Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Transfer”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coherent Phonon-Induced Modulation of Charge Transfer in 2D Hybrid Perovskites

Electron–phonon interactions play an essential role in charge transport and transfer processes in semiconductors. For most structures, tailoring electron–phonon interactions for specific functionality remains elusive. Here, it is shown that, in hybrid perovskites, coherent phonon modes can be used to manipulate charge transfer. In the 2D double perovskite, (AE2T) 2 AgBiI 8 (AE2T: 5,5“-diylbis(amino-ethyl)-(2,2”-(2)thiophene)), the valence band maximum derived from the [Ag 0.5 Bi 0.5 I4] 2– framework lies in close proximity to the AE2T-derived HOMO level, thereby forming a type-II heterostructure. During transient absorption spectroscopy, pulsed excitation creates sustained coherent phonon modes, which periodically modulate the associated electronic levels. Thus, the energy offset at the organic–inorganic interface also oscillates periodically, providing a unique opportunity for modulation of interfacial charge transfer. Density-functional theory corroborates the mechanism and identifies specific phonon modes as likely drivers of the coherent charge transfer. These observations are a striking example of how electron–phonon interactions can be used to manipulate fundamentally important charge and energy transfer processes in hybrid perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Ab Initio Simulation of Charge Transfer at the Semiconductor Quantum Dot/TiO 2 Interface in Quantum Dot-Sensitized Solar Cells

Quantum dot-sensitized solar cells (QDSSCs) have emerged as a promising solar architecture for next-generation solar cells. The QDSSCs exhibit a remarkably fast electron transfer from the quantum dot (QD) donor to the TiO 2 acceptor with size quantization properties of QDs that allows for the modulation of band energies to control photoresponse and photoconversion efficiency of solar cells. In order to understand the mechanisms that underpin this rapid charge transfer, the electronic properties of CdSe and PbSe QDs with different sizes on the TiO 2 substrate are simulated using a rigorous ab initio density functional method. Our method capitalizes on localized orbital basis set, which is computationally less intensive. Quite intriguingly, a remarkable set of electron bridging states between QDs and TiO 2 occurring via the strong bonding between the conduction bands of QDs and TiO 2 is revealed. Such bridging states account for the fast adiabatic charge transfer from the QD donor to the TiO 2 acceptor, and may be a general feature for strongly coupled donor/acceptor systems. All the QDs/TiO 2 systems exhibit type II band alignments, with conduction band offsets that increase with the decrease in QD size. This facilitates the charge transfer from QDs donors to TiO 2 acceptors and explains the dependence of the increased charge transfer rate with the decreased QD size.

14 SOLAR ENERGY↗
DOE OSTI2021

Charge Transfer Properties of Heterostructures Formed by Bi 2 O 2 Se and Transition Metal Dichalcogenide Monolayers

Atomically thin bismuth oxyselenide (Bi 2 O 2 Se) exhibits attractive properties for electronic and optoelectronic applications, such as high charge-carrier mobility and good air stability. Recently, the development of Bi 2 O 2 Se-based heterostructures have attracted enormous interests with promising prospects for diverse device applications. Although the electrical properties of Bi 2 O 2 Se-based heterostructures have been widely studied, the interlayer charge transfer in these heterostructures remains elusive, despite its importance in harnessing their emergent functionalities. Here, a comprehensive experimental investigation on the interlayer charge transfer properties of two heterostructures formed by Bi 2 O 2 Se and representative transition metal dichalcogenides (namely, WS 2 /Bi 2 O 2 Se and MoS 2 /Bi 2 O 2 Se) is reported. In this work, Kelvin probe force microscopy is used to measure the work functions of the samples, which are further employed to establish type-II band alignment of both heterostructures. Photoluminescence quenching is observed in each heterostructure, suggesting high charge transfer efficiency. Time-resolved and layer-selective pump–probe measurements further prove the ultrafast interlayer charge transfer processes and formation of long-lived interlayer excitons. These results establish the feasibility of integrating 2D Bi 2 O 2 Se with other 2D semiconductors to fabricate heterostructures with novel charge transfer properties and provide insight for understanding the performance of optoelectronic devices based on such 2D heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP

Large-scale scientific workflows rely heavily on high-performance file transfers. These transfers require strict quality parameters such as guaranteed bandwidth, no packet loss or data duplication. To have successful file transfers, methods such as predetermined thresholds and statistical analysis need to be done to determine abnormal patterns. Network administrators routinely monitor and analyze network data for diagnosing and alleviating these, making decisions based on their experience. However, as networks grow and become complex, monitoring large data files and quickly processing them, makes it improbable to identify errors and rectify these. Abnormal file transfers have been classified by simply setting alert thresholds, via tools such as PerfSonar and TCP statistics (Tstat). This paper investigates the feasibility of unsupervised feature extraction methods for identifying network anomaly patterns with three unsupervised classification methods—principal component analysis, autoencoder and isolation forest. Here, we collect file transfer statistics from two experiment sets—synthetic iPerf generated traffic and 1000 Genome workflow runs, with synthetically introduced anomalies. Our results show that while PCA and a simple autoencoder finds it difficult to detect clusters, the tree-variant isolation forest is able to identify anomalous packets by breaking down TCP traces into tree classes early.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

An Assessment of the General Applicability of the Relationship Between Nucleation of CO Bubbles and Mass Transfer of Phosphorus in Liquid Iron Alloys

The current paper seeks to demonstrate the general applicability of the authors’ recently developed treatment of surface renewal during decarburization of Fe-C-S alloys and its effect on the mass transport of phosphorus in the metal phase. The proposed model employs a quantitative model of CO bubble nucleation in the metal to predict the rate of surface renewal, which can then in turn be used to predict the mass-transfer coefficient for phosphorus. A model of mixed transport control in the slag and metal phases was employed to investigate the dephosphorization kinetics between a liquid iron alloy and oxidizing slag. Based on previous studies of the mass-transfer coefficient of FeO in the slag, it was possible to separate the mass transfer coefficient of phosphorus in metal phase, k m , from the overall mass-transfer coefficient k o . Using this approach, k m was investigated under a wide range of conditions and shown to be represented reasonably by the mechanism proposed. The mass-transfer model was tested against results from the literature over a wide range of conditions. The analysis showed that the FeO content in the slag, silicon in the metal and the experimental temperature have strong impact on, k m , almost entirely because of their effect on decarburization behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structure-based mechanism and inhibition of cholesteryl ester transfer protein

Purpose of Review: Cholesteryl ester transfer proteins (CETP) regulate plasma cholesterol levels by transferring cholesteryl esters (CEs) among lipoproteins. Lipoprotein cholesterol levels correlate with the risk factors for atherosclerotic cardiovascular disease (ASCVD). This article reviews recent research on CETP structure, lipid transfer mechanism, and its inhibition. Recent Findings: Genetic deficiency in CETP is associated with a low plasma level of low-density lipoprotein cholesterol (LDL-C) and a profoundly elevated plasma level of high-density lipoprotein cholesterol (HDL-C), which correlates with a lower risk of atherosclerotic cardiovascular disease (ASCVD). However, a very high concentration of HDL-C also correlates with increased ASCVD mortality. Considering that the elevated CETP activity is a major determinant of the atherogenic dyslipidemia, i.e., pro-atherogenic reductions in HDL and LDL particle size, inhibition of CETP emerged as a promising pharmacological target during the past two decades. CETP inhibitors, including torcetrapib, dalcetrapib, evacetrapib, anacetrapib and obicetrapib, were designed and evaluated in phase III clinical trials for the treatment of ASCVD or dyslipidemia. Although these inhibitors increase in plasma HDL-C levels and/or reduce LDL-C levels, the poor efficacy against ASCVD ended interest in CETP as an anti-ASCVD target. Nevertheless, interest in CETP and the molecular mechanism by which it inhibits CE transfer among lipoproteins persisted. Insights into the structural-based CETP-lipoprotein interactions can unravel CETP inhibition machinery, which can hopefully guide the design of more effective CETP inhibitors that combat ASCVD. Summary: Individual-molecule 3D structures of CETP bound to lipoproteins provide a model for understanding the mechanism by which CETP mediates lipid transfer and which in turn, guide the rational design of new anti-ASCVD therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Molecular Structures and Momentum Transfer Cross Sections: The Influence of the Analyte Charge Distribution

Structure elucidation by ion mobility spectrometry-mass spectrometry methods is based on the comparison of an experimentally measured momentum transfer cross-section to cross-sections calculated for model structures. Thus, it is imperative that the calculated cross-section must be accurate. However, it is not fully understood how important it is to accurately model the charge distribution of an analyte ion when calculating momentum transfer cross-sections. Here, we calculate and compare momentum transfer cross-sections for carbon clusters that differ in mass, charge state, and mode of charge distribution, and vary temperature and polarizability of the buffer gas. Our data indicate that the detailed distribution of the ion charge density is intimately linked to the contribution of glancing collisions to the momentum transfer cross-section. The data suggest that analyte ions with molecular mass ~3 kDa or momentum transfer cross-section 400–500 Å{sup 2} would be significantly influenced by the charge distribution in nitrogen buffer gas. Our data further suggest that accurate structure elucidation on the basis of IMS-MS data measured in nitrogen buffer gas must account for the molecular charge distribution even for systems as large as C{sub 960} (~12 kDa) when localized charges are present and/or measurements are conducted under cryogenic temperatures. Finally, our data underscore that accurate structure elucidation is unlikely if ion mobility data recorded in one buffer gas is converted into other buffer gases when electronic properties of the buffer gases differ. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

What Hinders Electron Transfer Dissociation (ETD) of DNA Cations?

Radical activation methods, such as electron transfer dissociation (ETD), produce structural information complementary to collision-induced dissociation. Herein, electron transfer dissociation of 3-fold protonated DNA hexamers was studied to gain insight into the fragmentation mechanism. The fragmentation patterns of a large set of DNA hexamers confirm cytosine as the primary target of electron transfer. The reported data reveal backbone cleavage by internal electron transfer from the nucleobase to the phosphate linker leading either to a•/w or d/z• ion pairs. This reaction pathway contrasts with previous findings on the dissociation processes after electron capture by DNA cations, suggesting multiple, parallel dissociation channels. However, all these channels merely result in partial fragmentation of the precursor ion because the charge-reduced DNA radical cations are quite stable. Two hypotheses are put forward to explain the low dissociation yield of DNA radical cations: it is either attributed to non-covalent interactions between complementary fragments or to the stabilization of the unpaired electron in stacked nucleobases. MS{sup 3} experiments suggest that the charge-reduced species is the intact oligonucleotide. Moreover, introducing abasic sites significantly increases the dissociation yield of DNA cations. Consequently, the stabilization of the unpaired electron by π–π-stacking provides an appropriate rationale for the high intensity of DNA radical cations after electron transfer. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2012

Mid-range adiabatic wireless energy transfer via a mediator coil

A technique for efficient mid-range wireless energy transfer between two coils via a mediator coil is proposed. By varying the coil frequencies, three resonances are created: emitter-mediator (EM), mediator-receiver (MR) and emitter-receiver (ER). If the frequency sweeps are adiabatic and such that the EM resonance precedes the MR resonance, the energy flows sequentially along the chain emitter-mediator-receiver. If the MR resonance precedes the EM resonance, then the energy flows directly from the emitter to the receiver via the ER resonance; then the losses from the mediator are suppressed. This technique is robust against noise, resonant constraints and external interferences. - Highlights: Black-Right-Pointing-Pointer Efficient and robust mid-range wireless energy transfer via a mediator coil. Black-Right-Pointing-Pointer The adiabatic energy transfer is analogous to adiabatic passage in quantum optics. Black-Right-Pointing-Pointer Wireless energy transfer is insensitive to any resonant constraints. Black-Right-Pointing-Pointer Wireless energy transfer is insensitive to noise in the neighborhood of the coils.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Performance evaluation of a metamaterial-based new cool roof using improved Roof Thermal Transfer Value model

A new cool roof with potential to generate significant energy savings in buildings has been developed from a metamaterial film named as RadiCold. Considering that the RadiCold film has unique optical and thermal characteristics and the current Roof Thermal Transfer Value model neglecting the effect of roof thermal mass that may lead to overestimating the cooling load from roofs, this work developed an improved Roof Thermal Transfer Value model and validated the model for both RadiCold cool roof and traditional roofing structures. Data from the reduced-size model building experiments showed that the improved Roof Thermal Transfer Value model can accurately describe the heat gains or losses via the roofs. Under real-world weather conditions in the United States (Tucson AZ, Los Angeles, CA, and Orlando FL), the improved Roof Thermal Transfer Value model has been applied to three types of roof exterior finishing: shingle, Thermoplastic Polyolefin (a cool roof material) and RadiCold. In a typical meteorology year, the modeling results show that the shingle and Thermoplastic Polyolefin roof transfer 78.9–294.1 kWh/(m 2 ·yr) and 8.5–128.2 kWh/(m 2 ·yr) of heat into the building space, respectively, but the RadiCold cool roof dissipates 137.6–268.7 kWh/(m 2 ·yr) of heat from the building space to outdoor environment (e.g., sky). The cooling load reduction from utilizing RadiCold cool roof results in cooling electricity savings of 113.0–143.9 kWh/(m 2 ·yr) compared to the shingle roof and 88.0–92.4 kWh/(m2·yr) compared to the Thermoplastic Polyolefin roof for the three analyzed locations with an assumed air conditioning system’s coefficient of performance of 3.0.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles is investigated using a novel transient three-dimensional computational fluid dynamics model. The model couples particle–gas hydrodynamics of solid–gas flows laden with polydisperse particles, radiative heat transfer in non-grey absorbing, emitting and anisotropically-scattering multi-component participating media, conduction heat transfer in the gas phase, and interfacial convection heat transfer. The multiphase particle-in-cell method is used to predict high-fidelity solid–gas flow characteristics, such as the local discrete particle size distribution, with increased computational efficiency by combining the advantages of both Eulerian and Lagrangian methods. The multi-component radiative transfer model is implemented using an advanced collision-based Monte Carlo ray-tracing method. The number of the prescribed discrete particle components is found to be the key parameter affecting the computational accuracy and efficiency, which primarily depends on the size distribution of the particles. For the model particle–gas flow featuring free-falling Gamma-distributed ceramic particles exposed to concentrated solar irradiation, the particle volume fraction, radiative, fluid flow and thermal characteristics appear to converge with the increasing number of the discrete particle components. Five particle components are sufficient to obtain physically meaningful results. A further increase in the number of the particle components only slightly increases the accuracy of the numerical predictions at the expense of a rapidly increasing computational time. For five particle components, the particle vertical velocity at the receiver exit for particles with the diameter of 43.4 μm is 57% of that for the particles with the diameter of 202.8 μm. The temperatures of these two particle components increase from the initial ambient values by factors of 2 and 1.2, respectively, during the simulation time. In conclusion, the model developed allows for increased fidelity of particle–gas flow simulations with significant radiative effects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Exploratory analysis and performance prediction of big data transfer in High-performance Networks

Big data transfer in large-scale scientific and business applications is increasingly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) via advance bandwidth reservation. Provisioning agents need to carefully schedule data transfer requests, compute network paths, and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized, could be simply wasted due to the exclusive access during the approved time window, and cause extra overhead and complexity for resource management. This calls for accurate performance prediction to reserve bandwidths that match actual needs and avoid over-provisioning. We employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements collected in the past several years from data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated testbeds. We first analyze the performance patterns in response to a comprehensive list of parameters in end-host systems, network connections, and data transfer applications, which motivate the use of machine learning and also help us identify the effects of latent factors. We then propose threshold- and clustering-based methods to eliminate negative effects of latent factors in data preprocessing and build a robust performance predictor based on customized domain-oriented loss functions. The performance of the proposed methods is verified by extensive experiments using SVR and RFR as well as theoretical analysis of the general performance bound.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2024

Experimental investigation of Multi-Mode heat transfer to a Free-Falling dilute particle cloud in a heated vertical tube

The development of dilute particle heat exchangers and reactors for advanced energy systems requires an understanding of the multi-mode heat transfer from a heated wall to falling particles. This study presents experimental results of the overall heat transfer coefficient for a free-falling, dilute flow of particles with solid volume fraction from 0.0005 to 0.006 corresponding to feed rates from 3.7 kg s -1 m -2 to 44 kg s -1 m -2 in a vertical, heated tube containing quiescent air at atmospheric pressure. Tube wall temperatures are varied between 300°C to 900°C while keeping the particle inlet temperature constant. The experimental results show that the overall heat transfer coefficient is a strong function of particle feed rate and surface temperature. Good agreement was obtained with prior studies conducted at comparable temperatures but lower particle feed rates (< 4 kg m -2 s -1 ). The established correlations for particle-to-wall radiation and particle-to-gas convection were used to estimate the wall-to-gas convective contribution from the measured overall heat transfer coefficient. The experimental results indicated a 4 to 6 times improvement in the wall convection in the solid-gas mixture compared to that expected from natural convection in a single-phase gas. Furthermore, the data presented here are applicable to characterize heat transfer in dilute particle heat exchangers, furnaces, and solar receivers.

14 SOLAR ENERGY↗
DOE OSTI2020

Electron transfer calculations between edge sharing octahedra in hematite, goethite, and annite

A key reaction underlying the charge transport in iron containing oxides, clays, micas is the Fe$^{2+}$-Fe$^{3+}$ exchange reaction between edge-sharing iron octahedra. These reactions facilitate conduction in these minerals by the thermally-activated hopping of small polarons across the lattice. Depending on the mineral and local charge state the small polaron can either encase an electron or hole. The probability for conduction of small polarons depends strongly on the height and adiabicity of the reaction barrier, with larger and more diabatic barriers yielding slow conduction associated with either weak coupling or a large prerequisite rearrangement of the lattice during charge transport. To model these reactions, a first principle electron transfer (ET) method was developed to model the small polaron hopping between the edge-sharing octahedra sites in hematite ($e^{-}$ polaron), goethite ($e^{-}$ polaron), and annite ($h^{+}$ polaron) bulk structures. The ET method is based on electronic structure methods (i.e., plane-wave Density Functional Theory) capable of performing calculations with periodic cells and large size systems efficiently while at the same time being accurate enough to be used in the estimation of the electron-transfer coupling matrix element, $V_{AB}$, and the electron transfer transmission factor, $\kappa_{el}$. Additionally, the calculations confirmed the existence of small polarons in all three minerals, and the reactions were predicted to be strongly adiabatic. It was found that transfer of a hole in the octahedral layer of annite had an adiabatic barrier of $0.311$ eV, and the transfer of an extra electron in hematite and goethite had adiabatic barriers of $0.242$ eV and $0.232$ eV respectively. The electronic coupling parameters,$V_{AB}$, were found to be $0.188$ eV, $0.196$ eV, and $0.102$ eV respectively for hematite, goethite, and annite. While similar bonding topologies pertain, the underlying basis for the differences is the subtle differences in local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Convective heat transfer enhancement through additively built multiscale micro-tetrahedron features

Use of Additive Manufacturing (AM) to improve the heat transfer characteristics of tip shrouds in high-pressure turbines is being considered by industries. Existing designs of these components integrate micro-cooling channels to reduce the bulk temperature for improved life. In this research, closely packed micro tetrahedron features in addition to AM roughness has been considered. Further, this multiscale surface characteristics increased surface area per unit volume available for heat exchange. Micro-tet features were designed, manufactured, characterized, and evaluated systematically while increasing their height. An enormous increase in the overall wetted surface area by 200 % was measured. The convective heat transfer enhancement was ~3.72 times EDM rough coupon, and friction factor enhancement was ~5.5 times EDM rough coupon. Furthermore, the proposed design offers 2.5 times enhanced heat transfer for a given 2 W pumping power compared to our EDM rough coupon. Heat transfer enhancement was observed to not vary strongly with increased Reynolds number. Such complex designs are only possible through additive manufacturing for increased heat transfer with little pressure penalty. Finally, increasing the micro-tet height for increased surface area and improved heat exchange beyond an upper limit might not be a significant benefit as it gets compensated by increasing skin friction.

42 ENGINEERING↗
DOE OSTI2014

Heat transfer characteristics of impinging steady and synthetic jets over vertical flat surface

In this paper, heat transfer characteristics of single-slot impinging steady and synthetic jets on a 25.4-mm × 25.4-mm vertical surface were experimentally investigated. The experiments were conducted with a fixed nozzle width of 1 mm. For the steady jet study, the parameters varied in the testing were nozzle length (4 mm, 8 mm, 12 mm, 15 mm), Reynolds (Re) number (100–2500), and dimensionless nozzle-to-plate spacing (H/D h = 5, 10, 15, 20). Correlations for average Nusselt (Nu) number were developed to accurately describe experimental data. The heat transfer coefficient over a vertical surface increases with increasing Re number. For a small nozzle-to-plate spacing (H/D h = 5), the average Nu number is not only a function of the Re number, but also a function of nozzle length. For large nozzle-to-plate spacing (H/D h ⩾ 10) and a nozzle length larger than 8 mm, the heat transfer coefficient is insensitive to H/D h and nozzle length. An 8-mm × 1-mm synthetic jet was studied by varying the applied voltage (20–100 V), frequency (200–600 Hz), and dimensionless nozzle-to-plate spacing (H/D h = 5, 10, 15, 20). Compared to the steady jet, the synthetic jet exhibited up to a 40% increase in the heat transfer coefficient. As a result, the dynamic Re number was introduced to correlate heat transfer characteristics between synthetic jets and steady jets. Using the dynamic Re number collapses the synthetic and steady jet data into a single Nu number curve.

33 ADVANCED PROPULSION SYSTEMS↗