Real-time Temperature Field Research Articles

Real-Time Temperature Field State Observer and Digital Replica to Support Cyber-Physical Testing

Real-Time Temperature Field State Observer and Digital Replica to Support Cyber-Physical Testing

Real-time 3D temperature field reconstruction for aluminum alloy forging die using Swin Transformer integrated deep learning framework

Temperature field distribution in forging dies is crucial for quality control and defect prevention, particularly for aluminum alloys. Current methods are limited to discrete points or surface measurements, making real-time three-dimensional temperature field acquisition challenging. In this paper, a novel Swin Transformer-integrated deep learning framework is proposed for real-time 3D temperature field reconstruction of forging dies, pioneering the application of transformer architecture in physical field prediction. In this framework, numerical simulations are first conducted to provide ground truth and fundamental insights into the temperature evolution, and then limited sparse thermal sensors are utilized to offer corrected real-time input parameters. The model for 3D temperature field reconstruction is developed through the combination of Swin Transformers with the U-shaped encoder-decoder structure, which is trained and tested with various sensor configurations, initialization methods, and datasets, including actual experiments. The results demonstrate that the proposed Swin-UNETR model achieves 3D temperature field prediction with time cost of 0.98 s per frame, mean absolute error of 0.8658 °C, showing a 17.23 % improvement over the next best CNN-based model (ResUNet3D at 1.0461 °C), and a 4.63 % improvement over the next best machine learning model (LightGBM at 0.9078 °C), which can be attributed to the Swin Transformer’s ability to capture both local and global contextual information and shifted window mechanism. The proposed method holds significant implications for ensuring the forming quality of forgings and propelling the development of digital twin technology in forging processes.

A real-time temperature field prediction method for steel rolling heating furnaces based on graph neural networks

In the billet reheating process during steel rolling, the real-time and accurate prediction of the temperature field is a prerequisite for the dynamic regulation of the heating process, which is crucial for ensuring the quality of billet reheating and reducing the energy consumption of the reheating furnace. The most commonly used finite element thermal field simulation and analysis methods are unable to meet the demand for real-time prediction under dynamic working conditions. Furthermore, traditional machine learning methods struggle to handle irregular data that includes spatial location information, resulting in inaccurate temperature field predictions, which in turn affect the furnace control efficiency and the quality of the product. In light of these limitations, this study proposes a Graph Neural Network (GNN)-based temperature field prediction method for steel rolling reheating furnaces. This method considers the interactions between the nodes within the reheating furnace and constructs a temperature field topology graph to effectively capture these interactions, including heat conduction and convection. Additionally, in the feature fusion and state updating mechanism of the model, we introduce process parameters, such as the air-fuel ratio, as additional inputs to enhance the ability of the GNN to handle complex variables. This enables real-time accurate simulation of the internal temperature distribution of the reheating furnace. The experimental results demonstrate that the model prediction error is controlled within 2.9 % and the response time is maintained within 20 ms, thereby validating the reliability and efficacy of the method in practical applications.

Investigation of SrB4O7:Tm2+ luminescence for temperature imaging with high sensitivity based on time-resolved luminescence.

In recent years, with the growing demand for non-contact and real-time optical temperature measurements, it has become imperative to develop new luminescent thermometry materials as well as novel temperature detection schemes with higher sensitivity. In this work, a series of Sr1-xB4O7:xTm2+ (x = 0.001-0.01) polycrystalline powder samples were prepared using a high temperature solid state reaction under ambient atmospheric conditions. The emission spectra and the luminescence decay curves of the red emission corresponding to the 4f125d → 4f13(2F7/2) transition of Tm2+ were recorded at intervals of 10 K from 280 K to 380 K. Both the emission intensity and the fluorescence lifetime exhibited remarkable temperature correlation in the studied temperature range, which reached the best relative temperature sensitivities of 3.55% K-1 and 3.86% K-1 at 363 K and 346 K, respectively. Furthermore, taking into account the highly sensitive variation of the fluorescence lifetime of Tm2+ in the SrB4O7 matrix as the temperature increased near room temperature, a time-resolved temperature measurement scheme was performed to realize real-time temperature field imaging. By utilizing the intensified charge coupled device (ICCD) camera with a time gate to acquire the integral intensity of distinct time intervals and calibrate the relationship between the ratio and the temperature, the experimental results demonstrated that this temperature measurement scheme can achieve a maximum relative sensitivity of 9.39% K-1 at 313 K, which significantly surpasses the relative sensitivity of the other two conventional temperature measurement schemes.

Real-time temperature field reconstruction using a few measurement points and RPIM-AGQ6 interpolation

In thermal management systems, temperature field monitoring is vital for the structural safety of electronic equipment. However, there are practical challenges when it comes to installing temperature sensors on some monitoring points directly. To solve this problem, a novel temperature field reconstruction method is proposed. This strategy offers the advantage of using only a limited number of discrete values to predict temperature fields across an entire plane. Initially, the approach constructs a composite interpolation function, named RPIM-AGQ6, by coupling the mesh-free radial point interpolation method (RPIM) with the quadrilateral area coordinate method (AGQ6) The temperature field is discretized and represented as the product of the nodal temperatures and the RPIM-AGQ6. Next, ill-posed equations are established and solved using Bayesian Multivariate Linear Regression (BMLR) to obtain the temperature in the key points. Subsequently, a novel optimization strategy is proposed to achieve the cooperative optimization of the number of sensors and reconstruction accuracy. Finally, the simulated calculation and experimental tests are used to demonstrate the effectiveness and accuracy of the proposed approach. The results show that the proposed methodology can accurately reconstruct the plane temperature field of plate structure with one and two hot sources and the relative percentage error is within 2.6 %. Therefore, it can be utilized as an effective tool to real-time monitor structural surface temperature.

Real-time temperature field and thermal deformation of slab track on cable-stayed bridge

This study aimed to master the real-time temperature fields of slab tracks on cable-stayed bridges and analyze the thermal deformations. The pivotal heat conduction parameters of the geotextile and rubber pad were obtained through testing, and the governing equations for heat conduction considering temperature variations were improved. A thermal-fluid-solid coupling model for slab track on cable-stayed bridge was proposed. The results indicated that the high temperatures of the track were concentrated within 0.05 m depth of the slab. Under the resistance of the isolation layer, the temperature on both sides of the geotextile isolation layer appeared obvious abrupt change. The time of maximum and minimum temperatures of the truss beam were the same as those of the air. The effects of real-time temperature change on the irregularity of the rail were obvious. In summer, the maximum vertical rail deformation was 201.88 mm and the transverse deformation was 17.87 mm. The temperature change in just one day caused vertical deformation of rail with a range of more than 60%. On a single day in summer, the maximum horizontal irregularity was 1.74 mm, which was less than the 2.0 mm specified in the code.

Study on choosing mobile sensor location to improve the prediction accuracy of indoor temperature distribution

Nonuniform indoor temperature distributions have been widely introduced due to the increasing concerns brought about by the trade-off between building energy consumption and thermal comfort. Related to this, obtaining real-time indoor temperature field is crucial for control and regulation. Previously, a rapid temperature prediction algorithm based on the contribution ratio of indoor climate (CRI) and sensor information was proposed. Compared with fixed sensors, mobile sensors have better moving flexibilities and higher prediction accuracies. Given that considerable data can be obtained from one sensor, the chosen mobile sensor location has a strong correlation with the prediction accuracy. However, only a few studies have investigated the impact of the sensor location. Thus, this study aimed to determine the optimal mobile sensor location for improving prediction accuracy using the proposed algorithm. Two differently scaled rooms were numerically built, and 1.2 m high points were set as the selected locations. After experimental validation of the simulation results, three factors (moving path, supply/return air, and air velocity) were investigated to determine their effects on prediction accuracy. The results showed that the air velocity was the only significantly impactful factor. Furthermore, two principles of choosing location were proposed: (1) when the percentage of dominant velocity is high, all points should have one identical dominant direction, and (2) when the percentage of dominant velocity is low, points should have a similar actual direction. These principles were verified in both models with a prediction accuracy greater than 85%.

Real-Time Intelligent Prediction Method of Cable’s Fundamental Frequency for Intelligent Maintenance of Cable-Stayed Bridges

Cable’s fundamental frequency (CFF) is an important characteristic of the working state of long-span cable-stayed bridges. The change in the bridge’s temperature field will influence CFF by altering the cable’s tension and the cables’ sags. An accurate regression model between the temperature-induced variation of CFF and the real-time changing temperature field should be established. Then, the reference value of the temperature-induced variation of CFF can be obtained after inputting the real-time temperature data. In this study, an intelligent real-time prediction model for CFF is proposed based on the full-bridge temperature field, including the average temperature of the main beam, the vertical temperature difference of the main beam, and the temperature of the cable tower. Besides, a machine learning method named the long short-term memory (LSTM) network is exploited to ensure the nonlinear fitting performance of the model, and a paradigm for optimal hyperparameter selection and training strategy selection is provided. To verify the superiority of the LSTM-based model, the output accuracy of the linear regression, BP network, and LSTM network was tested and compared using the monitoring data collected from cable sensors in the main span and side span, which provides an important basis for the intelligent maintenance and sustainable operation of the bridge cables.

Imaging Convective Phenomena inside Highly Refractive Cylindrical Enclosures

The conventional refractive index-based optical techniques show limitations in measuring the thermal field inside refractive surfaces due to the curvature effects. The present work reports on the application of lensless Fourier transform digital holographic interferometry for mapping heat transfer phenomena inside highly refracting axisymmetric enclosures. Experiments have been performed to characterize the buoyancy-driven natural convection heat transfer around a vertically oriented heated cylinder placed concentrically inside a relatively large cylindrical enclosure filled with de-ionized water. The experiments were performed under various heating conditions, and the corresponding holograms were analyzed in real-time to show the transients of the temperature field. Quantitative results were obtained in the form of a two-dimensional temperature distribution field and local heat transfer coefficients along the heated surface. Experimental results were validated by comparing the values of the surface temperatures obtained from the analysis with that obtained from the thermocouple data. The work presented highlights the ability of the lensless Fourier transform digital holographic technique to map the real-time temperature field inside a highly refracting enclosure.

Data-driven varying state-space model based on thermal network for transient temperature field prediction of motorized spindles

• 1) Rapid prediction of the transient temperature distribution. • 2) Parameter estimation driven by FE simulation and experimental data. • 3) Accuracy validated by thermal images of undetectable regions. • 4) Real-time correction of temperature prediction bias. Analyzing and modeling the thermal characteristics of the spindle is crucial to improving the thermal stability and intelligence of CNC machine tools. However, there is a lack of accurate real-time prediction methods for the transient temperature distribution inside the spindle. In this study, a thermal network consisting of thermal capacitances and resistors is constructed based on the thermal structure of a motorized spindle, and a varying state-space (VSS) model varying with node temperature and rotational speed is proposed to solve the thermal network. The parameters of this model are determined by a two-step estimation process, driven by simulation data of a finite element (FE) model under specific boundary conditions and experimental sensor data obtained from a series of thermal tests. The validation based on thermal experiment shows that the VSS model has high prediction accuracy with the average root mean square (RMS) bias of 0.5141°C. Thermal images of the rotating shaft also show that the proposed VSS model maintains high accuracy in predicting the temperature of the undetectable regions. In addition, a temperature prediction system (TPS) with bias correction is constructed based on two built-in temperature sensors in the spindle to further improve prediction accuracy, with the RMS bias reduced by 10.4% to 0.4606°C. All the results show that the real-time temperature field distribution of motorized spindles can be rapidly, accurately, and completely inferred based on the rotational speed and a few temperature sensors. The proposed modeling approach has the potential to be integrated into edge computing devices of intelligent spindles.

Real-time temperature field recovery of a heterogeneous reactor based on the results of calculations in a homogeneous core

Advanced pressurized water reactors are the main part of a new generation of nuclear power plant projects under development that provide cost-effective power production for various needs (Yemelyanov et al. 1982, Klimov 2002, Boyko et al. 2005, Baklushin 2011, Bays et al. 2019, Nuclear Technology Review 2019). The innovative technologies are aimed at improving the safety and reliability as well as at reducing the cost of NPPs. At the same time, improvements in design, technological and layout solutions are focused primarily on the reactor core. Assessments of the efficiency of these improvements are preceded by numerical simulations of the processes in the core, in particular heat generation and sink, with account for the difference between the study object and the standard version tested in operational practice. The authors of the article propose a method for calculating the temperature field in the core of a heterogeneous reactor (using the example of a pressurized water reactor), which makes it possible to quickly assess the level of temperature safety of various changes in the core and has the necessary speed for analyzing transients in real time. This method is based on the energy equation for an equivalent homogeneous core in the form of a heat equation that takes into account the main features of the simulated heterogeneous structure. The procedure for recovering the temperature field of a heterogeneous reactor uses the analytical relation obtained in this work for the heat sink function, taking into account inter-fuel element heat leakage losses. Calculations of temperature fields in the model of the PWR type reactor (The Westinghouse Pressurized Water Reactor Nuclear Plant 1984) were carried out in stationary and transient operating modes. The calculation results were compared with the results of CFD simulation. The area of competing use of the temperature field recovery method was indicated.

Application of Tucker Decomposition in Temperature Distribution Reconstruction

Constrained by cost, measuring conditions and excessive calculation, it is difficult to reconstruct a 3D real-time temperature field. For the purpose of solving these problems, a three-dimensional temperature distribution reconstruction algorithm based on Tucker decomposition algorithm is proposed. The Tucker decomposition algorithm is used to reduce the dimension of the measured data, and the processed core tensor is used for the temperature field reconstruction of sparse data. Theoretical analysis and simulations show that the proposed method is feasible; the overall optimization is realized by selecting the appropriate core tensor dimensions; and the reconstruction error is less than 3%. Results indicate that the proposed method can yield a reliable reconstruction solution and can be applied to real-time applications.

Research on the Variable-Temperature Cracking Mechanism of CRTS I Type Double-Block Ballastless Track on a Bridge.

The CRTS I type double-block ballastless track (CRTS I TDBBT) has the advantages of convenient construction and low cost, but it has low crack resistance and the temperature field distribution of the railway on the bridge is uneven and frequently changes, so it is necessary to study the mechanical properties of the CRTS I TDBBT under the load of a temperature field. The temperature field model of the CRTS I TDBBT on the bridge is established by finite element software, the real-time temperature field of the track bed slab is brought into the coupled model as a load, and the variation laws of the temperature stress of the CRTS I TDBBT under different schemes are compared. The temperature gradient in the CRTS I TDBBT track bed slab has the largest fluctuation range, and the positive and negative temperature gradient range can reach 93.34 °C. For the temperature longitudinal stress around the sleeper block of the track bed slab, the edge is the largest; the temperature longitudinal stress is reduced by at most 5.27% after the anti-cracking diagonal bars are added. When the expansion joint is added, the temperature stress can be reduced by up to 80.29%. The fluctuation range of the temperature gradient of the track bed is basically consistent with the fluctuation range of the local air temperature. The huge temperature difference leads to the occurrence of cracks in the track structure, and cracks are more likely to occur at the corners of the sleeper block. The addition of both anti-crack diagonal bars and expansion joints has an anti-crack effect, but the effect of adding expansion joints is better.

Development of Real-time Temperature Field Measurement System by Using Temperature Sensitive Paint

Thermocouple and infrared thermography have been widely used to measure a temperature. However, thermocouple is only one point measurement, and infrared thermography cannot use through infrared impermeable material such as water or acrylic board. To solve these problems, we have developed a real-time temperature measurement system by using temperature sensitive paint (TSP). TSP is a kind of luminescent paint and its luminescent intensity decreases with increasing temperature. Using temperature dependency of TSP, planar temperature distribution can be measured from an image of luminescent intensity taken by digital camera. TSP is composed of luminescent molecule, binder, and solvent. In the present study, Ru(phen)32+ is adopted as luminescent molecule, and blue LED is used to excite the molecule. To evaluate the present measurement system, the temperature of the side plate in a two-dimensional jet was measured.

Modeling of phase transition in fabrication of polymer-derived ceramics (PDCs)

Polymer-derived ceramics’ (PDCs) route, which converts preceramic polymers to ceramics through heat treatment, presents a flexible and energy-efficient approach to fabricate ceramic composites with arbitrary geometries and tailorable properties. Due to the huge gaps of thermal and mechanical properties of polymers and ceramics, the current state phase composition and phase distribution largely affect the heat transfer behavior and temperature field evolution that ultimately determine the subsequent polymer decomposition and phase redistribution. In this paper, a computational framework is developed to predict the continuum-level phase transition and its effect on mechanical properties. Molecular dynamics (MD) simulations are carried out first to track the atomic structure evolution and mass loss associated with gas generation. It is found that pyrolysis temperature primarily determines the amount of gases that can be generated. Gas diffusion is triggered as a result of the non-uniform temperature field. Ceramic phase formation depends on the interplay between gas generation and gas diffusion. This computational framework allows real-time temperature field and phase composition map to be explicitly extracted. The phase composition map is incorporated into a finite element model for compression simulation. The effects of heating rate, pyrolysis temperature and pyrolysis time on mechanical response are systematically studied. Conclusions from this study can provide direct guidance for fabricating PDCs with tailored properties.

Theory and technology of real-time temperature field monitoring of vertical shaft frozen wall under high-velocity groundwater conditions

This study aims to address the problems arising from frozen wall closing in prolonged time under high-velocity groundwater in artificial ground freezing. Based on the development and closure law of frozen wall in strata with seepage, an analytical formula of transient temperature rising in frozen soil is derived, and a deterministic relationship between the geometric dimensions of the frozen wall is revealed. Then a longitudinal temperature measurement analysis theory is established. To accurately locate the weak points of the frozen wall and groundwater flow direction in case of groundwater disturbance, the gray correlation analysis is used to uncover the correlation between the weak freezing pipes. These relationships and correlations constitute a systemic framework for monitoring the temperature field during ground freezing under the condition of fast groundwater flow. Finally, the theory is applied to analyze the frozen wall closure of an air shaft in the Dongpang Mine, China. The results show that the smallest radius of the frozen soil column is produced around No. 9 and 20 freezing pipes according the proposed longitudinal temperature theory. Using No. 9 and 20 holes as the parent factors and the analyses based on the gray correlation theory, No. 7 through 10 and 18 through 22 frozen holes with higher correlation coefficients are determined as the weak positions within the frozen wall, and the predicted weak positions were confirmed during the shaft excavation. The proposed theory and method are shown to be effective in identifying frozen wall weak points and preventing accidents related to frozen wall closure under high-velocity groundwater conditions.

Explosion venting hazards of temperature effects and pressure characteristics for premixed hydrogen-air mixtures in a spherical container

Explosion venting can effectively reduce the damage effect caused by accidental gas explosions during industrial production. Determining how to eliminate secondary disasters during an explosion is therefore a challenge that can be addressed through the application of explosion venting. This paper discussed the temperature effects and pressure characteristics of premixed hydrogen-air mixtures (PHAMs) in the safety design of vent devices. Tests were designed for the behaviours of hydrogen explosion venting under different bursting pressures. The variation in pressure was controlled by a pressure sensor on the inner wall of a spherical container, and the safety design was assessed theoretically. A high-speed photography device and infrared thermal imaging device were employed to capture the real-time flame field and temperature field during the hydrogen explosion venting process. A comparison of the dimensions of both fields revealed that the high-temperature area was smaller than the flame area. An evaluation of the dynamic hazard of hydrogen explosion venting was then performed based upon pressure characteristics and temperature effects. It was concluded that the prediction results of explosion venting diameter is crucial for industrial safety design.

3D numerical simulation of real-time temperature field in a hyperthermia cancer treatment using OcTree meshes

This paper presents a computational strategy for real-time monitoring of hyperthermia treatment of cancer using nanoparticles. In this strategy, a numerical scheme based on the finite volume method is used for the simulation of heat diffusion in a synthetic biological system. This synthetic model is discretized with OcTree meshes, which can perform local refinement, allowing a good representation of complex geometries, besides having advantages on the use of computational resources. For real-time estimation of temperature in the three-dimensional model, the capture of the temperature field on the external surface of the model is simulated. With the data from these simulations, inverse problems are proposed and solved using the L-BFGS method. The damage caused by a temperature increase in healthy and diseased tissues is estimated, thus simulating a criterion for treatment safety. Numerical examples are analyzed with tumors at different depths, illustrating some particularities of this approach.

Study on laser irradiation temperature field of carbon fiber reinforced plastic composites

Based on Abaqus software, the temperature profiles during laser heating CFRP materials in different fiber directions was investigated in this research. The 3D temperature distribution and temperature history of laminates with different ply directions were analyzed and compared through the homogenous model. It is found that the focusing characteristics of laser causes a large temperature gradient. Meanwhile, the temperature field of CFRP laminate extends toward the direction of fibers because of the large axial thermal conductivity of carbon fibers. The thermal conduction in the thickness direction is poor, so the lower layer will not reach the melting temperature. In order to verify the validity of the model, a real-time temperature field measurement device consisting of thermal imager and thermocouples was built. The results show that the model can effectively simulate the temperature field of composite materials irradiated by laser.

On the identification of flow instabilities in a differentially-heated closed cavity: Non-intrusive measurements

Transition from laminar to turbulent flow in differentially heated closed cavities has been studied quite extensively using numerical simulations, however, experimental studies are rather limited. In one of the numerical works Henkes and Hoogendoorn (1990), it has been indicated that two different mechanisms simultaneously lead to instabilities in the flow, which, in turn, are identified in the form of two frequencies in flow oscillations. The aim of the present work is to identify and investigate these two mechanisms using non-intrusive experiments. As a definite advancement over the conventional ways of predicting flow instabilities using physical probes, which often lead to undesirable flow perturbation(s), the present measurements have been performed in a complete non-intrusive manner. To achieve this, the experimental test section has been mapped using a laser-based Mach Zehnder interferometer. Interferometry-based results are further corroborated using smoke visualization technique. The experiments are conducted for three Rayleigh numbers in the transition regime. The dynamics of the flow is analyzed near one of the corners of the cavity where instability is likely to appear first. Using spectral analysis of the real-time temperature field, frequencies of oscillations have been identified. It is noted that as one moves inside the boundary layer, the amplitude corresponding to one of the two frequencies becomes quite dominant, which indicates towards the presence of Tollmien-Schlichting (TS) instability. Outside the boundary layer, another frequency, along with the above-mentioned frequency, is observed. This additional frequency is due to the instability caused by the hydraulic jump. With further increment in Rayleigh number, more frequencies are found in the flow, which lead to sudden enhancement in heat transfer from the thermally active walls of the cavity.