Holly A. H. Handley, J. See, Pamela (Pam) A. Savage-Knepshield
The Human Readiness Level (HRL) scale is a simple nine‐level scale that brings structure and consistency to the real‐world application of user‐centered design. It enables multidisciplinary consideration of human‐focused elements during the system development process. Use of the standardized set of questions comprising the HRL scale results in a single human readiness number that communicates system readiness for human use. The Human Views (HVs) are part of an architecture framework that provides a repository for human‐focused system information that can be used during system development to support the evaluation of HRL levels. This paper illustrates how HRLs and HVs can be used in combination to support user‐centered design processes. A real‐world example for a U.S. Army software modernization program is described to demonstrate application of HRLs and HVs in the context of user‐centered design.
{"title":"Human readiness levels and Human Views as tools for user‐centered design","authors":"Holly A. H. Handley, J. See, Pamela (Pam) A. Savage-Knepshield","doi":"10.1002/sys.21773","DOIUrl":"https://doi.org/10.1002/sys.21773","url":null,"abstract":"The Human Readiness Level (HRL) scale is a simple nine‐level scale that brings structure and consistency to the real‐world application of user‐centered design. It enables multidisciplinary consideration of human‐focused elements during the system development process. Use of the standardized set of questions comprising the HRL scale results in a single human readiness number that communicates system readiness for human use. The Human Views (HVs) are part of an architecture framework that provides a repository for human‐focused system information that can be used during system development to support the evaluation of HRL levels. This paper illustrates how HRLs and HVs can be used in combination to support user‐centered design processes. A real‐world example for a U.S. Army software modernization program is described to demonstrate application of HRLs and HVs in the context of user‐centered design.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"57 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew Collins, Caroline Krejci, Prashanth Rajivan
{"title":"Editorial for modeling and simulation special edition","authors":"Andrew Collins, Caroline Krejci, Prashanth Rajivan","doi":"10.1002/sys.21768","DOIUrl":"https://doi.org/10.1002/sys.21768","url":null,"abstract":"","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"2 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140970387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Araceli Zavala, Dinesh Verma, Jose E. Ramirez Marquez
The Systems Engineering Research Center (SERC) is a University Affiliated Research Center (UARC) of the US Department of Defense (DoD) formed in 2008 with more than 20 collaborator universities in the United States. Over the last decade, SERC has conducted research with Principal Investigators from universities within the SERC network, as reflected in technical reports (TR). These reports describe detailed information and analysis of the conducted research for every project under SERC support, such as written records of experiments or results of a scientific project. We analyzed the TRs from 2009 to early 2023 to identify research streams, topics, and evolution in systems engineering (SE) research using text mining and network analysis techniques, such as Louvain Community Detection and word similarity. As a result, we identified four major research streams over a decade of research projects, along with insights about topics and the evolution of SE within this time frame. Finally, we distinguished most profile authors and their most significant collaborations and networks.
{"title":"Exploring over a decade of systems engineering research center: A community detection and text analytics approach","authors":"Araceli Zavala, Dinesh Verma, Jose E. Ramirez Marquez","doi":"10.1002/sys.21760","DOIUrl":"https://doi.org/10.1002/sys.21760","url":null,"abstract":"The Systems Engineering Research Center (SERC) is a University Affiliated Research Center (UARC) of the US Department of Defense (DoD) formed in 2008 with more than 20 collaborator universities in the United States. Over the last decade, SERC has conducted research with Principal Investigators from universities within the SERC network, as reflected in technical reports (TR). These reports describe detailed information and analysis of the conducted research for every project under SERC support, such as written records of experiments or results of a scientific project. We analyzed the TRs from 2009 to early 2023 to identify research streams, topics, and evolution in systems engineering (SE) research using text mining and network analysis techniques, such as Louvain Community Detection and word similarity. As a result, we identified four major research streams over a decade of research projects, along with insights about topics and the evolution of SE within this time frame. Finally, we distinguished most profile authors and their most significant collaborations and networks.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":" 1165","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140988957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Eichmann, Jesko G. Lamm, Sylvia Melzer, T. Weilkiens, Ralf God
Cyber‐physical Systems (CPSs) are characterized by entities in both the physical and the virtual space, thus enabling an immersion of the physical world into the cyberspace. Connectivity via the cyberspace allows CPS cooperation for new services in product service systems (PSS). In consequence, cooperating CPSs act as actors with interest in the CPS in focus. Considering the needs of human actors and cooperating CPSs is a challenging task in CPS development because of many actors, interdepending CPS functions, and multiple CPS interfaces. For systems, the known Functional Architectures for Systems (FAS) method offers a solution approach for deriving functional system architectures from system use cases originating from human actors. For CPS development, this publication presents an expansion of the FAS method for developing functional architectures based on use cases originating from human actors as well as from cooperating CPSs and offers a model‐based approach based on the method description. In the authors’ opinion, interconnectable CPSs and models of cooperating CPSs can be integrated and interconnected with each other into a unifying aggregated model to represent the joint behavior of CPSs in an aggregated system. The paper explains this novel approach through a CPS functional architecture development example related to the prediction of remaining boarding time in an aircraft. The result is an approach that allows the consideration of initial CPS functions and new aggregated system functions, that pays special attention to the interconnectivity of CPSs and the required interfaces, and enables the systematic analysis of functions for the identification of redundancies.
{"title":"Development of functional architectures for cyber‐physical systems using interconnectable models","authors":"O. Eichmann, Jesko G. Lamm, Sylvia Melzer, T. Weilkiens, Ralf God","doi":"10.1002/sys.21761","DOIUrl":"https://doi.org/10.1002/sys.21761","url":null,"abstract":"Cyber‐physical Systems (CPSs) are characterized by entities in both the physical and the virtual space, thus enabling an immersion of the physical world into the cyberspace. Connectivity via the cyberspace allows CPS cooperation for new services in product service systems (PSS). In consequence, cooperating CPSs act as actors with interest in the CPS in focus. Considering the needs of human actors and cooperating CPSs is a challenging task in CPS development because of many actors, interdepending CPS functions, and multiple CPS interfaces. For systems, the known Functional Architectures for Systems (FAS) method offers a solution approach for deriving functional system architectures from system use cases originating from human actors. For CPS development, this publication presents an expansion of the FAS method for developing functional architectures based on use cases originating from human actors as well as from cooperating CPSs and offers a model‐based approach based on the method description. In the authors’ opinion, interconnectable CPSs and models of cooperating CPSs can be integrated and interconnected with each other into a unifying aggregated model to represent the joint behavior of CPSs in an aggregated system. The paper explains this novel approach through a CPS functional architecture development example related to the prediction of remaining boarding time in an aircraft. The result is an approach that allows the consideration of initial CPS functions and new aggregated system functions, that pays special attention to the interconnectivity of CPSs and the required interfaces, and enables the systematic analysis of functions for the identification of redundancies.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"5 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141006207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isabella V. Hernandez, B. C. Watson, M. Weissburg, Bert Bras
Increasing the resilience of modern infrastructure systems is recognized as a priority by both the International Council on Systems Engineering and the National Academy of Engineering. Resilience answers the key stakeholder need for a stable and predictable system by withstanding, adapting to, and recovering from unexpected faults. Increasing resilience in multi‐agent systems is especially challenging because resilience is an emergent system‐level property rather than the sum of individual agent functions. This paper uses biological systems as a source of inspiration for resilient functions, examining the central question How can biologically inspired design be used to increase the emergent property of resilience in multi‐agent systems? The paper uses functional decomposition to break down the individual functions that result in resilience and transfer the properties to generalized systems. Accordingly, the central hypothesis examined in this article is If functional decomposition is performed on eusocial insect colonies, then generalizable approaches to increase the emergent property of multi‐agent system resilience can be identified. The results provide two contributions. The first contribution is the identification of six general functions based on eusocial insect behavior that influence resilience. The second contribution is a description of the process of identifying and transferring insect behaviors into generalized design‐for‐resilience guidance. To support these contributions, a case study applies biologically inspired functions to an emergency power service system and proposes tactics for the power system to improve its resilience. Thus, this article provides a key step towards our goal of using biologically inspired design to influence the emergent property of resilience in multi‐agent systems.
{"title":"Using functional decomposition to bridge the design gap between desired emergent multi‐agent‐system resilience and individual agent design","authors":"Isabella V. Hernandez, B. C. Watson, M. Weissburg, Bert Bras","doi":"10.1002/sys.21758","DOIUrl":"https://doi.org/10.1002/sys.21758","url":null,"abstract":"Increasing the resilience of modern infrastructure systems is recognized as a priority by both the International Council on Systems Engineering and the National Academy of Engineering. Resilience answers the key stakeholder need for a stable and predictable system by withstanding, adapting to, and recovering from unexpected faults. Increasing resilience in multi‐agent systems is especially challenging because resilience is an emergent system‐level property rather than the sum of individual agent functions. This paper uses biological systems as a source of inspiration for resilient functions, examining the central question How can biologically inspired design be used to increase the emergent property of resilience in multi‐agent systems? The paper uses functional decomposition to break down the individual functions that result in resilience and transfer the properties to generalized systems. Accordingly, the central hypothesis examined in this article is If functional decomposition is performed on eusocial insect colonies, then generalizable approaches to increase the emergent property of multi‐agent system resilience can be identified. The results provide two contributions. The first contribution is the identification of six general functions based on eusocial insect behavior that influence resilience. The second contribution is a description of the process of identifying and transferring insect behaviors into generalized design‐for‐resilience guidance. To support these contributions, a case study applies biologically inspired functions to an emergency power service system and proposes tactics for the power system to improve its resilience. Thus, this article provides a key step towards our goal of using biologically inspired design to influence the emergent property of resilience in multi‐agent systems.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"121 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140658980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global population rise has increased vehicles on roads, complicating traffic management. Inefficient traffic control systems cause significant economic losses owing to commuter time wastage, high energy consumption, and greenhouse gas emissions. Traffic signal control systems (TSCSs) are vital in traffic management, impacting traffic flow significantly; therefore, studies are exploring new optimization approaches that adapt to changing traffic conditions. However, they concentrate on either new technology infusion or on control algorithm optimization, and do not holistically address the architectural configuration of the system. In this study, we presented a unique case study by applying an existing systematic framework to the TSCS system architecture design and selection process. This application demonstrates that TSCS enhancement is a multifaceted process that requires a comprehensive assessment of not only technical aspects, such as the control algorithm, but also factors including system architecture, security, and data integrity. Because of the increasing reliance of TSCSs on data exchange between their various subsystems, this case study also adopted a cybersecurity perspective of the system and introduced cyber resiliency as a crucial metric for evaluating TSCS architecture performance. Furthermore, through the applied framework, an optimal TSCS architectural configuration with executable options was identified by generating multiple TSCS architectural configurations using decision option patterns and identifying those on the Pareto frontier to understand the architectural decision‐making process. Traffic engineers and transportation planners can use this case study application as a guide to optimize TSCSs employed in existing transportation networks and design more efficient transportation networks for future urban development.
{"title":"Systematic application of traffic‐signal‐control system architecture design and selection using model‐based systems engineering and Pareto frontier analysis","authors":"Ana Theodora Balaci, Eun Suk Suh, Junseok Hwang","doi":"10.1002/sys.21759","DOIUrl":"https://doi.org/10.1002/sys.21759","url":null,"abstract":"The global population rise has increased vehicles on roads, complicating traffic management. Inefficient traffic control systems cause significant economic losses owing to commuter time wastage, high energy consumption, and greenhouse gas emissions. Traffic signal control systems (TSCSs) are vital in traffic management, impacting traffic flow significantly; therefore, studies are exploring new optimization approaches that adapt to changing traffic conditions. However, they concentrate on either new technology infusion or on control algorithm optimization, and do not holistically address the architectural configuration of the system. In this study, we presented a unique case study by applying an existing systematic framework to the TSCS system architecture design and selection process. This application demonstrates that TSCS enhancement is a multifaceted process that requires a comprehensive assessment of not only technical aspects, such as the control algorithm, but also factors including system architecture, security, and data integrity. Because of the increasing reliance of TSCSs on data exchange between their various subsystems, this case study also adopted a cybersecurity perspective of the system and introduced cyber resiliency as a crucial metric for evaluating TSCS architecture performance. Furthermore, through the applied framework, an optimal TSCS architectural configuration with executable options was identified by generating multiple TSCS architectural configurations using decision option patterns and identifying those on the Pareto frontier to understand the architectural decision‐making process. Traffic engineers and transportation planners can use this case study application as a guide to optimize TSCSs employed in existing transportation networks and design more efficient transportation networks for future urban development.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"68 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140665600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samuel Blair, Garrett Hairston, Henry Banks, Claire Kaat, Julie Linsey, Astrid Layton
Analyzing interactions between actors from a systems perspective yields valuable information about the overall system's form and function. When this is coupled with ecological modeling and analysis techniques, biological inspiration can also be applied to these systems. The diagnostic value of three metrics frequently used to study mutualistic biological ecosystems (nestedness, modularity, and connectance) is shown here using academic engineering makerspaces. Engineering students get hands‐on usage experience with tools for personal, class, and competition‐based projects in these spaces. COVID‐19 provides a unique study of university makerspaces, enabling the analysis of makerspace health through the known disturbance and resultant regulatory changes (implementation and return to normal operations). Nestedness, modularity, and connectance are shown to provide information on space functioning in a way that enables them to serve as heuristic diagnostics tools for system conditions. The makerspaces at two large R1 universities are analyzed across multiple semesters by modeling them as bipartite student‐tool interaction networks. The results visualize the predictive ability of these metrics, finding that the makerspaces tended to be structurally nested in any one semester, however when compared to a “normal” semester the restrictions are reflected via a higher modularity. The makerspace network case studies provide insight into the use and value of quantitative ecosystem structure and function indicators for monitoring similar human‐engineered interaction networks that are normally only tracked qualitatively.
{"title":"Bio‐inspired human network diagnostics: Ecological modularity and nestedness as quantitative indicators of human engineered network function","authors":"Samuel Blair, Garrett Hairston, Henry Banks, Claire Kaat, Julie Linsey, Astrid Layton","doi":"10.1002/sys.21756","DOIUrl":"https://doi.org/10.1002/sys.21756","url":null,"abstract":"Analyzing interactions between actors from a systems perspective yields valuable information about the overall system's form and function. When this is coupled with ecological modeling and analysis techniques, biological inspiration can also be applied to these systems. The diagnostic value of three metrics frequently used to study mutualistic biological ecosystems (nestedness, modularity, and connectance) is shown here using academic engineering makerspaces. Engineering students get hands‐on usage experience with tools for personal, class, and competition‐based projects in these spaces. COVID‐19 provides a unique study of university makerspaces, enabling the analysis of makerspace health through the known disturbance and resultant regulatory changes (implementation and return to normal operations). Nestedness, modularity, and connectance are shown to provide information on space functioning in a way that enables them to serve as heuristic diagnostics tools for system conditions. The makerspaces at two large R1 universities are analyzed across multiple semesters by modeling them as bipartite student‐tool interaction networks. The results visualize the predictive ability of these metrics, finding that the makerspaces tended to be structurally nested in any one semester, however when compared to a “normal” semester the restrictions are reflected via a higher modularity. The makerspace network case studies provide insight into the use and value of quantitative ecosystem structure and function indicators for monitoring similar human‐engineered interaction networks that are normally only tracked qualitatively.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"97 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140750530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Automation is the guiding principle of this new era, and despite the problems that humanity faces as a result of automation, technology has greatly benefitted people by streamlining challenging jobs across many industries. The mining business, where there are frequently unforeseen mishaps, is one such industry that requires complete automation. In this work, a new simulative processing environment termed DTFL‐DF—Digital twin federated learning decision forest a digital twin environment that is tailored to handle unforeseen fire incidents—is offered as a means of avoiding these unplanned catastrophes in the mining industry. Although the design presented here is intended for usage in the mining sector, it can also be applied to other sectors. The overall technological contribution of this study is to guarantee the processing of real‐time data in order to successfully handle mission‐critical operations without relying on past data. This is accomplished by adapting the digital twin's original design and distributing the processing environment within the edge‐fog layer. Results analysis in the form of robustness analysis, performance evaluation of the classification model, etc. provides strong support for the suggested methodology. For handling the decentralized training procedure, a brand‐new algorithm termed FL‐DF is put forth in order to speed up classification and prevent any sort of catastrophe.
{"title":"DTFL‐DF: Digital twin architecture powered by federated learning decision forest to mitigate fire accidents in mining industry","authors":"Udayakumar Kamalakannan, Ramamoorthy Sriramulu, Poorvadevi Ramamurthi","doi":"10.1002/sys.21755","DOIUrl":"https://doi.org/10.1002/sys.21755","url":null,"abstract":"Automation is the guiding principle of this new era, and despite the problems that humanity faces as a result of automation, technology has greatly benefitted people by streamlining challenging jobs across many industries. The mining business, where there are frequently unforeseen mishaps, is one such industry that requires complete automation. In this work, a new simulative processing environment termed DTFL‐DF—Digital twin federated learning decision forest a digital twin environment that is tailored to handle unforeseen fire incidents—is offered as a means of avoiding these unplanned catastrophes in the mining industry. Although the design presented here is intended for usage in the mining sector, it can also be applied to other sectors. The overall technological contribution of this study is to guarantee the processing of real‐time data in order to successfully handle mission‐critical operations without relying on past data. This is accomplished by adapting the digital twin's original design and distributing the processing environment within the edge‐fog layer. Results analysis in the form of robustness analysis, performance evaluation of the classification model, etc. provides strong support for the suggested methodology. For handling the decentralized training procedure, a brand‐new algorithm termed FL‐DF is put forth in order to speed up classification and prevent any sort of catastrophe.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"35 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140753136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Chaudemar, Ombeline Aïello, P. de Saqui-Sannes, Olivier Poitou
Over the past decades, Unmanned Aerial Vehicles (UAVs) have increasingly been used in a wide variety of missions that range from surveillance to delivery. Unlike aircraft that always carry goods and passengers from an airport to another, UAVs do not systematically implement the same type of mission. UAVs are indeed multi‐mission during their time in operation, and the systems engineering approaches developed for one mission aircraft must be adapted to the multi‐mission context. Therefore, UAV design requires application of mission engineering upstream systems engineering, either to assess there is a UAV system that may accomplish a new mission, or to specify a new UAV system according to a given mission. To achieve that goal, the authors of the paper support the use of Model‐Based Mission Engineering. A three‐layer architecture ‐ purpose, operation, functions or capabilities ‐ is proposed as a design framework for missions. The Goal‐Oriented Requirements Language (GRL) serves as mission description language. The paper extends GRL to better address mission‐based design of UAVs. It is proposed to distinguish between internal and external resources. A goal detailing mechanism is introduced. A degraded mode evaluation becomes possible. GRL tools make it possible to evaluate how much a UAV system ‐ at least, an operator, a ground station, and a UAV ‐ may satisfy every stakeholder in both nominal and degraded modes. The proposed approach is applied to a high voltage surveillance UAV. The case study enables the introduction of four actors—Authority, Client, UAV and MissionSupervisor—that turn out to be generic and can be reused for other missions and UAV designs.
{"title":"Mission‐based design of UAVs","authors":"J. Chaudemar, Ombeline Aïello, P. de Saqui-Sannes, Olivier Poitou","doi":"10.1002/sys.21754","DOIUrl":"https://doi.org/10.1002/sys.21754","url":null,"abstract":"Over the past decades, Unmanned Aerial Vehicles (UAVs) have increasingly been used in a wide variety of missions that range from surveillance to delivery. Unlike aircraft that always carry goods and passengers from an airport to another, UAVs do not systematically implement the same type of mission. UAVs are indeed multi‐mission during their time in operation, and the systems engineering approaches developed for one mission aircraft must be adapted to the multi‐mission context. Therefore, UAV design requires application of mission engineering upstream systems engineering, either to assess there is a UAV system that may accomplish a new mission, or to specify a new UAV system according to a given mission. To achieve that goal, the authors of the paper support the use of Model‐Based Mission Engineering. A three‐layer architecture ‐ purpose, operation, functions or capabilities ‐ is proposed as a design framework for missions. The Goal‐Oriented Requirements Language (GRL) serves as mission description language. The paper extends GRL to better address mission‐based design of UAVs. It is proposed to distinguish between internal and external resources. A goal detailing mechanism is introduced. A degraded mode evaluation becomes possible. GRL tools make it possible to evaluate how much a UAV system ‐ at least, an operator, a ground station, and a UAV ‐ may satisfy every stakeholder in both nominal and degraded modes. The proposed approach is applied to a high voltage surveillance UAV. The case study enables the introduction of four actors—Authority, Client, UAV and MissionSupervisor—that turn out to be generic and can be reused for other missions and UAV designs.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"17 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper looks at the bacteria chemotaxis control process utilizing the System Modeling Language (SysML) to leverage well‐defined and proven engineering tools for architecting, analyzing, and refining complex systems. It proposes a new methodology called reverse‐engineering object‐oriented systems engineering method (RE‐OOSEM) that converts descriptive biology research information into descriptive systems engineering information. It utilizes SysML and model‐based systems engineering (MBSE) to capture system architecture from biological system knowledge and inputs them into systems engineering tools. From an engineering point of view, this allows greater insight into how biological systems operate and suggests how much model detail is required to uncover a top‐down system understanding. RE‐OOSEM methodology guides the SysML chemotaxis control capture process. SysML syntax is used instead of biological syntax to facilitate biological chemotaxis control system analysis from an engineered system point of view. The model can act as a scaffolding to help uncover system function, the relationships of system components and processes, and bioinformatic phenotype and genotype correlation. An executable MathWorks Stateflow chemotaxis control process model based on the SysML architectural model is included. The results show the following engineering perspective observations. (1) Several control components are not dedicated but are available and utilized when needed. (2) Individual chemoreceptors act together as a sensor array. (3) Phosphate groups act as a signaling mechanism. (4) Methylation via CH3 groups of the chemoreceptor results in sensitivity adaptation. (5) Closed‐loop control collaboratively utilizes ligand bonding, phosphorylation, and methylation. (6) Timing relationships of the control subprocesses give insight into the system's architecture.
{"title":"Bacterial chemotaxis control process analysis with SysML","authors":"James D. Johansen","doi":"10.1002/sys.21752","DOIUrl":"https://doi.org/10.1002/sys.21752","url":null,"abstract":"This paper looks at the bacteria chemotaxis control process utilizing the System Modeling Language (SysML) to leverage well‐defined and proven engineering tools for architecting, analyzing, and refining complex systems. It proposes a new methodology called reverse‐engineering object‐oriented systems engineering method (RE‐OOSEM) that converts descriptive biology research information into descriptive systems engineering information. It utilizes SysML and model‐based systems engineering (MBSE) to capture system architecture from biological system knowledge and inputs them into systems engineering tools. From an engineering point of view, this allows greater insight into how biological systems operate and suggests how much model detail is required to uncover a top‐down system understanding. RE‐OOSEM methodology guides the SysML chemotaxis control capture process. SysML syntax is used instead of biological syntax to facilitate biological chemotaxis control system analysis from an engineered system point of view. The model can act as a scaffolding to help uncover system function, the relationships of system components and processes, and bioinformatic phenotype and genotype correlation. An executable MathWorks Stateflow chemotaxis control process model based on the SysML architectural model is included. The results show the following engineering perspective observations. (1) Several control components are not dedicated but are available and utilized when needed. (2) Individual chemoreceptors act together as a sensor array. (3) Phosphate groups act as a signaling mechanism. (4) Methylation via CH3 groups of the chemoreceptor results in sensitivity adaptation. (5) Closed‐loop control collaboratively utilizes ligand bonding, phosphorylation, and methylation. (6) Timing relationships of the control subprocesses give insight into the system's architecture.","PeriodicalId":509213,"journal":{"name":"Systems Engineering","volume":"38 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140076864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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