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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Finite grid instability and spectral fidelity of the electrostatic Particle-In-Cell algorithm

The origin of the Finite Grid Instability (FGI) is studied by resolving the dynamics in the 1D electrostatic Particle-In-Cell (PIC) model in the spectral domain at the single particle level and at the collective motion level. The spectral fidelity of the PIC model is contrasted with the underlying physical system or the gridless model. The systematic spectral phase and amplitude errors from the charge deposition and field interpolation are quantified for common particle shapes used in the PIC models. Lastly, it is shown through such analysis and in simulations that the lack of spectral fidelity relative to the physical system due to the existence of aliased spatial modes is the major cause of the FGI in the PIC model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1995

Numerical solution of the full potential equation using a chimera grid approach

A numerical scheme utilizing a chimera zonal grid approach for solving the full potential equation in two spatial dimensions is described. Within each grid zone a fully-implicit approximate factorization scheme is used to advance the solution one interaction. This is followed by the explicit advance of all common zonal grid boundaries using a bilinear interpolation of the velocity potential. The presentation is highlighted with numerical results simulating the flow about a two-dimensional, nonlifting, circular cylinder. For this problem, the flow domain is divided into two parts: an inner portion covered by a polar grid and an outer portion covered by a Cartesian grid. Both incompressible and compressible (transonic) flow solutions are included. Comparisons made with an analytic solution as well as single grid results indicate that the chimera zonal grid approach is a viable technique for solving the full potential equation.

Holst, Terry L.↗
NASA NTRS2022

Tropospheric Ozone Retrieval By A Combination of TROPOMI/S5P Measurements With BASCOE Assimilated Data

We present a new tropospheric ozone dataset based on TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P) total ozone measurements combined with stratospheric ozone data from the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by assimilating ozone observations from the Microwave Limb Sounder (MLS). The BASCOE stratospheric data are interpolated to the S5P observations and subtracted from the TROPOMI total ozone data. The difference is equal to the tropospheric ozone residual column from the surface up to the tropopause. The tropospheric ozone columns are retrieved at the full spatial resolution of the TROPOMI sensor (5.5×3.5 km 2 ) with daily global coverage. Compared to the Ozone Mapping and Profiler Suite Modern-Era Retrospective analysis for Research and Applications 2 (OMPS-MERRA-2) data, a global mean positive bias of 3.3 DU is found for the analysed period April 2018 to June 2020. A small negative bias of about −0.91 DU is observed in the tropics relative to the operational TROPOMI tropical tropospheric data based on the convective cloud differential (CCD) algorithm throughout the same period. The new tropospheric ozone data (S5P-BASCOE) are compared to a set of globally distributed ozonesonde data integrated up to the tropopause level. We found 2254 comparisons with cloud-free TROPOMI observations within 25 km of the stations. In the global mean, S5P-BASCOE deviates by 2.6 DU from the integrated ozonesondes. Depending on the latitude the S5P-BASCOE deviate from the sondes and between −4.8 and 7.9 DU, indicating a good agreement. However, some exceptional larger positive deviations up to 12 DU are found, especially in the northern polar regions (north of 70∘). The monthly mean tropospheric column and time series for selected areas showed the expected spatial and temporal pattern, such as the wave one structure in the tropics or the seasonal cycle, including a summer maximum, in the mid-latitudes.

Satellite Retrieval↗
DOE OSTI2016

87 Sr/ 86 Sr Concentrations in the Appalachian Basin: A Review

This document reviews 87 Sr/ 86 Sr isotope data across the Appalachian Basin from existing literature to show spatial and temporal variation. Isotope geochemistry presents a means of understanding the geochemical effects hydraulic fracturing may have on shallow ground substrates. Isotope fractionation is a naturally occurring phenomenon brought about by physical, chemical, and biological processes that partition isotopes between substances; therefore, stable isotope geochemistry allows geoscientists to understand several processes that shape the natural world. Strontium isotopes can be used as a tool to answer an array of geological and environmental inquiries. In some cases, strontium isotopes are sensitive to the introduction of a non-native fluid into a system. This ability allows strontium isotopes to serve as tracers in certain systems. Recently, it has been demonstrated that strontium isotopes can serve as a monitoring tool for groundwater and surface water systems that may be affected by hydraulic fracturing fluids (Chapman et al., 2013; Kolesar Kohl et al., 2014). These studies demonstrated that 87 Sr/ 86 Sr values have the potential to monitor subsurface fluid migration in regions where extraction of Marcellus Shale gas is occurring. This document reviews publicly available strontium isotope data from 39 sample locations in the Appalachian Basin (Hamel et al., 2010; Chapman et al., 2012; Osborn et al., 2012; Chapman et al., 2013; Capo et al., 2014; Kolesar Kohl et al., 2014). The data is divided into two sets: stratigraphic (Upper Devonian/Lower Mississippi, Middle Devonian, and Silurian) and groundwater. ArcMap™ (ESRI, Inc.) was used to complete inverse distance weighting (IDW) analyses for each dataset to create interpolated surfaces in an attempt to find regional trends or variations in strontium isotopic values across the Appalachian Basin. 87 Sr/ 86 Sr varies up to ~ 0.011 across the Appalachian Basin, but the current publicly available data is limited in frequency and regional extent, causing artifacts and high uncertainty when interpolating data for locations far from sampling sites. These factors highlight the need for additional strontium isotope sampling across the region. Identifying potential contamination from hydraulic fracturing fluid in Appalachian Basin groundwater using strontium isotopes would require additional sampling. For a more comprehensive strontium isotope database, samples would need to be collected during prefracturing, syn-fracturing, and post-fracturing stages. This would add a temporal component to the spatial data and make tracing of fluid migration with strontium isotopes more accurate. Future research and modeling that incorporates subsurface geology and watershed data would also serve to increase the accuracy and certainty of the interpolations of these analyses. Prospective geospatial Appalachian Basin isotope studies would also benefit from the integration of geologic mapping because surface and subsurface geology influences observed strontium isotope values.

58 GEOSCIENCES↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part I - Analysis with a Small Sample Size

Computer simulations, especially of complex phenomena, can be expensive, requiring high-performance computing resources. Often, to understand a phenomenon, multiple simulations are run, each with a different set of simulation input parameters. These data are then used to create an interpolant, or surrogate, relating the simulation outputs to the corresponding inputs. When the inputs and outputs are scalars, a simple machine learning model can suffice. However, when the simulation outputs are vector valued, available at locations in two or three spatial dimensions, often with a temporal component, creating a surrogate is more challenging. In this report, we use a two-dimensional problem of a jet interacting with high explosives to understand how we can build high-quality surrogates. The characteristics of our data set are unique - the vector-valued outputs from each simulation are available at over two million spatial locations; each simulation is run for a relatively small number of time steps; the size of the computational domain varies with each simulation; and resource constraints limit the number of simulations we can run. We show how we analyze these extremely large data-sets, set the parameters for the algorithms used in the analysis, and use simple ways to improve the accuracy of the spatio-temporal surrogates without substantially increasing the number of simulations required.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Spatiotemporal Interpolation of Elevation Changes Derived from Satellite Altimetry for Jakobshavn Isbrae, Greenland

Estimation of ice sheet mass balance from satellite altimetry requires interpolation of point-scale elevation change (dHdt) data over the area of interest. The largest dHdt values occur over narrow, fast-flowing outlet glaciers, where data coverage of current satellite altimetry is poorest. In those areas, straightforward interpolation of data is unlikely to reflect the true patterns of dHdt. Here, four interpolation methods are compared and evaluated over Jakobshavn Isbr, an outlet glacier for which widespread airborne validation data are available from NASAs Airborne Topographic Mapper (ATM). The four methods are ordinary kriging (OK), kriging with external drift (KED), where the spatial pattern of surface velocity is used as a proxy for that of dHdt, and their spatiotemporal equivalents (ST-OK and ST-KED).

Jakobshavn Isbrae↗
NASA NTRS2018

Super Resolution of Remote Sensing Images Using Edge-Directed Radial Basis Functions

Edge-Directed Radial Basis Functions (EDRBF) are used to compute super resolution(SR) image from a given set of low resolution (LR) images differing in subpixel shifts. The algorithm is tested on remote sensing images and compared for accuracy with other well-known algorithms such as Iterative Back Projection (IBP), Maximum Likelihood (ML) algorithm, interpolation of scattered points using Nearest Neighbor (NN) and Inversed Distance Weighted (IDW) interpolation, and Radial Basis Functin(RBF) . The accuracy of SR depends on various factors besides the algorithm (i) number of subpixel shifted LR images (ii) accuracy with which the LR shifts are estimated by registration algorithms (iii) and the targeted spatial resolution of SR. In our studies, the accuracy of EDRBF is compared with other algorithms keeping these factors constant. The algorithm has two steps: i) registration of low resolution images and (ii) estimating the pixels in High Resolution (HR) grid using EDRBF. Experiments are conducted by simulating LR images from a input HR image with different sub-pixel shifts. The reconstructed SR image is compared with input HR image to measure the accuracy of the algorithm using sum of squared errors (SSE). The algorithm has outperformed all of the algorithms mentioned above. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

Mareboyana, Manohar M.↗
DOE OSTI2026

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗
DOE OSTI2023

Fitting Matérn smoothness parameters using automatic differentiation

The Mat$\acute{e}$rn covariance function is ubiquitous in the application of Gaussian processes to spatial statistics and beyond. Perhaps the most important reason for this is that the smoothness parameter $\nu$ gives complete control over the mean-square differentiability of the process, which has significant implications for the behavior of estimated quantities such as interpolants and forecasts. Unfortunately, derivatives of the Mat$\acute{e}$rn covariance function with respect to $\nu$ require derivatives of the modified second-kind Bessel function $K$ $\nu$ with respect to $\nu$. While closed form expressions of these derivatives do exist, they are prohibitively difficult and expensive to compute. For this reason, many software packages require fixing $\nu$ as opposed to estimating it, and all existing software packages that attempt to offer the functionality of estimating $\nu$ use finite difference estimates for $\partial$ $\nu$ $K$ $\nu$ . In this work, we introduce a new implementation of $K$$\nu$ that has been designed to provide derivatives via automatic differentiation (AD), and whose resulting derivatives are significantly faster and more accurate than those computed using finite differences. Here, we provide comprehensive testing for both speed and accuracy and show that our AD solution can be used to build accurate Hessian matrices for second-order maximum likelihood estimation in settings where Hessians built with finite difference approximations completely fail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An a priori evaluation of a principal component and artificial neural network based combustion model in diesel engine conditions

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. Here, these observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for deviation from mass conservation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

MCNP6 Study of Spatial Fidelity Required for ROC Curve Convergence

The detection of special nuclear material at ports and borders is one of the primary missions of the Department of Homeland Security's (DHS) Domestic Nuclear Detection Office (DNDO). In support of this mission a large-scale modeling and simulation effort has been undertaken with the goal of providing a comprehensive tool-kit that addresses the complexity of problems involved with developing and maintaining technologies deployed to global nuclear detection architecture (GNDA) nodes. An important objective of DNDO's mission is to characterize detector system performance before deployment. In the effort to support this mission, the latest version of MCNP has been used to perform detectability studies of highly enriched uranium (HEU) to populate a database that will be used for the tool-kit. The characterization method used in the implementation of the database is the receiver operating characteristic (ROC). A ROC curve shows the limits of detectability of a given system as well as an overall metric of the efficacy of a detection system. This is accomplished by comparing total detector count distributions to the count distribution produced by background alone. For an in-depth explanation of the theory behind the MCNP production of ROC curves please refer to the paper, 'How To Use The Receiver Operating Characteristic Tally Option in MCNP6'. Building a useful database requires an expansive parameter space. The current tool-kit use nine parameters, which if varied with just 5 options each, results in nearly two million simulations to run. Depending on the set of parameters these simulations can take a few hours or a few weeks to complete. This computational cost necessitates the use of scaling algorithms to interpolate between the data contained in the database. The tool-kit employs a discrete event method to simulate the movement and detector response of special nuclear material (SNM) through a GNDA node. Given the nature of a discrete event simulation, constant motion of SNM must be split up in to discrete spatial detection points. The fidelity required of the spatial splitting to achieve a properly converged answer is investigated here for a neutron detection system. The detector used was a SNAP-3 neutron detector in front of a sphere of SNM in the presence of background radiation. A parameter study has been performed to determine the spatial fidelity required for ROC curve convergence for moving objects in a discrete event simulator. It appears that 5 points is the minimum number of detection points with 7 points needed for one of the parameter sets. The convergence worsens with increases to detection length but appears to improve with increasing detector distance. These results will help future work involving quantifying the accuracy based on given tolerances and parameters. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Distributed Fiber Optics Measurements of Rock Deformation and Failure in Triaxial Tests

The implementation of distributed strain measurement methods in triaxial and uniaxial tests have demonstrated the development of strain localization, even at early stages. This implies that single point measurement methods are location dependent. The use of distributed methods is required not only to improve the interpreted constitutive parameters obtained from triaxial tests, but also to understand the implications of strain localization in the failure process. Here, this work uses optical fibers in triaxial tests. The developed distributed measurement method was implemented on granite, gabbro, and sandstone samples and tested under different confining pressures, reaching 200 MPa on the granite sample. Using a temporal resolution of 0.25 Hz and 5 mm of spatial resolution, the strain evolution at over 300 locations at the sample surface was measured during testing. When compared to point sensing methods, the use of optical fiber greatly increases the number of measurements at the surface of the sample, and their interpolation provides the entire deformation of the sample surface. In all the tests performed, strain localizations were revealed before failure. A three-dimensional interpretation of a test, combining an optical scan of the sample and the distributed measurements, show good correlation between the fractures and the strain localization.

58 GEOSCIENCES↗
DOE OSTI2026

Integrated Neutronics Modeling for Inertial Fusion Energy Systems: Development and Application to LD-FIRST

Lawrence Livermore National Laboratory (LLNL) is proposing a new Laser Driven Fusion Integration Research and Science Test Facility (LD-FIRST) with the goal of providing an experimental testbed for future Inertial Fusion Energy (IFE) systems. However, IFE systems require detailed and accurate multiphysics modeling to quantify material damage, thermal loading, and tritium breeding within complex chamber environments. This article presents the first step in an integrated multiphysics framework that couples meshed CAD-based geometry within Monte Carlo neutronic simulations to enable high-fidelity analysis of IFE chamber concepts, with future coupling to external codes. The neutronics workflow utilizes OpenMC and its third-party capability to use CAD-based geometries through DAGMC and tally on unstructured meshes with Libmesh to evaluate neutron transport behavior, geometric fidelity, and material performance under reactor-relevant conditions. The use of tailored tallies on unstructured meshes in this framework allows direct transfer without interpolating to CFD simulation tools. Two IFE chambers were evaluated, both conceived by LLNL: HYLIFE-II and Laser IFE (LIFE). This work produced high-fidelity conformal surface and volumetric meshes of the HYLIFE-II and LIFE chambers with mapped spatial insight into material damage, thermal loading, and tritium breeding. The HYLIFE-II model was built utilizing available resources and used as a test case to verify that the neutronics framework can handle complex geometries. The LIFE chamber CAD was provided by LLNL and was the main focus of this work. This work analyzes multiple ternary alloy breeding materials for the LIFE chamber, across different 6 Li enrichments to produce data relevant to the LD-FIRST project. This work also investigates the level of model fidelity for the LIFE chamber, and results show that inclusion of detailed first wall and coolant structures increased the predicted tritium breeding ratio (TBR) by ~30%, highlighting the sensitivity of tritium breeding and the need for a high-fidelity simulation framework for IFE chambers. These developments provide a scalable toolset for the design and optimization of next-generation IFE chambers, forming a solid foundation for future coupled multiphysics analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2011

On-Orbit Spatial Characterization of MODIS with ASTER Aboard the Terra Spacecraft

This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (MODIS) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of MODIS, making it feasible to characterize MODIS on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit MODIS BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each MODIS band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each MODIS band. The best measurement match between ASTER and each MODIS band is obtained when the measurement difference reaches its weighted minimum. The position of each MODIS band in the AMPC is then used to calculate the BBR. The results are compared with those derived from MODIS onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 MODIS pixel. This approach is useful for other sensors without onboard spatial characterization capability. Index Terms Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), band-to-band registration (BBR), MODerate resolution Imaging Spectroradiometer (MODIS), spatial characterization.

Xie, Yong↗
DOE OSTI2021

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

17 WIND ENERGY↗
DOE OSTI2020

An Eulerian multimaterial framework for simulating high-explosive aquarium tests

Aquarium tests of cylindrical high-explosive charges provide optical data of the detonation front velocity and shape, propagation of the shock wave in the surrounding water, and expansion rates of the detonation products behind the front. Data from aquarium experiments is often used for calibration of reactive burn models based on phenomenological equations of state (EOS) and reaction rate laws. This paper presents a multimaterial numerical modeling framework to solve the 2D axisymmetric reactive Euler equations for high-explosive aquarium tests, in particular for ammonium nitrate - fuel oil (ANFO) explosives. An extension of the Ghost Fluid Method (GFM) is used to handle the dynamic material interfaces for the ANFO explosion products, the charge-confining material (polymethyl methacrylate PMMA), and the surrounding water. This study analyzes the sensitivity of calculations (both computational efficiency and numerical accuracy) to different algorithms for the material interface models including the original GFM versus Riemann solver-based strategies. A novel method for defining the left and right states in the interfacial Riemann problem eliminates the need for sorting or nodal interpolation during the projection along the material interface. Numerical tests indicate that populating the interface node values using the Riemann solution mitigate the overheating error observed in steady-state calculations. Solution convergence and computational efficiency are explored as a function of the spatial and temporal order of the schemes. Results from the computational model with analytical equations of state and fitted reaction rate parameters show very good quantitative agreement with experimentally observed detonation front velocity, reaction products expansion, and shock wave propagation in the surrounding water for a cylindrical ANFO charge encased in PMMA. Finally, the proposed modeling framework, in conjunction with experimental tests, provides a reliable tool to assess equations of state and reaction rate expressions for reactive burn models of confined high explosives.

42 ENGINEERING↗
DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗