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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Photo-oxidation of semicrystalline polymers: Effect of stress triaxiality on ductility

The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned ex situ using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Towards robust surrogate models: Benchmarking machine learning approaches to expediting phase field simulations of brittle fracture

Data-driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning techniques have the potential to provide a much needed speedup that would enable progress in areas such as multi-scale modeling and uncertainty quantification. Currently, phase field modeling (PFM) of fracture is one such approach that offers a convenient variational formulation to model crack nucleation, branching and propagation. To date, machine learning techniques have shown promise in approximating PFM simulations. While standard fracture benchmarks represent realistic scenarios frequently observed in practice, they typically do not provide sufficiently challenging tests for data-driven methods. Here, to address this gap, we introduce a challenging dataset based on PFM simulations designed to benchmark and advance ML methods for fracture modeling. This dataset includes three energy decomposition methods, two boundary conditions, and 1000 random initial crack configurations for a total of 6000 simulations. Each sample contains 100 time steps capturing the temporal evolution of the crack field. Alongside this dataset, we also implement and evaluate Physics Informed Neural Networks (PINN), Fourier Neural Operators (FNO), and UNet models as baselines, and explore the impact of ensembling strategies on prediction accuracy. With this combination of our dataset and baseline models drawn from the literature we aim to provide a standardized and challenging benchmark for evaluating machine learning approaches to solid mechanics. Our results highlight both the promise and limitations of popular current models, and demonstrate the utility of this dataset as a testbed for advancing machine learning in fracture mechanics research.

Benchmark dataset↗
DOE OSTI2024

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗
NASA NTRS2024

Spring 2021 Sea Ice Transport in the Southern Beaufort Sea Occurred During Coastal Lead Opening Events

Winds blew a record large portion of the Arctic’s multiyear sea ice (MYI) into the southern Beaufort Sea (SBS) in winter 2021. From early March, a network of buoys from the Sea Ice Dynamic Experiment (SIDEx) tracked the MYI as it drifted across the SBS toward the Chukchi Sea. Transport was episodic as the consolidated ice pack interacted with coastal boundaries and repeatedly fractured. We investigated variability in 2021 MYI transport by relating in situ sea ice drift to remotely sensed coastal lead opening events, which have been associated with increased ice drift speeds in winter. Daily ice concentration data show ten opening events occurred throughout March and April 2021. Opening lasted 1-5 consecutive days as southeasterly winds pushed the SBS ice pack away from coastal boundaries. During opening, the ice pack abruptly accelerated and its response to wind forcing stabilized around free drift conditions, drifting at 2.1 % of wind speeds (median rate of 13.7 km d −1 ). With this efficient wind-to-ice momentum transfer, nearly all (94 %) alongshore MYI transport in March-April 2021 occurred during opening events, which comprised just half of March-April days. Only 6 % of transport occurred during the other half of days without observed opening. On these days, the ice was mostly stationary (median 1.7 km d −1 drift rate, 0.6 % of wind speeds) as northwesterly winds compressed the pack against the coast. Spatiotemporal discontinuities in ice-wind speed ratios were measured across several coastal leads that transected the SIDEx buoy network, providing direct observations of changes in ice drift regime as coastal leads opened. These results quantify the disproportionate contribution of offshore and alongshore winds in breaking the SBS ice pack away from the coast, opening leads, and driving SBS ice transport during spring 2021, highlighting the critical role these episodic events play in consolidation season sea ice drift.

Oceanography↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
NASA NTRS1986

Morphology and properties of amine terminated poly(arylene ether ketone) and poly(arylene ether sulfone) modified epoxy resin systems

Epoxy resin networks cured with DDS were modified by incorporating tough ductile thermoplastics such as the amine terminated polyether sulfones and amine terminated polyether ketones. Both linear copolymers were able to significantly improve the fracture toughness values at the 15 and 30 weight percent concentrations examined. These improvements in fracture toughness were achieved without any significant change in the flexural modulus.

Cecere, J. A.↗
NASA NTRS1986

Toughening of BIS maleimide resins: Synthesis and characterization of maleimide terminated poly(arylene ether) oligomers and polymers

Amine functional poly(arylene ether) sulfones were previously reported. Herein, the chemistry was extended to amorphous poly(arylene ether) ketones because of their higher fracture toughness values, relative to the polysulfones. It was demonstrated that the amino functional oligomers undergo a self-crosslinking reaction at temperatures above about 220 C. This produces an insoluble, but ductile network that has excellent resistance. A ketamine structure hypothesis was proposed and verified using solid state magic angle NMR. In most cases, the water generated upon ketamine formation is too low to produce porosity and solid networks are obtained. The stability of the ketamine networks towards hydrolysis is excellent. The chemistry was further demonstrated to be able to crosslink preformed nonfunctional poly(arylene ether) ketones if a difunctional amine was utilized. This concept has the possibility of greatly improving the creep resistance of thermoplastics. Also, a new technique was developed for converting the amine functional oligomers cleanly into maleimide structures. This method involves reacting maleic anhydride with monomeric aminophenols in the presence of solvent mixtures.

Mcgrath, J. E.↗
NASA NTRS1987

Dynamic recrystallization and grain boundary migration in B2 FeAl

Transmission electron microscopy and optical microscopy were used to examine polycrystalline specimens of the B2-structured alloy FeAl strained under tension to fracture at elevated temperature. Strain-induced grain boundary migration was observed above 900 K and dynamic recrystallization was found at 1000 K and 1100 K. Little evidence of dynamic recovery was evident but some networks were formed at 1100 K.

Baker, I.↗
NASA NTRS2005

X-Aerogels for Structural Components and High Temperature Applications

Future NASA missions and space explorations rely on the use of materials that are strong ultra lightweight and able to withstand extreme temperatures. Aerogels are low density (0.01-0.5 g/cu cm) high porosity materials that contain a glass like structure formed through standard sol-gel chemistry. As a result of these structural properties, aerogels are excellent thermal insulators and are able to withstand temperatures in excess of l,000 C. The open structure of aerogels, however, renders these materials extremely fragile (fracturing at stress forces less than 0.5 N/sq cm). The goal of NASA Glenn Research Center is to increase the strength of these materials by templating polymers and metals onto the surface of an aerogel network facilitating the use of this material for practical applications such as structural components of space vehicles used in exploration. The work this past year focused on two areas; (1) the research and development of new templated aerogels materials and (2) process development for future manufacturing of structural components. Research and development occurred on the production and characterization of new templating materials onto the standard silica aerogel. Materials examined included polymers such as polyimides, fluorinated isocyanates and epoxies, and, metals such as silver, gold and platinum. The final properties indicated that the density of the material formed using an isocyanate is around 0.50 g/cc with a strength greater than that of steel and has low thermal conductivity. The process used to construct these materials is extremely time consuming and labor intensive. One aspect of the project involved investigating the feasibility of shortening the process time by preparing the aerogels in the templating solvent. Traditionally the polymerization used THF as the solvent and after several washes to remove any residual monomers and water, the solvent around the aerogels was changed to acetonitrile for the templating step. This process took a couple of days. It was experimentally determined that the polymerization reaction could be done in acetonitrile instead of THF with no detrimental effects to the properties of the resulting aerogel. Other changes in the time needed to crosslink the gels in the isocyanate solution as well as changes to the subsequent washing procedure could also shorten the processing time with no effect on the properties. Processing methods were also developed that allowed a variety of shapes as well as sizes of these materials to be formed.

Source record↗
DOE OSTI2024

Strain Field Around Individual Dislocations Controls Failure

Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Macromolecular differentiation of Golgi stacks in root tips of Arabidopsis and Nicotiana seedlings as visualized in high pressure frozen and freeze-substituted samples

The plant root tip represents a fascinating model system for studying changes in Golgi stack architecture associated with the developmental progression of meristematic cells to gravity sensing columella cells, and finally to "young" and "old", polysaccharide-slime secreting peripheral cells. To this end we have used high pressure freezing in conjunction with freeze-substitution techniques to follow developmental changes in the macromolecular organization of Golgi stacks in root tips of Arabidopsis and Nicotiana. Due to the much improved structural preservation of all cells under investigation, our electron micrographs reveal both several novel structural features common to all Golgi stacks, as well as characteristic differences in morphology between Golgi stacks of different cell types. Common to all Golgi stacks are clear and discrete differences in staining patterns and width of cis, medial and trans cisternae. Cis cisternae have the widest lumina (approximately 30 nm) and are the least stained. Medial cisternae are narrower (approximately 20 nm) and filled with more darkly staining products. Most trans cisternae possess a completely collapsed lumen in their central domain, giving rise to a 4-6 nm wide dark line in cross-sectional views. Numerous vesicles associated with the cisternal margins carry a non-clathrin type of coat. A trans Golgi network with clathrin coated vesicles is associated with all Golgi stacks except those of old peripheral cells. It is easily distinguished from trans cisternae by its blebbing morphology and staining pattern. The zone of ribosome exclusion includes both the Golgi stack and the trans Golgi network. Intercisternal elements are located exclusively between trans cisternae of columella and peripheral cells, but not meristematic cells. In older peripheral cells only trans cisternae exhibit slime-related staining. Golgi stacks possessing intercisternal elements also contain parallel rows of freeze-fracture particles in their trans cisternal membranes. We propose that intercisternal elements serve as anchors of enzyme complexes involved in the synthesis of polysaccharide slime molecules to prevent the complexes from being dragged into the forming secretory vesicles by the very large slime molecules. In addition, we draw attention to the similarities in composition and apparent site of synthesis of xyloglucans and slime molecules.

NASA Program Space Biology↗
NASA NTRS1987

Fabrication and characterization of amine terminated poly(arylene ether sulfone) modified epoxy-carbon fiber composites

Multifunctional epoxy resin networks were chemically modified with thermoplastic amine terminated poly(arylene ether sulfones) of controlled molecular weights. This system was then examined as both neat resin and as a matrix resin for carbon fiber composites. The neat resin displayed a significant increase in both fracture toughness and energy release rate values. This was attributed to the altered morphology, which could be varied from particles of polysulfone in an epoxy matrix to that of a quasi-continuous polysulfone phase.

Cecere, James A.↗
NASA NTRS1997

Structure-Property Relationships of Bismaleimides

The purpose of this research was to control and systematically vary the network topology of bismaleimides through cure temperature and chemistry (addition of various coreactants) and subsequently attempt to determine structure-mechanical property relationships. Characterization of the bismaleimide structures by dielectric, rheological, and thermal analyses, and density measurements was subsequently correlated with mechanical properties such as modulus, yield strength, fracture energy, and stress relaxation. The model material used in this investigation was 4,4'-BismaleiMidodIphenyl methane (BMI). BMI was coreacted with either 4,4'-Methylene Dianiline (MDA), o,o'-diallyl bisphenol A (DABA) from Ciba Geigy, or Diamino Diphenyl Sulfone (DDS). Three cure paths were employed: a low- temperature cure of 140 C where chain extension should predominate, a high-temperature cure of 220 C where both chain extension and crosslinking should occur simultaneously, and a low-temperature (140 C) cure followed immediately by a high-temperature (220 C) cure where the chain extension reaction or amine addition precedes BMI homopolymerization or crosslinking. Samples of cured and postcured PMR-15 were also tested to determine the effects of postcuring on the mechanical properties. The low-temperature cure condition of BMI/MDA exhibited the highest modulus values for a given mole fraction of BMI with the modulus decreasing with decreasing concentration of BMI. The higher elastic modulus is the result of steric hindrance by unreacted BMI molecules in the glassy state. The moduli values for the high- and low/high-temperature cure conditions of BMI/MDA decreased as the amount of diamine increased. All the moduli values mimic the yield strength and density trends. For the high-temperature cure condition, the room- temperature modulus remained constant with decreasing mole fraction of BMT for the BMI/DABA and BMI/DDS systems. Postcuring PMR-15 increases the modulus over that of the cured material even though density values of cured and postcured PMR were essentially the same. Preliminary results of a continuous and intermittent stress relaxation experiment for BMI:MDA in a 2:1 molar ratio indicate that crosslinking is occurring when the sample is in the undeformed state. Computer simulation of properties such as density, glass transition temperature, and modulus for the low- temperature cure conditions of BMI/MDA and BMI/DABA were completed. The computer modeling was used to help further understand and confirm the structure characterization results. The simulations correctly predicted the trends of these properties versus mole fraction BMI and were extended to other BMI/diamine systems.

Tenteris-Noebe, Anita D.↗
NASA NTRS1986

The crack layer approach to toughness characterization in steel

In a study of the laws of crack propagation and toughness characterization, it is feasible to employ two alternative approaches, including the fracture mechanics approach and the material science approach. The crack layer (CL) theory discussed by Khandogin and Chudnovsky (1978) and Chudnovsky (1980) considers the crack together with the surrounding defects as one system which has several degrees of freedom. It is pointed out that the CL theory defines the relationship between the parameters of fracture mechanics and the characteristics of microstructural changes which are the subject of material science. Experiments are described, taking into account a toughness characterization test and microscopic studies. Attention is given to a phenomenological study of toughness characterization, the morphology of crack layer, and the evaluation of energy stored in the dislocation network.

Bessendorff, M.↗
DOE OSTI2025

Numerical simulation of flow and mixing in fracture intersections

Fluid transport through fractured geological formations is strongly influenced by the redistribution of solutes at fracture intersections. In this study, we perform detailed numerical simulations of flow and scalar transport within the intersection of two smooth, planar fractures. The analysis focuses on the mixing ratio, the proportion of solute flux exiting along the outlet branch aligned with the primary inlet flow direction, relative to the total solute flux at the outlets. We systematically investigate how the mixing ratio varies with four key parameters: Peclet number, Reynolds number, flow rate ratio between outlet branches, and fracture intersection angle. Results show that the mixing ratio decreases with increasing Peclet number and outlet flow rate ratio, consistent with reduced diffusive spreading and enhanced streamline routing. While low Reynolds numbers have minimal impact, inertial effects at higher Reynolds numbers significantly increase the mixing ratio. Additionally, acute and obtuse intersection angles alter flow partitioning and modify the solute distribution at the outlets. These findings provide a quantitative basis for incorporating physically realistic mixing behavior—intermediate between complete mixing and streamline-following assumptions—into network-scale transport models. The results have direct relevance to subsurface energy systems, including geothermal energy production, carbon sequestration, and contaminant remediation.

58 GEOSCIENCES↗
DOE OSTI2024

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗
NASA NTRS2017

Antarctic Ice Shelf Potentially Stabilized by Export of Meltwater in Surface River

Meltwater stored in ponds and crevasses can weaken and fracture ice shelves, triggering their rapid disintegration. This ice-shelf collapse results in an increased flux of ice from adjacent glaciers and ice streams, thereby raising sea level globally. However, surface rivers forming on ice shelves could potentially export stored meltwater and prevent its destructive effects. Here we present evidence for persistent active drainage networks-interconnected streams, ponds and rivers-on the Nansen Ice Shelf in Antarctica that export a large fraction of the ice shelf's meltwater into the ocean. We find that active drainage has exported water off the ice surface through waterfalls and dolines for more than a century. The surface river terminates in a 130-metre-wide waterfall that can export the entire annual surface melt over the course of seven days. During warmer melt seasons, these drainage networks adapt to changing environmental conditions by remaining active for longer and exporting more water. Similar networks are present on the ice shelf in front of Petermann Glacier, Greenland, but other systems, such as on the Larsen C and Amery Ice Shelves, retain surface water at present. The underlying reasons for export versus retention remain unclear. Nonetheless our results suggest that, in a future warming climate, surface rivers could export melt off the large ice shelves surrounding Antarctica-contrary to present Antarctic ice-sheet models, which assume that meltwater is stored on the ice surface where it triggers ice-shelf disintegration.

Bell, Robin E.↗
DOE OSTI2024

Watching the Grand Ethiopian Renaissance Dam from a distance: Implications for sustainable water management of the Nile water

Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.

GRACE and GRACE-FO↗