Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “multiscale structure”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗
NASA NTRS2023

An Enabling Platform for Achieving Multiscale Multiphysics Analysis of Multiphase Materials

This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT) which address technical gaps in three of the Vision 2040 key discipline areas. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials and is available free through the NASA software catalog. It offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. The resulting anisotropic, evolving nonlinear, thermomechanical constitutive model can also be coupled with external software and used to perform multiscale analyses of more complex structures. A recent application to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis will be discussed. Since typical NASMAT analyses can be completed on the order of seconds to minutes, a second example will demonstrate the ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on implementing NASMAT within a multiscale digital thread/digital twin framework will also be addressed. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Multiscale↗
DOE OSTI2020

Hierarchical electrode design of highly efficient and stable unitized regenerative fuel cells (URFCs) for long-term energy storage

The unitized regenerative fuel cell (URFC) is a promising electrochemical device for intermittent renewable energy storage in chemical bonds. However, widespread application has been hindered due to low round-trip efficiencies (RTEs) and disappointing durability, in particular at high rates. In this study, we break through that barrier by demonstrating highly efficient, flexible, and stable URFCs via hierarchical design of the multiscale catalyst-layer structures. A more porous and less tortuous Pt and Ir catalyst layer is realized using a doctor blade fabrication method that significantly improves URFC performance. We demonstrate RTEs of 56% and 53% under constant-electrode and constant-gas mode, respectively, while operating at 1000 mA cm –2 , and significantly, a RTE of 45% at 2000 mA cm –2 , achievements that were previously viewed as unfeasible under the onerous demands of URFC operation. At the same time we demonstrate URFCs under both constant-electrode and constant-gas mode operated continuously for over 500 h with negligible degradation. These results demonstrate the viability of applying URFCs for long-term energy storage at previously unattainable efficiencies and cast new light on electrode design and optimization of URFCs.

25 ENERGY STORAGE↗
DOE OSTI2023

Capturing membrane structure and function in lattice Boltzmann models

Here, we develop a mesoscopic approach to model the nonequilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A general closure rule is developed to describe mass transport across the membrane, which is able to account for protein-mediated diffusion based on a coarse-grained representation. We demonstrate that our model is able to recover the Goldman equation from first principles and show that hyperpolarization occurs when membrane charging dynamics are controlled by multiple relaxation timescales. The approach provides a promising way to characterize non-equilibrium behaviors that arise due to the role of membranes in mediating transport based on realistic three-dimensional cell geometries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

River Delta Morphotypes Emerge From Multiscale Characterization of Shorelines

Abstract Delta shoreline structure has long been hypothesized to encode information on the relative influence of fluvial, wave, and tidal processes on delta formation and evolution. We introduce here a novel multiscale characterization of shorelines by defining three process‐informed morphological metrics. We show that this characterization yields self‐emerging classes of morphologically similar deltas, that is, delta morphotypes, and also predicts the dominant forcing of each morphotype. Then we show that the dominant forcings inferred from shoreline structure generally align with those estimated via relative sediment fluxes, while positing that misalignments arise from spatiotemporal heterogeneity in deltaic sediment fluxes not captured in their estimates. The proposed framework for shoreline characterization advances our quantitative understanding of how shoreline features reflect delta forcings, and may aid in deciphering paleoclimate from images of ancient deposits and projecting delta morphologic response to changes in sediment fluxes.

Vulis, L.↗
NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗
DOE OSTI2020

Microstructural Study of Hydration of C 3 S in the Presence of Calcium Nitrate Using Scanning Transmission X-Ray Microscopy (STXM)

Calcium nitrate (CN) is used widely as an effectively inorganic setting accelerator and antifreeze admixture in concrete structures. In this paper, the multiscale investigation of CN on the hydration of C 3 S was studied by scanning transmission X-ray microscopy (STXM) combined with near-edge X-ray absorption fine structure (NEXAFS), 29 Si MAS NMR, calorimetry, scanning electron microscope, and N 2 absorption. It was concluded that the calcium silicate hydrate (C-S-H) surrounds the unhydrated C 3 S at 1-day hydrated C 3 S in the presence of calcium nitrate, while portlandite is partly in transformation and is formed partly. Based on Ca L 3 , 2 -edge NEXAFS spectra for 1-day hydrated C 3 S particle, calcium nitrate does not change the structure of the asymmetrically 7-fold coordination of calcium in the C-S-H. Calcium nitrate can accelerate the hydration of C 3 S to some extent and polymerization of the silicate chains within C-S-H considerably at early age, resulting in the increasing specific surface area.

Li, Qinfei↗
DOE OSTI2021

Hierarchical porous metals with deterministic 3D morphology and shape via de-alloying of 3D printed alloys

The present disclosure relates to a method for forming a three dimensional, hierarchical, porous metal structure with deterministically controlled 3D multiscale pore architectures. The method may involve providing a feedstock able to be applied in an additive manufacturing process, and using an additive manufacturing process to produce a three dimensional (3D) structure using the feedstock. The method may involve further processing the 3D structure through at least a de-alloying operation to form a metallic 3D structure having an engineered, digitally controlled macropore morphology with integrated nanoporosity.

Qi, Zhen↗
NASA NTRS1991

Wave interactions with continuous fractal layers

Many natural structures possess self-similar multiscales which can be characterized by power law spectra. Under appropriate conditions, knowledge of the strength of these scale sizes provides information on the physical processes which formed these objects. In this paper, we investigate wave interactions with continuous fractal layers which model geological and variegated structures. Since fractal characteristics of the layers are embedded in the scattered field, they can be retrieved under appropriate conditions. This inversion can be performed in either the frequency or the time domain as desired.

Kim, Y.↗
DOE OSTI2025

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ionic-content-driven restructuring of spirobisindane ionene networks: implications for mechanics, self-healing, and gas transport

Polymers of intrinsic microporosity (PIMs) offer exceptional gas permeability but remain brittle and susceptible to physical aging, limiting their durability in separation applications. Here, we introduce a reconfigurable microporous polymer network that uniquely integrates permanent PIM microporosity with autonomous, intrinsic self-healing driven by imidazolium-based ionic motifs. Spirobisindane units generate the intrinsic free-volume architecture, while an imidazolium-containing polyamide ionene supplies dynamic ionic and hydrogen-bonding interactions that reorganize under mild activation. Incorporation of imidazolium-based ionic liquids further tunes cohesion, mobility, and densification, enabling the network to relax, re-associate, and retain microporosity without structural collapse. Through a comprehensive multiscale approach combining spectroscopy, scattering, thermal and mechanical characterization with all-atom molecular dynamics and density functional theory calculations, we elucidate how ionic content, as a single control parameter that reshapes free-volume distributions, modulates local coordination environments, and governs relaxation and healing kinetics. At intermediate ionic loadings, the networks achieve rapid, repeatable self-healing while maintaining CO$_2$ selectivity, demonstrating an optimal balance between segmental mobility and structural integrity. By establishing how hierarchical ionic interactions couple structure, dynamics, and transport in microporous ionene networks, this work provides generalizable design rules for adaptive soft-matter systems that require simultaneous mechanical resilience, reconfigurability, and selective gas transport.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theory and Simulation of Ultrafast Multidimensional Nonlinear X-ray Spectroscopy of Molecules (Final Report)

Emerging X-ray free electron laser (XFEL) beam sources offer new types of probes of matter with unprecedented spatial and temporal resolutions. These experimental advances must be met by robust theoretical and computational tools that provide predictive modeling capacity of the underlining electronic and structural dynamics. The latter will be essential for the design of sophisticated multi-pulse experiments and for their interpretation. The proposed research effort will focus on developing cutting- edge simulation tools for nonlinear multidimensional X-ray/optical spectroscopies and aims to address key questions in Priority Research Opportunities 1 (Probing and controlling electron motion within a molecule) and 3 (Capturing rare events and intermediate states in the transformation of matter) as mentioned in the BES Roundtable Report “Opportunities for Basic Research at the Frontiers of XFEL Ultrafast Science”. XFEL multidimensional nonlinear techniques, which combine sequences of X-ray and possibly optical pulses, provide a unique experimental toolbox for probing the dynamics of core and valence electronic excitations, as well as material structure. Predictive modeling of these dynamical processes requires the combination of analytical theory for nonlinear interactions of light and matter, robust quantum-chemical methodologies for the accurate description of electronic structure of various materials, and multiscale ab initio electron and nuclear dynamics techniques operating beyond Born-Oppenheimer approximation. These challenges will be addressed with three research thrusts (i) Develop and implement theoretical apparatus for modeling a broad range of multidimensional spectroscopic techniques enabled by present and upcoming XFEL facilities. This thrust also includes the incorporation of a computational module in the DOE supported open-source NWChem computational chemistry package as well as the development of other open-source codes ready for dissemination across a broad user base; (ii) Propose and design new multi-pulse experiments that make use of the capabilities of the incoming LCLS-II facility; (iii) Perform selected applications to specific molecular systems that can be carried out at LCLS-II and demonstrate how these X-ray sources may be used to study nonadiabatic dynamics through conical interactions, electronic correlations in multi-core excitons, and charge transfer/energy transfer processes. The proposed research will be carried out by a multi-disciplinary four-institution research team which combines academia and national laboratories and spans the broad and necessary expertise in theoretical spectroscopy, nonlinear optics, quantum chemistry, molecular non-adiabatic dynamics and code development. The work will be performed in a highly interactive team environment with junior researchers shared between institutions thus cementing cross- disciplinary interactions. The developed simulation tools will be immediately deployed for XFEL facility users, both experimentalists and theorists, via freely distributed codes and databases. Altogether, this project will facilitate establishing XFEL-based multidimensional spectroscopies as a novel diagnostic tool for monitoring electronic and structural dynamics in molecular materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Toward Multiscale, Multimaterial 3D Printing

Biological materials and organisms possess the fundamental ability to self-organize, through which different components are assembled from the molecular level up to hierarchical structures with superior mechanical properties and multifunctionalities. These complex composites inspire material scientists to design new engineered materials by integrating multiple ingredients and structures over a wide range. Additive manufacturing, also known as 3D printing, has advantages with respect to fabricating multiscale and multi-material structures. The need for multifunctional materials is driving 3D printing techniques toward arbitrary 3D architectures with the next level of complexity. In this paper, the aim is to highlight key features of those 3D printing techniques that can produce either multiscale or multimaterial structures, including innovations in printing methods, materials processing approaches, and hardware improvements. Several issues and challenges related to current methods are discussed. Ultimately, the authors also provide their perspective on how to realize the combination of multiscale and multimaterial capabilities in 3D printing processes and future directions based on emerging research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influences of shock imprinting on mix in a 3D-printed porous media

Mixing of materials in porous media can cause a significant impact on fusion yield as previously demonstrated by the National Ignition Facility (NIF) MARBLE Campaign. Initially, the reactants are separated, with deuterium in the lattice struts and a tritium gas fill in the voids. Lattice parameters such as the strut thickness and relative pitch, provide a control for the mix parameters in the experiment. Los Alamos National Laboratory’s (LANL) BOSQUE project looks to better understand how the mix of the reactants and shell materials impact the fusion burn and resultant yield on various laser platforms. xRAGE’s Eulerian hydrodynamics and adaptive mesh refinement (AMR) provide the unique ability to study the impacts of multiscale features of complex lattice structures. This modeling provides the ability to measure shock front variations as the wave progress’ through a given media. Initial conditions of the lattice are essential to accurately model mix and burn measured by experiment. By varying the initial orientation and densities of these lattice regions the early time dynamics of how the shock is launched into the system is changed and advocates for the study of resulting effects. In this work, we will study the sensitivities of shock effects in varying 3D printed geometric systems and how these shocks alter the structure and mix in the lattice. We will discuss both preliminary experimental results and simulations to help plan and constrain future experiments where we will study the impact of different lattice geometries and lattice bulk densities. This work concludes with the relative impacts of lattice geometries on shock speeds at different bulk densities and the resultant mix widths due to those shock interactions. We see agreement with theory at the higher end of our bulk density study, however, as we approach lower bulk density systems the dynamics of these interactions begin to change.

2 Photon Polymerization↗
DOE OSTI2021

Multi-scale Multi-physics Scientific Machine Learning for Water Cycle Extreme Events Identification, Labelling, Representation, and Characterization

Impacts of climate are usually felt through extreme events such as droughts, floods, thunderstorms, windstorms, wildfires, and so on, that are intimately tied to the water cycle. Predicting the frequency and severity of extreme events under climate change remains a significant challenge; meanwhile, the mechanisms and impacts of these extremes are far from well understood. There are several major science challenges: (1) Lack of labelled extreme events data and missing standards in defining extremes; (2) Computational demand of high-resolution ensemble climate modeling; (3) Modeling the multiscale multi-physics hierarchical structure of compound extremes; (4) Lack of understanding of mechanisms of extreme events; (5) Large uncertainty in extreme events impacts on infrastructure; (6) Subjective assessment of weather-related risk from seasonal to multi-decadal time scales and lack of metrics for risk assessment and mitigation control.

54 ENVIRONMENTAL SCIENCES↗