Gianfranco La Rocca

Knowledge based engineering: Between AI and CAD. Review of a language based technology to support engineering design

Knowledge based engineering (KBE) is a relatively young technology with an enormous potential for engineering design applications. Unfortunately the amount of dedicated literature available to date is quite low and dispersed. This has not promoted the diffusion of KBE in the world of industry and academia, neither has it contributed to enhancing the level of understanding of its technological fundamentals. The scope of this paper is to offer a broad technological review of KBE in the attempt to fill the current information gap. The artificial intelligence roots of KBE are briefly discussed and the main differences and similarities with respect to classical knowledge based systems and modern general purpose CAD systems highlighted. The programming approach, which is a distinctive aspect of state-of-the-art KBE systems, is discussed in detail, to illustrate its effectiveness in capturing and re-using engineering knowledge to automate large portions of the design process. The evolution and trends of KBE systems are investigated and, to conclude, a list of recommendations and expectations for the KBE systems of the future is provided.

DEVELOPMENT OF AN ICAD GENERATIVE MODEL FOR BLENDED WING BODY AIRCRAFT DESIGN

Aim of the EC sponsored project ‘Multidisciplinary Design and Optimization of Blended Wing-Bodies’ is the development and application of a fully integrated Computer Design Engine (CDE). TU Delft contributed to the project with the development of a Blended Wing-Body Multi-Model Generator, which is able to supply geometries and data to the analysis software, either COTS or tailor made, used by the various disciplinary groups in the project team (aerodynamics, structures, stability and control etc.). A full parametric definition of the aircraft has been implemented in the KTI ICAD environment. The ICAD Multi-Model Generator (or Generative Model) holds the ‘knowledge’ of the Blended Wing Body aircraft, such that consistent models can be generated, at different leve ls of fidelity, suitable for the various disciplines involved in the CDE. A large range of aircraft variants can be generated, just editing the values of the aircraft parameters, which are all collected in one single input file. The optimiser can change the parameters value within the optimisation loop, without the need for user interactive sessions. The generative model can be run in batch mode, even from remote sites.

Knowledge-Based Engineering Approach to Support Aircraft Multidisciplinary Design and Optimization

This paper introduces the concept of the design and engineering engine, which is a modular computational design system to support distributed multidisciplinary design and optimization of aircraft. In particular, this paper discusses the architecture and the functionalities of the multimodel generator module, which is a knowledge-based engineering application developed to model the geometry of both conventional and novel aircraft configurations and to automate the generation of dedicated models for low- and high-fidelity analysis tools. This paper demonstrates the capability of the knowledge-based engineering approach to record and automate complex engineering design processes, such as the generation of models for finite element analysis. The time reduction gained by process automation, together with the enabled use of high-fidelity analysis tools earlier in the design process, constitute significant achievements toward a broader exploitation of the multidisciplinary design and optimization methodology, as well as the development of novel aircraft configurations.

A Knowledge Based Engineering Approach to Support Automatic Generation of FE Models in Aircraft Design

Multidisciplinary Design and Optimisation (MDO) is acknowledged as the design methodology with the largest potential for helping aircraft industry pushing further the limits of current design. Nevertheless, large part of this potential is at date still unexploited. The difficulties associated with the management of the design process across distributed teams of specialists and the use High Fidelity analysis tools early in the design process have been indicated by the MDO community as two of the most relevant points of attention. The designer’ wish of evaluating many design configurations, including creative and innovative design solutions have been always frustrated by the huge amount of work required to set up the dedicated models required by the various analysis tools, such as FE and CFD. The lack of flexibility and robustness typical of current CAD systems and analysis tools has been the main obstacle to the full automation of the design verification process. In this paper, the use of Knowledge Based Engineering is proposed as an innovative approach to support designers both during the creative part of the design process and the design verification phase using High fidelity analysis tools. The development of a modular computational design framework, addressed as Design and Engineering Engine, is introduced here. In particular, the functionalities of the aircraft parametric modeling module (the Multi Model Generator) are discussed in this paper and it is shown how the implemented approach makes possible to automate the generation of suitable models for FE analysis.

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering: Sobieszczanski-Sobieski/Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Multidisciplinary Design Optimization supported by Knowledge Based Engineering supports engineers confronting this daunting and new design paradigm. It describes methodology for conducting a system design in a systematic and rigorous manner that supports human creativity to optimize the design objective(s) subject to constraints and uncertainties. The material presented builds on decades of experience in Multidisciplinary Design Optimization (MDO) methods, progress in concurrent computing, and Knowledge Based Engineering (KBE) tools.

Editorial: Knowledge based engineering to support complex product design

In the current design process of complex products, such as aircraft, road vehicles, etc. (as well as their subsystems and related manufacturing hardware), there is a strong imbalance between the time absorbed by lengthy and repetitive activities and the limited time left for the investigation of multiple and innovative configurations, and what-if scenarios. From one side the market requires products of increasing complexity to be developed in a shorter time frame, from the other the time left to designers for the exploitation of their skills and creativity is drastically reducing. Innovation and sustained quality are seriously hampered. New technologies are required to facilitate modelling the multidisciplinary nature of complex products and investigating their performances in a reliable and time efficient manner, also when the design process requires the involvement of large and distributed teams of discipline experts. The concepts of lean engineering, originated in the area of production and manufacturing, need to be adopted also in the design process. Smarter tools able to embed experts’ engineering knowledge are required to reduce and automate as far as possible all the repetitive and non creative activities that hamper the design process. In this respect, Knowledge Based Engineering (KBE) technology is able to provide designers with the required support. KBE technology stands at the cross point of diverse fundamental disciplines, such as Artificial Intelligence (AI), Computer Aided Design (CAD) and computer programming. Though these single contributing disciplines are widely represented in scientific literature, Knowledge Based Engineering is not yet. KBE has been for many years restricted domain of a few and highly competitive industries (aerospace and automotive in particular) and never turned into a subject of academic research. The very limited amount of available information, mainly in form of pamphlets from KBE vendors, has not stimulated the interest of the scientific community on KBE as a real engineering discipline. On the contrary, it has contributed generating the mixture of misunderstanding and skepticism that has marked the story of KBE at date.

Systems Engineering and Multi-disciplinary Design Optimization

The worlds of Systems Engineering and Multi-disciplinary Design Optimization are distinct disciplines which represent the qualitative and quantitative side of product development methodology. Merging these two worlds would improve the applicability of both. This will,however, require a substantial range of additional concepts, methods and tools on both sides. The Design and Engineering Engine is such a concept. It sets a framework in which part of the abstractions from Systems Engineering can be implemented using the Multi-disciplinary Design Optimization approach as a structured design domain search. The Design and Engineering Engine adds the concepts of High-Level Primitives and Capability Modules to structure a-priori product family characterization and re-usability of engineering processes. The potential of the concepts has been shown successful in several pilot projects.

Improving Feasibility of Point to Point Operations Through Civil Aerial Refuelling

Re-imagining of the aerial transportation system has become increasingly important as the need for significant environmental and economic efficiency gains has become ever more prevalent. A number of studies have highlighted the benefits of the adoption of air to air refuelling within civil aviation. However, it also opens up the potential for increased flexibility in operations through smaller aircraft, shifting emphasis away from the traditional hub and spoke method of operation towards the more flexible Point to Point operations. It is proposed here that one technology can act as an enabler for the other, realising benefits that neither can realise as a standalone. The impact of an air-to-air refuelling enabled point to point system is discussed, and the affect on economic and environmental cost metrics relative to traditional operations evaluated. An idealised airport configuration study shows the difference in fuel burn for point to point networks to vary from -23% to 28% from that of Hub and Spoke depending on the configuration. The sensitive natures of the concepts are further explored in a second study based on real airport configurations. The complex effect of the choice of a Point to Point or Hub and Spoke system on fuel burn, operating cost and revenue potential is highlighted. Fuel burn savings of 15% can be experienced with AAR over traditional refuelling operations, with point to point networks increasing the available seat miles (by approximately 20%) without a proportional increase in operating cost or fuel.

Further Steps towards Quantitative Conceptual Aircraft Design

To cope with the large growth of air transport and the tightening requirements on noise and emissions, it is expected that radical new aircraft concepts will be needed. The design of such new concepts will require high-fidelity computational systems to support the designer in his search through the design space. The design and engineering engine (DEE) is a concept for such computational systems that offers generative distributed product modelling based on knowledge-based engineering, design domain search based on multi-disciplinary design optimization principles and initial design vector determination based on the feasilization principle and agent technology to couple the components of the DEE in a flexible and distributed fashion. The different components have been successfully tested in several small-scale projects.

A critical look at design automation solutions for collaborative MDO in the AGILE paradigm

This paper presents a critical discussion on the automated problem formulation and workflow creation approach developed within the European project AGILE to support and accelerate the setup of aircraft MDO workflows in a large, heterogeneous team of experts. The developed framework is based on a methodological approach, called the AGILE paradigm, where a complete MDO system is formulated and executed in five main steps. In Step I the requirements are collected, in Step II a repository of disciplinary tools is established, in Step III the design optimization problem is formulated and structured according to a selected MDO architecture, in Step IV an executable workflow is assembled and finally operated in Step V. All steps have been streamlined and highly automated through the development of a novel set of MDO support applications and data standards, addressed as the AGILE MDO framework. This framework was tested through a series of design campaigns culminating with four design tasks, where a variety of unconventional aircraft configurations is collaboratively designed using MDO. After a brief introduction on the AGILE paradigm and the four design tasks, this paper will focus on a set of AGILE framework core components enabling the automated process to formulate and execute collaborative MDO systems. The strengths and current limitations of these components are discussed, based on the extensive feedback from the heterogeneous set of specialists involved in the four design tasks. Although drastic reductions in the setup time of an MDO system (up to 40 percent) appear to be already achievable, recommendations are provided to improve the flexibility, usability and scalability of the framework.