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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Ambient-Light-Canceling Camera Using Subtraction of Frames

The ambient-light-canceling camera (ALCC) is a proposed near-infrared electronic camera that would utilize a combination of (1) synchronized illumination during alternate frame periods and (2) subtraction of readouts from consecutive frames to obtain images without a background component of ambient light. The ALCC is intended especially for use in tracking the motion of an eye by the pupil center corneal reflection (PCCR) method. Eye tracking by the PCCR method has shown potential for application in human-computer interaction for people with and without disabilities, and for noninvasive monitoring, detection, and even diagnosis of physiological and neurological deficiencies. In the PCCR method, an eye is illuminated by near-infrared light from a lightemitting diode (LED). Some of the infrared light is reflected from the surface of the cornea. Some of the infrared light enters the eye through the pupil and is reflected from back of the eye out through the pupil a phenomenon commonly observed as the red-eye effect in flash photography. An electronic camera is oriented to image the user's eye. The output of the camera is digitized and processed by algorithms that locate the two reflections. Then from the locations of the centers of the two reflections, the direction of gaze is computed. As described thus far, the PCCR method is susceptible to errors caused by reflections of ambient light. Although a near-infrared band-pass optical filter can be used to discriminate against ambient light, some sources of ambient light have enough in-band power to compete with the LED signal. The mode of operation of the ALCC would complement or supplant spectral filtering by providing more nearly complete cancellation of the effect of ambient light. In the operation of the ALCC, a near-infrared LED would be pulsed on during one camera frame period and off during the next frame period. Thus, the scene would be illuminated by both the LED (signal) light and the ambient (background) light during one frame period, and would be illuminated with only ambient (background) light during the next frame period. The camera output would be digitized and sent to a computer, wherein the pixel values of the background-only frame would be subtracted from the pixel values of the signal-plus-background frame to obtain signal-only pixel values (see figure). To prevent artifacts of motion from entering the images, it would be necessary to acquire image data at a rate greater than the standard video rate of 30 frames per second. For this purpose, the ALCC would exploit a novel control technique developed at NASA s Jet Propulsion Laboratory for advanced charge-coupled-device (CCD) cameras. This technique provides for readout from a subwindow [region of interest (ROI)] within the image frame. Because the desired reflections from the eye would typically occupy a small fraction of the area within the image frame, the ROI capability would make it possible to acquire and subtract pixel values at rates of several hundred frames per second considerably greater than the standard video rate and sufficient to both (1) suppress motion artifacts and (2) track the motion of the eye between consecutive subtractive frame pairs.

Morookian, John Michael↗
NASA NTRS2011

Optimization of Adaboost Algorithm for Sonar Target Detection in a Multi-Stage ATR System

JPL has developed a multi-stage Automated Target Recognition (ATR) system to locate objects in images. First, input images are preprocessed and sent to a Grayscale Optical Correlator (GOC) filter to identify possible regions-of-interest (ROIs). Second, feature extraction operations are performed using Texton filters and Principal Component Analysis (PCA). Finally, the features are fed to a classifier, to identify ROIs that contain the targets. Previous work used the Feed-forward Back-propagation Neural Network for classification. In this project we investigate a version of Adaboost as a classifier for comparison. The version we used is known as GentleBoost. We used the boosted decision tree as the weak classifier. We have tested our ATR system against real-world sonar images using the Adaboost approach. Results indicate an improvement in performance over a single Neural Network design.

Adaboost↗
NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗
NASA NTRS2015

Aram Chaos: a Long Lived Subsurface Aqueous Environment with Strong Water Resources Potential for Human Missions on Mars

Aram Chaos, Mars is a crater 280 kilometers in diameter with elevations circa. minus 2 to minus 3 kilometers below datum that provides a compelling landing site for future human explorers as it features multiple scientific regions of interest (ROI) paired with a rich extensible Resource ROI that features poly-hydrated sulfates [1]. The geologic history of Aram Chaos suggests several past episodes of groundwater recharge and infilling by liquid water, ice, and other materials [1-3]. The creation of the fractured region with no known terrestrial equivalent may have been caused by melting of deep ice reservoirs that triggered the collapse of terrain followed by catastrophic water outflows over the region. Aram Chaos is of particular scientific interest because it is hypothesized that the chaotic terrain may be the source of water that contributed to the creation of nearby valleys such as Ares Vallis flowing toward Chryse Planitia. The liquid water was likely sourced as groundwater and therefore represents water derived from a protected subsurface environment making it a compelling astrobiological site [2]. The past history of water is also represented by high concentrations of hematite, Fe-oxyhydroxides, mono-hydrated and poly-hydrated sulfates [1, 2]. Poly-hydrated sulfates are likely to contain abundant water that evolves at temperatures below 500 degrees Centigrade thus conferring Aram Chaos a potentially high value for early in-situ resource utilization (ISRU) [4]. The geologic history also calls for future prospecting of deep ice deposits and possibly liquid water via deep drilling. The most recent stratigraphic units in the central part of Aram Chaos are not fractured, and are part of a dome-shaped formation that features bright, poorly-consolidated material that contains both hydrated sulfates and ferric oxides according to OMEGA (Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité) data [5]. These surface material characteristics are preliminary indications of their potential use in civil engineering activities that involve regolith moving and hauling, while further study is needed to assess traverse-ability challenges. The widespread distribution of sulfates is also of interest as a resource for the use of sulfur as a binding compound in regolith-based concrete for constructions. The terrain depressions caused by the rock fracturing events may challenge surface mobility but also suggest the possibility of using such natural features for additional shielding from space radiation and as emplacement of nuclear surface power reactors for the same reason. The high concentration of hematite (up to 16 percent) in some of the smoother recent terrains of the central part of Aram Chaos [2] is a favorable attribute for metal extraction ISRU to create iron-based feedstock for in-situ fabrication of replacement parts or their repairs. Preliminary data on Aram Chaos indicate that it offers a combination of many critical criteria for human missions to the surface of Mars: equatorial region at low Mars Orbiter Laser Altimeter (MOLA), evidence of hydrated minerals over large areas and at high concentrations tied to historic evidence of liquid water over long periods.

Sibille, L.↗
NASA NTRS2015

Midlatitude Ice-Rich Ground on Mars: An Important Target for Science and In Situ Resource Utilization on Human Missions

The region of ROI is characterized by proven presence of near surface ground ice and numerous periglacial features. Midlatitude ground ice on Mars is of significant scientific interest for understanding the history and evolution of ice stability on Mars, the impact that changes in insolation produced by variations in Mars’ orbital parameters has on the regions climate, and could provide human exploration with a reliable and plentiful in situ resource. For both science and exploration, assessing the astrobiological potential of the ice is important in terms of (1) understanding the potential for life on Mars and (2) evaluating the presence of possible biohazards in advance of human exploration. Heldmann et al. (2014) studied locations on Mars in the Amazonis Planitia region where near surface ground ice was exposed by new impact craters (Byrne et al. 2009). The study examined whether sites in this region were suitable for human exploration including reviewing the evidence for midlatitude ground ice, discussing the possible explanations for its occurrence, assessing its potential habitability for modern life, and evaluating the resource potential. They systematically analyzed remote-sensing data sets to identify a viable landing site. Five sites where ground ice was exposed were examined with HiRise imaging and were classified according to (1) presence of polygons as a proxy for subsurface ice, (2) presence and abundance of rough topographic obstacles (e.g., large cracks, cliffs, uneven topography), (3) rock density, (4) presence and abundance of large boulders, and (5) presence of craters. A suitable landing site was found having ground ice at only 0.15m depth, and no landing site hazards within a 25 km landing ellipse. This paper presents results of that study and examines the relevance of this ROI to the workshop goals.

Human Missions↗
NASA NTRS2016

The Mapping X-Ray Fluorescence Spectrometer (MAPX)

MapX will provide elemental imaging at ≤100 micron spatial resolution over 2.5 X 2.5 centimeter areas, yielding elemental chemistry at or below the scale length where many relict physical, chemical, and biological features can be imaged and interpreted in ancient rocks. MapX is a full-frame spectroscopic imager positioned on soil or regolith with touch sensors. During an analysis, an X-ray source (tube or radioisotope) bombards the sample surface with X-rays or αlpha-particles / gamma rays, resulting in sample X-ray Fluorescence (XRF). Fluoresced X-rays pass through an X-ray lens (X-ray μ-Pore Optic, "MPO") that projects a spatially resolved image of the X-rays onto a CCD. The CCD is operated in single photon counting mode so that the positions and energies of individual photons are retained. In a single analysis, several thousand frames are stored and processed. A MapX experiment provides elemental maps having a spatial resolution of ≤100 micron and quantitative XRF spectra from Regions of Interest (ROI) 2 centimers ≤ x ≤ 100 micron. ROI are compared with known rock and mineral compositions to extrapolate the data to rock types and putative mineralogies. The MapX geometry is being refined with ray-tracing simulations and with synchrotron experiments at SLAC. Source requirements are being determined through Monte Carlo modeling and experiment using XMIMSIM [1], GEANT4 [2] and PyMca [3] and a dedicated XRF test fixture. A flow-down of requirements for both tube and radioisotope sources is being developed from these experiments. In addition to Mars lander and rover missions, MapX could be used for landed science on other airless bodies (Phobos/Deimos, Comet nucleus, asteroids, the Earth's moon, and the icy satellites of the outer planets, including Europa.

Blake, David↗
NASA NTRS2016

MapX: An In Situ, Full-Frame X-Ray Spectroscopic Imager for the Biogenic Elements

Microbial life exploits microscale disequilibria at boundaries where valence, chemical potential, pH, Eh, etc. vary on a length scale commensurate with the organisms themselves - tens to hundreds of micrometers. These disequilibria can exist within cracks or veins in rocks and ice, at inter- or intra-crystalline boundaries, at sediment/water or sediment/atmosphere interfaces, or even within fluid inclusions trapped inside minerals. The detection of accumulations of the biogenic elements C,N,O,P,S at appropriate concentrations on or in a mineral/ice substrate would constitute permissive evidence of extant life, but context is also required. Does the putative biosignature exist in a habitable environment? Under what conditions of P, T, and chemical potential was the host mineralogy formed? MapX is an arm-deployed contact instrument that directly images the biogenic elements C, N, O, P, S, as well as the cations of the rock-forming minerals (Na, Mg, Al, Si, K, Ca, Ti, Cr, Mn, Fe) and important anions such as Cl, Fl. The instrument provides element images having ≤100 micron lateral spatial resolution over a 2.5 cm X 2.5 cm area, as well as quantitative XRF spectra from ground-selected or instrument-selected Regions of Interest (ROI) on the sample. Quantitative XRF spectra from ROI can be translated into mineralogies using ground- or instrument-based algorithms. Either an X-ray tube source (X-ray fluorescence) or a radioisotope source such as 244-Cm (alpha-particle and gamma-ray fluorescence) can be used, and characteristic X-rays emitted from the sample are imaged onto an X-ray sensitive CCD through an X-ray MicroPore Optic (MPO). As a fluorescent source, 244-Cm is highly desirable in a MapX instrument intended for life detection since high-energy alpha-particles are unrivaled in fluorescence yield for the low-Z elements. The MapX design as well as baseline performance requirements for a MapX instrument intended for life detection/identification of habitable environments will be presented.

micro-XRF spectrometer↗
NASA NTRS2017

Introduction of the ASGARD Code

ASGARD stands for 'Automated Selection and Grouping of events in AIA Regional Data'. The code is a refinement of the event detection method in Ugarte-Urra & Warren (2014). It is intended to automatically detect and group brightenings ('events') in the AIA EUV channels, to record event parameters, and to find related events over multiple channels. Ultimately, the goal is to automatically determine heating and cooling timescales in the corona and to significantly increase statistics in this respect. The code is written in IDL and requires the SolarSoft library. It is parallelized and can run with multiple CPUs. Input files are regions of interest (ROIs) in time series of AIA images from the JSOC cutout service (http://jsoc.stanford.edu/ajax/exportdata.html). The ROIs need to be tracked, co-registered, and limited in time (typically 12 hours).

Code development↗
NASA NTRS2018

Polar Volatiles Exploration in Peary Crater Enabled by NASA's Kilopower Project

For more than 50 years, scientists have discussed the possibility of the existence of water ice and other frozen volatiles at the lunar poles [1]. However, it was not until the 1990s when the polar orbiting spacecraft Clementine and Lunar Prospector collected data supporting these hypotheses [2]. Subsequent missions, including the Lunar Reconnaissance Orbiter (LRO) mission [3], and the Lunar Crater Observation and Sensing Satellite (LCROSS) mission [4], provided further evidence that supports the existence of water ice deposits at the lunar poles. During NASA's Constellation Program, several areas at both lunar poles polar were included in 50 Regions of Interest (ROI) for intensive study by the Lunar Reconnaissance Orbiter Camera (LROC) [5]. These polar ROI focused on peaks and craters rims that received high amounts of solar illumination, assuming initial missions back to the lunar surface would utilize solar arrays to generate electricity. Recently, the successful demonstration of NASA's Kilopower Project at the National Nuclear Security Administration (NNSA) Nevada National Security Site makes it possible to consider lunar polar missions at locations other than highly illuminated regions. The Kilopower Project was initiated in 2015 to demonstrate subsystem-level technology readiness of a small space fission power system [6]. This abstract describes the science objectives and operations for a mission concept developed at NASA Glenn Research Center's COMPASS Concurrent Engineering Team for a 1-year exploration of Peary Crater focused on prospecting for lunar polar volatiles.

Gruener, J. E.↗
NASA NTRS2017

Mars 2020 Site-Specific Mission Performance Analysis: Part 2. Surface Traversability

The Mars 2020 Rover Mission (M2020) is characterized by long-range traverses between scientific Regions Of Interest (ROIs), as well as the demanding requirement on the distance and time for the inter-ROI traverses. As a result, surface traversability is one of the major driving factors for the landing site selection of M2020. With the newly developed Mars Terrain Traversability analysis Tools (MTTT), we performed traversability analysis of the eight candidate landing sites with an unprecedented granularity. This paper describes the MTTT analysis capabilities, as well as how the MTTT capabilities were used to down-select from eight to three candidate landing sites for further evaluation.

Milkovich, Sarah↗
NASA NTRSDate not supplied

Cost and Throughput Analysis for the NASA Ames Arc Jet Modernization Program

NASA Ames Center is currently evaluating alternatives to modernize the Arc Jet Complex, a critical part of testing for NASA’s planetary missions. NASA’s Arc Jet Complex facilities “are used to simulate the aerothermodynamic heating that a spacecraft endures throughout hypersonic atmospheric entry, and to test candidate thermal protection system (TPS) materials and systems. “Because planetary mission schedules often have tight windows due to planetary alignment constraints, a small increase in schedule could result in a two-year delay. Such a delay could increase the cost of a $1billionmissionbyhundreds of millions of dollars due to project personnel pay and clean room storage. To avoid these costs, the authors support NASA Ames in evaluating return on investment (ROI) and effectiveness of alternatives for modernizing the complex. The first input into the ROI is the deconstruction and construction cost estimates, which are developed using independent research on highly specialized subsystems, vendor quotes, and Unified Facilities Criteria (UFC), depending on the facility and work package. One of the measures of effectiveness is throughput analysis of the test bays, as a main goal of the modernization is to increase the number of possible test runs per year. This analysis is conducted via a probabilistic simulation and accounts for a variety of stochastic factors that influence the sequence of test runs, such as the facility availability; test complexity; the need to pause to assess test results; test failure; and the possibility of a system failure. The methodologies for both these analyses are discussed, along with the challenges presented due to the unique nature of the highly specialized test equipment.

Jennifer Scheel↗
NASA NTRS2024

Converter/Compressor Building Solid Waste Management Unit (SWMU) #89 Monitoring Well 21 Area Interim Measure Work Plan

This Work Plan details the approach and design for the Interim Measure (IM) to remediate groundwater within the MW21 Area where VOC concentrations exceed Florida Department of Environmental Protection Natural Attenuation Default Concentrations. The IM includes in-situ bioremediation via injection of emulsified vegetable oil (EVO) and emulsified zero-valent iron (EZVI). The in-situ bioremediation technology consists of injecting an electron donor substrate into the subsurface to promote microbial breakdown of VOCs. The EVO injections for this IM are designed based on the use of Provectus ERD-CH4, which is a vegetable oil/carbon substrate mixture. The EZVI injections for this IM are designed based on the use of Provectus EZVI-CH4. The IM treatment layout consists of nine injection locations of EVO at approximately 10-foot radius of influence (ROI) and three injections locations of EZVI at approximately 6-foot ROI. The injection method will be direct push using a DPT rig. The overall injection depths range from 7 to 17 ft bls. The 7 ft bls top depth is designed to be 2 ft below the water table to prevent substrates from reaching the top of the water table. Injections are planned to be implemented using 2 ft intervals and will take place using a bottom-up approach to 2 ft below the water table. This work plan further describes the IM design, injection calculations, performance monitoring plan, and provides an injection layout. Revision 1 of this Work Plan includes quarterly performance sampling during Year 1 in accordance with F.A.C. 62-780. These changes are reflected in Section 7 and Table 2 of the Work Plan.

Mark J Jonnet↗
NASA NTRS2026

Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME↗
DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗
DOE OSTI2025

DNN-based Signal Processing for Liquid Argon Time Projection Chambers

We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal cancellation from bipolar responses and various detector effects observed in real data. We approach ROI identification as an image segmentation task, and employ a U-ResNet architecture. The network is trained on samples that incorporate detector geometry information and include a range of detector variations. Our approach significantly outperforms traditional methods while maintaining robustness across diverse detector conditions. This method has been adopted for signal processing in the Short-Baseline Neutrino program and provides a valuable foundation for future experiments such as the Deep Underground Neutrino Experiment.

Bhat, Avinay [Chicago U.]↗
NASA NTRS2012

Testing Saliency Parameters for Automatic Target Recognition

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

regions of interest (ROI)↗
DOE OSTI2024

Optimization of ray-tracing simulations to confirm performance of the GP-SANS instrument at the High-Flux Isotope Reactor

The CG-2 beamline at the High Flux Isotope Reactor (HFIR) exhibits a notable discrepancy between observed count rates and the count rates we would expect based on a Monte-Carlo neutron ray-trace simulation. These simulations consistently predict count rates approximately five times greater than those observed in four separate experimental runs involving different instrument configurations. This discrepancy suggests that certain factors are causing losses in measurements that are not adequately accounted for in the simulation, in particular guide reflectivity or misalignment. To investigate these discrepancies, a high-dimensional simulation parameter approach is applied in order to understand the losses. Region of Interest (ROI) groups along the instrument are assigned to different surfaces of the guide components within the simulation. This allows the parameters of those guide components to be varied as a group to minimize the complexity of the search space. The result is an optimization of simulation parameters using an iterative scheme that aims to minimize the difference between experimentally measured count rates and simulated count rates across all tested collimator combinations. This proposed methodology holds the potential to reveal previously unrecognized sources of intensity loss in the CG-2 beamline at HFIR and improve the accuracy of simulations, leading to enhanced understanding and performance of the beamline for various scientific applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization

Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is limited and cannot be universally deployed across all applications. Furthermore, integrating lossy compression with multi-resolution techniques to further boost storage efficiency encounters significant barriers. To this end, we introduce an innovative workflow that facilitates high-quality multi-resolution data compression for both uniform and AMR simulations. Initially, to extend the usability of multi-resolution techniques, our workflow employs a compression-oriented Region of Interest (ROI) extraction method, transforming uniform data into a multi-resolution format. Subsequently, to bridge the gap between multi-resolution techniques and lossy compressors, we optimize three distinct compressors, ensuring their optimal performance on multi-resolution data. These optimizations can improve the compression ratio of SOTA approaches by up to 3.3× under the same data quality loss. Lastly, we incorporate an advanced uncertainty visualization method into our workflow to understand the potential impacts of lossy compression. Experimental evaluation demonstrates that our workflow achieves significant compression quality improvements.

Wang, Daoce↗