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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Potential Energy Hotspot: Effects of Impact Velocity, Defect Geometry, and Crystallographic Orientation

In energetic materials, the localization of energy into “hotspots” is known to dictate the initiation of chemical reactions and detonation. Recent all-atom simulations have shown that more energy is localized as internal potential energy (PE) than can be inferred from the kinetic energy (KE) alone. The mechanisms associated with pore collapse and hotspot formation are known to depend on pore geometry and dynamic material response such as plasticity. Therefore, we use molecular dynamics (MD) simulations to characterize shock-induced pore collapse and the subsequent formation of hotspots in 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a highly anisotropic molecular crystal, for various defect shapes, shock strengths, and crystallographic orientations. We find that the localization of energy as PE is consistently larger than the KE in cases with significant plastic deformation. Additionally, an analysis of MD trajectories reveals the underlying molecular- and crystal-level processes that govern the effect of orientation and pore shape on PE localization. We find that the regions of highest PE relate to the areas of maximum plastic deformation, while KE is maximized at the point of impact. Comparisons against octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) reveal less energy localization in TATB, which could be a contributing factor to the latter’s insensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulating the non-monotonic strain response of nanoporous multiferroic composites under electric field control

In this work, we simulate and analyze the mechanical response of a class of multiferroic materials consisting of a templated porous nanostructure made out of cobalt ferrite (CFO) partially filled by atomic layer deposition (ALD) with a ferroelectric phase of lead zirconate titanate (PZT). The strain in the device is measured when an electric field is applied for varying ALD thicknesses, displaying a non-monotonic dependence with a maximum strain achieved for a coating thickness of 3 nm. To understand this behavior, we apply finite element modeling to the smallest repeatable unit of the nanoporous template and simulate the mechanical response as a function of PZT coating thickness. We find that this non-monotonic response is caused by the interplay between two driving forces opposing one another. First, increased porosity works toward increasing the strain due to a reduced system stiffness. Second, decreased porosity involves a larger mass fraction of PZT, which drives the electro-mechanical response of the structure, thus leading to a larger strain. The balance between these two driving forces is controlled by the shear coupling at the CFO/PZT interface and the effective PZT cross section along the direction of the applied electric field. Here, our numerical results show that considering a nonlinear piezoelectric response for PZT leads to an improved agreement with the experimental data, consistent with ex situ poling of the nanostructure prior to magnetic measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Role of nanoscale coherent precipitates on the thermo-mechanical response of martensitic materials (Final Report)

Coherent second phases can have a profound effect on the properties and performance of martensitic materials, and we lack a comprehensive, mechanistic understanding of the underlying processes. This limits our ability to rationally design second phases to tailor the response of martensitic materials. To address this situation, this project sought to develop a mechanistic, predictive understanding of the thermal and mechanical response of martensitic materials with nanoscale coherent heterogeneities. A synergistic combination of atomistic simulations and experiments was used to relate the local properties of each phase (in particular, their free energy landscape) and the material nanostructure (volume fraction, shape and size of second phase precipitates, and defects that may disrupt coherency) to the overall materials response. The focus was on second phases expected to induce phenomena or properties not otherwise achievable: second order martensitic transformation in SMAs, ultra-low stiffness, increased control of transition temperatures, and fatigue resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of directed aging on nonlinear elasticity and memory formation in a material

Disordered solids often change their elastic response as they slowly age. Using experiments and simulations, we study how aging disordered planar networks under an applied stress affects their nonlinear elastic response. We are able to modify dramatically the elastic properties of our systems in the nonlinear regime. Using simulations, we study two models for the microscopic evolution of properties of such a material; the first considers changes in the material strength, while the second considers distortions in the microscopic geometry. Both models capture different aspects of the experiments including the encoding of memories of the aging history of the system and the dramatic effects on the material’s nonlinear elastic properties. Our results demonstrate how aging can be used to create complex elastic behavior in the nonlinear regime.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Geometric and Material Variability Influences Stress States Relevant to Coastal Permafrost Bluff Failure

Scientific knowledge and engineering tools for predicting coastal erosion are largely confined to temperate climate zones that are dominated by non-cohesive sediments. The pattern of erosion exhibited by the ice-bonded permafrost bluffs in Arctic Alaska, however, is not well-explained by these tools. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is needed. We conducted physics-based numerical simulations of mechanical response that focus on the impact of geometric and material variability on permafrost bluff stress states for a coastal setting in Arctic Alaska that is prone to toppling mode block failure. Our three-dimensional geomechanical boundary-value problems output static realizations of compressive and tensile stresses. We use these results to quantify variability in the loci of potential instability. We observe that niche dimension affects the location and magnitude of the simulated maximum tensile stress more strongly than the bluff height, ice wedge polygon size, ice wedge geometry, bulk density, Young's Modulus, and Poisson's Ratio. Our simulations indicate that variations in niche dimension can produce radically different potential failure areas and that even relatively shallow vertical cracks can concentrate displacement within ice-bonded permafrost bluffs. These findings suggest that stability assessment approaches, for which the geometry of the failure plane is delineated a priori, may not be ideal for coastlines similar to our study area and could hamper predictions of erosion rates and nearshore sediment/biogeochemical loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A comparison of surrogate constitutive models for viscoplastic creep simulation of HT-9 steel

Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models become increasingly more complex – often involving coupled differential equations describing the effect of specific deformation modes – their associated computational costs can become prohibitive, particularly in optimization or uncertainty quantification tasks that require numerous model evaluations. To address this challenge, surrogate constitutive models that balance accuracy and computational efficiency are highly desirable. Data-driven surrogate models, that learn the constitutive relation directly from data, have emerged as a promising solution. In this work, we develop two local surrogate models for the viscoplastic response of a steel: a piecewise response surface method and a mixture of experts model. These surrogates are designed to adapt to complex material behavior, which may vary with material parameters or operating conditions. The surrogate constitutive models are applied to creep simulations of HT-9 steel, an alloy of considerable interest to the nuclear energy sector due to its high tolerance to radiation damage, using training data generated from viscoplastic self-consistent (VPSC) simulations. In conclusion, we define a set of test metrics to numerically assess the accuracy of our surrogate models for predicting viscoplastic material behavior, and show that the mixture of experts model outperforms the piecewise response surface method in terms of accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flow and Arching of Biomass Particles in Wedge-Shaped Hoppers

Poor understanding of the flow behavior of granular biomass material poses great challenges for the bioenergy industry, as the equipment functioning time is significantly reduced by handling issues like screw feeder clogging and hopper arching. In this work, the flow behavior of loblolly pine chips, including the mass flow rate and the critical outlet width, in a wedge-shaped hopper is investigated by combining physical experiments and numerical simulations. Comprehensive characterization of the flow response affected by the two material attributes (initial packing, particle density) and the three operational parameters (hopper outlet width, hopper inclination, and surcharge) is conducted. The results show that the hopper outlet width linearly controls the mass flow rate while the hopper inclination angle controls the critical outlet size. The packing determines whether the flow is smooth or surging, and the surcharge-induced compaction creates flow impedance. The magnitude of these influences varies from a slender hopper with a low inclination angle to a flat-bottom silo. These findings provide guidance for hopper operation in the material handling industry and shed light on the construction of a novel design method for material handling equipment in biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2023

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Recent developments integrating micromechanics and neural networks offer promising paths for rapid predictions of the response of heterogeneous materials with similar accuracy as direct numerical simulations. The deep material network is one such approaches, featuring a multi-layer network and micromechanics building blocks trained on anisotropic linear elastic properties. Once trained, the network acts as a reduced-order model, which can extrapolate the material’s behavior to more general constitutive laws, including nonlinear behaviors, without the need to be retrained. However, current training methods initialize network parameters randomly, incurring inevitable training and calibration errors. Here, we introduce a way to visualize the network parameters as an analogous unit cell and use this visualization to “quilt” patches of shallower networks to initialize deeper networks for a recursive training strategy. The result is an improvement in the accuracy and calibration performance of the network and an intuitive visual representation of the network for better explainability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrating Advanced Modeling and Accelerated Testing for a Modernized Fuel Qualification Paradigm

With the increasing interest in sodium fast reactor technology, as seen by applications to the U.S. Nuclear Regulatory Commission for the OKLO Aurora plant, fuel testing for the TerraPower Traveling Wave Reactor, and the impending construction and startup of the versatile test reactor (VTR), a modernized, accelerated approach to fuel qualification is needed. To guide this effort, a Phenomena Identification Ranking Table–styled analysis was performed for a U-Pu-Zr sodium-free annular fuel system. This analysis evaluated a series of fuel design properties and parameters against their contributions to key fuel performance phenomena. The resulting priority parameters were then reviewed against existing modeling and experimental capabilities to support investigation of the highest-priority parameters. A pathway for qualification was then established using highthroughput, high-volume experiments from MiniFuel and FAST in parallel with advanced physics-based model development. This effort outlines how the first stages of qualification can be reduced from the typical 20+-year development cycle to 5 to 7 years by deploying accelerated irradiation testing platforms. As with any accelerated test, these methods are prototypic in some aspects and less so in others; however, by coupling with advanced fuel performance modeling and simulation capabilities, the larger space of irradiation parameters and material response provided offers advantages for the validation of physics-based models supporting the deployment of novel fuel designs. As a test case, this paper utilizes a proposed Mark II fuel system for the upcoming VTR. Thus, an accelerated qualification method can be tested for the development of MARK II driver fuel so that by the time of VTR startup, lead test assemblies for a Mark II fuel can be initiated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Modeling detonation with CartaBlanca simulations

The accurate modeling of high explosive (HE) detonation and the con- sequent large solid deformation, failure, plastic flow, porosity growth, and shock wave propagation is important because simulations can capture spatial and temporal features that experimental diagnostics cannot capture. However, the simulation of the explosive event poses challenges to a computational scientist. These include the accurate modeling of ductile damage, crack formation, plastic deformation, as well as physical and nu- merical instabilities. The material response can be history-dependent and subject to large material deformation. Our research simulates the impact of a high explosive (Detasheet) onto a tantulum metal plate. We performed the simulations using CartaBlanca at different mesh resolutions. We decided the study would be impactful if we perform the simulations with the Material Point Method. Differences were observed at the different mesh resolutions in velocity and nodal stress magnitude, so increased mesh resolutions may be required. In addition, the Discontinuous Galerkin method would be needed to account for the large gas expansion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring pressure-dependent inelastic deformation and failure in bonded granular composites: An energetic materials perspective

In polymer-filled granular composites, damage may develop in mechanical loading prior to material failure. Damage mechanisms such as microcracking or plastic deformation in the binder phase can substantially alter the material’s mesostructure. For energetic materials, such as solid propellants and plastic bonded explosives, these mesostructural changes can have far reaching effects including degraded mechanical properties, potentially increased sensitivity to further insults, and changes in expected performance. Unfortunately, predicting damage is nontrivial due to the complex nature of these composites and the entangled interactions between inelastic mechanisms. In this work, we assess the current literature of experimental knowledge, focusing on the pressure-dependent shear response, and propose a simple simulation framework of bonded particles to study four limiting-case material formulations at both meso- and macro-scales. Further, to construct the four cases, we systematically vary the relative interfacial strength between the polymer binder and granular filler phase and also vary the polymer’s glass transition temperature relative to operating temperature which determines how much the binder can plastically deform. These simulations identify key trends in global mechanical response, such as the emergence of strain hardening or softening regimes with increasing pressure which qualitatively resemble experimental results. By quantifying the activation of different inelastic mechanisms, such as bonds breaking and plastically straining, we identify when each mechanism becomes relevant and provide insight into potential origins for changes in mechanical responses. The locations of broken bonds are also used to define larger, mesoscopic cracks to test various metrics of damage. We primarily focus on triaxial compression, but also test the opposite case of triaxial extension to highlight the impact of Lode angle on mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗
DOE OSTI2020

Dynamically morphing microchannels in liquid crystal elastomer coatings containing disclinations

Liquid crystal elastomers (LCEs) hold a major promise as a versatile material platform for smart soft coatings, since their orientational order can be predesigned to program a desired dynamic profile. In this work, we introduce temperature-responsive dynamic coatings based on LCEs with arrays of singular defects-disclinations that run parallel to the surface. The disclinations form in response to antagonistic patterns of the molecular orientation at the top and bottom surfaces, imposed by the plasmonic mask photoalignment. Upon heating, an initially flat LCE coating develops linear microchannels located above each disclination. The stimulus that causes a non-flat profile of LCE coatings upon heating is the activation force induced by the gradients of molecular orientation around disclinations. To describe the formation of microchannels and their thermal response, we adopt a Frank-Oseen model of disclinations in patterned director field and propose a linear elasticity theory to connect the complex spatially-varying molecular orientation to the displacements of the LCE. The thermo-responsive surface profiles predicted by the theory and by the finite element modeling are in good agreement with the experimental data; in particular, higher gradients of molecular orientation produce a stronger modulation of the coating profile. The elastic theory and the finite element simulations allow us to estimate the material parameter that characterizes the elastomer coating’s response to the thermal activation. The disclinations containing LCEs show potential as soft dynamic coatings with a predesigned responsive surface profile.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nuclear magnetic resonance and molecular simulation study of H 2 and CH 4 adsorption onto shale and sandstone for hydrogen geological storage

Understanding pure H 2 and H 2 /CH 4 adsorption and diffusion in earth materials is one vital step toward a successful and safe H 2 storage in depleted gas reservoirs. Despite recent research efforts such understanding is far from complete. In this work we first use Nuclear Magnetic Resonance (NMR) experiments to study the NMR response of injected H 2 into Duvernay shale and Berea sandstone samples, representing materials in confining and storage zones. Then we use molecular simulations to investigate H 2 /CH 4 competitive adsorption and diffusion in kerogen, a common component of shale. Our results indicate that in shale there are two H 2 populations, i.e., free H 2 and adsorbed H 2 , that yield very distinct NMR responses. However, only free gas presents in sandstone that yields a H 2 NMR response similar to that of bulk H 2 . About 10 % of injected H 2 can be lost due to adsorption/desorption hysteresis in shale, and no H 2 loss (no hysteresis) is observed in sandstone. Here, our molecular simulation results support our NMR results that there are two H 2 populations in nanoporous materials (kerogen). The simulation results also indicate that CH 4 outcompetes H 2 in adsorption onto kerogen, due to stronger CH 4 -kerogen interactions than H 2 -kerogen interactions. Nevertheless, in a depleted gas reservoir with low CH 4 gas pressure, about ~30 % of residual CH 4 can be desorbed upon H 2 injection. The simulation results also predict that H 2 diffusion in porous kerogen is about one order of magnitude higher than that of CH 4 and CO 2 . This work provides an understanding of H 2 /CH 4 behaviors in deleted gas reservoirs upon H 2 injection and predictions of H 2 loss and CH 4 desorption in H 2 storage.

08 HYDROGEN↗
DOE OSTI2021

Advances in Multimodal Characterization of Structural Materials

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers

This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Three-dimensional modeling and simulations of single-crystal and bi-crystal titanium for high-strain-rate loading conditions

High purity single crystal titanium (Ti) under shock wave loading is modeled under both one-dimensional and three-dimensional cylindrical conditions. Cylinder sizes of 10 μm and 20 μm radius are both considered in order to assess influence of boundary conditions. A thermodynamically consistent single crystal model for application to shock conditions is presented. The model accounts for the coupled non-linear elastic, dislocation slip, deformation twinning, and structural phase transformation response of the titanium material. Plate impact experiment results using a copper flyer are used to compare against the simulations for crystals oriented in [0001] and [10$\overline1$1] crystallographic directions. The one-dimensional and threedimensional simulations of the two differently oriented single crystals indicate differences between the one-dimensional and three-dimensional representation, especially for the [10$\overline1$1] oriented single crystal. This orientation breaks the relative orientation symmetry between the crystal and cylinder which otherwise exists for the [0001] oriented single crystal. A significant amount of heterogeneity in the field response of the[10$\overline1$1] oriented simulation was demonstrated due to the highly coupled nature of the deformation. A bi-crystal model composed of both the [0001] and [10$\overline1$1] orientations with the boundary between the two along the axis of the cylinder is also considered for a cylinder model size of 10 μm. The results indicate a strong interaction between the two grains that affects the ω phase volume fraction achieved relative to the single crystal calculations.

36 MATERIALS SCIENCE↗