Accurate Temperature Measurements Research Articles

Arcjet Evaluation of Thermocouple Performance in Flexible Thermal Protection System Materials

The flexible thermal protection system (FTPS) on NASA’s low-Earth-orbit flight test of an inflatable decelerator vehicle was instrumented with thermocouples to measure the in-depth thermal response during entry into Earth’s atmosphere. Accurate flight temperature measurements are critical for verifying vehicle performance during the flight test and reducing uncertainties in the thermal models, but the deployable nature of inflatable decelerator technology presents challenges. The thermocouples need to be compactable, cannot damage the FTPS or the inflatable structure, and need to be able to withstand high temperatures and large thermal gradients. The present paper details the arcjet testing that was performed to examine the potential error sources associated with instrumenting NASA’s FTPS with different thermocouple Types (Type K versus Type N), wire gauges (30 versus 28 American wire gauge), insulations (glass versus ceramic), and barriers (mica versus no mica). Several error sources were identified, including 1) conductive deposits on the thermocouple insulation electrically shorting the thermocouple leads; 2) melting of the glass thermocouple insulation, allowing for electrical shorting of the thermocouple leads; 3) thermocouple leads melting, resulting in loss of signal; and 4) oxidation of the positive thermocouple lead (known as green rot), generating a drift in the measured output. A mica tape wrap around each individual thermocouple lead was successfully used to mitigate the first error source, and switching to ceramic insulation eliminated the second error source. The third and fourth error sources were examined by exploring the effect of the thermocouple type and wire gauge. Thermocouple solutions that minimize the potential error sources at each layer in the FTPS are presented. Finally, the arcjet test results are compared to the previously reported ground-based tube furnace test results, and their applicability to the flight environment is discussed.

Measurement performance evaluation and noise compensation for a Fourier transform infrared–based pyrometer

The Fourier transform infrared (FTIR) spectrometer is widely used for spectrum analysis and radiation intensity measurement. In this work, a pyrometer with the temperature measurement range of 800°C to 1200°C is developed based on the FTIR spectrometer, and the calibration of the instrument coefficients using a standard radiation source is performed. On this basis, the readout noise and shot noise in the spectral signal are analyzed, and a detailed quantitative evaluation of the influences of two kinds of noise on the temperature measurement accuracy is also carried out in this work. Experimental results show that the temperature deviation caused by the two kinds of noise is less than 1°C when the wavelength is within the range of 2.0 to 5.4 μm. However, when the wavelength is greater than 5.4 μm, the maximum temperature deviation caused by the readout noise and shot noise can reach about 12°C and 18°C, respectively. In view of this, a Kalman filter method is introduced in this work to reduce temperature fluctuations caused by these noises, where the maximum fluctuation can be reduced from 83.9°C to 6.1°C with this filter method. These experimental results can provide a valuable guidance for the general-purpose calibration and assessment of the FTIR-based pyrometer.

Graphical multispectral radiation temperature inversion algorithm based on deep learning.

Neural networks are the most promising tool to solve the problem that an assumed emissivity model is needed in the field of multispectral radiometric temperature measurement. Existing neural network multispectral radiometric temperature measurement algorithms have been investigating the problems of network selection, network porting, and parameter optimization. The inversion accuracy and adaptability of the algorithms have been unsatisfactory. In view of the great success of deep learning in the field of image processing, this Letter proposes the idea of converting one-dimensional multispectral radiometric temperature data into two-dimensional image data for data processing to improve the accuracy and adaptability of multispectral radiometric temperature measurement by deep learning algorithms. Simulation and experimental validation are carried out. In the simulation, the error is less than 0.71% without noise and 1.80% with 5% random noise, which improves the accuracy by more than 1.55% and 2.66% compared with the classical BP (backpropagation) algorithm, and 0.94% and 0.96% compared with the GIM-LSTM (generalized inverse matrix-long short-term memory) algorithm. In the experiment, the error is less than 0.83%. This indicates that the method has high research value and is expected to lead multispectral radiometric temperature measurement technology to a new level.

Steady-state error estimation and calibration of a shielded total temperature probe for turbomachinery

Accurate measurement of the total gas temperature plays a vital role in the performance research of turbomachinery. The total temperature thermocouple (TC) used in the measurement often needs to be specially designed and calibrated. In the past, the calibration was usually completed by a complex and highly costly experiment. The present work developed a new shielded total temperature probe (NTTP) for relatively low-temperature gas measurement. Meantime, this new design's characteristics and different error sources are analyzed based on the Conjugate Heat Transfer (CHT) simulation method. The CHT results show that the thermal conduction error is kept at a small value in the range of Mach number from 0.2 to 0.6; The velocity error contributes more than 90% of the total error. Four standard temperature probes are selected for the comparison. The maximum measurement error is 1.13 K, which is 331.62%, 119.4%, 61.6% and 59.5% lower than the standard type-A, B, C and D, respectively. Moreover, the detailed flow field and the influence of TC junction position on measurement accuracy are discussed. With the increases of the junction away from the supporting, the total measurement error of the NTTP increases first and then decreases. To vindicate the applicability of the proposed design, the measurement error of the NTTP is verified by a new experimental method with the relatively static fluid as the gas flow source. The testing results show that when the inflow's Mach number is 0.52, the measurement error of the NTTP is about 40% lower than that of the type-C total temperature probe.

3D infrared temperature maps measurements of ablative materials during plasma wind tunnel experiments

Accurate surface temperature and recession measurements are crucial experimental data for plasma wind tunnel testing of ablative thermal protection materials. In this work we propose a novel methodology to reconstruct infrared temperature maps on 3D geometries undergoing surface recession. An optical calibration technique is used to extract 3D metric information from the 2D thermal images, thanks to a specific calibration target with control points. The evolution of the sample shape during the experiment is tracked from a side view, using a visual-range camera with dedicated image processing, and reconstructed in 3D under the assumption of axisymmetry. The surface temperature is projected on the time-varying 3D geometry from the calibrated thermograms. The technique is demonstrated on a graphite ablation experiment in air plasma. The reconstructed maps provide detailed multidimensional information about the transient temperature evolution, overcoming traditional approaches that are limited around the stagnation point. The technique allows to study ablation mechanisms with further detail, improving experimental data for material qualification and validation of simulation codes.

Chloroform-infiltrated photonic crystal fiber with high-temperature sensitivity.

The temperature sensor is the core part of the temperature measurement instrument, and its performance directly determines the temperature measurement accuracy. Photonic crystal fiber (PCF) is a new type of temperature sensor with extremely high potential. In this paper, we propose a high-performance, structurally simple, liquid-filled PCF temperature sensor, which is based on a SMF-PCF-SMF (single mode fiber, SMF) sandwich structure. By adjusting the structural parameters of the the PCF, it is possible to obtain optical properties that are superior to those of ordinary optical fibers. This allows for more obvious responsive changes of the fiber transmission mode under small external temperature changes. By optimizing the basic structure parameters, a new PCF structure with a central air hole is designed, and its temperature sensitivity is -0.04696 nm/°C. When filling the air holes of PCFs with temperature-sensitive liquid materials, the response of the optical field against the temperature fluctuations can be effectively enhanced. The Chloroform solution is used to selectively infiltrate the resulting PCF owing to its large thermo-optical coefficient. After comparing various filling schemes, the calculation results show that the highest temperature sensitivity of -15.8 nm/°C is finally realized. The designed PCF sensor has a simple structure, high-temperature sensitivity, and good linearity showing great application potential.

Cernox thermometer under hydrostatic pressure for enhanced temperature accuracy

Sensors that can be used in a pressurized environment are few. Thus, it is generally considered that the accuracy of temperature measurements decreases in experiments carried out under pressure. Based on a commercially available cryogenic temperature sensor, Cernox from Lake Shore Cryotronics, Inc., we developed and tested an enclosure that enables Cernox to be directly used inside a cylindrical pressure cell, next to the specimen under investigation. To isolate the Cernox thermometer from the pressurized medium inside the pressure cell, we combined the principles of an encapsulated Pt sensor and a cylindrical clamped piston cell. The encapsulated Cernox allows for precise measurement and control of the specimen’s temperature. It is also beneficial for accurately determining small changes in physical properties, such as temperature, or measuring the amount of hysteresis in the first-order phase transition. It would also be useful for accurately controlling the sample’s temperature when the sample approaches the transition temperature from one side.

Fluorous Liquids for Magnetic Resonance-Based Thermometry with Enhanced Responsiveness and Environmental Degradation.

Accurate temperature measurement via magnetic resonance is valuable for both in vitro and in vivo analysis of local tissue for evaluating disease pathology and medical interventions. 1H MRI-based thermometry is used clinically but is susceptible to error from magnetic field drift and low sensitivity in fatty tissue and requires a reference for absolute temperature determination. As an alternative, perfluorotributylamine (PFTBA), a perfluorocarbon liquid for 19F MRI thermometry, is based on chemical shift responsiveness and approaches the sensitivity of 1H MRI thermometry agents; however, environmental persistence, greenhouse gas concerns, and multiple resonances which can lead to MRI artifacts indicate a need for alternative sensors. Using a 19F NMR-based structure-property study of synthetic organofluorine molecules, this research develops new organofluorine liquids with improved temperature responsiveness, high signal, and reduced nonmagnetically equivalent fluorine resonances. Environmental degradation analysis using reverse-phase HPLC and quantitative 19F NMR demonstrates a rapid degradation profile mediated via the aryl fluorine core of temperature sensors. Our findings show that our lead liquid temperature sensor, DD-1, can be made in high yield in a single step and possesses an improved responsiveness over our prior work and an 83% increase in aqueous thermal responsiveness over PFTBA. Degradation studies indicate robust degradation with half-lives of less than two hours under photolysis conditions for the parent compound and formation of other fluorinated products. The improved performance of DD-1 and its susceptibility to environmental degradation highlight a new lead fluorous liquid for thermometry applications.

Stretchable and Skin-Mountable Temperature Sensor Array Using Reduction-Controlled Graphene Oxide for Dermatological Thermography.

Since thermometry of human skin is critical information that provides important aspects of human health and physiology, accurate and continuous temperature measurement is required for the observation of physical abnormalities. However, conventional thermometers are uncomfortable because of their bulky and heavy features. In this work, we fabricated a thin, stretchable array-type temperature sensor using graphene-based materials. Furthermore, we controlled the degree of graphene oxide reduction and enhanced the temperature sensitivity. The sensor exhibited an excellent sensitivity of 2.085% °C-1. The overall device was designed in a wavy meander shape to provide stretchability for the device so that precise detection of skin temperature could be performed. Furthermore, polyimide film was coated to secure the chemical and mechanical stabilities of the device. The array-type sensor enabled spatial heat mapping with high resolution. Finally, we introduced some practical applications of skin temperature sensing, suggesting the possibility of skin thermography and healthcare monitoring.

Features of creating a system of simultaneous built-in testing of deformation and temperature of composite structures by fiber-optic sensors

This article describes the relevance of improving existing and creating new effective methods of non-destructive testing and technical diagnostics of highly loaded aircraft structures made of polymer composite materials to ensure safe operation. Approaches to the creation of efficient systems for the simultaneous embedded testing of deformations and temperature of structures made of polymer composite materials by an optical method using embedded fiber-optic sensors based on fiber Bragg gratings are considered. The world experience in creating such systems, the methodology of non-destructive testing are analyzed, taking into account the creation of a spatial topology of fiber-optic sensors in a real product. It is shown that to solve this problem, it is most expedient to use the method of two optical fibers with different sensitivity to deformation and temperature, or to one of these parameters. The results of experimental studies on the simultaneous control by the proposed method of deformation and temperature of a structurally similar sample from a carbon composite processed by a vacuum method from a prepreg are presented. It has been established that the use of a quadratic model for optical control of structurally similar samples of carbon composite makes it possible to increase the accuracy of deformation and temperature measurements in comparison with the linear control model. It is confirmed that the proposed experimental technique allows for simultaneous control of deformation and temperature of structurally similar samples from carbon composites, while it can be adjusted and adapted to the actual operating conditions of a particular structure.

Accuracy and Precision Improvement of Temperature Measurement Using Statistical Analysis/Central Limit Theorem

This paper describes a method for increasing the accuracy and precision of temperature measurements of a liquid based on the central limit theorem. A thermometer immersed in a liquid exhibits a response with determined accuracy and precision. This measurement is integrated with an instrumentation and control system that imposes the behavioral conditions of the central limit theorem (CLT). The oversampling method exhibited an increasing measurement resolution. Through periodic sampling of large groups, an increase in the accuracy and formula of the increase in precision is developed. A measurement group sequencing algorithm and experimental system were developed to obtain the results of this system. Hundreds of thousands of experimental results are obtained and seem to demonstrate the proposed idea's validity.

Shell Engineering on Thermal Sensitivity of Lifetime-Based NIR Nanothermometers for Accurate Temperature Measurement in Murine Internal Liver Organ.

Lifetime-based NIR luminescent nanothermometry is ideally suited for temperature detection in living cells and in vivo, but the thermal sensitivity (Sr) modulation remains elusive. Herein, a thorough investigation is performed to unveil the shell effect on lifetime-based Sr by finely controlling the shell thickness of lanthanide-doped core-shell-shell nanoparticles. Owing to the space-dependent energy transfer and back energy transfer between Nd3+ and Yb3+ as well as the energy migration to surface quenchers, both active and inert shells can regulate the thermal-dependent nonradiative decays and NIR luminescence lifetime of Yb3+, which in turn modulates the Sr from 0.56% to 1.54% °C-1. After poly(acrylic acid) modification of the optimal architecture, the tiny nanoprobes possess robust stability to fluctuations in the microenvironment, which enables accurate temperature mapping of inflammation in the internal liver organ of living mouse. This work will provide new insights for optimizing Sr and guidance for precise temperature measurements in vivo.

On the Reliability of Temperature Measurements in Natural Gas Pipelines

Accuracy of temperature measurement of natural gas flows in closed conduits is a highly debated topic due to the complexity of the measurement chain and the related economic impact. First, specific thermo-fluid dynamic issues occur because of the difference between the temperature of the gas stream and that of the external ambient and the mean radiant temperature inside the pipe. Furthermore, the installation conditions of the temperature sensor (e.g., immersion length and diameter of the thermowell) play a crucial role. In this paper, the authors present the results of a numerical and experimental study conducted both in the laboratory and in-field aimed at analyzing the reliability of temperature measurement in natural gas networks as a function of the pipe temperature and of the pressure and velocity of the gas stream. The results obtained in the laboratory show errors ranging between 0.16 and 5.87 °C in the summer regime and between -0.11 and -2.72 °C in the winter regime, depending on the external pipe temperature and gas velocity. These errors have been found to be consistent with those measured in-field, where high correlation between the pipe temperatures, the gas stream and the external ambient have been also demonstrated, especially in summer conditions.

YAG:Ln3+ (Ln = Nd, Yb, Ce) nanocrystals for application in luminescent fiber-based temperature sensors

We developed and characterized luminescent temperature sensors with a simple construction based on YAG : Ln3 + (Ln = Nd, Yb, Ce) nanocrystals and silica multimode optical fibers. Lanthanide-doped nanocrystals 40 to 60 nm in size were synthesized in the form of powders using the modified Pechini method. The obtained materials exhibited high sensitivity of luminescence intensity to temperature variations at wavelengths of 550 nm (YAG : Ce3 + ), 1030 nm (YAG : Yb3 + ), and 1064 nm (YAG : Nd3 + ) in the temperature range 50°C to 600°C. Additionally, we offered a method to eliminate influence of vibration on accuracy of temperature measurements by adding SiO2 sol to powders after their synthesis in sensitive elements.

Challenges and opportunities in quantitative aerial thermography of building envelopes

The use of small unmanned aerial vehicles (UAVs) equipped with an infrared (IR) camera has created opportunities for qualitative and quantitative thermal assessments of building envelopes. However, it is currently unclear how successful this method is at quantifying heat losses through the building envelope. The inconsistency in findings indicates that sources of error that affect the accuracy of surface temperature measurements are not well understood by thermographers and that recommendations to minimize the errors in aerial thermography measurements have yet to be determined. In this study, laboratory and field experiments were conducted to investigate the scientific reasons for discrepancies between aerial (i.e. dynamic) and conventional stationary infrared thermography (IRT) observations. A set of practical approaches were presented to minimize the sources of error in UAV-IRT measurement. The results of field experiments showed a non-linear and dramatic variation of measured surface temperature during flight, where the deviations of results between dynamic and stationary thermography were beyond the manufacturer-reported accuracy of ±5 °C. Additionally, the results indicated that induced convection from drone propellers affects microbolometer stabilization with surrounding environmental conditions, which significantly influences the IR camera measurement accuracy. Finally, subsequent investigations utilized a shield around the camera to minimize the convective turbulence on the lens and thermal sensors, successfully achieving temperature deviations of less than 1 °C. These findings may inform manufacturers about the limitations of current IR camera technology during aerial surveys and therefore provide opportunities to define a more robust thermal imaging protocol for the quantification of building envelope thermal performance.

Soft sensor method of multimode BOF steelmaking endpoint carbon content and temperature based on vMF-WSAE dynamic deep learning

Abstract The difficulty of endpoint determination in basic oxygen furnace (BOF) steelmaking lies in achieving accurate real-time measurements of carbon content and temperature. For the characteristics of serious nonlinearity between process data, deep learning can perform excellent nonlinear feature representation for complex structural data. However, there is a process drift phenomenon in BOF steelmaking, and the existing deep learning-based soft sensor models cannot adapt to changes in the characteristics of samples, which may lead to their performance degradation. To deal with this problem, considering the characteristics of multimode distribution of process data, an adaptive updating deep learning model based on von-Mises Fisher (vMF) mixture model and weighted stacked autoencoder is proposed. First, the stacked autoencoder (SAE) and vMF mixture model are constructed for complex structural data, which can initially establish nonlinear mapping relationships and division of different distributions. Second, for each query sample, the basic SAE network will perform online adaptive fine-tuning according to its data with the same distribution to achieve dynamic updating. Moreover, each sample is assigned a weight according to its similarity with the query sample. Through the designed weighted loss function, the updated deep network will better match the working conditions of the query sample. Experimental studies with numerical examples and actual BOF steelmaking process data are provided to demonstrate the effectiveness of the proposed method.

Investigating an accurate method for measuring the outdoor mean radiation temperature

Accurate measurement of mean radiation temperature (MRT), a main parameter affecting outdoor thermal comfort under sunlight conditions, is immensely important in improving the thermal environment of urban outdoor spaces and enhancing outdoor thermal comfort. In this study, four different surfaces (limestone, grass, concrete, and asphalt pavement) were selected and the experiments were set up under shading and no-shading conditions on four different surfaces. Based on the above conditions to analyze and compare three different MRT estimation methods, these include the black sphere thermometer measurement method under different wind speed measurement frequencies (0.1 and 10 Hz) and the six-way integrated radiation measurement method, and the outdoor wind speed (Va) of 10 Hz is the three-dimensional wind speed of the combined x-y-z three directions. The results showed that MRT was influenced by the long- and short-waves more in the vertical direction than in the horizontal direction, and the different solar radiation storage capacities of the lower cushion surfaces during the daytime led to different temperature change delays after sunset. The results shows that at the thermal comfort requirement of ±2 °C, and the acceptable error probability were 65.3% and 74.6% at 0.1 and 10 Hz, respectively. While at the thermal comfort requirement of ±5 °C, the acceptable error probability were 83.4% and 89.3% at 0.1 and 10 Hz, respectively. Noted that ±2 °C and ±5 °C as acceptable thresholds for MRT measurement accuracy are specified in ISO standard 7726:1985. Therefore, 10 Hz exhibited significantly better performance than that of 0.1 Hz for MRT estimation. Under the unshaded conditions, the MRT measurements obtained by black-sphere thermometer method is in most cases lower than obtained by six-way radiometry method, where the MRT obtained at 0.1HZ and 10HZ wind speed measurement frequencies are lower by about 5.8 and 4.2, respectively, compared to those obtained by six-way radiometry. However, due to the variation of the solar altitude angle, there is also a slightly higher phenomenon present. In addition, the results show that the RMSE of the estimated errors after correction for different cushion surfaces are lower than those before correction. Limestone is reduced by 22.15%. Concrete is reduced by 23.47%, Grassland by 28.38% and Asphalt road by 25.28%. And the correction effect is more obvious in the lower cushion surface with higher absorption rate. The conducting test that used an inexpensive black-sphere thermometer to measure outdoor MRT accurately improved the distinction between MRT estimation measurements under different conditions. It also refined the feasibility of changes in the wind speed measurement frequency to improve the accuracy of the traditional black-sphere thermometer measurements, thus, highlighting a new methodology for accurate outdoor MRT measurements that can in turn advance the improvement of outdoor thermal comfort.

Prototype of Room Temperature and Humidity Monitoring Device in Shallot Storage Using Microcontroller Arduino

Allium ascalonicum L or commonly referred to as shallot is one type of horticultural plant that is important because it is widely used by humans as a mixture of spices in cooking. The need for shallots increasing every day accompanied by a large number of agricultural products, causing the stability of shallot availability in Merauke County to become unstable, To support the needs of consumers shallots imported from outside Merauke. Therefore the condition of the shallots in the storage area is cold and humid. While waiting to be sold in the storage area, it must be maintained temperature and humidity to reduce decay and shrinkage. This prototype monitoring device works to measure and maintain the temperature and humidity in the storage. The data collection method in this study is Literature Study, Observation, Interview, and Documentation. Microcontroller devices are designed or made to be able to control the state of temperature and humidity in the room where the onion is stored. The device also gives notifications via text message to users to be able to find out the state of the onion storage. The results of the study conducted using the DHT11 sensor obtained a temperature measurement accuracy rate of 93.848% and a humidity accuracy rate was 91.808%. This device can detect the temperature and humidity values in the shallot storage room.

Theoretical study on simultaneous measurement of seawater temperature and salinity based on dual fiber interferometers combined with nonlinear decoupling algorithm

Accurate measurement of temperature and salinity is an important foundation for oceanographic research. In this paper, dual fiber interferometers combined with a novel nonlinear decoupling algorithm is studied theoretically for simultaneous measurement of seawater temperature and salinity. The correlation analysis shows that there is not only a quadratic relationship between the position of interference dips and temperature, but also interaction between temperature and salinity. Therefore, the quadratic polynomial surface fitting method, containing the important interaction term, is used to build the relationship between interference dips position and both temperature and salinity. A quadratic polynomial surface-based nonlinear decoupling algorithm is developed, and the deviation of this algorithm are noticeably smaller than that of the commonly used linear decoupling algorithm. This work may offer useful reference for developing practical optical fiber seawater temperature and salinity sensors and establishing decoupling algorithms for other dual-parameter fiber-optic sensors.

Two-photon absorption laser induced fluorescence (TALIF) detection of atomic iodine in low-temperature plasmas and a revision of the energy levels of I I

In order to perfect the use of iodine, instead of xenon, in plasma thrusters, an experiment has been set up to investigate the feasibility of two-photon absorption laser induced fluorescence (TALIF) diagnostics in iodine plasmas. Levels and of atomic iodine were found qualified for that purpose, with a radiative lifetime of the former found equal to , which appears consistent with the predicted by the most recent calculations. Doppler-free two-photon spectroscopy has confirmed that the relative intensities of the hyperfine components follow well-known general formulas, which makes it possible to disentangle the hyperfine structure of from Doppler broadening. Accurate temperature measurements are shown to be possible, even though the relatively heavy mass of the iodine atom does not make it the most favorable gauge for measurements based on Doppler effect. Using an injection seeded pulsed laser as the primary laser source, the frequency-tripling of which has provided the ca 300 nm radiation used for excitation, absolute energy measurements of the two-photon excited levels revealed that all upper energy levels of I I have to be revised down, by , which pulls every energy level off its presently tabulated value by more than thirty times the currently admitted uncertainty bar.