Stirling Engine Systems Tradespace Exploration Framework

Abstract

The purpose of this work is to propose a tradespace exploration framework for the design and system analysis of Stirling engines. The framework can be used to execute trade studies for different objectives. The framework obtains Pareto frontiers of optimal designs by evaluating performance (power, efficiency) and cost metrics for 750 Stirling engine design alternatives. The proposed system design framework integrates four domain models. An engine cycle thermodynamic model is to calculate engine cycle and performance parameters. A heat exchanger model is to estimate areas of heat exchangers. An economic model to predict the capital cost of the engine system. And a tradespace model based on five design parameters identified as drivers of the design: Stirling engine type (alpha, beta, or gamma), engine bore, stroke, hot space temperature, and cold space temperature. The results of the model shed insights on the design of Stirling engines and develop guidelines to identify the most suitable combinations of engine architectures and design parameters to address specific applications. The paper shows how the proposed framework can be applied to the design of Stirling engines for two different applications, namely waste heat recovery and combined heat and power generation for residential real estate units. Considering the identified customer needs for these two applications, the results of the study indicate that alpha-type Stirling engines are more appropriate for industrial waste heat recovery, e.g. heat treating furnaces and cement kilns, having a power output 50% higher for a given efficiency then other engine types. Beta-type engines result more beneficial for residential combined heat and power generation. Gamma-type engines result advantageous for low power applications such as toy models and tool kit engines.

Novelty genesis: the mechanism of forming the new from the old

“…Factors related to technology affect strategy, market applications, and performance metrics of the product. They include the design decisions made at the early stages (Smirnov & Golkar, 2015), the way those decisions were made by team members (Smirnov & Golkar, 2019), and technical problems that might arise during later cycles of system testing (Smirnov et al, 2018). This evidence shows that, instead [PREPUBLICATION DRAFT: PLEASE, DO NOT CITE WITHOUT AUTHOR'S PERMISSION] of simply fixing a technical issue, problem-solving and exploration might lead to different performance metrics and market applications.…”

Defining Better Test Strategies with Tradespace Exploration Techniques and Pareto Fronts: Application in an Industrial Project

“…The diversity in domains where it has been used is growing and positive results have already being obtained for selecting design concepts of manned and unmanned space systems [Ross et al., ; Golkar and Crawley, ; Shaw et al., ], aircrafts [Lewis, Tackett, and Mattson, ], structural elements [Mattson and Messac, ; Lewis et al., ], military operations [Hong, Wee, and Kiat, ], and Stirling engines [Smirnov and Golkar, ]. In addition, tradespace exploration has been found effective in supporting concept selection of systems of systems both in research [Chattopadhyay, Ross, and Rhodes, , ] and in practice [Salado, ].…”

Understanding the differences between single‐ and multiobjective optimization for the conservation of multiple species

“…The advantage of this method is the consideration of both complementary and competitive relationships in optimal solutions generated (Lee et al, 2021). The key shortcoming of multiobjective optimization is a need for a priori set of constraints and optimizing objectives with relative ranking determined by the decision‐maker (Smirnov & Golkar, 2015).…”