Characterization and Modeling of Metal-Based Enhanced Conductive Materials for Fabrication
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36 MATERIALS SCIENCE↗
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Thundercloud electrification models in atmospheric electricity and meteorology
A survey is presented of presently-available theoretical models. The models are classified into three main groups: (1) convection models, (2) precipitation models, and (3) general models. The strengths and weaknesses of the models, their dimensionalities and degrees of sophistication, the nature of their inputs and outputs, and the various specific charging mechanisms treated by them, are considered. In results obtained to date, the convection models predict no significant electrification enhancement based on conductivity gradients and convection alone, with the assumed air circulation patterns. Results of the precipitation models show that the initial electrification can occur rapidly and stably through noninductive collision mechanisms involving ice, and breakdown-strength electric fields can relatively easily be achieved subsequently through the collisional-inductive mechanism. A critical difficulty of the collision mechanisms is imprecise knowledge of relaxation times versus contact times, which can easily lead to overestimates of electrification. The general model results tend to support those of the precipitation models in emphasizing the high potential effectiveness of the collisional-inductive mechanism.
Parker, L. W.↗
Numerical Simulation of Aircraft Trailing Vortices
The increase in air traffic is currently outpacing the development of new airport runways. This is leading to greater air traffic congestion, resulting in costly delays and cancellations. The National Aeronautics and Space Administration (NASA) under its Terminal Area Productivity (TAP) program is investigating new technologies that will allow increased airport capacity while maintaining the present standards for safety. As an element of this program, the Aircraft Vortex Spacing System (AVOSS) is being demonstrated in July 2000, at Dallas Ft-Worth Airport. This system allows reduced aircraft separations, thus increasing the arrival and departure rates, while insuring that wake vortices from a leading aircraft do not endanger trailing aircraft. The system uses predictions or wake vortex position and strength based on input from the current weather state. This prediction is accomplished by a semi-empirical model developed from theory, field observations, and relationships derived from numerical wake vortex simulations. Numerical experiments with a Large Eddy Simulation (LES) model are being conducted in order to provide guidance for the enhancement of these prediction algorithms. The LES Simulations of wake vortices are carried out with NASA's Terminal Area Simulation System (TASS). Previous wake vortex investigations with TASS are described. The primary objective of these numerical studies has been to quantify vortex transport and decay in relation to atmospheric variables. This paper summarizes many of the previous investigations with the TASS model and presents some new results regarding the onset of wake vortex decay.
Proctor, Fred H.↗
Digital Twin Empowered PV Power Prediction
The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.
14 SOLAR ENERGY↗
Investigations of radiation-induced and carrier-enhanced conductivity
A steady-state carrier computer code, PECK (Parker Enhanced Carrier Kinetics), that predicts the radiation-induced conductivity (RIC) produced in a dielectric by an electron beam was developed. The model, which assumes instantly-trapped holes, was then applied to experimental measurements on thin Kapton samples penetrated by an electron beam. Measurements at high bias were matched in the model by an appropriate choice for the trap-modulated electron mobility. A fractional split between front and rear currents measured at zone bias is explained on the basis of beam-scattering. The effects of carrier-enhanced conductivity (CEC) on data obtained for thick, free-surface Kapton samples is described by using an analytical model that incorporates field injection of carriers from the RIC region. The computer code, LWPCHARGE, modified for carrier transport, is also used to predict partial penetration effects associated with CEC in the unirradiated region. Experimental currents and surface voltages, when incorporated in the appropriate models, provide a value for the trap modulated mobility that is in essential agreement with the RIC results.
Meulenberg, A., Jr.↗
River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements
Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.
54 ENVIRONMENTAL SCIENCES↗
3D simulations of spinlike flames in Co/Al multilayers with enhanced conduction losses
Reactive Co/Al multilayers are uniformly structured materials that may be ignited to produce rapid and localized heating. Prior studies varying the bilayer thickness (i.e., sum of two individual layers of Co and Al) have revealed different types of flame morphologies, including: (a) steady/planar, (b) wavy/periodic, and (c) transverse bands, originating in the flame front. These instabilities resemble the “spin waves” first observed in the early studies of solid combustion (i.e., Ti cylinder in a N 2 atmosphere), and are likewise thought to be due to the balance of heat released by reaction and heat conduction forward into the unreacted multilayer. However, the multilayer geometry and three-dimensional (3D) edge effects are relatively unexplored. In this work, a new diffusion-limited reaction model for Co/Al multilayers was implemented in large, novel 3D finite element analysis (FEA) simulations, in order to study the origins of these spinlike flames. This reaction model builds upon previous work by introducing three new phase-dependent property models for: (1) the diffusion coefficient, (2) anisotropic thermal conductivity tensor, and (3) bulk heat capacity, as well as one additional model for the bilayer-dependent heat of reaction. These novel 3D simulations are the first to predict both steady and unsteady flames in Co/Al multilayers. Moreover, two unsteady modes of flame propagation are identified, which depend on the enhanced conduction losses with slower flames, as well as flame propagation around notched edges. Finally, future work will consider the generality of the current modeling approach and also seek to define a more generalized set of stability criteria for additional multilayer systems.
42 ENGINEERING↗
Computer Modeling of Electrostatic Aggregation of Granular Materials in Planetary and Astrophysical Settings
Electrostatic forces strongly influence the behavior of granular materials in both dispersed (cloud) systems and semi-packed systems. These forces can cause aggregation or dispersion of particles and are important in a variety of astrophysical and planetary settings. There are also many industrial and commercial settings where granular matter and electrostatics become partners for both good and bad. This partnership is important for human exploration on Mars where dust adheres to suits, machines, and habitats. Long-range Coulombic (electrostatic) forces, as opposed to contact-induced dipoles and van der Waals attractions, are generally regarded as resulting from net charge. We have proposed that in addition to net charge interactions, randomly distributed charge carriers on grains will result in a dipole moment regardless of any net charge. If grains are unconfined, or fluidized, they will rotate so that the dipole always induces attraction between grains. Aggregates are readily formed, and Coulombic polarity resulting from the dipole produces end-to-end stacking of grains to form filamentary aggregates. This has been demonstrated in USML experiments on Space Shuttle where microgravity facilitated the unmasking of static forces. It has also been demonstrated in a computer model using grains with charge carriers of both sign. Model results very closely resembled micro-g results with actual sand grains. Further computer modeling of the aggregation process has been conducted to improve our understanding of the aggregation process, and to provide a predictive tool for microgravity experiments slated for Space Station. These experiments will attempt to prove the dipole concept as outlined above. We have considerably enhanced the original computer model: refinements to the algorithm have improved the fidelity of grain behavior during grain contact, special attention has been paid to simulation time steps to enable establishment of a meaningful, quantitative time axis, and calibration of rounding accuracies have been conducted to test cumulative numerical influences in the model. The model has been run for larger grain populations, variable initial cloud densities, and we have introduced random net charging to individual grains, as well as a net charge to the cloud as a whole. The model uses 3 positive and 3 negative charges randomly distributed on each grain, with up to 160 grains contained within various size "boxes" that define the initial number densities in the clouds. Each charge represents localized charged region on a grain, but does not necessarily imply single quantized charge carriers. The Coulomb equations are then allowed to interact for each monopole: dipoles and any higher order charge coupling is a natural product of these "free" interactions over which the modeler exerts no influence. The charges are placed on surfaces of grains at random locations. A series of runs was conducted for neutral grains that had a perfect balance of negative and positive char carriers. Runs were also conducted with grains having additional fractional charges ranging between 0 and 1. By adding fractional charges of one sign, the model created grain populations in which all grains had excess charges the same sign, giving the cloud an overall net charge. This simulates clouds subjected to ionizing radiation (e. protoplanetary debris disk around a protosun), or any other process of charge biasing in a grain population (e.g., volcanic plumes). In another run series, random fractional charges of either sign were added to the grains so th some grains had a slight net positive charge while others had a slight net negative charge. This simulates triboelectrically-charged grain populations in which acquisition of an electron by one surface is at the expense creating a hole elsewhere. This dual sign charging was applied in two ways: in one case the cloud remained neutral by ensuring that all grain excess charges added to zero; in the other case, the cloud was permitted slight net char by not imposing a charge-balance condition. Additional information is contained in the original.
Marshall, J.↗
Effects of Deep Convection on Atmospheric Chemistry
This presentation will trace the important research developments of the last 20+ years in defining the roles of deep convection in tropospheric chemistry. The role of deep convection in vertically redistributing trace gases was first verified through field experiments conducted in 1985. The consequences of deep convection have been noted in many other field programs conducted in subsequent years. Modeling efforts predicted that deep convection occurring over polluted continental regions would cause downstream enhancements in photochemical ozone production in the middle and upper troposphere due to the vertical redistribution of ozone precursors. Particularly large post-convective enhancements of ozone production were estimated for convection occurring over regions of pollution from biomass burning and urban areas. These estimates were verified by measurements taken downstream of biomass burning regions of South America. Models also indicate that convective transport of pristine marine boundary layer air causes decreases in ozone production rates in the upper troposphere and that convective downdrafts bring ozone into the boundary layer where it can be destroyed more rapidly. Additional consequences of deep convection are perturbation of photolysis rates, effective wet scavenging of soluble species, nucleation of new particles in convective outflow, and the potential fix stratosphere-troposphere exchange in thunderstorm anvils. The remainder of the talk will focus on production of NO by lightning, its subsequent transport within convective clouds . and its effects on downwind ozone production. Recent applications of cloud/chemistry model simulations combined with anvil NO and lightning flash observations in estimating NO Introduction per flash will be described. These cloud-resolving case-study simulations of convective transport and lightning NO production in different environments have yielded results which are directly applicable to the design of lightning parameterizations for global chemical transport models. The range of mean values (factor of 3) of NO production per flash (or per meter of lightning channel length) that have been deduced from the model will be shown and compared with values of production in the literature that have been deduced using other methods, Results show that on a per flash basis, IC flashes are nearly as productive of NO as CG flashes. When combined with the global flash rate of 44 flashes per second from NASA's Optical Transient Detector (OTD) measurements, these estimates and the results from other techniques yield global NO production rates of 2-9 TgN/year. Vertical profiles of lightning NOx mass at the end of the 3-D storm simulations have been summarized to yield suggested profiles for use in global models. Simulations of the photochemistry over the 24 hours following a storm have been performed to determine the additional ozone production which can be attributed to lightning NO.
Pickering, Kenneth E.↗
Response Of Ceramic Insulation To Aerothermodynamic Heating
Thermal conductivities determined from engineering model used to predict accurately thermal responses of multicomponent insulation on spacecraft. Types of insulation studied include such composite parts as alumina-enhanced thermal barrier backed by low-density fibrous refractory material. Internal responses of various types of multicomponent insulation to aerothermodynamic heating calculated with help of computer program that implements engineering model for thermal conductivity. Transfer of heat by internal radiation plays major role in responses of fibrous materials at high temperatures and incorporated into model and program. Used in future spacecraft and exposed during reentry and aerobraking maneuvers in outer atmosphere to environments even harsher than that of Space Shuttle.
Stewart, David A.↗
Assessment and Improvement of the SST-Gamma Transition Model in Nalu-Wind
We conduct laminar–turbulent boundary-layer transition simulations using a local correlation-based transition model for two-dimensional incompressible flow and present enhancements to improve the accuracy of transition predictions. Menter’s Galilean-invariant 𝛾 transition model is implemented in the incompressible, unstructured-grid flow solver Nalu-Wind and is validated against experimental data and results from NASA’s flow solvers. The test cases of the AIAA Transition Prediction and Modeling Workshop are investigated, namely, the T3A/T3B flat plates and the NLF(1)-0416 and S809 airfoils. Based on the results, best practices for transition simulations, particularly for an unstructured-grid flow solver, are identified. Additional airfoil simulations are conducted for two wind turbine airfoils, S822 at Reynolds numbers of 𝑂(10 5 ) and DU00-W-212 at Reynolds numbers of 𝑂(10 7 ), to assess the model at low and high Reynolds numbers. Furthermore, through this work, we propose several approaches to enhance transition simulations, including 1) enforcing positivity of the implicit operator for the source terms of the transition model, 2) employing a constant turbulence intensity in stationary external flow simulations, and 3) recommending meshing for unstructured-grid flow solvers. Finally, we provide detailed documentation of the validation and data for the canonical cases to the transition modeling community.
17 WIND ENERGY↗
Atmospheric model development in support of SEASAT. Volume 1: Summary of findings
Atmospheric analysis and prediction models of varying (grid) resolution were developed. The models were tested using real observational data for the purpose of assessing the impact of grid resolution on short range numerical weather prediction. The discretionary model procedures were examined so that the computational viability of SEASAT data might be enhanced during the conduct of (future) sensitivity tests. The analysis effort covers: (1) examining the procedures for allowing data to influence the analysis; (2) examining the effects of varying the weights in the analysis procedure; (3) testing and implementing procedures for solving the minimization equation in an optimal way; (4) describing the impact of grid resolution on analysis; and (5) devising and implementing numerous practical solutions to analysis problems, generally.
Kesel, P. G.↗
A multiscale anisotropic polymer network model coupled with phase field fracture
The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.
42 ENGINEERING↗
Hot-spot model for inertial confinement fusion implosions with an applied magnetic field
Imposing a magnetic field on inertial confinement fusion implosions magnetizes the electrons in the compressed fuel; this suppresses thermal losses, which increases temperature and fusion yield. Indirect-drive experiments at the National Ignition Facility with 12 and 26 T applied magnetic fields demonstrate up to 40% increase in temperature, 3× increase in fusion yield, and indicate that magnetization alters the radial temperature profile [Moody et al., Phys. Rev. Lett. 129, 195002 (2022); Lahmann et al., APS DPP (2022)]. In this work, we develop a semi-analytic hot-spot model, which accounts for the two-dimensional (2D) Braginskii anisotropic heat flow due to an applied axial magnetic field. First, we show that hot-spot magnetization alters the radial temperature profile, increasing the central peakedness, which is most pronounced for moderately magnetized implosions (with 8–14 T applied field), compared to both unmagnetized (with no applied field) and highly magnetized (with 26 T or higher applied field) implosions. This model explains the trend in the experimental data, which finds a similarly altered temperature profile in the 12 T experiment. Next, we derive the hot-spot model for gas-filled (Symcap) implosions, accounting for the effects of magnetization on the thermal conduction and in changing the radial temperature (and density) profiles. Using this model, we compute predicted central temperature amplification and yield enhancement scaling with the applied magnetic field. The central temperature fits the experimental data accurately, and the discrepancy in the yield suggests a systematic (independent of applied field) degradation, such as mix, and additional degradation in the reference unmagnetized shot, such as reduced laser drive, increased implosion asymmetry, or the magnetic field suppressing ablator mixing into the hot-spot.
Alpha particles↗
Validation of the plasma-wall self-organization model for density limit in ECRH-assisted start-up of Ohmic discharges on J-TEXT
Abstract A recently developed plasma-wall self-organization model (Escande et al 2022 Nucl. Fusion 62 026001) predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted Ohmic start-up and sufficiently high initial neutral density. Experiments have been conducted on J-TEXT to validate such a density limit scenario based on this model. Experimental results demonstrate that increasing the pre-filled gas pressure or ECRH power during the start-up phase can help effectively enhance plasma purity and raise the density limit at the flat-top phase. The experimental data shows that density limit increases by a ratio 0.76 / 0.6 ≈ 1.27 for a decrease by a factor 0.13 / 0.33 ≈ 0.4 in C III radiation.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Interplay of the Spin Density Wave and a Possible Fulde-Ferrell-Larkin-Ovchinnikov State in CeCoIn 5 in Rotating Magnetic Field
The d-wave superconductor CeCoIn 5 has been proposed as a strong candidate for supporting the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state near the low-temperature boundary of its upper critical field. Neutron diffraction, however, finds spin-density-wave (SDW) order in this part of the phase diagram for field in the a-b plane, and evidence for the SDW disappears as the applied field is rotated toward the tetragonal c axis. It is important to understand the interplay between the SDW and a possible FFLO state in CeCoIn 5 , as the mere existence of an SDW does not necessarily exclude an FFLO state. In this work, based on a model constructed on the basis of available experiments, we show that an FFLO state competes with an SDW phase. The SDW state in CeCoIn 5 is stabilized when the field is directed close to the a-b plane. When the field is rotated toward the c axis, the FFLO state emerges, and the SDW phase disappears. In the FFLO state, the nodal planes with extra quasiparticles (where the superconducting order parameter is zero) are perpendicular to the field, and in the SDW phase, the quasiparticle density of states is reduced. We test this model prediction by measuring heat transported by normal quasiparticles in the superconducting state. As a function of field, we observe a reduction of thermal conductivity for field close to the a-b plane and an enhancement of thermal conductivity when field is close to the c axis, consistent with theoretical expectations. Our modeling and experiments, therefore, indicate the existence of the FFLO state when field is parallel to the c axis.
36 MATERIALS SCIENCE↗
Consistent responses of vegetation gas exchange to elevated atmospheric CO 2 emerge from heuristic and optimization models
Elevated atmospheric CO 2 concentration is expected to increase leaf CO 2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO 2 concentration through soil water depletion. The net effect of elevated CO 2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO 2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO 2 , but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO 2 assimilation is predicted to increase, with an amplification of the CO 2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO 2 concentration in both models. The consistent predictions by different models that canopy-level transpiration varies little under elevated CO 2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions.
54 ENVIRONMENTAL SCIENCES↗
The Corrected Distortion model for Lagrangian spray simulation of transcritical fuel injection
In this work, we present a detailed implementation and validation of the droplet modeling framework proposed by Dahms and Oefelein (2016) into the engine commercial CFD software CONVERGE using the User Defined Function (UDF) interface. The model accounts for the nonlinear deformation and oscillation experienced by liquid spray droplet injected into high pressure and temperature. Lagrangian spray simulations of Engine Combustion Network (ECN) Spray A are performed. Model validation against standard experimental measurements of liquid velocity, vapor mixture fraction is conducted. To perform more rigorous model validation, new experimental measurements based on Diffused Back Illumination (DBI) are introduced. The new measurements are processed for Projected Liquid Volume (PLV), which offers as close as possible one-to-one model validation for liquid penetration while offering new insights into the spray physics. Comparison with a One-D model based on adiabatic mixing theory by Siebers (1999) and Desantes et al. (2007) are also conducted. Through these model validation exercises, it is shown that the new framework improves liquid-phase penetration predictions, following a tendency for enhanced evaporation, compared to the standard approach for both Reynolds Average Navier Stokes (RANS) and Large Eddy Simulation (LES). Additionally, at the liquid length, maximum mixture fraction values predicted by the new approach are in good agreement those of an adiabatic mixing model. Qualitative analysis of the spray behaviors during the early stage of the injection process reveals that the proposed framework predicts significant increase in droplet evaporation rate with lower drop drag compared to the current standard approach.
42 ENGINEERING↗