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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct-electron detection. An electron probe size down to 0.5 nm in diameter is used and the sample investigated is a gold–palladium nanoparticle catalyst. Computational analysis of the 4D-STEM data sets is performed using a disk registration algorithm to identify the diffraction peaks followed by feature learning to map the individual grains. Two unsupervised feature learning techniques are compared: principal component analysis (PCA) and non-negative matrix factorization (NNMF). The characteristics of the PCA versus NNMF output are compared and the potential of the 4D-STEM approach for statistical analysis of grain orientations at high spatial resolution is discussed.

47 OTHER INSTRUMENTATION↗
NASA NTRS1994

Sea-Ice Feature Mapping using JERS-1 Imagery

JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

Maslanik, James↗
DOE OSTI2025

Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations

Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.

Arctic tundra↗
DOE OSTI2021

Radio Morphology of Red Geysers

We present 150 MHz, 1.4 GHz, and 3 GHz radio imaging (LoTSS, FIRST, and VLASS) and spatially resolved ionized gas characteristics (SDSS IV-MaNGA) for 140 local ($z$ < 0.1) early-type red geyser galaxies. These galaxies have a low star formation activity (with a star formation rate, SFR, ~ 0.01 $M$ ⊙ yr -1 ) but show unique extended patterns in spatially resolved emission-line maps that have been interpreted as large-scale ionized winds driven by active galactic nuclei (AGN). In this work, we confirm that red geysers host low-luminosity radio sources ($L$ 1.4GHz ~ 10 22 $WHz$ -1 ). Out of 42 radio-detected red geysers, 32 are spatially resolved in LoTSS and FIRST, with radio sizes varying between ~5–25 kpc. Three sources have radio sizes exceeding 40 kpc. A majority display a compact radio morphology and are consistent with either low-power compact radio sources (FR0 galaxies) or radio-quiet quasars. They may be powered by small-scale AGN-driven jets that remain unresolved at the current 5'' resolution of radio data. The extended radio sources, not belonging to the "compact" morphological class, exhibit steeper spectra with a median spectral index of -0.67, indicating the dominance of lobed components. Furthermore, the red geysers hosting extended radio sources also have the lowest specific SFRs, suggesting they either have a greater impact on the surrounding interstellar medium or are found in more massive halos on average. The degree of alignment of the ionized wind cone and the extended radio features are either 0° or 90°, indicating possible interaction between the interstellar medium and the central radio AGN.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2020

Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

NISAR↗
DOE OSTI2022

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗
NASA NTRS1977

A hot wire radiant energy source for mapping the field of view of a radiometer

The design and performance of a calibration device that allows the measurement of a radiometer's field of view are described. The heart of the device is a heated 0.0254-mm (0.001-inch) diameter filament that provides a variable, isothermal line source of radiant energy against a cold background. By moving this discrete line source across the field of view of a radiometer, the radiometer's spatial response can be completely mapped. The use of a platinum filament provides a durable radiation source whose temperature is stable and repeatable to 10 K over the range of 600 to 1200 K. By varying the energy emitted by the filament, the field of view of radiometers with different sensitivities (or multiple channel radiometers) can be totally mapped.

Edwards, S. F.↗
NASA NTRS2017

Atmospheric Waves and Dynamics Beneath Jupiters Clouds from Radio Wavelength Observations

We observed Jupiter at wavelengths near 2 cm with the Karl G. Jansky Very Large Array (VLA) in February 2015. These frequencies are mostly sensitive to variations in ammonia abundance and probe between approx. 0.5- 2.0 bars of pressure in Jupiters atmosphere; within and below the visible cloud deck which has its base near 0.7 bars. The resultant observed data were projected into a cylindrical map of the planet with spatial resolution of approx. 1500 km at the equator. We have examined the data for atmospheric waves and observed a prominent bright belt of radio hotspot features near 10 N, likely connected to the same equatorial wave associated with the 5-m hotspots. We conducted a passive tracer power spectral wave analysis for the entire map and latitude regions corresponding to eastward and westward jets and compare our results to previous studies. The power spectra analysis revealed that the atmosphere sampled in our observation (excluding the NEB region) is in a 2-D turbulent regime and its dynamics are predominately governed by the shallow water equations. The Great Red Spot (GRS) is also very prominent and has a noticeable meridional asymmetry and we compare it, and nearby storms, with optical images. We find that the meridional radio profile has a global north-south hemisphere distinction and find correlations of it to optical intensity banding and to shear zones of the zonal wind profile over select regions of latitude. Amateur optical images taken before and after our observation complemented the radio wave- length map to investigate dynamics of the equatorial region in Jupiters atmosphere. We find that two radio hotspots at 2 cm are well correlated with optical plumes in the NEB, additionally revealing they are not the same 5 m hotspot features correlated with optical dark patches between adjacent plumes. This analysis exploits the VLAs upgraded sensitivity and explores the opportunities now possible when studying gas giants, especially atmospheric dynamics of layers beneath upper level clouds.

radio observations↗
DOE OSTI2024

Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis

Abstract The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant–fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions. Here we used single-nucleus and spatial RNA sequencing to explore both Medicago truncatula and Rhizophagus irregularis transcriptomes in AM symbiosis at cellular and spatial resolution. Integrated, spatially registered single-cell maps revealed infected and uninfected plant root cell types. We observed that cortex cells exhibit distinct transcriptome profiles during different stages of colonization by AM fungi, indicating dynamic interplay between both organisms during establishment of the cellular interface enabling successful symbiosis. Our study provides insight into a symbiotic relationship of major agricultural and environmental importance and demonstrates a paradigm combining single-cell and spatial transcriptomics for the analysis of complex organismal interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

MAMS - A high spatial resolution multispectral scanner

The Multispectral Atmospheric Mapping Sensor (MAMS) is an airborne scanner which collects imagery in eight visible and three IR bands, with ground resolution of 100 m at a nominal aircraft altitude of 20 km. The visible channels provide continuous spectral coverage from 0.42 to 1.05 microns, and the IR channels measure upwelling and reflected radiation at combinations of 3.7, 6.5, 11.1, and 12.5 microns. These include channels nearly identical to the Landsat TM channels 1-4, and similar to those on the VISSR Atmospheric Sounder (VAS) and AVHRR instruments. The high spatial resolution permits investigation of surface thermal and atmospheric water vapor structure at scales not available from current stabilities. Significant modifications have been made since engineering flights in 1985 to improve the radiometric performance. The increased data quality and recent multidisciplinary applications of this data are presented.

Atkinson, Robert J.↗
NASA NTRS2005

Statistical Considerations of Data Processing in Giovanni Online Tool

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Suhung, Shen↗
NASA NTRS1994

Distribution of materials excavated by the lunar crater Bullialdus and implications for the geologic history of the Nubium region

Previous spectroscopic studies of the lunar crater Bullialdus, located in the Nubium Basin, indicated an unusual stratigraphy of two gabbroic layers overlying a noritic unit. The possible existence of a layered mafic pluton at Bullialdus was suggested. To investigate the geologic context with more detailed spatial information, charge-coupled device (CCD) images of Bullialdus were obtained using eight filters. A linear mixing model was used to investigate the fractional abundances of spectral end-members chosen from within the multispectral image. Since the reflectance properties of lunar materials over this wavelength range are sensitive to variations in composition and soil maturity, fractional abundance images were used to create a new geologic map of the crater. The spatial relationships of the surface materials confirm the previously inferred stratigraphy, and further reveal the central peaks to exhibit two distinct compositional units: noritic anorthosite and anorthositic norite. Three models for the origin of the observed stratigraphy are considered: Bullialdus has excavated stratigraphic units containing (1) early mare basalt overlying anorthositic-noritic crustal material, (2) part of a layered mafic pluton, and/or (3) part of an impact melt sheet formed by the Nubium Basin impact event.

Tompkins, Stefanie↗
NASA NTRS1996

Evolutionary status of the pre-protostellar core L1498

L1498 is a classic example of a dense cold pre-protostellar core. To study the evolutionary status, the structure, dynamics, and chemical properties of this core we have obtained high spatial and high spectral resolution observations of molecules tracing densities of 10(3)-10(5) cm-3. We observed CCS, NH3, C3H2, and HC7N with NASA's DSN 70 m antennas. We also present large-scale maps of C18O and 13CO observed with the AT&T 7 m antenna. For the high spatial resolution maps of selected regions within the core we used the VLA for CCS at 22 GHz, and the Owens Valley Radio Observatory (OVRO) MMA for CCS at 94 GHz and CS (2-1). The 22 GHz CCS emission marks a high-density [n(H2) > 10(4) cm -3] core, which is elongated with a major axis along the SE-NW direction. NH3 and C3H2 emissions are located inside the boundary of the CCS emission. C18O emission traces a lower density gas extending beyond the CCS boundary. Along the major axis of the dense core, CCS, NH3 and C3H2 emission show evidence of limb brightening. The observations are consistent with a chemically differentiated onion-shell structure for the L1498 core, with NH3 in the inner and CCS in the outer parts of the core. The high angular resolution (9"-12") spectral line maps obtained by combining NASA Goldstone 70 m and VLA data resolve the CCS 22 GHz emission in the southeast and northwest boundaries into arclike enhancements, supporting the picture that CCS emission originates in a shell outside the NH3 emitting region. Interferometric maps of CCS at 94 GHz and CS at 98 GHz show that their emitting regions contain several small-scale dense condensations. We suggest that the differences between the CCS, CS, C3H2, and NH3 emission are caused by a time-dependent effect as the core evolves slowly. We interpret the chemical and physical properties of L1498 in terms of a quasi-static (or slowly contracting) dense core in which the outer envelope is still growing. The growth rate of the core is determined by the density increase in the CCS shell resulting from the accretion of the outer low-density gas traced by C18O. We conclude that L1498 could become unstable to rapid collapse to form a protostar in less than 5 x 10(6) yr.

NASA Discipline Exobiology↗
NASA NTRS2011

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR data

A novel method for enhancement of the spatial resolution of 3-dimensional Flash Lidar images is being proposed for generation of elevation maps of terrain from a moving platform. NASA recognizes the Flash LIDAR technology as an important tool for enabling safe and precision landing in future unmanned and crewed lunar and planetary missions. The ability of the Flash LIDAR to generate 3-dimensional maps of the landing site area during the final stages of the descent phase for detection of hazardous terrain features such as craters, rocks, and steep slopes is under study in the frame of the Autonomous Landing and Hazard Avoidance (ALHAT) project. Since single frames of existing FLASH LIDAR systems are not sufficient to build a map of entire landing site with acceptable spatial resolution and precision, a super-resolution approach utilizing multiple frames has been developed to overcome the instrument s limitations. Performance of the super-resolution algorithm has been analyzed through a series of simulation runs obtained from a high fidelity Flash LIDAR model and a high resolution synthetic lunar elevation map. For each simulation run, a sequence of FLASH LIDAR frames are recorded and processed as the spacecraft descends toward the landing site. Simulations runs having different trajectory profiles and varying LIDAR look angles of the terrain are also analyzed. The results show that adequate levels of accuracy and precision are achieved for detecting hazardous terrain features and identifying safe areas of the landing site.

Bulyshev, Alexander↗
DOE OSTI2025

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking

As photometric surveys reach unprecedented statistical precision, systematic uncertainties increasingly dominate large-scale structure probes relying on galaxy number density. Defining the final survey footprint is critical, as it excludes regions affected by artefacts or suboptimal observing conditions. For galaxy clustering, spatially varying observational systematics, such as seeing, are a leading source of bias. Template maps of contaminants are used to derive spatially dependent corrections, but extreme values may fall outside the applicability range of mitigation methods, compromising correction reliability. The complexity and accuracy of systematics modelling depend on footprint conservativeness, with aggressive masking enabling simpler, robust mitigation. We present a unified approach to define the DES Year 6 joint footprint, integrating observational systematics templates and artefact indicators that degrade mitigation performance. This removes extreme values from an initial seed footprint, leading to the final joint footprint. By evaluating the DES Year 6 lens sample MagLim++ plus plus on this footprint, we enhance the Iterative Systematics Decontamination (ISD) method, detecting non-linear systematic contamination and improving correction accuracy. While the mask's impact on clustering is less significant than systematics decontamination, it remains non-negligible, comparable to statistical uncertainties in certain w(theta) scales and redshift bins. Supporting coherent analyses of galaxy clustering and cosmic shear, the final footprint spans 4031.04 deg2, setting the basis for DES Year 6 1x2pt, 2x2pt, and 3x2pt analyses. This work highlights how targeted masking strategies optimise the balance between statistical power and systematic control in Stage-III and -IV surveys.

Rodríguez-Monroy, M. [Madrid, IFT; IJCLab, Orsay]↗
NASA NTRS1978

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

Tom, C.↗
NASA NTRS1984

Using spatial logic in classification of Landsat TM data

A strategy for spatial/spectral classification of Landsat TM data is presented. The strategy is founded upon 'spatial logic', a logic that seeks to emulate important aspects of visual image interpretation. The carefully structured classification process begins with spectral stratification of the data into water, vegetated and non-vegetated pixels. A region growing algorithm is then used to define 'fields' of similar land cover composition. Fields are characterized by cover composition, size and neighborhood characteristics. A supervised iterative contextual classification algorithm is developed to assign final land use/land cover labels. Maps are generalized using a spatial post-processing technique. Positive, though preliminary, results are presented.

Merchant, J. W.↗
DOE OSTI2019

Experimental and Computational Analysis of NEAMS Pebble Bed Reactors

The Advanced High-Temperature Pebble Bed Reactor concept leverages a particle-based fuel format consisting of discrete spherical graphite pebbles arrayed in a packed bed architecture. Thermal regulation achieved via flow of gas (e.g., helium) or liquid (e.g., molten salt) coolants through the void spaces between pebbles in the bed (characteristic pebble diameters: ~ 6 cm, gas cooled; ~ 3 cm, liquid cooled). This design is of interest owing to inherent advantages including passive safety features and highly efficient heat transfer characteristics that enable high power densities to be achieved. Fully leveraging these advantages requires a fundamental understanding of the complex coolant flow structure within the pebble-shaped fuel bed. Unfortunately, complexities associated with non-invasively probing the micro-scale flow phenomena within the complex network of void spaces between pebbles have hindered efforts to characterize the underlying transport phenomena. Without this fundamental foundation, it becomes challenging to rationally construct macroscopic transport models based upon volume averages of micro-scale parameters that accurately capture the observed flow behavior. Consequently, this lack of fundamental knowledge has limited previous work to coarse comparisons between theory and extremely limited experimental data. Moreover, these comparisons have been made only in terms of integral or macroscopic results. Therefore, multipoint measurements with a high level of spatial and temporal resolution are critically needed to fully map the complex flow patterns and to provide data at high spatial density to permit accurate volume averaging in the pebble bed. For this project, we performed a coordinated experimental and computational effort to quantitatively map the full-field velocity and temperature fields in the interstitial spaces within the pebble bed. The major accomplishments of this project included the important knowledge acquired for the flow mixing and heat transfer in the interstitial pore scales, the effects of flow mixing in the near-wall and far-wall regions, and the by-pass flows of pebble bed systems. The produced high-resolution experimental data (not broadly available in existing literature) were then used for the numerical studies enabling the refinement and validation of standard simulation tools (Nek5000).

42 ENGINEERING↗