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Keywords = internal dynamic model

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12 pages, 908 KiB  
Article
Precision in Motion Management: Long-Term Local Control and Prognostic Insights in SBRT for Oligometastatic Lung and Liver Metastases
by Silke Dirkx, Sven Van Laere, Thierry Gevaert and Mark De Ridder
Viewed by 261
Abstract
Background/Objectives: Inadequate dosing and respiratory motion contribute to local recurrence for oligometastatic disease (OMD). While short-term LC rates are well-documented, data on long-term LC remain limited. This study investigated long-term LC after stereotactic body radiotherapy (SBRT), using respiratory motion management techniques. Methods: [...] Read more.
Background/Objectives: Inadequate dosing and respiratory motion contribute to local recurrence for oligometastatic disease (OMD). While short-term LC rates are well-documented, data on long-term LC remain limited. This study investigated long-term LC after stereotactic body radiotherapy (SBRT), using respiratory motion management techniques. Methods: This retrospective study took place at UZ Brussel with follow-up until Oct 2024. It analyzed oligometastatic patients treated with SBRT between Jul 2012 and Feb 2017. Treatment involved delivering 50 Gy in 10 fractions on the 80% isodose line, building on data from a prior prospective study. Lesion movement was managed using internal target volume (ITV) or dynamic tumor tracking (DTT) with marker. The primary endpoint of the study was long-term LC and identifying variables associated with it using a Cox proportional hazards model. Results: A total of 100 patients were treated for a total of 211 metastatic lesions. Lesions were predominantly in the lungs (74%) and treated using ITV (88%). LC rates at 1, 3, 5, and 10 years were 76.5%, 53.8%, 38.1%, and 36.3%, respectively. Improved LC was observed in locations other than lung and liver (HR: 0.309; p = 0.024) and with increasing age (HR: 0.975; p < 0.010). Worse LC was seen in liver lesions (HR: 1.808; p = 0.103) and systemic therapy post-radiotherapy (HR: 3.726; p < 0.001). No significant associations were found with tumor size or tumor motion, nor between the two motion management strategies used (DTT and ITV). Conclusions: Appropriate motion management is key in LC for OMD. No significant difference in LC was found between both techniques. Lesion location, patient age, and systemic therapy post-radiotherapy were prognostic factors for LC. Full article
(This article belongs to the Special Issue Stereotactic Radiotherapy in Tumor Ablation (Volume II))
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32 pages, 6342 KiB  
Article
Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery
by Monique Bohora Schlickmann, Inacio Thomaz Bueno, Denis Valle, William M. Hammond, Susan J. Prichard, Andrew T. Hudak, Carine Klauberg, Mauro Alessandro Karasinski, Kody Melissa Brock, Kleydson Diego Rocha, Jinyi Xia, Rodrigo Vieira Leite, Pedro Higuchi, Ana Carolina da Silva, Gabriel Maximo da Silva, Gina R. Cova and Carlos Alberto Silva
Remote Sens. 2025, 17(2), 320; https://doi.org/10.3390/rs17020320 - 17 Jan 2025
Viewed by 470
Abstract
Southern U.S. forests are essential for carbon storage and timber production but are increasingly impacted by natural disturbances, highlighting the need to understand their dynamics and recovery. Canopy cover is a key indicator of forest health and resilience. Advances in remote sensing, such [...] Read more.
Southern U.S. forests are essential for carbon storage and timber production but are increasingly impacted by natural disturbances, highlighting the need to understand their dynamics and recovery. Canopy cover is a key indicator of forest health and resilience. Advances in remote sensing, such as NASA’s GEDI spaceborne LiDAR, enable more precise mapping of canopy cover. Although GEDI provides accurate data, its limited spatial coverage restricts large-scale assessments. To address this, we combined GEDI with Synthetic Aperture Radar (SAR), and optical imagery (Sentinel-1 GRD and Landsat–Sentinel Harmonized (HLS)) data to create a comprehensive canopy cover map for Florida. Using a random forest algorithm, our model achieved an R2 of 0.69, RMSD of 0.17, and MD of 0.001, based on out-of-bag samples for internal validation. Geographic coordinates and the red spectral channel emerged as the most influential predictors. External validation with airborne laser scanning (ALS) data across three sites yielded an R2 of 0.70, RMSD of 0.29, and MD of −0.22, confirming the model’s accuracy and robustness in unseen areas. Statewide analysis showed lower canopy cover in southern versus northern Florida, with wetland forests exhibiting higher cover than upland sites. This study demonstrates the potential of integrating multiple remote sensing datasets to produce accurate vegetation maps, supporting forest management and sustainability efforts in Florida. Full article
(This article belongs to the Section Environmental Remote Sensing)
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20 pages, 5191 KiB  
Article
Development of a Small-Working-Volume Plunger Hydraulic Pump with Improved Performance Characteristics
by Alexey N. Beskopylny, Denis Medvedev, Vyacheslav Grishchenko and Evgeniy Ivliev
Actuators 2025, 14(1), 34; https://doi.org/10.3390/act14010034 - 16 Jan 2025
Viewed by 270
Abstract
Current trends in the development of technology are linked inextricably to the increasing level of automation in technological processes and production systems. In this regard, the development of systems for supplying working fluids with adjustable pumps that have high performance characteristics, an increased [...] Read more.
Current trends in the development of technology are linked inextricably to the increasing level of automation in technological processes and production systems. In this regard, the development of systems for supplying working fluids with adjustable pumps that have high performance characteristics, an increased service life and low operating costs is an important scientific and technical task. A primary challenge in the development of such systems lies in achieving low fluid flow rates while maintaining stable operating characteristics. This challenge stems from the fact that currently available controlled hydraulic pumps exhibit either a high cost or suboptimal life and efficiency parameters. This work focuses on the development of a plunger hydraulic pump with a small working volume. A mathematical model has been developed to investigate the characteristics, optimize the design of this pump and further expand the size range of such pumps. The solution was implemented on a computer using the dynamic modelling environment MATLAB/Simulink. In order to verify the mathematical model’s adequacy, a plunger pump prototype was built and integrated with a test bench featuring a measurement system. The test results showed higher pump efficiency and a significant reduction in hydraulic losses. An analysis of the obtained data shows that the pump is characterized by increased efficiency due to optimal flow distribution and reduced internal leakage, which makes it promising for use in hydraulic systems requiring improved operating characteristics. The developed pump has more rational characteristics compared to existing alternatives for use in water supply systems for induction superheaters. The experimental external characteristics of the developed pump are 10% higher than the external characteristics of the ULKA EX5 pump selected as an analogue, and the pressure characteristics are 65% higher. It offers production costs that are several times lower compared to existing cam-type plunger or diaphragm pumps with oil sumps and precision valve mechanisms. Additionally, it has significantly better operating characteristics and a longer service life compared to vibrating plunger pumps. Full article
(This article belongs to the Section Control Systems)
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33 pages, 3898 KiB  
Article
Effects of Predation-Induced Emigration on a Landscape Ecological Model
by James T. Cronin, Nalin Fonseka, Jerome Goddard, Ratnasingham Shivaji and Xiaohuan Xue
Viewed by 309
Abstract
Predators impact prey populations directly through consumption and indirectly via trait-mediated effects like predator-induced emigration (PIE), where prey alter movement due to predation risk. While PIE can significantly influence prey dynamics, its combined effect with direct predation in fragmented habitats is underexplored. Habitat [...] Read more.
Predators impact prey populations directly through consumption and indirectly via trait-mediated effects like predator-induced emigration (PIE), where prey alter movement due to predation risk. While PIE can significantly influence prey dynamics, its combined effect with direct predation in fragmented habitats is underexplored. Habitat fragmentation reduces viable habitats and isolates populations, necessitating an understanding of these interactions for conservation. In this paper, we present a reaction–diffusion model to investigate prey persistence under both direct predation and PIE in fragmented landscapes. The model considers prey growing logistically within a bounded habitat patch surrounded by a hostile matrix. Prey move via unbiased random walks internally but exhibit biased movement at habitat boundaries influenced by predation risk. Predators are assumed constant, operating on a different timescale. We examine three predation functional responses—constant yield, Holling Type I, and Holling Type III—and three emigration patterns: density-independent, positive density-dependent, and negative density-dependent emigration. Using the method of sub- and supersolutions, we establish conditions for the existence and multiplicity of positive steady-state solutions. Numerical simulations in one-dimensional habitats further elucidate the structure of these solutions. Our findings demonstrate that the interplay between direct predation and PIE crucially affects prey persistence in fragmented habitats. Depending on the functional response and emigration pattern, PIE can either mitigate or amplify the impact of direct predation. This underscores the importance of incorporating both direct and indirect predation effects in ecological models to better predict species dynamics and inform conservation strategies in fragmented landscapes. Full article
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28 pages, 11467 KiB  
Article
Design Guidelines for Fractional Order Cascade Control in DC Motors: A Computational Analysis on Pairing Speed and Current Loop Orders Using Oustaloup’s Recursive Method
by Marta Haro-Larrode and Alvaro Gomez-Jarreta
Viewed by 231
Abstract
Nested, or cascade speed and torque control has been widely used for DC motors over recent decades. Simultaneously, fractional-order control schemes have emerged, offering additional degrees of control. However, adopting fractional-order controllers, particularly in cascade schemes, does not inherently guarantee better performance. Poorly [...] Read more.
Nested, or cascade speed and torque control has been widely used for DC motors over recent decades. Simultaneously, fractional-order control schemes have emerged, offering additional degrees of control. However, adopting fractional-order controllers, particularly in cascade schemes, does not inherently guarantee better performance. Poorly paired fractional exponents for inner and outer PI controllers can worsen the DC motor’s behavior and controllability. Finding appropriate combinations of fractional exponents is therefore crucial to minimize experimental costs and achieve better dynamic response compared to integer-order cascade control. Additionally, mitigating adverse couplings between speed and current loops remains an underexplored area in fractional-order control design. This paper develops a computational model for fractional-order cascade control of DC motor speed (external) and current (internal) loops to derive appropriate combinations of internal and external fractional orders. Key metrics such as overshoot, rise time, and peak current values during speed and torque changes are analyzed, along with coupled variables like speed drop during torque steps and peak torque during speed steps. The proposed maps guide the selection of effective combinations, enabling readers to deduce robust or adaptive designs depending on specific performance needs. The methodology employs Oustaloup’s recursive approximation to model fractional-order elements, with MATLAB–SIMULINK simulations validating the proposed criteria. Full article
(This article belongs to the Section Electrical Machines and Drives)
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17 pages, 1748 KiB  
Article
Startup Survival Forecasting: A Multivariate AI Approach Based on Empirical Knowledge
by Francesc Font-Cot, Pablo Lara-Navarra, Claudia Sánchez-Arnau and Enrique A. Sánchez-Pérez
Information 2025, 16(1), 61; https://doi.org/10.3390/info16010061 - 16 Jan 2025
Viewed by 312
Abstract
Predicting the survival of startups is a complex challenge due to the multifaceted nature of entrepreneurial ecosystems and the dynamic interplay of internal and external factors. Despite advances in empirical research, existing models often lack integration with robust conceptual frameworks. This study addresses [...] Read more.
Predicting the survival of startups is a complex challenge due to the multifaceted nature of entrepreneurial ecosystems and the dynamic interplay of internal and external factors. Despite advances in empirical research, existing models often lack integration with robust conceptual frameworks. This study addresses these gaps by developing a multivariate AI-driven model for predicting startup survival, leveraging Lipschitz extensions, neural networks, and linear regression. Using a dataset of 20 startups, selected across diverse industries and evaluated on attributes such as team dynamics, market conditions, and financial metrics, the model demonstrated high accuracy and clustering capabilities. Key findings highlight the pivotal role of team dynamics and product differentiation in determining survival probabilities. By integrating conceptual insights with empirical data, the study bridges gaps in existing literature and offers a practical decision-making tool for entrepreneurs, investors, and policymakers. These findings underscore the importance of fostering collaborative, innovative ecosystems to enhance entrepreneurial success and societal well-being. Full article
(This article belongs to the Special Issue New Information Communication Technologies in the Digital Era)
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18 pages, 4557 KiB  
Article
Dynamic Simulation of Photothermal Environment in Solar Greenhouse Based on COMSOL Multiple Physical Fields
by Huan Liu, Fankun Meng, Zhengnan Yan, Yuliang Shi, Subo Tian, Yanjie Yang and Xiaoye Li
Agriculture 2025, 15(2), 187; https://doi.org/10.3390/agriculture15020187 - 16 Jan 2025
Viewed by 264
Abstract
Solar greenhouses are essential facilities for agricultural production in northern China, where uneven internal environments pose significant challenges. This study established a numerical model of photothermal conditions in solar greenhouses. Utilizing COMSOL MultiphysicsTM, we established a microclimate model that encompasses the [...] Read more.
Solar greenhouses are essential facilities for agricultural production in northern China, where uneven internal environments pose significant challenges. This study established a numerical model of photothermal conditions in solar greenhouses. Utilizing COMSOL MultiphysicsTM, we established a microclimate model that encompasses the greenhouse exterior and the soil directly below it, without considering the crops. This model coupled multiphysical fields with fluid flow and heat transfer processes. The boundary conditions and initial values of the external environment and soil were derived from meteorological data and an efficient interpolation function method, with the time step updated every 1h. The results demonstrate that the simulated values were in good agreement with the measured values. Our findings reveal the temporal dynamics of radiation and temperature changes, as well as spatial heterogeneity, within solar greenhouses under different winter weather conditions. Additionally, the potential of integrating with other real-time monitoring and control models was discussed. This study provides a theoretical foundation for developing microclimate models and predicting photothermal environments in greenhouses. Full article
(This article belongs to the Special Issue Research on Plant Production in Greenhouse and Plant Factory Systems)
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16 pages, 6259 KiB  
Article
Research into the Longitudinal Loading of an Improved Load-Bearing Structure of a Flat Car for Container Transportation
by Juraj Gerlici, Alyona Lovska and Kristína Kozáková
Viewed by 266
Abstract
Container transport is one of the most promising modes of international freight transport. Railway container transport is mainly carried out using flat cars. Container cars can be damaged under the most unfavorable operating load conditions of a 1520 mm track gauge, i.e., shunting [...] Read more.
Container transport is one of the most promising modes of international freight transport. Railway container transport is mainly carried out using flat cars. Container cars can be damaged under the most unfavorable operating load conditions of a 1520 mm track gauge, i.e., shunting collisions. In this context, an improvement to the supporting structure of flat cars is proposed to ensure their strength, involving the installation of special superstructures in their cantilever parts to limit the movement of the containers. The choice of the superstructure profiles was made on the basis of the section modulus of their components. Mathematical modeling of the dynamic loading of a flat car with containers in the event of a shunting collision was carried out. The determined value of acceleration was taken into account in the calculation of the strength of the load-bearing structure of the flat car. It was found that the maximum stresses were 24% lower than the allowable stresses. Therefore, the strength condition of the flat car was met. The results of this study will contribute to reducing damage to container transport vehicles in service, to the formulation of recommendations for their construction and to an increase in their profitability, including in international transport. Full article
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29 pages, 8040 KiB  
Article
Seismic Mitigation Effect and Mechanism Analysis of Split Columns in Underground Structures in Sites with Weak Interlayers
by Zigang Xu and Zongyao Xia
Appl. Sci. 2025, 15(2), 798; https://doi.org/10.3390/app15020798 - 15 Jan 2025
Viewed by 289
Abstract
The seismic damage of underground structures has been extensively investigated, and it has been demonstrated that underground structures located at weak interlayer sites are more prone to damage. In this study, a two-story two-span rectangular frame subway station structure is analyzed. A two-dimensional [...] Read more.
The seismic damage of underground structures has been extensively investigated, and it has been demonstrated that underground structures located at weak interlayer sites are more prone to damage. In this study, a two-story two-span rectangular frame subway station structure is analyzed. A two-dimensional soil-underground structure model is developed using the large-scale finite element analysis software ABAQUS. The equivalent linear soil-underground structure dynamic time-history analysis method is employed to examine the seismic response of underground structures at weak interlayer sites. Variations in the thickness and shear wave velocity of the weak interlayer soil are analyzed. The seismic mitigation effects of split columns and prototype columns in underground structures at weak interlayer sites are systematically compared. The findings indicate that the relative displacement and internal force of key structural components significantly increase when the weak interlayer intersects the underground structure. Furthermore, as the thickness of the interlayer increases, the displacement and internal force also escalate. When the thickness of the weak interlayer remains constant and the shear wave velocity decreases, the relative displacement and internal force of the key structural components gradually intensify. Replacing ordinary columns with split columns substantially reduces the internal force of the middle column, providing an effective seismic mitigation measure for underground structures. Full article
(This article belongs to the Special Issue Seismic Analysis and Design of Ocean and Underground Structures)
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20 pages, 3334 KiB  
Article
Interpretable State Estimation in Power Systems Based on the Kolmogorov–Arnold Networks
by Shuaibo Wang, Wenhao Luo, Sixing Yin, Jie Zhang, Zhuohang Liang, Yihua Zhu and Shufang Li
Electronics 2025, 14(2), 320; https://doi.org/10.3390/electronics14020320 - 15 Jan 2025
Viewed by 323
Abstract
Power system state estimation is a critical task for ensuring stable grid operation and serves as the foundation of grid control and analysis. Conventional approaches largely involve field measurements, network topology, and manual anomaly detection, which present significant limitations, particularly while dealing with [...] Read more.
Power system state estimation is a critical task for ensuring stable grid operation and serves as the foundation of grid control and analysis. Conventional approaches largely involve field measurements, network topology, and manual anomaly detection, which present significant limitations, particularly while dealing with dynamic and complex power systems. In recent years, deep learning techniques have been progressively applied in this field to overcome the shortcomings of conventional approaches, which are based on mathematical models and static analysis. However, existing deep learning techniques primarily focus on power system security analysis and computational resource management. In spite of the powerful capabilities in supervised learning tasks, the lack of interpretability still makes deep learning models less convincing, and thus might hinder their practical applications. In response to this issue, we apply a computational model for power system state estimation based on the Kolmogorov–Arnold network (KAN) model with learnable activation functions, visualization capabilities, and pruning features. From the perspective of feature interpretability, we find the influence of bus features on the model output, such as bus voltage magnitude. Moreover, through analysis of the internal structure of the model, we uncover a possibility of potential mechanisms of power system state estimation. Experimental results show that our study not only enhances the interpretability of power system state estimation but also effectively ensures grid security and stability through state estimation. Full article
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33 pages, 1886 KiB  
Article
Hybrid Plant Growth: Integrating Stochastic, Empirical, and Optimization Models with Machine Learning for Controlled Environment Agriculture
by Nezha Kharraz and István Szabó
Viewed by 339
Abstract
Controlled Environment Agriculture (CEA) offers a viable solution for sustainable crop production, yet the optimization of the latter requires precise modeling and resource management. This study introduces a novel hybrid plant growth model integrating stochastic, empirical, and optimization approaches, using Internet of Things [...] Read more.
Controlled Environment Agriculture (CEA) offers a viable solution for sustainable crop production, yet the optimization of the latter requires precise modeling and resource management. This study introduces a novel hybrid plant growth model integrating stochastic, empirical, and optimization approaches, using Internet of Things sensors for real-time data collection. Unlike traditional methods, the hybrid model systematically captures environmental variability, simulates plant growth dynamics, and optimizes resource inputs. The prototype growth chamber, equipped with IoT sensors for monitoring environmental parameters such as light intensity, temperature, CO2, humidity, and water intake, was primarily used to provide accurate input data for the model and specifically light intensity, water intake and nutrient intake. While experimental tests on lettuce were conducted to validate initial environmental conditions, this study was focused on simulation-based analysis. Specific tests simulated plant responses to varying levels of light, water, and nutrients, enabling the validation of the proposed hybrid model. We varied light durations between 6 and 14 h/day, watering levels between 5 and 10 L/day, and nutrient concentrations between 3 and 11 g/day. Additional simulations modeled different sowing intervals to capture internal plant variability. The results demonstrated that the optimal growth conditions were 14 h/day of light, 9 L/day of water, and 5 g/day of nutrients; maximized plant biomass (200 g), leaf area (800 cm2), and height (90 cm). Key novel metrics developed in this study, the Growth Efficiency Ratio (GER) and Plant Growth Index (PGI), provided solid tools for evaluating plant performance and resource efficiency. Simulations showed that GER peaked at 0.6 for approximately 200 units of combined inputs, beyond which diminishing returns were observed. PGI increased to 0.8 to day 20 and saturated to 1 by day 30. The role of IoT sensors was critical in enhancing model accuracy and replicability by supplying real-time data on environmental variability. The hybrid model’s adaptability in the future may offer scalability to diverse crop types and environmental settings, establishing a foundation for its integration into decision-support systems for large-scale indoor farming. Full article
(This article belongs to the Special Issue Application of Internet of Things in Agroecosystems)
19 pages, 4952 KiB  
Article
Optimization Research on the Performance of the RC-DTH Air Hammer Based on Computational Fluid Dynamics
by Zihao Liu, Yongjiang Luo, Wenchao He, Rui Tao, Jiangfu He, Yongliang Sun, Hongwei Chen and Qianting Hu
Appl. Sci. 2025, 15(2), 740; https://doi.org/10.3390/app15020740 - 13 Jan 2025
Viewed by 416
Abstract
To optimize the performance of the RC-DTH air hammer, a mathematical model detailing each phase of the piston’s movement has been constructed in the present work. Simultaneously, a novel piston structure of the RC-DTH air hammer (Type B) with diverse internal flow has [...] Read more.
To optimize the performance of the RC-DTH air hammer, a mathematical model detailing each phase of the piston’s movement has been constructed in the present work. Simultaneously, a novel piston structure of the RC-DTH air hammer (Type B) with diverse internal flow has been proposed. The impact performance of the structurally modified RC-DTH hammer is analyzed using Computational Fluid Dynamics (CFD). Additionally, an impact energy testing system for the RC-DTH air hammer is developed to confirm the validity of the numerical simulation results. Research results have shown that enhancing both the intake stroke of the upper chamber (F1) and the outlet stroke of the lower chamber (R2) of the RC-DTH air hammer piston can effectively improve the piston’s impact performance. Conversely, increasing the inlet stroke of the lower chamber (R1) and the outlet stroke of the upper chamber (F2) tends to diminish the piston’s impact performance. Moreover, the quality of the piston influences its striking frequency while having a minimal impact on single-impact energy. As the piston quality increases, the power of the impact diminishes. Once the piston valve stroke parameters are optimized, its impact performance is enhanced by 20.32%. Compared to the GQ89 hammer, the Type B hammer exhibits an 84% increase in impact energy and a 74% increase in impact power. Full article
18 pages, 6472 KiB  
Article
The Temporal and Spatial Evolution of Flow Heterogeneity During Water Flooding for an Artificial Core Plate Model
by Chen Jiang, Qingjie Liu, Kaiqi Leng, Zubo Zhang, Xu Chen and Tong Wu
Energies 2025, 18(2), 309; https://doi.org/10.3390/en18020309 - 12 Jan 2025
Viewed by 360
Abstract
In the process of reservoir water flooding development, the characteristics of underground seepage field have changed, resulting in increasingly complex oil–water distribution. The original understanding of reservoir physical property parameters based on the initial stage of development is insufficient to guide reservoir development [...] Read more.
In the process of reservoir water flooding development, the characteristics of underground seepage field have changed, resulting in increasingly complex oil–water distribution. The original understanding of reservoir physical property parameters based on the initial stage of development is insufficient to guide reservoir development efforts in the extra-high water cut stage. To deeply investigate the spatio-temporal evolution of heterogeneity in the internal seepage field of layered reservoirs during water flooding development, water–oil displacement experimental simulations were conducted based on layered, normally graded models. By combining CT scanning technology and two-phase seepage theory, the variation patterns of heterogeneity in the seepage field of medium-to-high permeability, normally graded reservoirs were analyzed. The results indicate that the effectiveness of water flooding development is doubly constrained by differences in oil–water seepage capacities and the heterogeneity of the seepage field. During the development process, both the reservoir’s flow capacity and the heterogeneity of the seepage field are in a state of continuous change. Influenced by the extra resistance brought about by multiphase flow, the reservoir’s flow capacity drops to 41.6% of the absolute permeability in the extra-high water cut stage. Based on differences in the variation amplitudes of oil–water-phase permeabilities, changes in the heterogeneity of the internal seepage field of the reservoir can be broadly divided into periods of drastic change and relative stability. During the drastic change stage, the fluctuation amplitude of the water-phase permeability variation coefficient is 114.5 times that of the relative stable phase, while the fluctuation amplitude of the oil-phase permeability variation coefficient is 5.2 times that of the stable stage. This study reveals the dynamic changes in reservoir seepage characteristics during the water injection process, providing guidance for water injection development in layered reservoirs. Full article
(This article belongs to the Section H: Geo-Energy)
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23 pages, 6888 KiB  
Article
Tuning of a Viscous Inerter Damper: How to Achieve Resonant Damping Without a Damper Resonance
by Jan Høgsberg
Appl. Sci. 2025, 15(2), 676; https://doi.org/10.3390/app15020676 - 11 Jan 2025
Viewed by 575
Abstract
Inerter dampers are effectively employed to mitigate and dampen structural vibrations in slender or high-rise buildings. The simple viscous inerter damper, with a viscous dashpot placed in series with an inerter, is designed to create resonant vibration damping, although the damper itself is [...] Read more.
Inerter dampers are effectively employed to mitigate and dampen structural vibrations in slender or high-rise buildings. The simple viscous inerter damper, with a viscous dashpot placed in series with an inerter, is designed to create resonant vibration damping, although the damper itself is without an internal resonance. The apparent resonant behavior is instead obtained by increasing the damper inertance until the two lowest modes of the considered building model interact, whereafter the viscous coefficient is adjusted until the desired response mitigation is achieved. The present modal interaction tuning requires that the reduced-order single-mode dynamic model of the building includes both inertia and flexibility from the (other) modes otherwise discarded by the model reduction. While the inertia correction adjusts the modal mass of the inerter damper, the corresponding flexibility introduces the apparent damper stiffness that creates the desired damper resonance. Thus, the accurate representation of other modes is essential for the design and resonant tuning of the simple viscous inerter damper. The resonant damper performance by the non-resonant viscous inerter damper is illustrated by a numerical example with a 20-story building model, for which the desired resonant modal interaction requires an inertance of almost ten times the entire translational building mass. Full article
(This article belongs to the Special Issue Vibration Monitoring and Control of the Built Environment)
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20 pages, 659 KiB  
Article
Risk Assessment in Mass Housing Projects Using the Integrated Method of Fuzzy Shannon Entropy and Fuzzy EDAS
by Seyed Morteza Hatefi, Hanieh Ahmadi and Jolanta Tamošaitienė
Sustainability 2025, 17(2), 528; https://doi.org/10.3390/su17020528 - 11 Jan 2025
Viewed by 505
Abstract
Mass building projects play a key role in the economic prosperity of any country. Furthermore, these projects are among the main drivers of environmental and social problems. In recent years, with the spread of the concept of sustainable development in the life cycle [...] Read more.
Mass building projects play a key role in the economic prosperity of any country. Furthermore, these projects are among the main drivers of environmental and social problems. In recent years, with the spread of the concept of sustainable development in the life cycle of construction projects and the dynamic and eventful nature of these projects, the issue of risk management in the sustainable construction industry has received more and more attention among researchers. The construction industry, like other industries, faces various risks. Therefore, it is crucial to identify and evaluate risks in mass construction projects due to the high volume of work. In this study, an integrated model based on fuzzy Shannon entropy and fuzzy EDAS is proposed for risk assessment in large-scale building projects. Initially, by reviewing related articles, 66 effective sub-indicators are identified and classified into 18 risk categories, including 6 external risks and 12 internal risks. Subsequently, a questionnaire is designed to assess the three factors of detection, probability of occurrence, and severity risks for each risk index. This questionnaire distributes to 15 mass production companies in the construction field in Isfahan. The fuzzy Shannon entropy method is then applied to determine the weight of risk factors. The weights of each factor, detection, probability of occurrence, and severity, are calculated as 0.386, 0.342, and 0.273, respectively. These weights are used in the fuzzy EDAS method to prioritize the identified risks in mass-building projects. The results of the fuzzy EDAS method determined the three most critical risks: “inflation rate volatility”, “import/export restrictions”, and “unforeseen climatic conditions”. Additionally, three low-risk sub-indicators are obtained: “limitation on working hours”, “collapse of the structure”, and “unpredictable fire”. Full article
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