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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Heat Capacity Mapping Mission (HCMM): Interpretation of imagery over Canada

Visual analysis of HCMM images acquired over two sites in Canada and supporting aircraft and ground data obtained at a smaller subsite in Alberta show that nightime surface temperature distribution is primarily related to the near-surface air temperature; the effects of topography, wind, and land cover were low or indirect through air temperature. Surface cover and large altitudinal differences were important parameters influencing daytime apparent temperature values. A quantitative analysis of the relationship between the antecedent precipitation index and the satellite thermal IR measurements did not yield statistically significant correlation coefficients, but the correlations had a definite temporal trend which could be related to the increasing uniformity of vegetation cover. The large pixel size (resulting in a mixture of cover types and soil/canopy temperatures measured by the satellite) and high cloud cover frequency found in images covering both Canadian sites and northern U.S. were considered the main deficiencies of the thermal satellite data.

Cihlar, J.↗
DOE OSTI2023

Quantitative investigation of sooting dynamics in droplet combustion using an automated image analysis algorithm

This paper reports an image analysis approach using a newly-developed open-source program to extract quantitative measurements of soot volume fraction (SVF) from digital video images of burning n-heptane droplets. The automated program developed in this work can analyze images of fixed and untethered droplets to quantify sooting dynamics. The images analyzed in the program were taken from experiments carried out in the Multi-user Droplet Combustion Apparatus (MDCA) onboard the International Space Station (ISS). In these experiments, video imaging of burning droplets was obtained using backlighting by a laser diode with a wavelength of 653 nm. Here, the light was collimated before it passed through the droplet and soot-containing region, after which the light was then attenuated and projected onto the camera’s sensors. This technique facilitates the measurements of SVF based on the principles of the full field light extinction method (FFLEM). The measurements provide quantitative data that reveal the sooting dynamics of liquid fuels during droplet combustion processes. The analyses of a soot-attenuating image (ISS n-heptane, untethered droplet) at an instant during the burning show that the SVF distribution has a peak at the soot shell location. It then decreases due to soot oxidation when the location is further away from the burning droplet. Regarding temporal effects on the maximum SVF (SVF max ), results show that SVF max first increases after the burning is initiated until a peak value is reached, after which SVF max decreases. The SVF max values identified in this study for n-heptane are quantitatively consistent with previously reported values for fiber-supported droplets and are reached relatively early in the burning history. n-Heptane images are also analyzed to show the effects of initial droplet sizes on the maximum soot volume fraction. Results show that SVF max decreases with increasing initial droplet size, which is consistent with visual observations of less soot formed and dimmer flame brightness as Do increases.

42 ENGINEERING↗
NASA NTRS2000

Thermographic Imaging of Defects in Anisotropic Composites

Composite materials are of increasing interest to the aerospace industry as a result of their weight versus performance characteristics. One of the disadvantages of composites is the high cost of fabrication and post inspection with conventional ultrasonic scanning systems. The high cost of inspection is driven by the need for scanning systems which can follow large curve surfaces. Additionally, either large water tanks or water squirters are required to couple the ultrasonics into the part. Thermographic techniques offer significant advantages over conventional ultrasonics by not requiring physical coupling between the part and sensor. The thermographic system can easily inspect large curved surface without requiring a surface following scanner. However, implementation of Thermal Nondestructive Evaluations (TNDE) for flaw detection in composite materials and structures requires determining its limit. Advanced algorithms have been developed to enable locating and sizing defects in carbon fiber reinforced plastic (CFRP). Thermal Tomography is a very promising method for visualizing the size and location of defects in materials such as CFRP. However, further investigations are required to determine its capabilities for inspection of thick composites. In present work we have studied influence of the anisotropy on the reconstructed image of a defect generated by an inversion technique. The composite material is considered as homogeneous with macro properties: thermal conductivity K, specific heat c, and density rho. The simulation process involves two sequential steps: solving the three dimensional transient heat diffusion equation for a sample with a defect, then estimating the defect location and size from the surface spatial and temporal thermal distributions (inverse problem), calculated from the simulations.

Plotnikov, Y. A.↗
DOE OSTI2023

Micromovements and discomfort associated with flight mission with helmet operation tasks with different levels of cognitive workload

When performing stationary tasks under elevated cognitive workload, individuals must perform continual muscle contractions to maintain stability of the body, resulting in fatigue of the postural muscles. When the muscles perform these contractions in a prolonged manner, the body potentially responds through small changes in body movements—micromovements that may lead to discomfort. The study purpose was to evaluate impact of cognitive load on micromovements. The micromovements were measured during three different cognitive workloads; low, medium, and high. The NASA-TLX score was used to evaluate the perceived mental workload and discomfort was assessed by visual analog scale. In total, 60 subjects (30 males and 30 females) were recruited and performed cognitive tasks that simulated flight operations such as changing the radio frequency based on air traffic control messages, balancing the fuel levels in simulated fuel tanks, and aiming a reticle in a designated moving target using the cyclic control. Cognitive load was defined by the frequency of events. Micromovements were defined by changes in the center of pressure (COP) of the seat pan and COP standard deviation. It was found that the high cognitive workloads had the highest NASA-TLX scores including mental demands, temporal demands, and effort. The neck area had the highest overall levels of discomfort followed by upper back. The highest standard deviation for COP shift and number of micromovements occurred for medium cognitive workloads. In conclusion, while there were some interesting trends, few trends reached a statistical significance due to high variability among subjects for the outcome variables.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2025

Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow

As electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.

14 SOLAR ENERGY↗
NASA NTRS2011

Determining Trends in Impervious Cover for the Mobile Bay, AL Region for 1974-2008, Based on a Landsat Time Series

This presentation will discuss the development and use of Landsat-based impervious cover products in conjunction with land use land cover change products to assess multi-decadal urbanization across the Mobile Bay region at regional and watershed scales. This nationally important coastal region has undergone a variety of ephemeral and permanent land use land cover change since the mid-1970s, including gradual but consequential increases in urban surface cover. This urban sprawl corresponds with increased regional percent impervious cover. The region s coastal zone managers are concerned about the increasing percent impervious cover, since it can negatively influence water quality and is an important consideration for coastal conservation and restoration work. In response, we processed multi-temporal Landsat data to compute maps of percent impervious cover for multiple dates from 1974 through 2008, roughly at 5-year intervals. Each year of product was classified using one single date of leaf-on and leaf-off Landsat data in conjunction with Cubist software. We are assessing Landsat impervious cover product accuracy through comparisons to available reference data, including available NLCD impervious cover products from the USGS, raw Landsat data, plus higher spatial resolution aerial and satellite data. In particular, we are quantitatively comparing the 2008 Landsat impervious cover products to those from QuickBird 2.4-meter multispectral data. Initial visual comparisons with the QuickBird impervious cover product suggest that the 2008 Landsat product tends to underestimate impervious cover for high density urban areas and to overestimate impervious cover in established residential subdivisions mixed with forested cover. Landsat TM and ETM data appears to produce more accurate impervious cover products compared to those using lower resolution Landsat MSS data. Although imperfect, these Landsat impervious cover products have helped the Mobile Bay National Estuary Program visualize basic urbanization trends for multiple HUC-12 watersheds of concern to them and their constituents

Spruce, Joseph P.↗
NASA NTRS1996

Smooth Pursuit of a Partially Occluded Object

There has long been qualitative evidence that humans can pursue an object defined only by the motion of its parts. We explored this quantitatively using an occluded diamond stimulus. Four subjects (one naive) tracked a line-figure diamond moving along an elliptical path (0.9 Hz) either clockwise (CW) or counterclockwise (CCW) behind either an X-shaped aperture (CROSS) or two vertical rectangular apertures (BARS), which obscured the corners. Although the stimulus consisted of only four line segments (108 cd/square m) moving within a visible aperture (0.2 cd/square m) behind a foreground (38 cd/square m), it is largely perceived as a coherently moving diamond. The inter-saccadic portions of eye-position traces were fit with sinusoids. All subjects tracked object motion with considerable temporal accuracy. The mean phase lag was 5 deg/6 deg (CROSS/BARS) and the mean relative phase between the horizontal and vertical components was +95 deg/+92 deg (CW) and -85 deg/-75 deg (CCW), which is close to perfect. Furthermore, a chi-square analysis showed that 56% of BARS trials were consistent with tracking the correct elliptical shape (p is less than 0.05), although segment motion was purely vertical. These data disprove the main tenet of most models of pursuit: that it is a system that seeks to minimize retinal image motion through negative feedback. Rather, the main drive must be a visual signal which has already integrated spatiotemporal retinal information into an object-motion signal.

Stone, L. S.↗
NASA NTRS2017

Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S􀂱3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn􀂶s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds􀂲all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan institutions as well as one in South Dakota and one in Alabama, this effort was able to provide next-day georeferenced estimates of cyanobacteria and scum concentrations. Very prompt processing and analysis of the hyperspectral imagery is necessary for the information to be acted upon. For example, a next-day report of an overflight over the Ohio River indicated that a bloom could be present as far downstream as the Cincinnati intake, but the Ohio EPA had not received visual reports of a bloom that far downstream. Water samples were obtained at the Cincinnati water intake, based on the flight data, and detected microcystins in the source water. The flight data helped State and municipal authorities realize the potential extent of that bloom, and triggered response sampling, before the visual river-wide scums started forming. The present document describes the process that was utilized to take raw remote sensing data and create information products; this includes system calibration and validation, efforts to correct atmospheric effects, and algorithms that produce the data products. Furthermore, successful research into improved algorithms for expanding the capability to delineate in water constituents is included. Finally, comparisons that show expected relationships between ground-based measurements and hyperspectral imager version 2 (HSI2) data results are presented, giving confidence in the remote sensing products.

Hyperspectral Imaging↗
DOE OSTI2022

Evaluation of artificial neural network performance for classification of potato plants infected with potato virus Y using spectral data on multiple varieties and genotypes

Potato virus Y (Potyviridae, PVY) is a plant virus that poses a significant threat to potato producers on a global basis. The pathogen has disrupted seed potato supplies and negatively impacted yield and quality of commercial potato crops. The potato industry currently manages PVY infection levels via insecticide applications, regional seed certification programs that rely on field scouting to visually assess individual plants for infection status, and destructive and costly tissue sampling coupled with laboratory assays. Despite these efforts, PVY continues to confound potato industry stakeholders resulting in economic harm. Remote sensing and machine learning provide for the development of new tools to more accurately detect and spatially quantify PVY-infected plants versus the current state of the art. However, there is a need to understand how the occurrence of many different potato varieties impact the dynamics of developing models to detect potato plants impacted with PVY and their potential effectiveness. This study evaluates classification modelling outcomes using spectral datasets collected in different temporal and spatial environments (greenhouse and a production field) on multiple potato varieties consisting of labelled instances of plants infected with PVY and those not infected with the virus. A modelling framework was developed to support iterative modelling runs using artificial neural network (ANN) architectures configured as binary classifiers to develop sample populations to support statistical analysis on model performance using specific spectral subsets. When using spectral data to detect PVY-infected plants, ANN models achieved the highest mean accuracy of 0.894 on a single variety. Conversely, the same ANN model architecture only achieved a mean accuracy of 0.575 on a spectral data set representing 29 potato breeding lines. Additionally, statistical analysis indicates spectral regions including the red edge, near infrared and shortwave infrared contain more important spectral features for the ANN classifier introduced in this research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Flow and heat transfer in the wake of a triangular arrangement of spheres

This research work seeks to investigate the influence of spacing and heat transfer on the wake behavior of a triangular arrangement of spheres. Four experimental configurations have been investigated at three Reynolds numbers, Re 1 = 350, Re 2 = 700, and Re 3 = 1050. Two isothermal cases were investigated with spacing between the spheres of zero and one sphere diameter, and two cases were investigated with an applied heat flux at the same spacing conditions. The time resolved particle image velocimetry results revealed various flow phenomena including flow separations, von Karman vortex shedding, and Kelvin–Helmholtz instabilities. The turbulent statistics reveal the effect of proximity and heat transfer on the time averaged values of the wake size, turbulent strengths, and Reynolds shear stress in the wake of each sphere, namely, the laminarization effects from the addition of heat and the suppression of the lead sphere wake from the proximity of the trailing spheres. These results are complemented by the application of proper orthogonal decomposition (POD) to the flow fields, which extracts the coherent structures from the flow. Here the modes that describe the coherent structures are extracted and described in detail, which provide further insight into effects of the experimental conditions on the temporal behavior of the flow. Many of the low order modes are found to be associated in pairs, corresponding to asymmetric structures or advection of a given structure downstream. The capability of POD to produce reduced order models of the flow is then utilized to facilitate vortex identification analysis. A turbulent kinetic energy based mode truncation criteria, which has been found to enhance vortex identification capability, is applied to select the POD modes and temporal coefficients to be used in the reduced order modeling. The reconstructed velocity fields are then analyzed with vortex identification algorithms to extract the vortex cores and boundaries. The combination of these approaches allows the study of the effect of proximity and heat transfer on the vortex characteristics, such as size, strength, and distribution.

42 ENGINEERING↗
DOE OSTI2024

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗
DOE OSTI2020

Metrology of Time-Domain Soft X-Ray Attosecond Pulses and Reevaluation of Pulse Durations of Three Recent Experiments

Attosecond pulses in the soft x-ray (SXR) to water-window energy region offer the tools for creating and studying target-specific localized inner-shell electrons or holes in materials, enabling monitoring or controlling charge and energy flows in a dynamic system on attosecond timescales. Recently, a number of laboratories have reported generation of continuum harmonics in the hundred-electron-volt to kilovolt region with few-cycle long-wavelength mid-infrared lasers. These harmonics have the bandwidth to support pulses with durations of a few to a few-ten attoseconds. But harmonics generated in a gas medium have attochirps that cannot be fully compensated by materials over a broad spectral range; thus, realistically what are the typical shortest attosecond pulses that one can generate? To answer this question, it is essential that the temporal attosecond pulses be accurately characterized. By reanalyzing the soft x-ray attosecond metrology reported in three recent experiments using a newly developed broadband phase retrieval algorithm, we demonstrate here that the generated attosecond pulses in the first two papers have durations of about 60 as, longer than what they have reported. Similarly, the duration from the third experiment is retrieved to be about half of the 322-as upper limit cited in that work. We also introduce the autocorrelation (AC) of the streaking spectrogram. By comparing the ACs from the experiments and from the retrieved SXR pulses, the accuracy of the retrieved results can be directly visualized. Our retrieval method is fast and accurate, and it shall provide a powerful tool for the metrology of the emerging few-ten-attosecond pulses.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2010

Centralized Alert-Processing and Asset Planning for Sensorwebs

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.

Castano, Rebecca↗
NASA NTRS2016

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

remote sensing↗
DOE OSTI2022

Soil oxidoreductase zymography: Visualizing spatial distributions of peroxidase and phenol oxidase activities at the root-soil interface

Decomposition of organic material in the rhizosphere – the most dynamic microbial habitat in soil – involves arrays of oxidoreductase and hydrolytic enzymes. Spatial distributions of various hydrolytic activities in soil have already been explored by zymographic techniques. However, the distribution of oxidative activity in the rhizosphere remains to be studied. Thus, we extended a Time-Lapse Zymography technique, using Amplex Red® reagent, to visualize and quantify distributions of phenol oxidase and peroxidase activities in the rhizosphere of Zea mays L. growing in a Haplic Phaeozem and the non-rhizospheric soil. The gross oxidative activity was greatest at the root surfaces, and fell to background soil levels 1.26 and 0.73 mm from seminal (>1 mm diameter) and lateral (<0.5 mm diameter) roots, respectively. The rhizosphere extent relative to the root radius was 59% broader around lateral than around seminal roots. The greatest activities, up to 30 nmol cm –2 min –1 , were peroxidase-dominated and closely associated with roots. Here, the results confirm the utility of the approach for studying spatio-temporal distributions of oxidative activities in soil. However, actual activity of oxidoreductases in the field will be strongly controlled by fluctuating environmental conditions such as soil aeration and the gradient of reactive oxygen species, which need to be considered especially in anoxic soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dynamic in situ imaging of methane hydrate formation in coal media

Fast 3D X-ray imaging has proved to provide crucial insights into multi-phase dynamic processes in various geomaterials. In particular, many in situ imaging experiments have been made to study gas-hydrate formation in porous sandy samples. Such imaging is challenging for the methane gas-hydrate formation in coal samples because of the coal micro-porosity structure and lower X-ray contrast. Here we present results of the first dynamic in situ micro-computed tomography experiment of methane-hydrate formation in coal samples. Synchrotron phase-contrast tomography techniques allowed to achieve necessary contrast levels to separate all the materials of interest (gas, water, coal, and gas hydrate) in reconstructed images with high spatial and temporal resolution. The imaging results are compared to the ones from a similar tomographic experiment with sand samples. Methane-hydrate formation is accompanied by the water movements caused by cryogenic water suction that happens in sequences of short fast movements with longer equilibrium states in between. Only one type of the hydrate formation was observed in coal (growth as shells on grain boundaries) as opposed to three types in sand (shells, growth into gas pockets, and inside water volumes). In particular, this leads to a slower hydrateformation speed in coal. For the coal sample, we also observed water extraction from grains, and interpreted it as competitive sorption of methane. Lastly, we visualized the dynamic behavior of this water extraction via microchannels inside the coal grains, and performed nano-tomography imaging of these channels for a better understanding of this phenomenon.

58 GEOSCIENCES↗