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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗
DOE OSTI2020

Atmospheric Modeling to Enable Prediction of Golden Eagle Interactions with Wind Power Plants

This panel will explore the use of technologies and methods that enhance our understanding of eagle behavior in and near wind energy facilities. The decreasing costs of tracking technologies and substantial computational capabilities are allowing for finer resolution and confidence of eagle observations and the modeling of such datasets increase our understanding of their movements and use of airspace and underlying landscapes. Behavior ecologists' intrinsic knowledge of eagle behavior can augment and further enhance inferences from technology-derived information alone, e.g., GPS, camera, radar, etc. The panel will discuss the state of science and, given the cost-effective tools available, what research objectives are emerging to better assess and reduce wind-eagle risk. The discussion will focus on the following areas: Integrating Behavioral and Quantitative Ecologist perspectives of bald eagle and golden eagle behavior and wind energy risk; Regional-scale vs. facility-scale investigations of bald eagle and golden eagle use of airspace. For example, avoidance behavior to assess risk at facility-scale, and eagle use of landscapes, e.g., territories, nesting, and life-cycle behavior; Bald eagle and golden eagle use of airspace and nexus with atmospheric flow dynamics of wind energy generation; GPS, biomonitoring, tracking camera, radar, and other tools/techniques for deepening the knowledge of eagle behavior in and around wind farms.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2023

NETL Direct Air Capture Center

In 2022 Congress authorized the $25M National Energy Technology Laboratory Direct Air Capture Center. The facility will be specifically targeted at accelerating the commercialization of technologies beyond the conceptual stage which have not yet reached full pilot-scale (TRL 3 to 6). The ability to operate over a wide range of conditions will help the developers to understand how their technologies respond in different climates, from summer to winter and arid to tropical. NETL recognizes that DAC technology is still early in its evolution, and a wide variety of highly varied technologies are being explored. The Center will be designed with substantial flexibility to accommodate the rapidly evolving technological landscape. Testing systems at three scales will be included: lab-scale systems designed to examine the long-term stability of DAC materials, bench-scale module testing systems capable of probing flow dynamics, and small pilot-scale skid rooms able to test prototype DAC units under a wide variety of climate conditions. The NETL DAC Center will feature dedicated engineering, technician, scientific and logistical support for experimental system design, installation, operation of experiments, and interpretation of results for projects including but not limited to kinetics of absorption/desorption, thermal duty, and post-mortem elemental characterization to understand degradation. The NETL DAC Center projects will also have access to dedicated process modeling and analysis to evaluate the technoeconomic aspects of new technologies. NETL’s Systems Engineering and Analysis (SEA) team, the Carbon Capture Simulation Initiative (CCSI), and the Institute for the Design of Advanced Energy Systems (IDAES) are all potential collaborators with NETL’s testing partners from industry, academia, and other research institutions. NETL also has world class capabilities in device scale modeling (i.e., MFIX) that will be available to help design more efficient contactors and optimize unique internal configurations that can be realized by advanced manufacturing. The talk will cover the design and capabilities of the center, the planned availability, and feedback will be solicited from the audience on DAC testing needs.

Luebke, David↗
DOE OSTI2023

Accelerating commercialization of direct air capture technology

In 2022 Congress authorized the $25M National Energy Technology Laboratory Direct Air Capture Center. The facility will be specifically targeted at accelerating the commercialization of technologies beyond the conceptual stage which have not yet reached full pilot-scale (TRL 3 to 6). The ability to operate over a wide range of conditions will help the developers to understand how their technologies respond in different climates, from summer to winter and arid to tropical. NETL recognizes that DAC technology is still early in its evolution, and a wide variety of highly varied technologies are being explored. The Center will be designed with substantial flexibility to accommodate the rapidly evolving technological landscape. Testing systems at three scales will be included: lab-scale systems designed to examine the long-term stability of DAC materials, bench-scale module testing systems capable of probing flow dynamics, and small pilot-scale skid rooms able to test prototype DAC units under a wide variety of climate conditions. The NETL DAC Center will feature dedicated engineering, technician, scientific and logistical support for experimental system design, installation, operation of experiments, and interpretation of results for projects including but not limited to kinetics of absorption/desorption, thermal duty, and post-mortem elemental characterization to understand degradation. The NETL DAC Center projects will also have access to dedicated process modeling and analysis to evaluate the technoeconomic aspects of new technologies. NETL’s Systems Engineering and Analysis (SEA) team, the Carbon Capture Simulation Initiative (CCSI), and the Institute for the Design of Advanced Energy Systems (IDAES) are all potential collaborators with NETL’s testing partners from industry, academia, and other research institutions. NETL also has world class capabilities in device scale modeling (i.e., MFIX) that will be available to help design more efficient contactors and optimize unique internal configurations that can be realized by advanced manufacturing. The talk will cover the design and capabilities of the center, the planned availability, and feedback will be solicited from the audience on DAC testing needs.

Luebke, David↗
DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE and Application to Molten Salt Reactors

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated a new two-phase model into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model. It provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model’s accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase model implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, the model is applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of the mixture drift-flux model for capturing the two-phase flow dynamics critical to MSR operations

42 - ENGINEERING↗
DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE for Molten Salt Reactor Application

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗
DOE OSTI2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions

Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.

Lee, Jonathan W.↗
DOE OSTI2024

Broadband Rotational Spectroscopy in Uniform Supersonic Flows: Chirped Pulse/Uniform Flow for Reaction Dynamics and Low Temperature Kinetics

ConspectusThe study of gas-phase chemical reactions at very low temperatures first became possible with the development and implementation of the CRESU (French acronym for Reaction Kinetics in Uniform Supersonic Flows) technique. CRESU relies on a uniform supersonic flow produced by expansion of a gas through a Laval (convergent-divergent) nozzle to produce a wall-less reactor at temperatures from 10 to 200 K and densities of 1016-1018 cm-3 for the study of low temperature kinetics, with particular application to astrochemistry. In recent years, we have combined uniform flows with revolutionary advances in broadband rotational spectroscopy to yield an instrument that affords near-universal detection for novel applications in photodissociation, reaction dynamics, and kinetics. This combination of uniform supersonic flows with chirped-pulse Fourier-transform microwave spectroscopy (Chirped-Pulse/Uniform Flow, CPUF) permits detection of any species with a modest dipole moment, thermalized to the uniform temperature of the gas flow, with isomer, conformer, and vibrational state specificity. In addition, the use of broadband, high-resolution, and time-dependent (microsecond time scale) micro- and mm-wave spectroscopy makes it an ideal tool for characterizing both transient and stable molecules, as well as studying their spectroscopy and dynamics.In this Account, we review recent advances made using the CPUF technique, including studies of photodissociation, radical-radical reaction dynamics, and low temperature kinetics. These studies highlight both the strength of universal and multiplexed detection and the challenges of coupling it to a high-density collisional environment. Product branching and product evolution as a function of time have been measured for astrochemically relevant systems, relying on the detailed characterization of these flow conditions via experiments and fluid dynamics simulations. In the photodissociation of isoxazole, an unusual heterocyclic molecule with a very low-energy conical intersection, we have identified 7 products in 5 reaction channels and determined the product branching, pointing to both direct and indirect pathways. We have also approached the same system from separated NO and C3H3 reactants to explore a broader range of the potential energy surface, demonstrating the power of multichannel branching measurements for complex radical-radical reactions. We determined the product branching in the C3H2 isomers in the photodissociation of the propargyl radical and identified the importance of a hydrogen atom catalyzed isomerization to the lowest energy cyclic form. This then motivated a study of direct D-H exchange reaction in radicals, in which we demonstrate that it is an important and overlooked pathway for deuterium fractionation in astrochemical environments. Recently, we have shown the measurement of low temperature kinetics inside an extended Laval nozzle, after which a shock-free secondary expansion to low temperature and density affords an ideal environment for detection by rotational spectroscopy. These results highlight the power and potential of the CPUF approach, and future prospects will also be discussed in light of these developments.

Dias, Nureshan↗
DOE OSTI2022

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. I. The O ( N ) model

The functional renormalization group (FRG) approach is a powerful tool for studies of a large variety of systems, ranging from statistical physics over the theory of the strong interaction to gravity. The practical application of this approach relies on the derivation of so-called flow equations, which describe the change of the quantum effective action under the variation of a coarse-graining parameter. In the present work, we discuss in detail a novel approach to solve such flow equations. This approach relies on the fact that RG equations can be rewritten such that they exhibit similarities with the conservation laws of fluid dynamics. This observation can be exploited in different ways. First of all, we show that this allows to employ powerful numerical techniques developed in the context of fluid dynamics to solve RG equations. In particular, it allows us to reliably treat the emergence of nonanalytic behavior in the RG flow of the effective action as it is expected to occur in studies of, e.g., spontaneous symmetry breaking. Second, the analogy between RG equations and fluid dynamics offers the opportunity to gain novel insights into RG flows and their interpretation in general, including the irreversibility of RG flows. Further, we work out this connection in practice by applying it to zero-dimensional quantum-field theoretical models. The generalization to higher-dimensional models is also discussed. Our findings are expected to help improving future FRG studies of quantum field theories in higher dimensions both on a qualitative and quantitative level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Large-Eddy Simulation Study of Flow and Combustion Dynamics in a Full-Scale Hydrogen–Air Rotating Detonation Combustor-Stator Integrated System

In the present work, a first-of-its-kind three-dimensional (3D) large-eddy simulation (LES) study is conducted to numerically investigate the combustion dynamics as well as aero-thermal phenomena in a full-scale nonpremixed hydrogen–air rotating detonation engine (RDE) (with a diverging-shaped lower-end wall), when integrated with nozzle guide vanes (NGV) acting as the turbine stator. The wall-modeled LES framework incorporates hydrogen–air detailed chemical kinetics and adaptive mesh refinement (AMR). A comparative analysis is carried out for two operating conditions with different fuel/air mass flow rates but global equivalence ratio of unity, and considering RDE configurations without and with stator. The LES model is validated against available experimental data for the low mass flux condition with respect to detonation wave speed/height, wave dynamics, and axial static pressure distribution. Numerical results indicate significant deflagrative combustion occurring in the fill region near the inner wall due to formation of recirculation zones in the injection near-field driven by the backward facing step. The leading detonation wave is found to be trailed by an azimuthal reflected-shock combustion (ARSC) wave, consistent with experimental observations, which consumes unburned vitiated reactants that leak through the main detonation wave. The main detonation wave characteristics, such as detonation wave speed/height and combustion efficiency, do not change appreciably with the presence of NGV. A novel combustion diagnostic technique based on chemical explosive mode analysis (CEMA) is employed to quantify the fraction of heat release occurring in the detonative mode versus deflagrative mode for the simulated conditions. The exit flow is found to be nearly fully subsonic and supersonic for the low and high mass flux conditions, respectively. Further analysis of the exit flow profiles shows that the presence of NGV renders the flow more axial and significantly impacts the exit Mach number and total pressure, while the total temperature shows negligible change. In addition, the low mass flux operating point, despite exhibiting more deflagrative losses within the combustor, yields overall lower pressure drop from plenum to exhaust, which is mainly attributed to lower pressure drop across the injectors. Lastly, the rotating detonation engine-nozzle guide vanes (RDE-NGV) configuration exhibits higher total pressure loss compared to rotating detonation engine (RDE) without stator across both the mass flux conditions. In conclusion, this study extends the state-of-the-art in numerical modeling of pressure gain combustion (PGC) systems by demonstrating high-fidelity 3D reacting LES of full-scale RDE-NGV systems relevant to RDE-turbine integration for stationary power generation.

Combustion↗
DOE OSTI2023

Computational fluid dynamics investigations of flow, heat transfer, and oxidation in heat recovery steam generator

Modern heat recovery steam generators (HRSGs) operate at elevated temperatures, leading to the formation of oxides inside the tubes of heat exchangers (HXs). This oxide growth reduces the heat recovery efficiency. Moreover, after reaching a certain critical thickness, some oxide scales detach from the tube surface (exfoliation), causing erosion damage to the components downstream. Predicting the metal temperature distribution and associated oxide thickness in the HXs of an HRSG can aid in mitigating these problems. Here, a computational fluid dynamics (CFD) model was developed within the commercial code STAR-CCM+ for the prediction of fluid flow, conjugate heat transfer, and associated oxidation in HRSGs. Moreover, a new Porous Media Model (PMM) method was developed to model the fin effect on the heat transfer in HX, which can substantially reduce the prohibitive computational costs of fin meshes. The developed CFD model was used to conduct a high-fidelity simulation of a real-scale HRSG to investigate flow, heat transfer, and oxide growth. The calculated oxide thickness on different tubes can be used to identify HX regions that require oxide-resistant coatings to prevent exfoliation and ensuing damages. Furthermore, this CFD framework can serve as a reference for future studies that intend to model and investigate high-temperature oxidation in HXs used for any applications.

42 ENGINEERING↗
DOE OSTI2020

Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics

The U.S. Department of Energy National Energy Technology Laboratory's (NETL) 50 kW th chemical looping reactor (CLR) has an underperforming cyclone, which was designed using empirical correlations. To improve the performance of this cyclone using computational fluid dynamics (CFD)-based modeling simulations, four critical design parameters including the vortex tube radius and length, barrel radius, and the inlet width and height were optimized. Here, NETL's open source multiphase flow with interphase exchange (MFiX) CFD code has been used to model a series of cyclones by systematically varying the geometric design parameters. To perform the optimization process, the surrogate modeling and sensitivity analysis followed by the optimization capability in nodeworks was used. The basic methodology for the process is to employ a statistical design of experiments (DOE) method to generate sampling simulations that fill the design space. Corresponding CFD models are then created, executed, and postprocessed. A response surface is created to characterize the relationship between input parameters and the quantities of interest (QoI). Finally, the CFD-surrogate is used by an optimization method to find the optimal design condition based on the objective and constraints prescribed. The resulting optimal cyclone has a larger diameter and longer vortex tube, a larger diameter barrel, and a taller and narrower solids inlet. The improved design has a predicted pressure drop 11 times lower than the original design while reducing the mass loss by a factor of 2.3.

42 ENGINEERING↗
DOE OSTI2022

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. II. Entropy production and irreversibility of RG flows

Herein we demonstrate that the reformulation of renormalization group (RG) flow equations as nonlinear heat equations has severe implications on the understanding of RG flows in general. We demonstrate by explicitly constructing an entropy function for a zero-dimensional Z 2 -symmetric model that the dissipative character of generic nonlinear diffusion equations is also hard-coded in the functional RG equation. This renders RG flows manifestly irreversible, revealing the semigroup property of RG transformations on the level of the flow equation itself. Additionally, we argue that the dissipative character of RG flows, its irreversibility and the entropy production during the RG flow may be linked to the existence of a so-called C– / A-function. In total, this introduces an asymmetry in the so-called RG time—in complete analogy to the thermodynamic arrow of time—and allows for an interpretation of infrared actions as equilibrium solutions of dissipative RG flows equations. The impossibility of resolving microphysics from macrophysics is evident in this framework. Furthermore, we directly link the irreversibility and the entropy production in RG flows to an explicit numerical entropy production, which is manifest in diffusive and non-linear partial differential equations (PDEs) and a standard mathematical tool for the analysis of PDEs. Using exactly solvable zero-dimensional Z 2 -symmetric models, we explicitly compute the (numerical) entropy production related to the total variation nonincreasing property of the PDE during RG flows toward the infrared limit. Finally, we discuss generalizations of our findings and relations to the C– / A-theorem as well as how our work may help to construct truncations of RG flow equations in the future, including numerically stable schemes for solving the corresponding PDEs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Experimental investigation of internal two-phase flow structures and dynamics of quasi-stable sheet cavitation by fast synchrotron x-ray imaging

The quasi-stable sheet cavitation produced in a small Venturi channel is investigated using a fast synchrotron X-ray imaging technique aided with conventional high speed photography. The use of X-rays instead of visible light solves cavitation opacity related issues, and X-ray phase contrast-based edge enhancement enables high-definition visualization of the internal two-phase morphology. The simultaneous acquisition of time-resolved velocity and void fraction fields through post-processing the recorded X-ray images reveals, for the first time, the complex diphasic flow structures inside the sheet cavity, which is essentially divided into 6 characteristic parts. Distinct from the current mainstream view, the globallysteady sheet cavitation is found to be characterized by a weak but constantly-existing re-entrant flow that can penetrate the entire cavity. The turbulent velocity fluctuations inside the sheet cavity are also investigated. The turbulence level in the reverse flow region is observed to be as low as in the outer main flow demonstrating the relatively steady status of the reentrant flow. Unlike the streamwise and cross-stream fluctuations, the shear stress appears to be weakly correlated with the velocity gradient. The collapse of vapor phase and the vaporization at the upstream cavity interface are found to be the primary causes of shear stress intensification.

42 ENGINEERING↗