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DEM Quality Evaluation Framework
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Comparison of different DEMs for hydrological studies in the mountainous areas
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Qualitative Benchmarking of a Developmental CFD-DEM Code
Presented by NETL at ASME V&V Virtual Symposium, 05/20
CFD-DEM Simulations of Reacting Fluidized Beds with MFIX-Exa
SIAM Conference on Parallel Processing for Scientific Computing, Virtual, February 23-26, 2022
PIV and CFD-DEM simulation of gas jet fluidization of a 1mm ceramic particle bed
Video recording of presentation
Insight into premixed diethoxymethane flames: Laminar burning velocities, temperatures, and emissions behaviour
Diethoxymethane ((CH 3 CH 2 O) 2 CH 2 , DEM) is a promising carbon-neutral fuel. DEM is a diether or acetal with a molecular structure similar to oxymethylene ethers (CH 3 O–(CH 2 O)n–CH 3 , OME n ). Thus, DEM can be expected to have a similar combustion behavior to OMEs, reducing harmful emissions such as NO x and particulate matter (PM) in internal combustion engines. From both experimental and kinetic modeling, fundamental studies on DEM are scarce in the literature. More studies are required to gain a detailed insight into the oxidation kinetics of DEM. Laminar burning velocity (LBV) is a critical property that allows a detailed assessment of the potential application of DEM in combustion devices. Unfortunately, the literature on the LBV of DEM is limited. Therefore, in this study we have investigated the LBV of DEM using two reactors for the first time, namely a heat flux burner and a combustion chamber. The experimental data is reported for equivalence ratio between 0.7 and 1.7, initial temperatures of 368–423 K, and initial pressure of 1–5 bar. In addition, we developed a detailed kinetic model extending our recent work of Shrestha et al. (Combust. Flame. 246 (2022) 112,426) to characterize the combustion behavior of DEM utilizing the new experimental data from this work and the literature data. Our model performs remarkably well in capturing the newly measured LBV experimental data over various experimental conditions. We found that DEM and dimethoxy methane (DMM) have similar values of LBVs (within ±1.5 cm/s) for a given condition, which indicates that intermediate chemistry governs the flame chemistry. Despite DEM being a larger molecule that is expected to have slightly lower LBVs than DMM, its effect on the measured values of LBVs is negligible. Finally, we experimentally measured NO x formation in DEM flame for the first time. The stochiometric flame has the highest NO x formation. The proposed model predicted the equivalence ratio dependence of NO x nicely. However, it overestimates the NO x formation for stoichiometric DEM/air mixtures by ~30 %. The model suggests that the thermal NO formation route is favored at lean and stochiometric conditions. In contrast, the prompt NO formation route is enhanced for rich mixtures.
The New Landsat Collection-2 Digital Elevation Model
The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset(NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from theCollection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 meters was measured. By using theses improved vertical values in a line of sight algorithm, horizonta improvements were noted in some of the most mountainous regions over multiple 30-meter Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.
Digital Elevation Models: Terminology and Definitions
Abstract:Digital elevation models (DEMs) provide fundamental depictions of the three-dimensionalshape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record theinterface between the atmosphere and the lithosphere using a discrete two-dimensional grid, withcomplexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere.The treatment of DEM surfaces, affected by these intervening spheres, depends on their intendeduse, and the characteristics of the sensors that were used to create them. DEM is a general term,and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) recordthe treatment of the intermediate surfaces. Several global DEMs generated with optical (visible andnear-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars andproducts of satellite altimetry, share the common characteristic of a georectified, gridded storagestructure. Nevertheless, not all DEMs share the same vertical datum, not all use the same conventionfor the area on the ground represented by each pixel in the DEM, and some of them have variable dataspacings depending on the latitude. This paper highlights the importance of knowing, understandingand reflecting on the sensor and DEM characteristics and consolidates terminology and definitions ofkey concepts to facilitate a common understanding among the growing community of DEM users,who do not necessarily share the same background
Applicability of discrete element method with spherical and clumped particles for constitutive study of granular materials
Discrete element method (DEM) has been intensively used to study the constitutive behaviour of granular materials. However, to what extent a real granular material can be reproduced by virtual DEM simulations remains unclear. This study attempts to answer this question by comparing DEM simulations with typical features of experimental granular materials. Three groups of models with spherical and clumped particles are investigated from four perspectives: (i) deviatoric stress and volumetric behaviour; (ii) critical state behaviour; (iii) stress-dilatancy relationship; and (iv) the evolution of principal stress ratio against axial strain. The results demonstrate that DEM with spherical or clumped particles is capable of qualitatively describing macroscopic deviatoric stress responses, volumetric behaviour, and critical state behaviour observed in experiments for granular materials. On the other hand, some qualitative deviations between experiments and the investigated DEM simulations are also observed, in terms of the stress-dilatancy behaviour and principal stress ratio against axial strain, which are proven to be critical for constitutive modelling. The results demonstrate that DEM with spherical or clumped particles may not necessarily fully capture experimental features of granular materials even from a qualitative perspective. It is thus encouraged to thoroughly validate DEM with experiments when developing constitutive models based on DEM observations.
Flight Test Results of a Synthetic Vision Elevation Database Integrity Monitor
This paper discusses the flight test results of a real-time Digital Elevation Model (DEM) integrity monitor for Civil Aviation applications. Providing pilots with Synthetic Vision (SV) displays containing terrain information has the potential to improve flight safety by improving situational awareness and thereby reducing the likelihood of Controlled Flight Into Terrain (CFIT). Utilization of DEMs, such as the digital terrain elevation data (DTED), requires a DEM integrity check and timely integrity alerts to the pilots when used for flight-critical terrain-displays, otherwise the DEM may provide hazardous misleading terrain information. The discussed integrity monitor checks the consistency between a terrain elevation profile synthesized from sensor information, and the profile given in the DEM. The synthesized profile is derived from DGPS and radar altimeter measurements. DEMs of various spatial resolutions are used to illustrate the dependency of the integrity monitor s performance on the DEMs spatial resolution. The paper will give a description of proposed integrity algorithms, the flight test setup, and the results of a flight test performed at the Ohio University airport and in the vicinity of Asheville, NC.
Lunar Polar Illumination for Power Analysis
This paper presents illumination analyses using the latest Earth-based radar digital elevation model (DEM) of the lunar south pole and an independently developed analytical tool. These results enable the optimum sizing of solar/energy storage lunar surface power systems since they quantify the timing and durations of illuminated and shadowed periods. Filtering and manual editing of the DEM based on comparisons with independent imagery were performed and a reduced resolution version of the DEM was produced to reduce the analysis time. A comparison of the DEM with lunar limb imagery was performed in order to validate the absolute heights over the polar latitude range, the accuracy of which affects the impact of long range, shadow-casting terrain. Average illumination and energy storage duration maps of the south pole region are provided for the worst and best case lunar day using the reduced resolution DEM. Average illumination fractions and energy storage durations are presented for candidate low energy storage duration south pole sites. The best site identified using the reduced resolution DEM required a 62 hr energy storage duration using a fast recharge power system. Solar and horizon terrain elevations as well as illumination fraction profiles are presented for the best identified site and the data for both the reduced resolution and high resolution DEMs compared. High resolution maps for three low energy storage duration areas are presented showing energy storage duration for the worst case lunar day, surface height, and maximum absolute surface slope.
Building a 2.5D Digital Elevation Model from 2D Imagery
When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.
High-Accuracy Tidal Flat Digital Elevation Model Construction Using TanDEM-X Science Phase Data
This study explored the feasibility of using TanDEM-X (TDX) interferometric observations of tidal flats for digital elevation model (DEM) construction. Our goal was to generate high-precision DEMs in tidal flat areas, because accurate intertidal zone data are essential for monitoring coastal environment sand erosion processes. To monitor dynamic coastal changes caused by waves, currents, and tides, very accurate DEMs with high spatial resolution are required. The bi- and monostatic modes of the TDX interferometer employed during the TDX science phase provided a great opportunity for highly accurate intertidal DEM construction using radar interferometry with no time lag (bistatic mode) or an approximately 10-s temporal baseline (monostatic mode) between the master and slave synthetic aperture radar image acquisitions. In this study, DEM construction in tidal flat areas was first optimized based on the TDX system parameters used in various TDX modes. We successfully generated intertidal zone DEMs with 57-m spatial resolutions and interferometric height accuracies better than 0.15 m for three representative tidal flats on the west coast of the Korean Peninsula. Finally, we validated these TDX DEMs against real-time kinematic-GPS measurements acquired in two tidal flat areas; the correlation coefficient was 0.97 with a root mean square error of 0.20 m.
Assessment of a tomography-informed polyhedral discrete element modelling approach for complex-shaped granular woody biomass in stress consolidation
The design of handling equipment for granular biomass primarily requires experiments. Discrete element models (DEM) can provide designers with detailed insight into the behaviour of granular materials. However, granular biomass comprising complex-shaped particles is difficult to model with DEM. A tomography-informed DEM approach and an exhaustive assessment of the ability of the approach to predict the bulk behaviour of milled pines using experimental data is presented. Nano-CT scan was conducted to obtain 3D particle surface geometries as the basis for particle shape approximation by a polyhedral model and a sphero-polyhedral model. These models were applied in the simulation of a compressibility test. Our parametric study showed that particle Young's modulus and restitution coefficient are the two main properties influencing the simulated bulk behaviour of the DEM particles and that the level of approximating DEM particle shape for real particles is critical for accurately replicating the bulk behaviour of milled pines. The polyhedral model demonstrated better suitability than its sphero-polyhedral counterpart for modelling pine particles. The polyhedral model calibrated in a compressibility test was then applied in the simulations of a friction test without additional parameter tuning. Interlocking was dominant in the shear of bulk pine particles. Remarkably, the polyhedral model predicted the frictional behaviour of the pine particles when compared to the experimental results. The limitations of the model, as well as possible ways for enhancement, are discussed. This work provided novel insights into the suitability of complex-shaped DEM models for granular woody biomass.
Topographic hydro-conditioning to resolve surface depression storage and ponding in a fully distributed hydrologic model
Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here, in this study, we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow.
An experiment-informed discrete element modelling study of knife milling for flexural biomass feedstocks
A discrete element method (DEM) based approach is used to study the relationships between material attributes (MAs), processing parameters (PPs), and quality attributes (QAs) for the knife milling of maize stalks. An approximate DEM shape model was conceptualized based on real maize stalks and calibrated based on experimental bending test data for flexural properties (elastic bending stiffness, elastic bending angle limit, elastoplastic ratio, etc.). DEM simulations of maize stalk comminution in a Jordan Reduction Solutions (“JRS”) knife mill were performed to investigate the relationships between the MAs (maize stalk size and breakage stress limit), PPs (impeller rotational speed), and QAs (mass throughput and output particle size distribution (PSD)). The DEM results suggest that stalk length has little influence on mass throughput and PSD, whilst stalks with larger cross sections tend to generate larger sizes of milled particles given the same breakage stress limit. Both the DEM and experimental results show that faster impeller rotation (or higher power) does not necessarily generate higher throughput or smaller output PSD, especially for maize stalks of higher breakage stress limit. The correlations between these MAs, PPs and QAs are found highly stochastic, though breakage stress limit dictates mass throughput, regardless of stalk size. The DEM-predicted output particle size tended to match the experimental data with coarse PSDs based on sieve size but showed weakened fidelity with finer material, indicating the potential for further model improvement.
Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling
The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.