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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Flow Injection Electrochemical Quartz Crystal Microbalance with ICP-OES Detection: Electroprecipitation and Stripping of Lanthanum and Neodymium in a Flow Cell

We used an improved version of our hyphenated analysis technique, flow injection electrochemical quartz crystal microbalance (EQCM) with inductively coupled optical emission spectroscopy, to investigate the electroprecipitation of lanthanum and neodymium from flowing solutions. The improved version has two independent flow injection circuits, allowing different conditions for electrochemical precipitation (pH=4.3 or 2.6) and quick stripping (2% HNO3) with EQCM mass detection and ICP-OES elemental analysis. Lanthanum or neodymium ions in a 500 uL sample were injected into a carrier stream and deposited onto an EQCM housed in a micro flow cell, owing to a localized high-pH layer. The deposits are subsequently stripped from the electrode using HNO3 and analyzed downstream using an ICP-OES. We found that using acidic solutions without supporting electrolyte leads to an increase of the amount of lanthanum detected by 4-fold. The enhanced deposition can be attributed to enhanced mass transfer by migration. Furthermore, we showed that by applying chronopotentiometry, we can detect a change in the hydrogen evolution reaction mechanism that enables the precipitation of lanthanides on the surface of the electrode. Understanding and enhancing the deposition of lanthanides is relevant for elemental or isotopic detection in nuclear forensics.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Flow Injection Electrochemical Quartz Crystal Microbalance with ICP-OES Detection: Recovery of Silver by Electrodeposition with Redox Replacement in a Flow Cell

We developed a new on-line hyphenated flow injection analysis technique (FI-EQCM-ICP-OES) that allows electrochemical deposition and stripping with mass detection and elemental analysis. This technique was used to study a new system for electrochemical recovery of silver from a 0.5 mM Ag + /5 mM Cu 2+ /0.5 M H 2 SO 4 solution by pulsed electrodeposition with redox replacement (EDRR) in a small flow cell. The metal ions in a 500 μ l sample are injected into the sulfuric acid carrier stream and deposited onto an electrochemical quartz crystal microbalance (EQCM) electrode housed in a 50 μ l flow cell. The deposits are subsequently stripped off electrochemically in the same cell and analyzed downstream in an ICP-OES. The stripped metal layer was found to be composed of Ag with no detectable Cu for a redox replacement time of 10 s, and 91 wt.% Ag–9 wt.% Cu for a redox replacement time of 5 s. Microscopy measurements demonstrated that the electrode was covered with silver particles, some of which contain Cu in the case of the 5 s replacement time. This technique allowed the study of mass changes on the electrode during electrodeposition and open circuit times in each EDRR cycle in flowing solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A unified non-equilibrium phase change model for injection flow modeling

The homogenous relaxation model (HRM) is one of the most widely used models to describe the liquid- gas phase transition. However, in its original formulation, it is unable to handle multispecies vapor-liquid equilibrium (VLE), which limits its applicability to single-component fluids. In this work, a unified non-equilibrium phase change model that considers the VLE of multicomponent mixtures is proposed building upon the HRM's structure. A time factor is introduced to mimic the effect of different phase change timescales due to different mechanisms, e.g., cavitation, flash-boiling, and evaporation. Here to assess the model's performance, computational fluid dynamics simulations of the internal and near-nozzle injection flow of the Engine Combustion Network's Spray G injector were performed using the nine-component PACE-20 fuel with both the unified model and the original HRM. The predicted fuel density in the near-nozzle region matched well with X-ray tomography measurements. The simulation results indicated that, whereas the HRM failed to capture the vaporization due to convective mixing between the fuel and ambient gas, the unified model performed well in predicting the mixing-driven vaporization and the corresponding evaporative cooling. Further comparisons using the nine-component fuel formula and a single-component fuel surrogate demonstrated the unified model's ability to predict preferential vaporization, which affects the predictions of local mixture composition and rate of vaporization. Finally, it is shown that the unified model is capable of representing multiple phase change mechanisms, and the relaxation time factor plays an important role in determining the degree of phase change due to the different mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Co-flow injection for serial crystallography at X-ray free-electron lasers

Serial femtosecond crystallography (SFX) is a powerful technique that exploits X-ray free-electron lasers to determine the structure of macromolecules at room temperature. Despite the impressive exposition of structural details with this novel crystallographic approach, the methods currently available to introduce crystals into the path of the X-ray beam sometimes exhibit serious drawbacks. Samples requiring liquid injection of crystal slurries consume large quantities of crystals (at times up to a gram of protein per data set), may not be compatible with vacuum configurations on beamlines or provide a high background due to additional sheathing liquids present during the injection. Proposed and characterized here is the use of an immiscible inert oil phase to supplement the flow of sample in a hybrid microfluidic 3D-printed co-flow device. Co-flow generation is reported with sample and oil phases flowing in parallel, resulting in stable injection conditions for two different resin materials experimentally. A numerical model is presented that adequately predicts these flow-rate conditions. The co-flow generating devices reduce crystal clogging effects, have the potential to conserve protein crystal samples up to 95% and will allow degradation-free light-induced time-resolved SFX.

3D printing↗
DOE OSTI2024

Systems and methods for geothermal energy storage

A method and system may be used for storing energy in a geothermal system and recovering both the stored energy as well as thermal energy on demand. The geothermal system may include injection and production wells that are hydraulically coupled in a geothermal energy reservoir that behaves as a confined reservoir system with thermal energy transferring to fluid injected into the injection well and removed via the production well. Injection flow rate, injection pressure, production flow rate, production backpressure, or fluid residence time may be managed to control energy consumption or energy generation profiles of the geothermal system. During an energy storage mode, the injection flow rate exceeds the production flow rate thereby storing energy in the geothermal reservoir. During an energy recovery mode, production backpressure is reduced thereby releasing the stored energy and electricity is generated by removing the thermal energy from the fluid in a heat engine.

Norbeck, Jack↗
DOE OSTI2021

Hydraulic and Thermal Stimulation Program at Raft River Idaho, A DOE EGS

A Department of Energy Enhanced Geothermal System (EGS) stimulation program has injected over 254 million gallons of water into the well RRG-9 ST1 since the summer of 2013. Three major stimulations have been conducted during the program increasing injection flow rates from less than 20 gpm to 550 gpm. Geologic, water chemistry, microseismic activity, and borehole imaging data have been used to develop a conceptual model describing possible flow paths of this injected water. This model contains two major fracture zones one of which intersects the RRG-9 ST1 wellbore. Modified Hall and injectivity index plots constructed using injection flow rates, surface temperatures, and wellhead pressures show steady improvement in the injectivity of the well. Here, the injectivity index has risen from 0.15 gpm/psi to 2.0 gpm/ psi. A pressure falloff test conducted on April 28, 2015 indicates a reservoir permeability of 1,220 md and -5.38 skin factor. The well stimulation program was simulated numerically using an Idaho National Laboratory reservoir simulation code, FALCON. These simulations show a significant increase in the permeability of connecting fracture pathways after each stimulation event.

Enhanced geothermal system↗
DOE OSTI2026

Total Dissolved Nitrogen and Ammonia Data for the East River Watershed, Colorado (2015-2025)

This data package contains mean values for total dissolved nitrogen (TDN) and ammonia concentrations for water samples taken from the East River Watershed in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. TDN was analyzed using a Shimadzu Total Nitrogen Module (TNM-1) combined with the TOC-VCSH analyzer (Shimadzu Corporation, Japan). TNM-1 is a non-specific measurement of total nitrogen (TN). All nitrogen species in samples are combusted to nitrogen monoxide and nitrogen dioxide, then reacted with ozone to form an excited state of nitrogen dioxide. Upon returning to ground state, light energy is emitted. Then, TDN is measured using a chemiluminescence detector. Ammonia was determined using a Lachat's QuikChem 8500 Series 2 Flow Injection Analysis System (LACHAT Instruments, QuckChem 8500 series 2, Automated Ion Analyzer, Loveland, Colorado). When ammonia in water samples is heated (60 degrees C) with salicylate and hypochlorite in an alkaline phosphate buffer, an emerald green color is produced which is proportional to the ammonia concentration. The color is intensified by the addition of nitroprusside. Ethylenediaminetetraacetic acid (EDTA) is added to the buffer to prevent the interference of metal ions (Ca, Mg, and Fe etc.). Ammonia-N is then determined by LACHAT flow injection and a colorimetric assay at an absorbance wavelength 660 nm. (Reference: LACHAT Instruments: QuickChem Method 90-107-06-3-A, Determination of Ammonia by Flow Injection Analysis (High Throughput, Salicylate Method/DCIC) (Multi Matrix method). Written by Lynn Egan (Application group), February 08, 2011.) All files are labeled by location and variable, and data reported are the mean values upon replicate measurements. All samples were analyzed under a rigorous quality assurance and quality control (QA/QC) process as detailed in the methods. This data package contains (1) a zip file (tdn_ammonia_data_2015-2025.zip) containing a total of 299 files: 298 data files of ammonia and TDN data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v7_20260901_flmd.csv) file that lists each file contained in the dataset with associated metadata; (3) a data dictionary (v7_20260901_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type; (4) PDF and docx files for the determination of Method Detection Limits (MDLs) for TDN data, which has been updated in 2026-08; and (5) PDF and docx files for the detemination of Method Detection Limits (MDLs) for Ammonia and the Interferences by LACHAT Flow Injection Analysis. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 105 locations containing TDN and Ammonia-N data. Update 2020-10-07: Updated the data files to remove times from the timestamps, so that only dates remain. The data values have not changed. Update 2021-04-11: Added Determination of Method Detection Limits (MDLs) for DIC, NPOC and TDN Analyses and Determination of Method Detection Limit for Ammonia and the Interferences by LACHAT Flow Injection Analysis documents, which can be accessed as PDFs or with Microsoft Word.Update on 6/10/2022: versioned updates to this dataset was made along with these changes: (1) updated total dissolved nitrogen and ammonia data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) restructure of units to comply with CSV reporting format requirements, (5) added -9999 for empty numerical cells, and (6) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2022-12-20: Updates were made to both the data files and reporting format specific files. Units were listed incorrectly, but have been fixed to reflect correct units (ug/L). File level metadata (flmd) and data dictionary (dd) files were updated to reflect the updated versions of these files. Available data was added up until 2022-06-01. Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-01-05. The file level metadata and data dictionary files were updated to reflect the additional data added. Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-10-27. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added. Revised versions of the PDF and docx files for determination of MDLs for TDN were added to replace previous versions. Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available TDN and Ammonia-N data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added. Update on 2026-09-01: Updates were made to both the data files and reporting format specific files. New available TDN and Ammonia-N data was added, up until the end of WY2025 (September 30, 2025). Updated versions, as of 2026-08-10, of the PDF and docx files for determination of MDLs for TDN data were added to this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Observations of phase changes in monoolein during high viscous injection

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

The effect of foam quality, particle concentration and flow rate on nanoparticle-stabilized CO 2 mobility control foams

CO 2 foam is regarded as a promising technology and widely used in the oil and gas industry, not only to improve oil production, but also to mitigate carbon emissions through their capture. This paper describes a series of nanoparticle-stabilized CO 2 foam generation and foam flow experiments under reservoir conditions. Stable CO 2 foam was generated when CO 2 and a nanosilica dispersion flowed through the core sample under 1500 psi and 25 °C. The foam changed from a fine-texture foam to a coarse foam as the foam quality increased from 20% to 95%. Foam mobility increased slightly with the increasing foam quality from 20% to 80% and then rapidly from 80% to 95%. A stable CO 2 foam was generated as the nanosilica concentration increased to 2500 ppm. Foam mobility and resistance factor increased with the increasing nanosilica concentration. As the injection flow rate increased to 60 ml h -1 , stable and fine-texture CO 2 foam was obtained. Foam mobility was observed to remain almost constant as the injection flow rate increased from 60 ml h -1 to 150 ml h -1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Real-time Intrusion Detection for High-bandwidth Research Networks using Unsupervised Deep Learning

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks across distributed collaboration sites for processing, storage, and analysis. Like general purpose networks, research networks experience attacks. However, monitoring traffic in such high-bandwidth network environments is challenging with conventional deep packet inspection (DPI)- based network intrusion detection systems (NIDS). Recently, machine learning (ML) algorithms have shown potential in detecting anomalous patterns with better generalizability and faster speed. Compared to the general purpose networks, traffic movement in research network is less volatile and more likely to benefit from the ML-based anomaly analysis. We present ThunderSecure, an efficient AI-powered system for detecting anomalies in 100G research networks. ThunderSecure implements a high-throughput packet processing infrastructure using multi-cores and GPUs. It takes time-series statistics from a variety of network measurements and uses 2D Convolutional Neural Network (CNN) to explore both spatial and temporal dependencies in network data stream. Patterns of science data traffic are learned with a one-class neural network, which blends an Adversarial Autoencoder (AAE) with Gaussian mixture density estimation. Testing traffic flows exhibiting significant deviations from the learned baseline of normality are marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets recorded from a 100G research network at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. To the best of our knowledge, this is the first ML work in the area of network anomaly detection that has been validated on such extreme scale datasets. Results show that ThunderSecure can recognize science data traffic that are captured long after the training and make nearly certain detection on those with anomalous flows injected, even in the case when the anomaly-to-normal mixing ratio is 0.1%.

Gong, Qian↗
DOE OSTI2020

Overview of lithium injection and flowing liquid lithium results from the US–China collaboration on EAST

A multi-institutional team consisting of national labs and universities has been conducting research to understand and control the plasma-material interface (PMI) to improve long pulse discharge control and performance in the EAST device in Hefei, China. One particular focus of the group has been to evaluate the performance of different plasma-facing component (PFC) technologies and materials, particularly lithium. Flowing liquid lithium PFC technologies are currently into their third generation of development and deployment in EAST, demonstrating recycling control and mitigation of edge-localized modes (ELMs). A lithium powder dropper has also been used to control ELMs while a lithium granule injector has demonstrated ELM triggering and pacing. To support this work, the facilities at the Center for Plasma Material Interactions such as HIDRA are being commissioned and utilized to develop/test the technologies before deployment on EAST. This paper will present a summary of the collaborative lithium PMI program on EAST.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Aero-thermal numerical characterization of blunt fin-induced shock wave–boundary layer interaction and its control through leading-edge cooling injection

This study represents a novel evaluation of active flow control to alleviate the aerothermal penalties created by the blunt fin-induced shock wave–boundary layer interaction. The manuscript analyzes the effect of flow injection on a blunt fin-induced shock wave–boundary layer interaction via computational fluid dynamics simulations with various degrees of resolution. The impact on the mean flow topology and wall variables was investigated utilizing Reynolds-averaged Navier–Stokes simulations. Detached-eddy simulations revealed the low-frequency shock motion, shock wave–boundary layer, and horseshoe vortex interaction. The test article was exposed to two different incoming boundary layer thicknesses; the thicker boundary layer led to the appearance of larger turbulent scales. The Detached-eddy simulations revealed the time history of the shock wave–boundary layer interaction, focusing on the inception and development of the recirculated flow regions. Ultimately, spectral proper orthogonal decomposition was employed to identify the structures associated with the low-frequency shock motion caused by the shock wave–boundary layer interaction.

Lozano, Francisco (ORCID:0000000277871125)↗
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗
DOE OSTI2020

Airfoil leading edge blowing to control bow shock waves

Abstract This manuscript presents a detailed characterization of active control of bow shock waves via leading edge injection, including subsonic coolant ejection and the appearance of Coanda effects. The flow phenomena occurring at steady and pulsating flow injection regimes were analyzed using steady and unsteady two-dimensional Reynolds-Averaged Navier Stokes, leading to a precise evaluation of the thermal load and drag reductions. Steady supersonic injection yields the largest abatement in thermal load and aerodynamic drag, while subsonic or fluctuating ones can also provide significant improvements at reduced cooling mass flow rates. Furthermore, a Coanda effect, causing a non-symmetric flow topology, was observed and analyzed for reduced injection port size. This Coanda effect is due to the sudden expansion happening from the injection port to the main flow and it causes the flow topology at the leading edge to become non-symmetric despite the complete symmetry of the problem. This is the first time in the literature such a phenomenon is documented for a supersonic airfoil leading edge injection. Furthermore, it enables the design of novel flow control strategies for the leading edge shock topology and flow structures in supersonic flows.

42 ENGINEERING↗
DOE OSTI2020

Leveraging operational information from wastewater injection wells to evaluate CO 2 injection performance for carbon storage applications in the Appalachian Basin

Abstract Geologic parameters, geophysical logging, injection testing, and operational metrics from wastewater injection wells were integrated to develop a preliminary design of a carbon storage facility in the Appalachian Basin. A scattered group of 10–20 commercial wastewater injection wells dispose off produced water from oil and gas wells in the region, utilizing a sequence of stacked deep saline formations for injection zones. These wastewater injection wells provide practical benchmarks for understanding the feasibility of carbon dioxide (CO 2 ) storage. Geologic models were developed based on characterization data from the wastewater injection wells. Reservoir simulations were calibrated according to injection testing and operational data from the wastewater injection wells. Long‐term operational data on injection flow rates and pressures measured in the wastewater injection wells were especially useful to evaluate the performance of carbon storage applications. The simulations were used to estimate injection pressures, radius of CO 2 saturation, and pressure response for industrial scale CO 2 storage applications. Results were also used to provide a design basis in terms of number of injection wells, well spacing, area of review, injection system components, monitoring plan, and CO 2 pipeline distribution system. The analysis demonstrates that there is sufficient injectivity in the deep saline formations in the west‐central Appalachian Basin to store commercial volumes of anthropogenic CO 2 . The geologic system appears suitable for supporting CO 2 injection rates of 0.5–1.0 million metric tons per year at injection pressures below formation fracture pressure in a single well. The long‐term operational data of wastewater injection wells within the study area suggested a lower permeability‐thickness values than indicated by initial reservoir tests. A workflow for developing realistic permeability values for input into reservoir simulations is presented. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

Valluri, Manoj↗
DOE OSTI2025

Multimode turbulent flow measurements using magnetic resonance imaging- and laser-based techniques and computational fluid dynamics simulations

We studied the flow field characteristics of a turbulent flow over a regularized cube array with a perpendicular injection flow through the floor between the second and third cubical elements, representing the complex flow interactions of a 3D jet and the wake flows behind cubical obstacles. Four different experimental measurements were performed: two magnetic resonance imaging-based measurements for three-dimensional three-component velocity (MRV) and concentration (MRC) and two laser-based techniques, particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), for two-dimensional two-component velocity and concentration measurement, respectively. The mainstream Reynolds number is Re = 15 000⁠, based on the primary inlet velocity U m and channel height D H ⁠, whereas the injector Reynolds number is Re j = 3400⁠, based on the injector velocity U j and the injector's exit width D j ⁠. Numerical simulations were performed for the studied flow configuration of turbulent flow over a regularized cube array using Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulation (LES) approaches. Results obtained from experimental measurements—including MRV, MRC, PIV, and PLIF—as well as RANS and LES simulations are discussed and compared along several horizontal and vertical planes of the studied configuration. In addition, 3D turbulent flow structures, such as leading-edge vortex, horseshoe vortex, and jet shear-layer vortex, and the isosurfaces of scalar concentration successfully revealed by MRV and MRC techniques were found to be in very good agreement with those 3D features extracted from RANS and LES simulations. In conclusion, the high-resolution experimental and numerical database obtained from this study could be useful for validation and verification of numerical codes.

Computational fluid dynamics↗