Michel van Tooren

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.

A multidisciplinary implementation methodology for knowledge based engineering: KNOMAD

Existing knowledge-based engineering methodologies offer opportunities for improvement, as the multidisciplinary character of engineering design is not well implemented and as the current methodologies are not optimally substantiated. To better address the integration of multidisciplinary engineering knowledge within a knowledge based engineering (KBE) framework, the KNOMAD methodology has been devised. KNOMAD stands for Knowledge Nurture for Optimal Multidisciplinary Analysis and Design and is a methodology for the analytical utilization, development and evolution of multi-disciplinary engineering knowledge within the design and production realms. The KNOMAD acronym can also be used to highlight KNOMADs formalized process of: (K)nowledge capture; (N)ormalisation; (O)rganisation; (M)odeling; (A)nalysis; and (D)elivery. These implementation steps are taken and repeated as part of the knowledge life cycle and in this context KNOMAD nurtures the whole Knowledge Management across that life cycle. The main contribution of the paper is to highlight the development of the KNOMAD methodology and to substantiate its individual steps with sufficient detail to support the application of KNOMAD in practice. A discipline-specific case study shows the potential of the KNOMAD methodology.

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.

An Investigation over CFD-Based Models for the Identification of Nonlinear Unsteady Aerodynamics Responses

An investigation is performed to assess the importance of the nonlinear effects on the dynamic behavior of a profile in a transonic flow. The analysis is done by applying a system identification approach to a computational fluid dynamics (CFD) code, considered as a black-box system. The CFD code is based on the Euler equations. Both frequency and time domain approaches are used to evaluate the nonlinear effects on the response of different airfoils. The results show that for weak shocks the aerodynamic operator describing the dynamics of the profile around a steady (transonic) flow condition is linear. For strong shocks results obtained with linear models appear to be conservative.

An enhanced unified uncertainty analysis approach based on first order reliability method with single-level optimization

Abstract In engineering, there exist both aleatory uncertainties due to the inherent variation of the physical system and its operational environment, and epistemic uncertainties due to lack of knowledge and which can be reduced with the collection of more data. To analyze the uncertain distribution of the system performance under both aleatory and epistemic uncertainties, combined probability and evidence theory can be employed to quantify the compound effects of the mixed uncertainties. The existing First Order Reliability Method (FORM) based Unified Uncertainty Analysis (UUA) approach nests the optimization based interval analysis in the improved Hasofer–Lind–Rackwitz–Fiessler (iHLRF) algorithm based Most Probable Point (MPP) searching procedure, which is computationally inhibitive for complex systems and may encounter convergence problem as well. Therefore, in this paper it is proposed to use general optimization solvers to search MPP in the outer loop and then reformulate the double-loop optimization problem into an equivalent single-level optimization (SLO) problem, so as to simplify the uncertainty analysis process, improve the robustness of the algorithm, and alleviate the computational complexity. The effectiveness and efficiency of the proposed method is demonstrated with two numerical examples and one practical satellite conceptual design problem.

Extension to the Class-Shape-Transformation Method Based on B-Splines

A new parameterization method to enhance shape optimization for aircraft design was developed based on the class-shape-transformation method. This method was implemented in a tool that combined all aspects of the aerodynamic design process: parameterization, aerodynamic analysis, and optimization. The parameterization method used a combination of Bernstein polynomials and B-splines to allow for both local and global control of a shape. Additionally, the use of B-splines made it possible to efficiently handle volume constraints, which are very common in aircraft design. The parameterization method was coupled to two different aerodynamic analysis tools: the commercial panel method code VSAERO and an in-house Euler code. As a first test case, a wing was optimized for maximum lift-to-drag ratio in subsonic conditions using VSAERO and various optimization algorithms. It was shown that the optimizer was capable of arriving at wing shapes that demonstrated laminar flow up to 80%, without violating the implemented volume constraints. As a second test case, an airfoil was optimized for lift-to-drag ratio in transonic conditions using the in-house Euler solver and a gradient-based optimizer. Refining the shape using B-splines proved to be an efficient way of increasing the design freedom, resulting in additional improvements in the drag divergence Mach number in the order of 0.02.

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.

Sequential Optimization and Mixed Uncertainty Analysis Method for Reliability-Based Optimization

A reliability-based optimization method under both aleatory and epistemic uncertainties is studied. The mixed uncertainties are analyzed by combined probability and evidence theory. If the mixed uncertainty analysis is directly embedded in reliability-based optimization to quantify the uncertain features of each search point, it would be computationally prohibitive. To address this problem, a sequential optimization and mixed uncertainty analysis method is proposed to decompose the reliability-based optimization problem into separate deterministic optimization and mixed uncertainty analysis subproblems, which are solved sequentially and alternately until convergence is achieved. The research focus is how to transform the reliability-based optimization problem into its quasi-equivalent deterministic formulation according to the information obtained in the uncertainty analysis. It is proposed to first decompose the total reliability target into each focal element of the epistemic uncertainties, so as to sim...

Post-buckled precompressed (PBP) piezoelectric actuators for UAV flight control

This paper presents the use of a new class of flight control actuators employing Post-Buckled Precompressed (PBP) piezoelectric elements in morphing wing Uninhabited Aerial Vehicles (UAVs). The new actuator relies on axial compression to amplify deflections and control forces simultaneously. Two designs employing morphing wing panels based on PBP actuators were conceived. One design employed PBP actuators in a membrane wing panel over the aft 60% of the chord to impose roll control on a 720mm span subscale UAV. This design relied on a change in curvature of the actuators to control the camber of the airfoil. Axial compression of the actuators was ensured by means of rubber bands and increased end rotation levels with almost a factor of two up to ±13.6° peak-to-peak, with excellent correlation between theory and experiment. Wind tunnel tests quantitatively proved that wing morphing induced roll acceleration levels in excess of 1500 deg/s2. A second design employed PBP actuators in a wing panel with significant thickness, relying on a highly compliant Latex skin to allow for shape deformation and at the same time induce an axial force on the actuators. Bench tests showed that due to the axial compression provided by the skin end rotations were increased with more than a factor of two up to ±15.8° peak-to-peak up to a break frequency of 34Hz. Compared to conventional electromechanical servoactuaters, the PBP actuators showed a net reduction in flight control system weight, slop and power consumption for minimal part count. Both morphing wing concepts showed that PBP piezoelectric actuators have significant benefits over conventional actuators and can be successfully applied to induce aircraft control.

Identification of the Dynamics of Large Wind Turbines by Using Photogrammetry

In this work, the initial results of the infield tests performed to investigate the feasibility of using photogrammetry in monitoring the dynamics of large scale wind turbines in operation are presented. Within the scope of the work, the response of a wind turbine, with a rotor diameter of eighty meters, was captured by using four CCD cameras simultaneously while the turbine was in operation. The captured response was then analyzed by using two different system identification techniques based on Least Square Complex Exponential (LSCE) method and Sub-space System Identification (SSI) while the dynamic characteristics (the frequencies, damping ratios and mode shapes) of the turbine were derived. Possible effects of very high modal damping ratios and relatively short measurement periods on the identified results were also considered.