Search Results (152)

The traditional deadbeat predictive current control (DPCC) strategies for a permanent magnet synchronous motor (PMSM), such as those based on an extended state observer (ESO) and quasi-resonant extended state observer (QRESO), usually require large observer bandwidth, rendering the system sensitive to noise. To address this issue, this paper proposes a cascaded quasi-resonant extended state observer-based DPCC (CQRESO-based DPCC) strategy. Specifically, the CQRESO is utilized to estimate the predicted values of d-axis and q-axis currents, as well as the system total disturbance caused by the deterministic and uncertain factors at time instant k + 1. Subsequently, the required control command voltage at time instant k + 1 is then calculated according to the deadbeat control principle. Finally, the comparative simulation results with ESO-based DPCC and QRESO-based DPCC strategies demonstrate that the proposed strategy can achieve dynamic and robust performance comparable to the ESO-based and QRESO-based DPCC strategies while utilizing a smaller observer bandwidth. Additionally, it exhibits superior steady-state performance and 5th and 7th harmonic current suppression capabilities (in the abc reference frame). Full article

Amidst the dual challenges of escalating ecological environmental pressures and economic transformation globally, green innovation emerges as a pivotal pathway toward achieving high-quality sustainable development. To elucidate how digitalization and novel productive forces synergistically drive the green transition, the research utilizes panel data from 30 provincial-level administrative regions in China spanning 2009 to 2022, constructing a green innovation efficiency measurement frame-work grounded in the Super Slack-Based Measure (Super-SBM)model, alongside a novel productive forces evaluation system based on the triad of laborers, labor objects, and means of production. Employing spatial difference-in-differences and double machine learning methodologies within a quasi-natural experimental design, the research investigates the causal mechanisms through which digital empowerment and novel productive forces influence regional green innovation efficiency. The findings reveal that both digital empowerment and novel productive forces significantly enhance regional green innovation efficiency, exhibiting pronounced positive spatial spillover effects on neighboring regions. Heterogeneity analyses demonstrate that the promotive impacts are more pronounced in eastern provinces compared to central and western counterparts, in provinces participating in carbon trading relative to those that do not, and in innovation-driven provinces versus non-innovative ones. Mediation analysis indicates that digital empowerment operates by fostering the aggregation of innovative talent and elevating governmental ecological attentiveness, whereas new-type productivity exerts its influence primarily through intellectual property protection and the clustering of high-technology industries. The results offer empirical foundations for policymakers to devise coordinated regional green development strategies, refine digital transformation policies, and promote industrial structural optimization. Furthermore, this research provides valuable data-driven insights and theoretical guidance for local governments and enterprises in cultivating green innovation and new-type productivity. Full article

The rapid evolution of the Fourth Industrial Revolution has significantly transformed educational practices, necessitating the integration of advanced technologies into higher education to address contemporary sustainability challenges. This study explores the integration of interactive metaverse environments and generative artificial intelligence (GAI) in promoting the green digital economy and developing e-entrepreneurship skills among graduate students. Grounded in a quasi-experimental design, the research was conducted with a sample of 25 postgraduate students enrolled in the “Computers in Education” course at King Khalid University. A 3D immersive learning environment (FrameVR) was combined with GAI platforms (ChatGPT version 4.0, Elai.io version 2.5, Tome version 1.3) to create an innovative educational experience. Data were collected using validated instruments, including the Green Digital Economy Scale, the e-Entrepreneurship Scale, and a digital product evaluation rubric. The findings revealed statistically significant improvements in students’ awareness of green digital concepts, entrepreneurial competencies, and their ability to produce sustainable digital products. The study highlights the potential of immersive virtual learning environments and AI-driven content creation tools in enhancing digital literacy and sustainability-oriented innovation. It also underscores the urgent need to update educational strategies and curricula to prepare future professionals capable of navigating and shaping green digital economies. This research provides a practical and replicable model for universities seeking to embed sustainability through emerging technologies, supporting broader goals such as SDG 4 (Quality Education) and SDG 9 (Industry, Innovation, and Infrastructure). Full article

The roof slab, as a critical component for partitioning the vertical space within RC frame structures, can effectively mitigate the propagation of shock waves and reduce damage levels in adjacent rooms. This study employed finite element (FE) modeling to investigate the vertical propagation of blast waves and roof ejection velocity in RC frames. The model’s reliability was verified by reconstructing internal explosion tests on RC frames and close-in explosion tests on masonry walls. On this basis, two typical single-room RC frame structures that are vertically adjacent were designed, and numerical simulations of the internal explosion were conducted under four explosive equivalents and four venting coefficients. The propagation of shock waves, load characteristics in the vertically adjacent room, and the dynamic response of roof slabs were examined. The results show that shock waves propagated to the vertically adjacent room decreased by approximately two orders of magnitude for peak overpressure and one order of magnitude for impulse due to the obstruction of shock waves by roof slabs, respectively, compared to the source explosion room. For larger venting coefficients, abundant energy was released through the venting openings, making it difficult to form a quasi-static pressure with a long duration inside the source explosion room. In addition to the shock wave, the explosive ejection of roof slabs in the explosion source room will further exacerbate the damage to the vertically adjacent room. Peak overpressure and impulse propagated to the vertically adjacent room were reduced significantly by the increase in the venting coefficient, resulting in an attenuation of structural damage. Finally, empirical models incorporating the venting coefficient were established to characterize the attenuation coefficients of power parameters, demonstrating the predictive capability for peak overpressure, impulse, and roof ejection velocity in both the explosion source room and the vertically adjacent room. Full article

A novel endplate bolted rigid joint is proposed in this study for connecting circular concrete-filled steel tube (CCFT) columns to wide-flange (WF) steel beams. The seismic performance and potential failure mechanisms of the proposed joint were investigated through quasi-static cyclic tests and finite element (FE) simulations. This study aims to address several engineering challenges commonly observed in existing joint configurations, including an irrational force-resisting mechanism, complicated detailing and installation, on-site construction difficulties, constraints on beam size, and limited repairability. By optimizing the force transfer path, the new joint effectively reduces the number of critical tension welds, thereby enhancing the ductility and reliability. The experimental results indicate that the joint exhibits adequate flexural strength, stiffness, and ductility, with stable moment–rotation hysteresis loops under cyclic loading. Moreover, full restoration of the joint can be achieved by replacing only the steel beam and endplate, facilitating post-earthquake repair. FE analysis reveals that, under the ultimate bending moment at the beam end, multiple through cracks develop in the high-strength grout—which serves as a key load-transferring component—and significant debonding occurs between the grout and the surrounding steel members. However, due to confinement from adjacent components, these internal cracks do not compromise the overall strength and stiffness of the joint. This research provides an efficient and practical connection solution, along with valuable experimental insights, for the application of CCFT columns in moment-resisting frames located in high seismic zones. Full article

Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and motivational processes, especially in relation to risk perception, decision-making, and betting persistence. Using ordinary least squares (OLS) and panel regression models applied to behavioral data from a gambling platform, we examine patterns that are consistent with increased personalization between two distinct time periods, 2016 and 2021. The datasets do not contain any direct metadata regarding AI interventions. However, we interpret changes in user behavior over time as indicative of evolving personalization dynamics within a broader technological and contextual landscape. Accordingly, our conclusions about algorithmic personalization are inferential and exploratory, drawn from temporal comparisons between 2016 and 2021. Our findings show that users receiving personalized bonuses or making early cash-out decisions tend to adjust their stake sizes and betting frequency in systematic ways, which may reflect indirect effects of technological reinforcement strategies. These behavioral patterns raise important ethical and regulatory questions, particularly regarding user autonomy, algorithmic transparency, and the protection of at-risk users. This research contributes to the literature on digital behavior influencing gambling by framing the analysis as observational and quasi-experimental and suggests that further studies use experimental and log-level data to more specifically analyze the algorithmic effects. However, no causal claims can be made about AI influence as the temporal contradictions are interpreted as broad phenomena of technological developments, since they are not measured as algorithmic interventions. Further studies should also investigate the development of predictive models aimed at countering gambling addiction; evaluate the long-term ethical implications of algorithmic personalization; and discuss potential solutions codeveloped to foster a responsible gambling climate. Full article

The offshore oil engineering jacket is a giant super-heavy steel frame structure with dimensions in the hundreds of meters. A high-precision free station control network is usually arranged around it to ensure construction accuracy. However, as the jacket is gradually assembled, its extreme weight will cause the widespread deformation of the surrounding ground surface, and each control point may be affected to varying degrees, resulting in the non-uniform deformation of the entire network. For adjustments of control networks in the subsequent phases, if the same starting point as the first phase is chosen without careful analysis, the starting points’ non-uniform deformation will degrade the whole network’s accuracy. Considering the particularities of the free station control network, this paper proposes an adjustment algorithm consisting of a three-step analytical method. Firstly, the initial coordinates of the points of the current phase are obtained through classical free network adjustment; second, stable and unstable points are identified via coordinate similarity transformation between the current and the first phase; and finally, quasi-stable adjustment is conducted. The experimental data analysis of a jacket control network shows that this method can effectively identify stable and unstable points, thereby ensuring construction accuracy and jacket stability. Full article

Probabilistic random vibration can speed up wear and tear on several components of the tracked vehicle, including the track system, drivetrain, and suspension. Extended exposure to high levels of vibration can cause structural damage to the vehicle frame and other critical components. Assessing random vibration in track vehicles requires a comprehensive approach that considers both the root causes and potential consequences of the vibrations. This random vibration significantly influences the structural performance of suspension arm which is key component of tracked vehicle. Damage due to fatigue is conventionally computed using time domain loaded signals with stress or strain data. This approach generally holds good when loading is periodic in nature but not be a good choice when dynamic resonance is in process. In this case an alternative frequency domain fatigue life analysis is used where the random loads and responses are characterized using a concept called Power spectral density (PSD). The current research article investigates the fatigue damage characteristics of a tracked vehicle suspension arm considering the dynamic loads induced by traversing on smooth and rough terrain. The analysis focusses on assessing the damage and stress response Power spectral density (PSD) ground-based excitation which is termed PSD-G acceleration. Quasi Static Finite Element Method based approach is used to simulate the operational conditions experienced by the suspension arm. Through comprehensive numerical simulations, the fatigue damage accumulation patterns are examined, providing insights into the structure integrity and performance durability of the suspension arm under varying operational scenarios. The obtained stress response PSD data and fatigue damage showed that the rough terrain response exhibits higher stresses in suspension arm. The accumulated stresses in case of rough terrain may prompt to brittle failure at specific critical locations. This research contributes to the advancement to the design and optimization strategies for tracked vehicle components enhancing their reliability and longevity in demanding operational environments. Full article

Precise determination of structural elastic–plastic displacement and component states under rare earthquakes is crucial for structural design. This article proposes a quasi-elastic–plastic optimization method for reinforced concrete structures. First, an approximate formula for calculating the yield bending moment of shear walls is provided through analysis of 64 shear walls. Second, a quasi-elastic–plastic analysis method is proposed. Using the elastic response spectrum analysis, strain energy for each component is calculated, and stiffness reduction factors for walls, beams, and columns are derived based on the energy equivalence principle. Finally, combining the elastic response spectrum analysis and the quasi-elastic–plastic analysis, various constraint indicators at the elastic and elastic–plastic design stages are calculated, and structural size optimization is completed using the particle swarm optimization method. The feasibility of this method is validated with examples of a 15-story reinforced concrete frame structure and a 15-story frame–shear wall structure. The quasi-elastic–plastic optimization with the particle swarm optimization efficiently completes elastic–plastic optimization for reinforced concrete structures, determining section sizes that meet performance standards while reducing material usage. Full article

In this paper, by using the zeroth-order q-Tricomi functions, the theory of three-variable q-Legendre-based Appell polynomials is introduced. These polynomials are studied by means of generating functions, series expansions, and determinant representation. Further, by utilizing the concepts of q-quasi-monomiality, these polynomials are examined as several q-quasi-monomial and operational representations; the q-differential equations for the three-variable q-Legendre-based Appell polynomials were obtained. In addition, we established a new generalization of three-variable q-Legendre-Hermite-Appell polynomials, and we derive series expansion, determinant representation, and q-quasi-monomial and q-differential equations. Some examples are framed to better illustrate the theory of three-variable q-Legendre-based Appell polynomials, and this is characterized by the above properties. Full article

The double crystal monochromator (DCM) is a spectrometer in synchrotron radiation beamlines, and its stability directly impacts the quality of the emitted light. In order to meet the requirements of the fourth generation of synchrotron light sources, researchers have designed a DCM using an active control method to ensure stability by actively compensating for crystal displacement through voice coil motors. The active control method imposes high demands on the vibration isolation performance of the DCM frame. In response to external excitation characteristics, this paper proposes a quasi-zero stiffness (QZS) isolation system based on a compressed buckling beam structure. Random vibration simulations using finite element analysis revealed that, under different operating conditions, the 3σ displacement of the core part of the DCM is maintained at the nanometer level. Moreover, this paper presents a calculation method based on elastic potential energy to establish force equilibrium equations for negative stiffness and analyzes stress distribution in the beam during vibration using the derived deflection curve. Validation through finite element simulations confirms the method’s accuracy in calculating negative stiffness and stress distribution. Because of the structural similarities, some of the results of this paper can be applied to the study of negative stiffness honeycomb materials. Full article

If M is an algebra in a semidegenerate congruence-modular variety $\mathcal{V}$, then the set $Con(M)$ of congruences of M is an integral complete l-groupoid (= $icl$-groupoid). For any morphism $f:M\to N$ of $\mathcal{V}$, consider the map $f^{•}:Con(M)\to Con(N)$, where, for each congruence $\epsilon$ of M, $f^{•}(\epsilon )$ is the congruence of N generated by $f(\epsilon )$. Then, $f^{•}$ is a semimorphism of $icl$-groupoids, i.e., it preserves the arbitrary joins and the top congruences. The neo-commutative $icl$-groupoids were introduced recently by the author as an abstraction of the lattices of congruences of Kaplansky neo-commutative rings. In this paper, we define the admissible semimorphisms of $icl$-groupoids. The basic construction of the paper is a covariant functor defined by the following: $(1)$ to each semiprime and neo-commutative $icl$-groupoid A, we assign a coherent frame $R(A)$ of radical elements of A; and $(2)$ to an admissible semimorphism of $icl$-groupoids $u:A\to B$, we assign a coherent frame morphism $u^{\rho }:R(A)\to R(B)$. By means of this functor, we transfer a significant amount of results from coherent frames and coherent frame morphisms to the neo-commutative $icl$-groupoids and their admissible semimorphisms. We study the m-prime spectra of neo-commutative $icl$-groupoids and the going-down property of admissible semimorphisms. Using some transfer properties, we characterize some classes of admissible semimorphisms of $icl$-groupoids: Baer and weak-Baer semimorphisms, quasi r-semimorphisms, quasi $r^{*}$-semimorphisms, quasi rigid semimorphisms, etc. Full article

Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved in recent decades allow for expanding the experimental possibilities and designing engines operating with a single particle. In this case, the system of interest cannot be addressed at a macroscopic level and their study is framed in the field of stochastic thermodynamics. In the present work, we study mesoscopic heat engines built with a Brownian particle submitted to harmonic confinement and immersed in a fluid acting as a thermal bath. We design a Stirling-like heat engine, composed of two isothermal and two isochoric branches, by controlling both the stiffness of the harmonic trap and the temperature of the bath. Specifically, we focus on the irreversible, non-quasi-static case—whose finite duration enables the engine to deliver a non-zero output power. This is a crucial aspect, which enables the optimisation of the thermodynamic cycle by maximising the delivered power—thereby addressing a key goal at the practical level. The optimal driving protocols are obtained by using both variational calculus and optimal control theory tools. Furthermore, we numerically explore the dependence of the maximum output power and the corresponding efficiency on the system parameters. Full article

This paper explores the systemic relationship between urban civilization initiatives and economic prosperity by examining the economic impact of China’s “National Civilized City” (NCC) designation. We begin by synthesizing literature that addresses the complex interactions between urban development and environmental sustainability, emphasizing a systems approach. A theoretical model is developed to capture the dynamic interplay between urban environmental strategies and socio-economic outcomes, framed within the context of the Sustainable Development Goals (SDGs). Employing a quasi-experimental difference-in-differences (DID) method, we analyze data from a panel of Chinese cities (1997–2019) to assess how the NCC title influences economic growth and urban sustainability. Our results indicate a notable 2.88% increase in GDP per capita associated with the designation; however, this effect varies based on the city’s administrative status and geographical location, highlighting the complex and conditional nature of policy impact on economic development. We conclude by offering policy recommendations that promote a holistic approach to urban planning, fostering synergies between environmental conservation and economic growth. These insights contribute to a deeper understanding of sustainable urban development strategies with relevance to both emerging and developed economies. Full article

Quasi-direct current (Q-DC) filamentary electrical discharges are used to control the shock train in a back-pressured Mach 2 duct flow. The coupled interaction between the plasma filaments and the shock train leading edge (STLE) is studied for a variety of boundary conditions. Electrical parameters associated with the discharge are recorded during actuation, demonstrating a close correlation between the STLE position and dynamics. High-speed self-aligned focusing schlieren (SAFS) and high frame-rate color camera imaging are the primary optical diagnostics used to study the flowfield and plasma morphology. Shock tracking and plasma characterization algorithms are employed to extract time-resolved quantitative data during shock–plasma interactions. Four distinct shock–plasma interaction types are identified and outlined, revealing a strong dependence on the spacing between the uncontrolled STLE and discharge electrodes and a moderate dependence on flow parameters. Full article