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Luciana, P., Krus, P. & Klofsten, M. (Eds.). (2023). Proceedings of IDEAS 2022: Interdisciplinary Conference on Innovation, Design, Entrepreneurship, and Sustainable Systems. Paper presented at IDEAS: Interdisciplinary Conference on Innovation, Design, Entrepreneurship, and Sustainable Systems. Springer
Open this publication in new window or tab >>Proceedings of IDEAS 2022: Interdisciplinary Conference on Innovation, Design, Entrepreneurship, and Sustainable Systems
2023 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

This book explores the cutting-edge ideas that are shaping the future of innovation, design, entrepreneurship, and sustainability. The proceedings of the interdisciplinary Conference on Innovation, Design, Entrepreneurship, and Sustainable Systems offer new perspectives on these topics. This book navigates the most recent research trends and practices, and gains unique insights on how to address innovation, design, and entrepreneurship on a sustainable basis. This book is an essential reference for anyone interested in staying up to date on the latest research, whether they are academics, designers, entrepreneurs, or sustainability enthusiasts. Get your copy now and take part in the debate about the future of sustainable innovation.

Place, publisher, year, edition, pages
Springer, 2023. p. 338
Series
Design Science and Innovation, ISSN 2509-5986, E-ISSN 2509-5994
Keywords
Innovation, design, entrepreneurship, and sustainable systems
National Category
Design
Identifiers
urn:nbn:se:liu:diva-193165 (URN)10.1007/978-3-031-29129-6 (DOI)9783031291289 (ISBN)9783031291296 (ISBN)9783031297113 (ISBN)
Conference
IDEAS: Interdisciplinary Conference on Innovation, Design, Entrepreneurship, and Sustainable Systems
Available from: 2023-04-18 Created: 2023-04-18 Last updated: 2023-04-27Bibliographically approved
Hällqvist, R., Eek, M., Braun, R. & Krus, P. (2023). Toward Objective Assessment of Simulation Predictive Capability. Journal of Aerospace Information Systems
Open this publication in new window or tab >>Toward Objective Assessment of Simulation Predictive Capability
2023 (English)In: Journal of Aerospace Information Systems, ISSN 1940-3151Article in journal (Refereed) Epub ahead of print
Abstract [en]

Two different metrics quantifying model and simulator predictive capability are formulated and evaluated; both metrics exploit results from conducted validation experiments where simulation results are compared to the corresponding measured quantities. The first metric is inspired by the modified nearest neighbor coverage metric and the second by the Kullback?Liebler divergence. The two different metrics are implemented in Python and in a here-developed general metamodel designed to be applicable for most physics-based simulation models. These two implementations together facilitate both offline and online metric evaluation. Additionally, a connection between the two, here separated, concepts of predictive capability and credibility is established and realized in the metamodel. The two implementations are, finally, evaluated in an aeronautical domain context.

Place, publisher, year, edition, pages
American Institute of Aeronautics and Astronautics, 2023
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:liu:diva-191130 (URN)10.2514/1.I011153 (DOI)000914113700001 ()
Note

Funding agencies: Vinnova; Saab Aeronautics; NFFP7 project Digital Twin for Automated Model Validation and Flight Test Evaluation

Available from: 2023-01-19 Created: 2023-01-19 Last updated: 2023-02-06Bibliographically approved
Lovaco, J., Knöös Franzén, L. & Krus, P. (2022). Agent-Based Simulation and Ontology Integration for System-of-System Exploration. In: IDEAS 2022 conference: . Paper presented at IDEAS2022, Sao Paulo, Brazil, 28-30 November, 2022.
Open this publication in new window or tab >>Agent-Based Simulation and Ontology Integration for System-of-System Exploration
2022 (English)In: IDEAS 2022 conference, 2022Conference paper, Published paper (Refereed)
Abstract [en]

The increasing interest in System-of-Systems (SoS) for engineering applications are introducing new challenges that must be overcome at an early design stage. One of these is the integration of different tools that can be used to make predictions about a system under development and how these together can be used to predict SoS performances by comparison of parameter spaces.The purpose of this paper is therefore to illustrate how different SoS architectures can be modeled, simulated, and evaluated throughout different scenarios by different teams of researchers following a common workflow.An ontology is used as an overarching knowledge base where information about entities, such as scenario details, can be extracted and used for the setup of Agentbased Simulations(ABS) through a tool integration software acting as master that controls the correct execution of the defined workflow.The tool integration software also enables additional modelling capabilities, such as a Design of Experiments (DOE) definition for design space explorations, an Optimizer with different algorithms, user-defined Python scripts, etc. 

National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-192101 (URN)
Conference
IDEAS2022, Sao Paulo, Brazil, 28-30 November, 2022
Available from: 2023-03-02 Created: 2023-03-02 Last updated: 2023-03-08
Lovaco, J., Staack, I. & Krus, P. (2022). Environmental Agent-Based Modelling For A Firefightingsystem Of Systems. In: 33rd Congress of the International Council of the Aeronautical Sciences: . Paper presented at ICAS2022, Stockholm, Sweden, 4-9 September, 2022.
Open this publication in new window or tab >>Environmental Agent-Based Modelling For A Firefightingsystem Of Systems
2022 (English)In: 33rd Congress of the International Council of the Aeronautical Sciences, 2022Conference paper, Published paper (Refereed)
Abstract [en]

In the field of System-of-Systems (SoS) engineering, the study of interactions between complex systems froma holistic point of view is important for finding emerging behaviours. To observe as many behaviours aspossible, especially when field testing is not a viable option, simulations play an important role in design spaceexploration and formulation for the Firefighting SoS framework. The presented work describes an AgentBased Model (ABM) approach for simulation of wildfire spread and its detection using collaborating vehicles:Unmanned Aerial Vehicles (UAVs), or partly autonomous air- and land-based vehicles. Implemented in theopen-source software NetLogo, the usage of its Geographic Information System (GIS) extension allows tosimulate scenarios at specific locations. This ABM will be used in the future for Agent-Based Simulations(ABS) for the study of an SoS framework oriented to firefighting, including design and optimization of the SoS,constituent systems and their subsystems.

Keywords
Systems of Systems, Agent-Based Simulation, Aerospace Systems, Cyber-Physical Modelling, Wildfire Detection
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-192091 (URN)
Conference
ICAS2022, Stockholm, Sweden, 4-9 September, 2022
Available from: 2023-03-01 Created: 2023-03-01 Last updated: 2023-03-08Bibliographically approved
Nepomuceno, L. M., Annes da Silva, R. G., Sobron, A., Krus, P. & Lundström, D. (2022). Estimation of lift characteristics of a subscale fighter using low-cost experimental methods. AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 94(8), 1379-1389
Open this publication in new window or tab >>Estimation of lift characteristics of a subscale fighter using low-cost experimental methods
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2022 (English)In: AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, ISSN 1748-8842, Vol. 94, no 8, p. 1379-1389Article in journal (Refereed) Published
Abstract [en]

Purpose While computational methods are prevalent in aircraft conceptual design, recent advances in mechatronics and manufacturing are lowering the cost of practical experiments. Focussing on a relatively simple property, the lift curve, this study aims to increase understanding of how basic aerodynamic characteristics of a complex stealth configuration can be estimated experimentally using low-cost equipment, rapid prototyping methods and remotely piloted aircraft. Design/methodology/approach Lift curve estimates are obtained from a wind tunnel test of a three-dimensional-printed, 3.8%-scale model of a generic fighter and from flight testing a 14%-scale demonstrator using both a simple and a more advanced identification technique based on neural networks. These results are compared to a computational fluid dynamics study, a panel method and a straightforward, theoretical approach based on radical geometry simplifications. Findings Besides a good agreement in the linear region, discrepancies at high angles of attack reveal the shortcomings of each method. The remotely piloted model manages to provide consistent results beyond the physical limitations of the wind tunnel although it seems limited by instrumentation capabilities and unmodelled thrust effects. Practical implications Physical models can, even though low-cost experiments, expand the capabilities of other aerodynamic tools and contribute to reducing uncertainty when other estimations diverge. Originality/value This study highlights the limitations of commonly used aerodynamic methods and shows how low-cost prototyping and testing can complement or validate other estimations in the early study of a complex configuration.

Place, publisher, year, edition, pages
EMERALD GROUP PUBLISHING LTD, 2022
Keywords
Lift estimation; Subscale; Flight testing; Rapid prototyping; Unmanned aerial vehicle
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-184398 (URN)10.1108/AEAT-04-2021-0105 (DOI)000777885300001 ()
Note

Funding Agencies|CoordenacAo de Aperfeicoamento de Pessoal de Nivel SuperiorCoordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [001]; VINNOVA [MESTA]Vinnova [2017-01502]

Available from: 2022-04-20 Created: 2022-04-20 Last updated: 2023-05-04Bibliographically approved
Schön, S., Knöös Franzén, L., Staack, I., Krus, P., Marcus, C., Amadori, K. & Jouannet, C. (2022). Exploring the Impact of Model Fidelity Through Interactive Visualizations for System of Systems. In: AIAA SciTech 2022 Forum, January 3-7, 2022, San Diego, CA & Virtual: . Paper presented at AIAA SCITECH Forum. USA: American Institute of Aeronautics and Astronautics
Open this publication in new window or tab >>Exploring the Impact of Model Fidelity Through Interactive Visualizations for System of Systems
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2022 (English)In: AIAA SciTech 2022 Forum, January 3-7, 2022, San Diego, CA & Virtual, USA: American Institute of Aeronautics and Astronautics, 2022Conference paper, Published paper (Refereed)
Abstract [en]

Studying Systems of Systems (SoS) in relation to Measures of Effectiveness (MoE) is a difficult task. This is due to that SoSs include several system levels and operate in changing environments. There are also computational challenges related to modeling and simulation of SoSs and it is difficult to predict behaviors. Therefore, choosing model fidelity for system models and assessing their impact on MoE is of high relevance to the field. This paper illustrates an approach to modeling and simulation for SoSs that can be used to assess the impact of scenario parameters and to explore when level of fidelity on system level affects the MoE. This is made through a case study based on Search and Rescue (SAR) operations where a Design Of Experiments (DOE) of scenario parameters is performed and simulations of each scenario experiment is performed. The case study shows how Agent Based Simulations (ABS) can be used to obtain the MoE for different SAR missions and how the choice of model fidelity for one of the aircraft’s sensors has different effects for various scenarios. Additionally, a Visual Analytics (VA) approach is introduced and used to create a dashboard for visualizing the obtained simulation results in an interactive way. This allows users to make explorations on the resulting data and see how different scenarios influence the performance of each SoS. Furthermore, the results show that changes in scenario parameters impacts the MoE and that this is difficult to predict, at least using a quantitative method. The results point to the importance of exploration for both the scenario, using an interactive dashboard, but also to the importance of exploring the simulation model to study emerging phenomenon. The results of this approach have raised questions regarding if a more qualitative approach of studying SoSs could be beneficial to study MoE for SoSs and if inspiration could be transferred from a more scientific point of view of systems.

Place, publisher, year, edition, pages
USA: American Institute of Aeronautics and Astronautics, 2022
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-191926 (URN)10.2514/6.2022-1467 (DOI)
Conference
AIAA SCITECH Forum
Projects
System-of-Systems Trade Space Exploration (S2TEP)
Funder
Vinnova, NFFP7/ 2017-04838
Available from: 2023-02-23 Created: 2023-02-23 Last updated: 2023-11-02
Knöös Franzén, L., Munjulury, R. C. & Krus, P. (2022). Ontology-Assisted Aircraft Concept Generation. In: 33rd Congress of the International Council of the Aeronautical Sciences: . Paper presented at ICAS2022, Stockholm, Sweden, 4-9 September, 2022. Stockholm, Sweden
Open this publication in new window or tab >>Ontology-Assisted Aircraft Concept Generation
2022 (English)In: 33rd Congress of the International Council of the Aeronautical Sciences, Stockholm, Sweden, 2022Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a method for generating a geometrical representation of a concept aircraft from an ontology description. An ontology is used as an overarching knowledge base where entities, such as required functions, their design alternatives, and requirements can be represented. Description logic reasoning is then used to process the available design space and generate suitable concepts to fulfil desired functions, as well as indicate suitable approaches for a subsequent sizing procedure. As ontology representations are limited in terms of numerical calculation capabilities, the obtained concept information must be extracted for additional processing. Further investigations, such as statistical analyses, are consequently performed in order to expand the available information of the concept generated from the ontology. This expansion is performed to obtain estimates of required inputs for a continued geometrical sizing procedure. The outcome of the method is an estimation of the concept’s geometry and its characteristics. This information can from here be reintroduced into the ontology representation for further processing and to expand the original knowledge base. A case study is introduced to test the proposed method and to show how it can be used to estimate the characteristics of an already existing aircraft from basic requirements and configuration details. The results from the method and sizing are also compared with publicly available data for the reference aircraft to see how accurate the estimates were.

Place, publisher, year, edition, pages
Stockholm, Sweden: , 2022
Keywords
Ontology, Aircraft Conceptual Design, Singular Value Decomposition, Geometry
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-191927 (URN)
Conference
ICAS2022, Stockholm, Sweden, 4-9 September, 2022
Projects
System-of-Systems Trade Space Exploration (S2TEP)
Available from: 2023-02-23 Created: 2023-02-23 Last updated: 2023-05-11Bibliographically approved
Raduenz, H., Uebel, K., Heybroek, K., Ericson, L., De Negri, V. & Krus, P. (2022). Rule- and Neural Network-based Energy Management for a Hydraulic HybridWheel Loader. In: Katharina Schmitz (Ed.), 13th International Fluid Power Conference AachenFluid Power: Digital, Reliable, Sustainable: . Paper presented at The 13th International Fluid Power Conference, 13. IFK, Aachen, Germany, June 13-15, 2022 (pp. 828-841).
Open this publication in new window or tab >>Rule- and Neural Network-based Energy Management for a Hydraulic HybridWheel Loader
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2022 (English)In: 13th International Fluid Power Conference AachenFluid Power: Digital, Reliable, Sustainable / [ed] Katharina Schmitz, 2022, p. 828-841Conference paper, Published paper (Refereed)
Abstract [en]

This paper highlights the importance of considering required control rules from the real-world implementation inoffline optimal control optimisations used to generate online energy management strategies (EMS). The controlrules are constraints on the optimal control problem. If not considered, the control optimisation results do notrepresent the reality and the EMS will have poor performance. In this paper, a neural network predicts the optimalcontrol decisions whenever the rules are not taking place. It is a rule- and neural network-based energymanagement strategy. A limitation to the use of neural networks as part of the EMS is that they do not ensurestable behaviour outside the region they were trained for. In the real application – in this case, a hybrid wheelloader – they will be deployed alongside control rules to ensure safety and reasonable operation. Hence theimportance of implementing the rules in the optimal control problem. Results show that better performance of theEMS is achieved if the rules from the application are considered in the optimal control problem.

Keywords
Neural network, energy management strategy, hybrid machines
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-191582 (URN)
Conference
The 13th International Fluid Power Conference, 13. IFK, Aachen, Germany, June 13-15, 2022
Funder
Swedish Energy Agency, P49119-1
Available from: 2023-02-01 Created: 2023-02-01 Last updated: 2023-02-08Bibliographically approved
Knöös Franzén, L., Staack, I., Krus, P., Jouannet, C. & Amadori, K. (2021). A Breakdown of System of Systems Needs Using Architecture Frameworks, Ontologies and Description Logic Reasoning. Aerospace, 8(4)
Open this publication in new window or tab >>A Breakdown of System of Systems Needs Using Architecture Frameworks, Ontologies and Description Logic Reasoning
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2021 (English)In: Aerospace, E-ISSN 2226-4310, Vol. 8, no 4Article in journal (Refereed) Published
Abstract [en]

Aerospace systems are connected with the operational environment and other systems in general. The focus in aerospace product development is consequently shifting from a singular system perspective to a System-of-Systems (SoS) perspective. This increasing complexity gives rise to new levels of uncertainty that must be understood and managed to produce aerospace solutions for an ever-changing future. This paper presents an approach to using architecture frameworks, and ontologies with description logic reasoning capabilities, to break down SoS needs into required capabilities and functions. The intention of this approach is to provide a consistent way of obtaining the functions to be realized in order to meet the overarching capabilities and needs of an SoS. The breakdown with an architecture framework results in an initial design space representation of functions to be performed. The captured knowledge is then represented in an ontology with description logic reasoning capabilities, which provides a more flexible way to expand and process the initial design space representation obtained from the architecture framework. The proposed approach is ultimately tested in a search and rescue case study, partly based on the operations of the Swedish Maritime Administration. The results show that it is possible to break down SoS needs in a consistent way and that ontology with description logic reasoning can be used to process the captured knowledge to both expand and reduce an available design space representation.

Place, publisher, year, edition, pages
MDPI, 2021
Keywords
system of systems, systems engineering, aerospace systems, architecture framework, ontology, description logic reasoning, search and rescue
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-175765 (URN)10.3390/aerospace8040118 (DOI)000642619100001 ()
Note

Funding: Swedish Innovation Agency (VINNOVA)Vinnova [NFFP7/2017-04838]

Available from: 2021-05-19 Created: 2021-05-19 Last updated: 2023-05-11Bibliographically approved
Sobron, A., Lundström, D. & Krus, P. (2021). A Review of Current Research in Subscale Flight Testing and Analysis of Its Main Practical Challenges. Aerospace, 8(3), Article ID 74.
Open this publication in new window or tab >>A Review of Current Research in Subscale Flight Testing and Analysis of Its Main Practical Challenges
2021 (English)In: Aerospace, ISSN 2226-4310, Vol. 8, no 3, article id 74Article in journal (Refereed) Published
Abstract [en]

Testing of untethered subscale models, often referred to as subscale flight testing, has traditionally had a relatively minor, yet relevant use in aeronautical research and development. As recent advances in electronics, rapid prototyping and unmanned-vehicle technologies expand its capabilities and lower its cost, this experimental method is seeing growing interest across academia and the industry. However, subscale models cannot meet all similarity conditions required for simulating full-scale flight. This leads to a variety of approaches to scaling and to other alternative applications. Through a literature review and analysis of different scaling strategies, this study presents an overall picture of how subscale flight testing has been used in recent years and synthesises its main issues and practical limitations. Results show that, while the estimation of full-scale characteristics is still an interesting application within certain flight conditions, subscale models are progressively taking a broader role as low-cost technology-testing platforms with relaxed similarity constraints. Different approaches to tackle the identified practical challenges, implemented both by the authors and by other organisations, are discussed and evaluated through flight experiments.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2021
Keywords
subscale flight testing, similarity, scale model, remotely piloted aircraft, demonstration, rapid prototyping
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-173294 (URN)10.3390/aerospace8030074 (DOI)000633221200001 ()
Note

Funding: Swedish Innovation Agency VINNOVA within project MESTA [NFFP 2017-01502]

Available from: 2021-02-12 Created: 2021-02-12 Last updated: 2021-05-05Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2315-0680

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