Internal Thermal Resistance Research Articles

Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes

A single loop Pulsating Heating Pipe (PHP) experimental setup was developed for non-invasive measurement of the local heat transfer coefficient and the mass flow along the PHP evaporator. These measurements are valuable to validate modeling tools used in the design of PHP. A two-step differential heat input method was used for measurement of mass flow and the results were compared with the optical and theoretical results. The conditions tested in the PHP were 50, 60 and 70% filling ratio, R134a as working fluid, internal diameter of 2 mm, saturation temperature of between 30 to 40 °C, inclination angles from 30 to 90° (vertical bottom heat mode) and heat loads on the evaporator from 10 up to 68 W. The results indicate a high performance in heat transfer of the PHP, with minimum internal thermal resistance values close to 0.008 K/W as well as local heat transfer coefficients greater than 10 kW/m2K for observed values of mass velocities between 60 and 140 kg/m2s. The results were compared with correlations from the literature and these were able to predict the results with a 20% average error margin, suggesting many similarities with convective boiling mechanisms.

A novel characteristic curve for thermoelectric cooler application in realistic thermal circumstances: Theory and experiment

On the materials level, the performance of thermoelectric (TE) devices can be defined by the thermoelectric figure of merit (zT). This, however, does not provide a complete picture due to the complex interplay between electronic and thermal transport properties and the uncertain thermal impedance matching between external and internal thermal resistances in different realistic thermal circumstances. Appropriate design of individual material properties and geometry parameters considering the realistic thermal circumstance can greatly enhance the device-level performance of TE devices. In this work, we develop a framework to clarify such interactions in thermoelectric coolers (TEC) with a newly proposed q-h characteristic curve, which can be used to identify how a TEC design is of effectiveness for a specific realistic thermal circumstance. The effects of zT, the individual TE material properties (i.e., thermal conductivity k, electrical conductivity σ and Seebeck coefficient S) as well as the geometry parameters (i.e., pillar height and filling factor) on the q-h characteristic curve are theoretically and experimentally investigated, respectively. TEC modules with higher zT, short pillars and high filling factor show stronger capability to handle high heat flux load, especially for the cases with high heat dissipation coefficient at hot side. The thermal property (k) and electrical properties (σ and S) are responsible for the low heat flux load (e.g., wearable TEC) and high heat flux load (e.g., on-chip TEC cooling), respectively. For wearable TEC, increasing the internal thermal resistance can prevent the back flow heat, which can be achieved with tall pillars, low filling factor and optimizing zT towards lowering thermal conductivity k. For on-chip TEC cooling, reducing the Joule heating and increasing the thermoelectric effect become dominant factors in lowering the code-side temperature of TEC modules. This can be achieved with short pillars, high filling factor and optimizing zT towards increasing the power factor S2σ. This work provides significant insights into the complex interplay between material-level properties, device-level parameters and the external thermal circumstance in determining the performance of TEC devices. The results enable researchers to design optimal TEC devices for realistic applications with different boundary conditions.

Upgrading the dynamic mathematical model of temperature sensors in gaseous media for low Biot number (Bi < 0.1)

A mathematical model incorporating the transient response of NTC thermistors is presented. The internal thermal conduction resistance of the sensor relative to the thermal convection resistance of the medium results in a low Biot number Bi<0.1, yielding a fast dynamic response in gaseous media. This is advantageous in applications requiring minimal fluid interaction. However, negligible energy exchanges occur, introducing measurement uncertainty and ignoring the behavior of the measuring instrument. Therefore, this work proposes an improvement strategy for the mathematical model of these sensors, complementing the conventional model based on the concept of time constant. The strategy considers the heat flow through the thermistor wires in the energy balance, assuming they are semi-infinite solids and applying an approximation to the heat flow formula. Satisfactory improvement results were obtained compared to the conventional model, based on controlled laboratory tests with various gases.

Internal Temperature Estimation of Lithium Batteries Based on a Three-Directional Anisotropic Thermal Circuit Model

In order to improve the accuracy of internal temperature estimation in batteries, a 10-parameter time-varying multi-surface heat transfer model including internal heat production, heat transfer and external heat transfer is established based on the structure of a lithium iron phosphate pouch battery and its three directional anisotropic heat conduction characteristics. The entropy heat coefficient, internal equivalent heat capacity and internal equivalent thermal resistance related to the SOC and temperature state of the battery were identified using experimental tests and the least square fitting method, and were then used for online calculation of internal heat production and heat transfer in the battery. According to the time-varying and nonlinear characteristics of the heat transfer between the surface and the environment of the battery, an internal temperature estimation algorithm based on the square root cubature Kalman filter was designed and developed. By iteratively calculating the estimated surface temperature and the measured value, dynamic tracking and online correction of the internal temperature of the battery can be achieved. The verification results using FUDS and US06 dynamic working condition data show that the proposed method can quickly eliminate the influence of initial temperature deviations and accumulated process errors and has the characteristics of a high estimation accuracy and good robustness. Compared with the estimation results of the adaptive Kalman filter, the proposed method improves the estimation accuracy of FUDS and US06 working conditions by 67% and 54%, respectively, with a similar computational efficiency.

A study on novel dual-functional photothermal material for high-efficient solar energy harvesting and storage

The solar-heat storage efficiency of devices based on phase change materials (PCMs) is limited due to the light absorption and internal heat transfer within the PCMs, unclear thermal conductivity-enhancement mechanism within nanocomposite PCMs, and uncontrollable photothermal-interface modulation. Therefore, a novel controllable strategy was proposed in this study to fabricate dual-functional photothermal storage three-dimensional (3D) phase change blocks (PCBs) with higher thermal conductivity (27.98 W/m·K) and spectral absorption (98.03 %) compared to those of most previously reported PCM-based devices. The as-synthesized PCBs contained millimeter-sized graphite plates with horizontal Van der Waals bonds and oriented micro/nanoscale graphite nanosheets. The structural properties of thin PCM layers between the PCB sheets have synergistically reduced the internal interfacial thermal resistance of the PCBs. Laser-controllable induction was used to fabricate integrated biomimetic-forest 3D optical absorbers on the high thermal conductivity interface of the PCBs, which significantly reduced the thermal resistance of the optical-thermal interface. The resulting 3D-PCBs, integrated with thermoelectric generators, powered portable electronic devices, expanding the applications of traditional PCM heat-storage devices. Therefore, this study will guide the future design of high-performance solar-thermal storage PCMs with a wide range of practical applications.

An improved methodology for thermal calculation and design optimization of a thermosiphon waste heat boiler for CCPP

The study is dedicated to enhancing design and computational methodologies for thermosiphon waste heat boilers (WHB) within combined cycle power plants (CCPP). The optimized WHB design and an improved thermal calculation approach are shown. The efficiency of the proposed WHB has been improved by optimizing the area and arrangement of the surface. The novel method incorporates considerations for the internal thermal resistance within thermosyphons and the graded velocity of natural circulation within the evaporation circuit. To refine the calculation method, empirical and experimental data concerning internal temperature gradient in thermosiphon functioning within a heat load spectrum of up to 17 kW/m2, were used. Important findings include three categories. Firstly, increasing the number of sections will slightly increase capital costs and decrease WHB gas temperature, which could be neglected by the unification of thermosiphon sections. Secondly, by applying this modified methodology to a power plant facility featuring a 6700 kW gas turbine engine (GTE), notable adjustments in thermal power were realized, amounting to 157 kW (approximately 6 %), along with corresponding electrical power adjustments of 149 kW (approximately 2 %). Third, the new method is limited to a GTE power of up to 10 MW due to the experimental data used for validation.

Advanced machine learning techniques: Forecasting thermal resistance in borehole heat exchanger system through RSM and hybrid DFNN-GA approaches

The thermal efficiency of ground heat exchanger (GHEs) relies on optimizing borehole thermal resistance and total internal thermal resistance for cost-effective and efficient design. This study aims to establish a robust correlation among various parameters, including thermal conductivity of pipe, grout, and ground, borehole depth, borehole and pipe diameter, pipe-pipe distance, fluid velocity, and heat transfer rate of the ground, with the 3D borehole thermal resistance (Rb,3D) and total internal thermal resistance (Ra,3D). This exploration of eight influential factors results in an l-130 design matrix with 130 data points. A 3D computational model, utilizing a four-resistance method, accurately calculates Rb,3D and Ra,3D, while analyzing heat transfer in both solids and fluids. Two prediction models, Response Surface Methodology (RSM) and a hybrid Deep Feedforward Neural Network-Genetic Algorithm (DFNN-GA), establish the correlation between Rb,3D and Ra,3D and the eight variables. The results highlight the efficacy of the prediction models, achieving R2 values of 79.87% and 87.90% for RSM and 94.00% and 99.15% for DFNN-GA, corresponding to the predictive accuracy of Rb,3D and Ra,3D, respectively. Furthermore, lower RSME, MAE, and AARE values are observed. A rigorous comparative analysis assesses the relative effectiveness of these methodologies in achieving the research goals.

Quasi-2D thermal network based heat soakage model for gas turbine transient performance modification

To overcome the limitations of traditional heat soakage analysis, a novel quasi-2D thermal network based heat soakage model is established with the consideration of component internal thermal resistance, combustor temperature profile, cooling technologies and thermal barrier coating. The method has been integrated into Turbomatch, a gas turbine performance software developed by Cranfield University, to offer a more realistic estimation of the heat soakage effect during the gas turbine transient manoeuvre. The accuracy of the heat soakage model has been validated against results obtained from GasTurb. Furthermore, a parametric analysis has been conducted to evaluate the effects of combustor temperature profile, cooling technologies, and thermal barrier coating. It is found that the combustor temperature profile will cause a significant increase in heat flow rate, which is approximately four times the conventional lumped parameter method based model. The implementation of cooling technologies and thermal barrier coating will reduce the heat flow rate by 48.97%. More importantly, the change in heat flow rate causes a further delay in engine transient response. Corrected rotational speed was decreased by 0.89%, and thrust was reduced by 2.24%. Moreover, a delay of 8s (233% increase) in the transient acceleration time was found when comparing the quasi-2D thermal network based heat soakage model with the traditional lumped parameter method based model. These highlight the significance of accurately evaluating the heat soakage effects during gas turbine transient simulation.

High thermal conductivity in three-dimensional BN/epoxy composites by engineered favorable interfacial adhesion between BN sheets

Because of their excellent insulation performance and processing properties, polymers are widely used in electrical and electronic applications. However, their further applications are severely constrained by their extremely low intrinsic thermal conductivity. Boron nitride (BN), which has high thermal conductivity and ideal insulation properties, is commonly used as a filler for improving the thermal conductivity of polymers. However, the high chemical inertia of the surface of BN makes it difficult to achieve an interconnection of BN sheets when building a three-dimensional (3D) BN skeleton in a polymer. In this study, urea melt pore preparation (UMPP) was used to fabricate a 3D BN skeleton. Urea was infiltrated into the BN skeleton to minimize the interfacial thermal resistance among the BN flakes and to join BNs. When the volume of a BN is 10 %, the thermal conductivity of the BN/epoxy composites is 3.15 W/(m·K). When the BN volume is 80 %, the thermal conductivity of BN/epoxy can reach 13.65 W/(m·K), which is 6500 % of pure epoxy resin. Additionally, the skeleton exhibits a remarkable mechanical strength capable of supporting weights up to 50,000 times its own, which facilitates easier handling and operation. The electrical resistivity volume of the UMPP composite is as high as that of the pure epoxy, whereas the dielectric loss is lower than that of pure epoxy. This study provides a new method for reducing internal interface thermal resistance of a skeleton formed by thermal conductive fillers with high chemical inertia such as boron nitride.

CFD-DEM coupled simulation of fluidized beds with improved lumped formulation for heat transfer

PurposeThis paper aims to present a novel approach for computing particle temperatures in simulations coupling computational fluid dynamics (CFD) and discrete element method (DEM) to predict flow and heat transfer in fluidized beds of thermally thick spherical particles.Design/methodology/approachAn improved lumped formulation based on Hermite-type approximations for integrals to relate surface temperature to average temperature and surface heat flux is used to overcome the limitations of classical lumped models. The model is validated through comparisons with analytical solutions for a convectively cooled sphere and experimental data for a fixed particle bed. The coupled CFD-DEM model is then applied to simulate a Geldart D bubbling fluidized bed, comparing the results to those obtained using the classical lumped model.FindingsThe validation cases demonstrate that ignoring internal thermal resistance can significantly impact the temperature in cases where the Biot number is greater than 0.1. The results for the fixed bed case clearly demonstrate that the proposed method yields significantly improved outcomes compared to the classical model. The fluidized bed results show that surface temperature can deviate considerably from the average temperature, underscoring the importance of accurately accounting for surface temperature in convective heat transfer predictions and surface processes.Originality/valueThe proposed approach offers a physically more consistent simulation without imposing a significant increase in computational cost. The improved lumped formulation can be easily and inexpensively integrated into a typical DEM solver workflow to predict heat transfer for spherical particles, with important implications for various industrial applications.

Precise Electrical Machine Stator Winding Modeling for Thermal Analysis of Efficient Cooling Concepts

&lt;div&gt;The current development of electric and hybrid electric vehicles has drawn more attention toward the development of electrical machines with high power densities. Though highly efficient, these machines heat up significantly during operation. By design, state-of-the-art water jacket cooling concepts remove the heat mainly through high internal thermal resistances of the electrical machine. The resulting maximum temperatures in the end winding region limit the achievable machine power output. In this study, alternative cooling concepts are presented, which efficiently use the existing heat conduction paths of an electric machine. For this purpose, two modeling methods for the stator windings were developed: a high-resolution approach that considers each individual wire and an abstract approach that uses zones of constant anisotropic thermal conductivity to specify the heat flow in the windings. Both models were used in conjugate heat transfer simulations of a long-term thermal test of the electrical machine integrated in the BMW i3. For both models the validation showed a very good agreement of simulated and measured temperatures. An evaluation of both methods showed the abstract approach to be more efficient than other simulation methods used in the current R&amp;amp;D. Its application for alternative cooling concepts revealed the necessary heat transfer coefficients at different fluid temperatures for a sole convective cooling of the end windings. However, it could be found that a homogeneous temperature distribution in the stator of the machine can only be achieved if a combination of water jacket cooling and convective end winding cooling is used.&lt;/div&gt;

Synergistic improvement of Seebeck coefficient and power density of an aqueous thermocell using natural convection for low-grade heat utilization

As a cutting-edge heat-to-electricity technology, thermocells possess the advantages of large Seebeck coefficient, low cost and high scalability, indicating a great prospect in low-grade heat recovery. Previous studies about thermocells focus on the electrode materials and electrolytes, but the internal heat and mass transfer mechanisms are less considered, especially the effects of natural convection on the performance of aqueous thermocells. The purpose of this study is to explore the influence of natural convection on the performance of aqueous thermocells. Firstly, a fundamental test bench for aqueous ferricyanide/ferrocyanide ([Fe(CN)6]3−/4-) thermocells using Pt as electrodes is designed and established. Based on the self-developed test bench, then the performance of thermocells related to electrode orientation θ are experimentally investigated under typical thermal boundary conditions, including the constant electrode temperature, and constant heating and cooling temperature. The experimental results under constant electrode temperature show that natural convection can significantly reduce the internal resistance of thermocells. The thermocell obtains the largest |Se| of 1.75 mV/K at θ = 90°, which is 19.9% higher than that of θ = 0°. Meanwhile, the thermocell achieves the maximum power density of 0.211 W/m2 at θ = 135°, which is 744% higher than that of θ = 0°. In addition, by combining the experimental results under constant heating and cooling temperature, it can be observed that natural convection can also sharply reduce the thermal resistance and then lead to a smaller temperature difference of two electrodes. Overall, natural convection has trade-off effects on internal resistance and thermal resistance, and the proper use of natural convection can succeed in prominent improvement of Seebeck coefficient and power density for thermocells.

Human body heat-driven thermoelectric generators as a sustainable power supply for wearable electronic devices: Recent advances, challenges, and future perspectives

Thermoelectric generators are devices that directly convert heat flux or the temperature difference between two hot and cold surfaces into electricity. With the advancement of the Internet of Things (IoT) technology and the development of wearable and portable devices, the issue of providing a sustainable power source is one of the main challenges in the development path of these tools. Creating electric power by harvesting the waste heat from the human body is one of the effective solutions in this way. For this reason, the development and improvement of the technology of wearable thermoelectric generators have received much attention recently. Due to the low-temperature difference between the two sides of wearable thermoelectric generators and the high thermal resistance between the skin and the heated surface of these modules, the performance of these systems is highly dependent on their structural parameters and environmental factors. In this paper, it has tried to review all the previous studies regarding the impact of structural factors (such as the matching of internal and external thermal resistances, geometrical parameters of the module, design of heat source and sink, and flexibility of thermoelectric module) and environmental parameters (including the effect of ambient air temperature and humidity, skin temperature, and the interaction of power consumers with thermoelectric modules). Based on the studies, it seems that in optimizing the performance of wearable thermoelectric generators (WTEGs), it is necessary to consider the effect of the human body's thermoregulatory responses, such as skin temperature and sweating rate. The change in skin temperature directly affects the performance of WTEGs, and the change in sweating rate can also affect the thermal resistance between the skin and the hot plate and overshadow the matching of thermal resistances during operation.

UNSTEADY OVERALL THERMAL RESISTANCES RELATED TO HEAT CONDUCTION FOR POROUS MEDIA HAVING HIGH BIOT NUMBERS

This study examines the means of determining the unsteady overall heat transfer coefficients for porous media with high Biot numbers. Changes in temperature during the cooling process are estimated using numerical simulations. In addition, the unsteady volume averaged internal thermal resistance values related to heat conduction in porous materials are obtained over the range of thermal conductivity ratios from 0.01 to 1000. A novel formula for calculation of the volume averaged internal thermal resistance for porous materials is devised as the functions of the Biot number and the Fourier number. This model is validated by comparing the outlet temperatures obtained using numerical simulations. The superiority of this newly developed model is also confirmed by comparison with a conventional approach. The new model can reproduce the unsteady temperature development in porous media having Biot numbers ranging from 0.01 to 100. It shows that this newly developed model can be applied in a wider range of Biot numbers than the conventional approach.

Cooling of an infinite rectangular plate with an adibatically insulated side

The work is devoted to the issues of non-stationary heat transfer. The article presents a solution for the distribution of the temperature field in an infinite rectangular plate with an adiabatically isolated side. As a result, an analytical expression of the plate temperature distribution is obtained in the form of a series containing trigonometric and exponential functions. The paper also considered special cases when the internal thermal resistance of thermal conductivity is greater and when the external resistance of heat output is less. Special cases were interpreted physically. One of the special cases leads the problem to a problem with boundary conditions of the first kind, when the surface temperature is constant, which indicates the reliability of the results obtained.

Thermal management and optimization of the reactor geometry for adsorbed natural gas storage systems subjected to free convection and radiative environment

The present investigation explores the effects of the reactor geometry (i.e., the aspect ratio of cylindrical and annular reactors with and without fins, fin spacing, the aspect ratio of fins for finned reactors, and outer to inner diameter ratio for annular unfinned reactors) on the heat and mass transfer characteristics of the adsorbed natural gas storage system employing passive cooling techniques. The authors try to capture how the geometric modification changes the surrounding buoyancy-driven flow physics and improves the proposed novel reactor's storage performance. The study also considers surface radiation, which significantly improves the heat transfer rate, especially for the reactor with lower internal thermal resistance. An attempt is made to reduce the internal thermal resistance of the adsorbent bed by adding 10% graphite by mass and suitably modeling the bed's thermal conductivity and thermal capacity. The result shows that, in terms of adsorbed amount and heat transfer rate, the reactors with an aspect ratio (AR) of 7.8 outperform the other aspect ratios. The simultaneous effects of reactor aspect ratio and fins spacing on the heat transfer and adsorption rates are expounded, and the optimum fin spacing as a function of reactor aspect ratio and diameter ratio (i.e., fin diameter to reactor diameter) is obtained. The best annular reactor outperforms the cylindrical reactor with and without fin in terms of volumetric and gravimetric storage capacity. The annular finned reactor achieves a maximum 33% improvement in storage capacity compared to the adiabatic case and isothermal efficiency of 90%.

On the influence of environmental boundary conditions on surface thermal resistance of walls: Experimental evaluation through a Guarded Hot Box

In this work, a Guarded Hot Box (GHB) was employed to evaluate the effects of environmental boundary conditions on the internal surface thermal resistance of a wall. For this purpose, the study was carried out through an experimental setup to measure temperature - surface and ambient - in the two chambers of the GHB and air velocity near the specimen wall in the hot chamber. The experimental analysis together with the analysis of the dimensionless parameters allowed to determine the internal convective coefficient for different air speeds. To evaluate the results obtained with the proposed methodology, some existing correlations for the determination of the convective coefficient were used. Moreover, the measurement of the emissivity of sample surface and baffle, and the determination of the mean radiant absolute temperature allowed to calculate the radiative coefficient. Therefore, the internal surface thermal resistance with different air velocities, given by the combination of convective and radiative heat transfer, was determined, and compared with the value offered by the standard ISO 6946. • Influence of environmental boundary conditions on walls surface thermal resistance. • Assessment of the convective heat transfer in function of the air speed through GHB. • Comparison between experimental data and conventional values provided by ISO6946.

Machine learning enabled condensation heat transfer measurement

Measuring condensation heat transfer and its associated heat transfer coefficient is not trivial. Rigorous measurements require careful experimental design and tradeoff studies to properly select sensor type, sample geometry and size, coolant fluid and flow rate, operating conditions, working fluid purity, purge methodology, and measurement protocol. Conventional tube-based condensation heat transfer measurements quantify the change in the enthalpy of a single-phase coolant flow via measurement of the inlet and outlet bulk coolant temperatures. The uncertainties associated with this classical and well-established experimental method are high. The high uncertainty stems from the high characteristic heat transfer coefficient or heat flux associated with the condensation process, making the thermal resistance on the external tube side typically on the same order of magnitude as the internal single-phase coolant convective heat transfer thermal resistance. Even when taking the utmost care and using extremely accurate sensors having low uncertainty, the relative uncertainties of heat flux and heat transfer coefficient can be in the range of 20% to 100%. Here, we take advantage of machine learning (ML) to develop an optical visualization method for dropwise condensation heat transfer characterization. Using state-of-the-art intelligent vision, we demonstrate a previously-unexplored method for characterizing the condensate droplet shedding frequency, droplet shedding size, and heat flux without the need for high-speed imaging. We verify our technique by conducting rigorous steam condensation measurements on Parylene C coated smooth copper tube samples having 500 nm, 1 μm, and 5 μm Parylene C thicknesses. We validate our ML predictions with data obtained simultaneously using the enthalpy-change method on a custom and well-established condensation chamber. In contrast to conventional heat transfer measurement methods, the uncertainty of our ML method is constant (∼10%) and does not vary with heat flux. We finally demonstrate the key advantage of our ML measurement technique on a custom-made tube having axially varying surface properties resulting in differing local heat transfer coefficient. Our ML heat transfer measurement method enables the high fidelity characterization of phase change heat flux, reduction in relative measurement uncertainty, resolution of local effects, and elimination of the need for temperature measurement across samples.

Nonequilibrium Phonon Thermal Resistance at MoS2/Oxide and Graphene/Oxide Interfaces

Accurate measurements and physical understanding of thermal boundary resistance (R) of two-dimensional (2D) materials are imperative for effective thermal management of 2D electronics and photonics. In previous studies, heat dissipation from 2D material devices was presumed to be dominated by phonon transport across the interfaces. In this study, we find that, in addition to phonon transport, thermal resistance between nonequilibrium phonons in the 2D materials could play a critical role too when the 2D material devices are internally self-heated, either optically or electrically. We accurately measure the R of oxide/MoS2/oxide and oxide/graphene/oxide interfaces for three oxides (SiO2, HfO2, and Al2O3) by differential time-domain thermoreflectance (TDTR). Our measurements of R across these interfaces with external heating are 2-4 times lower than the previously reported R of the similar interfaces measured by Raman thermometry with internal self-heating. Using a simple model, we show that the observed discrepancy can be explained by an additional internal thermal resistance (Rint) between nonequilibrium phonons present during Raman measurements. We subsequently estimate that, for MoS2 and graphene, Rint ≈ 31 and 22 m2 K GW-1, respectively. The values are comparable to the thermal resistance due to finite phonon transmission across interfaces of 2D materials and thus cannot be ignored in the design of 2D material devices. Moreover, the nonequilibrium phonons also lead to a different temperature dependence than that by phonon transport. As such, our work provides important insights into physical understanding of heat dissipation in 2D material devices.

Thermal resistance modeling of flat plate pulsating heat pipes

Flat plate pulsating heat pipes (FP-PHP) represent a future technology, enabling a more efficient thermal management of high heat flux devices. Whereas established thermal resistance models exist for wicked heat pipes, there are no such comprehensive models for pulsating heat pipes. In this paper, a conduction-based approach for pseudo-steady heat transfer is presented which can be used for 3D thermal simulations. For the calculation of the internal thermal resistance, multi-fluid correlations for flow boiling and condensation are utilized. A saturated homogenized state in-channel is assumed which allows the temperature-dependent determination of thermophysical fluid properties. A good agreement for the external temperature field was achieved compared to two independent experiments. The simulations show a significant sensitivity to the condenser conditions. Interestingly no adiabatic zone exists along the channels. Furthermore, it is shown that consideration of thermal spreading effects is key for the interpretation of the overall thermal resistance, effective heat fluxes and the design of optimal FP-PHPs.