Methodologies for designing, optimizing, and evaluating possible unconventional aircraft configurations for future civil aviation

A quasi-three-dimensional aerodynamic solver is developed for the aerodynamic analysis of wings in a transonic regime that is able to capture the effect of BLS in hybrid laminar flow control (HLFC) application or transition to turbulent flow for natural laminar flow (NLF). The tool provides accurate results, but without the high computational cost of high-fidelity tools. The solver combines the use of an Euler flow solver characterized by an integral boundary-layer method and linear stability analysis using a approximation for transition prediction. In particular, a conical transformation is adopted, including the determination of the shock-wave position. The solver is implemented in a multidisciplinary design optimization (MDO) framework, including wing weight estimation and aircraft performance analysis. The framework consists of different modules: aerodynamics, structure, suction system analysis, and performance evaluation. Using a genetic algorithm and considering HLFC technology, wing MDO has been performed to find the optimum wing planform and airfoil shape. A backward-swept wing (BSW) aircraft, developed inside the Cluster of Excellence–Sustainable and Energy Efficient Aviation (A) is studied. Novel technologies such as active flow control, limited maximum load factors due to load alleviation, and novel materials allow a fuel weight reduction of 6%.

Battery thermal management system (BTMS) is a complex and highly integrated system, which is used to control the battery thermal conditions in electric vehicles (EVs). The BTMS consists of many subsystems that belong to different disciplines, which poses challenges to BTMS optimization using conventional methods. This paper develops a general variable fidelity-based multidisciplinary design optimization (MDO) architecture and optimizes the BTMS by considering different systems/disciplines from the systemic perspective. Four subsystems and/or subdisciplines are modeled, including the battery thermodynamics, fluid dynamics, structure, and lifetime model. To perform the variable fidelity-based MDO of the BTMS, two computational fluid dynamics (CFD) models with different levels of fidelity are developed. A low fidelity surrogate model and a tuned low fidelity model are also developed using an automatic surrogate model selection method, the concurrent surrogate model selection (COSMOS). An adaptive model switching (AMS) method is utilized to realize the adaptive switch between variable-fidelity models. The objectives are to maximize the battery lifetime and to minimize the battery volume, the fan's power, and the temperature difference among different cells. The results show that the variable-fidelity MDO can balance the characteristics of the low fidelity mathematical models and the computationally expensive simulations, and find the optimal solutions efficiently and accurately.

Comparison of Reynolds Averaging Navier-Stokes (RANS) turbulent models in predicting wind pressure on tall buildings

A multidisciplinary optimization methodology for placement of heat generating semiconductor logic blocks on integrated circuit chips is presented. The methodology includes thermal and wiring length criteria, which are optimized simultaneously using the genetic algorithm. An effective thermal performance prediction methodology based on a superposition method is used to determine the temperature distribution on a silicon chip due to multiple heat generating logic blocks. Using the superposition method, the predicted temperature distribution in the silicon chip is obtained in much shorter time than with a detailed finite element model and with comparable accuracy. The main advantage of the present multidisciplinary design and optimization methodology is its ability to handle multiple design objectives simultaneously for optimized placement of heat generating logic blocks. Capabilities of the present methodology are demonstrated by applying it to several standard benchmarks. The multidisciplinary logic block placement optimization results indicate that the maximum temperature on a silicon chip can be reduced by up to 7.5°C, compared with the case in which only the wiring length is minimized.

Multidisciplinary design optimization of long-range slender guided rockets considering aeroelasticity and subsidiary loads

The main goal of the paper is to develop automatic control design methods for flexible aircraft. The motivation for the research is that such automatic control generation enables the inclusion of the control design algorithms into the multidisciplinary design optimization (MDO) of aircraft design. In such an extended MDO framework, called co-design, the sizing, structural dynamics, aerodynamics and the controllers of the aircraft are optimized in one single step. This way control technologies can be included early-on in the preliminary design stage of aircraft design. Since the control design is model based, first a control oriented aeroservoelastic (ASE) model needs to be developed. The modeling is done via the bottom-up modelling approach. The model generation also needs to be automatic due to parameter changes resulting from the MDO process. The research focuses on flexible aircraft, therefore, the control algorithms include baseline, manoeuvre load alleviation, gust load alleviation and flutter suppression controllers. All of these algorithms needs to be developed in such way that they can automatically executed in the MDO process. The overall MDO framework is implemented in the Remote Component Environment (RCE) and the aircraft investigated is the T-Flex demonstrator of the FLIPASED project. The paper presents the main concepts of the modeling and control synthesis, analysis for the above mentioned four controllers and the most important aspects of integrating such automatic control design methods into the RCE environment.

The German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).

This paper presents a framework for multi-objective and multidisciplinary design optimization using highfidelity analysis tools. In this framework the aerodynamic performance is evaluated based on a Navier‐Stokes equation solver, and the structure dynamics is computed using commercially available finite element software. We employ a genetic algorithm as a robust design optimization tool to facilitate the multi-objective optimization. We also use the response surface approach to tackle the difficulties associated with the organizational complexity and computational burden inherent in the multidisciplinary optimization. The coupling between the fluid solver and structural solver is realized through a thin-plate spline interpolation algorithm. The proposed approach is then used to perform aerostructural optimization of a three-dimensional transonic compressor blade. Our numerical results show that this method can improve the existing design and reduce the required computational time by orders of magnitude.

§A Multidisciplinary Design Optimization (MDOPT) framework has been developed for air vehicle design and analysis. The developed MDOPT system contains a collection of technology modules for performing optimization studies by means of a Graphical User Interface (GUI), and combining robust numerical optimization schemes with higher order computational analysis. A variety of multidisciplinary objective and constraint functions are available, including aerodynamic, weight, mission performance, and stability and control characteristics. This paper is intended to provide an overview of the MDOPT development and test case results for a generic fighter configuration, funded under an Air Force Contract, F33615-982-3014, with Boeing cost match funds. The period of development was established with contract activity beginning in September 1998 and ending April 2002. Continued MDOPT development and design applications are being pursued within Boeing using internal funding.

: This report documents the specific dynamics and mobility factors within a U.S. Army ground vehicle Design of Experiments (DOE) approach to designing an Occupant Centric Platform (OCP) using multi-disciplinary design optimization (MDO). Simplified dynamic and mobility factors that reflect pertinent vehicle design performance in these areas and that can be used in an MDO for an OCP with an underbody blast survivability focus are described. The calculation of each factor is based on portable scripts that fit well into the MDO framework.

The objective of this research is to examine how to design low-airframe-noise transport aircraft using Multidisciplinary Design Optimization (MDO). This involves optimizing aircraft to minimize maximum-take-off-weight, while constraining noise at the approach condition. A design methodology which incorporates noise as a design constraint into an MDO formulation is presented. An MDO framework was designed by integrating aircraft conceptual design tools previously developed at Virginia Tech with the Aircraft Noise Prediction Program (ANOPP). Design studies are presented for cantilever wing and Strut-Braced Wing (SBW) transport aircraft with 300 passengers and a 7,700 nm range. The results show that reducing airframe noise by reducing approach speed alone, will not provide significant noise reduction without a large performance and weight penalty. Therefore, more dramatic changes to the aircraft design are needed to achieve a significant airframe noise reduction. Another study showed that the trailing-edge (TE) flap can be eliminated, as well as all the noise associated with that device, without incurring a significant weight and performance penalty. If noise due to the leading-edge (LE) slats and landing gear are reduced, which is currently being pursued, the elimination of the flap will be very significant as the clean wing noise will be the next ‘noise barrier’. Lastly, an airframe noise analysis showed that a SBW aircraft, with short fuselage-mounted landing gear, could have a similar or potentially a lower airframe noise level than a cantilever wing aircraft.

Boundary-layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting tightly coupled aeropropulsive effects. NASA’s Single-aisle Turboelectric Aircraft with Aft Boundary-Layer propulsion (STARC-ABL) concept employs BLI on an electrically powered tail cone thruster to take advantage of the technology on what is otherwise a conventional airframe. Despite the traditional airframe of this concept, aeropropulsive integration is critical to the BLI propulsor’s performance. Therefore, it is vital to employ tightly coupled aeropropulsive models to design BLI systems. In this work, 3-D RANS simulations are used to model the aerodynamics, and 1-D thermodynamic cycle analyses are used to model the propulsion system. The two models are tightly coupled using NASA’s OpenMDAO framework, enabling efficient design optimization through gradient-based optimization with analytic derivatives. Using this coupled aeropropulsive framework, 18 computational fluid dynamics (CFD)-based aeropropulsive design optimizations are performed to study the power requirements of the BLI configuration and a reference podded configuration where the electric fan ingests freestream air. This study provides the first set of CFD-based performance data for the STARC-ABL concept across the design space of BLI fan size and pressure ratio. The results quantify the power savings through BLI compared to a traditional propulsion system.

This paper presents the results of reverse-engineering (RE) strategies, surface roughness and computational fluid dynamics (CFD) modelling for a Wren100 micro gas turbine (MGT). Utilising silicone moulds and resin tooling, precise blade geometry capture was achieved for 3D reconstruction allowing for discrete and parametric geometric models to be created. Using these geometries, CFD simulations employing both Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) models, alongside experimental wind tunnel cascade tests, were used to evaluate these reverse engineering strategies. The results show that while the parametric model captures overall MGT performance with fewer parameters, the discrete model provides enhanced accuracy, highlighting its suitability for detailed aerodynamic analyses. Contrary to initial expectations, surface roughness exhibited a noticeable impact on performance despite the lower Reynolds numbers (40,000), as demonstrated by the CFD model and wind tunnel experiments. The results indicate that surface roughness can reduce laminar separation bubbles on the blade leading edge, delay the onset of transition, and mitigate secondary flow losses. Overall, this study contributes to knowledge advancement in turbine blade reverse engineering and aerodynamics by detailing the impact of surface roughness on performance.

In support of NASA’s next generation heavy lift launch vehicle (HLLV), a simulation protocol has been developed to generate databases of the aerodynamic force and moment coefficients for HLLV ascent. The simulation protocol has been established and validated with a series of computational analyses that ensure best practices are achieved. Results of the sensitivity analyses using a full-scale Ares V flight vehicle are next applied in a validation study with three scaled-down Ares V wind tunnel test articles. Three independent computational fluid dynamic (CFD) flow solvers were included in the study. These included OVERFLOW, a viscous Reynolds Averaged Navier-Stokes (RANS) solver for structured overset grids, USM3D, a viscous RANS solver for unstructured tetrahedral grids, and Cart3D, an inviscid Euler solver using unstructured Cartesian grids and adjoint-based adaptive mesh refinement. First, a series of tests was independently performed for each applicable CFD code, including a grid convergence study and sensitivity studies of turbulence models and convective flux discretization methods. Once the proper grid resolution, physical models, and numerical parameters were determined for each of the codes, the process was continued with a code-to-code comparison. Each CFD code was applied to the Ares V flight vehicle at several points in the ascent trajectory, with all three codes obtaining consistent force and moment predictions. Finally, an extensive validation of the CFD approach was performed, in which the three codes were used to generate aero-databases of force and moment coefficients for three distinct Ares V wind tunnel test articles. These computations were performed concurrent to the experimental databases generated in the 14-inch wind tunnel at Marshall Space Flight Center (MSFC). Comparisons of the CFD results with the experimental data are reported and the viscous flow results compare well.

Simulation of tidal turbine array using coupled Computational Fluid and Rigid Body Dynamics