Knowledge representation framework for interactive capture and management of reflection process in product concepts development

A design process can be characterized by reflection-in-action; that is, the process consists of a series of problem solving activities and each is embodied with a problem and a solution. In this process, a designer represents a hypothetical concept on each design alternative, deploys and verifies the concept from multiple viewpoints considering other alternatives, and modifies it. An advanced integrated design environment should be based on a representation framework that embodies this process of reflection in concept development, which usually remains in the realm of the designer’s tacit knowledge. This paper proposes a knowledge representation framework for an integrated design environment, named DRIFT (Design Representation Integration Framework of Three layers), which interactively captures and manages reflection processes of generating and verifying design concepts. The core of DRIFT is a three-layered design process model of actions, operations, and argumentation. This model integrates various design tools and captures performed design activities. The action level captures the sequence of design operations. The model operation level captures the transition of design states, recording a design snapshot over design tools, which are integrated through ontology-based representation of design concepts. The argumentation level captures the process of defining problems and corresponding alternative solutions. Integration of three levels with a template of design operation extracted from Design-For-X approaches enables a proposed system to interactively and efficiently capture and manage the process of design concept development through operations over design tools. A design operation template works to limit the number of links between the three levels remaining easy to manage its semantics. This paper also demonstrates a prototype implementation of DRIFT and its application to conceptual design of a small mechatronic system with a system modeling method. The paper concludes with a discussion of some future issues.     

Neural networks and response surface polynomials for design of vehicle joints

Typically, design of a complex system starts by setting targets for its performance characteristics. Then, design engineers cascade these targets to the components and design the components to meet these targets. It is important to have efficient tools that check if a set of performance targets for a component corresponds to a feasible design and determine the dimensions and mass of this design. This paper describes a method to develop tools that relate response parameters that describe the performance of a component to the physical design variables that specify its geometry. Neural networks and response surface polynomials are used to rapidly predict the performance characteristics of the components given the component dimensions. The method is demonstrated on design of an automotive joint. The paper compares neural networks and response surface polynomials and shows that they are almost equally accurate for the problem considered.     

On querying simple conceptual graphs with negation

We consider basic conceptual graphs, namely simple conceptual graphs (SGs), which are equivalent to the existential conjunctive positive fragment of first-order logic. The fundamental problem, deduction, is performed by a graph homomorphism called projection. The existence of a projection from a SG Q to a SG G means that the knowledge represented by Q is deducible from the knowledge represented by G. In this framework, a knowledge base is composed of SGs representing facts and a query is itself a SG. We focus on the issue of querying SGs, which highlights another fundamental problem, namely query answering. Each projection from a query to a fact defines an answer to the query, with an answer being itself a SG. The query answering problem asks for all answers to a query.

This paper introduces atomic negation into this framework. Several understandings of negation are explored, which are all of interest in real world applications. In particular, we focus on situations where, in the context of incomplete knowledge, classical negation is not satisfactory because deduction can be proven but there is no answer to the query. We show that intuitionistic deduction captures the notion of an answer and can be solved by projection checking. Algorithms are provided for all studied problems. They are all based on projection. They can thus be combined to deal with several kinds of negation simultaneously. Relationships with problems on conjunctive queries in databases are recalled and extended. Finally, we point out that this discussion can be put in the context of semantic web databases.     

Multiobjective controller design handling human preferences

Trends in controller design point to the integration of several objectives to achieve new performances. Moreover, it is easy to set the controller design problem as an optimization problem. Therefore, future improvements are likely to be based on the adequate formulation and resolution of the multiobjective optimization problem. The multiobjective optimization strategy called physical programming provides controller designers with a flexible tool to express design preferences with a ‘physical’ meaning. For each objective (settling time, overshoot, disturbance rejection, etc.) preferences are established through categories such as desirable, tolerable, unacceptable, etc. to which numerical values are assigned. The problem is normalized and converted to a single-objective optimization problem but normally it results in a multimodal problem very difficult to solve. Genetic algorithms provide an adequate solution to this type of problems and open new possibilities in controller design and tuning.     

Evolutionary Design Systems and Generative Processes

Design tools that aim not only to analyse and evaluate, but also to generate and explore alternative design proposals are now under development. An evolutionary paradigm is presented as a basis for creating such tools. First, the evolutionary paradigm is shown to be the only successful design system on which this new phase of design tool could be based. Secondly, any characterisation of design as a search problem is argued to be a serious misconception. Instead it is proposed that evolutionary design systems should be seen as generative processes that are able to evaluate their own output. Thirdly, a generic framework for generative evolutionary design systems is presented. Fourth, the generative process is introduced as a key element within this generic framework. The role of the environment within this process is fundamental. Finally, the direction of future research within the evolutionary design paradigm is discussed with possible short and long term goals being presented.     

Ontology-based data integration and decision support for product e-Design

Currently, computer-based support tools are widely used to facilitate the design process and have the potential to reduce design time, decrease product cost and enhance product quality. Although there are promising information systems to manage product lifecycle and product-related data, including product data management (PDM) and product lifecycle management (PLM), significant limitations still exist, where information required to make decisions may not be available, may be lacking consistency, and may not be expressed in a general way for sharing between systems. Moreover, there remains little support for decision making that considers multiple complex technical and economical criteria, relations, and objectives in product design. To address these problems, this paper presents a framework for an ontology-based data integration and decision support environment for e-Design. The framework can guide designers in the design process, can make recommendations, and can provide decision support for parameter adjustments.     

Interdisciplinary communication medium for collaborative conceptual building design

Collaborative conceptual design involves intensive cross-disciplinary communication of design concepts and decisions. Difficulty in producing and expressing such information leads to extensive delays, miscommunication and confusion, which often have an impact upon the quality of the final design and the time required to achieve design concensus. Computer tools provide little support for the special needs for representation and reasoning posed by cross-disciplinary communication in collaborative conceptual building design. By building upon design theory, literature and observations for a case study of an actual building design project, we identify and devise computational strategies for addressing these needs. Our objective is to help improve the communication among design team members. Our test case focuses on the communication between architects and structural engineers. We propose a conceptual framework for interdisciplinary communication to support collaborative conceptual design and present a prototype called Interdisciplinary Communication Medium (ICM). Our conceptualization suggests that designers propose a shared form model, interpret the form model into discipline models, critique the discipline form models to derive behavior and compare it to function, and explain the results to other members of the team. We present this propose-interpret-critique-explain paradigm as a communication cycle for collaborative conceptual building design. We explore and test the conceptualization by modeling it with an experimental software prototype, ICM, that integrates graphic representations and AI reasoning about, the evolving building design. ICM provides a graphic environment as the central interface to reasoning tools to support collaborative design.     

The application of ubiquitous multimodal synchronous data capture in CAD

Design is an interactive and iterative process where the designer’s skills and knowledge are fused with emotive rationales aided by design tools. A design solution is thus influenced by the designer’s creativity, experience and emotional perception. Consequently, there is a need within computer aided design (CAD) research for ubiquitous tools to capture the affective states of engineers during design activities to further understand the product design process.This paper proposes a generic framework for ubiquitous multimodal synchronous data capture, based around the capture of CAD system activities, to monitor and log a variety of inputs, interactions, biophysical data and design solutions with a view to providing meta and chronological performance data for post design task analysis. The framework has been employed in two use cases namely, a CAD station activity and a collaborative design review. The results of these trials validated the architecture and use of the ubiquitous data capture approach demonstrating the practical application of time-phased data capture, analysis and the subsequent output of metadata in CAD environments providing a new perspective on, and a new way of investigating CAD-based design activities.This research also extrapolates the framework’s usefulness into future CAD and PLM systems by arguing why and how they need to adopt such ubiquitous platforms. It also subjectively points to potential opportunities and issues that might arise when implementing the ubiquitous multimodal metadata architecture in a real-life environment.     

Learning domain ontologies for semantic Web service descriptions

High quality domain ontologies are essential for successful employment of semantic Web services. However, their acquisition is difficult and costly, thus hampering the development of this field. In this paper we report on the first stage of research that aims to develop (semi-)automatic ontology learning tools in the context of Web services that can support domain experts in the ontology building task. The goal of this first stage was to get a better understanding of the problem at hand and to determine which techniques might be feasible to use. To this end, we developed a framework for (semi-)automatic ontology learning from textual sources attached to Web services. The framework exploits the fact that these sources are expressed in a specific sublanguage, making them amenable to automatic analysis. We implement two methods in this framework, which differ in the complexity of the employed linguistic analysis. We evaluate the methods in two different domains, verifying the quality of the extracted ontologies against high quality hand-built ontologies of these domains.

Our evaluation lead to a set of valuable conclusions on which further work can be based. First, it appears that our method, while tailored for the Web services context, might be applicable across different domains. Second, we concluded that deeper linguistic analysis is likely to lead to better results. Finally, the evaluation metrics indicate that good results can be achieved using only relatively simple, off the shelf techniques. Indeed, the novelty of our work is not in the used natural language processing methods but rather in the way they are put together in a generic framework specialized for the context of Web services.     

Development of a framework for truss-braced wing conceptual MDO

The paper describes the development of a multidisciplinary design optimization framework for conceptual design of truss-braced wing configurations. This unconventional configuration requires specialized analysis tools supported by a modular and flexible framework to accommodate different configurations. While the previous framework developed at Virginia Tech was a monolithic Fortran-77 code, the need for more flexibility for complex truss-braced wing configurations was addressed by the development of this new framework, which is based on Phoenix Integration ModelCenter^TM environment. The framework uses updated structural and aerodynamic design modules that enable a more general geometry definition. The new framework, thus, provides a foundation for future design concepts, especially multi-member truss-braced wing configurations. The fuel saving potential of these truss-braced wing configurations is presented by comparing different truss designs with gradually increased level of complexity.     

E-Science in the classroom – Towards viability

E-Science has the potential to transform school science by enabling learners, teachers and research scientists to engage together in authentic scientific enquiry, collaboration and learning. However, if we are to reap the benefits of this potential as part of everyday teaching and learning, we need to explicitly think about and support the work required to set up and run e-Science experiences within any particular educational context. In this paper, we present a framework for identifying and describing the resources, tools and services necessary to move e-Science into the classroom together with examples of these. This framework is derived from previous experiences conducting educational e-Science projects and systematic analysis of the categories of ‘hidden work’ needed to run these projects. The articulation of resources, tools and services based on these categories provides a starting point for more methodical design and deployment of future educational e-Science projects, reflection on which can also help further develop the framework. It also points to the technological infrastructure from which such tools and services could be built. As such it provides an agenda of work to develop both processes and technologies that would make it practical for teachers to deliver active, and collaborative e-Science learning experiences on a larger scale within and across schools. Routine school e-Science will only be possible if such support is specified, implemented and made available to teachers within their work contexts in an appropriate and usable form.     

Clustering factor estimation for totally clustered attributes

Cost models based on the clustering factor (CF) of the attributes have been proposed and shown to be attractive for block access estimation in databases, thanks to their accuracy and economy of use. While query optimizers can use the actual CFs, measured from the data, physical design methods and tools must rely on estimates before the data are stored.

In this paper we present a CF estimation procedure which can be applied to totally clustered attributes (e.g. ordered attributes). Simple and accurate approximations of the derived formulas are also introduced.

Simulations show the accuracy of the proposed CF estimates and the improvment in their behaviour compared to previously published estimates. Reliability for physical design of cost models based on the CF in the presence of a skewed data distribution is also discussed.     

Sensor scheduling in continuous time

Let N be the number of available sensor sources. Noisy observations of an underlying state process are available for these N sources. We consider the continuous time sensor scheduling problem in which N₁ of these N sources are to be chosen to collect data at each time point. This sensor scheduling problem (with switching costs and switching constraints) is formulated as a constrained optimal control problem. In this framework, the controls represent the sensors that are chosen at a particular time. Thus, the control variables are constrained to take values in a discrete set, and switchings between sensors can occur in continuous time. By incorporating recent results on discrete valued optimal control, we show that this problem can be transformed into an equivalent continuous optimal control problem. In this way, we obtain the sensor scheduling policy as well as the associated switching times.     

Truss topology optimization with discrete design variables—Guaranteed global optimality and benchmark examples

This paper considers the problem of optimal truss topology design subject to multiple loading conditions. We minimize a weighted average of the compliances subject to a volume constraint. Based on the ground structure approach, the cross-sectional areas are chosen as the design variables. While this problem is well-studied for continuous bar areas, we consider in this study the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single available bar area, i.e., a 0/1 problem. In contrast to the heuristic methods considered in many other approaches, our goal is to compute guaranteed globally optimal structures. This is done by a branch-and-bound method for which convergence can be proven. In this branch-and-bound framework, lower bounds of the optimal objective function values are calculated by treating a sequence of continuous but non-convex relaxations of the original mixed-integer problem. The main effect of using this approach lies in the fact that these relaxed problems can be equivalently reformulated as convex problems and, thus, can be solved to global optimality. In addition, these convex problems can be further relaxed to quadratic programs for which very efficient numerical solution procedures exist. By exploiting this special problem structure, much larger problem instances can be solved to global optimality compared to similar mixed-integer problems. The main intention of this paper is to provide optimal solutions for single and multiple load benchmark examples, which can be used for testing and validating other methods or heuristics for the treatment of this discrete topology design problem.     

Computer support for mechatronic control system design

This paper discusses the demands for proper tools for computer aided control system design of mechatronic systems and identifies a number of tasks in this design process. Real mechatronic design, involving input from specialists from varying disciplines, requires that the system can be represented in multiple views. Several tools are already available but there are still substantial shortcomings. The paper gives indications about the developments needed to come to better design tools in the future. A specific example is worked out in more detail, i.e., automated performance assessment of mechatronic motion systems during the conceptual design stage.     

Sequence Surveyor: leveraging overview for scalable genomic alignment visualization

In this paper, we introduce overview visualization tools for large-scale multiple genome alignment data. Genome alignment visualization and, more generally, sequence alignment visualization are an important tool for understanding genomic sequence data. As sequencing techniques improve and more data become available, greater demand is being placed on visualization tools to scale to the size of these new datasets. When viewing such large data, we necessarily cannot convey details, rather we specifically design overview tools to help elucidate large-scale patterns. Perceptual science, signal processing theory, and generality provide a framework for the design of such visualizations that can scale well beyond current approaches. We present Sequence Surveyor, a prototype that embodies these ideas for scalable multiple whole-genome alignment overview visualization. Sequence Surveyor visualizes sequences in parallel, displaying data using variable color, position, and aggregation encodings. We demonstrate how perceptual science can inform the design of visualization techniques that remain visually manageable at scale and how signal processing concepts can inform aggregation schemes that highlight global trends, outliers, and overall data distributions as the problem scales. These techniques allow us to visualize alignments with over 100 whole bacterial-sized genomes.