What lies beneath: Vertical temperature heterogeneity in a Mediterranean woodland savanna

Cow Body Shape and Automation of Condition Scoring

Power electric devices, such as line inductors or transformers, are limited by current, voltage, and operating temperature. Current is the main culprit behind the heating of all electric devices. Excess heating leads to faster degradation of the insulation and lowers the breakdown voltage. These factors determine the lifetime and reliability of these devices, which can be extended by lowering the operating temperature via cooling. This paper aims to present the numerical investigation of the coupled EM–CFD model of a line reactor (LR) with two cooling systems: air-based natural convection cooling system (AN), and air-natural with water-forced cooling system (ANWF). The design of the inductor cooling system was presented and described. The numerical investigation of both cooling systems is done considering power loss generation, cooling efficiency, and temperature distribution. In addition, the EM–CFD models of examined devices were validated by experiments considering thermal measurements using calibrated thermocouples, thermal image camera, pressure and flow rate measurements, where the temperature was measured in at least 35 points with probes. The tests were performed for three operating currents, resulting in 100%, 75%, and 50% of total power losses in the inductor. The numerical models reach an accuracy in temperature difference with respect to experiments within 5 K and 3.5 K for AN and ANWF cooling, respectively. The presented research shows that the ANWF system is superior and provides significant temperature reduction up to 68 K as well as the maximum temperature of the windings was reduced up to approx. 29.0K at 390 A RMS by use of ANWF. Furthermore, the hot-spot temperature in AN cooling system reached 135 °C, and up to 110 °C for the ANWF system, which can be further decreased down to 60.0 °C by lowering contact resistances. • An analysis of two different line reactor cooling systems: liquid- and air-based. • High accuracy of coupled EM–CFD numerical model within ±10 K. • The air-based cooling system hot-spot temperature of 135 °C at 390 A RMS current. • Significant cooling efficiency improvement by thermal contact resistance reduction. • Required design optimisation of the cooling panels in water-forced cooling system.

This paper presents a method to monitor the thermal peaks that are major concerns when designing Integrated Circuits (ICs) in various advanced technologies. The method aims at detecting the thermal peak in Systems on Chip (SoC) using arrays of oscillators distributed over the area of the chip. Measured frequencies are mapped to local temperatures that are used to produce a chip thermal mapping. Then, an indication of the local temperature of a single heat source is obtained in real-time using the Gradient Direction Sensor (GDS) technique. The proposed technique does not require external sensors, and it provides a real-time monitoring of thermal peaks. This work is performed with Field-Programmable Gate Array (FPGA), which acts as a System-on-Chip, and the detected heat source is validated with a thermal camera. A maximum error of 0.3 °C is reported between thermal camera and FPGA measurements.

Remote sensing (RS), with its large spatial coverage and easily accessible observations, has attracted a lot of attention in recent years. Thermal infrared (TIR) RS, collecting radiation between 3.75 and 12.5 μm in the electromagnetic spectrum, is one of the major parts of RS. TIR RS is widely used in various fields, including evapotranspiration (ET), global climate change, hydrological cycle, vegetation monitoring and urban climate given the important role TIR radiation plays in surface energy and water balance. TIR radiation is closely related to land surface temperature (LST) and land surface emissivity (LSE). Angular variation is an important characteristic of LSE, which could influence the subsequent estimation of surface upwelling longwave radiation (SULR) and LST. In this study, a look-up table (LUT) of directional emissivities was built from the MYD21A product. The compiled LUT was then applied to SULR and LST estimation by considering the angular variation of LSE. The results showed that the influence of LSE angular variation on SULR estimation was not pronounced. Whereas, the influence on LST retrievals was > 0.5 K and the accuracy of the split-window (SW) was improved by > 1 K over barren surfaces after considering LSE directionality. LST is connected to ET through the surface energy balance equation, thereby reflecting vegetation water availability. In this study, applying TIR radiation in agricultural drought early warning was of interest. Based on the underlying principle that the rate of LST rise between 1.5 and 3.5 h after the sunrise is approximately linear and over vegetated surfaces occurs more rapidly under dry conditions as a consequence of stomatal control, the temperature rise index (TRI) was developed using the LST retrievals from the geostationary Multifunction Transport Satellite-2 (MTSAT-2) instrument and using the Himawairi-8 brightness temperatures (BT), respectively. The proposed TRI was evaluated by comparing with more commonly-used indices, including precipitation condition index (PCI), soil moisture condition index (SMCI) and vegetation condition index (VCI). In addition, the indices were also compared to annual wheat yield over large areas in the Australian Wheatbelt. The results showed that the TRI produced spatiotemporal dryness patterns that were very similar to those in soil moisture and precipitation, but with more detail due to its finer resolution. A time lag was found between TRI and observed vegetation condition, supporting the use of TRI in early warning. Among the compared drought indices, the TRI had the strongest and earliest correlation with wheat yield. The TRI calculated from LST and BT had close performances. It is concluded that this study provides insights into the basic theory study as well as practical applications of TIR RS, and adds value to the state-of-the-art studies in the field of TIR RS.

Energy balance application for Erdemir Coke Plant with thermal camera measurements

Thermal camera for System-in-Package (SiP) technology: Transient thermal analysis based on FPGA and Finite Element Method (FEM)

Wildfires emit volatile organic compounds (VOCs) that contribute to ozone and aerosol pollution. Quantification is challenged by the diversity of emitted species and by their complex dependence on fire characteristics, with scarce field observations available for model evaluation. Remote sensing in the thermal infrared (IR) is a powerful tool for detecting fire VOCs: many compounds exhibit distinct signatures at these wavelengths, and measurements are unaffected by fine aerosols prevalent in smoke. Here, we develop the first thermal IR VOC measurements from an aircraft‐based platform, using radiance observations from the Scanning High‐resolution Interferometer Sounder (S‐HIS) deployed aboard the NASA ER‐2 during the 2019 FIREX‐AQ campaign. We focus on methanol and ethene, and employ a neural network retrieval adapted from Cross‐track Infrared Sounder (CrIS) algorithms. The S‐HIS retrievals achieved high precision ( R 2 = 0.95–0.99) and accuracy (median absolute bias <5.5 × 10 15 molec./cm 2 ) versus the full training data set. However, at low‐to‐moderate concentrations, retrieval performance is degraded by instrument noise. When considering scenes below the median methanol signal encountered during FIREX‐AQ, 30‐fold aggregation is needed to achieve R 2 = 0.8, and no amount of aggregation yields the performance that would be achievable for a single pixel with the 10× lower noise of CrIS. The S‐HIS VOC observations exhibit clear enhancements over and downwind of fires that align with those seen by CrIS. Our results provide a foundation for future aircraft‐based VOC measurements in the thermal IR, and emphasize the critical importance of instrument noise for the design of future airborne and spaceborne sounders.

During effusive eruptions, thermal satellite monitoring has proved well suited to map the thermal flux from lava flows. However, during lava fountaining events, thermal contributions from active flows and from the fountain itself cannot be separated in low resolution satellite data. Here using photogrammetry and atmospheric modeling techniques, we compare radiance estimates from long‐range ground‐based thermal camera data (from which the fountain can be excluded) with those from SEVIRI satellite images for a fountaining event at Mount Etna (12 August 2011). The radiant heat flux determined from the ground‐based camera showed similar behavior to values retrieved from Spinning Enhanced Visible and Infrared Imager (SEVIRI); thus the SEVIRI signal is interpreted to be dominated by the lava flows, with minimal contribution from the fountain. Furthermore, by modeling the cooling phase of each pixel inundated by lava, the mean thickness and lava volume (~2.4 × 106 m3) derived from camera images are comparable with those calculated from SEVIRI (~2.8 × 106 m3).

Achieving a quick temperature increase is a burning issue for biophysical applications, like germ inactivation and tumor ablation, and for energy performances, like solar collectors and steam generators. Based on the plasmon resonance phenomenon, noble metallic nanoparticles have emerged as promising weapons due to their very high biocompatibility, optical properties, and high surface-to-volume ratio, increasing energy conversion and allowing the maximum temperature to be reached faster. This work examines the energy conversion in sandwiched glassy platforms with gold nanorods. The platforms are kept vertically in the air and illuminated by a 0.5 W near-infrared laser (808 nm). To describe this aspect theoretically, the size and conversion efficiency of the electromagnetic properties are compromised between the proposed model and the stability of the nanorods. As a research approach, our model of cross-sections and polarizability for the surface effect is proposed, coupled with classical CFD numerical calculations. The results of the proposed model, validated by a thermal camera and spectroscopy measurements, indicate that as long as the energy conversion is visible with relatively low-power lasers (ΔT = 18.5 °C), the platforms do not offer fast heat dissipation. The results indicate that, despite the flow forcing by the air inflow, the entropy generation due to heat conduction is more than three orders higher than the dynamic entropy production. Flow forcing corresponds to the value of the velocity for classical convective motions. Therefore, the delivered heat flux must be distributed via convective transport or the associated high-conductive materials.

:The use of canal water for cooling is an important opportunity for companies to reduce their carbon emissions and save on energy bills. The available models used to evaluate the possibility of using canal water are too complicated and their applications are difficult. As such some potential opportunities for using canal water for cooling are being lost. This paper addresses current concerns to produce an interactive numerical model that will produce a three dimensional representation of the temperature distribution of heated water discharged into a still water region. The interactive model may be manipulated by non technical personnel to evaluate different discharge scenarios and ensure that the proposal does not infringe the stringent regulations imposed by the Environmental Agencies. The proposed model makes use of information gathered from real on-site testing using a thermal camera and grid measurements in addition to a laboratory experimental tank that duplicates the various on-site options. The parameters of temperature, velocity and boundaries were determined in both practical processes using a predefined grid mesh that covered the mixing zone. These practical results gave the turbulent diffusivity which was then used in the formulation of the model that was optimised to represent the real system results. It is shown that the results from the on-site testing, the laboratory results and the 3-D model all give complementary values so validating the final model.

Laser-assisted tape winding (LATW) is an automated process to manufacture tubular fiber reinforced thermoplastic composites such as flywheels rings, pipes, and pressure vessels. The pre-impregnated tapes are bonded to the substrate using a compaction roller and a laser heat source based on the in-situ consolidation mechanism. Multiple physical phenomena take place simultaneously during the LATW process, including kinematics, optics, and heat transfer. The main goal is to develop a generic and quantitatively accurate process design tool leading to predictable part properties suited for product and process optimization with a focus on the process temperature evolution. Firstly, a coupled kinematic-optical-thermal (KOT) model is presented to predict the temperature evolution during multi-layer hoop winding. The continuing heat accumulation during consecutive winding resulted in a gradually increasing process temperature which was also observed by the thermal camera measurements. The roller deformation altered the temperature field by changing the heating length and heat flux distribution. Next, the adjacent hoop winding process used to manufacture composite pipes was studied. Multiple heating and cooling cycles at the substrate edges result in a nonuniform temperature distribution along the substrate width. The obtained temperature history was used in a nonisothermal crystallinity model to predict the degree of crystallinity distribution. Afterwards, a generic KOT model was developed for an arbitrary tooling geometry and winding pattern. Helical winding of the dome part of a pressure vessel was studied by incorporating a varying local tooling curvature and a winding speed. The process temperature changed up to 17-20% due to the increased local surface curvature and process speed validated with the thermal camera measurements. Finally, an optimization framework was introduced by using an inverse KOT (IKOT) model. The optimal laser power distribution was obtained using a grid of independent laser cells. The optimized laser power distribution pattern remained the same during the hoop winding process while the total power reduced. A more non-uniform time-dependent laser power distribution was obtained for the helical winding case. The roadmap towards achieving an accurate process design tool for the LATW processes is evaluated at the end for any tooling geometry, winding angle and process parameters.

A thermographic camera method for measuring the core loss distribution

In this paper, the blackbody radiation (BBR) temperature rise experienced by a 40Ca+ ion confined in a miniature Paul trap and its uncertainty have been evaluated via finite-element method (FEM) modelling. The FEM model was validated through comparisons with thermal camera measurements at several points on a dummy trap. Before the validation, the thermal camera was calibrated by using a PT1000 resistance thermometer. The input modelling parameters were analyzed carefully, and their contributions to the uncertainty of the trap environment temperature were evaluated using the validated FEM model. The result shows that the temperature rise experienced by the 40Ca+ ion is 1.72 K with an uncertainty of 0.46 K. It results in a contribution of 2.2 mHz to the systematic uncertainty of a 40Ca+ ion optical clock, corresponding to a fractional uncertainty 5.4 × 10−18. This is much smaller than the uncertainty caused by the BBR shift coefficient, which is evaluated to be 4.8 mHz and at the 10−17 level in fractional frequency units.

The mass discharge rate is a key parameter for initializing volcanic ash dispersal models. Commonly used empirical approaches derive the discharge rate by the plume height as estimated by remote sensors. A novel approach based on the combination of weather radar observations and thermal camera imagery is presented here. It is based on radar ash concentration estimation and the retrieval of the vertical exit velocities of the explosive cloud using thermal camera measurements. The applied radar retrieval methodology is taken from a revision of previously presented work. Based on the analysis of four eruption events of the Mount Etna volcano (Sicily, Italy) that occurred in December 2015, the proposed methodology is tested using observations collected by three radar systems (at C and X band) operated by the Italian Department of Civil Protection. The total erupted mass was estimated to be about 9·109 kg and 2.4·109 kg for the first and second events, respectively, while it was about 1.2·109 kg for both the last two episodes. The comparison with empirical approaches based on radar‐retrieved plume height shows a reasonably good agreement. Additionally, the comparative analysis of the polarimetric radar measurements provides interesting information on the vertical structure of the ash plume, including the size of the eruption column and the height of the gas thrust region.

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements.