Advanced Simulation Research Articles

Advancing radiology education for medical students: leveraging digital tools and resources.

This study evaluates diverse educational resources to address the gaps in diagnostic radiology education for medical students, aiming to identify tools that enhance theoretical knowledge and practical diagnostic skills. Employing a multi-faceted review, we analyzed digital platforms, academic databases, and social media for resources beneficial to medical students in radiology, assessing their accessibility, content quality, and educational value. Our investigation uncovered a broad spectrum of resources, from foundational platforms to advanced simulation tools, varying in their approach to teaching radiology. Traditional resources provide essential theoretical knowledge, while digital tools, including interactive case studies and multimedia content, offer immersive learning experiences. Notably, resources integrating machine learning and social media facilitate dynamic, peer-to-peer learning and up-to-date case discussions. Despite the minimal current focus on VR, its role in enhancing interactive learning is notable. The diversity in educational tools highlights the evolving nature of radiology education, reflecting a shift towards more engaging and practical learning methodologies. Identifying and integrating a variety of educational resources into radiology education can significantly enhance learning outcomes for medical students, preparing them for the complexities of modern diagnostic radiology with a well-rounded educational approach.

Into the Groove: A Multitechnique Insight into the DNA–Vemurafenib Interaction

This study explores the interaction between Vemurafenib (VEM), a potent BRAF inhibitor, and calf thymus DNA (ctDNA) using a comprehensive array of biophysical and computational techniques. The primary objective is to understand the potential off-target effects of VEM on DNA, given its established role in melanoma therapy targeting the BRAF V600E mutation. The investigation employed methods such as ultraviolet–visible absorption spectroscopy, steady-state fluorescence, circular dichroism, isothermal titration calorimetry, and advanced molecular dynamics simulations. The results indicate that VEM interacts with DNA primarily through a minor groove-binding mechanism, causing minimal structural disruption to the DNA double helix. Viscosity measurements and melting temperature analyses further confirmed this non-intercalative mode of binding. Calorimetry data revealed an exothermic, thermodynamically favorable interaction between VEM and ctDNA, driven by both enthalpic and entropic factors. Finally, computer simulations identified the most probable binding site and mode of VEM within the minor groove of the nucleic acid, providing a molecular basis for the experimental findings.

Artificial intelligence techniques for dynamic security assessments - a survey

The increasing uptake of converter-interfaced generation (CIG) is changing power system dynamics, rendering them extremely dependent on fast and complex control systems. Regularly assessing the stability of these systems across a wide range of operating conditions is thus a critical task for ensuring secure operation. However, the simultaneous simulation of both fast and slow (electromechanical) phenomena, along with an increased number of critical operating conditions, pushes traditional dynamic security assessments (DSA) to their limits. While DSA has served its purpose well, it will not be tenable in future electricity systems with thousands of power electronic devices at different voltage levels on the grid. Therefore, reducing both human and computational efforts required for stability studies is more critical than ever. In response to these challenges, several advanced simulation techniques leveraging artificial intelligence (AI) have been proposed in recent years. AI techniques can handle the increased uncertainty and complexity of power systems by capturing the non-linear relationships between the system’s operational conditions and their stability without solving the set of algebraic-differential equations that model the system. Once these relationships are established, system stability can be promptly and accurately evaluated for a wide range of scenarios. While hundreds of research articles confirm that AI techniques are paving the way for fast stability assessments, many questions and issues must still be addressed, especially regarding the pertinence of studying specific types of stability with the existing AI-based methods and their application in real-world scenarios. In this context, this article presents a comprehensive review of AI-based techniques for stability assessments in power systems. Different AI technical implementations, such as learning algorithms and the generation and treatment of input data, are widely discussed and contextualized. Their practical applications, considering the type of stability, system under study, and type of applications, are also addressed. We review the ongoing research efforts and the AI-based techniques put forward thus far for DSA, contextualizing and interrelating them. We also discuss the advantages, limitations, challenges, and future trends of AI techniques for stability studies.

The Countoscope: Measuring Self and Collective Dynamics without Trajectories

Driven by physical questions pertaining to quantifying particle dynamics, microscopy can now resolve complex systems at the single-particle level, from cellular organisms to individual ions. Yet, available analysis techniques face challenges reconstructing trajectories in dense and heterogeneous systems where accurately labeling particles is difficult. Furthermore, the inescapable finite field of view of experiments hinders the measurement of collective effects. Inspired by Smoluchowski, we introduce a broadly applicable analysis technique that probes dynamics of interacting particle suspensions based on a remarkably simple principle: counting particles in finite observation boxes. Using colloidal experiments, advanced simulations, and theory, we first demonstrate that statistical properties of fluctuating counts can be used to determine self-diffusion coefficients, so alleviating the hurdles associated with trajectory reconstruction. We also provide a recipe for practically extracting the diffusion coefficient from experimental data at variable particle densities, which is sensitive to steric and hydrodynamic interactions. Remarkably, by increasing the observation box size, counting naturally enables the study of collective dynamics in dense suspensions. Using our novel analysis of particle counts, we uncover a surprising enhancement of collective behavior due to hydrodynamics as well as a new length scale which can be connected with hyperuniform structure. Our counting framework, the “countoscope,” thus enables efficient measurements of self and collective dynamics in dense suspensions and opens the way to quantifying dynamics and identifying novel physical mechanisms in diverse complex systems where single particles can be resolved. Published by the American Physical Society 2024

Clinical Simulation Program for the Training of Health Profession Residents in Confidentiality and the Use of Social Networks.

In the transition to a professional learning environment, healthcare professionals in their first year of specialized postgraduate clinical training (known as residents in Spain) are suddenly required to handle confidential information with little or no prior training in the safe and appropriate use of digital media with respect to confidentiality issues. The aims of this study were: (1) to explore the usefulness of an advanced clinical simulation program for educating residents from different healthcare disciplines about confidentiality and the dissemination of clinical data or patient images; (2) to explore the use of social networks in healthcare settings; and (3) to explore participants' knowledge and attitudes on current regulations regarding confidentiality, image dissemination, and the use of social networks; Methods: This was a cross-sectional study. Data were collected from all 49 first-year residents of different health professions at a Spanish hospital between June and August 2022. High-fidelity clinical simulation sessions designed to address confidentiality and health information dissemination issues in hospital settings, including the use of social networks, were developed and implemented. Data were assessed using a 12-item ad hoc questionnaire on confidentiality and the use of social media in the healthcare setting. Descriptive of general data and chi-square test or Fisher's exact test were performed using the SPSS 25.0 software; Results: All the participants reported using the messaging application WhatsApp regularly during their working day. A total of 20.4% of the participants stated that they had taken photos of clinical data (radiographs, analyses, etc.) without permission, with 40.8% claiming that they were unaware of the legal consequences of improper access to clinical records. After the course, the participants reported intending to modify their behavior when sharing patient data without their consent and with respect to how patients are informed; Conclusions: The use of advanced simulation in the training of interprofessional teams of residents is as an effective tool for initiating attitudinal change and increasing knowledge related to patient privacy and confidentiality. Further follow-up studies are needed to see how these attitudes are incorporated into clinical practice.

Integration of Geological Model and Numerical Simulation Technique to Characterize the Remaining Oil of Fractured Biogenic Limestone Reservoirs

AbstractFine geological modeling leads to accurate reservoirs numerical simulations. Fractured biogenic limestone has abundant storage spaces and flow paths to accumulate oil and gas. The complexity and diversity of fractured biogenic limestone also lead to challenges in accurately characterizing its pore volume and remaining oil. This investigation aimed to enhance the understanding of fractured biotite reservoir properties via geological modeling. Numerical simulations were used to characterize the remaining oil during the late stage of field development. Considering the differences in porosity and permeability between fractures and matrix, a facies-controlled stochastic modeling technique was used to establish a dual-porosity and dual-permeability (DPDP) model for numerical simulation. Core information, logging data, and multiple seismic attributes were combined to guide low-level sequence fault interpretation for tectonic refinement. Based on classified seismic inversion, sedimentary phases were reconstructed. A discrete fracture network (DFN) model was obtained based on fracture occurrences and density models. The optimized discrete adjoint (ODA) algorithm was utilized to calibrate model parameters. The findings revealed that dense tectonic fractures develop in thick biogenic limestone areas. Combined with advanced reservoir simulation technology, these findings suggest that areas of thicker biogenic limestone were consistent with areas of higher fracture matrix conductivity multipliers. The remaining oil distribution patterns were investigated, and to deploy new wells was guided. Therefore, it is essential to better understand the tectonic characteristics of fractured biogenic limestone reservoirs and their remaining oil distribution patterns by integrating multiple sources of information and mastering advanced reservoir simulation technology for oilfield development.

Digital-assisted diagnosis and orthodontic management of an impacted mandibular lateral incisor: a case report

BackgroundThe impaction of mandibular lateral incisors presents significant aesthetic and functional challenges in orthodontics, including Bolton ratio discrepancies and anterior occlusal anomalies. The increasing preference for nonextraction treatment further complicates space management within the dental arch. However, the advent of digital-assisted orthodontic technologies, particularly advanced digital simulations, has revolutionized the precision and effectiveness of diagnosis and treatment planning. These technologies enable clinicians to strategically leverage natural jaw development and create the necessary space for the alignment of impacted teeth without resorting to extraction.Case presentationThis case report details the treatment of a 12-year-old male with an impacted mandibular lateral incisor, which resulted in both aesthetic concerns and functional impairments, alongside Class II malocclusion. By employing a digital-assisted diagnostic approach, including comprehensive digital simulations, we meticulously evaluated the feasibility of a nonextraction treatment plan. The strategy centred on harnessing the patient’s mandibular growth potential to expand the available space naturally. The treatment involved surgical exposure of the impacted tooth, followed by precise orthodontic traction guided by continuous digital monitoring. The integration of digital tools throughout the treatment process was crucial in achieving successful eruption and alignment of the impacted tooth, thus restoring optimal aesthetics and function without the need for extraction.ConclusionThis case highlights the transformative impact of digital-assisted technologies in the management of complex orthodontic cases, such as impacted mandibular lateral incisors. The successful integration of these advanced tools with a nonextraction treatment approach underscores their potential to significantly enhance clinical outcomes. Digital technologies not only improve the accuracy and effectiveness of treatment but also facilitate a multidisciplinary approach that elevates the standard of patient care in addressing complex orthodontic challenges.

Building Biodiversity Digital Twins

A digital twin is a replica of a system, process, or object realized as a digital version. Digital twins are widespread in engineering and aim to can help many kinds of organizations simulate real situations and their outcomes, ultimately allowing them to make better decisions. Digital twins combine cutting-edge modelling approaches with powers of supercomputers with data streams. These data resources, coming through the research infrastructures, depend on data standardization, efficient data models and workflows, and on FAIRness (Findability, Accessibility, Interoperability, Reusability) of these elements. Digital twin concepts have been applied to biodiversity data since 2022, most notably through the Biodiversity Digital Twin project. The outcomes of dynamic modeling based on the biodiversity data (which availability changes in volumes and quality) against the globally available changing environmental and human impact data are expected to form the basis for management of natural resources and aims to support biodiversity recovery. The BioDT consortium brings together a dynamic team of experts in biodiversity data and standards, high performance computing, and FAIR data to realize the first set of biodiversity Digital Twin prototypes. Biodiversity evidence generated, standardized and shared from collections, systematic and long term surveys, eDNA and metabaroding, citizen science and other communities representing a range of biodiversity evidence types, can to be applied in the dynamic and interactive modelling solutions, known as digital tiwins. The Biodiversity Digital Twin project (and the twin approach in general) offers advanced simulation and prediction models to tackle global biodiversity challenges. This project is designed to address biodiversity dynamics through a set of use cases, providing insights and tools for conservation and restoration efforts. The BioDT project has revealed similarities and differences of applying Biodiversity Information Standards (TDWG) thinking and principles of data standardization to the communities with different levels of familiarity with standards and FAIR principles. The presentation at SPNCH-TDWG 2024 covered the process of building biodiversity digital twins by the second project year and exposed the work along the gradient of data intensity, of data FAIRness, and of complience to the international data standards. The details of ten BioDT project stories are covered in the special issue of the Pensoft RIO journal on BioDT project (Afsar et al. 2024, Chala et al. 2024, Frøslev et al. 2024, Ingenloff et al. 2024, Groeneveld et al. 2024, Khan et al. 2024, Mikryukov et al. 2024, Ovaskainen et al. 2024, Rolph et al. 2024, Taubert et al. 2024).

Mechanisms of Controllable Growth and Ohmic Contact of Two-Dimensional Molybdenum Disulfide: Insight from Atomistic Simulations.

ConspectusTwo-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs), in particular molybdenum disulfide (MoS2), have recently attracted huge interest due to their proper bandgap, high mobility at 2D limit, and easy-to-integrate planar structure, which are very promising for extending Moore's law in postsilicon electronics technology. Great effort has been devoted toward such a goal since the demonstration of protype MoS2 devices with high room-temperature on/off current ratios, ultralow standby power consumption, and atomic level scaling capacity down to sub-1-nm technology node. However, there are still several key challenges that need to be addressed prior to the real application of MoS2-based electronics technology. The controllable growth of wafer-scale single-crystal MoS2 on industry-compatible insulating substrates is the prerequisite of application while the currently synthesized MoS2 films mostly are polycrystalline with limited sizes of single-crystal domains and may involve metal substrates. The precise layer-control is also very important for MoS2 growth since its electronic properties are layer-dependent, whereas the layer-by-layer growth of multilayer MoS2 dominated by the van der Waals (vdW) epitaxy leads to poor thickness uniformity and noncontinuously distributed domains. High density up to 1013 cm-2 of sulfur vacancies (SVs) in grown MoS2 can cause unfavorable carrier scatting and electronic properties variations and will inevitably disturb the device performance. The dangling-bond-free surface of MoS2 gives rise to an inherent vdW gap at metal-semiconductor (M-S) contact, which leads to high electrical resistance and poor current-delivery capability at the contact interface and thereby substantially limits the performances of MoS2 devices.In this Account, we briefly review recent experimental and theoretical attempts for addressing the aforementioned challenges and present our own insights from atomistic simulations. We theoretically revealed the vital role of substrate steps for guiding unidirectional nucleation of monolayer MoS2 and uniform nucleation and edge-aligned growth of bilayer MoS2 by advanced simulations. The established thermodynamic mechanisms have successfully directed the experimental works on the controllable growth of 2 in. single-crystal monolayer and centimeter-scale uniform bilayer MoS2. The postgrowth repair mechanism of SV defect in MoS2 via thiol chemistry treatment has been theoretically explored with the consideration of side reaction of surface functionalization to help experimentally reduce SV defect density by 75%. Beyond the atomic level understanding, theoretical simulations proposed the electronic states hybridization mechanism across the semimetal-MoS2 vdW interface, thereby guiding experimental effort for realizing Ohmic contact at the MoS2-Sb(0112) vdW interface with record-low contact resistance.These advances provide a sound basis with an atomic-level understanding for addressing the related issues. However, there are still notable gaps in terms of system size and time scale of dynamics between atomistic simulations and experimental observations for the studies of MoS2 growth and interfaces. The combination of multiscale simulations and artificial intelligence technology is expected to narrow these gaps and provide a more insightful understanding of the controllable growth and interfacial properties modulation of MoS2. We conclude the Account with the standing challenges and outlook on future research directions from the theoretical perspective.

How to optimize government R&D budget allocation? A review of recent studies and research gaps

Purpose Research and Development (R&D) activities are important for technological innovation and present opportunities for entrepreneurship. These activities depend on the flow of funding. This paper aims to review approaches used in R&D project selection and budget allocation. Design/methodology/approach This study conducts a systematic review, examining the content of 60 relevant papers (spanning 2000–2022) concerning public R&D budget allocation. The analysis focuses on allocation methodology, R&D output evaluation, budget allocation efficiency and the management of uncertainty in the allocation process. Findings The systematic review reveals different methods proposed for allocating government R&D budgets. These methods range from classical optimization, multi-criteria analysis and hierarchical analysis to techniques such as balanced scorecard, data envelopment analysis and analytic hierarchy process, including fuzzy approaches. Recent trends indicate an increase in the use of advanced optimization, integration and simulation algorithms. Performance indicators for reflecting R&D project outputs or goals can be categorized into four main groups: output (e.g. publications, patents, graduates), outcome, productivity (e.g. citations, patent references, articles and patents per capita) and sector-specific metrics. Practical implications Future research directions in government R&D budget allocation may include optimizing allocation to maximize social, economic and political benefits, developing ranking models, decision-making frameworks, simulations and evaluations of factors influencing allocation type and strategy. Additionally, there is a growing interest in novel budget allocation algorithms leveraging artificial intelligence and self-adjusting meta-heuristic algorithms. Originality/value The systematic review showed that some important research gaps in (government) R&D budget allocation could be considered in future studies; for example, long-term social, economic and political benefits in budget allocation optimization models, comprehensiveness of allocating government R&D budgets to universities, higher education and research institutes, R&D budget allocation to strategic technology development, e.g. renewable energy sector, supply chain issues and renewable energy value chain; new budget allocation algorithms based on artificial intelligence and self-adjusting meta-heuristic algorithms; methods for optimizing the structures of government budget allocation to R&D, considering executive and regulatory conflicts.

The Method for Obtaining Shot Cloud Time Span and Range Dependence

When studying the behavior of a shot cloud in space, a variety of information and measurement systems can be applied, for example, based on light screens (photoelectronic blocking devices of a small ballistic measuring installation consisting of a linear emitter and an optical sensor based on a photodiode). To study the process of shot cloud movement in space and to assess its parameters (for example, length at a given range from the muzzle) correctly, it is advisable to have a simulation model of the optical sensor signal when the light screen is crossed by a shot cloud. Taking into account previous studies, it is necessary to know the magnitude of the scale parameter in the Rayleigh distribution describing the shot cloud in the direction of firing in time in order to obtain a similar model at some distance from the muzzle. A method that allows obtaining function of dependence of the mentioned scale parameter and the distance from the muzzle and based on real data from several optical sensors of light screens installed on the shooting track is proposed. The example of application the proposed method to obtain similar functions based on the results of processing optical sensor signals obtained in real experiments for cartridges loaded with three different shot types is given. The obtained dependences were approximated by polynomials of the first and second degree using the least squares method, and the error was estimated for various types of cartridges. Based on the obtained results, specific recommendations for the practical application of the developed method are proposed. The estimation of the confidence interval width for the expectation function of the shot cloud time span is performed. The ways of creating advanced signal simulation models from optical sensors of light screens when shooting with shot are outlined.

A Comparative Study of Traditional and Computer-aided Surgical Simulation Guides in Orthognathic Correction of Bimaxillary Protrusion.

To compare the efficacy of traditional occlusal guides with computer-aided surgical simulation (CASS) guides in enhancing postoperative outcomes for patients with bimaxillary protrusion. This retrospective study evaluated 34 patients undergoing anterior maxillary and mandibular subapical osteotomy at the Plastic Surgery Hospital of the Chinese Academy of Medical Sciences. Fourteen patients were treated using traditional occlusal guides, whereas 20 patients were treated with CASS guides (median age 28.6 years, median follow-up 259 days). Pre and postoperative cephalometric indicators were measured using cephalometric software. Data analysis was conducted using SPSS 14.0, with significant differences determined at P < 0.05. All 34 patients experienced primary healing without complications. Follow-up indicated significant improvements in key cephalometric measurements in the CASS group compared with the traditional group, including mandibular position (SNB angle, P < 0.001), jaw relationship (ANB angle, P < 0.001), facial angle (FH-NPo, P = 0.002), and condyle-to-sella distance (Co-S, P = 0.024). The CASS group also showed better aesthetic outcomes, with significant reductions in overjet (P = 0.012), overbite (P = 0.001), and improved alignment of upper and lower incisors (U1-L1 angle, P = 0.031). CASS-guided surgery offers a superior alternative to traditional methods for treating bimaxillary protrusion, providing more precise and aesthetically pleasing results. This study highlights the significant advantages of using advanced digital simulation and 3-dimensional printing technologies in orthognathic surgery.

Study on fracture behaviour of pipeline girth welds based on curved wide plate specimens: Experimental and numerical analysis

Understanding the fracture characteristics and strain capacity of pipelines with girth welds under external loads is crucial for evaluating pipeline safety. The use of curved wide plate (CWP) specimens closely resembling full-scale (FS) pipelines in geometry provides a more realistic representation of crack tip constraint states compared to small-size fracture toughness test specimens in laboratory settings. This study aims to investigate the ductile fracture characteristics of center cracks on the outer surface of girth welds in high-grade steel pipelines under external loads through large-scale CWP tensile tests and advanced numerical simulations. Tensile tests were conducted on CWP specimens using a kiloton tensile testing machine, with double crack opening displacement (COD) gauge monitoring crack mouth opening displacement (CMOD), and high-precision displacement sensors and strain gauges tracking deformation and strains at various positions. The study yielded significant experimental results, and a finite element (FE) model of the CWP was developed using the nonlinear finite element method (FEM) to validate the experimental data against simulation results. The FE model was then used to investigate the influence of material properties on crack propagation resistance and driving force curves. A method for determining the ultimate tensile strain capacity (UTSC) of pipelines based on actual material fracture toughness was proposed. This research contributes valuable experimental data for further exploration of fracture behaviour in large-scale pipeline girth welds and offers insights for safety evaluations of such welds.

Circularly Polarized High-Harmonic Beams Carrying Self-Torque or Time-Dependent Orbital Angular Momentum.

In the rapidly evolving field of structured light, self-torque has been recently defined as an intrinsic property of light beams carrying time-dependent orbital angular momentum. In particular, extreme-ultraviolet (EUV) beams with self-torque, exhibiting a topological charge that continuously varies on the subfemtosecond time scale, are naturally produced in high-order harmonic generation (HHG) when driven by two time-delayed intense infrared vortex beams with different topological charges. Until now, the polarization state of such EUV beams carrying self-torque has been restricted to linear states due to the drastic reduction in the harmonic up-conversion efficiency with increasing the ellipticity of the driving field. In this work, we theoretically demonstrate how to control the polarization state of EUV beams carrying self-torque, from linear to circular. The extremely high sensitivity of HHG to the properties of the driving beam allows us to propose two different driving schemes to circumvent the current limitations to manipulate the polarization state of EUV beams with self-torque. Our advanced numerical simulations are complemented with the derivation of selection rules of angular momentum conservation, which enable precise tunability over the angular momentum properties of the harmonics with self-torque. The resulting high-order harmonic emission, carrying time-dependent orbital angular momentum with a custom polarization state, can expand the applications of ultrafast light-matter interactions, particularly in areas where dichroic or chiral properties are crucial, such as magnetic materials or chiral molecules.

A novel technique to detect and mitigate harmonic during islanding in grid connected PV system

The integration of photovoltaic (PV) systems into the power grid has become increasingly prevalent, providing sustainable and renewable energy solutions. However, the occurrence of islanding events, where a portion of the PV system operates independently from the main grid, presents challenges in maintaining power quality. This research paper investigates the harmonic distortions during islanding in grid-connected PV systems and proposes effective mitigation strategies. The study employs advanced simulation tools to analyse the dynamic behavior of the PV system during islanding scenarios, focusing on the occurrence and characteristics of harmonics. A detailed investigation into the root causes of harmonic distortions is conducted, considering factors such as grid fluctuations, inverter operation, and system impedance. Based on the findings, this paper introduces novel harmonic mitigation techniques tailored for islanding conditions. These techniques encompass advanced control algorithms, filter designs, and modulation strategies to suppress harmonics and enhance the overall system performance during islanded operation. Comparative assessments of different mitigation approaches are presented, evaluating their effectiveness in minimizing harmonic distortions and maintaining grid code compliance. The research contributes valuable insights to the field of grid-connected PV systems, offering a comprehensive understanding of harmonic issues during islanding events and proposing innovative solutions for their mitigation. The outcomes of this study are crucial for advancing the reliability, stability, and power quality of PV systems that are connected to the grid, which makes it possible for green energy sources to be added to the grid without any problems.

Optimizing educational environments: microclimate analysis and energy efficiency through courtyard orientation in UAE schools

Sustainable school design is becoming increasingly important worldwide, particularly in the UAE, where schools are significant energy consumers. This study explores the impact of courtyard orientation on microclimate and energy consumption in UAE schools, utilizing a standardized template applied across 70 existing schools. By employing advanced simulation tools, ENVI-met and IES-ve software, the research provides a comprehensive analysis of air temperature and energy use related to different courtyard orientations, specifically on key dates of September 21st and March 21st, representing seasonal variations. The results indicate that North-facing courtyards consistently provide cooler microclimates compared to other orientations. Specifically, North-facing courtyards showed temperature reductions of 1.31°C in September and 1.9°C in March compared to the least favorable orientations. This orientation recorded the lowest average mass temperatures of 29.36°C in September and 25.13°C in March, surpassing the West-facing orientation by 0.39°C and 0.45°C, respectively. The primary factor for this improvement is the reduced solar radiation exposure on East-West aligned courtyards, which significantly lowers the heat gain. Additionally, the study assessed Physiologically Equivalent Temperature (PET) readings and cooling demands, both of which were found to be lower in North-facing courtyards. Cooling load reductions varied between 1% and 4%, depending on the day, further emphasizing the efficiency of this orientation. These findings suggest that strategic courtyard orientation is a critical design consideration for enhancing thermal comfort and energy efficiency in school buildings. The implications of this research are significant for sustainable design and construction practices. By highlighting the benefits of optimal courtyard orientation, this study offers practical solutions for reducing energy consumption and improving the indoor and outdoor thermal environments of schools. These insights contribute to the broader goal of developing greener, more sustainable educational facilities, particularly in hot climates like the UAE. This research not only informs architects and urban planners but also supports policymakers in implementing effective sustainability strategies in the educational sector.

Transitioning trends into action: A simulation-based Digital Twin architecture for enhanced strategic and operational decision-making

In the dynamic realm of nowadays manufacturing, integrating digital technologies has become paramount for enhancing operational efficiency and decision-making processes. This article presents a novel system architecture that integrates a Simulation-based Digital Twin (DT) with emerging trends in manufacturing to enhance decision-making, accompanied by a detailed technical approach encompassing protocols and technologies for each component. The DT leverages advanced simulation techniques to model, monitor, and optimize production processes in real time, facilitating both strategic and operational decision-making. Complementing the DT, trending technologies such as artificial intelligence, additive manufacturing, collaborative robots, autonomous vehicles, and connectivity advancements are strategically integrated to enhance operational efficiency and facilitate the adoption of the Manufacturing as a Service (MaaS) paradigm. A case study within a MaaS supplier context, deployed in an industrial laboratory with advanced robotic systems, demonstrates the practical application of optimizing dynamic job-shop configurations using Simulation-based DT, showcasing strategies to improve operational efficiency and resource utilization. The results of the industrial experiment were highly encouraging, underscoring the potential for extension to more intricate industrial systems, with particular emphasis on incorporating sustainability and remanufacturing principles.

Unveiling the Future of Safety: Cutting-Edge Simulation Testing of e-Kart Bumpers

Abstract This research project proves the importance of simulation technology in developing safe and efficient components for electric Go-Kart and how this approach could impact the future of automotive design and engineering. The development of electric Go-Kart present unique challenges in ensuring safety and performance, given the increasing demand for eco-friendly mobility solutions in motorsports. As the adoption of the electric vehicles grow, the importance of designing robust and reliable safety components, such as bumpers, become critical to protect drivers and enhance vehicle durability. While previous studies have explored Go-Kart safety and performance, they often relied on traditional testing methods that are time-consuming and limited in their ability to simulate complex crash scenarios. Moreover, many studies have not fully addressed the specific challenges associated with the unique dynamics of electric Go-Kart. This research fills these gaps by focusing on testing electric Go-Kart bumpers through advanced computer simulations used to thoroughly examine various crash and impact scenarios to assess the reliability and durability of the front, side and rear bumpers to improve safety and performance. The results of the stress analysis carried out on the electric Go-Kart body showed that the electric go-kart body experienced displacement and safety factors, with the stress experienced being at a point below the yield strength or yield strength so that the body construction was declared safe against the static loading received, so that the test results this provides detailed insight into material strength, structural design, and possible improvements that can be made to reduce the risk of rider injury.

Synchronization evaluation of digital twin for a robotic assembly system using computer vision

Traditional production processes are profoundly transforming in the era of Industry 4.0 and smart manufacturing. Smart manufacturing, a core element of Industry 4.0, employs advanced technologies such as automation, robotics, AI, big data analytics, and machine learning to boost productivity and manufacturing performance. Central to this evolution is the Digital Twin (DT), digital replicas of physical assets that blend real-time data with advanced analytics and simulations. Ensuring synchronization between the digital replica and its physical counterpart is crucial for the success of Digital Twins. This paper addresses the challenge of achieving and quantifying synchronization within DTs, focusing on replicating physical system behaviour and measuring deviations or delays. The study delves into the critical aspects of synchronization within digital twin applications, focusing on its implications for a robotic assembly system. The research successfully harnessed YOLOv8 to facilitate real-time event tracking and synchronization characterization, highlighting the potential of computer vision in enhancing synchronization accuracy and, consequently, the efficiency and reliability of manufacturing processes.

Shear buckling behaviour of beams with partial-depth stiffeners at the support

This paper presents the findings from experimental tests and numerical simulations on plate girders with various end post configurations. While EN 1993-1-5:2024 provides design rules for both rigid and non-rigid end posts, it does not address the shear resistance of partially stiffened webs. The use of partial-depth stiffeners faces risks due to the lack of thorough investigation into their mechanical behaviour. To explore this issue, small numbered experimental tests and large numbered parametric studies on beams with different web slenderness were conducted using advanced numerical simulations. The results indicated that the shear buckling capacity of girders is lower than the design recommendation when the web stiffener height is less than 50% of the web height. For girders with full-height stiffeners, EN 1993-1-5:2024 yields safe results. The accuracy of the EN 1993-1-5:2024 design rule for partially stiffened beams was also evaluated and new and shear buckling design curves were proposed for girders with partial-depth stiffeners.