Use Scenarios for Design Space Exploration With a Dynamic Multiobjective Optimization Formulation

Author(s):  
Shane K. Curtis ◽  
Braden J. Hancock ◽  
Christopher A. Mattson

In a recent publication, we presented a new strategy for engineering design and optimization, which we termed formulation space exploration. The formulation space for an optimization problem is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem formulations. By extending a computational search into this new space, the solution to any optimization problem is no longer predefined by the optimization problem formulation. This method allows a designer to both diverge the design space during conceptual design and converge onto a solution as more information about the design objectives and constraints becomes available. Additionally, we introduced a new way to formulate multiobjective optimization problems, allowing the designer to change and update design objectives, constraints, and variables in a simple, fluid manner that promotes exploration. In this paper, we investigate three use scenarios where formulation space exploration can be utilized in the early stages of design when it is possible to make the greatest contributions to development projects. Specifically, we look at s-Pareto frontier generation in the formulation space, formulation space boundary exploration, and a new way to perform inverse optimization. The benefits of these methods are illustrated with the conceptual design of an impact driver.

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Edgar Galvan ◽  
Richard J. Malak

It is important for engineers to understand the capabilities and limitations of the technologies they consider for use in their systems. However, communicating this information can be a challenge. Mathematical characterizations of technical capabilities are of interest as a means to reduce ambiguity in communication and to increase opportunities to utilize design automation methods. The parameterized Pareto frontier (PPF) was introduced in prior work as a mathematical basis for modeling technical capabilities. One advantage of PPFs is that, in many cases, engineers can model a system by composing frontiers of its components. This allows for rapid technology evaluation and design space exploration. However, finding the PPF can be difficult. The contribution of this article is a new algorithm for approximating the PPF, called predictive parameterized Pareto genetic algorithm (P3GA). The proposed algorithm uses concepts and methods from multi-objective genetic optimization and machine learning to generate a discrete approximation of the PPF. If needed, designers can generate a continuous approximation of the frontier by generalizing beyond these data. The algorithm is explained, its performance is analyzed on numerical test problems, and its use is demonstrated on an engineering example. The results of the investigation indicate that P3GA may be effective in practice.


Author(s):  
Xin Zhao ◽  
Smruti Sahoo ◽  
Konstantinos Kyprianidis ◽  
Sharmila Sumsurooah ◽  
Giorgio Valente ◽  
...  

Abstract To achieve the goals of substantial improvements in efficiency and emissions set by Flightpath 2050, fundamentally different concepts are required. As one of the most promising solutions, electrification of the aircraft primary propulsion is currently a prime focus of research and development. Unconventional propulsion sub-systems, mainly the electrical power system, associated thermal management system and transmission system, provide a variety of options for integration in the existing propulsion systems. Different combinations of the gas turbine and the unconventional propulsion sub-systems introduce different configurations and operation control strategies. The trade-off between the use of the two energy sources, jet fuel and electrical energy, is primarily a result of the trade-offs between efficiencies and sizing characteristics of these sub-systems. The aircraft structure and performance are the final carrier of these trade-offs. Hence, full design space exploration of various hybrid derivatives requires global investigation of the entire aircraft considering these key propulsion sub-systems and the aircraft structure and performance, as well as their interactions. This paper presents a recent contribution of the development for a physics-based simulation and optimization platform for hybrid electric aircraft conceptual design. Modeling of each subsystem and the aircraft structure are described as well as the aircraft performance modeling and integration technique. With a focus on the key propulsion sub-systems, aircraft structure and performance that interfaces with existing conceptual design frameworks, this platform aims at full design space exploration of various hybrid concepts at a low TRL level.


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