scholarly journals Configuring use-oriented aero-engine overhaul service with multi-objective optimization for environmental sustainability

2017 ◽  
Vol 162 ◽  
pp. S94-S106 ◽  
Author(s):  
Huibin Sun ◽  
Yang Liu ◽  
Tomohiko Sakao ◽  
Zhan Wang
2021 ◽  
Author(s):  
Hend Ahmed ◽  
Said M. Easa

Mobility, safety performance and environmental sustainability are priorities in the geometric design of roundabouts. This thesis presents a multi-objective optimization methodology for the geometric design of single-lane roundabouts. Mobility is defined in terms of roundabout delay and modeled using the (UK) empirical model. The collision frequency represents the safety objective, and modeled using the methodology outlined in the Highway Safety Manual. Environmental sustainability is represented by NOX, HC, CO2, and CO vehicle emissions and is modeled using the vehicle specific power (VSP) methodology. The presented model directly identifies the optimal geometric parameters of roundabouts. Traffic data, site conditions, and guidelines limitations were used as input data while the output decision values that minimize delay, collisions, and vehicle emissions are the optimal geometric parameters. The practical application of the proposed model is illustrated using an application example. The model was validated using an actual location, and a sensitivity analysis was conducted.


2021 ◽  
Author(s):  
Carlo Alberto Elmi ◽  
Ignazio Vitale ◽  
Hauke Reese ◽  
Antonio Andreini

Abstract The preliminary design of an aero-engine combustor is a multidisciplinary process that involves an extensive and systematic analysis of the design space. Simulation-driven approaches, in which several design configurations are numerically analyzed, may lead to heterogeneous models interacting with each other, sharing miscellaneous information within the process. Iterative and user-defined approaches, moreover, are inefficient when multiple and conflicting requirements are in place. To rely on integrated design methodologies has been demonstrated to be beneficial, especially if adopted in a structured approach to design optimization. In this paper, the application of the Combustor Design System Integration (DSI) to the definition of an optimal combustor preliminary configuration will be presented. Given a combustor baseline design, the multi-objective optimization problem has been defined by targeting an optimal distribution for temperature profiles and patterns at the combustor’s exit. Dilution port characteristics, such as hole number and dimension as well as the axial position of the row have been selected as design variables. To guarantee a water-tight design process while minimizing the user effort, the DSI tools were included in a dedicated framework for driving the optimization tasks. Here, a proper CFD domain for RANS, constituted by the flame tube region extended to the dilution port feeds, was adopted for imposing the air split designed for the combustor. Concerning a “complete” combustor sector, this allows a reduction in the computational effort while still being representative for its aero-thermal behavior. The optimization task was performed using a Response Surface Method (RSM), in which multiple, specific combustor configurations were simulated and the CFD result elaborated to build a meta-model of the combustor itself. Finally, the suitability of the resulting optimized configuration has been evaluated through an “a posteriori” analysis for thermal conditions and emission levels (NOx and CO). A lean combustion concept developed by Avio Aero with the aim of the homonymous EU research project, the NEWAC combustor, has been considered as test case.


2021 ◽  
Author(s):  
Hend Ahmed ◽  
Said M. Easa

Mobility, safety performance and environmental sustainability are priorities in the geometric design of roundabouts. This thesis presents a multi-objective optimization methodology for the geometric design of single-lane roundabouts. Mobility is defined in terms of roundabout delay and modeled using the (UK) empirical model. The collision frequency represents the safety objective, and modeled using the methodology outlined in the Highway Safety Manual. Environmental sustainability is represented by NOX, HC, CO2, and CO vehicle emissions and is modeled using the vehicle specific power (VSP) methodology. The presented model directly identifies the optimal geometric parameters of roundabouts. Traffic data, site conditions, and guidelines limitations were used as input data while the output decision values that minimize delay, collisions, and vehicle emissions are the optimal geometric parameters. The practical application of the proposed model is illustrated using an application example. The model was validated using an actual location, and a sensitivity analysis was conducted.


2020 ◽  
Vol 12 (18) ◽  
pp. 7733
Author(s):  
Dong Yang ◽  
Qidong Liu ◽  
Jia Li ◽  
Yongji Jia

Cloud manufacturing is an emerging service-oriented paradigm that works by taking advantage of distributed manufacturing resources and capabilities to collaboratively perform a manufacturing task, with the consideration of QoS (Quality of Service) requirements such as cost, time and quality. Incorporating environmental concerns and sustainability into cloud manufacturing to produce a much greener product has become an urgent issue since there is fierce market competition and an increasing environment consciousness from customers. In this paper, we present a multi-objective optimization approach to selecting and scheduling cloud manufacturing services from the viewpoints of the economy and environment including carbon emissions and water resource. Subject to the carbon cap regulation, a multi-objective model for a cloud manufacturing task is built with the aim of minimizing total costs, carbon emissions, and water resource use. Transportation mode selections and carbon emissions from both cloud manufacturing services and transportation activities are taken into account in this model. The ε-constraint method is employed to obtain the exact Pareto front of optimal solutions. A case study from automobile cloud manufacturing is used to illustrate the effectiveness of the presented approach. Numerical experiments are conducted to compare the presented approach and the simple additive weighting method. The results show that the presented ε-constraint method can obtain a better and more diverse Pareto set of solutions and that it can solve the models in a reasonable time.


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