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Flight loads calculations play a fundamental role in the development and certification of an aircraft and have an impact on the structural sizing and weight. The number of load cases required by the airworthiness regulations is in the order of tens of thousands and the analysis must be repeated for each design iteration. On large aircraft, CS-25 explicitly requires taking into account for loads prediction, airframe flexibility, unsteady aerodynamics and interaction of systems and structure, leading to computationally expensive numerical models. Thus there is a clear benefit in speeding-up this calculation process. This paper presents a methodology aiming to significantly reduce the computational time to predict loads due to gust and maneuvers. The procedure is based on Model Order Reduction, whose goal is the generation of a Reduced Order Model (ROM) able to limit the computational cost compared to a full analysis whilst retaining accuracy.

This paper proposes a solution for utilizing multi-body models in nonlinear state observers, to directly estimate the loads acting on the aircraft structure from measurement data of sensors that are commonly available on modern aircraft, such as accelerometers on the wing, rate gyros and strain gages. A high-fidelity aeroelastic multi-body model of a fixed-wing large passenger aircraft is presented, suitable for the monitoring of landing maneuvers. The model contains a modally reduced flexible airframe and aerodynamic forces modeled with a doublet-lattice method. In addition, detailed multi-body models of the nose and main landing gear are attached to the flexible structure, allowing to accurately capture the loads during a hard landing event. It is expected that this approach will make way for embedding non-linear multi-body models, with a high number of degrees of freedom, in state estimation algorithms, and hence improve health monitoring applications.

Vives College University and Kulab (KU Leuven University campus Ostend) in Belgium are undertaking an aeronautical research program about the development of a new Unmanned Aerial Vehicle (UAV). Since the UAV is completely electrically powered, the analysis of the energy management of the integrated electrical system was critical to the development of the UAV. LMS, A Siemens Business, is involved in the project to support the development of a multi-physics simulation model for electro-thermal analysis of the aircraft. This paper reports on the subsequent investigation of integrating the detailed electrical system model for a Pilot-in-the-Loop simulation. In order to perform this simulation, the model of the electrical system was converted into a real-time simulation model. The aim was to perform more realistic flight simulations to evaluate the performance of the aircraft before its first flight by taking into account the electrical system's behavior.

Flight load prediction is used to identify the maximum structural loads in an aircraft during flight manoeuvres and gusts. The motivation for this research activity was to assess the feasibility of using Commercial-off-the-shelf (COTS) software applications in the context of flight loads prediction during the early phases of design for commercial airline aircraft, which may drive significant time saving. The COTS that was used was the multi-body software LMS Virtual.Lab Motion. To build a relatively accurate model within the given time, existing FE models and aerodynamic data for a given aircraft model were used. Initially, the model was trimmed to a steady-level 1-g state. Subsequently, several gust cases were simulated. The results showed that a steady state was achieved before and after the gust, demonstrating the ability of the model to recover.