Accurate Prediction Of Temperature Distribution Research Articles

Linear modeling analysis of the heat balance of the transmission line in high frequency critical ice melting state

Abstract The icing of transmission lines can cause many problems such as increased line load, unbalanced tension, and galloping, posing a serious threat to the reliable operation of the power system. Therefore, linear modeling analysis of the heat balance under a high-frequency critical ice melting state of transmission lines is studied. The thermal conduction states of melting, heating, twisting, rotating melting, and ice layer detachment of ice melting conductors are analyzed. Based on the heat conduction process of thermal melting of ice on transmission lines, a simplified calculation formula for thermal melting ice time is derived to calculate times for heating, ice layer torsion, and air gap increase. At the same time, based on the law of conservation of energy, thermodynamic boundary conditions for iced conductors were established and corresponding physical models were constructed. Based on this model, we conduct a linear modeling of the heat balance in the melting state in order to provide a more accurate prediction of temperature distribution. The experimental results show that there is a negative correlation between environmental temperature and critical melting current, and the melting time decreases with the increase of environmental temperature.

On the importance of heat source model determination for numerical modeling of selective laser melting of IN625

Accurate prediction of temperature distribution and melt pool geometry in metal additive manufacturing is highly dependent on the appropriate selection of heat source models. In the present study, a three-dimensional (3D) finite element (FE) heat transfer model is developed utilizing Abaqus by integrating different heat source models focusing on the surface heat source model and volumetric heat source model for selective laser melting (SLM) of Inconel 625 (IN625). All of the predicted peak temperatures, molten pool width, and depth are evaluated and compared with the experimental results cited from open literature. The relative error in simulated peak temperature and melt pool geometry from the surface heat source model is much higher in comparison to the volumetric heat transfer model. Further, a hybrid heat source model incorporating surface and volumetric heat models is developed to fulfill the numerical modeling of SLM of IN625 with high accuracy, which is highly recommended for the in-depth simulation study.

Large-Scale Robot-Based Polymer and Composite Additive Manufacturing: Failure Modes and Thermal Simulation.

Additive manufacturing (AM) of large-scale polymer and composite parts using robotic arms integrated with extruders has received significant attention in recent years. Despite the contributions of great technical progress and material development towards optimizing this manufacturing method, different failure modes observed in the final printed products have hindered its application in producing large engineering structures used in aerospace and automotive industries. We report failure modes in a variety of printed polymer and composite parts, including fuel tanks and car bumpers. Delamination and warpage observed in these parts originate mostly from thermal gradients and residual stresses accumulated during material deposition and cooling. Because printing large structures requires expensive resources, process simulation to recognize the possible failure modes can significantly lower the manufacturing cost. In this regard, accurate prediction of temperature distribution using thermal simulations is the first step. Finite element analysis (FEA) was used for process simulation of large-scale robotic AM. The important steps of the simulation are presented, and the challenges related to the modeling are recognized and discussed in detail. The numerical results showed reasonable agreement with the temperature data measured by an infrared camera. While in small-scale extrusion AM, the cooling time to the glassy state is less than 1 s, in large-scale AM, the cooling time is around two orders of magnitudes longer.

An image-based computational modeling approach for prediction of temperature distribution during photothermal therapy

Nanoparticle-assisted photothermal therapy (NPTT) has recently renewed the interest of using hyperthermia in cancer therapy due to selective heating of tumor by utilizing light-responsive nanoparticles such as gold nanoparticles (AuNPs). Pre-treatment planning of NPTT can help to predict temperature distribution within the body in order to optimize the treatment parameters before the actual heating operation. The use of actual tumor geometry and nanoparticle distribution are key requirements for accurate prediction of temperature distribution during numerical calculations of the heat transfer process. This study attempts to develop a numerical modeling strategy for NPTT based on computed tomography (CT) imaging. To this end, CT26 colon tumor-bearing mice were injected with alginate-coated AuNPs (Au@Alg) and then underwent CT imaging. The tumor geometry and nanoparticle distribution map were obtained directly from CT image of the tumor and exported into a finite element simulation software for subsequent heat transfer modeling. The predicted temperature of the tumor from numerical modeling was found to be in reasonable agreement with the measured data from in vivo thermometry. This model has the potential to be used as a pre-treatment planning tool to design an individualized heating protocol for various tumor geometry before the actual heating treatment.

Improved thermal model considering hydrate formation and deposition in gas-dominated systems with free water

The accurate prediction of temperature is the basis for predicting hydrate formation. Presently available methods for the calculation of temperature distributions in pipelines are based solely on the traditional heat transfer mechanism between the high-temperature fluid in the pipeline and the low-temperature surroundings. The influences of hydrate formation and deposition behaviors on the temperature variation have not been considered in the heat transfer process. Hydrate formation is exothermic, and the hydrate layer formed by the deposition of hydrates has a resistance effect to the heat transfer process. In this study, an improved thermal model for predicting the temperature distribution in gas-dominated systems is proposed. In this model, the influences of hydrate formation and deposition behaviors on the variation in temperature are considered. The model is verified by comparing with experimental data from literature. The transient variation in temperature along the pipeline can be obtained using the model. The simulation results indicate that hydrate formation and deposition have a significant influence on the variation in temperature in the pipeline, and can cause an inhibiting effect on the later hydrate formation. This work adds further insight into the heat transfer process and can serve as useful reference for the accurate prediction of temperature distributions in pipelines.

Hardness Profile Prediction for a 4340 Steel Spline Shaft Heat Treated by Laser Using a 3D Modeling and Experimental Validation

Laser surface transformation hardening becomes one of the most effective processes used to improve wear and fatigue resistance of mechanical parts. In this process, the material physicochemical properties and the heating system parameters have significant effects on the characteristics of the hardened surface. To appropriately exploit the benefits presented by the laser surface hardening, it is necessary to develop a comprehensive strategy to control the process variables in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. The paper presents a study of hardness profile predictive modeling and experimental validation for spline shafts using a 3D model. The proposed approach is based on thermal and metallurgical simulations, experimental investigations and statistical analysis to build the prediction model. The simulation of the hardening process is carried out using 3D finite element model on commercial software. The model is used to estimate the temperature distribution and the hardness profile attributes for various hardening parameters, such as laser power, shaft rotation speed and scanning speed. The experimental calibration and validation of the model are performed on a 3 kW Nd:Yag laser system using a structured experimental design and confirmed statistical analysis tools. The results reveal that the model can provide not only a consistent and accurate prediction of temperature distribution and hardness profile characteristics under variable hardening parameters and conditions but also a comprehensive and quantitative analysis of process parameters effects. The modelling results show a great concordance between predicted and measured values for the dimensions of hardened zones.

Study of Frequency Effects on Hardness Profile of Spline Shaft Heat-Treated by Induction

This paper is devoted to the study of frequency effects on hardness profile of AISI 4340 spline shaft heat-treated by induction through an extensive 3D finite element method simulation and structured experimental investigation. Based on coupled electromagnetic and thermal fields analysis, the 3D model is used to estimate the temperature distribution and the hardness profile. The proposed study examines the hardening process parameters, such as frequency, induced current density and heating time, known to have an influence on hardened surface and builds the simulation model step by step. The established model can provide not only an accurate prediction of temperature distribution and hardness profile but also a comprehensive analysis of machine parameters effects, especially the frequency. The numerical results achieved by this model are good and present a great agreement to the experimental data.

Modeling of Heat Transfer Coefficient of Oxide Scale in Hot Forging

In hot forging processes, an accurate prediction of temperature distribution is important because it affects not only the forging load but also the material flow itself and the distribution of material properties in forged parts. An oxide scale will form at the surface of steel when heated to high temperature. The heat flows through this scale layer from the high temperature material to the dies or air, thus for an accurate prediction of temperature distribution, a precise evaluation of the heat transfer coefficient of scales is required. In actual hot forging processes, the thickness and composition of oxide scales will vary with the composition of steel, heating temperature and time, or the atmosphere. In this study, the heat transfer coefficients of oxide scales, formed on the surface of medium carbon steel with various heating temperature and heating time, are measured. A model of heat transfer coefficients is obtained as a function of the thickness of each oxide contents layer and the contact pressure.

Measurement of the Thermal Conductivity of Carbon Nanotube–Tissue Phantom Composites with the Hot Wire Probe Method

Developing combinatorial treatments involving laser irradiation and nanoparticles require an understanding of the effect of nanoparticle inclusion on tissue thermal properties, such as thermal conductivity. This information will permit a more accurate prediction of temperature distribution and tumor response following therapy, as well as provide additional information to aid in the selection of the appropriate type and concentration of nanoparticles. This study measured the thermal conductivity of tissue representative phantoms containing varying types and concentrations of carbon nanotubes (CNTs). Multi-walled carbon nanotubes (MWNTs, length of 900-1200nm and diameter of 40-60nm), single-walled carbon nanotubes (SWNTs, length of 900-1200nm and diameter <2nm), and a novel embodiment of SWNTs referred to as single-walled carbon nanohorns (SWNHs, length of 25-50nm and diameter of 3-5nm) of varying concentrations (0.1, 0.5, and 1.0mg/mL) were uniformly dispersed in sodium alginate tissue representative phantoms. The thermal conductivity of phantoms containing CNTs was measured using a hot wire probe method. Increasing CNT concentration from 0 to 1.0mg/mL caused the thermal conductivity of phantoms containing SWNTs, SWNHs, and MWNTs to increase by 24, 30, and 66%, respectively. For identical CNT concentrations, phantoms containing MWNTs possessed the highest thermal conductivity.

The zone-particle model for building fire simulation

An effective fire and smoke propagation model is important for evaluating building safety, indicating safe rescue paths in emergencies, and determining proper control strategies. In this paper, a new model to simulate smoke propagation and to characterize mixing behavior is developed. In this model, a function considering the mixing behavior between the hot smoke and cool air is introduced to better resolve the temperature and smoke profiles in the vertical direction. Smoothed particle hydrodynamics (SPH) approach is used to obtain the function distribution through reconstructing velocities of marker particles and determining locations of particles in each layer in the zone model. The fundamentals of the model are presented in detail in this paper. A test (a simple building with experimental data and CFD simulation) is used to verify the model, in which experimental data and CFD simulations are compared to predictions from the new model and those from a two-layer model implemented using CFAST (Consolidated Model of Fire and Smoke Transport, developed by NIST). Favorable agreement of the new model results is seen with experiment data or CFD simulations. The new model also provides more accurate prediction of temperature distribution in comparison to the two-layer model.

Prediction of pulsed-laser powder deposits’ shape profiles using a back-propagation artificial neural network

The cross-sectional shape profile geometry of blown powder clad deposit is important for overall structural integrity of the clad layer. The penetration zone of the clad deposit is represented within its shape profile geometry. The shape profile geometry of the clad deposit is also important for thermomechanical modelling. Although a rough estimation of blown powder clad deposit shape profile can be made based on the powder feeding parameters using empirical formulae, it may not be sufficiently accurate to be used in a thermomechanical model, as it may lead to inaccuracy in the prediction of temperature distributions, residual stresses, and distortion. The pulsed-laser blown powder deposition process is a highly coupled multivariable problem. Hence the deterministic numerical-methods-based prediction of pulsed-laser powder deposit shape profile geometry is time consuming, costly, and may not be adequate to predict the profile geometry over a wide range of varying process parameters. The present investigation deals with the cross-sectional shape profile geometry modelling of the pulsed-laser assisted superalloy powder deposition (PLPD) process using a soft computing approach. A simple yet effective mapping technique was used in the present work to map the experimentally obtained shape profiles of the powder deposits. The mapped characteristics of the powder deposits’ shape profiles were used in the back-propagation artificial neural network (ANN) modelling of the PLPD process. The present modelling technique can be conveniently used to incorporate the PLPD shape profile geometry parameters in thermomechanical analyses for accurate prediction of temperature distributions and residual stresses. Based on the present soft computing modelling methodology, an estimation of top reinforcement and penetration zone shape boundaries of a blown powder clad deposit can also be made.

Numerical studies of the melting process in the induction furnace with cold crucible

PurposeAims to present recent activities in numerical modeling of cold crucible melting process.Design/methodology/approach3D numerical analysis was used for electromagnetic problem and 3D large eddy simulation (LES) method was applied for fluid flow modeling.FindingsThe comparative modeling shows, that higher H/D ratio of the melt is more efficient when total power consumption is considered, but this advantage is held back by higher heat losses through the crucible walls. Also, calculations reveal that lower frequencies, which are energetically less effective, provide better mixing of the melt.Originality/value3D electromagnetic model, which allows to take into account non‐symmetrical distribution of Joule heat sources, together with transient LES fluid flow simulation gives the opportunity of accurate prediction of temperature distribution in the melt.

Power Loss Predictions in Geared Transmissions Using Thermal Networks-Applications to a Six-Speed Manual Gearbox

A model is presented which makes it possible to predict power losses in a six-speed manual gearbox. The following sources of dissipation, i.e., power inputs in the model, are considered: (i) tooth friction; (ii) rolling element bearings; (iii) oil shearing in the synchronizers and at the shaft-free pinion interfaces; and (iv) oil churning. Based upon the first principle of Thermodynamics for transient conditions, the entire gearbox is divided into lumped elements with a uniform temperature connected by thermal resistances which account for conduction, convection, and radiation. The numerical predictions compare favorably with the efficiency measurements from the actual gearbox at different speeds and torques. The results also reveal that, at lower temperatures (about 40°C), power loss estimations cannot be disassociated from the accurate prediction of temperature distributions.

Numerical and Experimental Heat Transfer Studies on Totally Enclosed Fan Ventilated Machines

Accurate prediction of temperature distribution in an electrical machine at the design stage is becoming increasingly important. It is essential to know the locations and magnitudes of hot spot temperatures for optimum design of electrical machines. A methodology based on the finite element method to analyze the steady-state and transient thermal problems in Totally Enclosed Fan Ventilated (TEFV) machines has been developed. The axi-symmetric model adopted is formulated purely from dimensional data, property data, and published convective correlations. In the present work, system analysis of a TEFV machine comprised of rotor, stator, body frame, and end covers has been carried out. The model has been validated by heat run tests conducted on three TEFV motors of rating 3.7, 7.5 and 15 kW and one Totally Enclosed Non-Ventilated (TENV) motor of 5.7 kW. Stalled tests have been carried out on the TENV motor at voltages of 300, 360 and 415 V to validate the predicted transient temperatures.

Finite element solution of conjugate heat transfer problems with and without the use of gap elements

This paper describes the finite element solution of conjugate heat transfer problems with and without the use of gap elements. Direct and iterative methods to incorporate gap elements into a general finite element program are presented, along with their advantages and disadvantages of the two gap element treatments in the framework of finite elements. The numerical performance of the iterative gap element treatment is discussed in detail in comparison with analytical solutions for both 2‐ and 3‐D gap conductance problems. Numerical tests show that the number of iterations depends on the non‐dimensional number Bi = hL/k, and it increases approximately linearly with Bi for Bi≥0.6. Here, for gap heat transfer problems, h is taken to be the inverse of the contact resistance. This conclusion holds true for both 2‐ and 3‐D problems, for both linear and quadratic elements and for both transient and steady state calculations. Further numerical results for conjugate heat transfer problems encountered in heat exchanger and micro chemical reactors are computed using the gap element approach, the direct numerical simulations and analytical solutions whenever solvable. The results reveal that for the standard heat exchanger designs, an accurate prediction of temperature distribution in the moving streams must take into consideration the radial temperature distribution and the accuracy of the calculations depends on the non‐dimensional number Bi = hR/2k. From gap element calculations, it is found that classical analytical solutions are valid for a heat transfer analysis of an exchanger system, only when Bi&lt;0.1. This important point so far has been neglected in virtually all the textbooks on heat transfer and must be included to complete the heat transfer theory for heat exchanger designs. Results also suggest that for thermal fluids systems with chemical reactions such as micro fuel cells, the gap element approach yields accurate results only when the heat transfer coefficient that accounts for the chemical reactions is used. However, when these heat transfer coefficients are not available, direct numerical simulations should be used for an accurate prediction of the thermal performance of these systems.

Planning of hyperthermic treatment for malignant glioma using computer simulation

Interstitial hyperthermia was applied using a radiofrequency generator in the treatment of four malignant glioma patients who had especially deep seated brain tumours or were at high risk. Prior to heating tumours, treatment planning based on an accurate prediction of temperature distribution is essential. The present paper introduces a novel treatment planning method and discusses its clinical efficacy. The two-dimensional finite element method was used for simulation of temperature distribution, which was calculated using the bioheat transfer equation. This technique was applied to plan treatment. Temperature was measured at two points during heating and these values were compared with those estimated by the simulation. In addition, the area of the contrast enhanced (CE) rim on the pre-heating computed tomography (CT) image was compared with the low density area of the CE rim on the post-heating CT image, which was obtained within 2 months after heating. The optimal position and number of radiofrequency (RF) electrodes to include the outside of the CE rim in the simulated area above 42°C contour could be easily determined using this planning system in all cases. The temperature estimated by the simulation was in good agreement with the actual values obtained (within 0.4°C). The post-heating CT image revealed that the hyperthermic procedure described herein achieved more than an 80% low density area within the CE rim in all cases (mean 86.0%). These results demonstrate that this novel treatment planning method may prove to be a clinically valuable tool in the treatment of malignant glioma with RF electrodes.

Finite element analysis of radial cooled rotating electrical machines

Accurate prediction of temperature distribution in an electrical machine at the design stage is becoming increasingly important. It is essential to know the locations and magnitudes of hot spot temperatures for optimum design of electrical machines. A methodology based on axi‐symmetric finite element formulation has been developed to solve the conduction‐convection problem in radial cooled machines using a new eight noded solid‐fluid coupled element. The axi‐symmetric model adopted is formulated purely from dimensional data, property data and published convective correlations. Steady state temperatures have been determined for 102 kW radial cooled motor at 100 percent and 75 percent loads and are validated with experimental results obtained from heat run tests. Parametric studies have been carried out to study the effect of critical parameters on temperature distribution and for optimising the design.