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Search Results (1,453)

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Keywords = geometric configuration

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24 pages, 2751 KiB  
Article
Double Wishbone Suspension: A Computational Framework for Parametric 3D Kinematic Modeling and Simulation Using Mathematica
by Muhammad Waqas Arshad, Stefano Lodi and David Q. Liu
Technologies 2025, 13(8), 332; https://doi.org/10.3390/technologies13080332 (registering DOI) - 1 Aug 2025
Abstract
The double wishbone suspension (DWS) system is widely used in automotive engineering because of its favorable kinematic properties, which affect vehicle dynamics, handling, and ride comfort; hence, it is important to have an accurate 3D model, simulation, and analysis of the system in [...] Read more.
The double wishbone suspension (DWS) system is widely used in automotive engineering because of its favorable kinematic properties, which affect vehicle dynamics, handling, and ride comfort; hence, it is important to have an accurate 3D model, simulation, and analysis of the system in order to optimize its design. This requires efficient computational tools for parametric study. The development of effective computational tools that support parametric exploration stands as an essential requirement. Our research demonstrates a complete Wolfram Mathematica system that creates parametric 3D kinematic models and conducts simulations, performs analyses, and generates interactive visualizations of DWS systems. The system uses homogeneous transformation matrices to establish the spatial relationships between components relative to a global coordinate system. The symbolic geometric parameters allow designers to perform flexible design exploration and the kinematic constraints create an algebraic equation system. The numerical solution function NSolve computes linkage positions from input data, which enables fast evaluation of different design parameters. The integrated 3D visualization module based on Mathematica’s manipulate function enables users to see immediate results of geometric configurations and parameter effects while calculating exact 3D coordinates. The resulting robust, systematic, and flexible computational environment integrates parametric 3D design, kinematic simulation, analysis, and dynamic visualization for DWS, serving as a valuable and efficient tool for engineers during the design, development, assessment, and optimization phases of these complex automotive systems. Full article
(This article belongs to the Section Manufacturing Technology)
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25 pages, 11545 KiB  
Article
Workpiece Coordinate System Measurement for a Robotic Timber Joinery Workflow
by Francisco Quitral-Zapata, Rodrigo García-Alvarado, Alejandro Martínez-Rocamora and Luis Felipe González-Böhme
Buildings 2025, 15(15), 2712; https://doi.org/10.3390/buildings15152712 (registering DOI) - 31 Jul 2025
Abstract
Robotic timber joinery demands integrated, adaptive methods to compensate for the inherent dimensional variability of wood. We introduce a seamless robotic workflow to enhance the measurement accuracy of the Workpiece Coordinate System (WCS). The approach leverages a Zivid 3D camera mounted in an [...] Read more.
Robotic timber joinery demands integrated, adaptive methods to compensate for the inherent dimensional variability of wood. We introduce a seamless robotic workflow to enhance the measurement accuracy of the Workpiece Coordinate System (WCS). The approach leverages a Zivid 3D camera mounted in an eye-in-hand configuration on a KUKA industrial robot. The proposed algorithm applies a geometric method that strategically crops the point cloud and fits planes to the workpiece surfaces to define a reference frame, calculate the corresponding transformation between coordinate systems, and measure the cross-section of the workpiece. This enables reliable toolpath generation by dynamically updating WCS and effectively accommodating real-world geometric deviations in timber components. The workflow includes camera-to-robot calibration, point cloud acquisition, robust detection of workpiece features, and precise alignment of the WCS. Experimental validation confirms that the proposed method is efficient and improves milling accuracy. By dynamically identifying the workpiece geometry, the system successfully addresses challenges posed by irregular timber shapes, resulting in higher accuracy for timber joints. This method contributes to advanced manufacturing strategies in robotic timber construction and supports the processing of diverse workpiece geometries, with potential applications in civil engineering for building construction through the precise fabrication of structural timber components. Full article
(This article belongs to the Special Issue Architectural Design Supported by Information Technology: 2nd Edition)
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15 pages, 24344 KiB  
Article
The Influence of Dimensional Parameters on the Characteristics of Magnetic Flux Concentrators Used in Tunneling Magnetoresistance Devices
by Ran Bi, Huiquan Zhang, Shi Pan, Xinting Liu, Ruiying Chen, Shilin Wu and Jun Hu
Sensors 2025, 25(15), 4739; https://doi.org/10.3390/s25154739 (registering DOI) - 31 Jul 2025
Abstract
Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing [...] Read more.
Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing magnetic flux concentrators (MFCs) offers an effective approach to enhance TMR sensitivity. In this study, the finite element method was employed to analyze the effects of different MFC geometric structures on the uniformity of the magnetic field in the air gap and the magnetic circuit gain (MCG). It was determined that the MCG of the MFC is not directly related to the absolute values of its parameters but rather to their ratios. Simulation analyses evaluated the impact of these parameter ratios on both the MCG and its spatial distribution uniformity, leading to the formulation of MFC design optimization principles. Building on these simulation-derived principles, several MFCs were fabricated using the 1J85 material, and an experimental platform was established to validate the simulation findings. The fabricated MFCs achieved an MCG of 7.325 times. Based on the previously developed TMR devices, a detection sensitivity of 2.46 nT/Hz @1Hz was obtained. By optimizing parameter configurations, this work provides theoretical guidance for further enhancing the performance of TMR sensors in magnetic field measurements. Full article
(This article belongs to the Section Physical Sensors)
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18 pages, 9390 KiB  
Article
An Integrated SEA–Deep Learning Approach for the Optimal Geometry Performance of Noise Barrier
by Hao Wu, Lingshan He, Ziyu Tao, Duo Zhang and Yunke Luo
Machines 2025, 13(8), 670; https://doi.org/10.3390/machines13080670 (registering DOI) - 31 Jul 2025
Abstract
The escalating environmental noise pollution along urban rail transit corridors, exacerbated by rapid urbanization, necessitates innovative and efficient noise control measures. A comprehensive investigation was conducted that utilized field measurements of train passing-by noise to establish a statistical energy analysis model for evaluating [...] Read more.
The escalating environmental noise pollution along urban rail transit corridors, exacerbated by rapid urbanization, necessitates innovative and efficient noise control measures. A comprehensive investigation was conducted that utilized field measurements of train passing-by noise to establish a statistical energy analysis model for evaluating the acoustic performance of both vertical (VB) and fully enclosed (FB) barrier configurations. The study incorporated Maa’s theory of micro-perforated plate (MPP) parameter optimization and developed a neural network surrogate model focused on insertion loss maximization for barrier geometric design. Key findings revealed significant barrier-induced near-track noise amplification, with peak effects observed at the point located 1 m from the barrier and 2 m above the rail. Frequency-dependent analysis demonstrated a characteristic rise-and-fall reflection pattern, showing maximum amplifications of 1.47 dB for VB and 4.13 dB for FB within the 400–2000 Hz range. The implementation of optimized MPPs was found to effectively eliminate the near-field noise amplification effects, achieving sound pressure level reductions of 4–8 dB at acoustically sensitive locations. Furthermore, the high-precision surrogate model (R2 = 0.9094, MSE = 0.8711) facilitated optimal geometric design solutions. The synergistic combination of MPP absorption characteristics and geometric optimization resulted in substantially enhanced barrier performance, offering practical solutions for urban rail noise mitigation strategies. Full article
(This article belongs to the Special Issue Advances in Noises and Vibrations for Machines)
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20 pages, 4809 KiB  
Article
Design of a Bidirectional Veneer Defect Repair Method Based on Parametric Modeling and Multi-Objective Optimization
by Xingchen Ding, Jiuqing Liu, Xin Sun, Hao Chang, Jie Yan, Chengwen Sun and Chunmei Yang
Technologies 2025, 13(8), 324; https://doi.org/10.3390/technologies13080324 (registering DOI) - 31 Jul 2025
Abstract
Repairing veneer defects is the key to ensuring the quality of plywood. In order to improve the maintenance quality and material utilization efficiency during the maintenance process, this paper proposes a bidirectional maintenance method based on gear rack transmission and its related equipment. [...] Read more.
Repairing veneer defects is the key to ensuring the quality of plywood. In order to improve the maintenance quality and material utilization efficiency during the maintenance process, this paper proposes a bidirectional maintenance method based on gear rack transmission and its related equipment. Based on the working principle, a geometric relationship model was established, which combines the structural parameters of the mold, punch, and gear system. Simultaneously, it solves the problem of motion attitude analysis of conjugate tooth profiles under non-standard meshing conditions, aiming to establish a constraint relationship between stamping motion and structural design parameters. On this basis, a constrained optimization model was developed by integrating multi-objective optimization theory to maximize maintenance efficiency. The NSGA-III algorithm is used to solve the model and obtain the Pareto front solution set. Subsequently, three optimal parameter configurations were selected for simulation analysis and experimental platform construction. The simulation and experimental results indicate that the veneer repair time ranges from 0.6 to 1.8 seconds, depending on the stamping speed. A reduction of 28 mm in die height decreases the repair time by approximately 0.1 seconds, resulting in an efficiency improvement of about 14%. The experimental results confirm the effectiveness of the proposed method in repairing veneer defects. Vibration measurements further verify the system’s stable operation under parametric modeling and optimization design. The main vibration response occurs during the meshing and disengagement phases between the gear and rack. Full article
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21 pages, 2255 KiB  
Article
Cloud-Based Architecture for Hydrophone Data Acquisition and Processing of Surface and Underwater Vehicle Detection
by Francisco Pérez Carrasco, Anaida Fernández García, Alberto García, Verónica Ruiz Bejerano, Álvaro Gutiérrez and Alberto Belmonte-Hernández
J. Mar. Sci. Eng. 2025, 13(8), 1455; https://doi.org/10.3390/jmse13081455 - 30 Jul 2025
Viewed by 70
Abstract
This paper presents a cloud-based architecture for the acquisition, transmission, and processing of acoustic data from hydrophone arrays, designed to enable the detection and monitoring of both surface and underwater vehicles. The proposed system offers a modular and scalable cloud infrastructure that supports [...] Read more.
This paper presents a cloud-based architecture for the acquisition, transmission, and processing of acoustic data from hydrophone arrays, designed to enable the detection and monitoring of both surface and underwater vehicles. The proposed system offers a modular and scalable cloud infrastructure that supports real-time and distributed processing of hydrophone data collected in diverse aquatic environments. Acoustic signals captured by heterogeneous hydrophones—featuring varying sensitivity and bandwidth—are streamed to the cloud, where several machine learning algorithms can be deployed to extract distinguishing acoustic signatures from vessel engines and propellers in interaction with water. The architecture leverages cloud-based services for data ingestion, processing, and storage, facilitating robust vehicle detection and localization through propagation modeling and multi-array geometric configurations. Experimental validation demonstrates the system’s effectiveness in handling high-volume acoustic data streams while maintaining low-latency processing. The proposed approach highlights the potential of cloud technologies to deliver scalable, resilient, and adaptive acoustic sensing platforms for applications in maritime traffic monitoring, harbor security, and environmental surveillance. Full article
(This article belongs to the Section Ocean Engineering)
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23 pages, 2253 KiB  
Article
Robust Underwater Vehicle Pose Estimation via Convex Optimization Using Range-Only Remote Sensing Data
by Sai Krishna Kanth Hari, Kaarthik Sundar, José Braga, João Teixeira, Swaroop Darbha and João Sousa
Remote Sens. 2025, 17(15), 2637; https://doi.org/10.3390/rs17152637 - 29 Jul 2025
Viewed by 149
Abstract
Accurate localization plays a critical role in enabling underwater vehicle autonomy. In this work, we develop a robust infrastructure-based localization framework that estimates the position and orientation of underwater vehicles using only range measurements from long baseline (LBL) acoustic beacons to multiple on-board [...] Read more.
Accurate localization plays a critical role in enabling underwater vehicle autonomy. In this work, we develop a robust infrastructure-based localization framework that estimates the position and orientation of underwater vehicles using only range measurements from long baseline (LBL) acoustic beacons to multiple on-board receivers. The proposed framework integrates three key components, each formulated as a convex optimization problem. First, we introduce a robust calibration function that unifies multiple sources of measurement error—such as range-dependent degradation, variable sound speed, and latency—by modeling them through a monotonic function. This function bounds the true distance and defines a convex feasible set for each receiver location. Next, we estimate the receiver positions as the center of this feasible region, using two notions of centrality: the Chebyshev center and the maximum volume inscribed ellipsoid (MVE), both formulated as convex programs. Finally, we recover the vehicle’s full 6-DOF pose by enforcing rigid-body constraints on the estimated receiver positions. To do this, we leverage the known geometric configuration of the receivers in the vehicle and solve the Orthogonal Procrustes Problem to compute the rotation matrix that best aligns the estimated and known configurations, thereby correcting the position estimates and determining the vehicle orientation. We evaluate the proposed method through both numerical simulations and field experiments. To further enhance robustness under real-world conditions, we model beacon-location uncertainty—due to mooring slack and water currents—as bounded spherical regions around nominal beacon positions. We then mitigate the uncertainty by integrating the modified range constraints into the MVE position estimation formulation, ensuring reliable localization even under infrastructure drift. Full article
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36 pages, 4967 KiB  
Review
Mechanical Behavior of Adhesively Bonded Joints Under Tensile Loading: A Synthetic Review of Configurations, Modeling, and Design Considerations
by Leila Monajati, Aurelian Vadean and Rachid Boukhili
Materials 2025, 18(15), 3557; https://doi.org/10.3390/ma18153557 - 29 Jul 2025
Viewed by 272
Abstract
This review presents a comprehensive synthesis of recent advances in the tensile performance of adhesively bonded joints, focusing on applied aspects and modeling developments rather than providing a full theoretical analysis. Although many studies have addressed individual joint types or modeling techniques, an [...] Read more.
This review presents a comprehensive synthesis of recent advances in the tensile performance of adhesively bonded joints, focusing on applied aspects and modeling developments rather than providing a full theoretical analysis. Although many studies have addressed individual joint types or modeling techniques, an integrated review that compares joint configurations, modeling strategies, and performance optimization methods under tensile loading remains lacking. This work addresses that gap by examining the mechanical behavior of key joint types, namely, single-lap, single-strap, and double-strap joints, and highlighting their differences in stress distribution, failure mechanisms, and structural efficiency. Modeling and simulation approaches, including cohesive zone modeling, extended finite element methods, and virtual crack closure techniques, are assessed for their predictive accuracy and applicability to various joint geometries. This review also covers material and geometric enhancements, such as adherend tapering, fillets, notching, bi-adhesives, functionally graded bondlines, and nano-enhanced adhesives. These strategies are evaluated in terms of their ability to reduce stress concentrations and improve damage tolerance. Failure modes, adhesive and adherend defects, and delamination risks are also discussed. Finally, comparative insights into different joint configurations illustrate how geometry and adhesive selection influence strength, energy absorption, and weight efficiency. This review provides design-oriented guidance for optimizing bonded joints in aerospace, automotive, and structural engineering applications. Full article
(This article belongs to the Special Issue Advanced Materials and Processing Technologies)
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36 pages, 27306 KiB  
Article
Integrating Social Network and Space Syntax: A Multi-Scale Diagnostic–Optimization Framework for Public Space Optimization in Nomadic Heritage Villages of Xinjiang
by Hao Liu, Rouziahong Paerhati, Nurimaimaiti Tuluxun, Saierjiang Halike, Cong Wang and Huandi Yan
Buildings 2025, 15(15), 2670; https://doi.org/10.3390/buildings15152670 - 28 Jul 2025
Viewed by 141
Abstract
Nomadic heritage villages constitute significant material cultural heritage. Under China’s cultural revitalization and rural development strategies, these villages face spatial degradation driven by tourism and urbanization. Current research predominantly employs isolated analytical approaches—space syntax often overlooks social dynamics while social network analysis (SNA) [...] Read more.
Nomadic heritage villages constitute significant material cultural heritage. Under China’s cultural revitalization and rural development strategies, these villages face spatial degradation driven by tourism and urbanization. Current research predominantly employs isolated analytical approaches—space syntax often overlooks social dynamics while social network analysis (SNA) overlooks physical interfaces—hindering the development of holistic solutions for socio-spatial resilience. This study proposes a multi-scale integrated assessment framework combining social network analysis (SNA) and space syntax to systematically evaluate public space structures in traditional nomadic villages of Xinjiang. The framework provides scientific evidence for optimizing public space design in these villages, facilitating harmonious coexistence between spatial functionality and cultural values. Focusing on three heritage villages—representing compact, linear, and dispersed morphologies—the research employs a hierarchical “village-street-node” analytical model to dissect spatial configurations and their socio-functional dynamics. Key findings include the following: Compact villages exhibit high central clustering but excessive concentration, necessitating strategies to enhance network resilience and peripheral connectivity. Linear villages demonstrate weak systemic linkages, requiring “segment-connection point supplementation” interventions to mitigate structural elongation. Dispersed villages maintain moderate network density but face challenges in visual integration and centrality, demanding targeted activation of key intersections to improve regional cohesion. By merging SNA’s social attributes with space syntax’s geometric precision, this framework bridges a methodological gap, offering comprehensive spatial optimization solutions. Practical recommendations include culturally embedded placemaking, adaptive reuse of transitional spaces, and thematic zoning to balance heritage conservation with tourism needs. Analyzing Xinjiang’s unique spatial–social interactions provides innovative insights for sustainable heritage village planning and replicable solutions for comparable global cases. Full article
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20 pages, 4277 KiB  
Article
BIM and HBIM: Comparative Analysis of Distinct Modelling Approaches for New and Heritage Buildings
by Alcínia Zita Sampaio, Augusto M. Gomes, João Tomé and António M. Pinto
Heritage 2025, 8(8), 299; https://doi.org/10.3390/heritage8080299 - 28 Jul 2025
Viewed by 174
Abstract
The Building Information Modelling (BIM) methodology has been applied in distinct sectors of the construction industry with a growing demonstration of benefits, supporting the elaboration of integrated and collaborative projects. The main foundation of the methodology is the generation of a three-dimensional (3D) [...] Read more.
The Building Information Modelling (BIM) methodology has been applied in distinct sectors of the construction industry with a growing demonstration of benefits, supporting the elaboration of integrated and collaborative projects. The main foundation of the methodology is the generation of a three-dimensional (3D) digital representation, the BIM model, concerning the different disciplines that make up a complete project. The BIM model includes a database referring to all the information regarding the geometric and physical aspects of the project. The procedure related to the generation of BIM models presents a significant difference depending on whether the project refers to new or old buildings. Current BIM systems contain libraries with various types of parametric objects that are effortlessly adaptable to new constructions. However, the generation of models of old buildings, supported by the definition of detailed new parametric objects, is required. The present study explores the distinct modelling procedures applied in the generation of specific parametric objects for new and old constructions, with the objective of evaluating the comparative complexity that the designer faces in modelling specific components. For a correct representation of new buildings in the design phase or for the reproduction of the accurate architectural configuration of heritage buildings, the modelling process presents significant differences identified in the study. Full article
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20 pages, 2772 KiB  
Article
Cable Force Optimization of Circular Ring Pylon Cable-Stayed Bridges Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization
by Shengdong Liu, Fei Chen, Qingfu Li and Xiyu Ma
Buildings 2025, 15(15), 2647; https://doi.org/10.3390/buildings15152647 - 27 Jul 2025
Viewed by 141
Abstract
Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization [...] Read more.
Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. RSM constructs surrogate models for strain energy and mid-span displacement, reducing reliance on finite element analysis, while MOPSO optimizes Pareto solution sets for rapid cable force adjustment. Validated through an engineering case, the method reduces the main girder’s max bending moment by 8.7%, mid-span displacement by 31.2%, and strain energy by 7.1%, improving stiffness and mitigating stress concentrations. The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. Engineers are thereby equipped with a rapid and reliable optimization framework for geometrically complex cable-stayed bridges, delivering significant improvements in structural safety and construction feasibility. Ultimately, this approach establishes both theoretical substantiation and practical engineering benchmarks for designing non-conventional cable-stayed bridge configurations. Full article
(This article belongs to the Section Building Structures)
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15 pages, 1047 KiB  
Article
The Venturi Reuleaux Triangle: Advancing Sustainable Process Intensification Through Controlled Hydrodynamic Cavitation in Food, Water, and Industrial Applications
by Lorenzo Albanese
Sustainability 2025, 17(15), 6812; https://doi.org/10.3390/su17156812 - 27 Jul 2025
Viewed by 243
Abstract
Hydrodynamic cavitation is one of the most promising technologies for sustainable process intensification in the food, nutraceutical, and environmental sectors, due to its ability to generate highly localized and intense implosions. Venturi-type devices, known for their simplicity and efficiency, are widely used for [...] Read more.
Hydrodynamic cavitation is one of the most promising technologies for sustainable process intensification in the food, nutraceutical, and environmental sectors, due to its ability to generate highly localized and intense implosions. Venturi-type devices, known for their simplicity and efficiency, are widely used for non-thermal extraction, microbial inactivation, and cellular disruption. However, the effectiveness of cavitation critically depends on internal geometry—particularly the perimeter-to-area ratio (P/A), which influences both pressure gradient distribution and the density of nucleation sites. In this context, an innovative configuration based on the Reuleaux triangle is proposed, allowing for a significant increase in the P/A ratio compared to conventional circular-section devices. This theoretical study extends the Navier–Stokes and Rayleigh–Plesset models to describe bubble dynamics and assess the influence of geometric and rotational variants (VRAt) on the localization and intensity of cavitation collapse. The results suggest that optimized internal geometries can reduce treatment times, increase selectivity, and improve the overall energy efficiency of cavitation processes, offering strong potential for advanced and sustainable industrial applications. This work is entirely theoretical and is intended to support the future design and experimental validation of next-generation cavitating devices. Full article
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17 pages, 1742 KiB  
Article
Assessment of Aerodynamic Properties of the Ventilated Cavity in Curtain Wall Systems Under Varying Climatic and Design Conditions
by Nurlan Zhangabay, Aizhan Zhangabay, Kenzhebek Akmalaiuly, Akmaral Utelbayeva and Bolat Duissenbekov
Buildings 2025, 15(15), 2637; https://doi.org/10.3390/buildings15152637 - 25 Jul 2025
Viewed by 272
Abstract
Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to [...] Read more.
Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to ensure healthy and favorable conditions for human life but also to the need for the rational use of energy resources. This area is becoming particularly relevant in the context of global challenges related to climate change, rising energy costs and increased environmental requirements. Practice shows that any technical solutions to ensure comfortable temperature, humidity and air exchange in rooms should be closely linked to the concept of energy efficiency. This allows one not only to reduce operating costs but also to significantly reduce greenhouse gas emissions, thereby contributing to sustainable development and environmental safety. In this connection, this study presents a parametric assessment of the influence of climatic and geometric factors on the aerodynamic characteristics of the air cavity, which affect the heat exchange process in the ventilated layer of curtain wall systems. The assessment was carried out using a combined analytical calculation method that provides averaged thermophysical parameters, such as mean air velocity (Vs), average internal surface temperature (tin.sav), and convective heat transfer coefficient (αs) within the air cavity. This study resulted in empirical average values, demonstrating that the air velocity within the cavity significantly depends on atmospheric pressure and façade height difference. For instance, a 10-fold increase in façade height leads to a 4.4-fold increase in air velocity. Furthermore, a three-fold variation in local resistance coefficients results in up to a two-fold change in airflow velocity. The cavity thickness, depending on atmospheric pressure, was also found to affect airflow velocity by up to 25%. Similar patterns were observed under ambient temperatures of +20 °C, +30 °C, and +40 °C. The analysis confirmed that airflow velocity is directly affected by cavity height, while the impact of solar radiation is negligible. However, based on the outcomes of the analytical model, it was concluded that the method does not adequately account for the effects of solar radiation and vertical temperature gradients on airflow within ventilated façades. This highlights the need for further full-scale experimental investigations under hot climate conditions in South Kazakhstan. The findings are expected to be applicable internationally to regions with comparable climatic characteristics. Ultimately, a correct understanding of thermophysical processes in such structures will support the advancement of trends such as Lightweight Design, Functionally Graded Design, and Value Engineering in the development of curtain wall systems, through the optimized selection of façade configurations, accounting for temperature loads under specific climatic and design conditions. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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26 pages, 16392 KiB  
Article
TOSD: A Hierarchical Object-Centric Descriptor Integrating Shape, Color, and Topology
by Jun-Hyeon Choi, Jeong-Won Pyo, Ye-Chan An and Tae-Yong Kuc
Sensors 2025, 25(15), 4614; https://doi.org/10.3390/s25154614 - 25 Jul 2025
Viewed by 273
Abstract
This paper introduces a hierarchical object-centric descriptor framework called TOSD (Triplet Object-Centric Semantic Descriptor). The goal of this method is to overcome the limitations of existing pixel-based and global feature embedding approaches. To this end, the framework adopts a hierarchical representation that is [...] Read more.
This paper introduces a hierarchical object-centric descriptor framework called TOSD (Triplet Object-Centric Semantic Descriptor). The goal of this method is to overcome the limitations of existing pixel-based and global feature embedding approaches. To this end, the framework adopts a hierarchical representation that is explicitly designed for multi-level reasoning. TOSD combines shape, color, and topological information without depending on predefined class labels. The shape descriptor captures the geometric configuration of each object. The color descriptor focuses on internal appearance by extracting normalized color features. The topology descriptor models the spatial and semantic relationships between objects in a scene. These components are integrated at both object and scene levels to produce compact and consistent embeddings. The resulting representation covers three levels of abstraction: low-level pixel details, mid-level object features, and high-level semantic structure. This hierarchical organization makes it possible to represent both local cues and global context in a unified form. We evaluate the proposed method on multiple vision tasks. The results show that TOSD performs competitively compared to baseline methods, while maintaining robustness in challenging cases such as occlusion and viewpoint changes. The framework is applicable to visual odometry, SLAM, object tracking, global localization, scene clustering, and image retrieval. In addition, this work extends our previous research on the Semantic Modeling Framework, which represents environments using layered structures of places, objects, and their ontological relations. Full article
(This article belongs to the Special Issue Event-Driven Vision Sensor Architectures and Application Scenarios)
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29 pages, 20260 KiB  
Review
Geodynamic, Tectonophysical, and Structural Comparison of the South Caspian and Levant Basins: A Review
by Lev Eppelbaum, Youri Katz, Fakhraddin Kadirov, Ibrahim Guliyev and Zvi Ben-Avraham
Geosciences 2025, 15(8), 281; https://doi.org/10.3390/geosciences15080281 - 24 Jul 2025
Viewed by 248
Abstract
The Paratethyan South Caspian and Mediterranean Levant basins relate to the significant hydrocarbon provinces of Eurasia. The giant hydrocarbon reserves of the SCB are well-known. Within the LB, so far, only a few commercial gas fields have been found. Both the LB and [...] Read more.
The Paratethyan South Caspian and Mediterranean Levant basins relate to the significant hydrocarbon provinces of Eurasia. The giant hydrocarbon reserves of the SCB are well-known. Within the LB, so far, only a few commercial gas fields have been found. Both the LB and SCB contain some geological peculiarities. These basins are highly complex tectonically and structurally, requiring a careful, multi-component geological–geophysical analysis. These basins are primarily composed of oceanic crust. The oceanic crust of both the South Caspian and Levant basins formed within the complex Neotethys ocean structure. However, this crust is allochthonous in the Levant Basin (LB) and autochthonous in the South Caspian Basin (SCB). This study presents a comprehensive comparison of numerous tectonic, geodynamic, morphological, sedimentary, and geophysical aspects of these basins. The Levant Basin is located directly above the middle part of the massive, counterclockwise-rotating mantle structure and rotates accordingly in the same direction. To the north of this basin is located the critical latitude 35° of the Earth, with the vast Cyprus Bouguer gravity anomaly. The LB contains the most ancient block of oceanic crust on Earth, which is related to the Kiama paleomagnetic hyperzone. On the western boundary of the SCB, approximately 35% of the world’s mud volcanoes are located; the geological reasons for this are still unclear. The low heat flow values and thick sedimentary layers in both basins provide opportunities to discover commercial hydrocarbon deposits at great depths. The counterclockwise-rotating mantle structure creates an indirect geodynamic influence on the SCB. The lithospheric blocks situated above the eastern branch of the mantle structure trigger a north–northeastward movement of the western segment of the Iranian Plate, which exhibits a complex geometric configuration. Conversely, the movement of the Iranian Plate induced a clockwise rotation of the South Caspian Basin, which lies to the east of the plate. This geodynamic ensemble creates an unstable geodynamic situation in the region. Full article
(This article belongs to the Section Geophysics)
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