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The occurrence frequency and catastrophe caused by flooding are increasing rapidly, highlighting the importance of real‐time impact‐based forecasting. However, traditional approaches primarily based on hydrodynamic models need large computational cost and generally fail to achieve real‐time flood mapping, especially for large‐scale watersheds. In this work, a novel, simple and convenient approach called Topography‐based Flood Inundation Mapping (TOPFIM) is developed to achieve rapid and accurate flood mapping. TOPFIM is characterized by an adaptive river segmentation method and a dynamic inundation volume allocation approach adhering full water volume constraint. The proposed approach is applied to the upper reaches of the Le'an River basin, China, and HEC‐RAS is employed as the benchmark for comparison. The results demonstrate that TOPFIM's simulation accuracy for inundation extent approaches that of hydrodynamic models, with an averaged critical success index of 0.83 and hit rate of 0.90 compared to HEC‐RAS's simulation. Moreover, TOPFIM generates flood inundation mapping prediction within 10 s rather than hours required by conventional hydrodynamic models. It signifies a pivotal practical enhancement that has the potential to effectively preserve lives and protect assets in times of flood emergencies. Overall, as a simple and convenient tool, TOPFIM demonstrates its potential for real‐time flood inundation mapping and risk analysis. Plain Language Summary Predicting the flooding inundation quickly and accurately can significantly reduce the losses caused by flooding. However, the current approaches relying on hydrodynamic models to simulate the movement of water are generally time‐consuming. This paper proposes a new method, called Topography‐based Flood Inundation Mapping (TOPFIM), which achieves fast and accurate flood mapping via a series of revision and integration based on Height Above the Nearest Drainage approach. The case study demonstrates that TOPFIM can achieve accurate flood mapping within 10 s, which is faster by a factor of 1,410 times compared to HEC‐RAS 2D over the study area of 1,716.57 km2. The notable accuracy and efficiency of TOPFIM underlines its potential for real‐time flood inundation mapping and risk analysis. Key Points Proposed a novel Topography‐based approach for Real‐Time Flood Inundation Mapping (TOPFIM) TOPFIM adapts to river segments and allocates flood volume based on topographical features by considering the water volume constraints TOPFIM has higher computational efficiency with accuracy approximating to hydrodynamic model

In this paper, we propose a queueing model to describe traffic breakdown phenomena caused by perturbations of on-ramp merging vehicles. In congested mainline traffic flow, we assume that a merging vehicle will trigger a jam queue formulation. If this jam queue cannot dissipate before the next vehicle merges into the main road, it could grow into a wide jam and eventually result in traffic breakdown. Different from many existing models that focused on the propagation of jam waves, the proposed model emphasizes the size evolution of a jam queue (local congested vehicle cluster) instead of its spatial evolutions. This new approach reduces analysis difficulties and allows us to directly link microscopic driving behaviors with macroscopic breakdown phenomena. Test results show that the simulated breakdown probability curve (parameter tuning using Next Generation Simulation vehicular trajectories) fits with the empirical breakdown probability curve that is estimated by Performance Measurement System (PeMS) data. This indicates that this new model can account for the probability of breakdown phenomena and help us set an appropriate inflow rate so as to void breakdown and meanwhile maintain a high road capacity.

Precise modeling of differential drive robots is crucial for effective control and trajectory planning in autonomous systems. A comparative analysis of two modeling approaches for a four-wheel differential drive robot is presented in this paper. The first approach, named Motor-Based Model (MBM), identifies four transfer functions, one for each motor, while the second approach, named Simplified Model (SM), uses only two transfer functions, one for linear velocity and another for angular velocity. Both models were validated by comparing their predicted trajectories against real odometry data obtained from a SLAM system implemented on a differential-drive robot. This provided a practical assessment of each model’s accuracy and underscored the importance of model selection in control design and navigation tasks. The results showed that the Motor-Based Model (MBM) consistently outperformed the Simplified Model (SM) in terms of odometry accuracy, both in position and orientation. Across all trajectories, the average RMSE for position using MBM was 0.309 m, while the SM recorded a higher average RMSE of 0.414 m. Similarly, the maximum position error averaged 0.522 m for MBM and 0.710 m for SM, confirming that MBM is more accurate and consistent in position tracking. Regarding the results of orientation estimation, when averaged across all experiments, the MBM maintained a lower angular RMSE of 0.170 rad in contrast to SM, which achieves an RMSE of 0.239 rad. The maximum angular error was also higher for the MBM at 0.316 rad, compared to 0.447 rad for the SM. Moreover, the computational performance evaluation indicated that the SM consistently outperformed MBM, achieving a 30% reduction in simulation time and substantially lower memory usage. These results demonstrate the relationship between model complexity and accuracy and suggest that the motor-specific model is more appropriate for applications requiring precise mapping or localization, such as SLAM, while the simplified model may be suitable for simpler use cases with lower computational requirements, such as embedded systems with limited resources. This paper provides a practical evaluation of the accuracy and computational performance of two modeling approaches, highlighting the implications of model selection for the design of navigation tasks.

Because of the introduction of significant amounts of electricity from intermittent energy, such as solar and wind, on power grids, hydraulic turbines undergo more transient operation with varying rotation speeds. Start and stop sequences are known to induce significant mechanical stress in the runner, decreasing its lifespan. Complex fluid–structure interactions are responsible for those high-stress levels, but the precise mechanisms are still elusive, even if many experimental and numerical studies were devoted to the subject. One possible mechanism identified through limited measurements on large turbines operating in powerhouses is rotor–stator interactions. It is already known that rotor–stator interaction (RSI) in constant-speed operating conditions can lead to runner failure when the RSI frequency is close to the natural frequencies of specific structural modes. Start and stop sequence investigations show that RSI can induce a transient resonance while the runner is accelerating/decelerating, which generates a frequency sweep that excites the structure. Studying transient RSI-induced resonance of structural modes associated with hydraulic turbine runners is complex because of the geometry and the potential impacts from other flow-induced excitations. This paper presents the development and validation of an experimental setup specifically designed to reproduce RSI-induced resonances in a rotating circular structure with cyclic periodicity mimicking the structural behavior of a Francis runner. Such a setup does not exist in the literature and will be beneficial for studying RSI during speed variations, with the potential to provide valuable insights into the dynamic behavior of turbines during transient conditions. The paper outlines the different design steps and the construction and validation of the experiment and its simplified runner. It presents important results from preliminary analyses that outline the approach’s success in investigating transient RSI in hydraulic turbines.

The paper proposes two mathematical models of a photo-voltaic (PV) cell—the complete model and the simplified model—which can be used also for modeling a PV module or a PV string under any environmental condition. Both of them are based on the well-known five-parameters model, while the approach allows to write a new descriptive equation, whose terms are functions of the information always available in the modern datasheet of a PV module’s manufacturer. This implies that no pre-processing of the datasheet parameters is needed to use the proposed model, whichever the solar irradiance and the cell/module temperature are. Moreover, these models are interpreted from a circuital point of view, providing the electrical circuits constituted only by basic electrical components. Particularly, in order to take into account the variability of the environment parameters, several variable resistors and voltage-controlled sources are used. The proposed models are tested with the datasheet parameters of commercial PV modules.

Energy balance of the photovoltaic system is influenced by many factors. In this article the effect of tilt and azimuth angle changes of the photovoltaic system energy production is analyzed. These parameters have significant impact on the amount of solar radiation which hits on the photovoltaic panel surface and therefore also on the energy absorbed by the module surface. The main aim of research was identification of the optimal position of photovoltaic system installation in the southern Slovakia regions. The experimental apparatus had two setups consisting of polycrystalline photovoltaic modules. The first setup was used for identification of the tilt angle changes in the range (0–90°). The second one was focused on the detection of the azimuth angle effect to the energy production. The measurement results were statistically processed and mathematically analyzed. Obtained dependencies are presented as two-dimensional and three-dimensional graphical relations. Regression equations characterize time relations between the tilt or azimuth angle and the energy produced by the photovoltaic system in Southern Slovakia. Obtained simplified mathematical model was verified by analytical model. Presented models can be used for the dimensioning and optimization of the photovoltaic system energy production.

The idea that enzymes catalyze reactions by dynamical coupling between the conformational motions and the chemical coordinates has recently attracted major experimental and theoretical interest. However, experimental studies have not directly established that the conformational motions transfer energy to the chemical coordinate, and simulating enzyme catalysis on the relevant timescales has been impractical. Here, we introduce a renormalization approach that transforms the energetics and dynamics of the enzyme to an equivalent low-dimensional system, and allows us to simulate the dynamical coupling on a ms timescale. The simulations establish, by means of several independent approaches, that the conformational dynamics is not remembered during the chemical step and does not contribute significantly to catalysis. Nevertheless, the precise nature of this coupling is a question of great importance.

Currently, floating offshore wind is experiencing rapid development towards a commercial scale. However, the research to design new control strategies requires numerical models of low computational cost accounting for the most relevant dynamics. In this paper, a reduced linear time-domain model is presented and validated. The model represents the main floating offshore wind turbine dynamics with four planar degrees of freedom: surge, heave, pitch, first tower fore-aft deflection, and rotor speed to account for rotor dynamics. The model relies on multibody and modal theories to develop the equation of motion. Aerodynamic loads are calculated using the wind turbine power performance curves obtained in a preprocessing step. Hydrodynamic loads are precomputed using a panel code solver and the mooring forces are obtained using a look-up table for different system displacements. Without any adjustment, the model accurately predicts the system motions for coupled stochastic wind–wave conditions when it is compared against OpenFAST, with errors below 10% for all the considered load cases. The largest errors occur due to the transient effects during the simulation runtime. The model aims to be used in the early design stages as a dynamic simulation tool in time and frequency domains to validate preliminary designs. Moreover, it could also be used as a control design model due to its simplicity and low modeling order.

Dou-gong is important component of ancient timber buildings in China, Japan, and South Korea, etc. It has important decoration and load transferring functions. Due to its complex structure, Dou-gong is difficult to be fully analyzed in large-scale structured. Therefore, it is necessary to establish a reliable and simplified Dou-gong calculation model. In this study, some traditional Chinese timber buildings built in the Song and Yuan dynasties (960–1368 AD) are investigated, and the characteristics of the typical Dou-gong model are obtained. Experimental study and refined finite-element analysis of the typical Dou-gong model is then carried out to study the load transferring mechanism under horizontal load. Then, the load path is extracted from the force-flow perspective to establish a simplified beam element model. The simplified model is then numerically and experimentally verified. The results show that the simplified model has a good consistency with the experimental model, and it is suitable for large-scale structural analysis of ancient timber buildings.

Modular lightweight shear walls can not only facilitate easy installation, thereby improving construction efficiency, but also demonstrate potential to enhance the lateral stiffness when applied in frame structures. The aim of this paper is to investigate the effectiveness of a novel modular cold-formed steel (CFS) shear wall connected with rectangular steel tubes on improving the lateral performance of existing frame structures. Based on the test results of the lateral resistance of four full-scale specimens of modular CFS shear walls connected with rectangular steel tubes, the fine model and simplified model of test specimens were respectively established by the SAP2000v26.0.0 software. The performance indices of the yield load, yield displacement, peak load, peak displacement, and ductility factor were compared, and the maximum error of performance indices was satisfactory. The numerical results show that both the fine and simplified models can well simulate the deformation of walls under lateral cyclic loading, while the simplified models substantially simplify the calculation, which is more adaptable to the subsequent analysis of the multi-story building structure. Then, seismic response analyses of a frame with infilled modular walls and another frame without infilled modular walls were performed. The results indicate that, under the same seismic condition, the lateral displacements of the top floor of the six-story frame with infilled modular walls were reduced by 11–71%, and the maximum inter-story displacement angles were reduced by 15–67% compared to the frame without infilled walls. Therefore, it is demonstrated that the infilled modular CFS shear walls can significantly improve the lateral stiffness and the seismic performance of the steel frame structures.