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 217 records · Page 12
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↗
NASA NTRS2005

Utilization of the Building-Block Approach in Structural Mechanics Research

In the last 20 years NASA has worked in collaboration with industry to develop enabling technologies needed to make aircraft safer and more affordable, extend their lifetime, improve their reliability, better understand their behavior, and reduce their weight. To support these efforts, research programs starting with ideas and culminating in full-scale structural testing were conducted at the NASA Langley Research Center. Each program contained development efforts that (a) started with selecting the material system and manufacturing approach; (b) moved on to experimentation and analysis of small samples to characterize the system and quantify behavior in the presence of defects like damage and imperfections; (c) progressed on to examining larger structures to examine buckling behavior, combined loadings, and built-up structures; and (d) finally moved to complicated subcomponents and full-scale components. Each step along the way was supported by detailed analysis, including tool development, to prove that the behavior of these structures was well-understood and predictable. This approach for developing technology became known as the "building-block" approach. In the Advanced Composites Technology Program and the High Speed Research Program the building-block approach was used to develop a true understanding of the response of the structures involved through experimentation and analysis. The philosophy that if the structural response couldn't be accurately predicted, it wasn't really understood, was critical to the progression of these programs. To this end, analytical techniques including closed-form and finite elements were employed and experimentation used to verify assumptions at each step along the way. This paper presents a discussion of the utilization of the building-block approach described previously in structural mechanics research and development programs at NASA Langley Research Center. Specific examples that illustrate the use of this approach are included from recent research and development programs for both subsonic and supersonic transports.

Rouse, Marshall↗
NASA NTRS1980

Grid generation for general three-dimensional configurations

A suitable grid system for complex three dimensional configurations such as wing/body/nacelle shape for the solution of nonlinear transonic flow problems was constructed. Two approaches were explored based on Thompson's body fitted coordinate concept. The most general approach was to divide the computational domain into multiple rectangular blocks where the configuration itself was also represented by a set of blocks whose structure follows the natural lines of the configuration. The block structured grid system was adaptable to complex configurations and gives good grid quality near physical corners. However, it introduced algorithm issues for the flow solution concerning the treatment of nonanalytic grid block boundaries and nonstandard grid cells. These issues were explored in relation to the grid generation. A more limited approach treats a wing/body configuration with only a single rectangular block in computational space. The issues involving nonstandard cells were avoided, but other limitations on grid resolution appear. Both a linear and a nonlinear system of grid generation equations were developed including methods of grid control.

Lee, K. D.↗
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↗
NASA NTRS1983

Mixture Models for Dependent Observations

Parametric mixture models appropriate for data presented in homogeneous blocks of varying sizes from several unidentified source populations are considered. For most applications, the data elements within each block are dependent. Models are proposed for multivariate normal data incorporating two types of dependence, exchangeability of elements within blocks, and a Markov structure for blocks. The consequences of assuming exchangeability, when in fact the Markov structure holds, are explored. Computational problems for each model are considered, and results of a simple test of the exchangeability hypothesis for LANDSAT data are presented.

Peters, C.↗
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↗
NASA NTRS1991

On linear structure and phase rotation invariant properties of block M-PSK modulation codes

Two important structural properties of block M(=2')-ary PSK modulation codes, linear structure and phase symmetry, are investigated. An M-ary modulation code is first represented as a code with symbols from the integer group S(MPSK) = (0,1,2,...M-1) under modulo-M addition. Then the linear structure of block MPSK modulation codes over S(M-PSK) with respect to modulo-M vector addition is defined, and conditions are derived under which a block MPSK modulation code is linear. Once the linear structure is developed, the phase symmetry of block M-PSK modulation codes is studied. In particular, a necessary and sufficient condition for a block MPSK modulation code that is linear as a binary code to be invariant under 2 h 180 deg/M phase rotation (for h = 1 to l) is derived. Finally, a list of short 8PSK and 16PSK modulation codes is given, together with their linear structure and the smallest phase rotation for which a code is invariant.

Kasami, Tadao↗