Real-time Temperature Profile Research Articles

Comparative performance of various susceptor materials and vertical cavity shapes for selective microwave hybrid heating (SMHH)

The microwave processing of materials is gaining popularity over the past decade due to its unique heating abilities. The microwave hybrid heating (MHH) technique has effectively processed bulk metallic materials. MHH is assisted by susceptor material which forces metals to absorb microwave radiations. Further, MHH is modified to selective microwave hybrid heating (SMHH) to increase the efficiency of the process. This work examines the performance of Graphite and Charcoal susceptors with a conical vertical cavity for SMHH using FEM simulation. It is observed that the maximum temperature achieved by Graphite was 215 °C at an exposure time of 300 s, whereas, for Charcoal susceptor, it is 655 °C. Further, the effect of different vertical cavity shapes (cylindrical and conical) on the SMHH technique is presented for Charcoal susceptor. For an exposure time of 300 s, the temperature rise in the conical and cylindrical cavity is 655 °C and 319 °C, respectively. From resistive heat flow, time-temperature profile and temperature distribution, it is clear how SMHH is significantly effective for a conical vertical cavity having Charcoal susceptor. In addition, the performance of the conical vertical cavity having Charcoal susceptor was validated through experimental study. The real-time temperature profile was determined through testo 885/testo 890 thermal imaging camera. The observed maximum temperature of the susceptor after heating for 300 s was 639.9 °C.

A Self-generated Chemotaxis-inspired routing method for digital microfluidic cooling of hotspots in integrated circuits

Effective thermal management is of great significance for the reliability of the high-density-power electronics such as the three-dimensional integrated circuits (3DICs). Cooling method based on digital microfluidic (DMF) driven by electrowetting-on-dielectric (EWOD) has been regarded as a promising solution to the effective thermal management of 3DICs. Compared with other traditional cooling methods, DMF has advantages of lower power consumption and especially adaptive cooling ability which can achieve accurate cooling for hot spots inside the 3DICs. However, there are hardly any researches investigating into the droplet routing methods for DMF cooling systems. In this paper, we propose a droplet route optimization method inspired by the self-generated chemotaxis which aims to achieve real-time and parallel routing for multiple coolant droplets to search and cool hot spots. Based on the proposed thermal model of integrated circuit and DMF cooling system, various cooling cases have been simulated with different configurations (e.g., the cooling route and the inlet number). Numerical results show that the proposed self-generated chemotaxis-inspired algorithm (SCA) is capable of searching multiple hot spots based on the real-time temperature profiles and realizing multiple droplets routing simultaneously (i.e., parallel routing and cooling). Compared with traditional ant-colony-algorithm route and direct route, the SCA route provides the best temperature mitigation performance in appropriate inlet-configuration, and its cooling performance can be further improved as the inlet number increases.

Temperature and Relative Humidity Profile Retrieval from Fengyun-3D/HIRAS in the Arctic Region

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

A real-time forecast of tunnel fire based on numerical database and artificial intelligence

The extreme temperature induced by fire and hot toxic smokes in tunnels threaten the trapped personnel and firefighters. To alleviate the potential casualties, fast while reasonable decisions should be made for rescuing, based on the timely prediction of fire development in tunnels. This paper targets to achieve a real-time prediction (within 1 s) of the spatial-temporal temperature distribution inside the numerical tunnel model by using artificial intelligence (AI) methods. A CFD database of 100 simulated tunnel fire scenarios under various fire location, fire size, and ventilation condition is established. The proposed AI model combines a Long Short-term Memory (LSTM) model and a Transpose Convolution Neural Network (TCNN). The real-time ceiling temperature profile and thousands of temperature-field images are used as the training input and output. Results show that the predicted temperature field 60 s in advance achieves a high accuracy of around 97%. Also, the AI model can quickly identify the critical temperature field for safe evacuation (i.e., a critical event) and guide emergency responses and firefighting activities. This study demonstrates the promising prospects of AI-based fire forecasts and smart firefighting in tunnel spaces.

Investigation of the Self-Heating of Q460 Butt Joints and an S-N Curve Modeling Method Based on Infrared Thermographic Data for High-Cycle Fatigue

In this study, we investigated the fatigue behavior of Q460 welded joints using tensile fatigue tests. Furthermore, real-time temperature profiles of the examined specimens were recorded by infrared thermography. Based on the obtained thermographic data, we calculated the entropy production rate of the specimens under different stress amplitudes. Hypothetically, the entropy production during high-cycle fatigue (HCF) could be divided into two parts. The first is induced by inelastic behavior that corresponds to damage accumulation, and the second originates from anelasticity associated with recoverable non-damaging microstructural motions. The turning point of entropy production under different stress levels represents an index for fatigue limit estimation. Then, considering the average damage threshold that exists during HCF, the entropy production related to damage accumulation (cumulative damage entropy) is obtained by testing three specimens under the same stress amplitude above the fatigue limit. Finally, a rapid three-parameter S-N curve with a survival probability rate of 50% is obtained. Then, combined with the maximum likelihood method, the 5% and 95% survival probability rate S-N curves are established. Most of experimental data are distributed in the area between S-N curves that correspond to 5% and 95% survival probability rate, indicating good accordance with the test data.

Observation of vertical wind profiling with lidar based on correction of sensitivity.

A high spectral resolution lidar (HSRL) for simultaneously detecting vertical wind, temperature, and the backscattering ratio in the troposphere is developed. The atmospheric temperature and vertical wind are determined by the Rayleigh scattering spectrum width and Mie scattering spectrum Doppler shift, respectively. The influence of temperature and the backscattering ratio on vertical wind measurement accuracy is also analyzed. The temperature and backscattering ratio affect the wind measurement, which produces the vertical wind offset. A correction considering the effects of the method is conducted considering real-time and on-site temperature profiles and the backscattering ratio to correct wind measurement sensitivity. Measurements of HSRL taken under different weather conditions (fine and hazy days) are demonstrated. Good agreement between the HSRL and the radiosonde measurements was obtained considering lapse rates and temperature inversions. The maximum temperature offsets were 1.3 and 4 K at a height of 1.5 km on fine and hazy days, respectively. Then, real-time and on-site temperature profiles and backscattering ratios were applied to correct the real-time and on-site wind. The corrected wind profiles showed satisfactory agreement with the wind profiles acquired from the calibrated wind lidar. The maximum detection offsets of the retrieved wind speed were reduced from 1 m/s to 0.55 m/s and from 1 m/s to 0.21 m/s, respectively, which were decreases of 0.45 and 0.79 m/s in fine and hazy days after correction of sensitivity. It is evident that the corrected wind method can reduce the influence of temperature and the backscattering ratio on the wind measurement and the offset of vertical wind. The reliability of the method is also proven.

Experimental study on integrated and autonomous conductivity-temperature-depth (CTD) sensor applied for underwater glider

This paper studies a novel CTD sensor (SZQ1-1) which is developed for underwater glider to meet the requirement of autonomous acquisition of high-quality profile hydrodynamic oceanography data. An independently developed electromagnetic induction type conductivity sensor, a quick response thermistor and a high-precision pressure sensor is used to integrate the CTD sensor. Several designs of compact mechanical structure and low-power control acquisition circuit are developed in the CTD sensor. The SZQ1-1 CTD is calibrated with measuring instrument in the laboratory and fourth-degree polynomial fitting equations are developed to fit the curves. After software-based calibration, the SZQ1-1 is compared with SBE 19plus by sea trial. The SZQ1-1 and SBE 19plus were carried by an underwater glider which dived in Northern South China Sea with a maximum depth of 500.36 m. Because the thermal lag error exists in the original data measured with the CTD sensor in the underwater glider, the measured conductivity and salinity data are revised again in the software. According to sea trial results, the real-time temperature, salinity and depth profile data obtained by SZQ1-1 sensor is consistent with the data measured with SBE 19plus.

Exposure Assessment and Sensitivity Analysis for Chilled Shrimp During Distribution: A Case Study of Home Delivery Services in Taiwan.

In this study, we evaluated the temperature requirements for home delivery in Taiwan by considering food safety risks of chilled shrimp that may be contaminated with Vibrio parahaemolyticus. Pathogenic V. parahaemolyticus was chosen because it was the main cause of foodborne outbreaks originating from contaminated seafood in Taiwan. The risk of becoming ill due to consumption of raw shrimp was estimated to be 7.3 × 10-3 per serving, estimated based on the real-time temperature profile. Lowering the maximum temperature to 7°C during transit and cooking shrimps at 100°C for 5 min could reduce the risk by more than 94%. These interventions, therefore, were suggested to be used as an integral part of temperature management control in the home delivery cold chain. These findings can help food authorities to institute temperature management policies and regulations to prevent broken cold chains and reduce food safety risks. PRACTICAL APPLICATION: This research may be applicable to home delivery services that deliver low-temperature food products, such as seafood products.

Drill-exit temperature characteristics in drilling of UD and MD CFRP composites based on infrared thermography

This paper presents a comprehensive study on the complex drill-exit temperature characteristics in the drilling of unidirectional (UD) and multidirectional (MD) CFRPs using a state-of-art microscopy infrared imaging system. For the first time, temperature variation and distribution at drill exit have been revealed in full detail, associated with the CFRP material properties and drilling conditions. Results suggest that the actual drill/CFRP interactions have critical but similar effects on the drill-exit temperatures for UD and MD CFRPs. Specifically, three distinct cutting regions with varying temperature characteristics are evident when the main cutting edge is acting on the drill exit material. In all cases, the temperature distribution features elliptical shape, of which the eccentricity depends on the lay-up sequence and the drilling depth. In addition, the real-time temperature profiles and 2D/3D maximum temperature distribution maps are created with high visualization. With the aid of those findings, the relationships between drilling temperature maxima, their locations and drilling depths have been discovered and temperature effects on drill-exit damages have been elucidated for the first time. MD CFRP is proven more difficult to achieve high drilling qualities at certain fiber cutting angles than UD CFRP due to the associated temperature effects. Such important knowledge enables the identification of the heat affected zones and subsequently informs strategies for reducing the negative temperature effects.

Understanding thermomechanical failure of athletic textiles via the pendulum skid method

Fiber textiles worn by some athletes and basketball and volleyball players experience higher than usual thermomechanical stresses compared to everyday garments because these athletes slide and dive on hardwood courts. Common textile testing procedures, such as the Martindale abrasion tester, effectively test textiles under modest loads and thousands of cycles, but this methodology does not suffice for athletic textiles. In addition, there is not a robust model nor a repeatable test that mimics high thermomechanical stress on fabrics and provides insights on fabric abrasion resistance. We present a model to calculate the temperatures and strain rates that are seen by fabrics undergoing thermomechanical deformation. To enable validation of the model, a fabric pendulum abrasion tester, an adaptation of the Cooper pendulum skid tester, was developed. The tester characterizes high-strain fabric abrasion deformation. This adaptation is statistically reliable and induces repeatable and realistic fabric failure within tens to hundreds of cycles, proving to be analogous to the loads athletes place on their textiles. Analog electronics on the pendulum abrasion tester generate real-time temperature and velocity profiles. A series of 11 unique athletic fabrics were abrasion tested, and it was found that fabrics with macroporosity experience the largest abrasion degradation. Significant degradation sites were further explored using scanning electron microscopy and X-ray diffraction analysis, and it was shown that thermomechanical loading’s effect on fiber microstructure is a function of the fabric construction. This novel abrasion tester and quantitative relationships between fabric structure and degradation mechanisms will enable more data-driven decisions when designing textiles for thermomechanical loads.

Functional Design of Dielectric-Metal-Dielectric-Based Thin-Film Encapsulation with Heat Transfer and Flexibility for Flexible Displays.

In this study, a new and efficient dielectric-metal-dielectric-based thin-film encapsulation (DMD-TFE) with an inserted Ag thin film is proposed to guarantee the reliability of flexible displays by improving the barrier properties, mechanical flexibility, and heat dissipation, which are considered to be essential requirements for organic light-emitting diode (OLED) encapsulation. The DMD-TFE, which is composed of Al2O3, Ag, and a silica nanoparticle-embedded sol-gel hybrid nanocomposite, shows a water vapor transmission rate of 8.70 × 10-6 g/m2/day and good mechanical reliability at a bending radius of 30 mm, corresponding to 0.41% strain for 1000 bending cycles. The electrical performance of a thin-film encapsulated phosphorescent organic light-emitting diode (PHOLED) was identical to that of a glass-lid encapsulated PHOLED. The operational lifetimes of the thin-film encapsulated and glass-lid encapsulated PHOLEDs are 832 and 754 h, respectively. After 80 days, the thin-film encapsulated PHOLED did not show performance degradation or dark spots on the cell image in a shelf-lifetime test. Finally, the difference in lifetime of the OLED devices in relation to the presence and thickness of a Ag film was analyzed by applying various TFE structures to fluorescent organic light-emitting diodes (FOLEDs) that could generate high amounts of heat. To demonstrate the difference in heat dissipation effect among the TFE structures, the saturated temperatures of the encapsulated FOLEDs were measured from the back side surface of the glass substrate, and were found to be 67.78, 65.12, 60.44, and 39.67 °C after all encapsulated FOLEDs were operated at an initial luminance of 10 000 cd/m2 for sufficient heat generation. Furthermore, the operational lifetime tests of the encapsulated FOLED devices showed results that were consistent with the measurements of real-time temperature profiles taken with an infrared camera. A multifunctional hybrid thin-film encapsulation based on a dielectric-metal-dielectric structure was thus effectively designed considering the transmittance, gas-permeation barrier properties, flexibility, and heat dissipation effect by exploiting the advantages of each separate layer.

Temperature profile of ex-vivo organs during radio frequency thermal ablation by fiber Bragg gratings.

We report on the integration of fiber optic sensors with commercial medical instrumentation for temperature monitoring during radio frequency ablation for tumor treatment. A suitable configuration with five fiber Bragg grating sensors bonded to a bipolar radio frequency (RF) probe has been developed to monitor the area under treatment. A series of experiments were conducted on <italic<ex-vivo</italic< animal kidney and liver and the results confirm that we were able to make a multipoint measurement and to develop a real-time temperature profile of the area, with a temperature resolution of 0.1°C and a spatial resolution of 5 mm during a series of different and consecutive RF discharges.

Comparison of Microwave and Conventional Frying on Quality Attributes and Fat Content of Potatoes.

A comparative analysis of quality attributes (moisture, fat, color, and relaxation modulus) of French fries was performed between conventional and microwave frying. Experiments were performed in triplicate for both frying operations at temperatures of 177, 185, and 193 °C for frying times of 60, 90, and 120 s. The real-time pressure and temperature profiles at above conditions indicated that during microwave frying, gage pressure had greater magnitudes that lasted longer, and the temperature increased to boiling point of water faster in comparison to conventional frying. Lower magnitude of negative pressure during microwave frying is expected to have caused lower fat content in fries obtained using this method (0.08 g/g solids less at 185 °C and 0.07 g/g solids less at 193 °C) than conventional frying. The lightness parameter (L* ) decreased to a lesser extent in microwave frying than in conventional frying. The stress relaxation function of the French fries were significantly different between the 2 frying operations. Consumer test confirmed that reduced fat uptake during microwave frying did not compromise with desirable quality attributes of French fries. X-ray micro-computed tomography scanning provided complementary understanding about differences in microstructural properties of fries made using microwave and conventional frying.

Application of optical sensing system in heavy oil recovery

While the heavy oil recovery in China is switching from the traditional Cyclic Steam Stimulation to the more innovative Steam Assisted Gravity Drainage (SAGD), real-time reservoir monitoring system become more and more important for petroleum industries, but tradition electrical systems’ performance on spatial resolution are not good enough. In this paper, we present an optical sensing system based on OTDR and corresponding interpretation, which can obtain the real-time temperature profile and its spatial resolution and temperature resolution is much higher than tradition electrical monitoring system. We utilized this system into the heavy oil recovery in Xinjiang oilfield, the experiment result shows that the position of steam cavity leading edge. This system can provide deep insight into the status of oil recovery process and provide basic data for the following operation.

The Effect of Pulsed Microwave Power on Transesterification of Chlorella sp. for Biodiesel Production

Pulsed microwave technique was employed for the production of biodiesel from Chlorellasp. via transesterification. Real-time microwave power and temperature profiles were used for the evaluation of efficiency of biodiesel production. The effect of power setting was determined in the range of 100–1000 W at the fixed reaction time (10 min) and temperature (60°C). In this work, the highest yield of biodiesel per unit energy consumption observed was 0.53% by weight of crude lipid per kilo joule at 250 W. From the results in this study, the efficiency of biodiesel production was correlated to the uniform pulse intensity and pulse frequency during the reaction process provided at the power setting of 250 W.

Correction of temperature influence on the wind retrieval from a mobile Rayleigh Doppler lidar**Project supported by the National Natural Science Foundation of China (Grant Nos. 41174130, 41174131, 41274151, and 41304123).

A mobile Rayleigh Doppler lidar based on double-edge technique is implemented for simultaneously observing wind and temperature at heights of 15 km–60 km away from ground. Before the inversion of the Doppler shift due to wind, the Rayleigh response function should be calculated, which is a convolution of the laser spectrum, Rayleigh backscattering function, and the transmission function of the Fabry–Perot interferometer used as the frequency discriminator in the lidar. An analysis of the influence of the temperature on the accuracy of the line-of-sight winds shows that real-time temperature profiles are needed because the bandwidth of the Rayleigh backscattering function is temperature-dependent. An integration method is employed in the inversion of the temperature, where the convergence of this method and the high signal-to-noise ratio below 60 km ensure the accuracy and precision of the temperature profiles inverted. Then, real-time and on-site temperature profiles are applied to correct the wind instead of using temperature profiles from a numerical prediction system or atmosphere model. The corrected wind profiles show satisfactory agreement with the wind profiles acquired from radiosondes, proving the reliability of the method.

A Novel Soft Sensor for Real-Time Monitoring of the Die Melt Temperature Profile in Polymer Extrusion

Polymer extrusion is the most fundamental technique for processing polymeric materials, and its importance is increasing due to the rapid growth of worldwide demand for polymeric materials. However, the process thermal monitoring is experiencing several problems resulting in poor process diagnostics and control. Most of the existing process thermal monitoring methods in industry only provide point/bulk measurements, which are less detailed and low in accuracy. Physical thermal profile measurements across the melt flow may not be industrially compatible due to their complexity, access requirements, invasiveness, etc. Therefore, inferential thermal profile monitoring techniques are invaluable for obtaining detailed, accurate, and industrially compatible measurements and, hence, to achieve improved process control. In this paper, a novel soft sensor strategy is proposed to predict the real-time temperature profile across the die melt flow in polymer extrusion for the first time in industry or research. It is capable of determining the melt temperature at a number of die radial positions only based on six readily measurable process parameters. A comparison between the simulation results of the novel melt temperature profile prediction soft sensor and the experimental measurements showed that the soft sensor can predict the real-time melt temperature profile of the die melt flow with good accuracy. Therefore, this will offer a promising solution for making real-time melt temperature profile measurements noninvasively in polymer extrusion, and also, it should be applicable to other polymer processes only with a few modifications. Moreover, this technique should facilitate in developing an advanced process thermal control strategy.

Design and Proof-of-Concept Use of A Circular PMMA Platform with 16-Well Sample Capacity for Microwave-Accelerated Bioassays

We demonstrate the design and the proof-of-concept use of a new, circular poly(methyl methacrylate)-based bioassay platform (PMMA platform), which affords for the rapid processing of 16 samples at once. The circular PMMA platform (5 cm in diameter) was coated with a silver nanoparticle film to accelerate the bioassay steps by microwave heating. A model colorimetric bioassay for biotinylated albumin (using streptavidin-labeled horse radish peroxidase) was performed on the PMMA platform coated with and without silver nanoparticles (a control experiment), and at room temperature and using microwave heating. It was shown that the simulated temperature profile of the PMMA platform during microwave heating were comparable to the real-time temperature profile during actual microwave heating of the constructed PMMA platform in a commercial microwave oven. The model colorimetric bioassay for biotinylated albumin was successfully completed in ~2 min (total assay time) using microwave heating, as compared to 90 min at room temperature (total assay time), which indicates a ~45-fold decrease in assay time. Our PMMA platform design afforded for significant reduction in non-specific interactions and low background signal as compared to non-silvered PMMA surfaces when employed in a microwave-accelerated bioassay carried out in a conventional microwave cavity.

A software to merge temperature and salinity profiles with climatology

Temperature and salinity are two major parameters deciding the characteristics of the ocean water column. Accurate information of these parameters is always a pre-requisite for any study of major climatic/physical processes. The insitu measurement of these parameters is done using instruments such as XBT, XCTD and CTD. Most of the instances, the data will not be collected upto the bottom depth due to instrument or time limitations. In such cases, the collected profiles are artificially extended up to ocean bottom, which is not always true. A better option is to extract the profile upto bottom by blending the insitu profile with climatology.The Profile blending software, written in Visual Basic, is for merging real time insitu temperature and salinity profiles with the climatology profiles for providing the data from surface to bottom. This s/w provides a smoother transition of gradient across the merge point without disturbing the insitu data. It also provides the climatological salinity profile for the corresponding near real time temperature profile obtained from expendable bathythermograph (XBT) records.

Optical properties of super stoichiometric TiN1 + x thin films

Nitrogen-rich titanium nitride (TiN1+x) thin films containing between 70.4at.% and 87.0at.% nitrogen were synthesized and deposited onto single crystal silicon with a (100) crystallographic orientation via the reactive magnetron direct current (DC)-sputtering by systematically varying the process pressure and substrate temperature. The ultraviolet and visible optical properties of these chemically unique TiN1+x thin films have been explored vs. surface roughness and stoichiometry. The specular and diffuse reflectances are linearly coupled to the root mean square surface roughness. The reflectance and absorption were shown to be wavelength dependent. Absorption coefficients for these non-transparent thin films were experimentally determined by monitoring the real-time transient temperature profile of the films and directly correlating the maximum temperature increment to the linear absorption coefficient. The linear absorption coefficient was found to range between 9.11×105 and 3.84×106cm−1 and is strongly coupled to the incident wavelength and nitrogen content. The interaction depths range between 2 and 11nm, indicating interaction only near the film surface.