System Design Framework Research Articles

Transverse energy absorption performance of sandwich tubes with various origami foldcores

Nowadays, composite sandwich tubes are extensively utilized in the civil and aerospace industries due to their superior strength-to-weight mechanical properties. Origami-based core offers a large enhancement of the mechanical properties, yet little study research focuses on the effect of various foldcore configurations on the transverse mechanical properties of sandwich tubes, necessitating the design method for applications. This study introduces an innovative approach by incorporating origami into the composite sandwich core to enhance the transverse energy absorption capacity. The quasi-static transverse mechanical properties of carbon fibre-reinforced polymer (CFRP) sandwich tubes with foldcores are studied under three-point bending-like local compression and transverse structural compression. A systematic geometric design framework and numerical modelling technique are provided. By integrating finite element analysis and experiments, the research investigates the effects of various origami foldcore configurations and geometric parameters on transverse energy absorption capacity. The experiment setup is provided by sandwich tubular specimens with a full-diamond configuration as the foldcore. The cylindrical tubes (foldcore) of the sandwich structures were manufactured using four plies [0°]4 of T700 (T300) woven CFRP with the hot press moulding (vacuum bag using female and male moulds) technique respectively. Then, the parametric study and damage mode analysis of eight different foldcore patterns (axial Miura, circumferential Miura, diamond, Kresling, and their curved-creased counterparts) were studied. The results showed the superior energy absorption performance of the sandwich tube with Miura-pattern foldcore over the origami-pattern counterparts, nested tube, and traditional honeycomb sandwich tube with CFRP or aluminium-made cores. Therefore, the structural parameters optimisation of the Miura pattern tube was carried out by the Response Surface method (RSM) and a design strategy for increasing the energy absorption capacity was found. The findings offer guidance for designing high-specific energy absorption tubular structures for future advanced engineering applications.

A virtual reality-based immersive teleoperation system for remote human-robot collaborative manufacturing

In recent years, the cutting-edge technologies in smart manufacturing have presented promising opportunities for the utilization of human-robot collaborative teleoperation in personalized manufacturing tasks. To effectively leverage the creative capabilities of humans while benefiting from the efficiency and stability of robots, the provision of an intuitive teleoperation interface assumes paramount importance. However, current teleoperation systems still face limitations in terms of intuitive operability. In this study, we present a virtual reality-based teleoperation system that offers operators a more intuitive interaction platform for robot control, thereby facilitating personalized manufacturing processes. The overall system framework design, as well as the main components are elaborated in detail. Furthermore, an evaluative case study based on the battery disassembly task is conducted to assess the performance of the proposed system. The results demonstrate that the proposed teleoperation system exhibits improved intuitiveness.

Towards a conceptual design framework for bee botanic gardens: integrating perceptions on urban biodiversity into landscape design processes

Botanic gardens, valued for their live plant collections, have evolved into scientific institutions with roles in conservation, education, research, and public recreation. This study repositions botanic gardens as essential urban habitats enhancing biodiversity, focusing particularly on their support for both European honeybees and Western Australian native bees. This research addresses the intersection of urbanisation and bee conservation by developing a conceptual design for a bee-friendly botanic garden in Yanchep, Western Australia. It employs semi-structured interviews and research through design (RtD) methods to collaborate with local beekeepers, landscape architects, and ecologists. A systematic design framework for a bee-friendly botanic garden in Yanchep, Western Australia was proposed, encompassing the entire design process, from scope to detailed considerations, and aiming to be applicable across other parts of Western Australia and Australia. The research highlights three key findings: the necessity of interdisciplinary collaboration, the importance of defining the garden type and functions early in the design process, and the need for diverse plant selection and nesting options to support native bees.

Design of Intelligent Financial System Based on Adaptive Learning Algorithm

The high-frequency trading system in the financial domain has long been a focal point of investigation. This study posits an intelligent financial system design framework predicated on a cross-adaptive self-entropy projection clustering model, aimed at enhancing the efficacy of high-frequency trading systems. A composite distribution model of financial data is formulated to derive sequences of financial data activities. And cross-adaptive learning algorithm is employed to ascertain the interrelated attributes of financial data. Following this, the support vector machine algorithm is applied for the classification processing of these interrelated features, yielding a set of financial data feature vectors, which are then fed into the gray correlation-based information feature extraction model. Through extensive empirical evaluations with authentic trading data, the proposed intelligent financial system design framework exhibits commendable performance, furnishing a viable solution for the intelligent optimization of high-frequency trading systems.

Turning Data Center Waste Heat into Energy: A Guide to Organic Rankine Cycle System Design and Performance Evaluation

This study delves into the adoption of the organic Rankine cycle (ORC) for recovering waste heat from data centers (DCs). Through a literature review, it examines energy reuse with a focus on electric power generation, the selection of working fluids, and system design principles. The objective is to develop a thorough framework for system design and analysis, beginning with a quantity and quality investigation of waste heat available. Air cooling systems, chosen often for their simplicity, account for about 70% of used cooling methods. Water cooling demonstrates greater effectiveness, albeit less commonly adopted. This study pays close attention to the selection of potential working fluids, meticulously considering the limitations presented by the available sources of heat and cold for vaporization and condensation, respectively. It reviews an ORC-based system setup, incorporating fluid streams for internal processes. The research includes a conceptual case study where the system is designed and simulations are conducted in the DWSIM environment. The simulation model considers hot air or hot liquid water returning from the data center cooling system for ORC working fluid evaporation. Ambient water serves for condensing, with pentane and isopentane identified as suitable organic fluids. Pentane assures ORC net electric efficiencies ranging between 3.1 and 7.1% when operating pressure ratios increase from 2.8 to 6.4. Isopentane systems, meanwhile, achieve efficiencies of 3.6–7.0% across pressure ratios of 2.7–6.0. Furthermore, the investigation provides key performance indicators for a reference data center in terms of power usage effectiveness (PUE), energy reuse factor (ERF), energy reuse effectiveness (ERE), and greenhouse gas (GHG) savings. This study concludes with guidelines for system analysis, including exergy considerations, and details the sizing process for evaporators and condensers.

On the optimal multi-objective design of fractional order PID controller with antlion optimization

This study introduces an optimal multi-objective design approach for a robust multimachine Fractional Order PID Controller (FOPID) using the Antlion algorithm. The research focuses on the need for effective stabilizers in multimachine power systems by employing traditional speed-based lead-lag FOPID controllers. The study formulates a multi-objective problem, optimizing the damping factor and damping ratio of lightly damped electromechanical modes to maximize a composite set of objective functions, tackled through the Antlion algorithm. Stability analysis of Single-Machine Infinite-Bus (SMIB) and multimachine power systems is conducted based on rotor speed and power deviation minimization in the time domain response, along with damping ratio and eigenvalue analysis. The proposed approach is implemented and tested on three IEEE test cases, showcasing significant improvements in stability through the reduction of maximum overshoot (Mp) and settling time (ts) of speed deviation. Comparative analysis with other optimization-based FOPID controllers underscores the superiority of the proposed approach in enhancing stability in multimachine power systems. The main impact of this research lies in its contribution to the advancement of stability enhancement techniques in multimachine power systems, offering a systematic framework for optimal FOPID controller design and empowering decision-making processes in power engineering.

A Systematic Literature Review (SLR) on Yixing Zisha Teapot Design as Intangible Cultural Heritage

Promoting traditional culture and intangible cultural heritage has always been a hot topic for the Chinese government, which has also formulated a series of policies to support the development of intangible cultural heritage. As the first batch of intangible cultural heritage recognized by the Chinese government, Yixing Zisha teapot-making techniques have gradually spread in design theory and practise with the promotion of the government and artisans. Therefore, this article systematically reviews the design of Yixing Zisha teapots from the perspective of intangible cultural heritage, emphasising design concepts and design thinking. Critical thinking of bibliometric analysis and literature review was conducted to achieve the research objectives. The results show preliminary design concepts and thinking that emerged in the Yixing Zisha teapot design. However, there needs to be a systematic design theory and framework to promote future design research, pointing out that the research gap can help promote the development of the Yixing Zisha teapot design.

Developing stable, simplified, functional consortia from Brachypodium rhizosphere for microbial application in sustainable agriculture

The rhizosphere microbiome plays a crucial role in supporting plant productivity and ecosystem functioning by regulating nutrient cycling, soil integrity, and carbon storage. However, deciphering the intricate interplay between microbial relationships within the rhizosphere is challenging due to the overwhelming taxonomic and functional diversity. Here we present our systematic design framework built on microbial colocalization and microbial interaction, toward successful assembly of multiple rhizosphere-derived Reduced Complexity Consortia (RCC). We enriched co-localized microbes from Brachypodium roots grown in field soil with carbon substrates mimicking Brachypodium root exudates, generating 768 enrichments. By transferring the enrichments every 3 or 7 days for 10 generations, we developed both fast and slow-growing reduced complexity microbial communities. Most carbon substrates led to highly stable RCC just after a few transfers. 16S rRNA gene amplicon analysis revealed distinct community compositions based on inoculum and carbon source, with complex carbon enriching slow growing yet functionally important soil taxa like Acidobacteria and Verrucomicrobia. Network analysis showed that microbial consortia, whether differentiated by growth rate (fast vs. slow) or by succession (across generations), had significantly different network centralities. Besides, the keystone taxa identified within these networks belong to genera with plant growth-promoting traits, underscoring their critical function in shaping rhizospheric microbiome networks. Furthermore, tested consortia demonstrated high stability and reproducibility, assuring successful revival from glycerol stocks for long-term viability and use. Our study represents a significant step toward developing a framework for assembling rhizosphere consortia based on microbial colocalization and interaction, with future implications for sustainable agriculture and environmental management.

Assembly process analysis and system design for deep in-situ fidelity corer

The deep in-situ corer is an essential tool for exploring the physical and mechanical behaviours of rocks at varying depths. Corers are multi-part products, encompassing extensive redundant assembly information stemming from the intricate assembly processes and numerous components. Thus, designing assembly systems for corers poses complexity challenges. This paper proposes an automated assembly system design framework, comprising assembly process analysis and system development. The proposed framework offers comprehensive design processes for multi-part product assembly systems, emphasizing managing information amount and complexity during the design phase. Specially, design principles and methods for minimizing information amount are analysed. And the directed graph is utilized to express the assembly information. Building upon this foundation, automated assemblability assessment and assembly process modular clustering is proposed to amalgamate and streamline assembly information, thus reducing design complexity. Leveraging pre-processed assembly information, the sub-functional solutions for assembly system are solved and optimized with AD (Axiomatic Design) and TRIZ (the Theory of Inventive Problem Solving). A case study of the deep-sea gas hydrate corer validated the effectiveness of the proposed methods in reducing information amount and yielding sub-functional solutions, thereby facilitating overall system design realization. Assembly experiments verified the designed system accomplished functional requirements. This study serves as a valuable reference for automated assembly analysis and system development for multi-part products, offering technical insights into developing deep in-situ cores from an assembly perspective.

A self-adaptive joint optimization framework for marine hybrid energy storage system design considering load fluctuation characteristics

Recently, with the development of new energy technologies, all-electric ships (AESs) with hybrid energy storage system (HESS) are becoming a promising solution to reduce fuel consumption and emissions. However, the high maneuverability of ships during the actual navigation places higher performance requirements on the HESS, which presents a nonlinear and multi-objective challenge for the HESS design. Therefore, it is necessary to consider the coupling between HESS sizing and energy management strategy (EMS). In this paper, a self-adaptive joint optimization framework (SJOF) for marine HESS design considering load fluctuation characteristics is proposed, which can find the optimal decision solution with excellent system economic and battery life performance for AES HESS design. Based on the rain flow counting (RFC) method, a multi-objective joint optimization method considering life cycle cost (LCC) and battery degradation index (BDI) is introduced into SJOF. Besides, a novel EMS including the self-adaptive segmentation mechanism (SSM) and power allocation is proposed, which can achieve the most efficient energy scheduling.

Monitoring system framework design for floating wind turbine using the deep learning technology and tower response identification considering sensor optimization

Comparing with the fixed wind turbines, the dynamic characteristics of floating wind turbines (FWTs) are more complex and resulting in distinctions in the monitoring system for structural responses. An integrated monitoring system framework concept design for FWT is proposed combing the dynamic responses correlations of different structural parts and the deep learning technology, in which the intact and partial sensor failure operation modes are considered separately. The monitoring system consists of four vital structural components, including the rotor and nacelle, tower, floating foundation, and mooring system. In order to improve the tower response identification accuracy, a new method for the sensor optimization is proposed to utilize more structural information of the structure based on the effective independence method (EIM) and modal assurance criteria (MAC) methods. A multi-perception (MLP) neural network model based on the input-output coupling mechanism is established to identify the acceleration responses at the tower top and forces at tower root. The optimized identification model can greatly improve the identification accuracy of critical sensors by more than 50%, especially for bending moments.

Developing an intelligent systems design framework based on multidisciplinary design analysis and multi-agent thinking integration

The design of real-world engineering systems deals with high complexity at the system and subsystem levels, as well as the interaction between the subsystems involved. Multidisciplinary Design Optimization (MDO), which aims to integrate the optimization algorithms in both system and subsystem levels along with exploring mechanisms of synergistic action among subsystems, is a renowned methodology to design complex engineering systems. In Multi-Agent Systems (MASs), as a complex system, to achieve the best system performance, agents have to work their individual tasks in a coordinated manner and in cooperation with other agents. Given some architectural resemblance between MDO and MAS, especially in subsystems interaction (agents, in MAS case), this paper addresses proposing a multi-agent multidisciplinary system design optimization strategy. This strategy by taking advantage of the capabilities of MDO proposes a consolidated framework for the optimal design of real world engineering systems. This strategy is extendable to multi-agent systems in a diverse range of missions and tasks. In this regard to illustrating its application a distributed cooperative search and coverage (CSC) mission in uncertain environments is considered as a case study for designing a MAS. The proposed framework contributes to designing a MAS by applying the history data of previously completed missions and the normalized cross-correlating (NCC) algorithm as well. The effectiveness of the proposed framework is demonstrated via simulations and comparison.

A user-centred collective system design approach for Smart Product-Service Systems: A case study on fitness product design

Emerging technologies have significantly contributed to the evolution of traditional product-service systems (PSS) into smart PSS. This transformation demands a fresh perspective and a more inventive design approach. In response, this study proposes a new User-Centred Collective System Design (CSD) framework and process for Smart PSS design, aiming to enhance stakeholder engagement during the entire design process, thus promoting highly effective and creative design solutions. A case study, titled ‘Next-G Smart Fitness PSS Design’, was carried out to test and implement this approach, contrasting the results of the CSD method with a designer-centred method. The outcomes showed a marked improvement in product novelty and user desirability of the design outcomes when using the proposed design framework. The proposed CSD framework could offer beneficial insights and user-centric viewpoints for practitioners dealing with complex challenges linked to smart PSS design.

Towards a pattern language for green space design in high density urban developments

ABSTRACT In the inevitable high-density urbanization process, existing urban green space (UGS) design approaches are ineffective in creating more green areas and combining multidisciplinary design principles to provide balanced sets of ecosystem services (ESs). This paper proposes a systematic framework for UGS design in the context of high-density urban development, results in spatial patterns, a pattern language, that combines specific design principles with a wide range of complementary ESs suitable for high-density environments. Such design approach can create more possibilities for UGS provisioning, deal with the complexity in high-density contexts, and provides consistency at different scale for UGS designs.

An efficient optimization framework for Urban drainage system design

An efficient optimization framework for Urban drainage system design

Efficient Multiobjective Optimization Framework for Induction Heating Systems Design

Efficient Multiobjective Optimization Framework for Induction Heating Systems Design

Teaching Case: Read to Win: Using the Game-based System Design Framework to Gamify a Summer Reading Program

The use of gamification for organizational initiatives, such as increased foot traffic and customer engagement, is on the rise. Given this, recent information systems graduates may find themselves on project teams aimed at making decisions about gamification efforts. Currently, information systems curriculum doesn’t typically address the use of specific frameworks to design and document requirements for a game-based information system to meet a business need. This teaching case exposes students to the use of the Game-based System Design Framework in combination with the Game-based System Design Diagram to enhance student learning around the design and documentation of a gamified information system. This case could be used in an undergraduate or graduate program in either a systems analysis and design or a capstone course. The use of this case assumes that students have a basic understanding of business requirements gathering and project scope statements. Additionally, in order to develop a solution to this case, it must be used in conjunction with the article “All Work and All Play? A Framework to Design Game-based Information Systems” (Barber et al., 2021).

Population balance model enabled digital design and uncertainty analysis framework for continuous crystallization of pharmaceuticals using an automated platform with full recycle and minimal material use

A systematic digital design framework for the development of a digital twin of a continuous crystallization process was presented using the model compound, diphenhydramine hydrochloride (DPH). The key features of the framework include operating space investigations, kinetic parameter estimation using population balance modeling, and systematic batch-to-continuous crystallization translation of the estimated parameters. An approach that compares experimental uncertainties with model-prediction uncertainties was used to justify the robustness of the parameter estimation procedure. For continuous crystallization development, a continuous configuration with full recycle and dissolution was developed, which enabled rapid process design with minimal material use. The results demonstrated successful model development for both batch and mixed-suspension-mixed-product-removal (MSMPR) crystallization configurations. This experimentally validated model, along with quantified uncertainty space of the kinetic parameters, serves as a digital twin of the process, which was later used to optimize the multistage MSMPR process to produce larger crystals with narrower distributions.

The VALUECARE Model for value-based, integrated health and social care services delivery supported by ICT for older adults: participatory research in 6 European countries

Introduction: In 2006, Michael Porter and Elizabeth Teisberg introduced the concept of value-based health care delivery by presenting a new framework for health system design. They proposed a fundamental unifying goal for health care: maximizing value for patients. Value is defined as the health outcomes achieved in response to the needs of a patient relative to the costs of delivering these outcomes. Consequently, understanding patient goals and values is integral to delivering high value. Participatory approaches are a key element in defining the care delivery model according to the patients’ needs and contribute to the sustainability of the care delivery. This study presents the VALUECARE model co-designed with older adults, care team members, health and social service managers and ICT experts to adapt the ValueCare concept supported by technology to the community context and end-users needs.
 Target group: Older people 65 years and older with comorbidity from 6 European countries (Croatia, Ireland, Portugal, Italy, Spain & The Netherlands) facing different health challenges (cardiovascular disease, cognitive decline, frailty, and stroke).
 Participants engaged in the co-design of the value based integrated care: A total of 369 participants were involved in participatory activities with the purpose of co-designing the VALUECARE care model and supportive digital solution (n= 127 older adults, n=86 caregivers, n=109 health and social care practitioners, n=7 ICT experts, n=34 service managers, n=3 policy makers, n=3 municipality providers).
 Co-design activities implemented: Qualitative data was collected using focus groups and interviews, combining face-to-face and online means with the participants trying to adapt the methodology foreseen in the project to the pandemic situation. The eHealth Enhanced Chronic Care Model was used as a heuristic tool to integrate the discourses of the different stakeholders including older adults and those involved in the delivery of health and social care for them and featuring the guiding principles and the core elements for value-based, integrated health and social care for this group supported by ICT solutions. 
 Results: VALUECARE model highlights best practice value-based, integrated care delivery through the application of a set of 6 guiding principles for the model (i.e. quality and safety, technology as supportive tool) across 7 different key core elements (i.e. health and care decision support, comprehensive support and monitoring). Applying these principles and elements, better health outcomes and care experience for older adults are expected and an improvement in the care team wellbeing. 
 Next steps: Based on the co-design sessions, the co-designed VALUECARE model is being implemented and tested in 6 pilot sites. Continuous and periodic feedback is being collected from participants (older people and care team members) to refine the model and ensure quality care delivery, at the end of the project, a validated model of value-based and integrated care supported by technology.

Improving Science Conceptual Understanding and Attitudes in Elementary Science Classes through the Development and Application of a Rule-Based AI Chatbot

Abstract This study aimed to develop a specialized rule-based AI chatbot tailored for a sixth-grade optics unit and to evaluate the impact of the implementation of the chatbot on students’ cognitive and affective outcomes related to science within the classroom setting. Specifically, this study explored how factors such as gender and achievement levels have an impact on student attitudes. The development of the rule-based chatbot adhered to the network-based instructional systems design framework, which involves the application of the analyze, design, develop, implement, and evaluate model to the e-learning design and development process. The participants were 192 sixth-grade students, with 81 in the experimental group and 111 in the control group. The results revealed a positive effect on students’ science achievement and interest, with a particularly significant impact on those with lower achievement levels. Notably, the chatbot played a crucial role in elevating the interest of female students in science. These findings highlight the need for continued research into the integration of rule-based AI chatbots in science education.