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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tao, Wei-Kuo↗
DOE OSTI2025

Unravelling Microstructure Selection in an Additively Manufactured Eutectic High‐Entropy Alloy

High-entropy alloys (HEAs) are promising candidates for advanced structural applications due to their excellent mechanical properties. Additive manufacturing (AM), with its rapid solidification conditions, enables the creation of unique nonequilibrium microstructures. To fully leverage the synergy between AM and HEAs, understanding how processing affects structure and properties is essential. Here, how solidification rate influences microstructure evolution and phase transformation pathway in laser additively manufactured AlCrFe2Ni2 eutectic HEAs is investigated. By increasing the laser scan speed and hence the solidification rate, distinct solidification modes evolving from coupled eutectic to anomalous eutectic and eventually to single-phase solidification are revealed. These transitions result in distinct microstructures and a wide range of mechanical properties. Thermodynamic modeling and molecular dynamics simulations reveal that low cooling rates allow for sufficient atomic diffusion and phase separation, facilitating coupled eutectic growth. In contrast, rapid cooling suppresses diffusion and destabilizes the solid–liquid interface, promoting anomalous or single-phase solidification. This integrated experimental and computational approach provides a multiscale understanding of solidification mechanisms in HEAs and underscores how kinetic effects can over-ride thermodynamic predictions under nonequilibrium conditions. Furthermore, these results demonstrate that AM can serve as a powerful tool to design HEAs with tailored microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

LDRD-DR: Accelerating Nuclear Fuel Qualification through Integrated Multiscale and Multiphysics Models [Slides]

Nuclear fuel qualification implies ensuring that a new fuel can safely operate in a reactor under both normal and accident conditions. Historically, extensive irradiation campaigns probe fuel performance relationships and interconnections in an integral sense, which is very time-consuming and costly. The presentation focus is on introducing advanced modeling and simulation into the qualification process in order to reduce the qualification timeline by targeting fewer integral tests

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Tissue scale agent-based simulation of premalignant progressions in Barrett’s esophagus

Barrett’s esophagus (BE) is a benign condition of the distal esophagus that initiates a multistage pathway to esophageal adenocarcinoma (EAC). Short of frequent intrusive (and costly) surveillance, effective screening for neoplasia in BE populations is yet to be established since progressors are rare and virtually undetectable without routine biopsies, which often sample only a small portion of the BE tissue. As a result, reliable estimation of the true prevalence of dysplasia in a BE population and evidence-based optimization of screening for at-risk individuals is challenging. Data-driven microsimulations, i.e., model-generated instances of disease history in a predefined virtual population, have found utility in the EAC screening literature as low-overhead alternatives to real-world hypothesis testing of optimal interventions for dysplasia. Despite the successes, computational limitations, paucity of knowledge and data on Barrett’s dysplasia, and the complexities of disease progression as a multiscale multiphysics process have hindered the treatment of disease progression in BE as a spatial process. Agent-based modeling of nucleation and proliferation processes in dysplasia warrants exploration in this context as an approximation that operates at a trade-off between computational tractability and precise representation of the composition and physics of the substrate (tissue). In this study, we describe spatially resolved simulations of premalignant progression toward EAC in a coarse-grained model of Barrett’s tissue that resolves the metaplastic tissue at a length scale of 0.42 mm (~3300 crypts/mm 2 ). Finally, the model is calibrated to reproduce historical high-grade dysplasia prevalence when model-generated patients are screened using the Seattle protocol.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Multidimensional modeling of fuel-cladding friction in an LWR fuel rod

Solving finite element problems with friction often increases the level of difficulty to obtain properly converged solutions. This type of challenge becomes more salient when advanced, possibly multiscale, material models are employed to capture the thermomechanical behavior of fuel and cladding materials. Here the present work details our recent developments in a nuclear fuel performance finite element code for the systematic consideration of friction in nuclear reactor finite element simulations. We show the application of friction and its effects on the mechanics of light-water reactor rods accounting for various fuel constitutive modeling techniques, model dimensionalities, pellet assumed geometries, and power conditions. In particular, we focus on the fuel rod mechanical behavior as it relates to fuel constitutive models, sensitivity to the coefficient of friction, pellet states of stress, and rod elongation. We discuss the trade-offs between the various multidimensional modeling options and highlight the relevance of frictional effects in the prediction of the fuel rod deformation and interfacial stresses. To relate our modeling results with actual reactor operation, simulations including frictional effects are compared with fuel rod elongation experimental data and some challenges for carrying out a full validation of the axial mechanics are discussed.

42 ENGINEERING↗
NASA NTRS2019

A Multiscale Nonlocal Progressive Damage Model for Composite Materials

In this paper, the advantages of a nonlocal progressive damage formulation are described and demonstrated. An approximation of the nonlocal formulation was implemented coupled with the MAT162 composite damage model as a User defined material model in the LS DYNA environment. A comparison of the local model and the nonlocal model is simulated for an 8-ply laminate under tension is carried for increasing mesh densities. The results show the regularization achieved by nonlocal models by providing mesh independent results.

Kodagali, Karan↗
NASA NTRSDate not supplied

Advances in Design Capabilities for Planetary Missions from the NASA Entry Systems Modeling and Instrumentation Portfolio

The Entry Systems Modeling project (ESM) is supported by both the NASA Space Technology and the Science Mission Directorates and focuses on developing simulation tools and validated models for characterizing the performance of entry systems tailored to planetary destinations across the Solar System. ESM is organized into six technical capability areas that together address all relevant factors related to spacecraft entry, as well as some aspects of descent: Thermal Protection System (TPS) Materials; Aerothermodynamics; Entry & Descent Vehicle Dynamics; Guidance, Navigation, and Control; Vehicle Systems Analysis; and Advanced Tools and Numerical Methods. Development within the capability areas is undertaken explicitly with a focus on transition and infusion to science missions, human exploration missions, and commercial space activities. The present talk details developments that specifically impact science missions, including simulation tool capabilities that aid in mission design and model development to understand entry system performance at a given destination. Examples of the successful infusion and transition of such project outcomes to science missions also are provided. Several simulation tool development efforts within ESM have resulted in new design capabilities for missions. One such outcome is improved toolsets for mission trajectory and concept of operations design. Specifically, an initiative to couple a leading tool for entry, ascent/descent, and orbital trajectory optimization (Program to Optimize Simulated Trajectories II or POST2) to those used within the Agency for interplanetary trajectory optimization (Copernicus and Monte) has made substantial progress, with the outcomes to date promising to allow efficient trajectory optimization across mission phases. Additionally, toolchains for the evaluation of vehicle performance during entry and descent have been developed that allow assessment of multi-dimensional aeroheating on detailed vehicle geometries, characterization of deployment and inflation of parachutes, and assessment of vehicle dynamic stability during descent. These capabilities are achieved by coupling diverse sets of physics together – material response, computational fluid dynamics, radiation, and vehicle dynamics – to suitably describe complex entry and descent phenomena. Several model development and validation efforts for specific destinations and entry regimes also are underway within the ESM project. For instance, new experimental capabilities to validate radiation models at low densities/high altitudes recently have been established with project support, specifically the Low-Density Shock Tube (LDST) at the NASA Ames Research Center Electric Arc Shock Tube (EAST) facility. The LDST is being leveraged to develop improved models of shock layer kinetics and radiation in Titan atmospheres, while future studies will be conducted in the LDST and the existing high velocity shock tube to provide validation data for radiation models of Venus, Ice Giants, and Mars atmospheres. Models describing the aerothermal and thermo-structural performance of Thermal Protection System (TPS) materials has been another focus, with multiscale modeling activities on-going for the two leading TPS materials applicable to a range of entry conditions and science missions: the Phenolic-Impregnated Carbon Ablator (PICA) and woven materials like 3D Mid-Density Carbon Phenolic (3MDCP). A continual effort is made to infuse and transition outcomes from ESM simulation tool and model development activities into relevant science missions. Significant progress has been made on this front, with missions such as Dragonfly, DAVINCI, and Mars Missions benefitting from project outcomes. The groundwork also is being laid to provide insights into forward looking missions to Gas/Ice Giants as well as for potential sample returns.

Justin Haskins↗
DOE OSTI2021

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Optimization Methodology of Polar Direct-Drive Illumination for the National Ignition Facility

Improved laser illumination uniformity drives shocks and implosions to create more extreme high energy density environments. Predominantly, the geometry of experiments that can be performed is dictated by the layout of beams at laser facilities, limiting inter-facility and multiscale investigations. This Letter presents the first automated, algorithmic approach for generating illumination configurations for high energy density experiments. The method is demonstrated in comparison to a polar direct drive solid target experiment at the National Ignition Facility. The new illumination configuration is simulated to create greater than ×3 higher peak pressure and almost ×2 higher density by maintaining better shock uniformity. Furthermore, the optimization process is performed with reduced computational expense and isotropic plasma profiles, while accounting for the impact of cross-beam energy transfer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The role of moisture in MgCl 2 salt: A multiscale approach to TES performance

This study presents a comprehensive multiscale analysis to evaluate the influence of moisture on the thermal performance of thermal energy storage systems using magnesium chloride (MgCl 2 ) as the phase-changing material. The system uses graphite foam with 90% relative density to enhance thermal conductivity. The analysis includes thermal conductivity calculations and specific heat capacity for different hydrate phases of MgCl 2 : Anhydrous, Mono, Di, Tetra, and Hexa. These properties were evaluated for the first time using the phonon density of states from Density Functional Theory simulations. Results showed that thermal conductivity decreased, while specific heat capacity increased by a factor of two as the phase changed from anhydrous to hexahydrate. Meso-scale models were created to account for the anisotropy of graphite foam and property variations of the MgCl 2 hydrate phases. Asymptotic Expansion homogenization simulations determined the anisotropic thermal conductivity for all phases. This unique methodology improved simulation accuracy, which matched experimental data for anhydrous MgCl 2 . A parametric study examined various operating conditions and their effect on TES performance. It revealed that higher charging temperatures did not enhance exergy efficiency, but increased discharge mass flow rates improved it due to better heat transfer. Thermal performance evaluated by the exergy efficiency remained consistent across hydrate systems under the tested conditions. Furthermore, the study suggests that this uniformity is linked to missing key data, particularly latent heat and melting point for different hydrates. Overall, it highlights the importance of multiscale effects and accurate material properties in designing and optimizing TES systems.

Molten salt degradation↗
NASA NTRS2010

Modeling Progressive Damage Using Local Displacement Discontinuities Within the FEAMAC Multiscale Modeling Framework

A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.

Ranatunga, Vipul↗
NASA NTRS2021

Evaluating the De Hoffmann-Teller Cross-Shock 2 Potential at Real Collisionless Shocks

Shock waves are common in the heliosphere and beyond. The collisionless nature of most astrophysical plasmas allows for the energy processed by shocks to be partitioned amongst particle sub-populations and electromagnetic fields via physical mechanisms that are not well understood. The electrostatic potential across such shocks is frame dependent. In a frame where the incident bulk velocity is parallel to the magnetic field, the deHoffmann-Teller frame, the potential is linked directly to the ambipolar electric field established by the electron pressure gradient. Thus measuring and understanding this potential solves the electron partition problem, and gives insight into other competing shock processes. Integrating measured electric fields in space is problematic since the measurements can have offsets that change with plasma conditions. The offsets, once integrated, can be as large or larger than the shock potential. Here we exploit the high-quality field and plasma measurements from NASA’s Magnetospheric Multiscale mission to attempt this calculation. We investigate recent adaptations of the deHoffmann-Teller frame transformation to include time variability, and conclude that in practice these face difficulties inherent in the 3D time-dependent nature of real shocks by comparison to 1D simulations. Potential estimates based on electron fluid and kinetic analyses provide the most robust measures of the deHoffmann-Teller potential, but with some care direct integration of the electric fields can be made to agree. These results suggest that it will be difficult to independently assess the role of other processes, such as scattering by shock turbulence, in accounting for the electron heating.

Steven J Schwartz↗
NASA NTRSDate not supplied

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho↗
DOE OSTI2023

Kinetic Growth of Multicomponent Microcompartment Shells

An important goal of systems and synthetic biology is to produce high value chemical species in large quantities. Microcompartments, which are protein nanoshells encapsulating catalytic enzyme cargo, could potentially function as tunable nanobioreactors inside and outside cells to generate these high value species. Modifying the morphology of microcompartments through genetic engineering of shell proteins is one viable strategy to tune cofactor and metabolite access to encapsulated enzymes. However, this is a difficult task without understanding how changing interactions between the many different types of shell proteins and enzymes affect microcompartment assembly and shape. Here, we use multiscale molecular dynamics and experimental data to describe assembly pathways available to microcompartments composed of multiple types of shell proteins with varied interactions. As the average interaction between the enzyme cargo and the multiple types of shell proteins is weakened, the shell assembly pathway transitions from (i) nucleating on the enzyme cargo to (ii) nucleating in the bulk and then binding the cargo as it grows to (iii) an empty shell. Atomistic simulations and experiments using the 1,2-propanediol utilization microcompartment system demonstrate that shell protein interactions are highly varied and consistent with our multicomponent, coarse-grained model. Furthermore, our results suggest that intrinsic bending angles control the size of these microcompartments. Altogether, our simulations and experiments provide guidance to control microcomparmtent size and assembly by modulating the interactions between shell proteins.

defects↗
DOE OSTI2020

Electro-reduction of organics on metal cathodes: A multiscale-modeling study of benzaldehyde on Au (111)

Here, we present a multiscale modeling study on the electro-reduction of benzaldehyde (BZY) on Au(111) under realistic electrochemical conditions. To model the electrochemical cell, we adopt a capacitor model in which complex solvents are confined between a Au cathode and a carbon anode. Classical molecular dynamics simulations reveal that electrode charge density and the presence of alcohol show strong effects on the density, adsorption geometry and dynamics of benzaldehyde on the Au electrode. Under charging conditions, the surface concentration of benzaldehyde on the Au electrode decreases, while the content of other species increases. Finally, we proposed a scheme that correlates the electric current running through the Au/solvent interface with the applied bias. This study provides a molecular level understanding of how solvent composition, in this case water/alcohol content, controls the activity of electrocatalytic hydrogenation

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A multiscale anisotropic polymer network model coupled with phase field fracture

The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.

42 ENGINEERING↗
NASA NTRS2012

Multiscale Fatigue Life Prediction for Composite Panels

Fatigue life prediction capabilities have been incorporated into the HyperSizer Composite Analysis and Structural Sizing Software. The fatigue damage model is introduced at the fiber/matrix constituent scale through HyperSizer s coupling with NASA s MAC/GMC micromechanics software. This enables prediction of the micro scale damage progression throughout stiffened and sandwich panels as a function of cycles leading ultimately to simulated panel failure. The fatigue model implementation uses a cycle jumping technique such that, rather than applying a specified number of additional cycles, a specified local damage increment is specified and the number of additional cycles to reach this damage increment is calculated. In this way, the effect of stress redistribution due to damage-induced stiffness change is captured, but the fatigue simulations remain computationally efficient. The model is compared to experimental fatigue life data for two composite facesheet/foam core sandwich panels, demonstrating very good agreement.

Bednarcyk, Brett A.↗