Knowledge loss between projects or generations of designers and engineers is an issue that happens more often than it should, especially in the world of high-speed aerospace vehicle design. This results in future generations wasting valuable time and resources relearning information that has already been generated through experimentation in the past. This issue could be resolved with the creation of a parametric library that houses data and knowledge and is continually updated for generations to come, which is the undertaking of the research project detailed in this paper. The solution to this issue (as formulated by the collective effort of members of the University of Texas at Arlington AVD Laboratory) is the Vehicle Configuration Compendium, or the VCC. The VCC aims to keep vehicle designers better informed of past projects and able to easily access conceptual design-relevant project data and knowledge by housing them in an interactive software. Currently, seven high-speed vehicles have been processed into the compendium of gathered information, using a carefully formulated data and knowledge compilation and review process. This data is then incorporated into a user-friendly software interface that will in the future encourage designers and design enthusiasts of all experience or proficiency levels to consider various vehicle configurations and forecast any new vehicle design performances by consulting past projects.
The VCC system is split into two primary functions, one being the database function and the other being the knowledgebase function. For these two functions to be operational, the VCC system requires input data and knowledge from a wide range of past-to-present aerospace vehicle applications including in-atmosphere, space-access, and in-space aerospace vehicle missions.
Database
First, the database side of the VCC is where the raw data of each aerospace vehicles is stored. There are three different levels of useful data that can be collected from each vehicle, namely, simulation data, ground test data, and flight test data. These three data types come in two forms, plots (e.g., CL vs α, CL vs CD, etc.), which are digitized into a raw data format where the user can view this data for any selected point when viewing the digitized plots, and single-valued information data such as vehicle performance data, geometric data, weight/volume data, historical/managerial data, cost data, etc. All of this collected data is separated and organized into eight primary disciplines: Synthesis, Aerodynamics, Aerothermodynamics, Geometry, Performance & Trajectory, Propulsion, Weight & Balance, and Stability & Control. While these are considered the primary disciplines, there are secondary disciplines (i.e., cost) that may be considered in future iterations of the VCC.
Again, this VCC database provides three functions, namely, aerospace vehicle statistics, aerospace vehicle method verification (disciplinary and multidisciplinary), and aerospace vehicle decomposition (mission, hardware, etc.). The aerospace vehicle statistics function allows histograms to be obtained for specified parameters. This is particularly useful when setting up the input deck (i.e., assumed independent variables) for a synthesis system. For a selected group of vehicles (likely with similar mission and configuration), histograms would allow for the identification of the most commonly used assumptions for independent variables. The aerospace vehicle method verification function would allow disciplinary methods to be verified against real data (wind tunnel, ground tests, flight data, simulation, etc.) to determine if a set of methods are applicable for certain vehicles. It would also allow verification and calibration of multidisciplinary methods (synthesis systems) by comparing the sizing results to the actual vehicle data. The aerospace vehicle decomposition function breaks down the mission, hardware, etc. of each vehicle within the VCC database for the purpose of providing a “snapshot” of the components of the vehicle, and to allow configuration/mission comparisons within the knowledgebase function of the VCC.
Knowledgebase
With the data gathered and stored in the database function of the VCC, the knowledgebase function can use this data to generate useful knowledge through the use of statistics, trend-based plotting, and vehicle data comparisons. Clearly, this means that the effectiveness of the knowledgebase is dependent on the number of vehicles that have been gathered in the database and how rich the amount of publicly available data is for each vehicle. The knowledgebase function is additionally capable of organizing and sorting other types of design and historical knowledge from past-to-current projects (e.g., design lessons learned, design guidelines, etc.).
Again, this VCC knowledgebase function is used to provide for three VCC tools: an aerospace vehicle configuration comparison tool, a configuration and trend-based disciplinary analysis method generation tool, and combined with the database function, a VCC teaching tool. The aerospace vehicle configuration comparison tool would be used to compare the vehicle data stored within the database function to determine how configuration choices effect disciplinary performance, such as aerodynamics, weights, etc. The trend-based disciplinary analysis method generation tool takes the comparison tool a step further by adding trendlines to the available data to allow them to be used as methods within the synthesis system, to improve current methods, or if there are no, or lack of, methods for calculating a particular parameter. The main configuration of each aerospace vehicle is defined by its’ longitudinal/pitch control layout. A Tail-First Configuration (TFC) is where the pitch control is located in-front of the wing, a Tail-Aft Configuration (TAC) is where the pitch control is located aft of the wing, a Flying-Wing Configuration (FWC) is where the pitch control is integrated into the wing, etc. Figure 5 shows a representative configuration layout for each configuration, and subsonic to supersonic (or higher) vehicles that fall within each category.