Search Results

Stringer misplacement in the latest design of full CFRP wing covers causes cost and lead time in the further processes due to reworks in the torsion box assembly., To improve and solve this matter, ARITEX has developed an automated Laser assisted Stringer positioning system that allows the flexible, one-by-one and accurate position of the non-cured Stringers in the wing cover. This paper describes how ARITEX has developed and implemented this system in two different CFRP wings using the same technical concept adapted to the context and geometry of each aircraft, and how the targets were achieved reducing the misplacement problem from previous projects.

Statistical process control (SPC) has been extensively used in many different industries including automotive, electronics, and aerospace, among others. SPC tools such as control charts, process capability analysis, sampling inspection, etc., have definitive and powerful impact on quality control and improvement for mass production and similar production systems. In aerospace manufacturing, however, applications of SPC tools are more challenging, especially when these tools are implemented in processes producing products of large sizes with slower production rates. For instance, following a widely accepted rule-of-thumb, about 100 units of products are required in the first phase of implementing a Shewhart type control chart. Once established, it then can be used for process control in the second phase for actual production process monitoring and control.

A multi-axis serially redundant, single channel, multi-path FBW (FBW) control system comprising: serially redundant flight control computers in a single channel where only one “primary” flight control computer is active and controlling at any given time; a matrix of parallel flight control surface controllers including stabilizer motor control units (SMCU) and actuator electronics control modules (AECM) define multiple control paths within the single channel, each implemented with dissimilar hardware and which each control the movement of a distributed set of flight control surfaces on the aircraft in response to flight control surface commands from the primary flight control computer, and a set of (pilot and co-pilot) controls and aircraft surface/reference/navigation sensors and systems which provide input to a primary flight control computer and are used to generate the flight control surface commands in accordance with the control law algorithms implemented in the flight control computers.

We applied ultrasonic propagation imaging (UPI) system for rapid and reliable quality control of fuel tanks for a space launcher. The fuel tank is an aluminum-lined CFRP propellant tank. The UPI system uses Q-switched laser (QL) to generate ultrasonic wave on the test specimen, and laser mirror scanner (LMS) to control the laser impinging point that scans the area of interest with high speed. Each ultrasonic wave generated by laser impinging was received by a piezoelectric sensor with coordinate information of the scanned area. After ultrasonic propagation image processing, results with impact damage and manufacturing defect information of the fuel tank were presented.

This paper shows how the quantity demanded, viewed as an independent variable, interacts with customer values, producer costs and constraints. Failure to analyze Demand as Independent Variable (pronounced “Dave”) increases the chances that new programs will not launch, or once started, will fail. All producers in all markets face demand curves that describe their customers' reaction to price changes. Aggregate market demand curves show how buyers react to price changes within broad product sets, while product demand curves show buyer responses to a specific item. Demand curves relate quantities sold relative to their prices. In several military, transit and fleet cases, minimum quantity requirements form upper price boundaries along demand curves. Allowing prices to go so high that buying authorities cannot acquire the required numbers of units likely means that there may not be sufficient resources to form systems that can accomplish the buyers' goals.

For many mission critical systems, demonstrating that all requirements have been met via a set of requirements-based tests is often mandated by internal processes or external standards. Traditional coverage approaches, however, do not address this mandate because they measure only the coverage of the design by determining which paths in the design have been executed. Determining whether a given set of test vectors covers the design requirements (as opposed to merely covering the design) is a challenge. Creating a set of test vectors to cover the requirements can be difficult and time consuming. Using techniques first identified in the 1970s and modern Model-Based Design tools, we present a novel approach, based on work presented in [2], to automatically generate a set of requirements-based test vectors. In this paper, we discuss how requirements captured in a natural language can be modeled using Cause-Effect graphs, introduced in [1].

The increased use of FPGAs over the past decade has induced an increased concern about radiation effects, in particular the effects of single event upsets (SEU) in SRAM-based FPGAs. Technology scaling and density increase have caused FPGAs to be more vulnerable to SEU. Therefore, external radiations present an issue not only for space based systems; but also for critical terrestrial applications operating in harsh environment, such as commercial avionics. In order to build robust fault tolerant systems, SEU effects have to be analyzed and modeled so that the designer understands and considers the system's possible faulty behaviors. In this paper, we present a complete automated methodology, based on the use of SEU controller provided by Xilinx, to efficiently emulate SEUs on an FPGA design and extract possible fault models based on radiation effects. The proposed method is applied on a reconfigurable flight control system based on a reference adaptive control model.

The renewed interest in the fuel efficient and low CO2 emission CROR (contra-rotating open rotor) propulsion system for future commercial aircrafts has recently led to a series of isolated and installed CROR wind tunnel test campaigns performed in close collaboration between Airbus and the engine manufacturers. These tests aim at better understanding the potentials and limitations of the CROR configuration, as well as at generating reference data for the development and calibration of numerical tools for both industry and research centers. One of these tested CROR concepts is the AI-PX7 CROR propeller designed by Airbus. In this context, this paper presents multidisciplinary design features of modern high-speed contra-rotating propellers for commercial aircrafts. The influence of main CROR design parameters like blade number, propeller tip speed, rotor diameter, etc. on the propeller aerodynamics, acoustics and structures is described.

Many Small Unmanned Aerial Vehicles (SUAV) are driven by small scale, fixed blade propellers. Flow produced by the propeller can have a significant impact on the aerodynamics of a SUAV. Therefore, in Computational Fluid Dynamic (CFD) simulations, it is often necessary to simulate the SUAV and propeller coupled together. For computational efficiency, the propeller can be modeled in a steady-state view by using momentum source terms to add the thrust and swirl produced by the propeller to the flow field. Many momentum source term models are based on blade element theory. Blade element theory divides the blade into element sections in the spanwise direction and assumes each element to operate independently as a two-dimensional (2D) airfoil.

Implementing Design for Environment (DfE) into the design process requires a strategic integration. Furthermore, as DfE is continuously evolving, flexible processes need to be implemented. This article focuses on the integration of DfE into an optimization framework with the objective of influencing next-generation aircraft. For this purpose, DfE and Structures groups are developing together a set of new environmental indicators covering all life cycle stages of the product by coupling a list of yes/no questions with an environmental matrix. The following indicators are calculated: Regulation risk, Impact of manufacturing the part, CO2 emissions and Recyclability potential. These indicators will be used as constraints in the multi-disciplinary design optimization (MDO) framework, meaning that the structure will be designed while complying with environmental targets and anticipating future regulation changes.

Recent advances in small unmanned air vehicles (UAV) lead to robust on-board stabilized platforms ready to use for real-world problems. As a result, many different autonomy functions have been demonstrated, which allow controlling the UAVs at high level. However, the great variety of platforms also poses new challenges when adapting these autonomy functions to new platforms. For instance modifying a trajectory planning algorithm, which was designed for a rotary-aircraft with a moving camera, to work on a fixed-wing aircraft with a static camera is not a trivial task. Often such algorithmic solutions are tailored so specifically to a certain platform that it becomes very complicated to reuse algorithms. This results in a variety of many different approaches trying to solve the same task. We therefore encourage designing algorithms for UAVs autonomy function to be more generic. As an example, we focus on the task to autonomously follow a moving ground object using an UAV.

A Hybrid Projectile (HP) is a round that transforms into a UAV after being launched. Some HP's are fired from a rifled barrel and must be de-spun and wings-level for lifting surfaces to be deployed. Control surfaces and controllers for de-spinning and wings-leveling were required for initial design of an HP 40 mm. Wings, used as lifting surfaces after transformation, need to be very close to level with the ground when deployed. First, the tail surface area needed to de-spin a 40 mm HP was examined analytically and simulated. Next, a controller was developed to maintain a steady de-spin rate and to roll-level the projectile in preparation of wing deployment. The controller was split into two pieces, one to control de-spin, and the other for roll-leveling the projectile. An adaptable transition point for switching controllers was identified analytically and then adjusted by using simulations.

The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated.

A robotic arm manipulator is often an appealing method to position drills, bolt inserters, automated fiber placement heads, or other end effectors. In a standard robot the flexibility of the cantilevered arm as well as backlash in the drive system lead to large positioning errors. Previous work has greatly reduced this error through the use of secondary scales and a mathematical model of the robot deflection running on a CNC controller. Further research improved upon this model by accounting for linear deformation of each robot link regardless of position. The parameters describing these deformations are determined through a calibration routine and then used in real time to guide the end effector accurately to any reachable pose. In practice this method has been used to achieve total on-part positioning accuracy of better than +/− 0.25mm.

One of the hardest tasks involving wind tunnel characterization is to determine the air-flow condition inside the test section. The Log-Tchebycheff method and the Equal Area method allow calculation of local velocities from measured differential pressures on rectangular and circular ducts. However, these two standard methods for air flow measurement are limited by the number of accurate pressure readings by the Pitot tube. In this paper, a new approach is presented for wind tunnel calibrations. This approach is based on a limited number of dynamic pressure measurements and a predictive technique using Neural Network (NN). To optimize the NN, the extended great deluge (EGD) algorithm is used. Wind tunnel testing involves a large number of variables such as wind direction, velocity, rate flow, turbulence characteristics, temperature variation and pressure distribution on airfoils.

Traditionally, automated fiber placement (AFP) motion platforms use rack and pinion drive trains coupled through a gearbox to a rotary motor. Extensive use of non-contact linear motors on a new AFP motion platform produces a quiet, low-maintenance system without sacrificing precision. A high-rail gantry arrangement allows dynamic performance improvements to machine acceleration and speed, while lowering power consumption costs and capital expenses. The seventh axis incorporated into the machine arrangement effectively produces an effective “five sides of a cube” work envelope, permitting complex spar and panel fabrication.

This paper focuses on the virtual integration and test approach used for the evaluation of an automation system developed for the multifunctional operation of fuel cells in commercial aircraft. In order to accomplish the virtual integration a model of the overall automation system is linked with a dynamic model of the complete fuel cell system. For this purpose a modeling approach for complex physical systems is described in this paper. During virtual testing various simulation runs are executed based on automatically generated test cases, which cover a complete flight mission. For this reason a flight mission is modeled as a Statechart that includes next to time- based flight phases also potential events and malfunctions (e.g. engine flame-out, cargo fire). An algorithm is described, which can find all possible state combinations including parallel event sequences.

Current methods of life cycle assessment (LCA) include input-output (IO) models and process-based LCA. These methods either require excessive effort and time to reach a conclusion (process LCA) or do not adequately model how a change in a product's design will affect the environmental footprint (IO LCA). A variation of process-based LCA developed specifically for aircraft is presented in this study. A tool implementing this LCA, “qUWick,” is rapid and easily applicable to multi-disciplinary design optimization of aircraft. Models developed for the material production, manufacturing, usage, and end-of-life of an aircraft are examined. Outputs of qUWick are discussed for future air vehicles. When compared to process LCAs with similar boundaries, qUWick gives similar results, however qUWick models several stages of an aircraft's life cycle more accurately than other aircraft process-based LCAs.

The performance enhancement of a vertical tail provided by aerodynamic flow control could allow for the size of the tail to be reduced while maintaining similar control authority. Decreasing tail size would create a reduction in weight, drag, and fuel costs of the airplane. The application of synthetic jet actuators on improving the performance of the vertical tail was investigated by conducting experiments on 1/9th and 1/19th scale wind tunnel models (relative to a Boeing 767 tail) at Reynolds numbers of 700,000 and 350,000, respectively. Finite-span synthetic jets were placed slightly upstream of the rudder hinge-line in an attempt to reduce or even eliminate the flow separation that commences over the rudder when it was deflected to high angles. Global force measurements on the 1/9th scale model showed that the flow control is capable of increasing side force by a maximum of 0.11 (19%). The momentum coefficient that created this change was relatively small (Cμ = 0.124%).

This paper introduces a novel approach in order to compare different eco design practices considering the value network of stakeholders. The proposed decision tool framework in this study helps manufactures in early stage of design to select a portfolio of eco design techniques to maximize the value perceived by all stakeholders in a dual life cycle approach including the business product life cycle as well as physical life cycle. A portfolio selection approach has been used to maximize the network value of stakeholders considering the life cycle cost and risk of techniques while satisfying the diversity of allocation resources on eco design practices based on strategic objectives of manufacturers. The dynamic characteristic of stakeholder's network as the result of implementing the different eco design techniques has also been considered in order to evaluate the synergy in stakeholder's network.