Search Results (12)

This article examines the modeling of sustainable development in transport logistics, focusing on the impact of climate factors, changing weather conditions, and digitalization processes. The study analyzes the complex influence of adverse weather phenomena, such as fog, rain, snow, extreme temperatures, and strong winds, whose frequency and intensity are increasing due to climate change, on the efficiency, safety, and reliability of transport systems across all modes except pipelines. Special attention is paid to the integration of weather-resilient sensor technologies, including LiDAR, thermal imaging, and advanced monitoring systems, to strengthen infrastructure resilience and ensure uninterrupted transport operations under environmental stress. The methodological framework combines comparative analytical methods with economic–mathematical modeling, particularly Leontief’s input–output model, to evaluate the mutual influence between the transport sector and sustainable economic growth within an interconnected ecosystem of economic and technological factors. The findings confirm that data-driven management strategies, the digital transformation of logistics, and the strengthening of centralized hubs contribute significantly to increasing the resilience and flexibility of transport systems, mitigating the negative economic impacts of climate risks, and promoting long-term sustainable development. Practical recommendations are proposed to optimize freight flows, adapt infrastructure to changing weather risks, and support the integration of innovative digital technologies as part of an evolving ecosystem. Full article

Heat flow sensors allow the straightforward measurement of the heat flow emitted from an object by attaching the sensor to the object. However, the inability of this method to control the surface emissivity of the sensor over a wide range lowers the measurement accuracy of a heat flow sensor. This study introduces a flexible heat flow sensor whose surface emissivity can be adjusted over a wide range. This sensor integrates a heat flow detector (HFD), which harnesses the Seebeck effect of a carbon nanotube/polymer composite to convert heat flow into voltage. This conversion exhibits a linear relationship with the heat flow, characterized by a proportional coefficient of 0.6556 mV·W⁻¹. The sensor features an emissivity-controlling layer (ECL), comprising a thin Al film deposited on a flexible polymer film substrate. The surface emissivity of the layer can be adjusted between 0.06 and 0.88 by modulating the thickness of the Al coating. The ECL can be easily attached to and detached from the HFD. The proposed sensor enables the measurement of heat flow from heat sources with various emissivities by simply affixing it to the source. This study shows that the deployment of such sensors is useful for the advanced thermal management of diverse facilities. Full article

Currently, the construction sector is witnessing a growing demand for lightweight solutions, which can be justified by the need to adopt high-performance solutions and the fact that the industry is struggling with a shortage of skilled labour. In this sense, this study focuses on a novel and flexible building wall system, constructed using an innovative extensible LSF profile. To enhance its functionality, a monitoring system comprising printed sensors was integrated into the wall. These sensors underwent a thorough verification process. To evaluate the hygrothermal performance of the complete LSF wall solution and validate the novel monitoring system, an extensive ageing test focused on heat/rain, freeze/thaw cycles was conducted on a large-scale wall prototype. Additionally, this research introduces a novel approach by simulating exceptional solar radiation conditions, surpassing the standard cycles outlined in EAD 040083-00-0404, for the first time in this kind of solution. The results cover the measurements taken inside the building system using the incorporated monitoring system. Additionally, supplementary external temperature and heat flow sensors were used to determine the thermal transmittance. Visual and thermography inspections were also carried out. The findings reveal no instances of failures or defects that could potentially impact the hygrothermal behaviour of the system. The hybrid LSF constructive solution leads to more stable temperatures on the inner surface. The presence of direct solar radiation can raise surface temperatures by up to 5 °C compared to surfaces not exposed to such radiation, even when a light-coloured surface is used. The monitoring system worked correctly. In conclusion, the innovative profile proved to be resistant to hygrothermal cycles and the monitoring system developed is efficient. Full article

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data (“big data”) is pervasive in both modern society and the farming industry. Information accessibility—coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms—offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms’ population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies—and because several unknowns, limitations, and open-ended questions are inevitable—their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis—together with the use of open standards and integration with pathogen molecular epidemiology—have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health. Full article

Bismuth telluride-based thin films have been investigated as the active material in flexible and micro thermoelectric generators (TEGs) for near room-temperature energy harvesting applications. The latter is a class of compact printed circuit board compatible devices conceptualized for operation at low-temperature gradients to generate power for wireless sensor nodes (WSNs), the fundamental units of the Internet-of-Things (IoT). CMOS and MEMS compatible micro-TEGs require thin films that can be integrated into the fabrication flow without compromising their thermoelectric properties. We present results on the thermoelectric properties of (Bi,Sb)₂(Se,Te)₃ thin films deposited via thermal evaporation of ternary compound pellets on four-inch SiO₂ substrates at room temperature. Thin-film compositions and post-deposition annealing parameters are optimized to achieve power factors of 2.75 mW m⁻¹ K⁻² and 0.59 mW m⁻¹ K⁻² for p-type and n-type thin films. The measurement setup is optimized to characterize the thin-film properties accurately. Thin-film adhesion is further tested and optimized on several substrates. Successful lift-off of p-type and n-type thin films is completed on the same wafer to create thermocouple patterns as per the target device design proving compatibility with the standard MEMS fabrication process. Full article

Based on the results of computational fluid dynamics simulations, this study designed and fabricated a flexible thermal-type micro flow sensor comprising one microheater and two thermistors using a micro-electromechanical system (MEMS) process on a flexible polyimide film. The thermistors were connected to a Wheatstone bridge circuit, and the resistance difference between the thermistors resulting from the generation of a flow was converted into an output voltage signal using LabVIEW software. A mini tube flow test was conducted to demonstrate the sensor’s detection of fluid velocity in gas and liquid flows. A good correlation was found between the experimental results and the simulation data. However, the results for the gas and liquid flows differed in that for gas, the output voltage increased with the fluid’s velocity and decreased against the liquid’s flow velocity. This study’s MEMS-based flexible microthermal flow sensor achieved a resolution of 1.1 cm/s in a liquid flow and 0.64 cm/s in a gas flow, respectively, within a fluid flow velocity range of 0–40 cm/s. The sensor is suitable for many applications; however, with some adaptations to its electrical packaging, it will be particularly suitable for detecting biosignals in healthcare applications, including measuring respiration and body fluids. Full article

Fabrication of ring-shaped deposits of microparticles on solid surfaces with the desired length scales and morphology of particle arrangements is of great importance when developing modern optical and electronic resonators, chemical sensors, touch screens, field-emission displays, porous materials, and coatings with various functional properties. However, the controlled formation of ring-shaped patterns scaling from a few millimeters up to centimeters with simultaneous control of particle arrangement at the microscale is one of the most challenging problems in advanced materials science and technology. Here, we report a fabrication approach for ring-shaped structures of microparticles on a glass surface that relied on a local thermal impact produced by the subsurface heater and heat sink. Thermocapillary convection in the liquid covering microparticles in combination with evaporative lithography is responsible for the particle transport and the assembling into the ring-shaped patterns. An advantageous feature of this approach is based on the control of thermocapillary flow direction, achieved by changing the sign of the temperature gradient in the liquid, switching between heating and cooling modes. That allows for changing the particle transfer direction to create the ring-shaped deposits and dynamically tune their size and density distribution. We have studied the influence of the power applied to the heat source/sink and the duration of the applied thermal field on the rate of the ring fabrication, the sizes of the ring and the profile of the particle distribution in the ring. The proposed method is flexible to control simultaneously the centimeter scale and microscale processes of transfer and arrangements of particles and can be applied to the fabrication of ring structures of particles of different nature and shape. Full article

The exhaust system of the light-duty diesel engine has been evaluated as a potential environment for a mechanical energy recovery system for powering an IoT (Internet of Things) remote sensor. Temperature, pressure, gas speed, mass flow rate have been measured in order to characterize the exhaust gas. At any engine point explored, thermal energy is by far the most dominant portion of the exhaust energy, followed by the pressure energy and lastly kinetic energy is the smallest fraction of the exhaust energy. A piezoelectric flexible device has been tested as a possible candidate as an energy harvester converting the kinetic energy of the exhaust gas flow, with a promising amount of electrical energy generated in the order of microjoules for an urban or extra-urban circuit. Full article

The experimental setup implements a simplified PASSYS test cell construction, which is combined with a detailed simulation to reduce measurement effort. To analyze the cell’s dynamic behavior, the test cell was closely monitored with thermal sensors, and different static and dynamic heating modes were applied during a three-week calibration period. Co-heating tests were performed for steady-state measurements and cyclic heating periods account for the transient behavior of the test cell. The cells response was compared to the results of transient simulations with the software packet Modelica. The equation based Modelica framework allowed a detailed transient thermal simulation of the test cell’s dynamic to be set up that shows close agreement with the measurements. In addition, the flexibility of Modelica allowed unforeseen events affecting the experimental setup to be replicated, thereby ensuring an uninterrupted heat flow history of all surfaces. More than 96% of the predicted air temperatures (1 min resolution) match the experimental values within an error band of ±1.5 K, and 90% of all predictions are within ±1.0 K. Full article

This paper presents an efficient and high-sensitive micro-sensor designed for wall shear stress measurement. The main technical application targeted is flow separation detection for closed-loop active flow control. The sensor is a temperature-resistance transducer operating on heat transfer. The device is micro-structured with three substrate-free wires presenting a high aspect ratio, and periodic perpendicular micro-bridges ensuring mechanical toughness and thermal insulation. This design achieves a homogeneous temperature distribution along the wires. Welded on a flexible printed circuit, the sensor is wall-mounted on a wind tunnel. The experiments, conducted in both attached and separated flow configurations, demonstrate the sensor sensitivity to wall shear stress up to 2.4 Pa and the ability of the 3-wires based design to perform flow direction sensing for back-flow detection. Full article

A sensor concept for detection of boundary layer separation (flow separation, stall) and reattachment on airfoils is introduced in this paper. Boundary layer separation and reattachment are phenomena of fluid mechanics showing characteristics of extinction and even inversion of the flow velocity on an overflowed surface. The flow sensor used in this work is able to measure the flow velocity in terms of direction and quantity at the sensor’s position and expected to determine those specific flow conditions. Therefore, an array of thermal flow sensors has been integrated (flush-mounted) on an airfoil and placed in a wind tunnel for measurement. Sensor signals have been recorded at different wind speeds and angles of attack for different positions on the airfoil. The sensors used here are based on the change of temperature distribution on a membrane (calorimetric principle). Thermopiles are used as temperature sensors in this approach offering a baseline free sensor signal, which is favorable for measurements at zero flow. Measurement results show clear separation points (zero flow) and even negative flow values (back flow) for all sensor positions. In addition to standard silicon-based flow sensors, a polymer-based flexible approach has been tested showing similar results. Full article

Flow sensors are the key elements in most systems for monitoring and controlling fluid flows. With the introduction of MEMS thermal flow sensors, unprecedented performances, such as ultra wide measurement ranges, low power consumptions and extreme miniaturization, have been achieved, although several critical issues have still to be solved. In this work, a systematic approach to the design of integrated thermal flow sensors, with specification of resolution, dynamic range, power consumption and pressure insertion loss is proposed. All the critical components of the sensors, namely thermal microstructure, package and read-out interface are examined, showing their impact on the sensor performance and indicating effective optimization strategies. The proposed design procedures are supported by experiments performed using a recently developed test chip,including several different sensing structures and a flexible electronic interface. Full article