bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of Thermionic Energy Conversion Performance and Parametric Effects Using Genetic Algorithms to Fit Physics-Inspired Model Equations to Prototype Test Data
Authors: Juette Elizabeth D. , Carey Van P. , Fleurial Jean Pierre 
Published: September 2023

Abstract
Several recent studies have generated experimental performance data for narrow-gap thermionic energy conversion devices. This investigation explores the use of genetic algorithm methods to fit existing data from literature with physics-inspired model equations. The resulting model equations can be used for performance prediction for system design optimization, or to explore parametric effects on performance. The model equations incorporate Richardson’s law for current density, including both the saturated and Boltzmann regimes, with appropriate relations for power delivered to the external load. The transition regime is characterized using two separate models, each accounting for non-uniformity in emission surfaces and other irregularities in the manufacturing process that impact the output power density. The trained models enable performance prediction of a small-gap thermionic energy conversion device with inputs of only emitter temperature and load resistance.
The prototype data considered here tested a thermionic energy conversion device to determine the output current and output power as a function of diode voltage and the emitter temperature. In this study, the prototype test data is used with postulated work function for the emitter and the collector materials and two additional parameters to characterize the transition region. As a result, these postulated functions are substituted into the physics-inspired models, yielding performance models with three adjustable constants. Optimized values of these constants are determined using a genetic algorithm to best fit the experimentally determined performance data for prototype thermionic conversion devices tested in earlier studies.
This process yields four insightful results. First, this work demonstrated two pathways to a model that can accurately predict performance trends. The developed models can also be used for design optimization and provide a pathway to a data-driven performance model. The two performance models each provide a method for extracting work function information from performance data. The extracted work function ultimately proves to be independent of the performance model used, as both models produce the same effective work function values for the prototype device. Finally, both of the final three-regime models illuminate the transition region between the saturated and Boltzmann regime.
Analysis of Renewable Energy Integrated Pumped Thermal Energy Storage Systems
Authors: Desai Nishith B. , Parisi Simone , Remygiakis Nikolaos , Haglind Fredrik 
Published: September 2023

Abstract
In this paper, a novel configuration of a pumped thermal electricity storage system is proposed which can integrate excess thermal energy from different renewable thermal energy sources, e.g. concentrated solar power, waste heat and deep geothermal energy plants, as well as excess electricity from direct electricity generating renewable energy sources, e.g. solar photovoltaic and wind energy plants. The proposed configuration can also be used as a retrofit option to existing conventional fossil fuel-based power plants. A conventional two-tank sensible heat storage is used as a thermal energy storage system that can be charged using direct renewable thermal energy and using a heat pump utilizing excess electricity. Different discharging cycles, including a Joule-Brayton system and a conventional steam Rankine cycle system, can be used. The proposed system can achieve a higher capacity factor compared to those of standalone plants.
As a case study, a conventional two-tank molten salt-based thermal energy storage system integrating concentrated solar power, considering a heliostat system, and a solar photovoltaic plant is investigated. The overall operational strategy of the plant was developed and based on that annual simulations were performed for a selected configuration. The results of the case study suggest that for a given requirement of capacity factor, the final selection of the capacities of the solar photovoltaic plant, heat pump and heliostat field should be done based on the minimum levelized cost of energy. Moreover, for high capacity factor requirements, the proposed configuration is promising.
Modelling Development of a Receiver-Reactor of Type R2Mx for Thermochemical Water Splitting
Authors: Vega Puga Estefania , Brendelberger Stefan , Weber Anika , Sattler Christian 
Published: September 2023

Abstract
This work reports on the development of a transient heat transfer model for a prototype reactor of type R2Mx for thermochemical water splitting by temperature and pressure swing of ceria. Key aspects of the R2Mx concept, which are also incorporated in the prototype design, include a movable monolithic redox structure combined with a linear transport system, a reduction reactor as well as a dedicated oxidation reactor. With the model, the operation of the prototype is simulated for consecutive water splitting cycles, in which ceria is reduced in a continuously heated reactor, oxidized in a separate oxidation reactor and transported in between the reaction zones.
A 2D axisymmetric numerical model of the prototype reactor was developed in ANSYS Mechanical. The model includes heat transfer calculations in combination with an approximated simulation of the transport of the redox material during cyclic operation. It incorporates the chemical reaction by means of a modified heat capacity for ceria and accounts for internal radiation heat transfer inside the porous redox material by applying effective heat transfer properties. A parametric analysis has been undertaken to evaluate different modes of operation of the oxidation reactor. Model results are used to size the power demand of the reduction reactor and vacuum pump, to define durations of the process steps as well as to assess operational parameters with respect to achieved temperatures.
Monitoring Perfusion-Based Convection in Cancer Tumor Tissue Undergoing Nanoparticle Heating by Analyzing Temperature Responses to Transient Pulsed Heating
Authors: Carlton Hayden , Korangath Preethi , Arepally Nageshwar , Attaluri Anilchandra , Ivkov Robert 
Published: September 2023

Abstract
The dynamic nature of perfusion in living tissues, such as solid tumors during thermal therapy, produces challenging spatiotemporal thermal boundary conditions. Changes in perfusion can manifest as changes in convective heat transfer that influence temperature changes during cyclic heating. Herein, we propose a method to actively monitor changes in local convection (perfusion) in vivo by using a transient thermal pulsing analysis. Syngeneic 4T1 tumor cells were injected subcutaneously into BALB/c mice and followed by caliper measurements. When tumor volumes measured 150–400 mm3, mice were randomly divided into one of two groups to receive intratumor injections of one of two iron oxide nanoparticle formulations for pulsed heating with an alternating magnetic field (AMF). The nanoparticles differed in both heating characteristics and coating. Intratumor temperature near the injection site as well as rectal temperature were measured with an optic fiber temperature probe. Following heating, mice were euthanized and tumors harvested and prepared for histological evaluation of nanoparticle distribution. To ascertain the heat transfer coefficient from heating and cooling pulses, we fit a lumped capacitance, Box-Lucas model to the time-temperature data assuming fixed tumor geometry and constant experimental conditions. For the first particle set, the injected nanoparticles dispersed evenly throughout the tumor with minimal aggregation, and with minimal change in convection. On the other hand, heating with the second particle generated a measurable decline in convective performance and histology analysis showed substantial aggregation near the injection site. We consider it likely that though the second nanoparticle type produced less heating per unit mass, its tendency to aggregate led to more intense local heating and tissue damage. Further analysis and experimentation is warranted to establish quantitative correlations between measured temperature changes, perfusion, and tissue damage responses. Implementing this type of analysis may stimulate development of robust and adaptive temperature controllers for medical device applications.
Approaches for Phenomenological Studies in Nucleate Boiling Using a Laser-Based Controlled Bubble Generation Technique
Authors: Dhillon Navdeep Singh , Choudhary Dilipkumar , Maree Jayden 
Published: September 2023

Abstract
Despite its importance in many industries, several important aspects of the nucleate boiling phenomenon remain poorly understood due to its inherent complexity and due to the statistical nature of heterogeneous bubble nucleation. This lack of understanding prevents meaningful progress in the enhancement of boiling performance parameters such as the heat transfer coefficient and the critical heat flux. To enable parametric phenomenological boiling studies, we present a laser-based controlled bubble generation technique that can produce spatially and temporally controlled bubbles representative of bubbles in actual nucleate boiling. We propose several phenomenological studies in boiling that can be undertaken using this approach to promote a mechanistic understanding of and enhancement in the boiling performance parameters.
Study on Ensemble Kalman Filter Based Building Fire Prediction and Dynamic Situation Awareness for Emergency Response
Authors: Kou Luyao , Wang Pei , Ba Rui , Liu Jiaming , Deng Qing , Zhang Hui 
Published: September 2023

Abstract
Numerical models provide detailed information of situation in buildings during a fire. But the models can have unsatisfactory practical performance for emergency response, due to model defects and deviations of pre-set input parameters. Data assimilation methods for error mitigation have shown great performance improvement by combining real-time measurements with fire models. However, these methods cannot revise the simulation effectively when there are obvious systematic errors between fire model and sensor readings. Ensemble Kalman filter (EnKF) is one of classical data assimilation methods. In this paper, a decentralized EnKF-based fire prediction method is proposed for the dynamic situation awareness in building fires. Individual EnKF-based fire model is established for each substructure of a building. The proposed method is less affected by systematic error of the fire model. Based on the EnKF predictions, important information of smoke and fire hazard are extracted and a fire hazard mapping is created for first responders. The multi-compartment case study validates the effectiveness of the EnKF-based fire prediction and dynamic situation awareness for emergency response.
Electron-Phonon Interactions for Nanoscale Energy Transport Simulations in Semiconductor Devices
Authors: Medlar Michael P. , Hensel Edward C. 
Published: September 2023

Abstract
An ideal semiconductor device would permit unimpeded flow of electrons from its source to its drain in a fashion that can be switched on and off by its gate at high frequency. Electron flow through real semiconductor devices is impeded by interactions with the crystalline structure of the material. Electrons which interact with the crystal may generate phonons which manifest as thermal energy generation and degrade real device performance from its ideal limit. Accurate simulation of electron-phonon interactions cannot rely on the traditional continuum assumption because of the reduced length and time scales of modern semiconductor devices. Allowable electron-phonon interactions are constrained by the conservation of energy and momentum. Direct enforcement of the conservation laws is achieved through computation of an interaction table that contains thousands of rows each of which representing a conservative interaction. The rows represent both phonon and electron creation and annihilation. The electron and phonon wavevector space is discretized into 65,856 elements and the table is computed by searching the discretized wavevector space for electron and phonon states that first satisfy the conservation of momentum. Subsequently, these states are compared against the conservation of energy using the phonon and electron dispersion relations. Anisotropic phonon dispersion relations were calculated using a second nearest neighbor lattice dynamics approach with interatomic force constants from Density Functional Theory. Electron dispersion relations were computed using an empirical pseudopotential approach. This method was demonstrated for computation of electron-phonon interactions in silicon, resulting in an initial interaction table containing approximately 58,000 interactions. Computation of the electron energies associated with the first conduction band in an anisotropic manner illustrate reasonable agreement with published work. The interaction densities show similar functionality relative to the electron-phonon interaction rate predictions and phonon generation rates from published literature. The interaction table directly enforces the conservation laws on all electron-phonon interactions and the interaction table approach can be used for high fidelity electron-phonon simulations to quantify the mechanism, rate, and location of thermal losses arising at the nanoscale.
Investigation of the Entropy Generation and Exergy Destruction Rates for a Novel Micro-Jet Heat Sink Working With a Nanofluid for Efficient Cooling of Motor Inverters in Electric Vehicles
Authors: Mazaheri Nima , Mwesigye Aggrey 
Published: September 2023

Abstract
Unlike the first law analysis which quantifies energy in systems, the second law of thermodynamics specifies the quality of energy and the direction of the processes. In this research, a novel heat sink based on micro-jet impingement for cooling inverters in electric vehicles is thermodynamically analyzed to establish the entropy generation and exergy destruction rates. The numerical simulations are performed using the finite volume method implemented in ANSYS Fluent. Numerical analyses are performed for typical motor inverter heat fluxes ranging from 100 to 300 W/cm2, Reynolds number between 5,000 and 20,000. Alumina-water nanofluid was considered with nanoparticles at concentrations of 0, 0.008, and 0.017 by volume. Results indicate that the maximum reduction in the thermal entropy generation rate is 6.65% when the nanoparticle concentration rises to 0.017. Whereas the frictional entropy generation rate increases by 73% for the same increase in nanoparticle volume fraction. Despite this, the total irreversibility drops as the concentration rises such that the highest reduction in the total irreversibility is 6.1% since the thermal entropy generation rate is the dominant source of irreversibility. With this, utilizing nanofluids decreases the exergy destruction rate leading to a lower amount of wasted energy. When the concentration is increased from 0 to 0.008 and 0 to 0.017 at a heat flux of 100 W/cm2, the optimal Reynolds numbers for maximum reduction in exergy destruction are 10,000 and 5,000, respectively.
Heat Flux Characterization From a Band Heater to Pipe Using Inverse Heat Conduction Problem Method
Authors: Peruchi Pacheco da Silva Ramon , Woodbury Keith , Samadi Forooza , Carpenter Joseph 
Published: September 2023

Abstract
An experimental apparatus was constructed to correlate water flow rate and temperature rise under an external band heater. Due to physical characteristics of the band heater, its transient heating behavior is unknown. This paper investigates the application of Inverse Heat Conduction Problem (IHCP) methods to characterize the heat flux from the band heater. Three experiments with different heating times (5, 10, and 20 seconds) and no flow rate were conducted to measure the transient temperature under the 400 W band heater. Type T thermocouples measure surface temperature at the centerline of the band heater. The experimental results are computed with five different heat conduction models. The models are chosen to identify how the heat flux response varies from a simplified to a realistic model. Additionally, the results of the experimental heat flux are compared to the manufacturer band heater data (58.9 kW/m2) for each model. The minimum time needed for the heater to fully energize the system is from 10 to 12 seconds. The residuals for each model are analyzed and are used to evaluate the appropriateness of the five different models.
A Numerical Study of Refrigerant Leakage From a Propane-Based Refrigeration System
Authors: Zhang Mingkan , Sharma Vishaldeep , Fricke Brian A. 
Published: September 2023

Abstract
Low Global Warming Potential (GWP) refrigerants, e.g. Propane (R290) (GWP = 3) and R1234yf (GWP = 4), are becoming a popular choice among refrigeration and HVAC systems, such as vending machines and air conditioning. However, most of Low GWP refrigerants are flammable (ASHRAE class A2 or A3), so safety is a very important consideration when designing and deploying low GWP refrigerants-based equipment in buildings. In the event of a refrigerant leak, the flammability of low GWP refrigerants depends on the local concentration of the refrigerant within the vicinity of the leak. In addition, the low GWP refrigerants concentration is affected by the indoor air environment, such as air flow rate and temperature. In the present study, a computational fluid dynamics (CFD) model is developed to model the flow and temperature of air surrounding a propane-based refrigeration system, as well as the concentration of leaked low GWP refrigerants surrounding the refrigeration system. The model results reveal the concentration distribution of low GWP refrigerants within the building, and as a result, the flammable regions within the building can be identified. Moreover, different ventilation layouts will be tested using the model to improve the design of ventilation. The numerical model can assist in the design of ventilation systems to minimize flammable regions within buildings due to leakage of flammable refrigerants.
Use of a Genetic Algorithm to Model the Interaction of Conduction and Nucleate Boiling Mechanisms During Evaporation of Water Droplets on Superheated ZnO Nanostructured Surfaces
Authors: Silva Anisa D. , Carey Van P. 
Published: September 2023

Abstract
At low surface superheat levels, water droplets deposited on ZnO nanostructured surfaces vaporize primarily by conduction transport of heat from the solid heated surface to the liquid-vapor interface. As the superheat is increased beyond the onset of bubble nucleation threshold (ONB), an increasing number of active nucleation sites are observed within the evaporating droplet reducing the time required to completely evaporate the droplet. There were two primary objectives of this investigation; first, to determine how system parameters dictate when ONB occurs and how its heat transfer enhancement effect increases with superheat. The second was to develop a physics-inspired model equation for the evaporation time of a droplet on a nanostructured surface which accounts for effects of conduction transport in the liquid layer of the droplet and nucleate boiling.
A shape factor model for conduction-dominated vaporization of the droplet was first constructed. A correction factor was introduced to account for deviation of the measured droplet evaporation times from the conduction-dominated model. The correction factor form was postulated using a modified form of the onset of nucleate boiling parameter used in the well-known model analysis developed by Hsu to predict onset of nucleation and active nucleation site range in a thermal boundary layer associated with forced convection boiling. Droplet footprint radii were experimentally observed to be affected by superheat and an additional term was introduced to account for this phenomenon. A term was also introduced to include correlations for boiling to incorporate system properties.
This modeling led to an evaporation time equation containing numerical constants dictated by the idealizations from the physical modeling. To develop an improved empirical model equation, these numerical values were taken to be adjustable constants, and a genetic algorithm was used to determine the adjustable constant values that best fit a data collection spanning wide variations of droplet size, surface apparent contact angle, and superheat level. The best-fit constants match the data to an absolute fractional error of 26%. The model equation developed in this study provides insight into the interaction between conduction transport and nucleate boiling effects that can arise in droplet vaporization processes.
Use of Artificial Intelligence Techniques, Correlation of Thermal Images and the Concept of Thermal Impedance Aiming to Estimate the Location and Size of Breast Tumours
Authors: Nascimento Jefferson G. , Menegaz Gabriela L. , Guimaraes Gilmar 
Published: September 2023

Abstract
Early and accurate detection of breast cancer is a critical part of the strategy to reduce mortality associated with this prevalent disease. We propose to develop techniques based on applying the thermal impedance method and artificial intelligence to detect the origin of the heat source (abnormal cancer metabolism) and its size. The low sensitivity to tiny and deep tumours, usually found when analyzing surface temperatures using thermal imaging, is circumvented by utilizing the concept of thermal impedance and artificial intelligence techniques such as deep learning. The thermal model’s development and the database’s creation based on its solution are described. It also presents the choice of detectable parameters in the thermal image, deep learning libraries and network training using convolutional neural networks. Estimates of the location and size of tumours using thermographic images obtained from simulated thermal models of a breast based on a Cartesian geometry and a scanned geometric shape of an anatomical phantom model are also described.
Prediction of the Inter-Tube Flow Mode Transitions in the Evaporators of Multi-Effect Thermal Desalination Plants
Authors: Mikhaeel Mina M. K. , Jacobi Anthony M. 
Published: September 2023

Abstract
Water is one of the most stressed resources on the planet. The limited availability of fresh water and the high cost of transportation have led to an increased interest in water desalination technologies. The two main categories of desalination techniques are membrane desalination and thermal desalination. Membrane technologies include pressure driven and electrical driven membranes. On the other hand, thermal desalination includes: multi-effect desalination (MED), multi-stage flash (MSF) desalination, and mechanical vapor compression desalination.
Multi-effect desalination plants are usually made of a series of evaporators (also known as effects). In each effect, hot steam flows inside the tubes and evaporates the seawater that falls on the outside of the tubes. The vapor formed at each effect flows to the next effect and acts as the heating medium for the falling seawater. The prevailing flow mode of the falling seawater (i.e. droplet, jet, or sheet) influences heat and mass transfer as well as dry out in the evaporators of Multi-Effect Desalination (MED) plants.
The objective of this paper is to predict and discuss the prevailing falling film flow modes in the evaporators of MED plants, under different operating conditions. The paper demonstrates the transitional Reynolds numbers between the main falling film modes for seawater. This closes a gap in the literature where there is a dearth of mode transition data for seawater. The effect of fluid properties and tube geometry on the transitions is discussed in details. The accuracy of the predicted transitional Reynolds numbers is evaluated via uncertainty quantification techniques.