Progress Towards Multidisciplinary Design Optimization of Truss Braced Wing Aircraft with Flutter Constraints

This paper discusses current work on STRUCTURAL ASPECTS OF the design optimization of a Truss Braced Wing (TBW) configuration. These wings offer significat potential for performance improvements in terms of fuel efficiency, but also offer challenges for a structural designer. The details of the structural analysis and design methodology are presented. Two different design methodologies are discussed: structural sizing based on beam idealization considering only bending stiffness and static analysis, and a finite element based sizing optimization approach including aeroelastic effects. The paper reports all aspects of the two approaches: design parameterization, model geometry and mesh generation, analysis and optimization. The first approach has been used in the past at Virginia Tech for Multidisciplinary Design Optimization (MDO) studies of a Strut-Braced Wing (SBW), and extensions to sizing of a more general TBW configuration are discussed. The second approach is used to perform some parametric studies presented here. Comparative studies are performed for wings designed for rigid and flexible trim subject to static stress constraints. The aeroelastic performance of some TBW configurations is investigated. Only structural sizing parameters are treated as design variables. Conclusions are drawn from these results for guidance to the ongoing MDO studies of the TBW, to be reported in future papers.

This paper presents a study of aircraft featuring truss-braced wing configurations that have been optimized for minimum fuel consumption using multidisciplinary design optimization. The investigation proceeds following an earlier Boeing Subsonic Ultra Green Aircraft Research study, which selected the truss-braced wing concept as the most promising of several concept vehicles. This comes from the fact that a significantly higher-aspect-ratio wing could achieve substantial reductions in induced drag but requires major structural changes to support such a large span. This problem was explored through the use of a multidisciplinary design and analysis environment implemented in ModelCenter®. Optimization was performed using ModelCenter’s Design Explorer and Darwin genetic algorithm optimizers. Using the multidisciplinary environment, a large multidimensional design space, featuring design variables spread across the major aircraft design disciplines, was explored. Configurations featuring a strut-braced wing and truss-braced wings with one and two juries were evaluated for different span limits. Subsequently, different laminar wing design options were investigated in conjunction with lift augmentation system options. The multidisciplinary optimization used for this investigation was able to produce candidate designs with the desired attributes and performance improvements while satisfying all relevant geometric and performance constraints.

The implementation of a general and flexible method of formulating problems of mathematical programming in structural and multidisciplinary optimization systems is described. The method, which is based on the so-called bound formulation, enables the formulation and solution of problems involving local, integral, mintmax, maxlmin and possibly non-differentiable user-defined functions in any conceivable mix and using user-defined mathematical functions. The computer implementation involves a parser capable of interpreting and performing symbolic dfierentiation of the user defined functions. A sample problem of thermo-elasticity is given. It is concluded that this approach is well suited for multidisciplinary design optimization systems. 1. Motivation One of the great challenges of research in design automation is the development of practically applicable systems for multidisciplinary design optimization. Such systems will, if they are truly generally applicable, cause a revolution in the way design laboratories work. Several papers with the focus on system design rather than single applications have emerged in recent years. Some examples are Esping (1986), Rasmussen (1989), Papalarnbros & Chirehdast (1990), Choi & Chang (1991), Botlun et. al. (1 992), Rasmussen et. al. (1993), and Cardoso & Santos (1 993). Obtaining the necessary generality, however, is a very difficult task. Designing even simple components involves many different considerations. For the sake of the argument, we may categorize them into groups of increasing complexity: The functional behavior, for instance weight, energy consumption, power output, efficiency, eigenfrequencies, strength, stiffness, pressures, velocities, accelerations, temperatures, electric and magnetic properties, etc. These qualities can often be modeled mathematically and analyzed by means of digital computers. The fabricational behavior, for instance the cost of machining, the necessary production facilities, the necessary manpower, stock and inventory, financial requirements, etc. These properties are usually very difficult to analyze because of the many degrees of freedom in choice of production planning and processes, the dependency of other products manufactured simultaneously, and even the dependence on the economic boundary conditions formed by the outside world. The aesthetic properties that are impossible to evaluate objectively, but are none the less tightly connected with the functional and fabricational properties. For instance, the shape of the hull of a ship determines strength, stiffness and drag properties, but it also forms an important part of the visual impression. In the development of multidisciplinary systems, we have only begun to cover the first category of product properties, so it may be argued that there is still a long way to go. At the Institute of Mechanical Engineering, Aalborg University, Denmark, a system for multidisciplinary design optimization is under development. The system is called 'Associate Professor of Mechanical Engineering '+~esearch Assistant Copyright O 1994 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Multidisciplinary design optimization (MDO) is expected to play a major role in the competitive transportation industries of tomorrow, i.e., in the design of aircraft and spacecraft, of high speed trains, boats, and automobiles. All of these vehicles require maximum performance at minimum weight to keep fuel consumption low and conserve resources. Here, MDO can deliver mathematically based design tools to create systems with optimum performance subject to the constraints of disciplines such as structures, aerodynamics, controls, etc. Although some applications of MDO are beginning to surface, the key to a widespread use of this technology lies in the improvement of its efficiency. This aspect is investigated here for the MDO subset of structural optimization, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures (here, statically indeterminate trusses and beams for proof of concept) is performed. In the system level optimization, the design variables are the coefficients of assumed displacement functions, and the load unbalance resulting from the solution of the stiffness equations is minimized. Constraints are placed on the deflection amplitudes and the weight of the structure. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. This approach is expected to prove very efficient, especially for complex structures, since the design task is broken down into a large number of small and efficiently handled subtasks, each with only a small number of variables. This partitioning will also allow for the use of parallel computing, first, by sending the system and subsystems level computations to two different processors, ultimately, by performing all subsystems level optimizations in a massively parallel manner on separate processors. It is expected that the subsystems level optimizations can be further improved through the use of controlled growth, a method which reduces an optimization to a more efficient analysis with only a slight degradation in accuracy. The efficiency of all proposed techniques is being evaluated relative to the performance of the standard single level optimization approach where the complete structure is weight minimized under the action of all given constraints by one processor and to the performance of simultaneous analysis and design which combines analysis and optimization into a single step. It is expected that the present approach can be expanded to include additional structural constraints (buckling, free and forced vibration, etc.) or other disciplines (passive and active controls, aerodynamics, etc.) for true MDO.

Effect of Variable Selection on Multidisciplinary Design Optimization: a Flight Vehicle Example

Response surface methods have been used for a variety of applications in aerospace engineering, particularly in multidisciplinary design optimization. We investigate the use of kriging models as alternatives to traditional second-order polynomial response surfaces for constructing global approximations for use in a real aerospace engineering application, namely, the design of an aerospike nozzle. Our objective is to examine the difeculties in building and using kriging models to create accurate global approximations to facilitate multidisciplinary design optimization. Error analysis of the response surface and kriging models is performed, along with a graphical comparison of the approximations. Four optimization problems are also formulated and solved using both sets of approximation models to gain insight into their use for multidisciplinary design optimization. We end that the kriging models, which use only a constant “global” model and a Gaussian correlation function, yield global approximations that are slightly more accurate than the response surface models.

The development of high-fidelity multidisciplinary analysis and optimization (MDAO) capabilities is essential for advancing modern aerospace vehicle design. Traditional workflows often suffer from limited interoperability between structural solvers, aerodynamic tools, and optimization frameworks. To address these limitations, this project focuses on integrating NASTRAN, a structural solver, into the OpenMDAO framework. This effort was conducted under NASA Contract 80GRC023CA047 by M4 Engineering, Inc., as part of the broader initiative to enhance Model-Based Systems Analysis and Engineering (MBSA&E) capabilities. The primary objective of the project was to develop a robust, reusable, and modular Python-based interface that allows NASTRAN to interface within OpenMDAO workflows and improve structural optimization capabilities. This enables engineers to leverage NASTRAN's structural analysis and sensitivity capabilities while benefiting from OpenMDAO's flexibility and advanced optimization drivers. In support of this objective, multiple demonstration models were created across various NASTRAN solution sequences (SOLs), including static, aeroelastic, flutter, and buckling analyses. These models were used to evaluate the accuracy, robustness, and computational performance of the integration. Additionally, capabilities were developed to extract sensitivity data, aggregate constraint outputs, and streamline the generation of OpenMDAO components from existing NASTRAN input decks. The work described herein also included integration of third-party aerodynamic tools (e.g., transonic CFD solvers and GROM) with OpenMDAO, development of representative aircraft configurations such as the truss-braced wing (TTBW) and blended-wing body (BWB), and final deployment into NASA's Aviary conceptual design framework. The outcomes of this project provide a foundation for future multidisciplinary optimizations using high-fidelity structural models and demonstrates some of the challenges.

This study investigates the effect of a novel wing-tip on the aeroelastic behavior of passenger aircraft with very flexible truss-braced wings (TBW). These flexible TBW designs are obtained from the multidisciplinary design optimization (MDO) tool presented here while minimizing fuel burn of a double-aisle aircraft having a flight mission similar to a Boeing 777-200 LR. The novel wing-tip mechanism which can sweep forward and aft relative to the wing is termed the Novel Control Effector (NCE). Results show that the NCE tip can be used to achieve required roll control by judiciously sweeping it relative to the wing at various flight conditions. It has an added benefit that it can also be used for flutter avoidance. Such benefits of the NCE tip allows the operation of TBW configurations which have up to 12% lower fuel burn than comparable optimized conventional cantilever wing designs. Without the NCE tip, such configurations have both less than desirable flutter margin and roll control capability. The NCE tip is thus an enabling technology for truss-braced wing aircraft.

Multidisciplinary Design Optimization (MDO) has been used to investigate the use of anew concept for a transonic transport, the strut-braced wing. The incorporation of a strutinto more traditional transonic transport concepts required the application of computationaldesign techniques that had been developed at Virginia Tech over the previous decade.Formalized MDO methods were required to reveal the benefits of the tightly coupledinteraction between the wing structural weight and the aerodynamic performance. Toperform this study, a suite of approximate analysis tools was assembled into a complete,conceptual-level MDO code. A typical mission of the Boeing 777-200IGW was chosen as thedesign mission profile. Several single-strut configurations were optimized for minimumtakeoff gross weight, with the best single-strut configuration showing a nearly20% reductionin takeoff gross weight, a 29% reduction in fuel weight, a 28% increase in the lift-to-dragratio, and a 41% increase in seat-miles per gallon relative to a comparable cantileverconfiguration. The use of aeroelastic tailoring in the design illustrated ways to obtain furtherbenefits. The paper synthesizes the results of the five-year effort, and concludes with adiscussion of the effects various constraints have on the design, and lessons learned oncomputational design during the project.

The editors of Structural and Multidisciplinary Optimization and Springer-Verlag are pleased to announce a new service for our authors and readers: Online First, the immediate online publication of all accepted papers as soon as the authors have returned the corrected proofs. Whereas the fully electronic versions of Structural and Multidisciplinary Optimization used to appear at the same time as the printed journal, from now on the electronic version of all articles will be available to subscribers via the Internet weeks before the printed version appears. This means an enormous reduction in publication time. It will no longer be necessary for manuscripts to wait until the “next available issue”. As each paper is ready for publication, it will be published on the Web with its own publication date as follows: “Published online: ”. Each article will receive an international identification code – the “Digital Object Identifier” (DOI), which is registered with the International DOI Foundation and is unique, like the ISBN for books or the ISSN for periodicals. Contributions published Online First are citable by journal title and DOI. The print version will also have the final page numbers, the DOI and the online publication date. Furthermore, the DOI is linked to the URL (Uniform Resource Locator) and the bibliography when the printed issue is released. The DOI is never changed and can be used, for example, to create hyperlinks between Online First articles. Online First articles appear in their final form. Therefore, papers cannot be changed or withdrawn after electronic publication. Any corrections that might be necessary have to be made in an Erratum, which will be hyperlinked to the article. Each article will be announced in LINK alert, which is a free alerting service (http://link.springer.de/alert). A table of contents showing all papers that have been accepted for publication in Structural and Multidisciplinary Optimization but not yet printed can be found via the Springer Web page: http://link.springer.de/link/service/journals/ 00158/tocs.htm or http://link.springer-ny.com/link/service/journals/ 00158/tocs.htm by clicking Online First.

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.

Multidisciplinary design optimization (MDO) using design of experiments (DoE) and response surface method (RSM) is one of the effective methods for reducing weight of car body structure. However, large amount of information obtained from the optimization makes the optimization itself not useful. This problem is caused by large number of variables of vehicle model. This paper proposes a trade-off analysis process using sensitivity analysis, multi-objective optimization, hierarchical cluster analysis and parallel coordinate plot for analyzing optimization information. As a result, it was clarified very important parts for reducing body weight. Accordingly, even the designers without the expert knowledge may easily be able to make a knowledge discovery for car-body weight reduction.

Aircraft can be used for many different purposes. To be able to design a successful aircraft proper discovery and understanding of objectives is essential. The same is true of all the constraints that limit the design space. Such constraints can be derived from the combination of market analysis, flight dynamics, flight performance, and airworthiness requirements. Designing superior aircraft is a multidisciplinary multi‐level systems engineering challenge. This chapter describes various objectives and constraints designers must address in order to design acceptable products. While the technologies of systems engineering and multidisciplinary optimization are not the subject of this chapter, it is important to master these technologies so that design problem definition and formulation are done properly. The presentation of objectives and constraints here reflects associated airplane design practices and the state of the art of systems engineering and multidisciplinary design optimization.

To make the engine design intelligent and automatic, multi-disciplinary design optimization (MDO) is applied to explore engine's design. The design of modern engine concerns multi-subsystem and multi-disciplinary, which coupling each other. MDO is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. The integrated intelligent platform provides the integration for multi-disciplinary, which includes the methods design of experiment, response surface, approximate model and optimization, which can explore the variables' relationship and couple subsystem and realize the tightly coupled such as aerodynamics and structural weight, perform their balanced design and obtain their best synergism. The integrated plat is applied to the inlet system of gasoline engine, the optimal inlet system help save the fuel consumption obviously, the relationship of variables is studied by the response surface model. The integrated intelligent systems will play more important role to improve engine's energy efficiency.

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.