Search Results (417)

In practice, the structural analysis and design of pedestrian systems subjected to human-induced vibrations is often based on simplified biodynamic models that can be used in place of even more complex computational strategies to describe Human-Structure Interaction (HSI) phenomena. Among various walking features, the vertical reaction force that a pedestrian transfers to the supporting structure during motion is a key input for design, but results from the combination of multiple influencing parameters and dynamic interactions. Robust and practical strategies to support a realistic HSI description and analysis have hence been the object of several studies. Following earlier research efforts, this paper focuses on the optimised calibration of the input parameters for the consolidated Spring-Mass-Damper (SMD) biodynamic model, which reduces a single pedestrian to an equivalent SDOF (with body mass m, spring stiffness k, and viscous damping coefficient c) and is often used for vibration serviceability purposes. In the present study, this calibration process is carried out with smartphone-based acquisitions and experimental records from the Centre of Mass (CoM) of each pedestrian to possibly replace more complex laboratory configurations and devices. To verify the potential and accuracy of such a smartphone-based approach, different pedestrians/volunteers and substructures (i.e., a rigid concrete slab or a timber floor prototype) are taken into account, and a total of 145 original gaits are post-processed for SMD modelling purposes. The analysis of the experimental results shows a rather close match with previous findings in terms of key pedestrian parameters. This outcome poses the basis for a more generalised application of the smartphone-based strategy to a multitude of similar applications and configurations of practical interest. The validity of calibration output and its possible sensitivity are further assessed in terms of expected effects on substructures, with a critical discussion of the most important results. Full article

In animal facilities, monitoring and controlling the thermal environment are essential in ensuring productivity and sustainability. However, many production units face challenges in implementing and maintaining effective thermal monitoring and control systems. Given the need for Smart Livestock Farming systems, this study aimed to develop and validate an easy-to-use, low-cost embedded system (ES_LC) for the real-time monitoring of dry-bulb air temperature (T_db, in °C) and relative humidity (RH, in %) in animal production facilities. The ES_LC consists of data collection/transmission modules and a server for Internet of Things (IoT) data storage. ES_LC modules and standard recording sensors (SRS) were installed in prototype animal facilities. Over 21 days, their performance was evaluated based on the Data Transmission Success Rate (DTSR, in %) and Data Transmission Interval (DTI, in minutes). Additionally, agreement between the ES_LC modules and the SRS was assessed using the daily mean root mean square error (RMSE) and mean relative error (RE) across different T_db and RH ranges. The ES_LC successfully collected and transmitted data to the cloud server, achieving an average DTSR of 94.04% and a predominant DTI of one minute. Regarding measurement agreement, distinct daily mean RMSE values were obtained for T_db (0.26–2.46 °C) and RH (4.37–16.20%). Furthermore, four sensor modules exhibited mean RE values below 3.00% across all T_db ranges, while all sensor modules showed progressively increasing mean RE values as RH levels rose. Consequently, calibration curves were established for each sensor module, achieving a high correlation between raw and corrected values (determination coefficient above 0.98). It was concluded that the ES_LC is a promising solution for thermal monitoring in animal facilities, enabling continuous and reliable data collection and transmission. Full article

As maritime transportation and human activities at sea continue to grow, ensuring the safety of offshore infrastructure has become an increasingly pressing research focus. However, traditional high-precision sensor systems often involve prohibitive costs, and the Automatic Identification System (AIS) faces signal loss or data manipulation problems, highlighting the need for a complementary, affordable, and reliable supplemental solution. This study introduces a monocular vision-based safety monitoring framework for offshore infrastructures. By combining advanced computer vision techniques such as Grounded SAM and horizon-based self-calibration, the proposed framework achieves accurate vessel detection, instance segmentation, and distance estimation. The model integrates open-vocabulary object detection and zero-shot segmentation, achieving high performance without additional training. To demonstrate the feasibility of the framework in practical applications, we conduct several experiments on public datasets and couple the proposed algorithms with the Leaflet.js and WebRTC libraries to develop a web-based prototype for real-time safety monitoring, providing visualized information and alerts for offshore infrastructure operators in our case study. The experimental results and case study suggest that the framework has notable advantages, including low cost, convenient deployment with minimal maintenance, high detection accuracy, and strong adaptability to diverse application conditions, which brings a supplemental solution to research on offshore infrastructure safety. Full article

In data-scarcity scenarios, few-shot object detection (FSOD) methods exhibit a notable advantage in alleviating the over-fitting problem. Currently, research on FSOD in the field of remote sensing is advancing rapidly and FSOD methods based on the fine-tuning paradigm have initially displayed their excellent performance. However, existing fine-tuning methods often encounter classification confusion issues. This is potentially because of the shortage of explicit modeling for transferable common knowledge and the biased class distribution, especially for fine-grained targets with higher inter-class similarity and intra-class variance. In view of this, we first propose a decoupled self-distillation (DSD) method to construct class prototypes in two decoupled feature spaces and measure inter-class correlations as soft labels or aggregation weights. To ensure a robust set of class prototypes during the self-distillation process, we devise a feature filtering module (FFM) to preselect high-quality class representative features. Furthermore, we introduce a progressive prototype calibration module (PPCM) with two steps, compensating the base prototypes with the prior base distribution and then calibrating the novel prototypes with adjacent calibrated base prototypes. Experiments on MAR20 and customized SHIP20 datasets have demonstrated the superior performance of our method compared to other existing advanced FSOD methods, simultaneously confirming the effectiveness of all proposed components. Full article

As a result of progress in space technology, more scientific missions are benefiting from using CubeSats equipped with radiometers. CubeSat constellations are especially effective in overcoming obstacles in cost, weight, and power. However, these benefits have certain significant downsides, including the difficulty in calibration due to the increased sensitivity of instruments to ambient conditions. Such limitations prevent conventional calibration methods from being reliably applied to CubeSat radiometers. A novel, constellation-level calibration framework called “Adaptive Calibration of CubeSat Radiometer Constellations (ACCURACy)” is being developed to address this issue. ACCURACy, in its current version, uses telemetry data obtained from thermistors in each CubeSat to cluster constellation members into time-adaptive groups of radiometers in similar states. Each radiometer is assigned membership to a cluster and this status is updated as in-orbit measurements shift in the clustering model. This paper introduces the ACCURACy framework, discusses its theoretical background, and presents a MATLAB prototype with performance and uncertainty analyses using synthetic radiometer data in comparison with traditional radiometer calibration methods. Full article

Seismic isolation systems play a crucial role in enhancing structural resilience during earthquakes, with lead rubber bearings being a widely adopted solution. These bearings incorporate lead cores to effectively dissipate seismic energy. However, their widespread application is constrained by significant drawbacks, including high costs and environmental concerns associated with lead. This study introduces a novel sustainable S-shaped steel damper made from standard steel. The influence of key geometrical parameters—thickness, width, and the distance from the bolt hole to the arc’s start—on the cyclic behavior of the dampers was investigated. Seven prototypes were designed, manufactured, and experimentally tested to evaluate their horizontal stiffness and damping performance. Subsequentially, the experimental results were considered for the validation of a numerical model based on a full 3D Finite Element discretization. The model, calibrated using simple uniaxial steel material tests, facilitates the identification of optimal geometric features for the production of S-shaped steel dampers without the need for extensive prototype fabrication and experimental testing. Additionally, the model can be seamlessly integrated into future numerical structural analyses, enabling a comprehensive evaluation of performance characteristics. In conclusion, this research provides critical insights into the geometric optimization of S-shaped steel dampers as cost-effective and sustainable dissipation devices. It offers both experimental data and a robust numerical model to guide future designs for improved seismic mitigation performances. Full article

The rapid advancement of model-based simulation has driven the increased adoption of virtual testing in power machinery, raising demands for high accuracy and real-time signal processing. This study introduces a real-time signal simulation and acquisition system leveraging field-programmable gate array (FPGA) technology, designed with flexible scalability and seamless integration with NI hardware-based test systems. The system supports various dynamic signals, including position, injection, and ignition signals, providing robust support for virtual testing and calibration. Comprehensive testing across scenarios involving oscilloscopes, signal generators, and the rapid control prototyping (RCP) platform confirms its high accuracy, stability, and adaptability in multi-signal processing and real-time response. This system is a state-of-the-art and extensively virtual field-tested platform for both power systems and power electronics. Full article

The nonlinearity problem of digital pixels restricts the reduction in power consumption at the pixel-level circuit. The main cause of nonlinearity is discussed in this article and low power consumption is attained by reducing the static current in capacitive transimpedance amplifiers (CTIAs) and comparators. Linearity was successfully improved through the use of an off-chip calibration method. A 64 × 64 array prototype digital readout integrated circuit (DROIC) was fabricated using a 0.18 μm 1P6M CMOS process. Experimental results indicated that the post-calibration linearity reached 99.6% with an input current of up to 1.5 μA. The static power consumption per digital pixel was 6 μW. Full article

Microplastics are plastic particles ranging in size from 1 μm to 5 mm, emitted at the source or resulting from the degradation of larger objects. Today, their global distribution is one of the major environmental problems recognized by the United Nations Sustainable Development Goals, polluting aquatic, terrestrial and atmospheric systems and requiring avant-garde solutions. Solid–liquid filtration is widely used in both industrial and biological systems, where some aquatic species are examined using very specialized filter-feeding apparatus, and when applied to industrial processes, microparticles can be separated from the water while minimizing maintenance costs, as they require less backwashing or additional energy consumption. The REMOURE project uses the Mediterranean species Mobula mobular (Bonnaterre, 1788) as a reference for the testing and optimization of low-cost microplastic filters applied to wastewater. For this purpose, a hydrodynamic test rig was designed and constructed by considering the hydraulic feeding conditions of the marine species, with a scale factor of 6. This paper presents the design conditions and the evaluation of the test results for the combination of three different variables: (1) flap disposition (two different models were considered); (2) inclination with respect to the flow direction; and (3) flow velocity. The models were printed in polyamide and videos were recorded to evaluate the behaviour of dye injection through the lobes. The videos were processed, and the results were statistically treated and used to calibrate a CFD model to optimize the filter design to be studied in a prototype wastewater treatment plant. Full article

To assess the viability of locations for wave energy farms and design effective coastal protection measures, knowledge of local wave regimes is required. The work described herein aims to develop a low-cost, self-powering wave-measuring device that comprises a floating buoy with a central moonpool. The relative motion of the water level in the moonpool to the buoy will pressurise and depressurise the air above the water column. The variation in air pressure may then be used to estimate the sea-state incident upon the buoy. Small-scale proof of concept tank testing was conducted at a 1:20 scale and at a larger 1:2.4 scale before a full-scale prototype was deployed at the Smartbay test site facility in Galway Bay, Ireland. A number of techniques by which full-scale sea states may be estimated from the pressure spectrum are explored. A successful technique, based on the average of multiple linear squared magnitude of the transfer functions obtained under different wave regimes is developed. The applicability of this technique is then confirmed using validation data obtained during the full-scale sea trials. While the technique has proven useful, investigation into potential seasonal bias has been conducted, and suggestions for further improvements to the technique, based on further calibration testing in real sea states, are proposed. Full article

The design of reliable and accurate indoor lighting control systems for LEDs’ (light-emitting diodes) color temperature and brightness, in an effort to affect human circadian rhythms, has been emerging in the last few years. However, this is quite challenging since parameters, such as the melanopic equivalent daylight illuminance (mEDI), have to be evaluated in real time, using illuminance values and the spectrum of incident light. In this work, to address these issues, a prototype platform has been built based on the low-cost and low-power Arduino UNO R4 Wi-Fi BLE (Bluetooth Low Energy) board, which facilitates experiments with a new control approach for LEDs’ correlated color temperature (CCT). Together with the aforementioned platform, the methodology for mEDI calculation using an 11-channel multi-spectral sensor is presented. With proper calibration of the sensor, the visible spectrum can be reconstructed with a resolution of 1 nm, making the estimation of mEDI more accurate. Full article

Background: Occupational risk assessments of VDT users are usually hindered by the variability of tasks that office workers perform. Digital eye strain is related to the amount of work time dedicated to screen fixation. Purpose: This study aimed to improve the risk assessment of VDT workers by introducing an advanced version of software developed at the University of Brescia. Methods: The prototype enables the recording of the times in front of the screen and those in which the operator actively fixes. It was tested on 30 employees from different offices. The system includes a webcam placed over the workers’ screens and connected with a laptop running specifically developed monitoring software. This experiment required worker-to-worker calibration of the system by the investigators. Results: The obtained data allowed us to distinguish between the period of screen fixation and the presence in front of the monitor. The visual activity varied greatly on a daily basis because of the differences between tasks. The mean facial detection time was approximately 48%, whereas the mean eye fixation time was 29%. Conclusions: The results suggest that our prototype is a promising tool for investigating the relative contributions of screen fixation to the development of digital occupational eye strain. Full article

The main aim of this study is the concept of the magnet holder for the THz undulator utilized in the PolFEL superradiant light source. To achieve maximum flux at high K values (radiation frequencies ranging from 0.5 THz to 5 THz, and K values exceeding 3), it is necessary to use large permanent magnets with dimensions of 100 × 100 × 39.9 mm. For the above assumptions and parameters and specific requirements for magnet positioning, existing design solutions in the literature were found to be insufficient. The main challenges in the design of this holder included the following: (a) the unusually large size of the magnets, (b) requirements of wide-range calibration, and (c) large magnetic forces acting on each magnet, which can approach almost 4 kN. Taking into consideration these challenges, the prototype of the magnet holder was developed and manufactured. The paper presents the findings from both numerical and experimental studies aimed at validating the mechanical behavior and deformation of the proposed magnet holder. The measurements were conducted using two methods—traditional with the use of dial indicators and a novel approach based on the application of the Digital Image Correlation. The results from these numerical and experimental studies indicate that all specified requirements have been satisfactorily met. The study confirms the capability for accurate magnet positioning, demonstrating stable deformation of the holder under a magnetic load. Additionally, it was proved that the positioning of the magnets is both linear and repeatable, with calibration achievable within a range of at least ±0.25 mm. Full article

Pulsating flow signals are widely used in the fields of dynamic calibration of flow meters and reliability testing of fluid transmission pipelines. A high-frequency pulsating flow control valve is proposed, its structure and working principle are introduced, and its mathematical model is also established. Finally, an experimental platform is built to experimentally verify the performance of the high-frequency pulsating flow signal generation of this flow control valve prototype. When applying sinusoidal flow signals of 1–25 Hz, the amplitude of the output flow starts to decay after 2 Hz, and the frequency corresponding to the decay to −3 dB is about 23.5 Hz. The experimental results show that the valve can effectively generate unidirectional sinusoidal flow with a maximum amplitude of 25 L/min and a frequency of 23.5 Hz. Full article

Air pollution monitoring in industrial regions like Moravia-Silesia faces challenges due to complex environmental conditions. Low-cost sensors offer a promising, cost-effective alternative for supplementing data from regulatory-grade air quality monitoring stations. This study evaluates the accuracy and reliability of a prototype node containing low-cost sensors for carbon monoxide (CO) and particulate matter (PM), specifically tailored for the local conditions of the Moravian-Silesian Region during winter and spring periods. An analysis of the reference data observed during the winter evaluation period showed a strong positive correlation between PM, CO, and ${\mathrm{NO}}_2$ concentrations, attributable to common pollution sources under low ambient temperature conditions and increased local heating activity. The Sensirion SPS30 sensor exhibited high linearity during the winter period but showed a systematic positive bias in ${\mathrm{PM}}_{10}$ readings during Polish smog episodes, likely due to fine particles from domestic heating. Conversely, during Saharan dust storm episodes, the sensor showed a negative bias, underestimating ${\mathrm{PM}}_{10}$ levels due to the prevalence of coarse particles. Calibration adjustments, based on the ${\mathrm{PM}}_1{\mathrm{/PM}}_{10}$ ratio derived from Alphasense OPC-N3 data, were initially explored to reduce these biases. For the first time, this study quantifies the influence of particle size distribution on the SPS30 sensor’s response during smog episodes of varying origin, under the given local and seasonal conditions. In addition to sensor evaluation, we analyzed the potential use of data from the Copernicus Atmospheric Monitoring Service (CAMS) as an alternative to increasing sensor complexity. Our findings suggest that, with appropriate calibration, selected low-cost sensors can provide reliable data for monitoring air pollution episodes in the Moravian-Silesian Region and may also be used for future adjustments of CAMS model predictions. Full article