bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the rectal‐interdigital temperature gradient as a diagnostic marker of shock in dogs
Authors: Schaefer Jonathan D. , Reminga Christin L. , Reineke Erica L. , Drobatz Kenneth J. 
Published: September 2020

AbstractObjectiveTo evaluate the difference in the rectal‐interdigital temperature gradient (RITG) between dogs that were presented to an emergency room with clinical signs of shock compared to those without signs of shock, and if this gradient can be used as a diagnostic marker for shock.DesignProspective, single center, observational study conducted from 2014 to 2015.SettingUniversity veterinary teaching hospital.AnimalsTwenty dogs with a clinical diagnosis of shock and 60 dogs without a clinical diagnosis of shock (controls).Measurements and main resultsUpon presentation to the emergency room and prior to intervention, measurements of rectal temperature, interdigital temperature, ambient temperature, systemic markers of perfusion (capillary refill time [CRT], heart rate [HR], respiratory rate [RR], Doppler blood pressure [DBP], and venous plasma lactate concentration), and venous blood gas analytes were recorded. Dogs were initially determined to be in shock by the attending clinician, and post hoc inclusion criteria were applied. Shock was defined as abnormalities in ≥3 of the 6 following criteria: HR > 120/min, RR > 40/min, CRT > 2 seconds, rectal temperature <37.8°C (100.0°F), venous plasma lactate concentration >2.5 mmol/L, or DBP < 90 mm Hg. Animals with circulatory shock had a significantly increased RITG. An increased RITG was also correlated with individual perfusion parameters including prolonged CRT (ρ = .353, P = 0.0013), tachycardia (ρ = .3485, P = 0.0015), decreased DBP (ρ = –0.6162, P = 0.0003), and shock index (ρ = 0.6168, P = 0.0003). Receiver operator curve analysis indicated a RITG cutoff point of 11.6°F had 90% specificity for the diagnosis of shock (area under the curve = 0.7604).ConclusionsThe RITG in this study was associated with a diagnosis of shock and therefore may serve as a diagnostic marker of circulatory shock. Future studies with larger sample sizes to validate the use of temperature gradients and other peripheral perfusion abnormalities as diagnostic and monitoring tools are warranted.
Investigation of Supercritical Flow and Shape of Flip Bucket Spillways on Coefficients of Dynamic Pressure
Authors: Vatandoust Hessam , Yarmohammadi Hamidreza , Kavianpour Mohammadreza 
Published: September 2020

Abstract
Pressure fluctuation is one of the major turbulent flow characteristics. It may cause crucial problems for hydraulic structures. This research is based on experimental studies, and it focuses on the measurements of pressure fluctuations along flip bucket spillways with different geometrical characteristics. The function of the flip bucket spillway is discharging floods from reservoir dams which are energy storage source measurements of dynamic pressures on three different models of flip buckets that were performed for this investigation. Pressure fluctuation of the flip buckets have been measured within a range of Froude numbers from 5 to 13 (Fr = u/gy, where u is the flow speed, y is the depth, and g is 9.81 m/s2). Statistical characteristics of pressure fluctuations, the location, and the values of maximum and minimum fluctuations have also supplemented the study. The results show that the coefficients of pressure fluctuations (Cp = RMS/(0.5(u2/g)) where RMS is the root-mean-square of pressure fluctuation, u is the flow speed, and g is 9.81 m/s2) reduce as the Froude number (Fr) of flow increases, except a maximum Froude number. Pressure coefficients increase along the flip bucket with incremental mutations in the transformation area of the flip bucket. In the middle part of the flip bucket spillway, pressure coefficient values decrease. Additionally, as B/r (B is the width of the flip bucket and r is the radius of the flip bucket) ratio increases, pressure coefficients become larger and this process continues along the flip bucket.
Assimilation of Experimental Data to Create a Quantitatively Accurate Reduced-Order Thermoacoustic Model
Authors: Garita Francesco , Yu Hans , Juniper Matthew P. 
Published: September 2020

Abstract
We combine a thermoacoustic experiment with a thermoacoustic reduced order model using Bayesian inference to accurately learn the parameters of the model, rendering it predictive. The experiment is a vertical Rijke tube containing an electric heater. The heater drives a base flow via natural convection, and thermoacoustic oscillations via velocity-driven heat release fluctuations. The decay rates and frequencies of these oscillations are measured every few seconds by acoustically forcing the system via a loudspeaker placed at the bottom of the tube. More than 320,000 temperature measurements are used to compute state and parameters of the base flow model using the Ensemble Kalman Filter. A wave-based network model is then used to describe the acoustics inside the tube. We balance momentum and energy at the boundary between two adjacent elements, and model the viscous and thermal dissipation mechanisms in the boundary layer and at the heater and thermocouple locations. Finally, we tune the parameters of two different thermoacoustic models on an experimental dataset that comprises more than 40,000 experiments. This study shows that, with thorough Bayesian inference, a qualitative model can become quantitatively accurate, without overfitting, as long as it contains the most influential physical phenomena.
Laboratory Assessment of a Headband-Mounted Sensor for Measurement of Head Impact Rotational Kinematics
Authors: Huber Colin M. , Patton Declan A. , Wofford Kathryn L. , Margulies Susan S. , Cullen D. Kacy , Arbogast Kristy B. 
Published: September 2020

Abstract
Head impact sensors measure head kinematics in sports, and sensor accuracy is crucial for investigating the potential link between repetitive head loading and clinical outcomes. Many validation studies mount sensors to human head surrogates and compare kinematic measures during loading from a linear impactor. These studies are often unable to distinguish intrinsic instrumentation limitations from variability caused by sensor coupling. The aim of the current study was to evaluate intrinsic sensor error in angular velocity in the absence of coupling error for a common head impact sensor. Two Triax SIM-G sensors were rigidly attached to a preclinical rotational injury device and subjected to rotational events to assess sensor reproducibility and accuracy. Peak angular velocities between the SIM-G sensors paired for each test were correlated (R2 &gt; 0.99, y = 1.00x, p &lt; 0.001). SIM-G peak angular velocity correlated with the reference (R2 = 0.96, y = 0.82x, p &lt; 0.001); however, SIM-G underestimated the magnitude by 15.0% ± 1.7% (p &lt; 0.001). SIM-G angular velocity rise time (5% to 100% of peak) correlated with the reference (R2 = 0.97, y = 1.06x, p &lt; 0.001) but exhibited a slower fall time (100% to 5% of peak) by 9.0 ± 3.7 ms (p &lt; 0.001). Assessing sensor performance when rigidly coupled is a crucial first step to interpret on-field SIM-G rotational kinematic data. Further testing in increasing biofidelic conditions is needed to fully characterize error from other sources, such as coupling.
A Comparative Study Between Two-Dimensional and Three-Dimensional Simulation Results of Melting Inside a Container
Authors: Hu Nan , Fan Li-Wu 
Published: September 2020

Abstract
Bother two-dimensional (2D) and three-dimensional (3D) simulations on two example melting problems, i.e., melting in a differentially-heated rectangular cavity and constrained melting in a horizontal cylindrical capsule, were carried out to investigate the rationality of 2D simplification. The effects of thermophysical properties of the phase change material, size of the container along the direction perpendicular to the 2D cross-section, as well as wall superheat were taken into consideration for a systematic and detailed comparison. It was shown that a small length of the container perpendicular to 2D plane will result in a confine space to limit the development of velocity distribution (i.e., parabolic velocity profile) due to the end effects, leading to to an almost identical melting rate to that obtained by the 2D simplified case. A larger size indicates stronger thermal convection (bulk uniform velocity profile) and faster melting rate. When fixing a large size of the container perpendicular to the 2D plane, decreasing the heating temperature and increasing the viscosity of liquid PCM (e.g., by adding nanoparticles) reduce the discrepancy between 2D and 3D simulation results.
Comparative Study of Heat Transfer in a Mini/Micro Pipe With Water and Liquid Metal As Fluid
Authors: Zhang Xu-Dong , Gao Jian-Ye , Liu Jing 
Published: September 2020

Abstract
Recently, the new research field of room temperature liquid metal cooling for extreme heat flux electronic devices has gradually attracted much attention. And many investigations claimed that liquid metal cooling has a better heat transfer performance than water cooling. However, such a conclusion was just applicable to the special geometry sizes. This paper is dedicated to deeply interpret and systematically compare the laminar heat transfer in a mini/micro pipe with water and liquid metal as heat transfer fluid. Theoretical analysis for the laminar fully developed segment and numerical investigation for the laminar developing segment were conducted. The results indicated that liquid metal galinstan shows a better heat transfer performance in mini-pipe. And the shorter the pipe, the better performance the liquid metal cooling has. However, when the velocity is small, the galinstan cooling is worse than water cooling in micro-pipe. Moreover, based on thermal resistance analysis, the general criterion equation for laminar developed segment was derived to judge which cooling method possesses a better heat transfer performance. Overall, this comparative study provides a comparison method and criterion about liquid metal cooling and water cooling, which will attribute to the coolant selection and heat sink design.
Thermal Performance of Sensible Energy Storage Module Consisting of a Cementitious Matrix: The Effect of Operating Conditions
Authors: Caspar Justin , Bravo Julio , Wang Shuoyu , Abdulridha Ahmed , Neti Sudhakar , Romero Carlos , Naito Clay , Sulieman Muhannad , Quiel Spencer , Yao Zheng , Oztekin Alparslan 
Published: September 2020

Abstract
The fluid flow and heat transfer inside a concrete thermal energy storage module is simulated for various heat transfer fluid flow rates and inlet temperatures. The storage performance of the module is characterized based on the volume-averaged temperature and normalized energy distribution through the block versus time. In the turbulent flow regime, induced mixing in the pipe strongly enhanced the performance of the module compared to the laminar regime. The block was able to fully charge and discharge in a turbulent flow regime, whereas that behavior was not present in the laminar flow regime.
Varying the heat transfer temperature had an effect on the time rate of change of temperature as well as the charge times. As the thermal gradient increased, the initial time rate of temperature in the block increased as well as the charge time. Since the block has higher theoretical energy at a larger gradient, power over a longer duration is necessary to reach a saturation point. By characterizing the thermal performance of the module, the effect of material properties and operational parameters can be studied in order to design a module that can meet the needs of a power generation plant.
Condensation and Evaporation Heat Transfer Characteristics in Horizontal Smooth and Three-Dimensional Enhanced Tubes
Authors: Zhang Jianghui , Guo Yu , Zhang Chuancai , He Yan , Kukulka David J. , Li Wei 
Published: September 2020

Abstract
An experimental investigation of condensation and evaporation heat transfer characteristics was performed in a smooth tube and two enhanced tubes (1EHT, 3EHT) using R134A as refrigerant. All tested tubes have the same inner diameter of 14.68mm and outer diameter of 15.88mm. The enhanced surface of the 1EHT tube is made up by dimples and a series of petal arrays, while that of 3EHT tube is rectangular cavities. The test runs are performed at a saturation temperature of 45°C, over the quality range of 0.8–0.2 for condensation and at a saturation temperature of 6°C, over the quality range of 0.1–0.6 for evaporation. For evaporation, the heat transfer coefficient ratio (hEHT/hs) is approximately 1.2–1.4 for mass from 50–90 kg/m2s. For condensation, the 1EHT tube provides the best condensation heat transfer performance. This is mainly due to the dimples and rectangular cavities that increase heat transfer surface area and interface turbulence, producing additional disturbances, secondary flows near the boundary and flow separation.
A Multiobjective Parameter Study of Two-Phase Flow Channel Design
Authors: Evich Nicholas A. , Larimer Nicholas R. , Frecker Mary I. , Rau Matthew J. 
Published: September 2020

Abstract
Advanced manufacturing techniques have improved dramatically in recent years and design freedom for engineered components and systems has never been greater. Despite these advancements, the majority of our design tools for thermal-fluids systems are still rooted within traditional architectures and manufacturing techniques. In particular, the complex nature of two-phase flow and heat transfer has made the development of design methods that can accommodate these complex geometries enabled by new manufacturing techniques challenging. Here, we investigate a new design method for two-phase flow systems. We conduct a multiobjective parameter study considering two-phase flow and heat transfer through a single channel with a circular cross section. To increase our design degrees of freedom, we allow the channel to increase or decrease in cross-sectional area along its flow length, but constrain the channel inlet and outlet to a constant hydraulic diameter. Maximizing heat transfer and minimizing pressure drop are the two design objectives, which we evaluate using two-phase heat transfer correlations and the Homogeneous Equilibrium Model. We find that using small expansion angles can greatly reduce two-phase flow pressure drop and also provide high heat transfer coefficients when compared to straight channel designs. We present a set of feasible designs for varying input heat fluxes, liquid mass flow rates, and channel orientation angles and show how the ideal expansion channel angle varies with these operational conditions.
Application of Artificial Neural Network As a Near-Real Time Technique for Solving Non-Linear Inverse Heat Conduction Problems in a One-Dimensional Medium With Moving Boundary
Authors: Najafi Hamidreza , Uyanna Obinna , Zhang Jian 
Published: September 2020

Abstract
Developing accurate and stable solutions for inverse heat conduction problems (IHCPs) is crucial in many industrial applications where direct measurement of surface conditions, such as heat flux or temperature, is not possible in practice and temperature measurement from interior points can be obtained alternatively. IHCPs are mathematically ill-posed and therefore developing stable solutions for them is challenging. Application of intelligent algorithms for solving IHCPs has been successfully explored for several cases. In the present paper, the problem of near real-time surface heat flux estimation in a one-dimensional domain with temperature dependent material properties and moving boundary is considered. An artificial neural network (ANN) is developed to use the temperature measurement data from interior points for limited number of time steps as the inputs and calculate the surface heat flux and recession rate at the current time step as the output of the network. For this purpose, a multi-layer perceptron (MLP) network is selected, trained and tested using heat flux-temperature data that were evaluated via COMSOL Multiphysics for a 1D medium that is exposed to standard heat flux profiles on its surface (including triangular, parabolic and step function). A randomly generated heat flux profile is also applied to the surface of the medium and temperature distribution is calculated via COMSOL Multiphysics. The temperature data are then used as the inputs to the network and surface heat flux is evaluated under this condition to assess the capability of the developed ANN in surface heat flux estimation. The performance of the network when using different number of inputs (previous and future time steps from which temperature data are needed for surface heat flux estimation) as well as different network topology are explored in the presence of random measurement error. The results show that the developed approach allows accurate near real-time surface heat flux estimation in a 1-D medium with temperature dependent material properties and moving boundary. The solution of this problem can be further extended to be used in sensors for ablative thermal protection system in space vehicles.
Use of Genetic Algorithms and Machine Learning to Explore Parametric Trends in Nucleate Boiling Heat Transfer Data
Authors: McClure Emma R. , Carey Van P. 
Published: September 2020

Abstract
Exploring parametric effects in pool boiling is particularly challenging because the dependence of the resulting surface heat flux on many parameters is non-linear, and the mechanisms can interact in complex ways. Historically, parametric effects in nucleate boiling processes have most often been deduced by fitting relations obtained from physical models to experimental data, or looking for correlated trends in non-dimensionalized data. Using such approaches, observed trends are often influenced by the framing of the analysis that results from the modeling or the collection of dimensionless variables used. Machine learning strategies can be attractive alternatives because they can be constructed either to minimize biases or to emphasize specific biases that reflect knowledge of the physics of the system. The investigation summarized here explored the use of machine learning methods as a tool for determining parametric trends in boiling heat transfer data, and as a means for developing methods to predict boiling heat transfer. Results are presented that demonstrate how genetic algorithms and other machine learning tools can be used to extract heat flux dependencies on system parameters. A key element of the machine learning analysis process is preparation of the data used. Use of raw data and use of dimensionless rescaled data are explored, and the advantages and disadvantages of each are assessed. Data for nucleate boiling of a binary mixture are analyzed to determine the heat flux dependence on wall superheat, gravity, Marangoni effects and pressure. The results provide new insight into how gravity and Marangoni effects interact in boiling processes of this type. The results also demonstrate how machine learning tools can clarify how different mechanisms interact in the boiling process, as well as directly providing the ability to predict heat transfer performance for design of heat transfer devices that involve nucleate boiling. Potential use of machine learning tools on big data collections for nucleate boiling processes to more broadly assess parametric effects is also discussed.
Design and Optimization of Microchannel Heat Sink for Densely Packed High Concentration Solar Cells
Authors: M. Ali Abdallah Y. , Abo-Zahhad Essam M. , Radwan Ali , Elqady Hesham I. , El-Kady M. F. , Ookawara Shinichi , El-Shazly A. H. 
Published: September 2020

Abstract
High cell operation temperature causes a significant reduction in cell efficiency. Besides, this high temperature reduces the cell lifespan and physical damages could happen due to thermal stresses. An advanced and efficient cooling scheme is obligatory to operate a high concentration solar module under its recommended operating conditions. The main objective of this work is to design and optimize a microchannel heat sink in terms of channel geometry for high concentration photovoltaic module works under high solar concentration for more efficient and uniform cooling. A complete three-dimensional model for the high concentrator photovoltaic module coupled with the microchannel heat sink is developed. A densely packed high concentration solar module consists of AZURSPACE product triple-junction solar cells (electrical efficiency is 43.2% at a cell temperature of 25 °C) is considered as a heat source in this work. The multi-objective optimization method is adopted to obtain the optimum channel dimensions. Both channel width and height are defined as variable parameters. The optimum design is obtained then its thermal performance is investigated under different working conditions. The results confirmed the ability of the optimized cooling device to offer efficient thermal management and uniform cooling for a densely packed high concentration solar module.
Numerical Investigation of Thermal Properties for Li-Ion Battery
Authors: Wang Xiuling 
Published: September 2020

Abstract
Li-ion battery is becoming a popular energy storage device in Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV) due to its high energy density, high voltage and low self-discharge rate. The major concerns in designing Li-ion batteries are their life, performance and safety, which have close relations to their thermal behaviors. The temperature of Li-ion batteries rises during charge/discharge process. It goes faster especially with high charge/discharge rate during fast charging procedure. In this research, CFD models are developed based on ANSYS/FLUENT MSMD battery model coupled with electrochemical submodel-Newman, Tiedeman, Gu and Kim (NTGK) empirical model. Detailed simulation results are obtained in battery thermal and electrochemical behavior for different bi-cell electrode and current collector tab configurations. The temperature, potential, current density distribution at the battery length scale are determined, temperature gradient distribution is computed, and the maximum temperature at different discharge rate are also compared. The thermal investigation can provide valuable input for Li-ion battery design and analysis, especially for fast-charging batteries where heat distribution and cooling is critical for the battery design.
Numerical Simulation of Heat, Air, and Moisture Transfer Through a Wall of Porous Media
Authors: Tesfamariam Kiflom B. , Lin Cheng-Xian (Charlie) , Liu Fang 
Published: September 2020

Abstract
This paper presents the results of two-dimensional (2D) numerical simulation of heat, air, and moisture transfer through porous walls, which have important application background in the built environment and other engineering fields. The air flows, heat and moisture transfer in the walls are studied using a transient heat, air, and moisture (HAM) model. This model treats the non-isothermal airflow through two-dimensional porous geometries in a time-dependent format. The model includes the Brinkman equation describes the flow of air and other mathematical equations that calculate the heat and moisture transfer through the porous region. The equations are solved by a finite element method (FEM) using physics-based modeling, which is implemented in the commercial simulation software, COMSOL Multiphysics. The model prediction is first validated by using published benchmark solutions. Eventually, the numerical results are presented to illustrate the complex effects of material porosity and permeability on the heat and moisture transport, and moisture content variation in space and time through the walls, at different humidity and temperature conditions. Within the investigated parameter ranges, it is demonstrated that the relative humidity and temperature difference are the driving forces for the transient heat, air, and moisture transport processes through the porous area in the porous walls.