[MUSIC] Welcome to our lecture on parameterized reduced-order digital models in Aerospace, which is composed of two parts. Namely part A, which we will discuss today, which I called Hard Computing Methods. We will also discuss later, part B, which is called Soft Computing Methods. And both parts are parts of our Munich Aerospace online course on Digitalization in Aeronautics and Space. Let's look to the title, which sounds a little strange. First of all, the question is, what do such reduced or surrogate digital models mean? The second point is, why do we talk about their parameterization? And the third point is, why do we have two parts, part A and part B? And today, we will focus on part A, namely the fundamentals of the related methods. And equally important, a series of applications, and not only from a numerical and digitalization point of view, but also from a physical and technical background point of view. Before we jump into details, I would like to make some remarks on myself. After having finished my doctoral dissertation at TU Darmstadt, I was working for 20 years in aerospace industry. Followed by 20 years in TU Munchen at the aerospace department and with lectures on aerospace structures, materials, and related subjects. So the detailed points we are now looking more into is, what do these reduced digital models mean? Why do we want to parameterize, and why is our lecture composed of this part A and later on the part B? So let's discuss this with some typical example. And first of all, we have to observe that in the, especially in the development but also in the operation of aerospace systems, we have to observe parameters which might vary a lot. For example, in operational conditions, the operational parameters which relate to aircraft are the payload mass, composed of fuel and passengers. And also the center of gravity of fuel and the center of gravity of the aircraft, the Mach number, the flight velocity, the flight level or flight head, and so forth. And in order to achieve a good design, we have to treat in the development and design phase possible structural and generally system design parameters. Which are the plan form of the aircraft, which are certain shapes of the wing and of structural parts, stiffeners position, geometries, types of materials, and so forth. Generally in the design and development phase, we want to achieve some goals, but most of all we have to satisfy a lot of requirements. And the important point is that these development design steps very much depend on digital models where we carry out the optimization steps to achieve the goals and to satisfy the requirements. So let's continue with this example by looking on the dynamic gust load alleviation in aircraft wings. Which means that we first look on to the stationary lift distribution, neglecting effects of the fuselage, shown here on the dotted line. Then we have the gust load effect. If the aircraft is flying through a gust and excited by a gust or turbulence, the lift is significantly increased, especially so at the outer wing edges. Which means that the wing root bending moment is increased, which is not so nice, especially also for the aircraft structure and for the required mass and weight needed. And in order to control this and to alleviate this, we are applying the so-called wing load alleviation. There is a passive means, which means a proper aero-elastic tailoring of the wing such that it deforms under such gust loads in a proper way and does not increase so much the outer wing lift. And secondly, an alternative and often investigated also active means, namely the proper use and proper control of flaps in order to influence the aerodynamic forces acting on the wing. In the end, for such alleviation problems, we are talking about mechanical system or structural control interaction problems. Which means that we are dealing with a plant, the aircraft especially, which is disturbed from outside by disturbance W. And this disturbance and the output from this disturbance is measured by certain sensors, which the result of which is an input to our controller. Which activates the plant, the aircraft, in a proper way in order to optimize and maximize the performance. And to determine the parameters, especially those of the plant and of the transfer function of the controller, we have to deal with these transfer functions G and H. And the essential point is in the basic ideas that these transfer function are often a result of large system models, which specifically relates to the transfer functions G of the plant or aircraft. And this is the reason why we are looking to the condensation and reduction of such large systems in order to properly determine the interaction of G and H for the overall system. [MUSIC]
