Advanced Research Laboratory for Multifunctional Lightweight Structures (ARL-MLS) MDO

Research in Multidisciplinary Design Optimization

Problem Statement

The utilization of Multidisciplinary Design Optimization (MDO) is an increasingly popular field of R&D in several industries such as oil, aerospace, energy, automotive, etc. ARL MLS has been at the forefront of applying novel MDO methodologies in several such applications and continues to expand its domain based on complimentary technological practices such as computational mechanics, engineering design, biomedical product development, concurrent engineering, virtual product development and many more. Dealing with large systems problems, we provide sustainable optimization solutions while considering uncertainties and tailored developing Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods. Some of our interests include:

Accurate Coupled System modelling and execution.
Cost efficient computational framework for large systems.
Lack of application specific methodologies and guidelines.
Advanced decision-making processes for smart automation.
Visualization of multidimensional systems and their interaction.
Uncertainty handling for reliable design solutions.

Solutions

To overcome the many global challenges in the field of MDO, ARL – MLS has been actively developing cutting edge solutions such as:

Realtime validated system models for precise analysis and optimization.
Tested algorithms and advanced surrogate models for efficient computation.
Avionics targeted design methodologies with high fidelity constraints for improved performance.
Multi Criteria Decision Making (MCDM) infused Machine Learning (ML) and Artificial Intelligence (AI) induced models for higher order decision making.
State of the art architectures and frameworks for system mapping and formulation.
Advanced Reliability/ Possibility Based Design Optimization (RBDO / PBDO) methods to compute uncertainties for reliable system design.
Applying multiple optimization regimes such as topology, topography, DFX and DOE methods to enrich subsystem and component design.

Projects

Uncertainty Based MDO

Abstract

Aircraft conceptual design traditionally utilizes simplified analysis methods and empirical equations to establish the basic layout of new aircraft. Applying optimization methods to aircraft conceptual design may yield solutions that are found to violate constraints when more sophisticated analysis methods are introduced. The designer’s confidence that proposed conceptual designs will meet their performance targets is limited when conventional optimization approaches are utilized. Therefore, there is a need for an optimization approach that takes into account the uncertainties that arise when traditional analysis methods are used in aircraft conceptual design optimization. This research introduces a new aircraft conceptual design optimization approach that utilizes the concept of Reliability Based Design Optimization (RBDO). A framework for multi-objective, multidisciplinary RBDO was developed for this purpose. The performance and effectiveness of the RBDO-MDO approaches implemented were evaluated to identify the most promising approaches for aircraft conceptual design optimization. Additionally, an approach for quantifying the errors introduced by approximate analysis methods was developed. The approach leverages available historical data to quantify the uncertainties introduced by approximate analysis methods in two engineering case studies: the conceptual design optimization of an aircraft wing box structure and the conceptual design optimization of a commercial aircraft. The case studies were solved with several of the most promising RBDO-MDO integrated approaches. The proposed approach yields more conservative solutions and estimates the risk associated with each solution, enabling designers to reduce the likelihood that conceptual aircraft designs will fail to meet objectives later in the design process.

Citation

Park, H. U., Chung, J., Behdinan, K., and Lee, J. W., “Multidisciplinary Wing Design Optimization Considering Global Sensitivity and Uncertainty of Approximation Method”, Journal of Mechanical Science and Technology, Vol. 28 (6), 2231-2242, 06/2014.

Aircraft Derivative Design Optimization Process

Abstract

Aluminum Cross-Car Beam is significantly lighter than the conventional steel counterpart and presents superior energy absorption characteristics. The challenge is however, its considerably higher cost, rendering it difficult for the aluminum one to compete in the automotive market. In this work, using material distribution techniques and stochastic optimization, a Multidisciplinary Design Optimization procedure is developed to optimize an existing CrossCar Beam model with respect to the cost. Topology, Topography, and gauge optimizations are employed in the development of the optimization disciplines. Based on a qualitative cost assessment, penalty functions are designed to penalize costly designs. Noise-VibrationHarshness (NVH) performance is the key constraint of the optimization. To fulfill this requirement, natural frequencies are obtained using modal analysis. Undesirable designs with respect to the NVH criteria are gradually eliminated from the optimization cycles. The new design is verified by static loading scenario and evaluated in terms of the cost saving it offers.

Citation

Rahmani, M., and Behdinan, K., “PSO-based Multidisciplinary Design Optimization of Cross-Car Beam Assembly”, Proceedings of the CSME Congress 2014, Toronto, ON, 06/2014.

Aluminum Cross-Car Beam Optimization

Abstract

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet the new market demands while keeping the development time and the cost to a minimum. Many researchers have studied the derivative design process, but these research considered the baseline and the derivatives together, while using the whole set of design variables. Therefore, an efficient process that can reduce the cost and the time for the aircraft derivative design is needed. In this dissertation, Aircraft Derivative Design Optimization process (ADDOPT) was developed which obtains the global changes from the local changes in the aircraft design to develop the aircraft derivatives efficiently. The sensitivity analysis was implemented to ignore design variables that have low impact on the objective function. This avoids wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, the classification of uncertainty from its characteristics and sources of uncertainty involved in the aircraft design process were suggested to consider with design optimization. Uncertainty from the fidelity of analysis tools was applied in design optimization to increase the probability of optimization results. To handle uncertainty in low fidelity analysis tools on aircraft conceptual design optimization, Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were performed. In this research, Extended Fourier Amplitude Sensitivity Test (eFAST) method was implemented in ADDOPT for Global Sensitivity Analysis (GSA) method and Collaborative Optimization (CO) based framework with RBDO and PBDO were also used. These methods were evaluated using numerical examples. ADDOPT was carried through on the civil jet aircraft derivative design. The objective of the optimization problem was to increase cruise range while satisfying the requirement such as the number of passengers. The proposed process reduced computation effort by reducing the number of design variables and achieved the target probability of failure when considering uncertainty from low fidelity analysis tools.

Citation

Park, H. U., Lee, J. W., Byun, Y. H., Chung, J., and Behdinan, K., “A new process for the requirements based aerospace system design and optimization”, The Korean Society for Aerospace and Space Sciences, Vol. 37 (3), 255-266, March 2009.

Framework for Control-Configuration Integration in Aircraft Conceptual Design

Abstract

The emerging flight-by-wire and flight-by-light technologies increase the possibility of enabling and improving aircraft design with excellent handling qualities and performance across the flight envelope. As a result, it is desired to take into account the dynamic characteristics and automatic control capabilities at the early conceptual stage. In this paper, an integrated control-configured aircraft design sizing framework is presented. It makes use of multidisciplinary design optimization to overcome the challenges which the flight dynamics and control integration present when included with the traditional disciplines in an aircraft sizing process. A commercial aircraft design example demonstrates the capability of the proposed methodology. The approach brings higher freedom in design, leading to aircraft that exploit the benefits of control configuration. It also helps to reduce time and cost in the engineering development cycle.

Citation

R. Perez, H. Liu and K. Behdinan, "Multidisciplinary Optimization Framework for Control-Configuration Integration in Aircraft Conceptual Design", Journal of Aircraft, vol. 43, no. 6, pp. 1937-1948, 2006.

Available: 10.2514/1.22263.

Aircraft Conceptual Design Optimization Considering Fidelity Uncertainties

Abstract

Aircraft conceptual design is traditionally carried out by manipulating low-fidelity analysis methods such as empirical equations or simplified physics. In an optimization framework, predicted optimum conceptual designs often lie directly on one or more of the specified constraint boundaries. Any discrepancies introduced by approximating the constraint values may result in designs that are found to fall short of performance targets when subjected to better analysis methods later in the design process. This research uses historical data to estimate the discrepancies associated with the simplified analysis methods commonly used in aircraft conceptual designs. A design optimization framework was developed that implements reliability-based design optimization methods to compensate for the discrepancies associated with the approximate analysis methods. This yields optimized aircraft conceptual designs that are less likely to fail to meet any specified performance requirements when reevaluated using high-fidelity methods later in the design process.

Citation

Neufeld, D., Chung, J., & Behdinian, K. (2011). Aircraft conceptual design optimization considering fidelity uncertainties. Journal of aircraft, 48(5), 1602-1612.