Design Of Systems Research Articles

CHATTER MITIGATION IN REAMING: EXPLORING EFFECTIVE TOOL HOLDER DESIGN

Reaming is a crucial technology in finishing operations, demanding high stability in the machining process for optimal results. The clamping system significantly influences the dynamic properties of the system tool – clamping - machine and is key in mitigating chatter. The introduction of new designs in clamping exchangeable reaming heads presents several challenges, particularly in terms of vibration suppression. This study explores various constructions of clamping bars, examining their dynamic properties in both static conditions and during machining. Through these evaluations, the research aims to understand how different designs impact the stability and effectiveness of reaming operations. The measured data from these experiments reveal how the construction of the holder influences machining process stability, providing insights into optimizing clamping system designs for improved reaming performance. the outcomes of this study contribute to the development of more effective and efficient clamping systems for finishing operations.

Impedance Specifications for Stability Design of Grid-Connected DC Distribution Power Systems

Impedance Specifications for Stability Design of Grid-Connected DC Distribution Power Systems

Magnetic characterisation of ferromagnetic material

In magnetic and electromagnetic non-destructive testing, the physical properties of the material are often not well known or completely unknown. The design of the non-destructive testing systems that provide the magnetisation is often oversized in order to get enough magnetic saturation (e.g. in magnetic flux leakage method or in magnetoscopy method). An improvement of the device performances, expressed usually by the signal to noise ratio, can be obtained only when the designer of the device well knows the material characteristic in terms of magnetic curve, the curve that links the magnetic field strengths to the magnetic flux density. A good device must be able to saturate the material sample under test but not to overcame determinate values. In fact, when the magnetisation is low, the leakage of the flux is negligible, while when the magnetisation is too strong the material tends to be like air and the leakage flux is negligible too. The experimental characterisation is derived from the technique adopted for the testing of soft magnetic material adopted in electrical machines or electromechanical actuators. In the present paper will be presented some material characterisation useful for the non-destructive testing of railway track, metallic ropes or reinforcement iron.

Optimizing MEP Design in Pharmaceutical Cleanroom with the Integration of 2D To 7D in BIM

Abstract: This paper examines the optimization of pharmaceutical cleanroom design using 2D to 7D Modelling in Building Information Modelling (BIM). The goal is to enhance the reliability, different methods, statistical data, and performance of pharmaceutical production plants by effectively allocating components within design constraints. Mathematical optimization techniques improve facility design, ensuring robustness and operational efficiency. The study proposes a reliable optimal design for air-conditioning systems in pharmaceutical cleanrooms, considering uncertainties in design parameters and operational strategies. Resilient cleanroom systems are developed, and adaptable to various conditions while maintaining high performance standards. Additionally, the research explores the application of experimental design methodologies in optimizing drug delivery systems, such as factorial and etc, to enhance the quality and efficiency of pharmaceutical products and processes.

Hydrogen Production using PEM Electrolyzer

Abstract: This paper presents a simulation study of alkaline electrolysis for H2 production using Aspen Plus. The simulation model incorporates reactor, separators, mixer, and heat exchanger units to accurately represent the AWE process. The model is designed to evaluate the performance of an AWE system under different operating conditions and aims to achieve a reference H2 production rate of 0.179663 kg/hr. The simulation results demonstrate that the AWE system can successfully produce H2 at the specified rate. The model provides a detailed analysis of the system's behavior and H2 production rate, under varying operating conditions. The findings of this study provide valuable insights into optimizing the design and operation of AWE systems for large-scale H2 production

Design and Development of LM24 plate Casting using Solid Cast Simulation Technique

Abstract: This research deals with the elimination of defects in aluminium alloy castings and enhancement in the casting yield and quality. The main intention of the work is to improve the quality of a cast component using Computer Aided Casting Simulation Software. SOLID Cast simulation software is used for simulating the solidification process of casting and visualizing outputs showing possible problematic areas or defects which may occur in the cast product. Plate Castings of aluminium alloy - LM 24 are produced with different designs of gating systems and tested for defects like porosity using Archimedes immersion Technique and also Radiographic testing is used to check the quality of the castings. The produced castings are observed to be sound, and the results obtained are in agreement with the simulation results. Hence it is verified that solidification simulation helps in improving the quality of castings without any shop-floor trails. Casting yield and percentage porosity values are determined for 12 castings produced with different gating systems. The best results are observed to be produced by the castings having a 1-Ingate system in horizontal or lateral positions.

Avionics System Design using MBSE Methodology

Abstract: The West Air Sweden Flight 294 serves as a reminder of tragic crashes of aircraftdue to Avionics System failure. Due to malfunction of the Inertial Reference Unit (IRU), the aircraft lost its control resulting in tragic loss of life of the peopleon board. The Avionics System is a complex set of instruments, logical and physical links which must comply with the guidelines of Dob178c. The design of the system is complicated. This paper aims to understand the behavior of the Avionics System using the state-of-the-art Model Based System Engineering (MBSE) technology. This includes the two widely used tools – Capella and Simulink. We aim to understand the dynamic nature of avionics through these tools. Model Based System Engineering can be specifically beneficial because it will help the engineers to detect the flaws in the avionics system much earlier. This will potentially contribute to helping to prevent aircraft crashes due to avionics system failure. The idea of model-based system engineering includes the concept of taking a model as a reference to systematically solve the complex designs of any engineering stage. Before the concept of Model Based Systems Engineering came to be, Documents Based Systems Engineering was the trend in the system engineering department. However, it would take a lot of time, effort and accuracy to correctly pinpoint the information and accordingly design the system from a bunch of documents. MBSE, however, eases such kind of trouble by providing a model as a reference for the systems design

BlockEdge: Building Bridges to Safe and Efficient Distributed Systems

Abstract: In the ever-evolving landscape of distributed systems, ensuring safety, efficiency, and scalability remains a paramount challenge. BlockEdge emerges as a pioneering framework designed to address these critical issues by leveraging the principles of blockchain technology and advanced consensus mechanisms. This abstract outlines the key features, innovations, and potential impacts of BlockEdge on the realm of distributed computing. BlockEdge integrates blockchain's immutable ledger properties with a novel consensus algorithm tailored for distributed systems. Unlike traditional blockchain applications that prioritize decentralization for financial transactions, BlockEdge focuses on enhancing the performance and reliability of distributed applications. The framework employs a hybrid consensus model that combines Byzantine Fault Tolerance (BFT) with Proof-of-Stake (PoS), optimizing both security and energy efficiency. A standout feature of BlockEdge is its modular architecture, which allows seamless interoperability between different types of distributed networks. This modularity facilitates the integration of various consensus protocols, catering to the specific needs of diverse applications, from IoT networks to large-scale data processing systems. By enabling secure and efficient cross-chain communication, BlockEdge effectively mitigates the silo effect prevalent in current distributed system designs.

Innovative fertilizers with added plant extracts in the cultivation of Valeriana officinalis and Raphanus sativus and in the control of Botrytis and powdery mildew

Research objective: The main objective of this article is to report the results obtained from the use of innovative fertilisers with added plant extracts in agriculture. In particular, this article will deal with two important topics: i) study of the effect of innovative fertilisers on the biomass of vegetable plants; ii) possible control on mortality due to diseases such as Botrytis and powdery mildew. The information reported in this research work can support the design of cultivation systems in which agricultural sustainability is fundamental due to the presence of plant extracts as an alternative to synthetic plant protection products. Materials and Methods: The plants were grown in pots under controlled conditions; 30 seedlings per thesis, divided into 3 replications of 10 plants each, were planted in early January 2024. The plants used in the trial were Valeriana officinalis L. and Raphanus sativus. The five experimental groups in cultivation were: i) group control, irrigated with water and previously fertilised substrate; ii) group with Aktigen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iii) group with Lifegen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iv) group with QI-gen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); v) Group with Ecklonia maxima (EK): (peat 70% + pumice 20%), irrigated with water and previously fertilised substrate, (3 ml per plant once a week). On 5 May 2024, plant height, number of leaves, primary root length (mm), biomass of the aerial and root system, and number of dead plants (Botrytis and powdery mildew) were recorded. Results and Discussion: The experiment showed that the use of innovative fertilisers enriched with plant extracts can indeed significantly improve the vegetative and root growth of Valeriana officinalis L. and Raphanus sativus. All treatments showed a significant improvement over the untreated control and the commercial Ecklonia maxima treatment for the agronomic parameters analysed, but the Qi-gen treatment was significantly the best for increasing vegetative and root biomass. Improvements were also found in plant height, leaf number and root length. The trial also revealed the significant effect on Botrytis control of the product Aktigen and on powdery mildew of the product Lifegen, in fact they reduced the mortality of Valeriana officinalis and Raphanus sativus seedlings. Conclusions: A number of scientific studies have shown that the application of biofertilizers can improve plant growth, productivity, quality, and tolerance to biotic and abiotic stresses. Because of their multiple properties, they have become increasingly important as advanced agricultural techniques in global agriculture. This type of product, which includes natural substances, will contribute significantly to ecologically and economically sustainable agricultural production systems in the coming years, as well as serving as the foundation for large-scale sustainable agriculture in the future.

What distance learning students want from an AI Digital Assistant

With the release of Generative AI systems such as ChatGPT, an increasing interest in using Artificial Intelligence (AI) has been observed across domains, including higher education. While emerging statistics show the popularity of using AI amongst undergraduate students, little is yet known about students’ perceptions regarding AI including self-reported benefits and concerns from their actual usage, in particular in distance learning contexts. Using a two-step, mixed-methods approach, we examined the perceptions of ten online and distance learning students from diverse disciplines regarding the design of a hypothetical AI Digital Assistant (AIDA). In the first step, we captured students’ perceptions via interviews, while the second step supported the triangulation of data by enabling students to share, compare, and contrast perceptions with those of peers. All participants agreed on the usefulness of such an AI tool while studying and reported benefits from using it for real-time assistance and query resolution, support for academic tasks, personalization and accessibility, together with emotional and social support. Students concerns related to the ethical and social implications of implementing AIDA, data privacy and data use, operational challenges, academic integrity and misuse, and the future of education. Implications for the design of AI-tailored systems are also discussed.

Human centered design of digital assistance systems for disabled people: trial and evaluation of the workshop program “friendlyAI@work”

ZusammenfassungDigitalen Assistenzsystemen wird das Potenzial zugeschrieben, Menschen mit Behinderungen eine selbstbestimmtere Teilhabe am Arbeitsleben zu ermöglichen. Eine solche potenzialerschließende Wirkung dieser Assistenztechnologien setzt in betrieblichen Anwendungskontexten fundiertes arbeitswissenschaftliches Gestaltungswissen für eine menschzentrierte Arbeitssystemgestaltung voraus. Das im Rahmen des Projektes „HUMAINE“ entwickelte Workshopkonzept „friendlyAI@work“ zielt darauf ab, betrieblichen Akteuren digitale Gestaltungskompetenz für eine humangerechte KI-Implementierung zu vermitteln. Es basiert auf Prinzipien des Aktionslernens, bei dem ein kollektiver, an Umsetzungsbeispielen ausgerichteter Kompetenzerwerb im Fokus steht. Im Beitrag berichten wir über erste Befunde zur Wirksamkeit des Workshopprogramms, die wir im Kontext der Einführung digitaler Assistenzsysteme in einer Werkstatt für Menschen mit Behinderung (WfbM) ermittelten. Die Evaluation des 18-monatigen Programms im Rahmen einer interventionsbasierten Fallstudie mit zwischen fünf und elf Teilnehmenden deutet auf positive Effekte sowohl im Hinblick auf einen Zuwachs individueller digitaler Gestaltungskompetenz wie auch der Fähigkeit zur humanzentrierten Arbeitssystemgestaltung hin. Darüber hinaus konnten im Rahmen des Programms Maßnahmen zur nachhaltigen Sicherung der erworbenen digitalen Gestaltungskompetenz umgesetzt werden (z. B. Einführung einer ganzheitlichen Gefährdungsbeurteilung bei der Planung technischer Systeme). Als wichtige Erfolgsfaktoren für den Lernerfolg erwies sich die cross-funktionale Zusammensetzung der Teilnehmenden, das an Praxisbeispielen ausgerichtete Lernkonzept und das agile Moderationsverfahren. Im Rahmen des auf Mixed-Method basierenden Evaluationsdesigns stellte sich darüber hinaus die Berücksichtigung individueller Lernvoraussetzungen in diversen Lerngruppen als kritischer Erfolgsfaktor heraus.Praktische Relevanz: Damit intelligente Technologien Menschen mit Behinderung bei der Arbeit sinnvoll unterstützen können, sind Kenntnisse über eine humanzentrierte Arbeitsgestaltung von hoher Bedeutung. Die digitalen Assistenten müssen so gestaltet sein, dass sie die persönlichen Ressourcen der Arbeitenden stärken und negative Beanspruchungsfolgen verhindert werden. Das Workshopprogramm „friendlyAI@work“ will Gestaltungsverantwortliche befähigen, digitale Assistenzsysteme in ihren Organisationen humanzentriert und nutzerfreundlich zu implementieren. Im Workshop werden Kenntnisse über die Funktionalitäten von Künstlicher Intelligenz und ihre Anwendung in Assistenzsystemen vermittelt. Darüber hinaus werden die Teilnehmenden an die Prinzipien humangerechter Technik- und Arbeitsgestaltung herangeführt und ihre Handlungskompetenz im Rahmen konkreter betrieblicher Umsetzungsbeispiele gefördert. Eine 18-monatige Erprobung des Workshopprogramms bei der Iserlohner Werkstätten gGmbH ergab eine gute Teilnehmendenakzeptanz und Erfolge bei der humangerechten Gestaltung ihrer Assistenz-Arbeitsplätze.

Ethical, legal and social implications (ELSI) of the design of AI systems: Systematization of the consideration through procedure models and guidelines

ZusammenfassungWesentliche Erfolgsfaktoren für die rechtlich angemessene und menschengerechte Nutzung von Künstlicher Intelligenz (KI) basieren auf der breiten Reflexion rechtlicher, ethischer und sozialer Aspekte (ELSA) im Rahmen organisatorischen Prozesse in Unternehmen und Institutionen. Künftig bedarf es aufgrund der Vielzahl zu erwartender KI-Vorhaben einer systematischen Betrachtung. Eine Möglichkeit dies zu Verankern sind Vorgehensmodelle inkl. Eines entsprechenden Referenzprozessmodells. Eine Ergänzung stellen Leitfäden dar. Ausgewählte Aspekte werden hierbei seit einigen Jahren in interdisziplinären und transdisziplinären Forschungsprojekten intensiv diskutiert und angewandt. Der folgende Beitrag ist im Rahmen des KARL-Projekt entstanden und erörtert relevante Bezugspunkte im Rahmen der Implementierung von KI in zukünftige Arbeitsumgebungen. Vor diesem Hintergrund wird die Frage bearbeitet, welche Herausforderungen Informatiker/-innen im Gestaltungsprozess selbst adressieren können und zu welchen Fragen weitere Akteur/-innen (Rechtswissenschaftler/-innen, Ethik-Expert/-innen sowie Expert/-innen der sozialen Technikgestaltung) einbezogen werden sollten. Insgesamt plädieren die Autor/-innen für einen prozessorientierten Ansatz, in dem unterschiedliche Aspekte der Technikgestaltung systematisch berücksichtigt werden.Praktische Relevanz Die Arbeitswissenschaft wird zunehmend mit Fragestellungen der Integration von KI in verschiedene Arbeitsprozesse konfrontiert. Die Betrachtung von ELSA ist eine Teilaufgabe in der Gestaltung und Reflektion dieser Entwicklung.

Sustainable Fishing Livelihoods: Exploring the Potential of Sail Technology Using Computational Fluid Dynamic in Traditional Fishing Boats

The potential of using sails and Computational Fluid Dynamics (CFD) to improve the sustainability of traditional fishing boats in the Maluku region. This study highlights the importance of cost-effectiveness and environmental sustainability in the fishing industry. This study shows that Computational Fluid Dynamics (CFD) is effective in simulating the thrust force generated by sails. Sails were used to generate thrust forces on conventional fishing vessels by implementing CFD methodology with three different models. Various sail shapes were incorporated into the modelling process to assess their impact on the thrust force. Subsequently, a comprehensive analysis was conducted to evaluate the sail thrust force under typical operating conditions, focusing specifically on the average speed of the vessel at 15 knots in the waters surrounding the Maluku Islands. The results reveal that sail model 1 has the highest thrust force, amounting to 240.2 N. Sail models 3 and 2 generate thrust forces of 238.9 N and 227.9 N, respectively. The fluid flow conditions around sail model 1 and screen model 2 provide valuable insights into how the sail interacts with the fluid environment to produce thrust. By understanding and optimizing these fluid dynamics, designers and engineers can enhance the performance of sail models and improve their efficiency in harnessing wind power for propulsion. This study highlights the importance of ship science and technology in the design of appropriate propulsion systems for traditional fishing vessels.

Integrated urban land cover analysis using deep learning and post‐classification correction

AbstractThe quantification of urban impervious area has important implications for the design and management of urban water and environmental infrastructure systems. This study proposes a deep learning model to classify 15‐cm aerial imagery of urban landscapes, coupled with a vector‐oriented post‐classification processing algorithm for automatically retrieving canopy‐covered impervious surfaces. In a case study in Corpus Christi, TX, deep learning classification covered an area of approximately 312 km2 (or 14.86 billion 0.15‐m pixels), and the post‐classification effort led to the retrieval of over 4 km2 (or 0.18 billion pixels) of additional impervious area. The results also suggest the underestimation of urban impervious area by existing methods that cannot consider the canopy‐covered impervious surfaces. By improving the identification and quantification of various impervious surfaces at the city scale, this study could directly benefit a variety of environmental and infrastructure management practices and enhance the reliability and accuracy of processed‐based models for urban hydrology and water infrastructure.

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

Self-assembly of discrete multi-chromophoric systems.

Self-assembly of chromophoric systems is a prerequisite to create well-ordered, processable nanomaterials with multiple functionalities. In the past two decades, the field of functional organic materials has primarily focused on systems featuring only one type of dye/π-conjugated unit. Consequently, many reports with mechanistic insights on the self-assembly of the dyes featuring different molecular packing have been reported. Subsequently, we have witnessed several attempts to organize the multi-chromophoric systems in solution and solid-state via different approaches using self-assembly as a tool. Incorporation of more than one dye is important in creating materials with tuneable optoelectronic properties. Consequently, self-assembly of more than one chromophoric systems have been investigated to some extent. This review aims to discuss the self-assembled materials derived from discrete π-conjugated systems comprising more than one dye units connected through covalent bonding (multi-chromophoric systems). Molecular design of various multi-chromophoric systems leading to the formation of crystals, liquid crystals and supramolecular polymers have been correlated with corresponding properties. We envisage that classification of self-assembled multi-chromophoric systems, with a note on tuneable optoelectronic properties, can provide a deeper understanding on the molecular design strategies, which is important in the fabrication of functional organic materials with optimum performances.

Internal temperature estimation for lithium-ion batteries through distributed equivalent circuit network model

Lithium-ion cells experience significant internal thermal gradients during operation, with a direct impact on their safety, performance, cost and lifetime. The estimation of the internal temperature of cells is therefore particularly important. In this work, a 3D distributed electro-thermal model for internal temperature estimation is developed for a cylindrical cell (LG M50T, NMC811). The model is parameterized and comprehensively validated against experimental data for 21700 cells, including direct core temperature measurements. Multiple types of electrical load are considered, including constant current discharge, pulse discharge, drive cycle and instant discharge/charge switching. The developed model is used to estimate core temperature based on surface temperature measurement. The predictions are shown to have good accuracy at relatively low computational cost. We show that the widely adopted two-node lumped thermal estimation model is increasingly inaccurate for more aggressive discharges, when thermal gradients become higher. Compared to the standard two-node model, the distributed equivalent circuit network model predicts the effects of detailed internal cell structure (electrode, current collector, metal can and tab) and distributed internal heat generation. The results are of immediate interest to cell manufacturers and battery pack designers, while the modelling and parameterization framework is a useful tool for energy storage systems design.

Flow-Induced Vibration Analysis by Simulating a High-Speed Train Pantograph

This paper investigates the aerodynamic behavior and dynamic characteristics of high-speed train pantographs under various operating conditions using advanced aerodynamic simulations and dynamic analyses. The simulations show significant fluctuations in aerodynamic loads during tunnel entry and exit, heavily influenced by train speed and pantograph position (raised/lowered). Modal simulations reveal distinct low-frequency vibrations in pantographs, significantly impacted by external aerodynamic forces. Importantly, the lowered position exposes the pantograph to upward aerodynamic forces, leading to increased bow-net contact force and off-line rate, ultimately compromising current collection stability. Both maximum contact force and off-line rate further increase with higher train speeds. To improve pantograph design, the paper proposes adjustments to the airbag’s equivalent spring stiffness and the bow head’s density. These modifications aim to mitigate contact force and enhance the stability and reliability of pantographs at high speeds. This research offers theoretical and practical insights, aiding in the design, optimization, and refinement of future pantograph systems.

Real-world waste dispersion modelling for benthic integrated multi-trophic aquaculture.

In real-world situations, marine fish farms accommodate multiple fish species and cohorts within the farm, leading to diverse farm layouts influenced by cage dimensions, configurations, and intricate arrangements. These cage management practices are essential to meet production demands, however, farm-level complexities can impact model predictions of waste deposition and benthic impact near fish cages. This is of particular importance when the cages are used for integrated multi-trophic aquaculture (IMTA) with benthic feeders, where this waste not only affects environmental conditions but also provides a potential food source. The Cage Aquaculture Particulate Output and Transport (CAPOT) model incorporated multiple species, cohorts, and cage arrangements to estimate waste distribution from a commercial fish farm in the Mediterranean between October 2018 and July 2019. This spreadsheet model estimated dispersion for individual fish cages using a grid resolution of 5 m x 5 m. The study categorized discrete production periods for each fish cage every month, aligning with intermittent changes in biomass and food inputs due to different cage management practices throughout production. This approach facilitated the use of detailed input data and enhanced model representativeness by considering variations in cage biomass, food types, settling velocities, and configurations. Model outputs, represented in contour plots, indicated higher deposition directly below fish cages that varied monthly throughout fish production cycles. Deposition footprints reflected changes in cage biomass, food inputs, and farm-level practices reflecting this real-world scenario where aquaculture does not follow a production continuum. Moreover, cohort dynamics and cage movements associated with the cage management practices of the fish farm influenced the quantity and fate of wastes distributed around fish cages, revealing variability in deposition footprints. Clearly, these findings have important implications for the design of benthic IMTA systems, with species such as sea cucumber and polychaetes. Variability in waste deposition creates challenges in identifying where the benthic organisms should be placed to allow optimal uptake of waste to meet their food requirements and increase survivability. Evidently, models have an important role to play and this study emphasizes the need for representative input data to describe actual food inputs, cage biomass changes, and management practices for more representative farm-scale modelling and essentially to improve particulate waste management. To effectively mitigate benthic impacts through IMTA, models must quantify and resolve particulate waste distribution and impact around fish farms to maintain a balanced system with net removal of wastes. Resolving farm-level complexities provides vital information about the variability of food availability and quality for extractive organisms that helps improve recycling of organic wastes in integrated systems, demanding a more representative modelling approach.

Empathetic and Emotive Design Heuristics.

The design of user interfaces and systems that promote positive emotional interaction and reaction from end users is becoming a critical area in the design of applications and systems for use by the general population. In this paper we describe our work in the creation of a set of empathetic design heuristics that were developed from examination of the literature in this area within the context of healthcare user interface design. The heuristics and their potential application are explored.