AHFE Open AccessHuman Factors in Software and Systems Engineering
Editors: Tareq Z. Ahram
Topics: Systems Engineering
Publication Date: 2025
ISBN: 978-1-964867-57-1
DOI: 10.54941/ahfe1005992
Articles
Applying Model-Based Requirement Patterns Library Concept to Astronaut Space Suit System for Deep-Space Travel and Mars Surface Exploration Missions
Risk of extinction and survival has always pushed humans to develop new technologies, starting from the innovation of a wheel up to producing advanced materials and alternative energy sources. Becoming a multiplanetary species reduces the risk of extinction from home grown and external threats like nuclear wars, effects from extreme temperature changes, and asteroid impact. Going to Mars is beyond current medical, technological, and economical challenges. A trip to Mars requires over 140 million miles deep-space travel in harsh space environment with no assistance readily available. Similarly, landing, exploring, and returning from Martian surface exposes numerous challenges with extreme uncertainties. Astronauts Space Suit System plays a vital role in all these missions. This paper proposes an analysis of a space suit system that would be suitable for long duration space travel, Extravehicular Mobility Unit (EMU) and surface exploration missions. When designing suits for deep-space space travel and Extravehicular Activity (EVA) on the surface of Mars, it is important to start with the top-level systems requirements, such as life support, mobility, microgravity, human factors, ergonomics, and protection from environmental hazards. To better understand this human systems integration, the designers can utilize Model-Based Systems Engineering (MBSE) with Model-Based Pattern Library (MBPL) concept to specify the necessary requirements for the suits. In this approach, the original requirements are decomposed and translated into Object-Oriented Models (OOMs) that are generated using System Modelling Language (SysML). This paper also demonstrates a unique systems-of-systems approach that combines human health and physiology, system requirement analysis for human factors and ergonomics using MBSE and pattern libraries. Once built, the pattern libraries can be used to develop the various logical architectures for the space suits with mission and program specific requirements.
Bhushan Lohar, John Wade, Abhishek Mange, Mir Ali, Ryan Colquhoun, Lyliandra Larson
Open Access
Article
Conference Proceedings
Model-Based Architectural Patterns Concept for Home Security System Solutions
The home security system is a comprehensive guard against threats to the home and rental properties. The history of the home security system is extensive and has become revolutionary in transforming its abilities to better perform for the user. This system protects owners, residents, their valuables, and provides peace of mind. This vital tool can be enhanced by using a Model Based Systems Engineering (MBSE) technique, Model-Based Architectural Patterns (MBAP), to produce an elevated level of safety to users. The detailed abilities associated with MBAP development will provide an all-inclusive experience for users to have a personalized security system for their property. This paper discusses a concept that aims to highlight the compound ability of home security and its capacity to provide varieties of viable solutions with various levels of protection using MBAP method. The diverse levels of protection that will be outlined in these patterns will explore different types of intrusions and user interruptions that would require protection of the home through a security system. The concept in this paper also discusses already existing wireless communication protocols which allows for an analysis of the different connectivity types that can be used to demonstrate the choices and variations in the home security system. Additionally, the purpose of this research is to show how the use of advanced Model-Based Systems Engineering (MBSE) methods and tools with an architectural pattern library concept can enhance the determination, selection process and solution competence of the home security system. The user requirements, need satisfactions, human factors, and appropriate security levels can be developed using a template like a work-flow process. The work-flow process can accomplish the specific needs and wants of the system in relation to stakeholder desires. This process can display the accurate repetition needed to provide unique protection to each user. The idea is to demonstrate the pattern library development and provide a user template that will serve as an outline of the system. The pattern library will be evolved from requirements that outline the necessary abilities of the system. This paper demonstrates the concept of using advanced MSBE to enhance the home security system selection, requirements allocation and verification to serve as a basis for improving system performance by developing a Model-Based Patten Library (MBPL) from the MBAP’s created that provides unique solutions per user requirements and needs. The patterns will contain a multi-level decomposition of the system and be allocated to the applicable system elements that support various security system protocols like Z-wave.
Daijha Hilliard, Bhushan Lohar, John Wade, Kari Lippert, Saeed Latif
Open Access
Article
Conference Proceedings
IT Tool Stack Optimization in Collaborative Projects: An Evaluation and Recommendation Framework
In modern industrial engineering, configuring IT tool systems is fundamental to ensuring productivity and quality in collaborative projects. Small and medium-sized enterprises (SMEs) face distinctive challenges in selecting and adopting these systems—not only due to limited IT and AI expertise but also because of insufficient consideration of human perceptual factors such as technology acceptance and subjective practical experience. These challenges adversely affect overall quality, productivity, and technology adoption.This study proposes a user-centric framework for evaluating and recommending IT tools for system design. The framework employs standardized human-centric evaluation methods based on the Critical to Quality (CTQ) methodology. By integrating requirements engineering with machine learning (ML) models—including collaborative and content-based filtering techniques—the approach systematically analyzes data to identify similarities among users and project archetypes, thereby recommending the most effective tool configurations. Moreover, ML models are utilized to refine recommendations by matching individuals across projects and incorporating cognitive factors related to perceived tool usage efficiency. This systematic approach to IT tool stack configuration aligns with organizational objectives and project-specific requirements, ultimately enhancing collaborative capabilities, productivity, and technology adoption and acceptance rates in SMEs.
Can Cagincan, Juliane Balder, Roland Jochem, Rainer Stark
Open Access
Article
Conference Proceedings
Antenna technology in energy recovery systems
Nowadays, we observe dynamic technological progress. Often, due to the multitude of responsibilities, we are not aware of the conveniences that modern technology gives us. Modern man cannot imagine life without the possibility of using radio communication systems, including mobile telephony. Systems for obtaining electricity from phenomena occurring in the natural or industrial human environment are known under two names: energy harvesting and energy scavering. Both of these names refer to the same phenomena and methods. Sometimes in the literature the use of these names depends on the nature of the energy being processed. The name energy scavering is used when the type of energy source and its efficiency are not known, while energy harvesting is used when the source of potential energy is well described and regular.The dynamic development of applications requiring autonomous energy sources favors the rapid development of EH technology. The main area of application of EH is wireless sensor networks (WSN), where the energy demand of a single autonomous node depends on the current operating mode. In the standby state, the demand for electricity usually does not exceed several μW, and during measurement it does not exceed 100 μW. The greatest demand occurs during information transmission and ranges from 0.1 to 1 mW. Such energy demand values clearly indicate the possibility of using EH generators as additional power sources for smartphones.Another area of application of EH technology are systems for recharging batteries used in larger measurement systems where there are other traditional ways of charging batteries.One of the fundamental problems that arise when analyzing the possibility of using electromagnetic radiation as a source of recovered energy is the issue related to the assessment of the field strength distribution in the area of operation of the designed system. Knowledge of this distribution allows the designer to assess the degree of land cover. Therefore, every designer faces a serious problem of selecting an appropriate propagation model that will best describe the reality created by the designed system.An important aspect when analyzing the possibility of using electromagnetic radiation as a source of recovered energy is the proper selection of antenna technologies that can be used for the above application. In this chapter of the study, microstrip antennas are proposed for the above purpose.The work presents a designed measurement antenna that can operate from 500 MHz to 7.6 GHz, the operating bandwidth is 7.1 GHz,
Marian Wnuk
Open Access
Article
Conference Proceedings
Exploration of a Generative AI Assistant for Model-Based System Engineering (eGAIA4MBSE)
Model-Based System Engineering (MBSE) has served as a formal model of systems engineering in terms of requirements, design, analysis, verification, and validation. This process is applied and updated throughout the lifecycle of a project. Such creative models provide the means to exchange information about the system. A consensus exists that the MBSE process has improved the systems engineering process especially when compared to the document-based approach. MBSE uses a form of XML called SysML to represent the MBSE model and a set of diagrams like UML diagrams used in the software development arena. MBSE has grown in use and expanded into other areas including simulation. This poster represents the ongoing work to incorporate and integrate avenues of Generative Artificial Intelligence (GenAI) into MBSE. GenAI has quickly reached a level of capability, maturity, and widespread use in recent years. The generation of content as well as supporting MBSE users in Development including the supporting SysML, positions GenAI to play an important role in the modeling with MBSE. Work is underway to explore how GenAI can generate the MBSE content and support the end user in providing crucial feedback on the rules and processes involved with MBSE while generating MBSE content. This work tends to show how GenAI along with RAG-based MBSE information can be incorporated into GenAI to serve as an AI agent which supports the development, validation, and documentation of said models. GenAI has been poised to be such an agent for this creative MBSE generation and user support in the systems engineering process. The application of GenAI with MBSE is still in the infant stages and this work seeks to explore the effectiveness of that integration.
Bryan Croft
Open Access
Article
Conference Proceedings
Simulation based study on heat transfer in microchannel heat sink with square ribs surface
A simulation-based study is carried out on microchannel heat sink with smooth surface and square ribs embedded surface. The heat sink is made of microchannels where each channel is 150 μm in width, and 1 cm in length. Water is used to study the heat sink. The study is conducted for a range of Reynolds numbers, from 100 to 500. The fluids' inlet and outlet temperatures, and the surface temperatures are used to calculate the thermal performance. According to the investigation, a higher Reynolds number raises the heat transfer coefficient and increasing Nusselt number. Additionally, it has been noted that raising the Reynolds number lowers the friction factor. It was evident that the square ribs microchannel had a higher heat transfer rate than the smooth channel. Additionally, it is observed that the heat sink with square ribs microchannels overall friction factor is higher than the heat sink with smooth channels. It is also found that the pressure drop increases with increasing Reynolds number.
Bobby Mathew, Fadi Alnaimat
Open Access
Article
Conference Proceedings
Job Analysis of Gas and Electric Power Dispatchers for Control Room Design Decision Support
Power and gas dispatchers control crucial infrastructure of modern society. Key tasks include reacting quickly to problems such as gas leaks and short circuits. Phases of low performance needs, alternating with phases of high performance requirements, with time critical components, make the job challenging. To guide future optimizations in workplace design regarding support systems, ergonomic design of the control center’s hardware and software, and the selection of applicants and training, a job analysis survey was performed. A total of 27 dispatchers filled out the Fleishman Job Analysis System questionnaire (F-JAS). Scales with high scores in the categories cognition, sensory skills and social/interpersonal skills suggest potential to optimize the jobs and are discussed in more detail to guide future research to enhance efficiency, effectiveness, and safety of the workplace.
Thomas E F Witte, Torsten Gfesser, Jessica Schwarz, Stephanie Hochgeschurz
Open Access
Article
Conference Proceedings
Exploring Political Factors in Clean Energy Transition Using Machine Learning Technique
A nationwide transition to clean energy still faces persistent political challenges in the past decade. It is because the public support for clean energy policies remains deeply polarized among partisan and ideological lines. While there is an established scientific consensus of climate change, the urgence to change the status quo fails to trigger existential insecurity of individual Americans. While extensive studies have examined the role of partisanship, regional economy, and media framing in shaping these divisions, scholars know very little about the emotional foundation that drive individual voter’s clean energy preferences and behaviors. A major challenge for the scholarship is due to the lack of longitudinal data that contains measurement of both individual emotions as well as clean energy ideologies over time. This study introduces a simulation-based methodology that combining machine learning with traditional survey analysis to examine how anxiety and fear, two emotions related to existential security, shape clean energy policy ideologies and behaviors in the net of social and political factors. Our analytical strategy proceeds in three stages. First, utilizing multiple waves of cross-sectional data collected by Chapman University since 2014, we train a semi-parametric model to estimate the relationship between commonly used apolitical demographic features and anxiety and fear. We will also run the robustness check to make the model is time invariant. Second, we apply the model to two of most recent probabilistic samples collected by Pew Research Center where it contains clean energy ideology and behavior items but lacks emotional measures. And finally, we analyze how these simulated emotional predispositions interact with a range of political and social factors to predict support for clean energy initiatives. Preliminary findings suggest that political and partisan preference may suppress the effective size of existential insecurity to the support of clean energy. And we find this impact is also varied across different clean energy behaviors. The study makes several key contributions. First and methodologically, the study demonstrates how machine learning can bridge gaps between datasets with different focuses and enables more comprehensive analysis of clean energy related studies with nationally representative data. Second and theoretically, it advances our understanding of how emotions related to existential insecurity shape clean energy policy behaviors. Future research could extend this framework to examine how different aspects of policy framing might differentially affect the suppression of climate-related fears. Additionally, longitudinal applications of this approach combining with large language modeling could help track how the relationship between political framing and negative emotions evolves in response to changing environmental conditions and policy-making.
Zining Yang, Ruiqian Li
Open Access
Article
Conference Proceedings
Sociotechnical Challenges in the Implementation of Hydrogen Fuel Cell Trucking
As automobile and semi-truck manufacturers wheel out new hydrogen fuel cell vehicles (HFCV), new infrastructure to refuel and repair these vehicles must be developed. In this paper, the authors examine the sociotechnical hurdles to developing the infrastructure needed to refuel or recharge these vehicles in the state of Alabama and throughout the Southeast of the United States. Currently, no infrastructure exists in the state to support the use of HFCV trucks. However, given the presence of Interstates 10 and 65 which connect northern cities like Chicago and Indianapolis with shipping ports like New Orleans and Mobile, regional infrastructure will be required to support these new trucks. In this paper, the authors break down the sociotechnical issues using a multiple domain matrix to examine the social, technical, and sociotechnical challenges to implementing the infrastructure needed for hydrogen semi-trucks
Sean Walker, Mohamed El-sharkh
Open Access
Article
Conference Proceedings
Empowering Transportation Electrification and Grid Planning: A Bottom-Up Predictive Modeling Framework
Transportation electrification plays a crucial role in the transition to green energy. As households, businesses, and public entities increasingly shift from gas vehicles to electric vehicles (EVs), the demand for charging infrastructure leads to a significant rise in energy consumption. To effectively plan grid buildout, utilities need to rely on granular geographic data to pinpoint when and where EVs will start to emerge or grow in number on the grid. This process involves utilizing multiple models, including detection models to identify existing EVs that are currently unknown to utilities; propensity models to predict which customers are more likely to adopt electric vehicles in the near future; and forecasting models to anticipate which service areas will experience a greater rise in energy demand due to increasing EV adoption, thus requiring more immediate attention. While there is overlap in data sources and preliminary work on this topic, this paper outlines a blueprint for a bottom-up approach that leverages diverse data to create multiple predictive models tailored to different business needs.
Alec Zhixiao Lin, Isaac Chen Fu
Open Access
Article
Conference Proceedings
Power Shortages and Sustainable Solutions in South Africa: The Role of Inga 3 Hydropower and Green Supply Chains
The current energy crisis in South Africa, within the transformational context of the Inga 3 Hydropower Project and further through green supply chains, is the subject of this research. It fully describes how shortages of electricity have dire implications for key industries such as mining, manufacturing, and services, all exacerbated by aging infrastructure and dependence on coal. The Inga 3 project involves 4,215 MW of capacity and is discussed here as an example of how a renewable energy alternative could alleviate South Africa's energy deficit.This paper looks at the feasibility of integrating Inga 3 into the South African power grid from a technical, economic, and environmental point of view, considering how green supply chain management can help toward greater sustainability and efficiency. GSCM integrates sustainability within the supply chain for benefits to include reduced carbon footprints, resource optimization, and enhanced environmental performance.These are exciting economic, social, and environmental benefits related to the inclusion of renewable energy and green supply chains; they include job opportunities, reductions in energy costs, and enhancements of industrial efficiencies. The infrastructure improvement, political will, and financial commitments pose the challenges to attain these targets. Finally, this study concludes with policy recommendations toward the implementation of renewable energy and sustainability with a view to transforming the energy platform in South Africa.
Frank Mushingelette Mbangu, John Ikome, Aa Alugongo
Open Access
Article
Conference Proceedings