Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “block 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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗
DOE OSTI2024

Adaptive Mesh Refinement Simulations for Turbulent Reacting Flow

With the increased availability of exascale computing hardware, detailed simulations of realistic devices can be performed at practically relevant time and length scales. Insights into the multiscale driving mechanisms in compressible reacting flow systems with complex geometry, such as combustors, can be used for design optimization and technology improvements. However, to effectively perform these simulations, advanced numerical algorithms must be used to maintain solution accuracy without incurring undue computational costs. PeleC, part of the Pele suite of codes, leverages block-structured adaptive mesh refinement (AMR) through the AMReX library to capture fine-scale flow features in compressible reacting flows. In this talk, we discuss recent improvements to the numerical algorithms, particularly in regard to describing flows at complex boundary structures, and PeleC's performance on exascale computing hardware. We will demonstrate that PeleC is well-suited for modern, extreme-scale, heterogenous compute platforms.

combustion↗
DOE OSTI2024

Influence of Real Gas Effects on Chemical Kinetics in Oxycombustion in Supercritical Carbon Dioxide

Oxycombustion in supercritical carbon dioxide is an integral part of the Allam Cycle, a technology that enables carbon-neutral use of fossil-fuels and carbon-negative use of biofuels. We simulate oxycombustion in a realistic combustor geometry for two sets of fuel conditions: pure methane, and a 40 percent methane/60 percent carbon dioxide blend, both at 343.15 K. The fuel jet mixes with a preheated swirler of 20 percent oxygen and 80 percent carbon dioxide at 1005.35 K, with a 100 percent carbon dioxide coflow at 783.15 K. The entire system operates at a pressure of 300 bar, putting the entire system above the critical temperature and pressure of carbon dioxide. Simulations are performed using PeleC, a compressible block-structured adaptive-mesh refinement (AMR) reacting flow code. Direct comparison of results using thermodynamically self-consistent implementations of the ideal gas equation of state and the Soave-Redlich-Kwong (SRK) equation of state allow quantification of the real gas impacts on combustion kinetics, flow temperatures, and pollutant formation.

carbon dioxide↗
DOE OSTI2024

Thermal conductivity of 3D-printed block-copolymer-inspired structures

This study primarily focuses on examining the impact that geometric structure has on thermal conductivity of multi-phase constructs in different 3D-printed poly(lactic acid), PLA, samples. The investigated structures are inspired by morphologies formed by diblock copolymers: lamellae, hexagonally packed cylinders, and gyroid. This research also investigates how volume percentage and material combination influence the thermal conductivity of these structures. Further, the samples can be tailored to simulate various thermal management structures observed in practical applications, such as thermal interface materials in electronic devices. Thermal conductivity ratio is controlled using air, the least conductive material at 0.026 W/(m K), PLA at 0.136 W/(m K), and thermal paste at 5.11 W/(m K). Different models were tested against thermal conductivity measurements in order to capture the effect of material type (PLA-Air versus PLA-Thermal Paste), volume percentage, structure, and orientation. Simple, effective medium models were good predictions of thermal conductivity in lamellar structures, but it was necessary to develop models for conduction through cylindrical and gyroid structures. Finally, all results were normalized to find a universal model that is independent of structure and material. This approach provides a simple method to predict how to reduce or enhance transport properties and heat management capabilities of 3D printed objects.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine Learning Framework for Characterizing Processing–Structure Relationship in Block Copolymer Thin Films

The morphology of block copolymers (BCPs) critically influences material properties and applications. This work introduces a machine learning (ML)-enabled, high-throughput framework for analyzing grazing incidence small-angle X-ray scattering (GISAXS) data and atomic force microscopy (AFM) images to characterize BCP thin film morphology. A convolutional neural network was trained to classify AFM images by surface features, achieving 97% testing accuracy. Classified images were then analyzed to extract 2D grain size measurements from the samples in a high-throughput manner. ML models were trained to predict domain orientation based on processing parameters such as solvent ratio, additive type, and additive ratio. GISAXS-based properties were predicted with strong performances (R 2 > 0.75), while AFM-based property predictions were less accurate (R 2 < 0.60), likely due to the localized nature of AFM measurements compared to the bulk information captured by GISAXS. Beyond model performance, interpretability was addressed using SHapley Additive exPlanations (SHAP). SHAP analysis revealed that the additive ratio had the largest impact on morphological predictions, where additive provides the BCP chains with increased volume to rearrange into thermodynamically favorable morphologies. This interpretability helps validate model predictions and offers insight into parameter importance. Altogether, the presented framework combining high-throughput characterization and interpretable ML offers an approach to exploring and optimizing BCP thin film morphology across a broad processing landscape.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enhancing Plastic Recycling Through Nano-Scale Structure Analysis in Custom Block Copolymer Filaments (Rev.1)

As plastic production continues to increase, new methods to combat plastic waste are needed. This paper explores upcycling, a way to increase the utility or value of waste plastic. This can be done using block copolymers as compatibilizers. Block copolymers are made of two immiscible polymer blocks that phase separate on the nanoscale, forming small structures. The orientation of these nano-scale structures influences mechanical properties, and we show that orientation can be controlled by directional 3D (three dimensional) printing. Using small-angle X-ray scattering (SAXS), we analyze block copolymer filaments extruded at varying speeds. The SAXS data provide a baseline understanding of nano-scale structure in these unique filaments for future use in 3D printing experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Supramolecular Assembly of Halide Perovskite Building Blocks

The structural diversity and tunable optoelectronic properties of halide perovskites originate from the rich chemistry of the metal halide ionic octahedron [MX 6 ] n- (M = Pb 2+ , Sb 3+ , Te 4+ , Sn 4+ , Pt 4+ , etc.; X = Cl - , Br - , and I - ). The properties of the extended perovskite solids are dictated by the assembly, connectivity, and interaction of these octahedra within the lattice environment. Hence, the ability to manipulate and control the assembly of the octahedral building blocks is paramount for constructing new perovskite materials. Here, we propose a systematic supramolecular strategy for the assembly of [MX 6 ] n- octahedra into a solid extended network. Interaction of alkali metal-bound crown ethers with the [M(IV)X 6 ] 2- octahedron resulted in a structurally and optoelectronically tunable "dumbbell" structural unit in solution. Further, single crystals with diverse packing geometries and symmetries will form as the solid assembly of this new supramolecular building block. This supramolecular assembly route introduces a new general strategy for designing halide perovskite structures with potentially new optoelectronic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tunable structural color of bottlebrush block copolymers through direct-write 3D printing from solution

Additive manufacturing of functional materials is limited by control of microstructure and assembly at the nanoscale. In this work, we integrate nonequilibrium self-assembly with direct-write three-dimensional (3D) printing to prepare bottlebrush block copolymer (BBCP) photonic crystals (PCs) with tunable structure color. After varying deposition conditions during printing of a single ink solution, peak reflected wavelength for BBCP PCs span a range of 403 to 626 nm (blue to red), corresponding to an estimated change in d-spacing of >70 nm (Bragg- Snell equation). Physical characterization confirms that these vivid optical effects are underpinned by tuning of lamellar domain spacing, which we attribute to modulation of polymer conformation. Using in situ optical microscopy and solvent-vapor annealing, we identify kinetic trapping of metastable microstructures during printing as the mechanism for domain size control. More generally, we present a robust processing scheme with potential for on-the-fly property tuning of a variety of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Symmetry-breaking in double gyroid block copolymer films by non-affine distortion

Soft-matter bicontinuous networks find a double gyroid structure from block copolymer (BCP) self-assembly. A gyroid structure composed of dissimilar blocks has proven its potential as a soft crystal capable of tuning structural periodicity and symmetry, of which the lattice dimension is variable with molecular weight of the polymer. Using an asymmetric polystyrene- b -poly(methyl methacrylate) (PS- b -PMMA), in this study we show that the self-assembled gyroid films formed via a solvent vapor annealing (SVA) process undergo unique structural distortion due to directional deformation immediately upon deswelling. During the SVA process with PS- b -PMMA films, transient cylinders developed from the as-cast morphology transform into a cubic gyroid structure in a swollen state. Rapid and spontaneous deswelling processes -the manners in which the films contract along the z-direction while retaining an enlarged lateral dimension of the cubic form -lead to triclinic gyroid structures with z-directional contraction ratios ( C z ) of 2.5 and 2.0, respectively. Our X-ray analysis reveals that the deswelling process of the swollen gyroid films produces a notable symmetry-breaking in non-affine gyroid structure that elicits several forbidden reflections such as {110} and {200} reflections. For further characterization of the symmetry-breaking, we delineate the structural features of noncubic gyroid films by computing electron-density difference maps assisted with X-ray measurements. Level-set approach is accordingly developed to quantitate the structural characteristics of the maps in terms of inversion symmetry-breaking, suggesting its possible application to optical Weyl photonic crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems

In this work, we present an efficient and scalable algorithm for performing matrix-vector multiplications (matvecs) for block Toeplitz matrices. Such matrices, which are shift-invariant with respect to their blocks, arise in the context of solving inverse problems governed by autonomous systems, and time-invariant systems in particular. In this article, we consider inverse problems that infer unknown parameters from observational data of a linear time-invariant dynamical system given in the form of partial differential equations (PDEs). Matrix-free Newton-conjugate-gradient methods are often the gold standard for solving these inverse problems, but they require numerous actions of the Hessian on a vector. Matrix-free adjoint-based Hessian matvecs require solution of a pair of linearized forward/adjoint PDE solves per Hessian action, which may be prohibitive for large-scale inverse problems. Time invariance of the forward PDE problem leads to a block Toeplitz structure of the discretized parameter-to-observable (p2o) map defining the mapping from inputs (parameters) to outputs (observables) of the PDEs. This block Toeplitz structure enables us to exploit two key properties: (1) compact storage of the p2o map and its adjoint, and (2) efficient fast Fourier transform–based Hessian matvecs. The proposed algorithm is mapped onto large multi-GPU clusters and achieves more than 80% of peak bandwidth on NVIDIA A100 GPUs. Excellent weak scaling is shown for up to 48 A100 GPUs. For the targeted problems, the implementation executes Hessian matvecs within fractions of a second, which is orders of magnitude faster than can be achieved by conventional matrix-free Hessian matvecs via forward/adjoint PDE solves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Structure and dynamics of lipid membranes interacting with antivirulence end-phosphorylated polyethylene glycol block copolymers

The structure and dynamics of lipid membranes in the presence of extracellular macromolecules are critical for cell membrane functions and many pharmaceutical applications. The pathogen virulence-suppressing end-phosphorylated polyethylene glycol (PEG) triblock copolymer (Pi-ABAPEG) markedly changes the interactions with lipid vesicle membranes and prevents PEG-induced vesicle phase separation in contrast to the unphosphorylated copolymer (ABAPEG). Pi-ABAPEG weakly absorbs on the surface of lipid vesicle membranes and slightly changes the structure of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) unilamellar vesicles at 37 °C, as evidenced by small angle neutron scattering. X-ray reflectivity measurements confirm the weak adsorption of Pi-ABAPEG on DMPC monolayer, resulting in a more compact DMPC monolayer structure. Neutron spin-echo results show that the adsorption of Pi-ABAPEG on DMPC vesicle membranes increases the membrane bending modulus $κ$.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Synthetic Band Structure Engineering of Graphene Using Block Copolymer-Templated Dielectric Superlattices

Engineering the electronic band structure of two-dimensional (2D) materials by imposing spatially periodic superlattice (SL) potentials opens a pathway to unconventional electronics. Nanopatterning the gate electrode or surface dielectric near 2D crystals provides a powerful strategy for realizing electrostatically tunable “remote” SLs with flexibility in lattice design. Here, we demonstrate the effectiveness of block copolymer (BCP)-templated dielectric nanopatterns for fabricating etch-free high-grade metal oxide SLs. Alumina (AlO x ) nanopatterns with hexagonal symmetry and a 38 nm SL wavelength are produced as a model material by directly converting a self-assembled BCP film via block-selective vapor phase infiltration. Despite micrometer-scale rotational disorder inherent to BCP self-assembly, electronic transport measurements of graphene reveal replica Dirac points at zero field and Hofstadter mini-gaps under finite magnetic fields. These results indicate the successful formation of remote SL potentials in graphene resulting from optimized AlO x nanopattern fabrication to achieve consistent lattice symmetry and periodicity at a macroscopic scale. The findings of this study, combined with the versatile, scalable, and cost-effective nature of BCP nanopatterning, highlight the potential of BCP-templated nanostructures for remote SL engineering in 2D crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structure-guided multivalent nanobodies block SARS-CoV-2 infection and suppress mutational escape

Monoclonal antibodies are an important weapon in the battle against COVID-19. However, these large proteins are difficult to produce in the needed quantities and at low cost. Attention has turned to nanobodies, which are aptly named, single-domain antibodies that are easier to produce and have the potential to be administered by inhalation. Koenig et al. describe four nanobodies that bind to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and prevent infection of cells (see the Perspective by Saelens and Schepens). Structures show that the nanobodies target two distinct epitopes on the SARS-CoV-2 spike protein. Multivalent nanobodies neutralize virus much more potently than single nanobodies, and multivalent nanobodies that bind two epitopes prevent the emergence of viral escape mutants.

60 APPLIED LIFE SCIENCES↗