A Modern CORBA-Based Approach to Ad Hoc Distributed Process Orchestrations Applied to MDO

§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 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.

This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs) when the primary focus is o ...

DOI: 10.2514/1.19969 Multidisciplinary designoptimization isanimportant approachfor the conceptualdesignof space planesbecause these planes are characterized by disciplines that interact with one another. A multidisciplinary design optimization problemof asingle-stage-to-orbit space plane isformulated andsolved inthis study.Themodeling andoptimization ofrigidbodycharacteristics,suchastrimandstability,arefocusedonbecauseasingle-stage-to-orbitspaceplanehas a tendency for considerable shift of both the aerodynamic center and the center of gravity. Moreover, the design of the air-breathing engines are integrated with the airframe and its effect on the rigid body characteristics are also modeled in the framework of multidisciplinary design optimization. Using the all-at-once-based multidisciplinary design optimization approach, which incorporates sparse nonlinear programming and metamodeling, the design of the vehicle and its flight trajectory are successfully optimized. Finally, the characteristics of the optimal solution are investigated, especially the relationships among the airframe-engine integration, rigid body characteristics, and payload transportation capability.

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.

Due to technological evolution and the development of several environmental aerospace projects, the aeronautical community has been implementing advanced design strategies, aiming to find next-generation configurations that allow mitigating the undesirable impact of aircraft on the environment. Unconventional solutions have attracted the attention of designers, and several aircraft concepts have been proposed in order to achieve ambitious goals. Given the lack of significant design experience with unconventional aircraft, Multidisciplinary Design Optimization (MDO) frameworks enable to understand the impact of various technologies, obtaining reductions in energy use per passenger-kilometer beyond that provided by the configuration itself. In this thesis, multifidelity and multidisciplinary optimization methodologies have been applied towards designing a next-generation commercial airliner, which combines a Box-Wing configuration with Boundary Layer Ingestion (BLI) engines. This project presents four fundamental objectives: (i) To understand the current design issues, methods, and evolving trends of unconventional configurations. This is performed through a compilation of information in the form of a stateof-the-art literature review. (ii) To develop a low-fidelity MDO method to determine the main geometric, aerodynamic, stability, propulsion and performance characteristics of the aircraft, based on its design requirements and constraints. (iii) To carry out Computational Fluid Dynamics (CFD) simulations and wind-tunnel experiments on a scale-model of the aircraft, in order to perform a back-to-back analysis of non-boundary layer ingesting and boundary layer ingesting versions of the aircraft. (iv) To implement a high-fidelity Aerodynamic Shape Optimization method for the Box-Wing concept based on Reynolds-Averaged Navier-Stokes (RANS) equations.

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%.

The exploration of polar regions has become increasingly critical due to rapid climate change and the strategic significance of Arctic resources. Autonomous Underwater Vehicles (AUVs) serve as the primary modality for data acquisition in these harsh, ice-covered environments. However, the operational reliability of AUVs is severely compromised by multi-source uncertainties, including complex under-ice hydrodynamics, acoustic communication failures, variable sea ice draft, and stochastic sensor errors. Traditional deterministic optimization methods often fail to account for these variabilities, leading to designs that are optimal in theory but fragile in practice. This paper proposes a comprehensive Multidisciplinary Design Optimization (MDO) framework integrated with Monte Carlo simulations to enhance the robustness of AUVs operating under polar ice. We define a stochastic coupling mechanism that links hydrodynamic, structural, energy, and navigation subsystems. By embedding Monte Carlo sampling within the optimization loop, we evaluate the probability of mission success and enforce reliability constraints against environmental and systemic uncertainties. The results demonstrate that the proposed robust optimization approach significantly reduces the variance in mission performance metrics compared to deterministic baselines. We provide a detailed analysis of the trade-offs between optimality and reliability, offering a theoretical foundation for the next generation of polar-class AUVs.

Hierarchical design scenarios arise when the performance of large-scale, complex systems can be affected through the optimal design of several smaller functional units or subsystems. Monte Carlo simulation provides a useful technique to evaluate probabilistic uncertainty in customer-specified requirements, design variables, and environmental conditions while concurrently seeking to resolve conflicts among competing subsystems. This paper presents a framework for multidisciplinary simulation-based design optimization, and the framework is applied to the design of a Formula 1 racecar. The results indicate that the proposed hierarchical approach successfully identifies designs that are robust to the observed uncertainty.

: 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.

The Electrical Wiring Interconnection System is a complex system that contributes significantly to aircraft weight. Novel aircraft configurations require new system layouts, and the increase in the electrification of aircraft and their subsystems adds significantly to the complexity. Despite its impact on weight, wire routing remains a mainly manual and cumbersome task that is not considered early enough. Future aircraft design exploration can benefit from improved wire routing and weight estimation in the early design phases. This paper proposes a method for automated wire routing, aiming to estimate wire length and weight with sufficient precision, thereby enabling the investigation of different component placements within a multi-disciplinary design analysis and optimization framework. The presented automated wire routing tool utilizes simplified routing models and parametric geometric information to estimate wire length, eliminating the need for detailed geometric models. The tool also incorporates key regulatory requirements, such as system segregation, separation to mitigate electromagnetic interference, and maintaining the required bend radius while avoiding obstacles and no-go areas. The path between the two components is computed using the A* (A-star) graph-based path-finding algorithm. A representative case study for the communication system and flap control system demonstrates the effectiveness of the methodology: the wire length can be estimated with an average relative error of 12% in a few seconds. This enables efficient trade-offs in component layout configurations in the conceptual design stages of aircraft development.

Floating offshore wind turbines (FOWTs) are still in the pre-commercial stage and, although different concepts of FOWTs are being developed, cost is a main barrier to commercializing the FOWT system. This article aims to use a shape parameterization technique within a multidisciplinary design analysis and optimization framework to alter the shape of the FOWT platform with the objective of reducing cost. This cost reduction is then implemented in 30 MW and 60 MW floating offshore wind farms (FOWFs) designed based on the static pitch angle constraints (5 degrees, 7 degrees and 10 degrees) used within the optimization framework to estimate the reduction in the levelized cost of energy (LCOE) in comparison to a FOWT platform without any shape alteration–OC3 spar platform design. Key findings in this work show that an optimal shape alteration of the platform design that satisfies the design requirements, objectives and constraints set within the optimization framework contributes to significantly reducing the CAPEX cost and the LCOE in the floating wind farms considered. This is due to the reduction in the required platform mass for hydrostatic stability when the static pitch angle is increased. The FOWF designed with a 10 degree static pitch angle constraint provided the lowest LCOE value, while the FOWF designed with a 5 degree static pitch angle constraint provided the largest LCOE value, barring the FOWT designed with the OC3 dimension, which is considered to have no inclination.

A web services-based multidisciplinary design optimization framework for complex engineering systems with uncertainties