Dynamic Element Research Articles

Intelligent system for monitoring the operational properties of ship power equipment

The peculiarity of monitoring the technical condition of ship vehicles is that during the service life the main energetic installation is not changed, but its continuous maintenance and periodic repairs are carried out. In the organization of such activities, the leading role belongs to technical diagnostics, which allows you to determine the technical condition of the material, as well as predict possible changes for a certain period. Intelligent system of monitoring of operational properties of ship power equipment with Markov circuits, probabilistic dynamics elements, calculations on probabilistic models, multi-criteria optimization of diagnostic parameters, simulation and scenario generation is proposed. In detail, the content of the main structural units of the system for monitoring the operational properties of ship power equipment is considered. The input information was a generalization of experience in the operation of vehicles. The stages of construction of Markov circuits are described in relation to diagnostics of turbochargers, the feature of which is a replacement of discrete time by a continuous sequence of states. Considered by a separate unit of calculation on probabilistic models on the basis of spectra of vibration signals by combining their main discrete features and establishing new diagnostic parameters. The visualization of relationships consists in the construction of digraphs of interactions of the main structural elements of the SES taking into account probabilistic models. Multi-criteria optimization in the presented system is considered from the standpoint of statistical criteria and their convolution. Simulation and generation of basic scenarios is described, from the point of view, the conversion of analog data about workflows to digital form. Provided information support and tools of the system for monitoring the operational properties of ship power equipment

Investigation of Lateral and Longitudinal Deformation of Submarine Nuclear Power Plant Water-Intake Tunnel on Non-Uniform Soft Soil during Earthquake

The safety-grade water-intake immersed tunnel plays a vital role in the nuclear power cooling system, and its seismic safety is crucial. This paper employs the response displacement method and dynamic time-history analysis using the finite element software ANSYS to construct a beam–spring model and a 3D finite element model of a shield tunnel and foundation. It also develops equivalent linear dynamic constitutive and viscoelastic boundary element subprograms. This study focuses on the weak joint sections of immersed tunnels, conducting a seismic performance analysis under extreme safety earthquake conditions (SL-2). The results indicate that the joint stiffness of immersed tunnels and the increase in seismic peak values do not affect the trend of joint opening variation with longitudinal position. The change in joint opening is primarily located where the thickness of the cover layer changes abruptly or where the soil hardness is unevenly distributed. The joint opening is mainly influenced by seismic forces when considering static and dynamic superposition. When the stiffness of the joint GINA water stop exceeds a certain value, the correlation between stiffness change and joint compression–tension variation gradually weakens. This research can provide a reference for the seismic design of similar projects.

Transport behavior of particles and evolution of plugging zones in rough fractures: Insights from a novel coupled CFD-DEM model

The meso-mechanism of particle bridging and plugging in rough fractures remains unclear. Therefore, this study explores a novel meso-model for simulating particle transport in rough fractures by combining Computational Fluid Dynamics and Discrete Element Method (CFD-DEM). The dynamic behavior of particles and the corresponding evolution mechanism of plugging zones are investigated. The simulation innovatively uses particle boundaries to correct fluid flow, greatly simplifying the fluid mesh partitioning while ensuring accuracy. The results reveal the connection between particles’ transport and bridging behavior in rough fracture spaces, the distribution characteristics of plugging zones, and fluid flow characteristics. The distribution of bridging favorable zones determines the position and pattern of the front edge of subsequent plugging zones. The stress accumulated by particles has little effect on the strong force chain of the front edge. The force chain strength of the double-particle bridging structure is greater than that of the single-particle bridging structure. Due to weak shear planes, the double-particle bridging structure is more prone to shear failure and instability under external loads. Improving the particle size distribution range can reduce bridging blind zones and achieve better sealing performance. The results provide theoretical help for the design of field operation processes.

Gas and powder flow characteristics of packed bed: A two-way coupled CFD-DEM study

A two-way coupled Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) calculation was performed to numerically investigate the gas and powder flow characteristics within a packed bed. The analysis and discussion focused on the effects of gas phase velocity, particle shape, and size on the flow behavior of the powders. The results revealed that the average absolute velocity of the powder increased with an increase in the inlet gas flow rate. Conversely, the average dimensionless velocity exhibited the opposite trend. Particle shape significantly impacted the flowability of the powders. A critical value of sphericity equal to 0.96 was observed. For powders with sphericity less than 0.96, the average velocity fluctuated around a progressively decreasing value over time, and the powders tended to accumulate in the inlet region. In contrast, powders with a sphericity greater than 0.96 exhibited average velocities fluctuating around a constant value throughout the simulation. Additionally, a smaller number of these particles remained within the fluid domain, indicating a higher flow rate through the packed bed and ultimately exiting the fluid domain. Regarding the influence of particle size, the flowability reached a minimum value at a radius of 0.14 mm, with the average powder velocity mirroring this trend. Powders with a radius exceeding 0.14 mm demonstrated increasing flowability and average velocity. The observed impact on flowability was likely due to a combination of mechanisms. The findings presented in this paper offer valuable insights into the dynamics of powders within a packed bed. This knowledge can be instrumental in the design and analysis of packed bed reactors.

Research on the Movement Speed of Situational Map Symbols Based on User Dynamic Preference Perception

When designing situational maps, selecting distinct and visually comfortable movement speeds for dynamic elements is an ongoing challenge for designers. This study addresses this issue by conducting two experiments to measure the human eye’s ability to discern moving speeds on a screen and examines how symbol movement speeds within situational maps affect users’ subjective experiences, task performance, and visual comfort. The first experiment measured participants’ speed discrimination capabilities for Landolt Ring of varying sizes moving at 0–256°/s, yielding speed discrimination thresholds of 7–23% and a sensitive velocity range of 1–64°/s. The second experiment evaluated observers’ visual perceptions of moving elements within a cognitive task across the same range of 1–64°/s, identifying three significant benchmarks—8°/s, 16°/s, and 32°/s. These can be utilized to categorize slow-, moderate-, and fast-moving symbols in situational maps. The findings can aid in designing human–machine interface environments with improved viewer experience and visual comfort for both Air Traffic Control interfaces and situational maps.

A Review of Factors Affecting the Lighting Performance of Light Shelves and Controlling Solar Heat Gain

In areas with a deep floor plan, the distribution of natural light is not uniform. Consequently, relying solely on daylight may not suffice to meet the space’s lighting requirements, necessitating the use of artificial lighting in darker areas. Therefore, a lighting system is needed that not only controls the glare near the windows but also increases the light at the end of the room and provides uniform daylight. One of the widely used systems is the “light shelf”, which has three main functions: shading, increasing the depth of light penetration, and reducing glare. Review articles about light shelves were published in 2015 and 2017, while more than 80% of the studies have been carried out since 2016, and light shelves with more diverse forms and dynamic elements and many consolidations have been proposed. Therefore, there is a need for a more comprehensive review. The main question of this research is how different parameters (including climate, material, ceiling, and integrated systems) can help to increase the efficiency of light shelves. By using a systematic review, studies in the past three decades were classified in order to determine the effect of these parameters on improving lighting performance and controlling solar heat gain.

Dynamic visual SLAM based on probability screening and weighting for deep features

Most Simultaneous Localization and Mapping (SLAM) systems highly rely on static environments assumption, leading to low pose estimation accuracy in dynamic environments. Dynamic Visual SLAM (VSLAM) methods have exhibited remarkable advantages in eliminating negative effects of dynamic elements. However, most current methods, only built on traditional indirect VSLAM using hand-crafted features, are still inadequate in utilizing and processing deep features. To this end, this paper proposes a dynamic VSLAM algorithm based on probability screening and weighting for deep features. Specifically, a deep feature extraction module is designed to generate deep features leveraged in the overall pipeline. Then, probability screening and weighting scheme is proposed for processing deep features, through which the dynamic deep feature points are eliminated in a coarse-to-fine manner and the various contributions of static ones is distinguished. Sufficient quantitative and qualitative experiments prove that our proposed method is superior to other counterparts in terms of localization accuracy.

Fluid-structure interaction and life prediction of small-scale damaged horizontal axis wind turbine blades

Throughout their operational lifespan and exposure to various environmental conditions, wind turbines experience diverse loading scenarios that could lead to blade cracking, affecting their structural integrity. This research focuses on analyzing the blade lifespan of two small-scale wind turbines, namely Air Silent X and Pikasola. The investigation introduces deliberate irregularities like holes, erosion, and cracks to examine their effects on blade durability. Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) are used to assess aerodynamic loads, deflection, and stress levels on the blades under different wind speeds. Leveraging the fracture analysis tool within ANSYS, the study predicts blade lifespan in terms of cycles. The findings revealed that anomalies located near high-stress regions tend to reduce the lifespan of blades compared to those positioned in lower-stress areas.

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states.

Postnatal genomic regulation significantly influences tissue and organ maturation but is under-studied relative to existing genomic catalogs of adult tissues or prenatal development in mouse. The ENCODE4 consortium generated the first comprehensive single-nucleus resource of postnatal regulatory events across a diverse set of mouse tissues. The collection spans seven postnatal time points, mirroring human development from childhood to adulthood, and encompasses five core tissues. We identified 30 cell types, further subdivided into 69 subtypes and cell states across adrenal gland, left cerebral cortex, hippocampus, heart, and gastrocnemius muscle. Our annotations cover both known and novel cell differentiation dynamics ranging from early hippocampal neurogenesis to a new sex-specific adrenal gland population during puberty. We used an ensemble Latent Dirichlet Allocation strategy with a curated vocabulary of 2,701 regulatory genes to identify regulatory "topics," each of which is a gene vector, linked to cell type differentiation, subtype specialization, and transitions between cell states. We find recurrent regulatory topics in tissue-resident macrophages, neural cell types, endothelial cells across multiple tissues, and cycling cells of the adrenal gland and heart. Cell-type-specific topics are enriched in transcription factors and microRNA host genes, while chromatin regulators dominate mitosis topics. Corresponding chromatin accessibility data reveal dynamic and sex-specific regulatory elements, with enriched motifs matching transcription factors in regulatory topics. Together, these analyses identify both tissue-specific and common regulatory programs in postnatal development across multiple tissues through the lens of the factors regulating transcription.

High-order elements in position-based dynamics

High-order elements in position-based dynamics

The 5'-terminal stem-loop RNA element of SARS-CoV-2 features highly dynamic structural elements that are sensitive to differences in cellular pH.

We present the nuclear magnetic resonance spectroscopy (NMR) solution structure of the 5'-terminal stem loop 5_SL1 (SL1) of the SARS-CoV-2 genome. SL1 contains two A-form helical elements and two regions with non-canonical structure, namely an apical pyrimidine-rich loop and an asymmetric internal loop with one and two nucleotides at the 5'- and 3'-terminal part of the sequence, respectively. The conformational ensemble representing the averaged solution structure of SL1 was validated using NMR residual dipolar coupling (RDC) and small-angle X-ray scattering (SAXS) data. We show that the internal loop is the major binding site for fragments of low molecular weight. This internal loop of SL1 can be stabilized by an A12-C28 interaction that promotes the transient formation of an A+•C base pair. As a consequence, the pKa of the internal loop adenosine A12 is shifted to 5.8, compared to a pKa of 3.63 of free adenosine. Furthermore, applying a recently developed pH-differential mutational profiling (PD-MaP) approach, we not only recapitulated our NMR findings of SL1 but also unveiled multiple sites potentially sensitive to pH across the 5'-UTR of SARS-CoV-2.

Exploring the influence of subjective thermal perception on electroencephalogram characteristics based on prior thermal experience

Achieving thermal comfort for occupants in a dynamic environment that reflects their previous thermal experiences is essential for enhancing satisfaction. Current models do not fully consider these dynamic elements, thus limiting advancements in occupants' thermal comfort. This study aims to delineate the characteristics of electroencephalogram (EEG) responses aligned with subjective thermal perception in various thermal environment scenarios, inclusive of past thermal experiences. It focuses on identifying EEG indices, brain regions, and temporal markers that can distinguish between different thermal perceptions. The study involves sixteen male participants who undergo three thermal experience scenarios: predicted mean vote (PMV) 0 → PMV +2, PMV +2 → PMV –2, and PMV -2 → PMV +2. Our results highlight the sensitivity of the F3 channel in the left frontal lobe to thermal environments. The study identifies a pivotal time frame of 6 min after the experiment's start as significant for differentiating thermal perception groups. Additionally, it reveals that the EEG indices reacting to thermal changes vary depending on the participants' previous thermal experiences. These findings indicate that physiological signals, particularly EEG responses, can serve as effective biomarkers for distinguishing thermal perceptions in diverse thermal experience scenarios. This research emphasizes the need to integrate a variety of thermal environment scenarios, considering previous thermal experiences, into personal comfort models for more effective and tailored thermal comfort solutions.

Connecting Solar Wind Velocity Spikes Measured by Solar Orbiter and Coronal Brightenings Observed by SDO

The Parker Solar Probe's discovery that magnetic switchbacks and velocity spikes in the young solar wind are abundant has prompted intensive research into their origin(s) and formation mechanism(s) in the solar atmosphere. Recent studies, based on in situ measurements and numerical simulations, argue that velocity spikes are produced through interchange magnetic reconnection. Our work studies the relationship between interplanetary velocity spikes and coronal brightenings induced by changes in the photospheric magnetic field. Our analysis focuses on the characteristic periodicities of velocity spikes detected by the Proton Alpha Sensor on the Solar Orbiter during its fifth perihelion pass. Throughout the time period analyzed here, we estimate their origin along the boundary of a coronal hole. Around the boundary region, we identify periodic variations in coronal brightening activity observed by the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory. The spectral characteristics of the time series of in situ velocity spikes, remote coronal brightenings, and remote photospheric magnetic flux exhibit correspondence in their periodicities. Therefore, we suggest that the localized small-scale magnetic flux within coronal holes fuels a magnetic reconnection process that can be observed as slight brightness augmentations and outward fluctuations or jets. These dynamic elements may act as mediators, bonding magnetic reconnection with the genesis of velocity spikes and magnetic switchbacks.

Modeling and Control of an MR-Safe Pneumatic Radial Inflow Motor and Encoder (PRIME).

Magnetic resonance (MR) conditional actuators and encoders are the key components for MR-guided robotic systems. In this article, we present the modeling and control of our MR-safe pneumatic radial inflow motor and encoder. A comprehensive model is developed that considers the primary dynamic elements of the system, including: 1) motor dynamics, 2) pneumatic transmission line dynamics, and 3) valve dynamics. After model validation, we present a simplified third order model that facilitates design of a first order sliding mode controller (TO-SMC). Finally, the motor hardware is tested in a 7T MRI. No image distortion or artifacts were observed. We posit the MR-safe motor and dynamic model will lower the entry barriers for researchers interested in MR-guided robots and promote wider adoption of MR-guided robotic systems.

Ecological carrying capacity assessment incorporating ecosystem service flows

Ecological carrying capacity focuses on the limits of human development, serving as a policy instrument for guiding regional sustainable development. Regional space exhibits openness and dynamics. Nonetheless, ecological carrying capacity assessments seldom account for the potential influence of dynamic elements. The endeavor to integrate ecosystem service flows into ecological carrying capacity assessment represents an innovative approach to address this issue. This paper reviews multiple methods of assessing ecological carrying capacity and highlights the deficiencies in representing dynamic elements. Subsequently, the research progress in ecosystem service flows is examined, encompassing connotations, features, and models. Based on common theories, intermediary linkages, and the impact of incorporating spatiotemporal dynamics, the relationship between them is analyzed. The advantages of ecosystem service flows are also elucidated, which provide explicit spatial information and integrate biophysical processes when representing dynamic elements. The framework for ecological carrying capacity assessment incorporating ecosystem service flows comprises five steps: key theory selection, objectives and scope establishment, identification of supply and demand matching and assessment of flow utility, ecosystem service flow analysis, and ecological carrying capacity assessment. In the future, the research will focus on conducting quantitative pilot projects in typical regions, removing barriers to ecosystem service flows, and developing a dynamic ecological carrying capacity assessment model that considers multiple factors.

The effects of game mechanics on user retention in using social live streaming services

PurposeSocial live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.Design/methodology/approachThis study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.FindingsThe results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.Originality/valueDriven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.

Asset Allocation Strategies: A Case Study in Mutual Fund and Inaurance Portfolios in Wallet Wealth LLP

This case study explores effective asset allocation strategies, focusing on mutual funds and insurance portfolios, with an emphasis on incorporating a de-risking factor. It underscores the importance of strategic asset allocation customised to each person’s risk profiles, Investing objectives, and temporal horizons . By utilizing mutual funds and insurance products, investors can construct diversified portfolios to mitigate risk and optimize returns. The study examines how different combinations of these instruments can enhance portfolio resilience and performance. Moreover, the integration of a de-risking factor adds a dynamic element to distribution of assets. This entails modifying the asset in the portfolio. mix depending on the state of the market and risk preferences to minimize downside risk and capture upside potential. Through historical analysis and scenario simulations, the study evaluates the efficacy of various asset allocation strategies, highlighting the benefits of incorporating a de-risking approach. It demonstrates how this strategy can protect capital during market downturns while capitalizing on growth opportunities in favorable market conditions.

A Comparative Review on Enhancing Visual Simultaneous Localization and Mapping with Deep Semantic Segmentation.

Visual simultaneous localization and mapping (VSLAM) enhances the navigation of autonomous agents in unfamiliar environments by progressively constructing maps and estimating poses. However, conventional VSLAM pipelines often exhibited degraded performance in dynamic environments featuring mobile objects. Recent research in deep learning led to notable progress in semantic segmentation, which involves assigning semantic labels to image pixels. The integration of semantic segmentation into VSLAM can effectively differentiate between static and dynamic elements in intricate scenes. This paper provided a comprehensive comparative review on leveraging semantic segmentation to improve major components of VSLAM, including visual odometry, loop closure detection, and environmental mapping. Key principles and methods for both traditional VSLAM and deep semantic segmentation were introduced. This paper presented an overview and comparative analysis of the technical implementations of semantic integration across various modules of the VSLAM pipeline. Furthermore, it examined the features and potential use cases associated with the fusion of VSLAM and semantics. It was found that the existing VSLAM model continued to face challenges related to computational complexity. Promising future research directions were identified, including efficient model design, multimodal fusion, online adaptation, dynamic scene reconstruction, and end-to-end joint optimization. This review shed light on the emerging paradigm of semantic VSLAM and how deep learning-enabled semantic reasoning could unlock new capabilities for autonomous intelligent systems to operate reliably in the real world.

Fractional Second-Grade Fluid Flow over a Semi-Infinite Plate by Constructing the Absorbing Boundary Condition

The modified second-grade fluid flow across a plate of semi-infinite extent, which is initiated by the plate’s movement, is considered herein. The relaxation parameters and fractional parameters are introduced to express the generalized constitutive relation. A convolution-based absorbing boundary condition (ABC) is developed based on the artificial boundary method (ABM), addressing issues related to the semi-infinite boundary. We adopt the finite difference method (FDM) for deriving the numerical solution by employing the L1 scheme to approximate the fractional derivative. To confirm the precision of this method, a source term is added to establish an exact solution for verification purposes. A comparative evaluation of the ABC versus the direct truncated boundary condition (DTBC) is conducted, with their effectiveness and soundness being visually scrutinized and assessed. This study investigates the impact of the motion of plates at different fluid flow velocities, focusing on the effects of dynamic elements influencing flow mechanisms and velocity. This research’s primary conclusion is that a higher fractional parameter correlates with the fluid flow. As relaxation parameters decrease, the delay effect intensifies and the fluid velocity decreases.

Overcoming Fear and Improving Public Speaking Skills through Adaptive VR Training

This paper examines the effectiveness of virtual reality (VR) in training public speaking skills. The fear of public speaking (FPS) is a common problem that can have a significant impact on an individual’s professional and personal life. Traditional therapies for public speaking anxiety have been shown to be effective, but there is growing interest in the use of VR as an alternative or supplement to these therapies. This study aims to investigate the VR medium in improving public speaking skills and to explore the potential mechanisms underlying this effect. A framework was developed with the aim to investigate the possibility of improving public speaking skills through VR. Key features of this framework include the ability to adjust the audience size and alter the dimensions of the room. Additionally, it allows for the modification of initial audience behaviors. One of the innovative aspects is the inclusion of an evolving attention span in the virtual audience, adding a dynamic element to the VR experience. The framework excels in tracking various metrics in real time and has the audience react dynamically based on them. These metrics include movement and voice parameters. The system is designed to present this data as immediate feedback to the user, but also as a summary after a presentation has concluded. After an extensive two-phased testing, the results are discussed. These findings suggest that VR can be an effective means for improving public speaking skills and potentially helping in alleviating fear of public speaking.