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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Simultaneous x-ray and neutron 4D tomographic study of drying-driven hydro-mechanical behavior of cement-based materials at moderate temperatures

The drying of cement-based materials is intimately related to their durability, which has significant economic, social and environmental repercussions. The evolution of the saturation of the pore network and the associated drying shrinkage are in fact leading causes of cracking and of the ensuing penetration of aggressive chemicals. This process is highly heterogeneous, due to the thermo-hydric spatial gradients developing in the material from the exposed surfaces to its core and because of local effects, driven by the intrinsically heterogeneous micro-structure (e.g., by the distribution of pores and aggregates). It follows that macroscopic, sample-scale measurements cannot fully disclose the complexity of the underlying processes. In the last few decades, significant advances in full-field techniques have allowed an unprecedented insight into these local processes. For cement-based materials, x-ray and neutron tomography lend themselves as ideal, and highly complementary, tools for the study of their thermo-hydro-mechanical behavior. Notably, the high sensitivity to density variations of x-ray imaging gives access to the developments of fractures, in 4D (3D + time). On the other hand, neutron tomography allows the study of the evolution of the moisture field in 4D, thanks to its high hydrogen sensitivity. The combination of these two techniques provides a unique insight in thermo-hydro-mechanical couplings, e.g., the effect of cracks on the water content field. This contribution presents novel 5D datasets (3D tomographies along time, plus truly simultaneous x-ray and Neutron rapid acquisitions) in-operando of a cement paste and of a concrete sample heated at moderate temperatures (up to 140{sup ∘}C). The analysis of this 5D data-set (once aligned in time and across modalities) allows for example a quantification of the 4D moisture profiles which were found to predict an overall water loss at hydric equilibrium coherent with the corresponding analytical analysis. In the cement paste sample, the x-ray dataset captures the evolution of an extensive cracking network, opening and propagation toward the core of the sample. A novel analysis procedure is here proposed which allows the extraction of these fractures and the analysis of their interplay with local drying as captured through neutron imaging. This for example reveals the depth of penetration of drying in the vicinity of the fractures along time, which is essential for the assessment and calibration of hydro-mechanical coupled models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cantor-derived medium-entropy alloys: bridging the gap between traditional metallic and high-entropy alloys

The year 2004 marked the beginning of a new era in the design of metallic materials, as the concept of multiple principal component alloys, commonly known as High-Entropy Alloys (HEAs), was proposed by Cantor and Yeh. The unexpected single-phase microstructure, instead of the expected brittle intermetallic compounds, was attributed to the large entropy of mixing and immediately caught the attention of the scientific community. Today, HEAs are considered important advanced materials and a broad range of alloys using nominally the same design principle have been investigated. Despite that, the CrMnFeCoNi (Cantor) alloy stands out as the most successful HEA due to its outstanding mechanical properties and microstructure. In this scenario, variants of the Cantor alloy, named medium-entropy alloys (MEAs), are gaining significant interest as they display a better industrial potential than both HEAs and traditional alloys. These variants of the Cantor alloy with only three or four main elements result in 15 possible combinations. The microstructure of these alloys is discussed in terms of advanced characterization as well as thermodynamic parameters and computational simulation. Their phase stability is addressed over a wide range of temperatures and strain rates. The mechanical properties, especially the fracture toughness, of the CrFeCoNi and CrCoNi alloys have been reported to be even superior to those of the Cantor alloy and most modern engineering alloys. This is associated with the formation of a continuous sequence of strengthening mechanisms, including hierarchical twin networks, which serve to prolong the strain hardening. The present article reviews and critically assesses, for the first time, recent advances in these Cantor-derived MEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of cyclic plasma heating on surface damage of micro-porous tungsten

The operating temperature window of solid tungsten (W) is dictated by its Ductile to Brittle Transition Temperature (DBTT) and re-crystallization temperature; roughly between 300-1300 °C. The brittleness of W at lower temperatures is exasperated when it undergoes recrystallization. We investigate here the thermal shock resistance of micro-porous W as a meta-material fabricated in a 3D open-cell network structure. We present experimental results for the effects of cyclic high-enthalpy arc-jet plasma on surface damage in three testing categories. Observed damage includes surface ablation of asperities, melting and solidification of W-fuzz on samples that have been exposed to a prior helium plasma, and micro-cracks at ligament triple junctions. Scanning electron microscope (SEM) observations show more micro-cracking on 54% and 23% foams compared to the 43% ones. In all tested samples, thermal expansion/contraction displacements were accommodated by ligament rotation and a network of micro-cracks. Furthermore, no large through-thickness crack were observed.

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.↗
DOE OSTI2021

Deep reinforcement learning control of hydraulic fracturing

Hydraulic fracturing is a technique to extract oil and gas from shale formations, and obtaining a uniform proppant concentration along the fracture is key to its productivity. Recently, various model predictive control schemes have been proposed to achieve this objective. But such controllers require an accurate and computationally efficient model which is difficult to obtain given the complexity of the process and uncertainties in the rock formation properties. In this article, we design a model-free data-based reinforcement learning controller which learns an optimal control policy through interactions with the process. Deep reinforcement learning (DRL) controller is based on the Deep Deterministic Policy Gradient algorithm that combines Deep-Q-network with actor-critic framework. In addition, we utilize dimensionality reduction and transfer learning to quicken the learning process. We show that the controller learns an optimal policy to obtain uniform proppant concentration despite the complex nature of the process while satisfying various input constraints.

42 ENGINEERING↗
DOE OSTI2021

A Self-Healable Sulfide/Polymer Composite Electrolyte for Long-Life, Low-Lithium-Excess Lithium-Metal Batteries

Solid electrolyte-protected lithium-metal anodes promise energy-dense, safe cells. While sulfide solid electrolytes enable facile processability and fast ion transport, they suffer from complex chemo-mechanical issues, including Li plating-induced fracture and Li stripping-induced contact loss. To address these issues, a grafting approach is implemented to functionalize the sulfide solid electrolyte (Li 3,85 Sn 0.85 Sb 0.15 S 4 ) with a self-healing unit. This leads to a dynamic bonding between the solid electrolyte network and a mechanically robust polymer scaffold, which reversibly accommodates the volume changes of the lithium-metal anode. Thus, the approach improves the interfacial contact between the lithium-metal anode and the composite electrolyte, enabling stable cycling at a mild stack pressure (160 kPa). With a negative to positive capacity ratio equals to 1, pouch full cells with a high-nickel cathode (nickel content > 90%) and lithium-metal anode display 92% capacity retention for 140 cycles. Engineering the interface between solid electrolyte and the polymeric binder offers a promising pathway to address the chemo-mechanical issues.

36 MATERIALS SCIENCE↗
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.↗
DOE OSTI2022

Subsurface stress criticality associated with fluid injection and determined using machine learning

Machine-learning methods and apparatus are disclosed to determine critical state or other parameters related to fluid-driven failure of a terrestrial locale impacted by anthropogenic activities such as hydraulic fracturing, hydrocarbon extraction, wastewater disposal, or geothermal harvesting. Acoustic emission, seismic waves, or other detectable indicators of microscopic processes are sensed. A classifier is trained using time series of microscopic data along with corresponding data of critical state or failure events. In disclosed examples, random forests and artificial neural networks are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to live data from a fluid injection locale in order to assess a frictional state, assess seismic hazard, assess permeability, make predictions regarding a future fluid-driven failure event, or drive engineering solutions for mitigation or remediation. Variations are disclosed.

Johnson, Paul Allan↗
DOE OSTI2024

Utah FORGE: Microseismic Surface Network Catalogs for Wells 16A(78)-32 and 16B(78)-32 Stimulation 2022 and Circulation 2023

This dataset includes microseismic surface network catalogs for Utah FORGE. Data were recorded during the stimulation of well 16A(78)-32 in 2022 and the circulation tests between wells 16A(78)-32 and 16B(78)-32 in 2023. Near-surface seismic monitoring during circulation experiments in wells 16A(78)-32 and 16B(78)-32 revealed fracture growth after shut-in. The catalog provided here offers a comprehensive list of microseismic events, including details on their spatial and temporal distribution, magnitude, and clustering behavior.

15 GEOTHERMAL ENERGY↗
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↗
DOE OSTI2021

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
NASA NTRS1973

Study of hypervelocity meteoroid impact on orbital space stations

Structural damage resulting in hypervelocity impact of a meteorite on a spacecraft is discussed. Of particular interest is the backside spallation caused by such a collision. To treat this phenomenon two numerical schemes were developed in the course of this study to compute the elastic-plastic flow fracture of a solid. The numerical schemes are a five-point finite difference scheme and a four-node finite element scheme. The four-node finite element scheme proved to be less sensitive to the type of boundary conditions and loadings. Although further development work is needed to improve the program versatility (generalization of the network topology, secondary storage for large systems, improving of the coding to reduce the run time, etc.), the basic framework is provided for a utilitarian computer program which may be used in a wide variety of situations. Analytic results showing the program output are given for several test cases.

Leimbach, K. R.↗