Search Results (65)

The evaluation of vibro-acoustic comfort in vehicle cabins is frequently limited by fragmented treatment of noise and vibration indicators and by the absence of structured, reproducible assessment frameworks. This study proposes an advanced, correlation-driven and process-oriented methodology for vibro-acoustic comfort evaluation, designed to support systematic analysis and decision-making across varying vehicle operating conditions. The proposed framework is formulated as a sequential process comprising experimental data acquisition, signal preprocessing, statistical correlation analysis, and decision-oriented interpretation. The framework was experimentally validated on five special-purpose armored platforms under both stationary and dynamic operating regimes, with repeated measurement trials to ensure robustness. Interior and exterior sound pressure levels, together with vibration-related parameters, are experimentally measured under stationary and dynamic operating regimes. Pearson correlation coefficients are employed to quantify interdependencies among vibro-acoustic variables and identify dominant contributors affecting comfort-related conditions. The results indicate statistically significant correlations between interior noise levels and selected vibration indicators, revealing distinct correlation patterns associated with different operating states. Based on these findings, correlation strength was classified as weak (|r| < 0.3), moderate (0.3 ≤ |r| < 0.6), and strong (|r| ≥ 0.6), enabling structured contributor ranking. The primary contribution of this work consists in elevating correlation analysis from a descriptive statistical technique to a formalized assessment process suitable for integration into predictive modeling and optimization workflows. The framework provides a transferable methodological structure, validated within the investigated vehicle category. Full article

Indoor environmental quality significantly affects human perceptions of comfort and well-being due to the fact that most daily activities are spent indoors. However, surface colors are generally considered to be aesthetic choices rather than environmental factors. The purpose of this research is to assess the effect of surface colors on visual comfort, thermal intent, and plant-supportive lighting conditions. This study uses a controlled experimental method and four easily interpretable parameters: surface reflectance (albedo), illuminance, correlated color temperature, and photosynthetic photon flux density. The experiment uses a miniature enclosed chamber to standardize the geometry and lighting conditions to test a set of carefully chosen printed and painted color surfaces. The lighting parameters were directly measured using consumer-level spectral and illuminance meters. The surface reflectance parameter is estimated to be red, green, and blue color codes. The novelty of this research is that it provides a preliminary screening method that can convert color choice into quantifiable implications on indoor environments, with clear assumptions and limitations. The results can be used to inform design decisions that link color choice to specific task-oriented lighting requirements, climate-oriented thermal intent (cooler vs. warmer), and plant-rich interior environments. Full article

The adoption of Interior Permanent Magnet Synchronous Motor (IPMSM) in Battery Electric Vehicle (BEV) and Plug-in Hybrid Electric Vehicle (PHEV) drives the need for innovative approaches to improve control performance and power conversion efficiency. This paper aims at evaluating advanced Model Predictive Control (MPC) strategies for IPMSM drives in a methodic comparison with the most widespread Field Oriented Control (FOC). Different extensions of direct Finite Control Set MPC (FCS-MPC) and indirect Continuous Control Set MPC (CCS-MPC) MPCs are considered and evaluated in terms of reference tracking performance, robustness, power efficiency, and complexity based on Matlab, Simulink™ simulations. Results confirm the inherent better control quality of MPCs over FOC in general and allow us to further identify some possible directions for improvement. Moreover, indirect MPCs perform better, but complexity may prevent them from supporting real-time implementation in some cases. On the other hand, direct MPCs are less complex and reduce inverter losses but at the cost of increased Total Harmonic Distortion (THD) and decreased robustness to parameters deviations. These results also highlight various trade-offs between different predictive control strategies and their feasibility for high-performance automotive applications. Full article

This paper presents a phase-based analysis of the spatial and architectural development of underground stations in the Warsaw Metro, focusing on 28 non-transfer stations constructed between 1983 and 2019. The research examines how design and functional solutions evolved over five construction phases in response to changing engineering methods, organizational frameworks, and urban contexts. A comparative analytical framework was developed, incorporating quantitative and qualitative parameters related to spatial layout, access schemes, and interior design features. The methodology combines archival documentation analysis, in situ field surveys, and typological classification. Findings reveal a clear trajectory from utilitarian, dual-purpose stations emphasizing structural durability and civil defense, toward more user-oriented designs prioritizing accessibility and intuitive navigation. Later phases show an expansion of multifunctional elements, including retail spaces, reflecting contemporary trends in metro station design. It contributes to a broader understanding of how adaptive design strategies enable metro infrastructure to respond to evolving urban needs and challenges, highlighting the importance of contextual integration for future metro developments. Full article

The determination of precise and reliable interior (IO) and relative (RO) orientation parameters for thermal infrared (TIR) cameras is critical for their subsequent use in photogrammetric processes. Although 2D calibration boards have become the predominant approach for TIR geometric calibration, these targets are susceptible to projective coupling and often introduce error through manual construction methods, necessitating the development of 3D targets tailored to TIR geometric calibration. Therefore, this paper evaluates TIR geometric calibration results obtained from 2D board and 3D field calibration approaches, documenting the construction, observation, and calculation of IO and RO parameters. This includes a comparative analysis of values derived from three popular commercial software packages commonly used for geometric calibration: MathWorks’ MATLAB, Agisoft Metashape, and Photometrix’s Australis. Furthermore, to assess the validity of derived parameters, two InfraRed Thermography 3D-Data Fusion (IRT-3DDF) methods are developed to model historic building façades and medieval frescoes. The results demonstrate the success of the proposed 3D field calibration targets for the calculation of both IO and RO parameters tailored to photogrammetric data fusion. Additionally, a novel combined TIR-RGB bundle block adjustment approach demonstrates the success of applying ‘out-of-the-box’ deep-learning neural networks for multi-modal image matching and thermal modelling. Considerations for the development of TIR geometric calibration approaches and the evolution of proposed IRT-3DDF methods are provided for future work. Full article

In this study, the ballistic effectiveness of Kevlar 29 composites was analyzed by combining 400 and 460 GSM grammages with a polyurethane matrix. Plates measuring 300 mm × 250 mm were fabricated using hand lamination and compression techniques, with reinforcement designs consisting of 10, 14, and 18 layers of Kevlar 29 fabric oriented at a 90° angle. Ballistic tests were conducted following the parameters of the NIJ 0108.01 standard, applying five impacts with 9 mm FMJ and 22 (5.5 mm) caliber bullets. Both the composites and pure Kevlar were evaluated. Post-damage visual analysis was conducted on the front and back faces, as well as the interior of the composite, to identify delamination and fractures. The results show that .22 caliber bullets were captured at various stacking levels depending on the configuration, whereas 9 mm bullets penetrated all the plates. Localized fractures and delamination associated with the impacts were observed, highlighting the importance of stacking design and grammage in the material’s energy dissipation capacity. Full article

The generation of aerial and unmanned aerial vehicle (UAV)-based 3D point clouds in forests and their subsequent structural analysis, including tree delineation and modeling, pose multiple technical challenges that are partly raised by the calibration of non-metric cameras mounted on UAVs. We present a novel method to deal with this problem for forest structure analysis by photogrammetric 3D modeling, particularly in areas with complex textures and varying levels of tree canopy cover. Our proposed method selects various subsets of a camera’s interior orientation parameters (IOPs), generates a dense point cloud for each, and then synthesizes these models to form a combined model. We hypothesize that this combined model can provide a superior representation of tree structure than a model calibrated with an optimal subset of IOPs alone. The effectiveness of our methodology was evaluated in sites across a semi-arid forest ecosystem, known for their diverse crown structures and varied canopy density due to a traditional pruning method known as pollarding. The results demonstrate that the enhanced model outperformed the standard models by 23% and 37% in both site- and tree-based metrics, respectively, and can therefore be suggested for further applications in forest structural analysis based on consumer-grade UAV data. Full article

This study compares the photogrammetric performance of three multi-camera systems—two spherical cameras (INSTA 360 Pro2 and MG1) and one multi-camera rig (ANT3D)—to evaluate their accuracy and precision in confined environments. These systems are particularly suited for indoor surveys, such as narrow spaces, where traditional methods face limitations. The instruments were tested for the survey of a narrow spiral staircase within Milan Cathedral and the results were analyzed based on different processing strategies, including different relative constraints between sensors, various calibration sets for distortion parameters, interior orientation (IO), and relative orientation (RO), as well as two different ground control solutions. This study also included a repeatability test. The findings showed that, with appropriate ground control, all systems achieved the target accuracy of 1 cm. In partially unconstrained scenarios, the drift errors ranged between 5 and 10 cm. Performance varied depending on the processing pipelines; however, the results suggest that imposing a multi-camera constraint between sensors and estimating both IO and RO parameters during the Bundle Block Adjustment yields the best outcomes. In less stable environments, it might be preferable to pre-calibrate and fix the IO parameters. Full article

Physical properties of the Sun (orientation of rotation axis, oblateness coefficient $J_{2\odot }$, and change rate of the gravitational parameter ${\dot{\mu }}_{\odot }$) are determined using a dynamical model describing the motion of the Sun, planets, the Moon, asteroids, and Trans-Neptunian objects (TNOs). Among the many kinds of observations used to determine the orbits and physical properties of the bodies, the most important for our study are precise interplanetary ranging data: Earth–Mercury ranges from MESSENGER spacecraft and Earth–Mars ranges from Odyssey and MRO. The findings allow us to improve the model of the Sun in modern planetary ephemerides. First, the dynamically determined direction of the Sun’s pole is ≈2° off the visible axis of rotation of the Sun’s surface, which is corroborated by present knowledge of the Sun’s interior. Second, the change rate of the Sun’s gravitational parameter is found to be smaller (in absolute value) than the nominal value derived from the estimate of mass loss through radiation and solar wind. Possible interpretations are discussed. Full article

Hospital intensive care units (ICUs) frequently experience inadequate lighting conditions, with low daytime and excessive nighttime illuminance, which can negatively affect patient recovery and the work performance of health personnel. This study examines the impact of window design parameters—specifically, window-to-wall ratio (WWR) and window position—and interior surface reflectance on visual comfort, lighting performance, energy consumption, and human well-being in intensive care units (ICUs) in Mediterranean climates, according to orientation. Using dynamic lighting metrics, such as daylight autonomy (DA) and circadian stimulus autonomy (CSA), this research quantifies the influence of these design factors. The results suggest that a WWR of 25% is optimal for achieving sufficient DA and CSA values, with centered window configurations preferred for uniform daylight distribution and circadian stimulus. This study further emphasizes the significance of interior reflectance, recommending bright coatings to maximize outcomes, while advising against dark finishes, particularly in north-facing rooms or with smaller WWRs. Although Seville shows slightly better performance than Barcelona, the proposed configurations are effective across both locations, highlighting the prioritization of window sizing, positioning, and reflectance over Mediterranean geographical differences. These findings offer practical guidance for ICU design to enhance natural lighting, supporting patient recovery and overall well-being through improved circadian alignment. Full article

The calibration of cameras plays a critical role in close-range photogrammetry because the precision of calibration has a direct effect on the quality of results. When handling image capture using a camera, traditional swarm intelligence algorithms such as genetic algorithms and particle swarm optimization, in conjunction with Zhang’s calibration method, frequently face difficulties regarding local optima and sluggish convergence. This study presents an enhanced hybrid optimization approach utilizing both the principles of differential evolution and particle swarm optimization, which is then employed in the context of camera calibration. Initially, we establish a measurement model specific to the camera in close-range photogrammetry and determine its interior orientation parameters. Subsequently, employing these parameters as initial values, we perform global optimization and iteration using the improved hybrid optimization algorithm. The effectiveness of the proposed approach is subsequently validated through simulation and comparative experiments. Compared to alternative approaches, the proposed algorithm enhances both the accuracy of camera calibration and the convergence speed. It effectively addresses the issue of other algorithms getting trapped in local optima due to image distortion. These research findings provide theoretical support for practical engineering applications in the field of control theory and optimization to a certain extent. Full article

A challenge remains in achieving adequate surface roughness of SLM fabricated interior channels, which is crucial for fuel delivery in the space industry. This study investigated the surface roughness of interior fine flow channels (1 mm diameter) embedded in SLM fabricated TC4 alloy space components. A machine learning approach identified layer thickness as a significant factor affecting interior channel surface roughness, with an importance score of 1.184, followed by scan speed and laser power with scores of 0.758 and 0.512, respectively. The roughness resulted from thin layer thickness of 20 µm, predominantly formed through powder adherence, while from thicker layer of 50 µm, the roughness was mainly due to the stair step effect. Slow scan speeds increased melt pools solidification time at roof overhangs, causing molten metal to sag under gravity. Higher laser power increased melt pools temperature and led to dross formation at roof overhangs. Smaller hatch spaces increased roughness due to overlapping of melt tracks, while larger hatch spaces reduced surface roughness but led to decreased part density. The surface roughness was recorded at 34 µm for roof areas and 26.15 µm for floor areas. These findings contribute to potential adoption of TC4 alloy components in the space industry. Full article

The extreme accuracy of Juno radio science data allows us to perform very precise orbit determination experiments. While previous works focused on the estimation of the gravitational field of Jupiter, in this article, we aim to accurately determine the planet’s orientation in space. For this purpose, we implement a rotational model of Jupiter, taking into account also its main deformations, as they affect the planet’s inertia components. Rotation parameters are estimated simultaneously with all other parameters (especially gravity and tides), in order to obtain a global and coherent solution. In our experiments, we find that Juno data manage to constrain Jupiter’s pole direction with an accuracy of around ${10}^{-7}$ radians for the whole duration of the mission, allowing us to improve its long-term ephemerides. Moreover, Juno data provide an upper bound on the maximum displacement between Jupiter’s pole and spin axis of less than 10 m, which allows us to investigate possible short-period nutation effects due to, for example, atmospheric and interior processes of the planet. Full article

This paper presents a photogrammetry-based system for capturing turbulent aerated flow topography in a laboratory environment, especially for complex hydraulic phenomena character-ised by turbulent, non-stationary, and non-homogeneous aerated flows. It consists of ten high-resolution cameras equipped with monochromatic sensors and custom-built LED lights, all synchronised for accurate data acquisition. Post processing involves Structure-from-Motion and Multi-View Stereo techniques to calculate exterior and interior orientation parameters that ensure accurate alignment within a desired coordinate system, and conversion to point clouds. The proposed method showed great potential for capturing free water surface topography of turbulent aerated flows with high spatial and temporal resolution over the entire field of view of the cameras. Due to the unique capabilities of this system, direct comparisons with existing benchmarks were not possible. Instead, average free water surface profiles were derived from selected control cross sections, using 2D LIDAR measurements for verification. Both the LIDAR and photogrammetry averaged profiles showed remarkably good agreement, with deviations within ±20 mm. Validation showed that photogrammetry can be used to measure the complex aerated turbulent free water surface. In this way, this approach, involving consecutive image dataset acquisition at predefined intervals, is proving to be a valuable tool for observing, visualising, analysing, investigating, and gaining a comprehensive understanding of the dynamics of the free water surface. Full article

Camera calibration is necessary for many machine vision applications. The calibration methods are based on linear or non-linear optimization techniques that aim to find the best estimate of the camera parameters. One of the most commonly used methods in computer vision for the calibration of intrinsic camera parameters and lens distortion (interior orientation) is Zhang’s method. Additionally, the uncertainty of the camera parameters is normally estimated by assuming that their variability can be explained by the images of the different poses of a checkerboard. However, the degree of reliability for both the best parameter values and their associated uncertainties has not yet been verified. Inaccurate estimates of intrinsic and extrinsic parameters during camera calibration may introduce additional biases in post-processing. This is why we propose a novel Bayesian inference-based approach that has allowed us to evaluate the degree of certainty of Zhang’s camera calibration procedure. For this purpose, the a prioriprobability was assumed to be the one estimated by Zhang, and the intrinsic parameters were recalibrated by Bayesian inversion. The uncertainty of the intrinsic parameters was found to differ from the ones estimated with Zhang’s method. However, the major source of inaccuracy is caused by the procedure for calculating the extrinsic parameters. The procedure used in the novel Bayesian inference-based approach significantly improves the reliability of the predictions of the image points, as it optimizes the extrinsic parameters. Full article