Thermal Feedback Research Articles

Impact of surface current and temperature feedback on kinetic energy over the North-East Atlantic from a coupled ocean / atmospheric boundary layer model

A one-dimensional Atmospheric Boundary Layer (ABL1D) model is coupled with the NEMO ocean model and implemented over the Iberian–Biscay–Ireland (IBI) area at 1/36° resolution to investigate the damping effect of the current and the thermal feedback on the kinetic energy (KE) at the mesoscale. This type of coupling between an ocean model and an ABL1D is a newly proposed approach as an alternative of intermediate complexity between bulk forcing and full coupling with an atmosphere model. In ABL1D, the prognostic tracers are nudged toward large-scale variables and the wind is guided by a low-frequency geostrophic wind provided from the ERA-Interim reanalyses. First, the ABL1D is successfully validated against satellite observations regarding the wind, and the dynamic coupling coefficient (linking the near surface wind and wind-stress to the of the surface currents) are consistent with the literature, over the period 2016–2017. Our results show that the thermal feedback has a negligible impact on kinetic energy (KE) and does not influence the strength of the current feedback in the region. Given the ABL1D physics, this further indicates that the changes in the vertical wind structure caused by CFB are primarily governed by local mechanical mechanisms associated with surface wind-stress condition, rather than by thermodynamic or non-local processes within the planetary boundary layer. The induced KE reduction by the current feedback amounts to 14% at the surface and propagates down to 2000 m, indicating that it can modify the vertical distribution of KE throughout the water column. KE reductions in the surface boundary layer (0 – 300 m) and in the interior (300 – 2000 m) are attributed to a reduction of the surface wind work by 4%, and of the pressure work by 7%, respectively. The Ekman pumping anomalies induced by the current feedback tend to attenuate eddy activity and horizontal pressure gradients at depth, illustrating the potential of the current feedback to induce a geostrophic adjustment on the water column. These results illustrate the relevance of the proposed ABL1D coupling approach for reproducing the wind-current coupling (a.k.a. current feedback effect) which cannot be taken into account straightforwardly with simple bulk forcing.

Experimental study on flame behavior and heat transfer mechanism of ethanol spill fire in tunnels under upwind and downwind environment

The primary objective of this work was to examine the influence of wind speed and wind direction, specifically upwind and downwind, on the flame characteristics, heat transfer processes, and burning rate laws of ethanol spill fires within a tunnel environment. The findings reveal that the flame height is initially controlled by the by the discharge rate, which ultimately transitions to being controlled by longitudinal ventilation. As wind speed escalates in upwind conditions, the combustion area first decreases and then increases, whereas in downwind scenarios, it first increases and then decreases. Convection emerges as the predominant thermal feedback mechanism for spill fires in windy conditions, particularly exhibiting heightened intensity in downwind environment. It is noteworthy that between 20% and 45% of the heat within the fuel layer dissipates through conduction and convection between the fuel and its substrate, with downwind environments experiencing heightened heat loss; approximately 90% of this heat loss in ethanol spill fires is attributed to conduction. These disparities in heat transfer processes ultimately culminate in a higher burning rate for spill fires in upwind environments compared to downwind counterparts.

RABBITS – II. The impact of AGN feedback on coalescing supermassive black holes in disc and elliptical galaxy mergers

ABSTRACT In this study of the ‘Resolving supermAssive Black hole Binaries In galacTic hydrodynamical Simulations’ (RABBITS) series, we investigate the orbital evolution of supermassive black holes (SMBHs) during galaxy mergers. We simulate both disc and elliptical galaxy mergers using the ketju code, which can simultaneously follow galaxy (hydro-)dynamics and small-scale SMBH dynamics with post-Newtonian corrections. With our SMBH binary subgrid model, we show how active galactic nuclei (AGNs) feedback affects galaxy properties and SMBH coalescence. We find that simulations without AGN feedback exhibit excessive star formation, resulting in merger remnants that deviate from observed properties. Kinetic AGN feedback proves more effective than thermal AGN feedback in expelling gas from the centre and quenching star formation. The different central galaxy properties, which are a result of distinct AGN feedback models, lead to varying rates of SMBH orbital decay. In the dynamical friction phase, galaxies with higher star formation and higher SMBH masses possess denser centres, become more resistant to tidal stripping, experience greater dynamical friction, and consequently form SMBH binaries earlier. As AGN feedback reduces gas densities in the centres, dynamical friction by stars dominates over gas. In the SMBH hardening phase, compared to elliptical mergers, disc mergers exhibit higher central densities of newly formed stars, resulting in accelerated SMBH hardening and shorter merger time-scales (i.e. $\lesssim 500$ Myr versus $\gtrsim 1$ Gyr). Our findings highlight the importance of AGN feedback and its numerical implementation in understanding the SMBH coalescing process, a key focus for low-frequency gravitational wave observatories.

Experimental investigation on flame characteristics in a linear array of dual spill fire

In the process of petroleum production and transportation, a porous leakage accident can easily lead to combustion behaviors such as fire merging, resulting in more severe consequences. This study explores the combustion characteristics of merging spill fires through experimental investigations, incorporating dual leakage holes with varying spacing to examine their impact on the combustion process. The experimental results suggest that the flame height undergoes a pattern of initial decrease followed by an increase with the gradual expansion of leakage spacing, owing to the coupling effects of air entrainment and thermal radiation feedback within the additional entrainment zone. Based on the developmental pattern of flames with respect to leakage spacing, this study categorizes the dual spill fire into three states: which are: (1) full merging state, (2) intermittent merging state, and (3) separation state. The flame height prediction model is established for different merging states, considering parameters such as the fuel discharge rate and the leakage spacing of dual spill fire. The experiment reveals that the flame pulsation frequency (FPF) of the spill fire follows the pattern observed in pool fire FPF, and an FPF model for dual spill fire in all states is obtained through the fitting. Finally, the coupled heat transfer between dual fire sources is considered, and a burning rate model for dual spill fire in intermittent merging states is established.

Study on flame propagation characteristic and mechanism of polypropylene dust explosion

Polypropylene dust explosion poses a significant threat to the safe production of synthetic resin. To elucidate the flame propagation mechanism of polypropylene dust explosions, the flame propagation characteristics of polypropylene dust were experimentally studied. The minimum explosible concentration (MEC) for polypropylene particles with diameter < 75 μm, 75–100 μm, and 100–212 μm was 50 g/m3,100 g/m3,150 g/m3, respectively. Obvious fluctuations were observed in the flame propagation velocity of small particles, with smaller particles exhibiting more pronounced fluctuations, primarily caused by thermal feedback between the particles in the preheating zone and the reaction zone. While for large particles, the flame temperature exhibited multiple peaks, resulted from the discrete flame floating in front of the flame. The combustion process of polypropylene dust comprised the diffusion combustion of large particles and the gas-phase combustion of combustible gases pyrolyzed by small particles.

Feature correlation method for image reconstruction evaluation in under-sampled scanning probe microscopy

We introduce an advanced feature-correlation approach for evaluating the accuracy of data completion in scanning probe microscopy (SPM). Our method utilizes characteristic patterns from conventional SPM images and their reconstructions via data interpolation. We develop a refined comparative evaluation algorithm based on correlation coefficients. This algorithm provides a precise assessment by effectively addressing SPM-specific distortions such as thermal drift, feedback error, and noise limitations often overlooked by traditional metrics such as peak signal-to-noise ratio and structural similarity index measure. The effectiveness of our approach is demonstrated through its application in high-resolution and extensive scanning tunneling microscopy assessments.

Modelling flame-to-fuel heat transfer by deep learning and fire images

In numerical fire simulations, the calculation of thermal feedback from the flame to the solid and liquid fuel surface plays a critical role as it connects the fundamental gas-phase flame burning and condensed-phase fuel gasification. However, it is a computationally intensive task in CFD fire modelling methods because of the requirement of a high-resolution grid for calculating the interface heat transfer. This paper proposed a real-time prediction of the flame-to-fuel heat transfer by using simulated flame images and a computer-vision deep learning method. Different methanol pool fires were selected to produce the image database for training the model. As the pool diameters increase from 20 to 40 cm, the dominant flame-to-fuel heat transfer shifts from convection to radiation. Results show that the proposed AI algorithm trained by flame images can predict both the convective and radiative heat flux distributions on the condensed fuel surface with a relative error below 20%, based on the input of real-time flame morphology that can be captured by a larger grid size. Regardless of growing or decaying fires or puffing flames induced by buoyancy, this method can further predict the non-uniform distribution of heat transfer coefficient on the interface rather than using empirical correlations. This work demonstrates the use of AI and computer vision in accelerating numerical fire simulation, which helps simulate complex fire behaviours with simpler models and smaller computational costs. Highlights A total framework between AI model and fire simulation software is designed to further enhance the reliability of AI-based fire simulations. A standard pool fire simulation database is built using numerical model recommend by the IAFSS Computation Group. A deep learning model is developed to predict both the convective and radiative heat flux distributions on the condensed fuel surface using numerical images database. The demonstration showcases the application of AI and computer vision to accelerate numerical fire simulation.

Near-Surface Atmospheric Response to Meso- and Submesoscale Current and Thermal Feedbacks

Abstract Current feedback (CFB) and thermal feedback (TFB) have been shown to strongly influence both atmospheric and oceanic dynamics at the oceanic mesoscale (10–250 km). At smaller scales, oceanic submesoscale currents (SMCs; 0.1–10 km) have a major influence on the ocean’s energy budget, variability, and ecosystems. However, submesoscale air–sea interactions are not well understood because of observational and modeling limitations related to their scales. Here, we use a realistic submesoscale-permitting coupled oceanic and atmospheric model to quantify the spatiotemporal variability of TFB and CFB coupling in the northwest tropical Atlantic Ocean. While CFB still acts as a submesoscale eddy killer by inducing an energy sink from the SMCs to the atmosphere, it appears to be more efficient at the submesoscale by approximately 30% than at the mesoscale. Submesoscale CFB affects the surface stress, however, the finite time scale of SMCs for adjusting the atmospheric boundary layer results in a diminished low-level wind response, weakening partial ocean reenergization by about 70%. Unlike at the mesoscale, submesoscale CFB induces stress/wind convergence/divergence, influencing the atmospheric boundary layer through vertical motions. The linear relationship between the surface stress derivative or wind derivative fields and sea surface temperature gradients, widespread at the mesoscale, decreases by approximately 35% ± 7% or 77% ± 10%, respectively, at the submesoscale. In addition, submesoscale TFB induces turbulent heat fluxes comparable to those at the mesoscale. Seasonal variability in meso- and submesoscale CFB and TFB coupling is mostly related to background wind speed. Also, disentangling submesoscale CFB and TFB is challenging because they can reinforce or counteract each other.

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. We focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.Novelty and Significance statement:• A new computational model is proposed to simulate wildland fire behavior at high levels of resolution capable of capturing vegetation- and flame-scale phenomena.• Solid biomass vegetation processes are treated using a discrete particle model that features a porous medium formulation and includes a description of in-depth oxygen mass diffusion, and exothermic oxidative pyrolysis and char oxidation reactions.• The computational model is shown to be capable of simulating the transition from flaming to smoldering combustion, often observed in wildland fire spread problems.

Effect of width and slope of large cross-section tunnel on ceiling smoke temperature under natural ventilation

ABSTRACT When a fire occurs in a large cross-section tunnel with slope, the distribution characteristic of ceiling smoke temperature illustrates special laws under the effect of chimney effect, the thermal radiation feedback, and the air entrance limit from walls. A series of numerical simulations are conducted through FDS simulation software based on the actual size of highway tunnel. The influence of large cross-section tunnel width and slope on ceiling smoke temperature when fire occurs are discussed. The research results show that (1) as the tunnel slope increases from 5° to 20°, the distance between the maximum ceiling smoke temperature point and the fire source is 0.5 m, 1 m, 1.7 m, 2.4 m, respectively, and the distance between the ceiling impact point and the fire source is 1 m, 1.8 m, 2.3 m, 3 m, respectively. As the tunnel width increases from 10 m to 20 m, the distance between maximum ceiling smoke temperature point and fire source increases 0.9 m, 1.1 m, 1.3 m, 1.8 m, 2.5 m, and 2.6 m. (2) The prediction formula of maximum ceiling smoke temperature is modified, and a dimensionless relationship among the maximum ceiling smoke temperature and tunnel slope and tunnel width is established. (3) The formula of longitudinal ceiling smoke temperature distribution is modified, and the relationship among tunnel slope, tunnel width, tunnel height, and longitudinal ceiling smoke temperature distribution is established. The research conclusions can provide a theoretical basis for fire prevention design, smoke control and evacuation of this kind of large cross-section tunnel fire.

A sensory-motor hand prosthesis with integrated thermal feedback

Recently, we reported the presence of phantom thermal sensations in amputees: thermal stimulation of specific spots on the residual arm elicited thermal sensations in their missing hands. Here, we exploit phantom thermal sensations via a standalone system integrated into a robotic prosthetic hand to provide real-time and natural temperature feedback. The subject (a male adult with unilateral transradial amputation) used the sensorized prosthesis to manipulate objects and distinguish their thermal properties. We tested his ability to discriminate between (1) hot, cold, and ambient temperature objects, (2) different materials (copper, glass, and plastic), and (3) artificial versus human hands. We also introduced the thermal box and block test (thermal BBT), a test to evaluate real-time temperature discrimination during standardized pick-and-place tasks. The subject performed all three discrimination tasks above chance level with similar accuracies as with his intact hand. Additionally, in all 15 sessions of the thermal BBT, he correctly placed more than half of the samples. Finally, the phantom thermal sensation was stable during the 13 recording sessions spread over 400days. Our study paves the way for more natural hand prostheses that restore the full palette of sensations. This work was funded by the Bertarelli Foundation (including the Catalyst program); the Swiss National Science Foundation through the National Centre of Competence in Research (NCCR) Robotics; the European Union's Horizon 2020 research and innovation program; the Horizon Europe Research& Innovation Program; the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP); and the Tuscany Health Ecosystem.

Developing a novel personal thermoelectric comfort system for improving indoor occupant’s thermal comfort

Personal comfort systems (PCSs), which target to condition only the occupied zones of indoor space, have received considerable interest due to their validity in thermal comfort improvement and building energy saving. Recently, the thermoelectric module (TEM) has been utilized in the design of PCS for its high reliability, small size and noise-free operation. However, the PCSs using the TEM generally lack the effective control strategy with occupant’s feedback, thus reducing their actual effectiveness on improving thermal comfort. In this paper, a novel personal thermoelectric comfort system (PTCS) is developed with a feedback control framework embedded into it. The PTCS is mainly composed of a thermoelectric conversion unit, a micro blower, control/drive modules and a tube network. A thermal comfort feedback control strategy is proposed for the PTCS. In this strategy, a thermal comfort feedback table is established based on offline experiments, and the tube outlet airflow velocity and temperature setpoints are obtained simultaneously through the table look-up method. Then, the neuron PID control algorithm and pulse width modulation (PWM) of voltage are adopted to adjust the tube outlet airflow velocity and temperature for tracking the obtained setpoints. Experimental results validate the effectiveness of the thermal comfort feedback control strategy. Thermal imaging results on human body demonstrate the availability of the developed PTCS. Performance comparison with other PCSs is also provided, which indicates the potential for practical applications.

Remapping Wetness Perception in Upper Limb Amputees

Recent research has made remarkable strides in restoring sensory feedback for prosthetic users, including tactile, proprioceptive, and thermal feedback. Herein, a sensory modality that has been largely neglected is explored: the ability to perceive wetness. Providing moisture‐related information to prosthesis users can increase their overall sensory palette toward a more natural sensory experience. A rapid decrease in skin temperature is found to trigger the illusion of contact with something wet. Two body parts were tested, the upper arm and the lateral abdomen, in a group of non amputated participants, and it was found that a wetness sensation can be elicited and maintained for at least 10 s in 86% and 93% of participants, respectively. It is then demonstrated how to mediate the wetness sensation in real‐time using a thermal wearable device that mimics the thermal properties of the skin. Finally, two upper limb amputee individuals used their prosthetic arm, sensorized with the device, to discriminate between three levels of moisture; their detection accuracy was similar to one they had with their intact hands. The current study is a stepping stone for future prostheses aimed at restoring the richness of sensory experience in upper limb amputees.

3D Multimodal Sensing and Feedback Finger Case for Immersive Dual‐Way Interaction

AbstractWith the rapid development of virtual reality (VR) technology, artificial intelligence , and the Internet of Things , a new era of immersive interaction with the digital world has emerged. In this context, a novel soft finger case with 3D multi‐modal sensing and feedback functions (3D‐SFC) is presented. The device leverages multiple material properties to create a modulated fingertip haptic feedback for the perception of orientation and force, triboelectric nanogenerator (TENG) sensing with dynamic and static responses and control of movement, and thermal feedback based on resistive heating of TENG electrodes. The integrated TENG tactile sensing unit in the device is capable of recognizing the texture of an object's surface, providing users with a more natural and intuitive way of interacting with digital objects. The spatial consistency of multi‐modal sensing and feedback enhances human‐machine interaction in various fields such as healthcare, manufacturing and assembly, and gaming, etc. The proposed device represents a new intelligent sensing solution for achieving cross‐space sensory interaction, opening up new possibilities for the future of VR and digital interaction.

Burning characteristic and ceiling temperature of moving fires in a tunnel: A comparative study

Moving fire is a very important fire scenario in highway tunnel and subway tunnel. Compared to fixed fire sources, there is still limited research on moving fires in tunnels. In order to reveal the burning characteristics and evolutionary mechanisms of moving fires in tunnels, this study conducted reduced scale tunnel fire experiments on moving fires under natural ventilation conditions (Movefire) at travelling speeds ranging from 0.5 m/s to 2.0 m/s, as well as fixed fires under longitudinal ventilation (Ventfire) velocities ranging from 0.5 m/s to 2.0 m/s. The results demonstrate that it is unreasonable to solely use Ventfire experiments as a substitute for Movefire experiments to study fire development and ceiling smoke temperature distributions. When the travelling speed of fire and the ventilation velocity were equal, the HRRs of Movefires were less than those of Ventfires. At the same relative moving velocity of 0.5 m/s, Ventfire received more fresh air to increase burning intensity, while Movefire experienced decreases in thermal feedback and burning intensity. The Movefire smoke temperature rise was small and short in duration, while the Ventfire smoke temperature rise was large and long in duration. Furthermore, the dimensionless maximum ceiling temperature rise of the Movefire experiment was lower than that of the Ventfire experiment. And then a modified ceiling temperature model applicable to the Movefire experiment was proposed by introducing a speed correction factor.

Neural correlates of thermal stimulation during active touch.

Thermal feedback technologies have been explored in human-computer interaction to provide secondary information and enhance the overall user experience. Unlike fast-response haptic modalities such as vibration and force feedback, the human brain's processes associated with thermal feedback are not fully understood. In this study, we utilize electroencephalography (EEG) brain imaging to systematically examine the neural correlates associated with a wide range of thermal stimuli, including 9, 15, 32, and 42°C, during active touch at the fingertip. A custom experimental setup is developed to provide thermal stimulation at the desirable temperature levels. A total of 30 participants are recruited to experience the four levels of thermal stimulation by actively touching a thermal stimulation unit with the index finger while recording brain activities via EEG. Time-frequency analysis and power spectral density (PSD) of the EEG data are utilized to analyze the delta, theta, alpha, beta, and gamma frequency bands. The results show that the delta, theta, and alpha PSDs of 9 and 15°C stimuli are significantly higher than the PSDs of 32 and 42°C in the right frontal area during the early stage of the stimulation, from 282 ms up to 1,108 ms (One-way ANOVA test, Holm-Bonferroni correction, p < 0.05). No significant differences in PSDs are found between 9 and 15°C thermal stimuli or between 32 and 42°C thermal stimuli. The findings of this study inform the development of thermal feedback system in human-computer interaction.

Data-Driven Contact-Based Thermosensation for Enhanced Tactile Recognition.

Thermal feedback plays an important role in tactile perception, greatly influencing fields such as autonomous robot systems and virtual reality. The further development of intelligent systems demands enhanced thermosensation, such as the measurement of thermal properties of objects to aid in more accurate system perception. However, this continues to present certain challenges in contact-based scenarios. For this reason, this study innovates by using the concept of semi-infinite equivalence to design a thermosensation system. A discrete transient heat transfer model was established. Subsequently, a data-driven method was introduced, integrating the developed model with a back propagation (BP) neural network containing dual hidden layers, to facilitate accurate calculation for contact materials. The network was trained using the thermophysical data of 67 types of materials generated by the heat transfer model. An experimental setup, employing flexible thin-film devices, was constructed to measure three solid materials under various heating conditions. Results indicated that measurement errors stayed within 10% for thermal conductivity and 20% for thermal diffusion. This approach not only enables quick, quantitative calculation and identification of contact materials but also simplifies the measurement process by eliminating the need for initial temperature adjustments, and minimizing errors due to model complexity.

Experimental study on the influence of restricted distance on the discrete flame spread of different widths

In this paper, the effects of varying material widths on the propagation of discrete fires within diverse confined space conditions are investigated experimentally. The width-induced mechanisms influencing the flame spread of discrete solid surfaces in distinct confined spaces are comprehensively discussed, encompassing flame characteristics, pyrolysis front dynamics, flame spread rate, and mass loss rate. The findings reveal that the dimensionless flame height and width conform to a negative power relationship at varying restricted distances. Furthermore, a positive correlation between the width of the PMMA in confined spaces and both the flame spread rate and the mass loss rate is established. Notably, when the width is fixed, the confined space plays a dominant role in the propagation of flames. As the restricted distance decreases, the flames become more slender. Additionally, flame height, flame spread rate, and mass loss rate increase with the widening of the material. However, as the restricted distance becomes smaller, the effect of width becomes less pronounced. Under conditions of same restricted distance, an increased width results in a higher radiation factor, thereby enhancing the thermal feedback of the wall to the material, which in turn accelerates the spread rate of discrete flames. Moreover, due to the dominant role of radiant heat feedback provided by the confined walls to the discrete PMMA panels, the proportion of heat transferred by convection in the flames is minimal. Consequently, the influence of the convective coefficient's width variation on flame spread is relatively minor within confined spaces. Ultimately, an energy conservation model under confined spaces was established, which facilitated the analysis of the comprehensive mechanism of flame spread influenced by varying confined spaces and material widths.

Skin-interfaced microfluidic sweat collection devices for personalized hydration management through thermal feedback.

Non-electronic wearables that utilize skin-interfaced microfluidic technology have revolutionized the collection and analysis of human sweat, providing valuable biochemical information and indicating body hydration status. However, existing microfluidic devices often require constant monitoring of data during sweat assessment, thereby impeding the user experience and potentially missing anomalous physiological events, such as excessive sweating. Moreover, the complex manufacturing process hampers the scalability and large-scale production of such devices. Herein, we present a self-feedback microfluidic device with a unique dehydration reminder through a cost-effective "CAD-to-3D device" approach. It incorporates two independent systems for sweat collection and thermal feedback, including serpentine microchannels, reservoirs, petal-like bursting valves and heating chambers. The device operates by sequentially collecting sweat in the channels and reservoirs, and then activating thermal stimulators in the heating chambers through breaking the valves, initiating a chemical exothermic reaction. Human trials validate that the devices effectively alert users to potential dehydration by inducing skin thermal sensations triggered by sweat sampling. The proposed device offers facile scalability and customizable fabrication, and holds promise for managing hydration strategies in real-world scenarios, benefiting individuals engaged in sporting activities or exposed to high-temperature settings.

Micro Flow Sensor With High Sensitivity and Resolution Based on Thermal Feedback and Digitized Power Distribution

Micro Flow Sensor With High Sensitivity and Resolution Based on Thermal Feedback and Digitized Power Distribution