Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “constitutive models”

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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Analysis of New Composite Architectures

Efficient and accurate specialty finite elements methods to analyze textile composites were developed and are described. Textile composites present unique challenges to the analyst because of the large, complex 'microstructure'. The geometry of the microstructure is difficult to model and it introduces unusual free surface effects. The size of the microstructure complicates the use of traditional homogenization methods. The methods developed constitute considerable progress in addressing the modeling difficulties. The details of the methods and attended results obtained therefrom, are described in the various chapters included in Part 1 of the report. Specific conclusions and computer codes generated are included in Part 2 of the report.

Whitcomb, John D.↗
NASA NTRSDate not supplied

Kinetic Model Development of the Carbon Vapor Deposition Reactor to Predict Performance Versus Design

To enable complete closure of a Sabatier-based atmosphere revitalization system where oxygen recovery is predicated by carbon dioxide reduction to methane and water, there must be a means of recovering the hydrogen from the byproduct methane. Honeywell’s carbon vapor deposition (CVD) reactor is a potential technology that provides a thermochemical means by which methane decomposes at high temperatures (> 1,000 °C) into hydrogen, solid carbon, and a small percentage of hydrocarbons. This advanced methane pyrolysis reactor utilizes a carbon fiber substrate to capture and immobilize the solid pyrolytic carbon rather than allowing continuation toward undesirable soot. The CVD reactor is a highly dynamic system whose characteristic geometry changes while operating. The reactor model was developed to provide predictive performance assessment capabilities at different operating conditions, geometries, and configurations to aid in technology development. Modeling of the CVD reactor considered the multitude of simultaneous and interdependent physicochemical processes that are entailed, including: (1) the homogeneous gas-phase pyrolysis reactions, (2) the heterogeneous deposition reactions, and (3) the transport of gaseous species in the reactor domains. A 1-D CVD reactor model was developed based on a general packed-bed, axial-dispersion plug flow reactor model with a solid substrate balance to account for carbon deposition. The model includes 59 species and 243 reactions constituting the methane pyrolysis reaction network, carbon deposition, and interconversions of oxygenate species. The reactor model was compared to brassboard test data, where it was shown to be able to capture the pertinent physicochemical phenomena as evidenced by its agreement with short-duration run data (i.e., looking at different temperature and flow rate conditions), as well as trend agreement with the brassboard reactor’s long-duration test data. Recommendations are provided on further model development steps as well as its use cases.

Air Revitalization↗
DOE OSTI2021

DEM analysis of the effect of interface transition zone on dynamic splitting tensile behavior of high-strength concrete based on multi-phase model

Highlights: • Crushable aggregates with the real geometry shape are generated by using clump-cluster method. • Flat-Joint Model is adopted as the constitutive law. • The tensile strength is almost not affected by ITZ strength when its strength exceeds 0.8 times that of mortar. • A modified formula that can reflect the functional relationship between the ITZ strength and the TDIF is proposed. The tensile strength is one of the main parameters in the design of concrete structures and has an important influence on the cracking performance and durability of concrete materials. As the weak region in concrete, the strength of the interface transition zone (ITZ) directly affects the dynamic mechanical response of concrete. Meanwhile, considering that the tensile performance of concrete is far weaker than its compressive performance, the study of the strength of ITZ is of great significance to the dynamic tensile fracture characteristics and mechanical properties of concrete. In this paper, a method combining 3D scanning technology and Clump-Cluster was proposed to generate a real geometry shape model of crushable aggregate. On this basis, the 3D discrete element model (DEM) of high-strength concrete was constructed using the Flat-Joint Model (FJM). The effects of the ITZ strength on the failure mode, number of microcracks, tensile strength and strain rate effect of high-strength concrete under strain rates from 0.01/s to 100/s were studied by splitting tensile test. The simulation results indicate that the number of microcracks generated decreases with the increase of ITZ strength, and the proportion of ITZ cracks decreases obviously. When the ITZ strength exceeds the critical value of 0.8 times that of mortar, the tensile strength is almost not affected by ITZ strength. In addition, based on the numerical simulation results, a modified formula that can reflect the functional relationship between the ITZ strength and the dynamic increasing factor of the concrete tensile strength (TDIF) is proposed, and the rationality of the TDIF modified formula is verified.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics

Co-injection of conservative tracers with carbon dioxide (CO 2 ) is a viable tool for monitoring subsurface processes during geological CO 2 storage (GCS). This research investigates the simulation and history-matching of a gas tracer (sulfur hexafluoride, SF 6 ) during CO 2 flooding, employing a core flooding result in Berea sandstone. Four extensively used saturation functions are assessed for their efficacy in history matching of CO 2 /SF 6 injection at the core scale. The history-matching process incorporates particle swarm optimization (PSO) to fine-tune constitutive relationships parameters. Next, employing transport models at the aquifer scale, we interrogate the impact on tracer transport and mixing of saturation function uncertainties, arising from the non-uniqueness of constitutive relationships parameters and saturation function types. To assess the effects of geological heterogeneity on behavior of tracer breakthrough curves (BTCs), we employ two normalized parameters assessing the degree of mixing and SF 6 breakthrough time. The aquifer-scale investigation encompasses both homogeneous and heterogeneous systems with and without capillary heterogeneity effects. Our findings underscore the critical importance of addressing saturation function uncertainties, emphasizing the significance of auxiliary experiments and innovative methodologies to enhance predictive accuracy. The findings highlight significant disparities in arrival times, BTC peaks, tails, and mixing levels, even under optimal conditions. Heterogeneity, with or without capillary heterogeneity, plays a crucial role in shaping BTC variations, resulting in accelerated SF 6 breakthrough times and reduced BTC peaks. Evaluation of monitoring points distant from the injector reveals a dampening effect on the SF6 BTC peak, particularly in heterogeneous systems with capillary heterogeneity, where the peak is halved. These insights underscore the challenges associated with tracer monitoring and the necessity for enhanced methodologies to improve predictive accuracy in subsurface processes during GCS.

58 GEOSCIENCES↗
DOE OSTI2022

A level set approach for the computational study of a yield stress fluid filling a thin mold

Many important engineering and scientific applications such as cement slurries, foams, crude oil, and granular avalanches involve the concept of yield stress. Therefore, modeling yield stress fluids in different flow configurations, including the accurate prediction of the yield surface, is important. In this paper, we present a computational model based on the finite element method to study the flow of yield stress fluids in a thin mold and compare the results with data from flow visualization experiments. Here, we use the level set method to describe the interface between the filling fluid and air. We use polypropylene glycol as a model Newtonian fluid and Carbopol for the model yield stress fluid, as the Carbopol solution demonstrates yielding without thixotropy. To describe the yielding and shear-thinning behavior, we use a generalized Newtonian constitutive equation with a Bingham–Carreau–Yasuda form. We compare the results obtained from the mold filling experiments with the results from the three-dimensional (3D) model and from a reduced-order Hele-Shaw (HS) model that is two-dimensional, including the effect of shear-thinning along the thin direction only approximately. We show that both the 3D and the HS model can capture the experimental meniscus shape reasonably well for all the fluids considered at three different flow rates. This indicates that the shape evolution is insensitive to the dimensionality of the model. However, the viscosity and yield surfaces predicted by the 3D and HS models are different. The HS model underestimates the high viscosity and unyielded regions compared to the estimation by the 3D model.

42 ENGINEERING↗
DOE OSTI2021

Efficient flexible characterization of quantum processors with nested error models

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2006

Multiscale Modeling of Grain-Boundary Fracture: Cohesive Zone Models Parameterized From Atomistic Simulations

A multiscale modeling strategy is developed to study grain boundary fracture in polycrystalline aluminum. Atomistic simulation is used to model fundamental nanoscale deformation and fracture mechanisms and to develop a constitutive relationship for separation along a grain boundary interface. The nanoscale constitutive relationship is then parameterized within a cohesive zone model to represent variations in grain boundary properties. These variations arise from the presence of vacancies, intersticies, and other defects in addition to deviations in grain boundary angle from the baseline configuration considered in the molecular dynamics simulation. The parameterized cohesive zone models are then used to model grain boundaries within finite element analyses of aluminum polycrystals.

Glaessgen, Edward H.↗
NASA NTRS2003

Application of Powder Diffraction Methods to the Analysis of Short- and Long-Range Atomic Order in Nanocrystalline Diamond and SiC: The Concept of the Apparent Lattice Parameter (alp)

Two methods of the analysis of powder diffraction patterns of diamond and SiC nanocrystals are presented: (a) examination of changes of the lattice parameters with diffraction vector Q ('apparent lattice parameter', alp) which refers to Bragg scattering, and (b), examination of changes of inter-atomic distances based on the analysis of the atomic Pair Distribution Function, PDF. Application of these methods was studied based on the theoretical diffraction patterns computed for models of nanocrystals having (i) a perfect crystal lattice, and (ii), a core-shell structure, i.e. constituting a two-phase system. The models are defined by the lattice parameter of the grain core, thickness of the surface shell, and the magnitude and distribution of the strain field in the shell. X-ray and neutron experimental diffraction data of nanocrystalline SiC and diamond powders of the grain diameter from 4 nm up to micrometers were used. The effects of the internal pressure and strain at the grain surface on the structure are discussed based on the experimentally determined dependence of the alp values on the Q-vector, and changes of the interatomic distances with the grain size determined experimentally by the atomic Pair Distribution Function (PDF) analysis. The experimental results lend a strong support to the concept of a two-phase, core and the surface shell structure of nanocrystalline diamond and SiC.

Palosz, B.↗
DOE OSTI2024

A guayule C-repeat binding factor is highly activated in guayule under freezing temperature and enhances freezing tolerance when expressed in Arabidopsis thaliana

Natural Rubber (NR)-producing guayule (Parthenium argentatum Gray) has been developed as a new crop to diversify NR production. Guayule NR is mainly synthesized in its stem and is upregulated by cold temperatures. A guayule C-repeat binding factor 4 (PaCBF4) was highly expressed in cold-treated stem tissue, coinciding with active rubber biosynthesis and accumulation. Sequence alignments of PaCBF4 with other CBFs indicated that PaCBF4 contains DNA-binding domains responsible for regulating cold-regulated (COR) gene expression. Spatial gene expression profiling of PaCBF4 revealed that stems had the highest expression level among different organs examined. We further confirmed the function of PaCBF4 as regulator of cold-signaling processes by expressing it in the model plant Arabidopsis under a constitutive ubiquitin promoter from potato. Further, the resulting transgenic Arabidopsis lines expressing PaCBF4 turned on expression of a set of Arabidopsis COR genes under both room (24ºC) and cold (4ºC) temperatures, in contrast to the wild-type Arabidopsis that expressed these COR genes solely upon cold treatment. Furthermore, the transgenic plants displayed enhanced freezing tolerance at -5ºC, exhibiting a survival rate of 88–98% compared with 0% survival rate of wild-type plants. Our results suggest that PaCBF4 is a functional member of the guayule CBF gene family and plays a significant role in cold and freeze tolerance. Interestingly, overexpressing PaCBF4 in Arabidopsis did not affect the normal phenotype of the plant during vegetative and inflorescence growth, but the gene led to more undeveloped siliques after flowering.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

First application of a liquid argon time projection chamber for the search for intranuclear neutron-antineutron transitions and annihilation in 40 Ar using the MicroBooNE detector

We present a novel methodology to search for intranuclear neutron-antineutron transition (n→n̅) followed by n̅-nucleon annihilation within an 40 Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of n→n̅ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select n→n̅ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22 ± 6.04)% and (0.0020 ± 0.0003)%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of 3.32 ×10 26 neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the n→n̅ lifetime in 40 Ar of τ m ≳ 1.1×10 26 years, and on the free n→n̅ transition time of τ n→n̅ ≳ 2.6×10 5 s, each at the 90% confidence level. This analysis represents a first-ever proof-of-principle demonstration of the ability to search for this rare process in LArTPCs with high efficiency and low background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Chemical classification program synthesis using generative artificial intelligence

Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEBI) database. These programs can be used for efficient deterministic run-time classification of SMILES structures, with natural language explanations. The programs themselves constitute an explainable computable ontological model of chemical class nomenclature, which we call the ChEBI Chemical Class Program Ontology (C3PO). We validated our approach against the ChEBI database, and compared our results against deep learning models and a naive SMARTS pattern based classifier. C3PO outperforms the naive classifier, but does not reach the performance of state of the art deep learning methods. However, C3PO has a number of strengths that complement deep learning methods, including explainability and reduced data dependence. C3PO can be used alongside deep learning classifiers to provide an explanation of the classification, where both methods agree. The programs can be used as part of the ontology development process, and iteratively refined by expert human curators.

Artificial Intelligence↗
DOE OSTI2024

Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel

Improving the understanding of how computational fluid dynamics (CFD) direct numerical simulations (DNS) of flows in the High Flux Isotope Reactor (HFIR) perform when run in parallel using the high performance computing (HPC) platform Summit at the Oak Ridge Leadership Computing Facility (OLCF) is of particular importance to boost the computational tools used to support HFIR conversion to low enriched fuel (LEU). Evaluation of scaling performance was driven by the increasing importance of graphics processing unit (GPU) usage in HPC, which is becoming the standard for modern supercomputers such as Summit. The desired results are to obtain a strong positive correlation between the computational resources dedicated to a problem and the relative speed-up of the simulation in comparison to a benchmark. This capability will allow substantially improvement in HFIR flow analytical capabilities, specifically when predicting turbulence properties at high Reynolds numbers. The study leverages previous simulation results performed with code PHASTA (finite element) on HPC platforms Cori (NERSC) and Theta (ALCF) [1] with computing options provided in the computing platform OpenFOAM (finite volume) at OLCF. Transitioning from PHASTA to OpenFOAM will (1) eliminate dependence on third-party software for mesh generation and manipulation, (2) reduce resource needs by employing modern architectures, and (3) build expertise for future modeling of HFIR-specific problems like heat transfer in involute geometry, entrance effects, flow structure in channel corners, and so on—all important issues when defining the available thermal margins in the transition to LEU. CPUs and GPUs differ significantly in their architecture and utilization, as discussed in the literature [2]. The most important differences are in the approach to computations and their memory. A single GPU contains a large quantity of cores, enabling it to perform with a much higher throughput than a CPU, but execution requires a different approach. GPU codes execute instructions using the Single-Instruction Multiple-Thread (SIMT) approach in which a single instruction is used for groups of threads called warps. A warp typically consists of 32 threads which must execute the same set of instructions, although on separate threads. Alternately, a CPU has far fewer cores that are much more flexible in their operation, excelling at quickly performing more complex serial computations. This is why GPUs have greater throughput when properly utilized. The second important difference is seen when comparing their memory spaces. Limited memory allocations and CPU–GPU communications cause a significant bottleneck in GPU-accelerated programs. Further study was required to properly take advantage of GPU resources. A comprehensive analysis of code performance and the model-specific features of turbulence constitutes the core of this work. In this study, a DNS simulation of HFIR channel turbulence was performed with the finite volume CFD code OpenFOAM v2112 and CUDA v11.0 on Red Hat Enterprise Linux v8.2. The OpenFOAM installation had AMGx integrated to enable GPU acceleration and utilizes the PETSc4FOAM library. The computational resources and the problem size were scaled on CPU and CPU + GPU architectures to gain a better understanding of the performance of a DNS problem on modern computing hardware. The study aimed to analyze the scaling of the code exclusively on CPUs and then to examine the scaling of the codes with GPU acceleration enabled. Scaling studies included CPU and GPU acceleration on a mesh of varying resolution to analyze the impact of problem size relative to computational resources. In the course of preparing the GPU configuration on Summit, mainly using the AMGX solvers, difficulties were encountered stemming from constant changes resulting from extensive ongoing development activities and the changing environment. This resulted in the inability to complete the GPU portion of the work. The code was compiled and tested, but production runs to assess acceleration were not performed because the used discretional compute time allocation expired as year-end approached. The Summit HPC platform is scheduled for decommissioning in 2024, making it unattractive for future use with Nvidia-based GPUs. Therefore, the work will be moved onto NERSC machines in FY24. An application was prepared and submitted, and sufficient node-hours were awarded to continue the research in the next calendar year. This report summarizes work performed thus far, which mostly focused on CPU OpenFOAM computing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

First Demonstration of a Liquid Argon Time Projection Chamber Based Search for Intranuclear Neutron-Antineutron Transitions and Annihilation in $^{40}$Ar using the MicroBooNE Detector

We present a novel methodology to search for intranuclear neutron-antineutron transition ($n\rightarrow\bar{n}$) followed by $\bar{n}$-nucleon annihilation within an $^{40}$Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of $n\rightarrow\bar{n}$ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select $n\rightarrow\bar{n}$ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22$\pm$6.04)\% and (0.0020$\pm$0.0003)\%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of $3.32 \times10^{26}\,$neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the $n\rightarrow\bar{n}$ lifetime in $^{40}$Ar of $\tau_{\textrm{m}} \gtrsim 1.

43 PARTICLE ACCELERATORS↗
NASA NTRS1976

Rate and time dependent behavior of structural adhesives

Studies on two adhesives (Metlbond 1113 and 1113-2) identified as having applications in the bonding of composite materials are presented. Constitutive equations capable of describing changes in material behavior with strain rate are derived from various theoretical approaches. It is shown that certain unique relationships exist between these approaches. It is also shown that the constitutive equation derived from mechanical models can be used for creep and relaxation loading. A creep to failure phenomenon is shown to exist and is correlated with a delayed yield equation proposed by Crochet. Loading-unloading results are presented and are shown to correlate well with the proposed form of the loading-unloading equations for the modified Bingham model. Experimental results obtained for relaxation tests above and below the glass transition temperature are presented. It is shown that the adhesives obey the time-temperature superposition principle.

Renieri, M. P.↗
NASA NTRS1985

Micromechanics of high temperature deformation and failure

The micromechanics of the constitutive behavior of elastoplastic materials at high temperatures was examined. The experimental work focused on the development of microscopic defects in superalloys (Waspaloy), especially the formation of voids at grain boundary carbides, and slip induced surface cracks within grains upon cyclic loading at high temperatures. The influence of these defects on the life expectancy of the material was examined. The theoretical work consists of two parts: (1) analytical description of the mechanisms that lead to defects observed experimentally; and (2) development of macroscopic elastoplastic nonlinear constitutive relations based on mechanical modeling.

Nasser, S. N.↗
NASA NTRS1985

A continuous damage model based on stepwise-stress creep rupture tests

A creep damage accumulation model is presented that makes use of the Kachanov damage rate concept with a provision accounting for damage that results from a variable stress history. This is accomplished through the introduction of an additional term in the Kachanov rate equation that is linear in the stress rate. Specification of the material functions and parameters in the model requires two types of constituting a data base: (1) standard constant-stress creep rupture tests, and (2) a sequence of two-step creep rupture tests.

Robinson, D. N.↗
NASA NTRS1985

The effects of molecular weight on the single lap shear creep and constant strain rate behavior of thermoplastic polyimidesulfone adhesive

The bonded shear creep and constant strain rate behaviors of zero, one, and three percent endcapped thermoplastic polyimidesulfone adhesive were examined at room and elevated temperatures. Endcapping was accomplished by the addition of phthalic anhydrides. The primary objective was to determine the effects of molecular weight on the mechanical properties of the adhesive. Viscoelastic and nonlinear elastic constitutive equations were utilized to model the adhesive. Ludwik's and Crochet's relations were used to describe the experimental failure data. The effects of molecular weight changes on the above mentioned mechanical behavior were assessed. The viscoelastic Chase-Goldsmith and elastic nonlinear relations gave a good fit to the experimental stress strain behavior. Crochet's relations based on Maxwell and Chase-Goldsmith models were fit to delayed failure data. Ludwik's equations revealed negligible rate dependence. Ultimate stress levels and the safe levels for creep stresses were found to decrease as molecular weight was reduced.

Dembosky, Stanley K.↗
NASA NTRS1986

Dislocation dynamics during the growth of silicon ribbon

The thermal viscoplastic stresses and the dislocation densities in silicon ribbon are computed for an axially changing thermal profile by using an iterative finite difference method. A material constitutive equation (Haasen-Sumino model) which involves an internal variable (mobile dislocation density) is used. The results are interpreted as showing that there is a maximum width of silicon ribbon that can be grown when viscoplasticity and dislocations are considered. This maximum width limitation does not exist if the material behavior is elastic.

Dillon, O. W., Jr.↗