Search Results (781)

Hydraulic concrete is prone to cracking and interactive propagation under complex stress, threatening its structural integrity and service life. To address limitations of traditional numerical methods (e.g., mesh dependency in FEM) and imprecision of existing meshless methods for characterizing multi-fissure interactions, this study improved SPH to model double-crack interactions in hydraulic concrete under three-point bending and clarify the underlying mechanisms. A modified SPH framework was developed by introducing a failure parameter (ξ) to refine the kernel function, enabling simulation of particle progressive failure via the Mohr–Coulomb criterion; a three-point bending numerical model of concrete beams containing double precast fissures (induced and obstacle) was established, with simulations under varying obstacle fissure angles (α = 0–75°) and distances (d = 0.02–0.06 m). The results show that the obstacle fissure angles significantly regulate the crack paths: as the α increases, the tensile stress concentration shifts from the obstacle fissure’s middle to its ends, causing cracks to deflect toward the lower end, with a reduced propagation length and lapping time; at an α = 75°, the obstacle fissure’s lower tip dominates failure, forming an “induced fissure–lower end of obstacle fissure–top” penetration mode. The fissure distances affect the stress superposition: a smaller d (e.g., 0.02 m) induces vertical propagation and rapid lapping with the obstacle fissure’s lower end, while a larger d (e.g., 0.06 m) weakens the stress at the induced fissure tip, promoting horizontal deflection toward the obstacle fissure’s upper end and transforming the failure into “upper-end dominated.” This confirms that the improved SPH method effectively simulates crack behaviors, providing insights into multi-fissure failure mechanisms and theoretical support for hydraulic structure crack control and safety evaluation. Full article

This article presents a new approach to the problem of transforming one quantum state into another. It is shown that an $r$-qubit superposition $|\mathit{x}⟩$ can be obtained from another $r$-qubit superposition $|\mathit{y}⟩$, by using only ${(2}^r-1)$ rotations, each presented by one controlled rotation gate. The quantum superpositions with real amplitudes are considered. The traditional two-stage approach $U_y^{-1}{U}_x:|\mathit{x}⟩\to |{0⟩}^{\oplus r}\to |\mathit{y}⟩$ requires twice as many rotations. Here, both transformations to the conventual basis state, $U_x: |\mathit{x}⟩\to |{0⟩}^{\oplus r}$ and $U_y: |\mathit{y}⟩\to |{0⟩}^{\oplus r}$, use ${(2}^r-1)$ rotations each on two binary planes, and many of these rotations require additional sets of CNOTs to be represented as 1- or 2-qubit-controlled gates. The proposed method is based on the concept of the discrete signal-induced heap transform (DsiHT) which is unitary and generated by a vector and a set of angular equations with given parameters. The quantum analog of this transform is described. The main characteristic of the DsiHT is the path of processing the data. It is shown that there exist such fast paths that allow for effective computing of the DsiHT, which leads to the simple quantum circuits for state preparation and transformation. Examples of such paths are given and quantum circuits for preparation and transformation of 2-, 3-, and 4-qubits are described in detail. CNOT gates are not used, but only controlled gates of elementary rotations around the $y$-axis$.$ It is shown that the transformation and, in particular, only rotation gates with control qubits are required for initialization of 2-, 3-, and 4-qubits. The quantum circuits are simple and have a recursive form, which makes them easy to implement for arbitrary $r$-qubit superposition, with $r\ge 2.$ This approach significantly reduces the complexity of quantum state transformations, paving the way for more efficient quantum algorithms and practical implementations on near-term quantum devices. Full article

As critical assets for surveillance, reconnaissance, and transport, shipborne helicopters play an indispensable role in modern maritime operations. Ensuring the safety and stability of shipboard landings is therefore of paramount importance, particularly under complex sea conditions. This study presents a comprehensive investigation into the dynamic interaction between helicopters and moving ships during the landing phase, with a particular emphasis on the influence of ship motions on the unsteady aerodynamic flow field and rotor loads. A coupled numerical–theoretical framework is developed, which overcomes the limitations of traditional models that typically consider static or single-degree-of-freedom (SDOF) ship motions. This work systematically analyzes the effects of multi-degree-of-freedom (MDOF) ship motions—including roll, pitch, and heave—on the coupled aerodynamic environment and rotor dynamic response. The results demonstrate that each motion component imposes a distinct influence on the flow-field characteristics, with pitch identified as the dominant contributor to turbulence intensity, particularly during the mid-to-late landing phase. Furthermore, it is found that a linear superposition of individual motions cannot accurately represent the combined effect of MDOF motions. Instead, their interaction leads to complex nonlinear effects, which may attenuate certain flow instabilities. These findings provide critical insights into ship–helicopter dynamic coupling and offer a scientific basis for improving landing safety under adverse sea conditions. Full article

In this work, we investigate the quantum coherence and purity in hydrogen atoms under dissipative dynamics, with a focus on the hyperfine structure states arising from the electron–proton spin interaction. Using the Lindblad master equation, we model the time evolution of the density matrix of the system, incorporating both the unitary dynamics driven by the hyperfine Hamiltonian and the dissipative effects due to environmental interactions. Quantum coherence is quantified using the $L_1$ norm and relative entropy measures, while purity is assessed via von Neumann entropy, for initial states, including a maximally entangled Bell state and a separable state. Our results reveal distinct dynamics: for the Bell states, both coherence and purity decay exponentially with a rate proportional to the dissipation parameter, whereas for a kind of separable state, coherence exhibits oscillatory behavior modulated via the hyperfine coupling constant, superimposed on an exponential decay, and accompanied by a steady increase in entropy. Higher dissipation rates accelerate the loss of coherence and the growth of von Neumann entropy, underscoring the environment’s role in suppressing quantum superposition and driving the system towards mixed states. These findings enhance our understanding of coherence and purity preservation in atomic systems and offer insights for quantum information applications where robustness against dissipation is critical. Full article

Seeking to advance mutual clustering of the tourism economy and cultural industries while safeguarding cultural sustainability in tourism, this paper delves into the patterns of co-development and the contributing forces across spatial and temporal dimensions in the Yellow River Basin. Using a combined spatial and temporal analytical lens, along with spatial autocorrelation testing and a spatial Durbin model embedded in a synergetic systems approach, the present study analyzes the evolutionary characteristics of the spatiotemporal pattern of the collaborative agglomeration of the Yellow River Basin’s tourism and cultural industries in 2011 and 2021 and the internal mechanism of its influencing factors. We then propose countermeasures and suggestions to boost the quality–efficiency synergy agglomeration of the basin’s tourism and cultural industries. The results showed the following: ① From 2011 to 2021, a positive overall spatial autocorrelation was noted in the basin’s tourism and cultural industries. Temporally, it presented a variation trend of “rise–fall–rise”, and spatially, it presented a distribution characteristic of “higher in the central and eastern regions versus in its western parts”. ② From 2011 to 2021, the local spatial autocorrelation (LSA) of the basin’s tourism and cultural industries remained at a low level. Moreover, significant differences were noted in the LSA among different regions. In spatial terms, the clustering intensity of tourism and cultural industries was stronger in the central and eastern parts of the basin versus in its western parts. ③ Influencing variables for tourism–culture collaborative agglomeration across the basin involve both temporal superposition effects and spatial radiation driving effects. The industrial economy, policies, and innovation exert enduring effects on the development and cross-regional spillover outcomes of the two collaborative agglomerations. Serving as a theoretical reference and policy resource, this study addresses how to promote the quality–efficiency synergy in the Yellow River Basin’s tourism and cultural industries while enhancing cultural sustainability in the tourism industry. Moreover, it can also provide experiences and references for other similar regions. Full article

Quantum machine learning (QML) has emerged as a promising approach for enhancing image classification by exploiting quantum computational principles such as superposition and entanglement. However, practical applications on complex datasets like CIFAR-100 remain limited due to the low expressivity of shallow circuits and challenges in circuit optimization. In this study, we propose HQCNN–REGA—a novel hybrid quantum–classical convolutional neural network architecture that integrates data re-uploading and genetic algorithm optimization for improved performance. The data re-uploading mechanism allows classical inputs to be encoded multiple times into quantum states, enhancing the model’s capacity to learn complex visual features. In parallel, a genetic algorithm is employed to evolve the quantum circuit architecture by optimizing gate sequences, entanglement patterns, and layer configurations. This combination enables automatic discovery of efficient parameterized quantum circuits without manual tuning. Experiments on the MNIST and CIFAR-100 datasets demonstrate state-of-the-art performance for quantum models, with HQCNN–REGA outperforming existing quantum neural networks and approaching the accuracy of advanced classical architectures. In particular, we compare our model with classical convolutional baselines such as ResNet-18 to validate its effectiveness in real-world image classification tasks. Our results demonstrate the feasibility of scalable, high-performing quantum–classical systems and offer a viable path toward practical deployment of QML in computer vision applications, especially on noisy intermediate-scale quantum (NISQ) hardware. Full article

Quantum computing, with its foundational principles of superposition and entanglement, has the potential to provide significant quantum advantages, addressing challenges that classical computing may struggle to overcome. As data generation continues to grow exponentially and technological advancements accelerate, classical machine learning algorithms increasingly face difficulties in solving complex real-world problems. The integration of classical machine learning with quantum information processing has led to the emergence of quantum machine learning, a promising interdisciplinary field. This work provides the reader with a bottom-up view of quantum circuits starting from quantum data representation, quantum gates, the fundamental quantum algorithms, and more complex quantum processes. Thoroughly studying the mathematics behind them is a powerful tool to guide scientists entering this domain and exploring their connection to quantum machine learning. Quantum algorithms such as Shor’s algorithm, Grover’s algorithm, and the Harrow–Hassidim–Lloyd (HHL) algorithm are discussed in detail. Furthermore, real-world implementations of quantum machine learning and quantum deep learning are presented in fields such as healthcare, bioinformatics and finance. These implementations aim to enhance time efficiency and reduce algorithmic complexity through the development of more effective quantum algorithms. Therefore, a comprehensive understanding of the fundamentals of these algorithms is crucial. Full article

Channels with three standard symmetrical sections and one asymmetric section are mounted as cantilever beams with the web oriented vertically. A classical solution to the analysis of stress in each thin-walled cantilever channel is provided using the principle of wall shear flow superposition. The latter is coupled with a further superposition between axial stress arising from bending and from the constraint placed on free warping imposed at the fixed end. Closed solutions for design are tabulated for the net shear stress and the net axial stress at points around any section within the length. Stress distributions thus derived serve as a benchmark structure for alternative numerical solutions and for experimental investigations. The conversion of the transverse free end-loading applied to a thin-walled cantilever channel into the shear and axial stress that it must bear is outlined. It is shown that the point at which this loading is applied within the cross-section is crucial to this stress conversion. When a single force is applied to an arbitrary point at the free-end section, three loading effects arise generally: bending, flexural shear and torsion. The analysis of each effect requires that this force’s components are resolved to align with the section’s principal axes. These forces are then considered in reference to its centroid and to its shear centre. This shows that axial stress arises directly from bending and from the constraint imposed on free warping at the fixed end. Shear stress arises from flexural shear and also from torsion with a load offset from the shear centre. When the three actions are combined, the net stresses of each action are considered within the ability of the structure to resist collapse from plasticity and buckling. The novelty herein refers to the presentation of the shear flow calculations within a thin wall as they arise from an end load offset from the shear centre. It is shown how the principle of superposition can be applied to individual shear flow and axial stress distributions arising from flexural bending, shear and torsion. Therein, the new concept of a ‘trans-moment’ appears from the transfer in moments from their axes through centroid G to parallel axes through shear centre E. The trans-moment complements the static equilibrium condition, in which a shift in transverse force components from G to E is accompanied by torsion and bending about the flexural axis through E. Full article

In this study, a current vector pattern is analyzed for inter-turn fault (ITF) diagnosis of induction machines (IMs), and an ITF diagnosis algorithm is proposed. When an ITF occurs in IMs, a negative-sequence current is generated due to fault resistance, even though a positive-sequence voltage is applied to IMs. Based on the mathematical model of IMs with an ITF, the current vector patterns in the stationary coordinate frame are analyzed. The superposition of positive- and negative-sequence components results in an elliptical current vector trajectory, and its orientation varies depending on the fault conditions. The co-simulation using finite element analysis and circuit simulation is implemented to analyze the current vector pattern of IMs with an ITF. The ITF diagnosis is proposed based on the current vector pattern. A 12 kW, four-pole, three-phase IM and terminal box, which was used to implement an ITF, is manufactured, and an experiment setup is established to verify the ITF algorithm. The effectiveness of the proposed ITF algorithm is validated through experimental verification of the manufactured IM and terminal box. Full article

With the development of underground space in urban areas, the demand for tunneling through existing railways is increasing. The adverse effects of cut-blasting during the construction of tunnels under crossing existing railways are investigated. Combined with the principle of blasting seismic wave superposition, LS-DYNA numerical simulation is used to analyze the seismic wave superposition law under different superposition methods. This study also investigates the vibration reduction effect of millisecond blasting for cut-blasting under the different classes of surrounding rocks. The results show that the vibration reduction forms of millisecond blasting can be divided into separation and interference of waveform. Based on the principle of superposition of blasting seismic waves, vibration reduction through wave interference is further divided. At the same time, a new vibration reduction mode is proposed. This vibration reduction mode can significantly improve construction efficiency while improving damping efficiency. The new vibration reduction mode can increase the vibration reduction to 80% while improving construction efficiency. Additionally, there is a significant difference in the damping effect of different classes of surrounding rock on the blasting seismic wave. Poor-quality surrounding rock enhances the attenuation of seismic wave velocity and peak stress in the surrounding rock. In the Zhongliangshan Tunnel, a tunnel cut-blasting construction at a depth of 42 m, the best vibration reduction plan of Class III is 3 ms millisecond blasting, in which the surface points achieve separation vibration reduction. The best vibration reduction plan of Class V is 1 ms millisecond blasting, in which the surface points achieve a new vibration reduction mode. During the tunnel blasting construction process, electronic detonators are used for millisecond blasting of the cut-blasting. This method can reduce the vibration effects generated by blasting. The stability of the existing railway is ultimately guaranteed. This can improve construction efficiency while ensuring construction safety. This study can provide significant guidance for the blasting construction of the tunnel through the railway. Full article

In the Kelameili volcanic gas reservoir, primary hydraulic fracturing treatments in some wells take place on a limited scale, resulting in a rapid decline in production post stimulation and necessitating re-fracturing operations. However, prolonged production has led to a significant evolution in the in situ stress field, which complicates the design of re-fracturing parameters. To address this, this study adopts an integrated geology–engineering approach to develop a formation-specific geomechanical model, using rock mechanical test results and well-log inversion to reconstruct the reservoir’s initial stress field. The dynamic stress field simulations and re-fracturing parameter optimization were performed for Block Dixi-14. The results show that stress superposition effects induced by multiple fracturing stages and injection–production cycles have significantly altered the current in situ stress distribution. For Well K6, the optimized re-fracturing parameters comprised a pump rate of 12 m³/min, total fluid volume of 1200 m³, prepad fluid ratio of 50–60%, and proppant volume of 75 m³, and the daily gas production increased by 56% correspondingly, demonstrating the effectiveness of the optimized re-fracturing design. This study not only provides a more realistic simulation framework for fracturing volcanic rock gas reservoirs but also offers a scientific basis for fracture design optimization and enhanced gas recovery. The geology–engineering integrated methodology enables the accurate prediction and assessment of dynamic stress field evolution during fracturing, thereby guiding field operations. Full article

With the large-scale integration of renewable energy sources, traditional distribution networks are gradually evolving into a new form of flexible interconnection distribution networks. To enhance the rapidity and accuracy of power flow control through flexible interconnection devices, there is an increasing demand for precise grid equivalent models. Existing grid equivalent models predominantly adopt single-port configurations for radial networks, while there is limited research on two-port network equivalent models tailored for flexible interconnection distribution networks. Focusing on the scenario of flexible interconnection distribution networks integrated with Rotary Power Flow Controllers (RPFCs), this paper proposes an equivalent modeling method of two-port networks based on the superposition theorem under small disturbance conditions. A flexible interconnection distribution network model incorporating RPFCs and its corresponding two-port equivalent model are developed. The parameters of the two-port equivalent model are derived through superposition theorem calculations, enabling the realization of power decoupling control functionality for RPFCs. The simulation results show that the deviations between the set value of active power and the actual value remains at about 3%, and the deviations between the set value of reactive power and the actual value is between 4% and 7%, thereby verifying the effectiveness of the constructed two-port model in power flow control and further supporting the accuracy of the proposed method. Full article

Field foundation pile loading tests were conducted in the context of an actual bridge pile foundation project. The test data were analyzed to determine the reasons for the variation in the complex geological conditions of the seashore. Moreover, finite element analysis was conducted to evaluate the influence of pile length and diameter on the settlement of coastal friction foundation piles. Increasing the pile length from 65 m to 75 m reduced the settlement by 25.7%, while increasing the diameter from 1.5 m to 2.0 m led to a 35.9% reduction. Increasing the pile spacing reduced the amount of structural settlement. Group pile foundation pile spacings should be 2.5–3.0 D. Pile group superposition reduced the most obvious effects and the settlement reduction rate was the fastest. Under seismic conditions, the pile group foundation exhibited 5.60 times greater horizontal displacement, 3.57 times higher bending moment, and 5.30 times increased shear force relative to static loading. The formula for predicting the settlement of oversized friction pile group foundations was modified based on settlement values calculated using finite elements. The revised formula is suitable for calculating the settlement of friction pile group foundations in coastal areas. Full article

Multibeam echosounder systems (MBESs) are widely used in unmanned surface vehicle swarms (USVs) to perform various marine bathymetry surveys because of their excellent performance. To address the challenges of systematic error superposition and edge beam error propagation in multibeam bathymetry surveying, this study proposes a novel error adjustment method integrating crossover error density clustering and beam incident angle (BIA) compensation. Firstly, a bathymetry error detection model was developed based on adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN). By optimizing the neighborhood radius and minimum sample threshold through analyzing sliding-window curvature, the method achieved the automatic identification of outliers, reducing crossover discrepancies from ±150 m to ±50 m in the deep sea at a depth of approximately 5000 m. Secondly, an asymmetric quadratic surface correction model was established by incorporating the BIA as a key parameter. A dynamic weight matrix ω = 1/(1 + 0.5θ²) was introduced to suppress edge beam errors, combined with Tikhonov regularization to resolve ill-posed matrix issues. Experimental validation in the Western Pacific demonstrated that the RMSE of crossover points decreased by about 30.4% and the MAE was reduced by 57.3%. The proposed method effectively corrects residual systematic errors while maintaining topographic authenticity, providing a reference for improving the quality of multibeam bathymetric data obtained via USVs and enhancing measurement efficiency. Full article

With the increasing severity of traffic congestion, the impact of random traffic patterns has emerged as an indispensable factor in the fatigue design and assessment of highway bridges. In this study, an analytical approach has been proposed for modeling the effects of random traffic patterns on fatigue damage. A fatigue damage ratio, referred to as RPEF, is introduced to establish the correlation between damage and traffic characteristics. Two quantitative parameters representing two characteristics of traffic loads, namely the average loading occurrence number (scale parameter) and the vehicle headway COVs (shape parameter), have been found to be excellent indices for clustering the different dimensional randomness of RPEFs. Based on a comprehensive case study, the realization of using equivalent RPEFs to evaluate bridge fatigue damage under mixed traffic conditions was explored. The results indicate that the actual fatigue damage of bridges can be evaluated through the superposition of different traffic pattern effects, provided that the pattern classification number fits the fluctuations in traffic flow. It is necessary to ensure the rationality of traffic pattern classification for structures with spans greater than 50 m, as an overly simplistic traffic pattern classification may lead to an underestimation of fatigue damage. Full article