A framework for enhanced decision-making in aircraft conceptual design optimisation under uncertainty

2020 ◽  
pp. 1-30
Author(s):  
D.H.B. Di Bianchi ◽  
N.R. Sêcco ◽  
F.J. Silvestre
Keyword(s):  
Decision Making ◽  
Conceptual Design ◽  
Computational Cost ◽  
Uncertainty Reduction ◽  
Design Optimisation ◽  
Challenges And Opportunities ◽  
Feasibility Robustness ◽  
Definition Of ◽  
Multidisciplinary Design Optimisation ◽  
Aircraft Conceptual Design

Abstract This paper presents a framework to support decision-making in aircraft conceptual design optimisation under uncertainty. Emphasis is given to graphical visualisation methods capable of providing holistic yet intuitive relationships between design, objectives, feasibility and uncertainty spaces. Two concepts are introduced to allow interactive exploration of the effects of (1) target probability of constraint satisfaction (price of feasibility robustness) and (2) uncertainty reduction through increased state-of-knowledge (cost of uncertainty) on design and objective spaces. These processes are tailored to handle multi-objective optimisation problems and leverage visualisation techniques for dynamic inter-space mapping. An information reuse strategy is presented to enable obtaining multiple robust Pareto sets at an affordable computational cost. A case study demonstrates how the presented framework addresses some of the challenges and opportunities regarding the adoption of Uncertainty-based Multidisciplinary Design Optimisation (UMDO) in the aerospace industry, such as design margins policy, systematic and conscious definition of target robustness and uncertainty reduction experiments selection and prioritisation.

Aircraft conceptual design for optimal environmental performance

2012 ◽  
Vol 116 (1175) ◽  
pp. 1-22 ◽  
Author(s):  
R. P. Henderson ◽  
J. R. R. A. Martins ◽  
R. E. Perez
Keyword(s):  
Operating Cost ◽  
Aircraft Design ◽  
Aircraft Emissions ◽  
Design Optimisation ◽  
Commercial Aviation ◽  
Fuel Burn ◽  
Design Variables ◽  
Multidisciplinary Design Optimisation ◽  
Aircraft Conceptual Design ◽  
Geometry Engine

Abstract Consideration of the environmental impact of aircraft has become critical in commercial aviation. The continued growth of air traffic has caused increasing demands to reduce aircraft emissions, imposing new constraints on the design and development of future airplane concepts. In this paper, an aircraft design optimisation framework is used to design aircraft that minimise specific environmental metrics. Multidisciplinary design optimisation is used to optimise aircraft by simultaneously considering airframe, engine and mission. The environmental metrics considered in this investigation are CO2 emissions — which are proportional to fuel burn — and landing-takeoff NOx emissions. The results are compared to those of an aircraft with minimum direct operating cost. The design variables considered in the optimisation problems include aircraft geometry, engine parameters, and cruise settings. An augmented Lagrangian particle swarm optimiser and a genetic algorithm are used to solve the single objective and multi-objective optimisation problems, respectively.

scholarly journals Multidisciplinary Optimisation of Aircraft Structures with Critical Non-Regular Areas: Current Practice and Challenges

Aerospace ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 223
Author(s):  
Massimo Sferza ◽  
Jelena Ninić ◽  
Dimitrios Chronopoulos ◽  
Florian Glock ◽  
Fernass Daoud
Keyword(s):  
Degrees Of Freedom ◽  
Computational Cost ◽  
Aircraft Design ◽  
Element Model ◽  
Main Role ◽  
Design Optimisation ◽  
Load Paths ◽  
Design Variables ◽  
Internal Deformation ◽  
Multidisciplinary Design Optimisation

The design optimisation of aerostructures is largely based on Multidisciplinary Design Optimisation (MDO), which is a set of tools used by the aircraft industry to size primary structures: wings, large portions of the fuselage or even an entire aircraft. The procedure is computationally expensive, as it must account for several thousands of loadcases, multiple analyses with hundreds of thousands of degrees of freedom, thousands of design variables and millions of constraints. Because of this, the coarse Global Finite Element Model (GFEM), on which the procedure is based, cannot be further refined. The structures represented in the GFEM contain many components and non-regular areas, which require a detailed modelling to capture their complex mechanical behaviour. Instead, in the GFEM, these components are represented by simplified models with approximated stiffness, whose main role is to contribute to the identification of the load paths over the whole structure. Therefore, these parts are kept fixed and are not constrained during the optimisation, as the description of their internal deformation is not sufficiently accurate. In this paper, we show that it would nevertheless be desirable to size the non-regular areas and the overall structures at once. Firstly, we introduce the concept of non-regular areas in the context of a structural airframe MDO. Secondly, we present a literature survey on MDO with a critical review of several architectures and their current applications to aircraft design optimisation. Then, we analyse and demonstrate with examples the possible consequences of neglecting non-regular areas when MDO is applied. In the conclusion, we analyse the requirements for alternative approaches and why the current ones are not viable solutions. Lastly, we discuss which characteristics of the problem could be exploited to contain the computational cost.

The application of Pareto methods to multidisciplinary design optimisation

2001 ◽  
Vol 105 (1048) ◽  
pp. 329-334
Author(s):  
J. C. Harris ◽  
S. V. Fenwick
Keyword(s):  
Pareto Frontier ◽  
Multidisciplinary Design ◽  
Design Optimisation ◽  
Diverse Range ◽  
Trade Offs ◽  
Future System ◽  
System Requirements ◽  
Definition Of ◽  
High Level ◽  
Multidisciplinary Design Optimisation

Abstract Multidisciplinary design optimisation (MDO) provides a framework for the timely exchange of data necessary to support the highly integrated tasks typical of aerospace design. This will help reduce the duration of the design cycle and improve efficiency of the final product. Well implemented MDO capabilities will play an increasingly important role in DERA's activities to support the definition of future system requirements and the assessment of new equipment. The framework in which an MDO approach is realised must be flexible and accommodate the diverse range of individual discipline-based tools that contribute to the overall process. This paper describes DERA's activity within the EC Framework IV ‘FRONTIER’ project to investigate the use of modern graphical user interface (GUI) methods and genetic algorithms (GAs) for the combined aerodynamic and structural design of a modern combat aircraft. The application of the techniques to identify a Pareto frontier in high level design objective space that represents the boundary beyond which improvements cannot be made without sacrificing one or other aspect of overall aircraft performance is described. The scope of the methods as an aid during the definition of system requirements and for the evaluation of trade-offs during the concept assessment stage of a project is discussed.

DATABASE DESIGN FOR E-GOVERNANCE APPLICATION: A FRAMEWORK FOR THE MANAGEMENT INFORMATION SYSTEMS OF THE VIETNAM COMMITTEE FOR ETHNIC MINORITY AFFAIRS

2017 ◽  
Author(s):  
Nguyen Viet Hung ◽  
Phan Van Hung ◽  
Be Trung Anh
Keyword(s):  
Decision Making ◽  
Information System ◽  
Ethnic Minority ◽  
Ethnic Minorities ◽  
Good Governance ◽  
Local Governance ◽  
Geographical Information ◽  
Base System ◽  
Challenges And Opportunities ◽  
Competency Based

Data mode “good governance” developed in the last century for process of sustainable base system, providing basic information and on-line services, supports the development, challenges and opportunities in the context of globalization and integration. In this paper I discuss a framework for the design of e-Local Governance (eLG) that integrates Information System (IS), Geographical Information System (GIS) and Atlas with focus on ethnic minorities in Vietnam. The design framework is based on various classifications such categories as sex, age, ethnic group, education background and income. The database system is built to enhance the Committee for Ethnic Minority Affairs (CEMA) capabilities in the planning and decision making process by providing the authorities with data, internet GIS, internet communication and some ecological economic models to disseminate results to the ethnic minorities. The unique feature of the CEMADATA using GIS is that it helps users not only to improve the public services and to provide information and encourage ethnic minorities to participate in decision making processes, but also to support the competency-based training for IT staff

A Unifying Principle for a Researcher Learning Safety: Reduce Uncertainty!

2018 ◽  
Author(s):  
Camilla Kao ◽  
Russell Furr
Keyword(s):  
Decision Making ◽  
Best Practices ◽  
Mission Statement ◽  
Safety Information ◽  
Health And Safety ◽  
Mission Statements ◽  
Definition Of ◽  
Physical And Chemical

Conveying safety information to researchers is challenging. A list of rules and best practices often is not remembered thoroughly even by individuals who want to remember everything. Researchers in science thinking according to principles: mathematical, physical, and chemical laws; biological paradigms. They use frameworks and logic, rather than memorization, to achieve the bulk of their work. Can safety be taught to researchers in a manner that matches with how they are trained to think? Is there a principle more defined than "Think safety!" that can help researchers make good decisions in situations that are complex, new, and demanding?<div><br></div><div>Effective trainings in other professions can arise from the use of a mission statement that participants internalize as a mental framework or model for future decision-making. We propose that mission statements incorporating the concept of <b>reducing uncertainty</b> could provide such a framework for learning safety. This essay briefly explains the definition of <b>uncertainty</b> in the context of health and safety, discusses the need for an individual to <b>personalize</b> a mission statement in order to internalize it, and connects the idea of <b>greater control</b> over a situation with less uncertainty with respect to safety. The principle of reducing uncertainty might also help <b>non-researchers</b> think about safety. People from all walks of life should be able to understand that more control over their situations provides more protection for them, their colleagues, and the environment.</div>

An Analysis of the Demand for Reporting on Internal Control

2000 ◽  
Vol 14 (3) ◽  
pp. 325-341 ◽  
Author(s):  
Heather M. Hermanson
Keyword(s):  
Decision Making ◽  
Financial Reporting ◽  
Internal Control ◽  
Operational Definition ◽  
Financial Statement ◽  
Individual Investors ◽  
Internal Auditors ◽  
Additional Information ◽  
User Groups ◽  
Definition Of

The purpose of this study is to analyze the demand for reporting on internal control. Nine financial statement user groups were identified and surveyed to determine whether they agree that: (1) management reports on internal control (MRIC) are useful, (2) MRICs influence decisions, and (3) financial reporting is improved by adding MRICs. In addition, the paper examined whether responses varied based on: (1) the definition of internal control used (manipulated as broad, operational definition vs. narrow, financial-reporting definition) and (2) user group. The results indicate that financial statement users agree that internal controls are important. Respondents agreed that voluntary MRICs improved controls and provided additional information for decision making. Respondents also agreed that mandatory MRICs improved controls, but did not agree about their value for decision making. Using a broad definition of controls, respondents strongly agreed that MRICs improved controls and provided a better indicator of a company's long-term viability. Executive respondents were less likely to agree about the value of MRICs than individual investors and internal auditors.

scholarly journals A Methodology for Redesigning Networks by Using Markov Random Fields

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1389
Author(s):  
Julia García Cabello ◽  
Pedro A. Castillo ◽  
Maria-del-Carmen Aguilar-Luzon ◽  
Francisco Chiclana ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Random Fields ◽  
Markov Random Fields ◽  
Application Performance ◽  
Cross Border ◽  
Markov Random ◽  
User Groups ◽  
Universal Definition ◽  
Definition Of ◽  
Decision Making Model

Standard methodologies for redesigning physical networks rely on Geographic Information Systems (GIS), which strongly depend on local demographic specifications. The absence of a universal definition of demography makes its use for cross-border purposes much more difficult. This paper presents a Decision Making Model (DMM) for redesigning networks that works without geographical constraints. There are multiple advantages of this approach: on one hand, it can be used in any country of the world; on the other hand, the absence of geographical constraints widens the application scope of our approach, meaning that it can be successfully implemented either in physical (ATM networks) or non-physical networks such as in group decision making, social networks, e-commerce, e-governance and all fields in which user groups make decisions collectively. Case studies involving both types of situations are conducted in order to illustrate the methodology. The model has been designed under a data reduction strategy in order to improve application performance.

scholarly journals Highway Speed Prediction Using Gated Recurrent Unit Neural Networks

2021 ◽  
Vol 11 (7) ◽  
pp. 3059
Author(s):  
Myeong-Hun Jeong ◽  
Tae-Young Lee ◽  
Seung-Bae Jeon ◽  
Minkyo Youm
Keyword(s):  
Neural Network ◽  
Intelligent Transportation Systems ◽  
Moving Average ◽  
Computational Cost ◽  
Nonlinear Problems ◽  
Transportation Systems ◽  
Mobility Data ◽  
Challenges And Opportunities ◽  
Moving Average Model ◽  
Gated Recurrent Unit

Movement analytics and mobility insights play a crucial role in urban planning and transportation management. The plethora of mobility data sources, such as GPS trajectories, poses new challenges and opportunities for understanding and predicting movement patterns. In this study, we predict highway speed using a gated recurrent unit (GRU) neural network. Based on statistical models, previous approaches suffer from the inherited features of traffic data, such as nonlinear problems. The proposed method predicts highway speed based on the GRU method after training on digital tachograph data (DTG). The DTG data were recorded in one month, giving approximately 300 million records. These data included the velocity and locations of vehicles on the highway. Experimental results demonstrate that the GRU-based deep learning approach outperformed the state-of-the-art alternatives, the autoregressive integrated moving average model, and the long short-term neural network (LSTM) model, in terms of prediction accuracy. Further, the computational cost of the GRU model was lower than that of the LSTM. The proposed method can be applied to traffic prediction and intelligent transportation systems.

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