For aircraft system certification, a huge amount of testing is required to guarantee safe, robust, and error-free behavior under all operating and environmental conditions. Typically these tests at a system level are performed on physical test benches where all the relevant components including actuators, sensors, and control computer are integrated.
Due to the conflicting trends of increasing complexity of systems and drastically reduced development times, virtual testing has become one of the solutions to overcome this challenge. Multibody simulation is the preferred approach for virtual testing of high-lift devices because it offers a good compromise between computational speed and accuracy.
Since 2002, the Airbus High Lift Test Department has developed experience on this topic in collaboration with the Hamburg University of Technology (TUHH), and with partners within the EU R&D project VIVACE.
In the meantime, the virtual testing activities have been continuously expanded and have become more and more established—e.g., by using virtual testing for risk mitigation purposes or in contributing to system certification.
The approach that is pursued by the High Lift Test Department is based on the strong coupling of physical and virtual test to obtain the highest possible confidence in the simulation results. Starting with a model variant that represents the physical test bench in all relevant details (e.g., external load application), the model will be validated using results from the test bench and then finally extended to a very aircraft-like variant.
The main differences between test-bench-like models and aircraft-like models are the application of airloads (discrete load cylinders vs. distributed pressure loads), the interface conditions (attaching the high lift system to a rigid test bench vs. a flexible wing), and the consideration of load-dependent wing deformation (test bench without deformation vs. application of wing bending and twist according to load case under consideration).
Significant benefits can be achieved using this integrated approach in terms of time and cost reduction together with increasing quality of results. Results of physical tests combined with results from virtual tests lead to a deeper understanding of the system under test and its behavior at an earlier time, thus reducing the risk of late problem findings and late design changes.
The use of simulation for aircraft system certification is not just related to build simulation models with sufficient accuracy and quality. Regulations from airworthiness authorities also request a well-defined and robust process for the complete data chain involved in the certification.
Currently used requirements-based engineering (RBE) is the formal way of developing new aircraft and their systems. Within test departments this has led to a requirements-based testing (RBT) process.
All required functions and properties of the system in terms of performance, safety, etc., are specified verbally within single requirements managed by a database system based on Doors (Telelogic).
By use of a Test Management System (TMS), the formal verification of each of the requirements is assigned to one or more of the existing test tools. Each test tool has a local process and data management environment. After test execution, the TMS collects all the test results from the local platforms and generates automatically the required test analysis reports and finally the certification documentation (coverage report).
Besides the need for traceability of the relationships between all relevant simulation data (established by simulation data management), it is also mandatory to have a simulation process management in place that is enabling the efficient use of virtual testing and the related simulation technology. This comprises all the major steps of the simulation process starting with pre-processing, i.e., creating the simulation models; continuing with solving, i.e., execution of the models to generate simulation results; and finishing with post-processing of the results, i.e., extracting key values as well as generation of tables and plots.
For successful implementation of virtual testing in the existing test process, a solution was developed based on MSC SimManager called the High Lift System Virtual Test (HLSVT) portal. One of the most important and critical aspects was the correct capturing of the virtual test process itself and its interface with the TMS. A detailed specification capturing all objects, process steps, and related attributes was established and refined during setup of the portal.
Besides the virtual test process, the modeling process is also driven by the virtual test portal. The process is captured and implemented by execution of scripts (e.g., SimXpert templates) or interactive pre-processor sessions triggered by the portal. Besides configuration control in the sense of answering the question which model was used to generate a certain simulation result, this enables also to capture which input data and processes were used to generate the used model.
To increase simulation performance, i.e., to enable sensitivity analysis, simulation multi-runs and corresponding script-based post processing launched by the portal are possible.
The execution of a multibody simulation model generally leads to a considerable amount of data. The parameters measured in the model lead to an important number of time series, each of them consisting of a high number of time steps (depending on the output resolution, which is usually quite high, especially in case of dynamic simulations). Though for the evaluation of a system requirement, i.e., drawing a passed/failed conclusion, usually only a few key values are needed. Therefore, it is mandatory to have an efficient post-processing process in place, enabling robust and convenient key-value extraction out of the simulation raw-results. This process also covers the global virtual test requirement for traceability and reproducibility of data.
A post-processing definition table is used to define how the simulation raw result has to be treated. This comprises a block-wise definition of the parameters that are to be treated, their conditioning such as application of offsets or scaling factors and the definition of the key-value extraction.
The definition table is implemented in Microsoft Excel and also contains a template of the key-value output table and a formatting macro to optimize its appearance.
Starting at a given simulation result, the HLSVT portal provides the simulation result and the post-processing definition table to a Matlab function which reads the data as well as the definition and performs the requested operations. This comprises the actual extraction of values and writing into the output table as well as the creation of corresponding plots. Besides the key values, the output table also contains hyperlinks to the created plots. After execution of the post-processing, the generated outputs are collected by the HLSVT portal and prepared for an upload to the TMS, where the system requirements evaluation is performed.
Besides a single simulation result, multiple results originating from a variation of test conditions (i.e., level of applied load) also can be processed. In this case, one common definition table is used; each simulation result of the set of results is processed separately, but written in one common output table. Besides the plots of the single evaluations, a consolidated plot is also produced, showing the evolution of the observed parameter for the changing test conditions.
In addition to pure post-processing of simulation results, the same Matlab function is also able to perform model validation activities by producing comparisons between simulation results and corresponding reference data, e.g. physical measurements or simulation results of alternative simulation methods and tools, e.g. FEM analysis results. In this case, additional information is provided in the input definition, specifying the treatment of the reference data as well as defining the comparison that is to be performed. Like in the case of simple post-processing, an output table and corresponding plots are generated.
This article is based on SAE International technical paper 2013-01-2280 by Tobias Ulmer and Jaymeen Amin, Airbus Operations GmbH, presented at the SAE 2013 AeroTech Congress & Exhibition.