Design by continuous collaboration between manual and automatic optimization

Numerical optimization is traditionally viewed as a machine centric activity. This view dominates the majority of numerical optimization packages today, where user interaction is normally limited to the problem definition phase or visualization of the results with little or no interaction at design or run time. Surprisingly we are surrounded by many examples of successful engineering systems which allow human interaction at run time, e.g. automobiles, aircraft etc. In fact, Integrated Human Machine Systems (IHMS) and dedicated engineering design groups have already shown that the distribution of the intelligent function between the human and artificial agents at design time leads to a more effective utilization of their complementary capabilities. This paper discusses the implementation of a generic semi-automatic optimization concept in which the human designer continuously collaborates with a numerical agent to navigate the design space and modify it when necessary. The concept allows human interaction at various levels of automation. The potential of this approach is shown by way of three human-in-the-loop optimization examples: . conceptual design optimization of subsonic aircraft; . optimization of trajectory of a Mars rover vehicle; . configuration optimization of a multistage rocket. This technique is located in a multidisciplinary area formed by the cross section of Visualization, Numerical Optimization and Computational Steering

Aircraft conceptual design by collaborative manual and automatic agents

In real applications, it is extremely difficult (if not impossible) to define function(s) that measure the `true merit' of a design object. For example, even the most prominent aircraft designers would not dare to claim that a particular set of merit and constraint functions measures the `true merit' of a class of aircraft. The traditional approach to set up a `machine centric' optimization cannot effectively address this issue because there is no user interaction with the numerical optimization at design or run time. The semi-automatic concept, however, can help because the user is allowed to interact with the design problem and the design progress in-the-loop, such that the design criteria can be improved relatively easily at design time. This paper briefly describes the semi-automatic design optimization setup which was introduced in full detail in a previous paper by the author. A simple multidisciplinary aircraft conceptual design optimization problem is then specified based on Torenbeek (1992). Various modes of in-the-loop user control on the search progress and the search problem then illustrate the potential benefits of allowing the user to interact with a numerical agent at various levels of automation

Interactive exploration and modeling of large data sets: a case study with Venus light scattering data

We present a system where visualization and the control of the simulation are integrated to facilitate interactive exploration and modeling of large data sets. The system was developed to estimate properties of the atmosphere of Venus from comparison between measured and simulated data. Reuse of results, distributed computing, and multiple views on the data were the major ingredients to create an effective environment

Flipping the analytical coin : closing the information flow loop in high speed (real time) analysis

Analysis modules tend to be set up as one way flow of information, i.e a clear distinction between cause and effect or input and output. However, as the speed of analysis approaches real time (or faster than movie rate), it becomes increasingly difficult for an external user to distinguish between cause and effect because they are simultaneously available for visualization and can be viewed in any desired order. This paper discusses some potential benefits of setting up a Flipping Analytical Coin Tool (FACT) which closes the information flow loop, thereby taking advantage of the apparent equivalence between forward and reverse analysis. A simple and stable non-linear algorithm is derived which uses the principle of dimensional similarity in each independent dimension of the problem to efficiently calculate the reverse path of high speed multidimensional functions or analysis modules. An example application in the field of conceptual thermodynamic design of a turbofan engine demonstrates the usefulness of this approach to interactive design optimization of complex engineering systems. The method given here is applicable to both well and ill-posed problems

Interactive exploration and modeling of large data sets: A case study with Venus light scattering data.

We present a system where visualization and the control of the simulation are integrated to facilitate interactive exploration and modeling of large data sets. The system was developed to estimate properties of the atmosphere of Venus from comparison between measured and simulated data. Reuse of results, distributed computing, and multiple views on the data were the major ingredients to create an effective environment