Probabilistic Characterization of Operational Uncertainties in Transport Aircraft using OpenSky

The aerodynamic design of transonic wings is already a mature field, and the use of aerodynamic shape optimization is a well-established discipline in industrial setting. Aircraft manufacturers design configurations by considering a representative but limited set of flight conditions. In practice, airlines do not always fly at the conditions they were designed to operate. Flight altitude, airspeed and aircraft weight are affected by operational requirements and environmental uncertainties. As a result, aircraft altitude, Mach number and lift coefficient, three of the most important parameters when performing aerodynamic design, can not be treated as single deterministic values in the design process. A full probabilistic approach is required to better characterize the real performance of the aircraft. However, there is a lack of aircraft operational data necessary to characterize uncertainty sources in flight. The objective of this paper is the characterization and quantification of operational uncertainty sources based on aircraft surveillance data. The definition of these uncertainties will be essential for the robust design of the next generation of commercial aircraft. To understand the variability in operating conditions of a representative aircraft fleet, surveillance data from the OpenSky network is gathered. The Mach number is directly obtained from the BDS-60 codes, while the altitude is provided by the ADS-B. The lift coefficient of the aircraft at each instant is roughly estimated according to the Breguet equation and the initial and final fuel weights. These are determined by the distance between departure and arriving airports. After the Mach, lift coefficient and altitude are obtained for each individual flight, they are filtered for cruise conditions (level flight). A Kernel Density Estimation is used to obtain the full probability distribution function. This methodology enables the accurate characterization of operational uncertainties that will be required for the aerodynamic robust design of the next generation of aircraft. The design will be tailored to the airliners operations. This framework can also be used by designers and operators to understand how aircraft are operated in reality

Development of Efficient Surrogate-Assisted Methods to Support Robust Design of Transonic Wings

Mit dem kontinuierlichen Anstieg der Anzahl kommerzieller Flüge sind ökologische und ökonomische Bedenken die Hauptantriebskräfte für die Reduzierung der Betriebskosten und der Emission von Treibhausgasen. Der Einsatz der aerodynamischen Formoptimierung spielt dabei eine Schlüsselrolle, um den Luftwiderstand und den gesamten CO2-Fußabdrucks von Flugzeugen zu reduzieren. Sie wurde bisher regelmäßig auf deterministische Weise durchgeführt und vernachlässigte Unsicherheiten. Die Sensitivität einer optimierten Konfiguration gegenüber betrieblichen, umweltbedingten und geometrischen Unsicherheiten kann jedoch die tatsächliche Leistung eines Flugzeugs beeinflussen. Die Suche nach einer robusten Konfiguration, die weniger empfindlich auf solche zufälligen Änderungen reagiert, ist in der Praxis ein attraktiveres Ziel. Aktuelle robuste Entwurfsansätze leiden aber unter einem großen Rechenaufwand, wenn es um aerodynamische Probleme im industriellen Maßstab geht und wurden hauptsächlich an akademischen und vereinfachten Testfällen demonstriert. Das Ziel dieser Dissertation ist die Entwicklung von effizienten robusten Entwurfsmethoden und deren Anwendung auf die robuste aerodynamische Formoptimierung von Tragflächen und Flügeln unter realistischen Unsicherheiten. Die erste Methodik führt eine robuste Entwurfsformulierung mit zwei Ebenen ein, die auf Gaussian Prozessen basiert. Die Kombination eines ersatzmodellbasierten Optimierungsalgorithmus mit einem ersatzmodellbasierten Ansatz zur Quantifizierung von Unsicherheiten macht die Methode unter einer geringen bis moderaten Anzahl von Entwurfsparametern und Unsicherheiten effektiv. Die zweite Methode etabliert ein effizientes gradientenbasiertes Ansatz für den robusten Entwurf, der unempfindlich gegenüber der Anzahl der Entwurfsparameter ist, indem eine adjungierte Formulierung verwendet wird. Der dritte Ansatz beinhaltet eine Bayes'sche Formulierung für robustes Design, die unempfindlich gegenüber der Anzahl der Unsicherheiten ist. Diese Methoden werden erfolgreich mit analytischen Testfunktionen und 2D-Problemen zur Tragflächenoptimierung validiert. In allen Fällen übertreffen die robust optimierten Konfigurationen diejenigen, die auf deterministische Weise optimiert wurden, wenn sie Unsicherheiten ausgesetzt sind. Die erste industrietaugliche Anwendung konzentriert sich auf den robusten Entwurf einer 3D-Anordnung von Stoßbeulen, die für ein modernes Transportflugzeug nachgerüstet werden können. Realistische Unsicherheiten in Machzahl, Auftriebsbeiwert und Flughöhe werden aus Flugbetriebsdaten extrahiert. Die robuste Konfiguration übertrifft nicht nur die mit traditionellen Einpunkt- und Mehrpunkt-Optimierungsverfahren erhaltenen Konfigurationen, sondern demonstriert auch das Potenzial des robusten Entwurfs nachrüstbarer Stoßbeulen. Die zweite Anwendung beschäftigt sich mit dem robusten Entwurf von 2.5D Flügeln mit natürlicher laminarer Strömung für eine Kurzstrecken-Zivilflugzeugkonfiguration unter Umwelt- und Betriebsunsicherheiten. Es wird gezeigt, dass die robusten Konfigurationen unter Verwendung der robusten Entwurfsformulierung mit zwei Ebenen in der Lage sind, die Laminarität unter Strömungsstörungen besser aufrechtzuerhalten und den Entwurfsbereich in Bezug auf Machzahl, Auftriebsbeiwert und kritische N-Faktoren zu erweitern. Die Berücksichtigung von Unsicherheiten im Optimierungsprozess erweist sich als äußerst vorteilhaft in Bezug auf Robustheit und Leistungsverbesserung beim Entwurf von transsonischen Profilen und Flügeln. Die in dieser Arbeit entwickelten, maßgeschneiderten Methoden sind die Voraussetzung für die Berücksichtigung von Unsicherheiten in die aerodynamische Formoptimierung und ermöglichen den Übergang von einer deterministischen zu einer probabilistischen Formulierung

Gradient-Based Aerodynamic Robust Optimization Using the Adjoint Method and Gaussian Processes

The use of robust design in aerodynamic shape optimization is increasing in popularity in order to come up with configurations less sensitive to operational conditions. However, the addition of uncertainties increases the computational cost as both design and stochastic spaces must be explored. The objective of this work is the development of an efficient framework for gradient-based robust design by using an adjoint formulation and a non-intrusive surrogate-based uncertainty quantification method. At each optimization iteration, the statistic of both the quantity of interest and its gradients are efficiently obtained through Gaussian Processes models. The framework is applied to the aerodynamic shape optimization of a 2D airfoil. With the presented approach it is possible to reduce both the mean and standard deviation of the drag compared to the deterministic optimum configuration. The robust solution is obtained at a reduced run time that is independent of the number of design parameters

Robust Design of Transonic Natural Laminar Flow Wings under Environmental and Operational Uncertainties

The introduction of laminar flow configurations is envisioned to provide new opportunities to further reduce aircraft fuel consumption. The robustness of laminar wings is critical, both against instabilities that can unexpectedly trigger transition and against off-design conditions outside the cruise point. However, current inverse design methodologies not only provide suboptimal configurations, but are unable to come up with robust configurations. The objective of this paper is the development and demonstration of a framework for the robust direct design of transonic natural laminar flow wings using state-of-the-art industrial tools such as computational fluid dynamics, linear stability theory and surrogate models. The deterministic optimization problem, which serves as a baseline, searches for the optimum shape that minimizes drag applying a surrogate based optimization strategy. In that case Cross-Flow and Tollmien-Schlichting critical N-Factors are fixed according to calibration data. For the robust approach, uncertainties in these critical N-Factors as well as operational conditions such as Mach number are considered to account for situations that could prematurely trigger transition and thus significantly decrease performance. The surrogate based optimizer is therefore coupled with a surrogate based uncertainty quantification methodology, following a bi-level approach. The objective function shifts towards the expectation of the drag to minimize average fuel consumption, or the 95% quantile to account for extreme events. The framework is able to come up with state-of-the-art natural laminar configurations for a short-haul civil aircraft configuration. The deterministic optimum is able to delay transition till 60% of the wing upper surface where the shock is present but is highly sensitive to small changes in the predefined critical N-Factors, as minor deviations will lead to fully turbulent configuration and hence an increase in drag. The robust configurations are more balanced, as the transition location smoothly moves upstream as the critical N-Factors are reduced. As a direct consequence, obtained pressure profiles are more resistant against instabilities, extending the current design envelope of natural laminar flow wings

Efficient Bilevel Surrogate Approach for Optimization Under Uncertainty of Shock Control Bumps

The assessment of uncertainties is essential in aerodynamic shape optimization problems to come up with configurations that are more robust against operational and geometrical uncertainties. However, exploring the stochastic design space significantly increases the computational cost. The aim of this paper is to develop a framework for efficient optimization under uncertainty by means of a bilevel surrogate approach and to apply it to the robust design of a retrofitted shock control bump over an airfoil. The framework combines a surrogate-based optimizer with an efficient surrogate-based approach for uncertainty quantification. The optimizer efficiently finds the global optimum of a given quantile of the quantity of interest through the combination of adaptive sampling and a moving trust region. At each iteration of the optimization, the surrogate-based uncertainty quantification uses an active infill criterion to accurately quantify the quantile requiring a reduced number of samples. Two different quantiles of the drag are chosen for the design of the shock control bump: the 95% to increase the robustness at off-design conditions, and the 50% for a configuration that is preferred for day-to-day operations. In both cases, the optimum bumps are more robust, compared to the one obtained through classical deterministic optimization

Wind tunnel investigations of potential UAV configuration to meet requirements of TERN mission

In the mid 80’s, a wind tunnel study of a 1/6 scale model RPV was performed to determine the influence of the close-coupled canard on the aerodynamic coefficients. Now, more than 20 years after, these tests are repeated for the design of a full scale prototype for TERN mission, where the necessity of minimum Weight Specific Kinetic Energy for operation on Littoral Combat ships is the key feature that makes the close coupled canard a design candidate. To determine the aerodynamic characteristics of the model a wind tunnel study was done. The results are compared with the previous data, and the stability coefficients were determined. The existing wood model of a close coupled canard with a swept delta platform was used. With a gap of 0.27 mean geometric chord of wing (MGCw) and a stagger of 1.01 MGCw, its geometry is near optimal for maximum lift enhancement. Once a new spindle was machined, the pyramidal balance calibrated and the acquisition program modified, tests were performed at Reynolds number of 600,000 in order to reproduce the conditions of the previous experiments. Several configurations were tested: the Wing/Body (W/B) and the Wing/Body/Canard (W/B/C) with different canard deflection (decalage) of 0°,+10°,+20°,-10° and -20°, with angle of attack and sideslip sweeps. The loads were obtained from the balance, transferred to the computer through Labview and later analyzed by MatLab. The results show that the close coupled canard increases lift coefficient and delays stall compared to the Wing/Body configuration. The lift coefficient increases as the canard deflection is increased. The highest CL/CD is for the W/B, as is the smallest drag. The neutral point is shifted from 0.3 MGCw for W/B to 0.1 MGCw for W/B/C. All configurations can be trimmed. In overall, the new results match the ones obtained 20 years ago. The trends in lift, drag and pitching moment are the same. Small differences are appreciated due to the fact that the effect of the tunnel blockage was not corrected. Also, the new results present lower drag due to the absence of grit type boundary trips. It has been demonstrated the influence the canard has on the aerodynamic coefficient. The lift enhancement due to the flow reattachment produced by the canard vortex delays stall and allows level flight at higher angles of attack than the conventional W/B configuration. The results were reliable as they matched the experimental data obtained more than 20 years ago. The gathered data will be used to calibrate a VLM which will be employed for the design of a vehicle for TERN missionSabater Campomanes, C. (2015). Wind tunnel investigations of potential UAV configuration to meet requirements of TERN mission. Universitat Politècnica de València. http://hdl.handle.net/10251/51540Archivo delegad

Best Practices for Surrogate Based Uncertainty Quantification in Aerodynamics and Application to Robust Shape Optimization

This chapter introduces the use of aerodynamic shape optimization applied to industrial problems, motivates the use of a robust approach over the classical deterministic optimization, and presents different alternatives for the robust-based and reliability-based problems. The use of surrogates for the Uncertainty Quantification of operational and geometrical uncertainties is a cost-effective solution for high dimensional models if the gradient information is introduced by means of the adjoint method. Finally, the proposed methodology is applied through the reliability-based optimization of an airfoil under operational uncertainties

Optimization under Uncertainty of Shock Control Bumps for Transonic Wings

Shock control bumps are retrofit devices that increase the performance of transonic wings by decreasing wave drag. They are highly sensitive to the shock wave location and random fluctuations in flight. The objective of this paper is to optimize a 3D shock control bump for a transonic wing under stochastic flight conditions such as freestream Mach number and lift coefficient. An efficient robust gradient-based optimization framework that relies on the adjoint formulation is used. The mean and standard deviation of the drag coefficient and its gradients are efficiently obtained using Gaussian Processes. The optimum is obtained at a reduced number of iterations that is independent to the number of design parameters. The robust configuration outperforms the traditional single-point and multi-point optimum in terms of average drag reduction. A pareto front of robust optimum configurations in terms of variability and expectation of the drag is provided, enabling the designer to choose the desired configuration based on their individual needs. By taking uncertainty into account, shock control bumps extend their operating range and are able to efficiently mitigate shock waves for a range of flight condition

External Flow Effects in the Engine/Airframe Integration Testing Technique: A New Thrust/Drag Bookkeeping Approach at the German-Dutch Wind Tunnels

The integration of the engine with the airframe is investigated in the German-Dutch Wind tunnels (DNW) using special scale engines called Turbofan Powered Simulators (TPS). The bookkeeping of thrust and drag must be clear. The TPS thrust is determined under static conditions in a calibration facility, and then subtracted in the wind tunnel test from the balance force of the aircraft model (airframe + TPS) to obtain the airframe drag including jet interference drag. A critical assumption valid for traditional turbofan engines is that the external flow does not affect the statically calibrated thrust. However, with the rise of more efficient engines with higher bypass ratio this may not be the case due to the close coupling between the engine flow and the wing. The objective of this Thesis is to identify the current limitations of the testing procedure as well as to produce scientific basis to deal with these limitations. This is achieved by means of a consistent thrust/drag bookkeeping combining numerical methods and a modified experimental setup.External flow effects are identified by means of the analysis of theoretical models, the comparison with testing procedures undertaken in similar facilities, the review of standard bookkeeping techniques of full-scale turbofan engines and the analysis of previous test data. The change in thrust is quantified using a mathematical model integrated in an error propagation study by means of Monte Carlo simulations. The influence of the external flow and wing pressure field is further studied through a numerical analysis in RANS-SST for a very high bypass ratio TPS unit, and a Through-Flow Nacelle respectively. The latter configuration is also tested in the Low Speed Tunnel in DNW to investigate which instrumentation can be used to detect external flow effects in the future. In this case the velocity in the fan exhaust plane is measured with a hot wire and static pressure sensors are placed in the intake, exhaust and boattail.The theoretical, numerical and experimental approach show that the external flow and wing pressure field change the conditions in the TPS exhaust with respect to static calibration. In the wind tunnel, the nozzle exhaust shear layer decreases in size as the difference in velocities between plume and free air is decreased, reducing the flow spreading rate and increasing the local pressure at the nozzle exit plane. The local Nozzle Pressure Ratio is reduced. This leads to flow suppression, the reduction of the fan mass flow and exhaust velocity. In addition, the scrubbing and boattail drag, currently bookkept as loss of thrust in the modified standard net thrust, are changed from static to wind tunnel conditions. These effects change the TPS thrust leading towards an improperly bookkeeping of the aircraft installation drag. The bias error produced by external flow effects is one order of magnitude higher than the random instrumentation error and should be corrected for, especially at low power settings. Differences decrease proportionally to the Fan Nozzle Pressure Ratio until chocked conditions are reached, where the freestream velocity has no influence in the TPS performance. A possible solution lies in the advanced derivation of thrust and drag. The current approach neglects the thrust contribution from the nozzle exhaust to infinite downstream. According to the definition of the Jones thrust, a better solution lies in the assumption that the flow is expanded from the exhaust to infinity downstream without any transfer of energy of momentum. The decrease in mass flow and velocity can be effectively captured by pressure taps located at the intake or fan plane. A linear correlation exists between both stations, that can be used for the bookkeeping of the TPS thrust in the wind tunnel according to additional calibration in the wind tunnel. The new bookkeeping method can also be used to correct for the decrease in local jet exhaust Mach number from design conditions, the parameter of interest in engine/airframe integration tests. The research presents and solves the limitations of the new generation of turbofan engines by accounting for the local conditions at the TPS exhaust due to external flow effects. The new thrust/drag bookkeeping method leads to optimized configurations by improving the accuracy of engine/airframe integration tests.Aerospace Engineerin

Robust Design of 3D Shock Control Bumps to Transport Aircraft under Realistic Uncertainties

With the continuous increase in the number of commercial flights, environmental and economic concerns are key drivers towards the reduction of operational cost and emission of greenhouse gasses. The use of aerodynamic shape optimization plays a key role in reducing aerodynamic drag and the overall carbon footprint of aircraft. It has been regularly carried out in a deterministic fashion, neglecting uncertainty. However, the sensitivity of the optimal shape to operational and environmental uncertainties can affect the real aircraft performance. A possible solution to increase the robustness of existing aircraft is the development of retrofits that are tailored to the current airliner's operations. Shock control bumps are attractive retrofit for aircraft flying in routes at considerably higher speeds than the design point. The objective of this paper is the robust design of a 3D array of shock control bumps that can be retrofitted to the XRF1 transport aircraft configuration. Realistic uncertainties in Mach number, lift coefficient and altitude are extracted following aircraft surveillance data using the OpenSky Network for a selected air route. A tailored Gradient-Based Robust Design methodology that combines the adjoint method with Gaussian Processes is used for the optimization under these uncertainties. The robust optimum array of bumps is able to mitigate the normal shock wave over the upper surface of the wing, reducing the average drag by 3.2% compared to the clean wing. More importantly, its performance is superior compared to the configurations obtained at single-point and multi-point optimization, showcasing the benefits of a probabilistic formulation for the retrofit of 3D shock control bumps