Prediction Of Temperature Field Research Articles

Microstructure and wear resistance of Ti6Al4V surfaces processed by pulsed laser

When pulsed laser beams deposit spatially and temporally localized power on the metallic surfaces, microstructure and mechanical properties could change significantly. During and after each pulse, the exposed surface experiences a cycle of thermal processes involving extremely high heating and cooling rates, which consequently cause significant microstructure evolution. Changes in mechanical strength follow such microstructural changes. In this work, the influence of pulsed laser processing (PLP) on microstructural evolution, resulting hardness and wear resistance of Ti6Al4V surfaces is investigated. Average pulse power is varied from surface heating to melting regimes in processing. A 2D axisymmetric finite element model of a single pulse is utilized to obtain the heating and cooling histories, and a phase transformation mapping procedure is used to obtain the microstructural evolution. Melting (MZ) and heat affected zones (HAZ) observed at the cross sections of the processed surfaces are found to correlate with the predicted temperature field. The resulting phases in those zones are predominantly martensitic α′ and α phase; higher laser power produces thicker martensitic α′ surface layers several microns into the processed surface. Nanoindentation, nano/microscale and mesoscale wear tests are then applied to the processed surfaces to identify the effects of microstructure on hardness and wear resistance. The surface processed by higher laser power shows higher hardness and wear resistance compared to the surface processed by low power laser. The hardness and wear resistance of the surface processed by low power laser shows no obvious change from substrate material. Mixture of hard martensitic surface layer and underlying ductile substrate resulting from PLP facilitate superior resistance to abrasive and partly low cycle fatigue wear.

Inverse Simulation of Heat Source in Electrical Discharge Machining (EDM)

Temperature field is the main material loading in EDM and responsible for rim zone modifications. For adjusting dedicated surface integrity, it is necessary to quantify the material loading. A direct measurement of temperatures near the working area is not possible due to very high temperatures and corresponding gradients. Also numerical prediction of temperature field is difficult, because no general model for power distribution during EDM process exists. One possibility to obtain this power distribution is inverse simulation. For given temperatures in the inner workpiece a heat source with defined power fraction can be calculated. Hence, the entire temperature field can be determined.

Effects of Model Reduction on Simulated Temperature Fields in Milling

Temperature fields generated in machining processes affect, among other internal material loads, the material modifications in the workpiece surface layer and therefore influence the functional performance of the final component. In particular this might become critical for multipass machining where the amount of heat in the workpiece is accumulated with every path and layer being cut. In the present work a finite element modelling approach for the milling of a complete steel plate is proposed that minimizes computation time while providing a reasonable accuracy of predicted temperature fields. The milling process is modelled as a moving heat source taking into account material removal. Computation time can be reduced up to 98% by systematically increasing the width of the material removal and the heat source width. The effects of the model reduction regarding the temperature fields are investigated in comparison to a reference simulation and furthermore to experiments.

Collocation methods for fuzzy uncertainty propagation in heat conduction problem

Based on the combination of collocation technology and fuzzy theory, this paper proposes a full grid fuzzy collocation method (FGFCM) and a sparse grid fuzzy collocation method (SGFCM) for fuzzy uncertainty propagation in heat conduction problem. Converting fuzzy parameters into interval variables by level-cut strategy, the Legendre polynomial series provides a surrogate function for temperature response. To calculate the expansion coefficients, FGFCM evaluates the deterministic solutions directly on the full tensor product grids, whereas Smolyak algorithm is introduced in SGFCM to reduce the number of collocation points. According to the smoothness property of surrogate function and fuzzy decomposition theorem, the interval bounds and membership functions of uncertain temperature response are derived, respectively. Comparing result with traditional Monte Carlo simulation and parameter perturbation method, two numerical examples evidence the remarkable accuracy and effectiveness of proposed methods for fuzzy temperature field prediction in engineering.

A coupled continuum-discrete bioheat transfer model for vascularized tissue

For a living tissue embedded with multiscale and heterogeneous vascular network, the thermal transport process is considerable complicated so that it is hard to establish a credible and feasible bioheat transfer model for many biomedical applications. This paper is aimed at establishing a novel bioheat transfer model to characterize the heat transfer process in the vascularized tissue. The coupled continuum-discrete model denoted by CCD was proposed in this work. CCD model consists of 3D temperature equation for solid tissue and 1D equation for blood vessel, which are coupled through the discrete heat-source terms. The blood vessels are classified as visible vessel with detailed geometry information obtained from medical image or vascular tree generation method, and invisible capillary without configuration information. The discrete terms for different vascular sizes were separately established to represent the multiscale conjugated blood-tissue thermal interaction. The comparison of CCD model and the existing bioheat models was discussed in detailed. An efficient numerical scheme for CCD model was also developed and demonstrated to accurately predict temperature field of the vascularized tissue, which is furthermore applied to investigate the heat transfer in a realistic vascularized liver.

Predictive modeling and optimization of multi-track processing for laser powder bed fusion of nickel alloy 625

This paper presents an integrated physics-based and statistical modeling approach to predict temperature field and meltpool geometry in multi-track processing of laser powder bed fusion (L-PBF) of nickel 625 alloy. Multi-track laser processing of powder material using L-PBF process has been studied using 2-D finite element simulations to calculate temperature fields along the scan and hatch directions for three consecutive tracks for a moving laser heat source to understand the heating and melting process. Based on the predicted temperature fields, width, depth and shape of the meltpool is determined. Designed experiments on L-PBF of nickel alloy 625 powder material are conducted to measure the relative density and meltpool geometry. Experimental work is reported on the measured density of built coupons and meltpool size. Statistically-based predictive models using response surface regression for relative density, meltpool geometry, peak temperature, and time above melting point are developed and multi-objective optimization studies are conducted by using genetic algorithm and swarm intelligence.

Analytical approach for evaluating temperature field of thermal modified asphalt pavement and urban heat island effect

This paper aims to present an analytical approach to predict temperature fields in asphalt pavement and evaluate the effects of thermal modification on near-surface environment for urban heat island (UHI) effect. The analytical solution of temperature fields in the multi-layered pavement structure was derived with the Green’s function method, using climatic factors including solar radiation, wind velocity, and air temperature as input parameters. The temperature solutions were validated with an outdoor field experiment. By using the proposed analytical solution, temperature fields in the pavement with different pavement surface albedo, thermal conductivity, and layer combinations were analyzed. Heat output from pavement surface to the near-surface environment was studied as an indicator of pavement contribution to UHI effect. The analysis results show that increasing pavement surface albedo could decrease pavement temperature at various depths, and increase heat output intensity in the daytime but decrease heat output intensity in the nighttime. Using reflective pavement to mitigate UHI may be effective for an open street but become ineffective for the street surrounded by high buildings. On the other hand, high-conductivity pavement could alleviate the UHI effect in the daytime for both the open street and the street surrounded by high buildings. Among different combinations of thermal-modified asphalt mixtures, the layer combination of high-conductivity surface course and base course could reduce the maximum heat output intensity and alleviate the UHI effect most.

3D and transient numerical modelling of door opening and closing processes and its influence on thermal performance of cold rooms

This paper presents the comparison of three-dimensional and transient CFD modelling of the opening and closing processes of hinged and sliding doors and its influence on the thermal performance of cold rooms. A species transport model is used to model a tracer gas. The air infiltration through the door opening is determined by the tracer gas concentration decay technique. The prediction of air temperature and velocity fields in the cold room as function of external air temperature allows quantifying the increase of the air infiltration rate and consequently of the average air temperature inside the cold room. When the hinged door is used, the formation of vortices during the opening movement promotes a larger and faster thermal interaction between the two contiguous air masses. The air infiltration during the sliding door opening/closing is 20% lower than for a hinged door. Consequently, the average air temperature inside the cold room is 17% lower. The air infiltration rate was numerically predicted and compared with analytical models’ results. The numerical model predicts closely the air infiltration rate for each door type. Moreover, the transient CFD modelling extends the results of the analytical models allowing the analysis of the influence of door opening and closing processes on the air temperature and velocity fields.

An upper-bound finite element solution for rolling of stainless steel 304L under warm and hot deformation conditions

Purpose The purpose of this paper is to investigate the thermomechanical behavior of stainless steel AISI 304L during rolling at elevated temperatures. Design/methodology/approach Two-dimensional finite element analysis together with the upper-bound solution were used for predicting temperature field and required power in warm and hot rolling operations. The required power and heat of deformation were estimated employing an upper-bound solution based on cylindrical velocity field and at the same time, temperature distributions within the rolling steel and the work rolls were determined by means of a thermal finite element analysis. To consider the effect of flow stress and its dependence on temperature, strain and strain rate, a neural network model was used and combined with the thermal and mechanical models. Finally, the microstructure of rolled steel was studied and the effect of rolling conditions was justified employing the predictions. Findings The results have shown that the predicted temperature variations were in good agreement with the experiments. Moreover, the model was shown to be capable of determining the effects of various rolling parameters such as reduction and rolling speed with low-computational cost as well as reasonable accuracy. Originality/value A combined upper-bound finite element analysis was developed to predict the required power and temperature field during plate rolling while the model can be employed under both hot and warm rolling conditions.

The application of inverse modeling in characterizing hydraulic conductivity beneath the city of Berlin, Germany

In geothermal reservoir characterization and basin modeling, often conclusions are drawn and decisions are made using uncertain or incomplete data sets. Particularly, there are limited hydrogeological data in the Berlin area in the North German Basin. The groundwater in this sedimentary basin is divided into a shallow freshwater aquifer (with about 500 m depth) and a brackish to saline groundwater aquifer within deeper sedimentary layers. Between these two different groundwater compartments, a natural hydrogeological boundary is provided by the presence of an impervious clay-enriched layer (Rupelian Clay), which is discontinuous, eroded or not deposited in some local areas. Thereby, the distribution of hydraulic conductivity of Rupelian Clay aquitard that represents a vertical and horizontal partitioning of the aquifers below Berlin is of main importance in groundwater management. We use an inverse modeling approach to estimate the spatial distribution of hydraulic conductivity of the Rupelian Clay aquitard, using available local data within the Berlin province. We use a commercial finite element fluid flow simulator that interfaces to a parameter estimation package. A Gauss–Levenberg–Marquardt algorithm is used to adjust the hydraulic conductivity of the aquitard such that the hydraulic head observations are reproduced. Subsequently, the updated hydraulic conductivity of the Rupelian Clay is used as input to the forward modeling, in order to estimate the pressure and temperature fields. The results of the inverse modeling suggest a more continuous distribution of the Rupelian Clay layer below the Berlin area in comparison with previous published studies. Hence, the convective heat and fluid flow are more restricted, and there is less interaction between shallow and deep aquifers. Change in the predicted temperature field is more pronounced for deeper strata.

Evaluation of pavement responses and performance with thermal modified asphalt mixture

The thermal properties of asphalt mixture play an important role in determining asphalt pavement temperature and accordingly viscoelastic pavement responses under vehicular loading. This paper aims to quantify the effect of thermal modified asphalt mixture on pavement responses and performance. A validated microstructure model of asphalt mixture was developed to predict thermal properties of asphalt mixtures with different thermal additives. The three-dimensional (3-D) finite element (FE) models were developed to predict temperature fields in the pavement structure and critical pavement responses under vehicular loading. The accuracy of the 3-D FE model was validated with field measurements. The critical responses in different thermal-modified pavement structures were analyzed. The long-term pavement performance including rutting and fatigue cracking were evaluated using the mechanistic-empirical analysis procedure. The analysis results show that using low-conductivity asphalt mixture in the surface course and high-conductivity asphalt mixture in the deeper layer decreased rutting effectively at high temperature and moderate temperature, but increased rutting slightly at low temperature. Using low-conductivity asphalt mixture in the pavement, especially in the upper layers could effectively improve the resistance to fatigue cracking at high temperature and moderate temperature, but slightly decrease the fatigue cracking resistance at low temperature. Finally, thermal-modified pavement structures that can improve both rutting and fatigue cracking resistance effectively were recommended.

Predictions of Temperature and Pressure Fields Due to Collapse of a Bubble in Sulfuric Acid Solution Under Ultrasound

A gas bubble under the influence of an ultrasonic field so strong to destroy any material due to high pressures and temperatures reached during the collapse is the topic of the present paper. In the current work, simulations have been performed to describe the radial dynamics of a gas (argon) bubble being strongly forced to periodic oscillation in a highly viscous liquid like aqueous sulfuric acid solution. The basic equations for nonlinear bubble oscillation in a sound field are given, together with a survey of some important existing studies. The hydrodynamics forces acting on the bubble are taken into account to consider the bubble dynamics under the action of a sound wave. The theory permits one to predict correctly the bubble radius–time behavior and the characteristics of a microsize bubble in sulfuric acid solutions, such as the peak temperature and pressure fields generated at this occasion.

Development of a New Biaxial Testing System for Generating Forming Limit Diagrams for Sheet Metals Under Hot Stamping Conditions

Conventional experimental approaches used to generate forming limit diagrams (FLDs) for sheet metals at different linear strain paths are not applicable to hot stamping and cold die quenching processes because cooling occurs prior to deformation and consistent values of heating rate, cooling rate, deformation temperature and strain rate are not easy to obtain. A novel biaxial testing system for use in a Gleeble testing machine has been adopted to generate forming limits of sheet metals, including aluminium alloys, magnesium alloys and boron steel, under practical hot stamping conditions in which heating and cooling occur. For example, the soaking temperature is about 900 °C and the deformation temperature range is 550–850 °C for boron steel [1] and the soaking temperature is about 535 °C and the deformation temperature range is 370–510 °C for AA6082 [2]. Resistance heating and air cooling were introduced in this pioneering system and the thermal analysis of different heating and cooling strategies was investigated based on a type of cruciform specimen. FE models with a UAMP subroutine were used to predict temperature fields on a specimen in ABAQUS 6.12. Digital image correlation (DIC) system was used to record strain fields of a specimen by capturing images throughout the deformation history and its post-processing software ARAMIS was used to determine forming limits according to ISO standards embedded in the software. Heating and cooling strategies were determined after the analysis. Preliminary results of forming limit curves at the designated temperatures are presented in order to verify the feasibility of this new method.

A three-dimensional model and numerical simulation regarding thermoseed mediated magnetic induction therapy conformal hyperthermia.

In order to ensure the safety and effectiveness of magnetic induction hyperthermia in clinical applications, numerical simulations on the temperature distributions and extent of thermal damage to the targeted regions must be conducted in the preoperative treatment planning system. In this paper, three models, including a thermoseed thermogenesis model, tissue heat transfer model, and tissue thermal damage model, were established based on the four-dimensional energy field, temperature field, and thermal damage field distributions exhibited during hyperthermia. In addition, a numerical simulation study was conducted using the Finite Volume Method (FVM), and the accuracy and reliability of the magnetic induction hyperthermia model and its numerical calculations were verified using computer simulations and experimental results. Thus, this study promoted the application of computing methods to magnetic induction therapy and conformal hyperthermia, and improved the accuracy of the temperature field and tissue thermal damage distribution predictions.

Study of three LES subgrid-scale turbulence models for predictions of heat and mass transfer in large-scale compartment fires

ABSTRACTNumerical assessment was performed to investigate the wall-adaptive features offered by two subgrid-scale (SGS) turbulence models: Wall-Adapting Local Eddy Viscosity (WALE) and Vreman against the Smagorinsky model. The gas temperature and velocity field predictions were enhanced using WALE over Smagorinsky, especially at the flaming and near-wall regions since WALE considers both strain and rotation rates of the turbulent structure and the turbulent viscosity approaches zero at the wall. Conversely, the simulation results by Vreman were under-predicted against the experimental data. The WALE model could notably enhance the simulation accuracy for large-scale compartment fires due to significant improvements of the flow diffusivity modeling.

Collocation methods for uncertain heat convection-diffusion problem with interval input parameters

This paper proposes a full grid interval collocation method (FGICM) and a sparse grid interval collocation method (SGICM) to solve the uncertain heat convection-diffusion problem with interval input parameters in material properties, applied loads and boundary conditions. The Legendre polynomial series is adopted to approximate the functional dependency of temperature response with respect to the interval parameters. In the process of calculating the expansion coefficients, FGICM evaluates the deterministic solutions directly on the full tensor product grids, while the Smolyak sparse grids are reconstructed in SGICM to avoid the curse of dimensionality. The eventual lower and upper bounds of temperature responses are easily predicted based on the continuously-differentiable property of the approximate function. Comparing results with traditional Monte Carlo simulations and perturbation method, the numerical example evidences the remarkable accuracy and effectiveness of the proposed methods for interval temperature field prediction in engineering.

Uncertainty propagation of heat conduction problem with multiple random inputs

Uncertainty propagation analysis in engineering systems constitutes a significant challenge. To effectively solve the uncertain heat conduction problem with multiple random inputs, a random collocation method (RCM) and a modified random collocation method (MRCM) are established based on the spectral analysis theory. In both methods, the truncated high-order polynomial series is adopted to approximate the temperature responses with respect to random parameters, and the eventual probabilistic moments are derived by using the orthogonal relationship of polynomial bases. In the pivotal process of calculating the expansion coefficients, RCM evaluates the deterministic solutions directly on full tensor product grids, whereas the Smolyak sparse grids are reconstructed in MRCM to avoid the huge computational cost caused by high dimensions. Comparing the results with traditional Monte Carlo simulation, two numerical examples verify the remarkable accuracy and effectiveness of the proposed methods for random temperature field prediction in engineering.

Multisite multivariate modeling of daily precipitation and temperature in the Canadian Prairie Provinces using generalized linear models

Based on the Generalized Linear Model (GLM) framework, a multisite stochastic modelling approach is developed using daily observations of precipitation and minimum and maximum temperatures from 120 sites located across the Canadian Prairie Provinces: Alberta, Saskatchewan and Manitoba. Temperature is modeled using a two-stage normal-heteroscedastic model by fitting mean and variance components separately. Likewise, precipitation occurrence and conditional precipitation intensity processes are modeled separately. The relationship between precipitation and temperature is accounted for by using transformations of precipitation as covariates to predict temperature fields. Large scale atmospheric covariates from the National Center for Environmental Prediction Reanalysis-I, teleconnection indices, geographical site attributes, and observed precipitation and temperature records are used to calibrate these models for the 1971–2000 period. Validation of the developed models is performed on both pre- and post-calibration period data. Results of the study indicate that the developed models are able to capture spatiotemporal characteristics of observed precipitation and temperature fields, such as inter-site and inter-variable correlation structure, and systematic regional variations present in observed sequences. A number of simulated weather statistics ranging from seasonal means to characteristics of temperature and precipitation extremes and some of the commonly used climate indices are also found to be in close agreement with those derived from observed data. This GLM-based modelling approach will be developed further for multisite statistical downscaling of Global Climate Model outputs to explore climate variability and change in this region of Canada.

Numerical prediction of temperature field for cargo containment system (CCS) of LNG carriers during pre-cooling operations

To minimize the thermal gradient of cargo containment system (CCS), the cargo tanks of LNG carriers must be pre-cooled gradually before loading bulk LNG cargos. This paper presents a numerical prediction of the thermodynamics associated with the pre-cooling operation of the membrane-type tanks of the LNG carriers using a computational fluid dynamics (CFD) model. In this work, the CCS physical model is used and the latent heat caused by the phase transition during the LNG boiling process is included when calculating the associated heat transfer. The numerical results are firstly compared with the experimental data available in literature. The characteristics of conjugate heat transfer, the temperature field in the CCS and fluid inside the cargo tank, the temperature gradient in the insulation layers are focused, which are distinguished it from previous work. The results and conclusions may help guiding the pre-cooling operation for LNG carriers.

Crack Risk Evaluation of Early Age Concrete Based on the Distributed Optical Fiber Temperature Sensing

Cracks often appear in concrete arch dams, due to the thermal stress and low tensile strength of early age concrete. There are three commonly used temperature controlling measures: controlling the casting temperature, burying cooling pipe, and protecting the surface. However, because of the difficulty to obtain accurate temperature and thermal stress field of the concrete, the rationality and economy of these measures are not assessed validly before and after construction. In this paper, a crack risk evaluation system for early age concrete is established, including distributed optical fiber temperature sensing (DTS), prediction of temperature and stress fields, and crack risk evaluation. Based on the DTS temperature data, the back-analysis method is applied to retrieve the thermal parameters of concrete. Then, the temperature and thermal stress of early age concrete are predicted using the reversed thermal parameters, as well as the laboratory test parameters. Finally, under the proposed cracking risk evaluation principle, the cracking risk level of each concrete block is given; the preliminary and later temperature controlling measures were recommended, respectively. The application of the proposed system in Xiluodu super high arch dam shows that this system works effectively for preventing cracks of early age concrete.