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•Flame propagation behaviors in explosion venting were discussed.•The quantitative relationship of the maximum flame front length was received.•Obtained the variation of the ...temperature field in explosion venting.•Safety design feasibility of the over-scope of NFPA 68 and EN 14491 was assessed.
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.
A high grinding temperature will cause thermal damage to a workpiece surface and deterioration of surface integrity, which is the bottleneck of grinding. The present grinding temperature theoretical ...model is based on grain homogeneity and the continuous heat source distribution in the grinding zone. However, the random change in interference between the effective grains and a workpiece during the machining process causes a change in the grain tribological properties, resulting in varying transient grinding temperatures. Based on the current situation, the grain tribological mechanism and an improved temperature model based on a discrete heat source are proposed to reveal the temperature variation law of a workpiece in an actual grinding process. First, the surface topography model of a grinding wheel is established based on the geometric characteristics of grains, and the determination mechanism of effective grains is revealed. Furthermore, the interference mechanical behavior of the grains and workpiece is analyzed according to the kinematic law of grains in the sliding, plowing, and cutting stages. The mechanical model and specific grinding energy model at different stages are established, and the thermal distribution mechanism of effective grains is revealed. Finally, a temperature field mathematical model of a discrete heat source is established, and numerical simulation is performed to demonstrate the dynamic temperature change process of different grains. A new experimental method for measuring temperature at different positions of the workpiece with a bipolar thermocouple array is designed, and a regional numerical simulation and experimental temperature comparison method is innovatively proposed. Experimental results show that the grinding temperature measured under different cutting depth conditions is in good agreement with the numerical results, and the variation law is consistent. The minimum error in 64 groups of experimental measuring and numerical calculation comparison zones can reach 4.9%, and the proportion of zones with errors less than 10% can approach 86%. This study will provide a theoretical basis for the accurate suppression of workpiece surface thermal damage and the development of precision grinding in engineering discipline and machinery industry.
The detailed measuring of temperature field in vortex tube with smaller size thermocouple is significantly important to understand the energy separation phenomenon in such tube. This experimental ...study presents a comprehensive method to measure the 2D temperature field of vortex tube using self-made thermocouple with a temperature sensing point diameter of 80 μm. The temperature distributions along a special radial line, and on a special 2D domain, the isentropic efficiency and COP (coefficient of performance) of the vortex tube were measured with mass flow rate ranging from 100 to 180 SLM and cold flow ratio from 0.30 to 0.80. A two-dimensional temperature field measurement method in vortex tube with axial resolution of 0.1 mm and circumferential resolution of 1° is proposed. The thermal performances of a vortex tube combined diverging and straight hot outlet are obtained. It is found that dimensionless cold temperature difference can be represented as a function of the cold mass fraction. A radial temperature distribution was obtained at flow rate of 100–160 SLM and cold flow ratio of 0.3–0.8. It is found that at a given cold flow ratio, the dimensionless temperature at the same axial position under different flow rates follows the same third-order polynomial function of the radial position.
•A setup using the thermocouples to measure 2D temperature fields in the vortex tube was reported.•2D temperature fields and the performances of a diverging-straight vortex tube were measured.•Given cold flow ratio, the dimensionless temperatures along the same radial of the vortex tube have the same distribution.•A correlation between the ratio of cold temperature to its maximum and the cold mass fraction is obtained.
During a tunnel fire incident, a substantial volume of high-temperature smoke gathers and disperses beneath the tunnel ceiling, posing significant risks of casualties and structural harm. A ...comprehensive comprehension of the temperature distribution of smoke beneath the ceiling is pivotal for the fire-resistant design and formulation of rescue plans for tunnel structures. This paper initially employs the FTP theory to analyze the fire scene resulting from fire spread under vehicle congestion. Subsequently, A set of numerical simulations is performed, and a prediction model of the temperature field for transverse symmetrical double fires is established according to the simulation results. Finally, an air entrainment model for transverse symmetrical double fires is proposed. The air entrainment amount under different fire spacing is obtained by theoretical derivation. Combined with the relationship between air entrainment amount, flame height, and maximum temperature, the variation of temperature field under the ceiling with fire spacing is explained from the mechanism. The results show that: the maximum temperature beneath tunnel ceiling increases with the increase of the fire power, decreases and then increases with the increase of the fire spacing and the variation has symmetry; The temperature attenuation along transverse and longitudinal directions under the ceiling following the exponential attenuation model, and the temperature attenuation rate is positively correlated with the maximum temperature. The transverse temperature attenuation is smaller than that of the longitudinal temperature under the same conditions; There is an internal relationship between the air entrainment, flame height and temperature field of the transverse double fires. The variation law of the temperature field beneath the ceiling depends on the degree of air entrainment limitation. Based on mirror model, this paper indicates that when the fire spacing is within a certain range, the combustion of the double fires can be effectively represented as near-wall fire.
Recently, surrogate models based on deep learning have attracted much attention for engineering analysis and optimization. Since constructing data pairs in most engineering problems is ...time-consuming, data acquisition is becoming the predictive capability bottleneck of most deep surrogate models, which also exist in surrogate for thermal analysis and design. In contrast with data-driven learning, enforcing the physical laws in building surrogates has emerged as a promising alternative to reduce the dependence on annotated data. This paper develops a physics-informed convolutional neural network (CNN) for the thermal simulation surrogate without labeled data. Firstly, we leverage the finite difference method to integrate heat conduction equation and loss function construction, guiding surrogate model training to minimize the violation of physical laws. Since the solution is sensitive to boundary conditions, we properly impose hard constraints by padding in the Dirichlet and Neumann boundaries. The proposed network can learn a mapping from heat source layout to the steady-state temperature field without labeled data, which equals solving an entire family of partial difference equations (PDEs). Moreover, the neural network architecture is well-designed to improve the prediction accuracy of the problem at hand, and pixel-level online hard example mining is proposed to overcome the imbalance of optimization difficulty in the computation domain, which is beneficial to the network training of physics-informed learning. The experiments demonstrate that the proposed method can provide comparable predictions with numerical methods and data-driven deep learning models. We also conduct various ablation studies to investigate the effectiveness of the proposed network components and training methods in this paper. Furthermore, the developed methods can be applied to other design and optimization applications which need to solve parameterized PDEs.
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•A 3D combustion temperature prediction method, GDNN, uses CFD simulations to achieve online reconstructions was proposed.•A temperature field correction method employs actual ...measurement points was proposed to correct the prediction results.•Optimal parameters for the proposed prediction and correction method were selected through a parameter analysis.•The proposed GDNN and correction method jointly yield the lowest error, demonstrating their real-world effectiveness.
Predicting furnace temperature distribution is vital for coal-fired boiler safety. Existing methods, including finite element calculations and three-dimensional (3D) reconstruction still face limitations. A 3D combustion temperature field prediction method, GDNN, which utilizes offline-computed computational fluid dynamics (CFD) simulation results for online reconstructions of entire boiler, was proposed. GDNN method leverages the knowledge of the temperature field acquired by the base neural network model and Gaussian processes. Furthermore, a temperature field correction method is introduced, which employs intermediate variables of the GDNN model and measured values from temperature sensors to establish a correction model for the entire predicted temperature field. We compared GDNN's effectiveness with four well-established algorithms: Extreme Learning Machine (ELM), Least Absolute Shrinkage and Selection Operator (LASSO), Deep Neural Network(DNN), and Radial Basis Function (RBF) network, by also substituting these algorithms as the base model in our proposed method. The experimental results demonstrate that the proposed prediction method exhibits the highest performance, and the correction method effectively improves the overall results. The optimal parameters for predicting and correcting 3D furnace temperature field results were determined through experimental comparison, and the proposed method was applied to a 350 MW boiler, achieving an error of 2.41%, proving its real-world effectiveness.
I present a numerical package (CosmoTransitions) for analyzing finite-temperature cosmological phase transitions driven by single or multiple scalar fields. The package analyzes the different vacua ...of a theory to determine their critical temperatures (where the vacuum energy levels are degenerate), their supercooling temperatures, and the bubble wall profiles which separate the phases and describe their tunneling dynamics. I introduce a new method of path deformation to find the profiles of both thin- and thick-walled bubbles. CosmoTransitions is freely available for public use.
Program summary
Program Title: CosmoTransitions
Catalogue identifier: AEML_v1_0
Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEML_v1_0.html
Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland
Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 8775
No. of bytes in distributed program, including test data, etc.: 621096
Distribution format: tar.gz
Programming language: Python.
Computer: Developed on a 2009 MacBook Pro. No computer-specific optimization was performed.
Operating system: Designed and tested on Mac OS X 10.6.8. Compatible with any OS with Python installed.
RAM: Approximately 50 MB, mostly for loading plotting packages.
Classification: 1.9, 11.1.
External routines: SciPy, NumPy, matplotLib
Nature of problem: I describe a program to analyze early-Universe finite-temperature phase transitions with multiple scalar fields. The goal is to analyze the phase structure of an input theory, determine the amount of supercooling at each phase transition, and find the bubble-wall profiles of the nucleated bubbles that drive the transitions.
Solution method: To find the bubble-wall profile, the program assumes that tunneling happens along a fixed path in field space. This reduces the equations of motion to one dimension, which can then be solved using the overshoot/undershoot method. The path iteratively deforms in the direction opposite the forces perpendicular to the path until the perpendicular forces vanish (or become very small). To find the phase structure, the program finds and integrates the change in a phase’s minimum with respect to temperature.
Running time: Approximately 1 minute for full analysis of the two-scalar-field test model on a 2.5 GHz CPU.
The spontaneous combustion of coal in goaf has important implications for the safe mining of working faces; hence, it is crucial to prevent and control such occurrences. Here, we establish an ...experimental system to investigate the morphological distribution, evolution, and migration process of the temperature field of the thermal core area in systems with various particle sizes. Furthermore, we propose a high-temperature-region inversion method based on the morphological evolution model of the temperature field. Our experimental results demonstrate that particle size is a critical factor influencing the temperature field morphology under a given heating condition. During the heating stage, the isothermal surface within the thermal core area forms an ellipsoidal shape, with a transverse section comprising concentric circles, and a longitudinal section comprising ellipses. During the heat dissipation stage, the isothermal surface of the small-particle-size system encircles the thermal core area from the upper direction downwards, while the isothermal surface of the large-particle-size system encircles the thermal core area from the lower direction upwards. Moreover, the thermal core area of the large-particle-size system migrates upwards, while the thermal core area of the small-particle-size system migrates a shorter distance. Finally, we used a geometrically simplified temperature field in loose media to propose a high-temperature-region inversion method, which was verified by experiments. This study is crucial for understanding the distribution and evolution of temperature fields in loose media and predicting the formation and development of high-temperature regions.
•Three heat transfer mechanisms were simultaneously considered.•Temperature fields on both global and local scales were obtained.•A digital image processing technology was adopted to construct the ...representative volume element finite element model.•Mechanical and thermal properties on two scales were included in computation and linked via homogenization.•Effect of temperature fields on damage initiation of asphalt pavement was analyzed.
The present study developed a microstructure-based multiscale finite element (FE) method to investigate the effect of temperature fields on the damage initiation within the asphalt pavement under traffic loading. Three heat transfer mechanisms that dominate the temperature distribution in the pavement structure, i.e., thermal radiation, convection, and conduction, were considered in the multiscale modeling. Both mechanical and thermal properties of asphalt concrete (AC) on two physical length scales, namely, global (pavement level) and the local (mixture level) scales, were included in the computation and connected via a homogenization process. A digital image processing (DIP) technology was adopted to establish the local-scale representative volume element (RVE) model that interpreted the realistic heterogeneity of the AC microstructure, and a bilinear cohesive zone model was employed to model the damage initiation in the RVEs. The results showed that the developed multiscale FE model provided an insight into the damage behavior of asphalt pavement subjected to temperature fields varying with time on both the global and local scales, indicating the importance of considering temperature fields in pavement structural analysis. By means of the presented method, the influence of temperature fields, pavement structures, mixture microstructures and component properties, and interface behavior between mortar matrix phase and coarse aggregates on the pavement damage initiation could be rationally taken into account in the analysis. In light of these benefits, the presented approach can be expected to be utilized as a mechanistic tool for improving the performance prediction and evaluation as well as mixture and structural design of asphalt pavements.
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