, i.e. the parametric descriptions of objects, are different for the aesthetic design process and the functional design process.
The use of surrogate or meta-models has been suggested previously in the context of design optimization without any aesthetic design phase (see e.g. [4,5,6]).
However, as will be explained later in greater detail, in the framework put forward in this patent surrogate models are embedded into the aesthetic design phase in order to enable a tight coupling between aesthetic design and functional design.
Document “Integrated modeling, finite-element analysis, and engineering design for thin-shell structures using subdivision” by F. Cirak et al (Division of Engineering and Applied Science, California Institute of Technology, Pasadena, Calif. 91125, USA, available online 20 Mar. 2002) describes geometric modeling and mechanical simulation of thin flexible structures, such as those found in the automotive and aerospace industries. The use of subdivision surfaces as a foundation for modeling, simulation, and design in a unified framework is described.
Document “Haptic function evaluation of multi-material part design” by Z. Yang et al (Computer-Aided Design, Volume 37, Issue 7 (June 2005), ISSN:0010-4485) describes haptic shape modeling for industrial and conceptual design. A real-time haptic interface of synthesized shape modeling and haptic function evaluation of product design for multi-material part is described.
In contrast to these documents, the invention discloses the combination of aesthetic design with meta-models, which approximate computational aided engineering calculations (CAE). Such calculations can be CFD and/or FEM methods. The integration of the meta-models is not trivial because the aesthetic process and the CAE process work on different representations of the given design. The meta-model adds a third representation.
The invention provides a method which allows aesthetic optimization of an object in a tight coupling with the functional optimization of the object. While these two processes are traditionally separated for the reason that the functional optimization of an object is a very complex and time consuming process, where the aesthetic optimization is a continuous and constant process, the invention teaches to integrate both these processes in a tandem-setup.
The (aesthetic) designer needs to constantly change the aesthetic appearance of the object and it hinders his work if, after every change of the aesthetic appearance of the object, the designer has to wait for the calculations of the functional performance values to be finished (this process, for example, uses computational fluid dynamics CFD). Also, waiting for the results of the calculations leads to a very time consuming design process.
The invention however, solves this problem by using an approximation model of the computer aided engineering (CAE) simulation which allows quickly approximating the CAE calculations and provides an immediate feedback to the designer on the current change. It is also possible to provide to the designer information of alternatives to the design decision which provide better functionality in respect to the functional quality values.
The invention allows a continuous modeling process of the object according to aesthetic measures while allowing direct feedback on its effect on the functional design based on the approximation model.
In brief, the invention works with three models: one for the aesthetic design process, one for the functional changes performed according to the functional quality values and one “meta-model”, the approximation model for the functional model, that allows to quickly approximate the changes performed to the functional model without actually running the full functional calculations
It is the object of the invention to propose a process that allows a tight coupling between the aesthetic and the functional design processes, thereby achieving an efficient and comprehensive approach for designing real-world objects which at the same time meet physical and aesthetic requirements. E.g. when designing cars, motorbikes and planes using the invention, the physical requirements can be e.g. minimizing weight and/or drag.
Thus the invention also allows the manufacturing of aesthetic real-world objects, which also satisfy functional criteria, which functional criteria can be expressed in terms of physical entities.
This object is achieved by means of the features of the independent claims. The dependent claims develop further the central idea of the present invention.
A first aspect of the invention relates to a method for providing designers direct feedback on the functional quality of their current aesthetic design of real-world objects, thus improving the design process and facilitating the manufacturing of aesthetic and functional real-world object.
The method comprising the following steps:
The invention also proposes a method comprising the following steps additional or alternative:
The method may comprise the additional or alternative step of:
The method may comprise the following steps:
The method may comprise additionally or alternatively at least one of the following steps:
The method may comprise additionally or alternatively at least one of the following steps:
The aesthetic representation of the design may be based on CAD data, while the optimization process will be performed based on a different functional representation, e.g. free form deformation [8] or NURBS [7].
The derivation of the functional quality of the aesthetic design which is required in the first process as well as in the second process including the additional optimization loop has to be very fast so that the designer receives direct and real-time feedback of the functional quality of the object (besides his own aesthetic judgment). Current CAE methods do not allow this fast feedback, therefore, models have to be employed, which represent a functional approximation of the CAE calculations. Examples of such models (which have been termed surrogates or meta-models or surrogate models in the context of functional design optimization [4]) are neural networks, Kriging (Gaussian) models, response surface models, polynomial models. Based on available CAE data that has been generated prior to the aesthetic design process (and which can also constantly be updated during the aesthetic design process), the model is generated using methods from e.g. neural network learning or mathematical statistics. Such models can then replace the costly CAE calculations. The models are very fast and can be used in real-time in direct interaction with the designer. The models can directly receive the aesthetic object representation, e.g. CAD data, as input or use their own model-dependent representation. In the latter case, a transformation has to be included from the aesthetic representation to the model representation.
Step d) may be done in order to change the aesthetic appearance of the design.
The physical signal may be a visual indication and/or a haptic feedback.
The invention also relates to computer software program product, implementing a method according to any of the preceding claims when run on a computing device.
The invention furthermore relates to a computer-assisted system for designing real-world objects, the system comprising the following steps:
Finally the invention relates to a computer-assisted system for designing real-world objects, the system comprising:
In an further aspect the invention relates to a computer-assisted system for integrating aesthetic and functional design processes for physical objects, the system may comprise:
The system may comprise additionally or alternatively at least one of:
A preferred embodiment of the present invention is now described with reference to the figures where like reference numbers indicate identical or functionally similar elements. Reference in the specification to “one embodiment” or to “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
Some portions of the detailed description that follows are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps (instructions) leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical, magnetic or optical signals capable of being stored, transferred, combined, compared and otherwise manipulated. It is convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. Furthermore, it is also convenient at times, to refer to certain arrangements of steps requiring physical manipulations of physical quantities as modules or code devices, without loss of generality.
However, all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or “determining” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system memories or registers or other such information storage, transmission or display devices.
Certain aspects of the present invention include process steps and instructions described herein in the form of an algorithm. It should be noted that the process steps and instructions of the present invention could be embodied in software, firmware or hardware, and when embodied in software, could be downloaded to reside on and be operated from different platforms used by a variety of operating systems.
The present invention also relates to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, application specific integrated circuits (ASICs), or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus. Furthermore, the computers referred to in the specification may include a single processor or may be architectures employing multiple processor designs for increased computing capability.
The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may also be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will appear from the description below. In addition, the present invention is not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any references below to specific languages are provided for disclosure of enablement and best mode of the present invention.
In addition, the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, the disclosure of the present invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the claims.
Further features, objects and advantages of the invention will become evident when reading the following detailed description of an embodiment, taken in conjunction with the figures of the enclosed drawings.
a is a general view of the modules of a first embodiment of a design system according to the invention where only a functional quality value is communicated to the user.
b is a modification of the system of
c shows details of the optimization module P1 of
a to 6c show examples of interfacing results of the functional quality estimation and/or functional optimization back to the user. 6a: displaying a quality index of an aesthetic design, 6b: colour encoding of favourable and unfavourable (according to the functional quality values) directions for the aesthetic design process, 6c: haptic encoding of favourable and unfavourable (according to the functional quality values) directions for the aesthetic design process.
To summarize, the invention proposes to at least partially merge the computer based (CAD, immersive interactive displays, virtual clay systems) aesthetic design phase with the functional design process e.g. from CAE systems. This makes the overall process more efficient, the aesthetic process more comprehensive, i.e. no changes are made to the styling after the aesthetic design process has been completed, and the integration of functional requirements easier and as a result more comprehensive. In order to allow such a tight integration of both processes and therefore to realize the described advantages, mainly two problems have to be solved. Firstly, the computation time required for the CAE analysis (e.g. aerodynamic parameters with computational fluid dynamics CFD, or dynamic stability) does not allow the online calculation of CAE based functional performance indices during the aesthetic based design process, i.e. while the stylist is constantly changing the shape of a design (e.g. an automotive), it is not possible to continuously calculate the quality indices for every shape. Secondly, if the performance indices for each shape are available (i.e. question one is solved), how can this information be conveyed to the stylist in a way that s/he (who does not necessarily have a strong technological background) can use this information most efficiently.
The problems formulated in the above section are solved in the following ways. In order to circumvent the time constraint, a model M1 will be used during the aesthetic design process instead of the true CAE calculations. This model serves a similar purpose as surrogate models during traditional design optimization. A variety of different model structures are conceivable, examples are neural networks, response surface models, polynomial models, Kriging (Gaussian) models. These models approximate the function of the CAE calculations. Since the model response time is very fast it can be used during the design process as an immediate feedback to the designer on the current shape as shown in
Additionally, a fast optimization process can be carried out using the model as a quality measure (denoted by process P1 in
In general, different representations of the object (i.e. its parametric description) will be used for the aesthetic design process, for the functional design process and for the model. When merging the different processes, interfaces between those representations are necessary. Representations suitable for the aesthetic design processes are usually determined by the computational tools used by the designers, a standard tool and the associate representations are CAD data. The functional representations have to be low dimensional and have to be suitable for computational changes of the design in the context of CAE systems like fluid dynamics. Since most CAE systems rely on a computational grid or mesh for the calculations, functional representations must either be able to adapt the computational grid of the CAE solver or they must be suitable for automatically generating new grids/meshes during the functional design process based on the current functional representation. NURBS [7] and free form deformation [8] representations have been shown to be very suitable functional representations. Model representations are usually low dimensional functional representations. Universal representations like STL representations [9] can be employed in order to switch between the three types of representations.
Therefore, in a typical embodiment of the invention, the model receives a parameterization of the shape as input, e.g. the control points of a NURBS representation or a Free Form Deformation representation, see e.g. [7, 8] or alternatively CAD representations. The output of the model would be a quality index/value or several quality indices/values that are used to functionally characterize the design (e.g. drag coefficients for aerodynamic optimization of automotive chassis).
The second problem on how to convey the information back to the designer can be solved in different ways. In the case of
Firstly, promising directions can be calculated from the current shape and the shapes produced by the optimization process P1, these directions can be color coded and displayed behind (left figure) or on (right figure) the current design (
The invention may find application in the design of any real-world object, but especially in the following fields: Land, Air and Sea vehicles, Automotive design, motorcycle design, aeronautic design, boat design, furniture design, industrial design.
CAD—computer aided design
CAE—computer aided engineering
CFD—computational fluid dynamics
Aesthetic design—a process involving a designer where an object is shaped according to the artistic taste of the designer and/or according to some brand specifics (e.g. automotive design, furniture design)
Functional design—a process where an object is shaped according to some objective physical quality measures provided by experiments (including computer experiments), e.g. minimization of drag, maximization of thermal resistance, maximization of crash resistance.
Aesthetic representation—a parametric description of an object that is most suitable for variations invoked by a human designer during the aesthetic design process, e.g. CAD data or digital clay data
Functional representation—a parametric description of an object that is most suitable for determining the physical quality measures of the object and/or for variations invoked by a computer program during an optimization process, e.g. free form deformation [8] or NURBS [7].
Model representation—a parametric description of an object that is most suitable for determining the physical quality measures of the object based on a specific model (e.g. a neural network). Often such a representation is a lower dimensional version of a functional representation.
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[2] SensAble Technologies. 3D Touch-enabled Modeling for Product Design, Digital Content Creation (DCC) & Fine Arts. http://www.sensable.com/industries-design-model.htm
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[4] Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. A
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[5] EP 1205877 A1 “Approximate fitness functions” of Honda Research Institute Europe GmbH
[6] EP 1557788 A1 “Reduction of fitness evaluations using clustering technique and neural network ensembles” of Honda Research Institute Europe GmbH
[7] Les Piegl and Wayne Tiller. The NURBS book. Springer, 1996.
[8] Stefan Menzel and Bernhard Sendhoff. Representing the change—free form deformation for evolutionary design optimization. In T. Yu, L. Davis, C. Baydar and R. Roy (Eds) Evolutionary Computation in Practice, 63-86, 2008.
[9] Lars Graening, Stefan Menzel, Martina Hasenjäger, Thomas Bihrer, Markus Olhofer and Bernhard Sendhoff. Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries. In Journal of Mathematical Modelling and Algorithms, 7 (4), 329-350, 2008.
Yang, Z., Lian, L., and Chen, Y. 2005. Haptic function evaluation of multi-material part design. Comput. Aided Des. 37, 7 (June 2005), 727-736.
Fehmi Cirak, Michael J. Scott, Erik K. Antonsson, Michael Ortiz, Peter Schroder, Integrated modeling, finite-element analysis, and engineering design for thin-shell structures using subdivision, Computer-Aided Design, Volume 34, Issue 2, February 2002, Pages 137-148, ISSN 0010-4485, DOI: 10.1016/S0010-4485(01)00061-6.
| Number | Date | Country | Kind |
|---|---|---|---|
| 09 167 789.8 | Aug 2009 | EP | regional |
