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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
DOE OSTI2018

Multi-scale computational analysis of unidirectional carbon fiber reinforced polymer composites under various loading conditions

In this study, a multi-scale computational analysis based on representative volume element (RVE) modeling and molecular dynamics (MD) simulations is developed to investigate the microscopic failure mechanisms of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The average properties of the 200-nm thickness interphase region between fiber and matrix are characterized through MD simulations and an analytical gradient model. The results demonstrate that the interphase region has higher Young’s modulus and strength, compared to the bulk matrix. This stiffened interphase region influences the composite response significantly. Specifically, the traditional two-phase model with zero-thickness interface fails to capture the stress-strain behavior compared to the experimental data. However, by adding the interphase region to a modified RVE model, the accuracy of simulation results will be improved significantly. Furthermore, a coupled experimental-computational micromechanics approach is adopted to calibrate and validate the cohesive parameters of the interface. By including the cohesive interface, our modified RVE model accurately captures the failure strength of the composites. Finally, different failure mechanisms for specimens are investigated using our multi-scale computational framework. In conclusion, the results show that the failure modes of UD CFRP composites are very complex and multiple failure mechanisms co-exist depending on the loading conditions, agreeing well with our experimental analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Butterfly-Accelerated Volume Integral Equation Solver for Broad Permittivity and Large-Scale Electromagnetic Analysis

In this work, a butterfly-accelerated volume integral equation (VIE) solver is proposed for fast and accurate electromagnetic (EM) analysis of scattering from heterogeneous objects. The proposed solver leverages the hierarchical off-diagonal butterfly (HOD-BF) scheme to construct the system matrix and obtain its approximate inverse, used as a preconditioner. Complexity analysis and numerical experiments validate the O(N log 2 N) construction cost of the HOD-BF-compressed system matrix and O(N log 1.5 N) inversion cost for the preconditioner, where N is the number of unknowns in the high-frequency EM scattering problem. For many practical scenarios, the proposed VIE solver requires less memory and computational time to construct the system matrix and obtain its approximate inverse compared to a H matrix-accelerated VIE solver. The accuracy and efficiency of the proposed solver have been demonstrated via its application to the EM analysis of large-scale canonical and real-world structures comprising of broad permittivity values and involving millions of unknowns.

42 ENGINEERING↗
DOE OSTI2022

Multiscale analysis in solids with unseparated scales: fine-scale recovery, error estimation, and coarse-scale adaptivity

There are several engineering applications in which the assumptions of homogenization and scale separation may be violated, in particular, for metallic structures constructed through additive manufacturing. Instead of resorting to direct numerical simulation of the macroscale system with an embedded fine scale, an alternative approach is to use an approximate macroscale constitutive model, but then estimate the model-form error using a posteriori error estimation techniques and subsequently adapt the macroscale model to reduce the error for a given boundary value problem and quantity of interest. Here, we investigate this approach to multiscale analysis in solids with unseparated scales using the example of an additively manufactured metallic structure consisting of a polycrystalline microstructure that is neither periodic nor statistically homogeneous. As a first step to the general nonlinear case, we focus here on linear elasticity in which each grain within the polycrystal is linear elastic but anisotropic.

42 ENGINEERING↗
DOE OSTI2017

Pore-scale capillary pressure analysis using multi-scale X-ray micromotography

Here, a multi-scale synchrotron-based X-ray microtomographic dataset of residually trapped air after gravity-driven brine imbibition was acquired for three samples with differing pore topologies and morphologies; image volumes were reconstructed with voxel sizes from 4.44 µm down to 0.64 µm. Capillary pressure distributions among the population of trapped ganglia were investigated by calculating interfacial curvature in order to assess the potential for remobilization of residually-trapped non-wetting ganglia due to differences in capillary pressure presented by neighbor ganglia. For each sample, sintered glass beads, Boise sandstone and Fontainebleau sandstone, sub-volumes with different voxel sizes were analyzed to quantify air/brine interfaces and interfacial curvatures and investigate the effect of image resolution on both fluid phase identification and curvature estimates. Results show that the method developed for interfacial curvature estimation leads to reliable capillary pressure estimates for gas ganglia. Higher resolution images increase confidence in curvature calculations, especially for the sandstone samples that display smaller gas-brine interfaces which are then represented by a higher number of voxels when imaged with a micron or sub-micron voxels size. The analysis of sub-volumes from the Boise and Fontainebleau dataset highlights the presence of a residually-trapped gas phase consisting of ganglia located in one or few pores and presenting significantly different capillary pressures, especially in the case of Fontainebleau sandstone. As a result, Ostwald ripening could occur, leading to gas transfer from ganglia with higher capillary pressure to surrounding ganglia with lower capillary pressures. More generally, at the pore-scale, most gas ganglia do present similar capillary pressures and Ostwald ripening would then not represent a major mechanism for residually-trapped gas transfer and remobilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Large-Scale Image Analysis for Investigating Spatio-Temporal Changes in Nuclear DNA Damage Caused by Nitrogen Atmospheric Pressure Plasma Jets

The effective clinical application of atmospheric pressure plasma jet (APPJ) treatments requires a well-founded methodology that can describe the interactions between the plasma jet and a treated sample and the temporal and spatial changes that result from the treatment. In this study, we developed a large-scale image analysis method to identify the cell-cycle stage and quantify damage to nuclear DNA in single cells. The method was then tested and used to examine spatio-temporal distributions of nuclear DNA damage in two cell lines from the same anatomic location, namely the oral cavity, after treatment with a nitrogen APPJ. One cell line was malignant, and the other, nonmalignant. The results showed that DNA damage in cancer cells was maximized at the plasma jet treatment region, where the APPJ directly contacted the sample, and declined radially outward. As incubation continued, DNA damage in cancer cells decreased slightly over the first 4 h before rapidly decreasing by approximately 60% at 8 h post-treatment. In nonmalignant cells, no damage was observed within 1 h after treatment, but damage was detected 2 h after treatment. Notably, the damage was 5-fold less than that detected in irradiated cancer cells. Moreover, examining damage with respect to the cell cycle showed that S phase cells were more susceptible to DNA damage than either G1 or G2 phase cells. The proposed methodology for large-scale image analysis is not limited to APPJ post-treatment applications and can be utilized to evaluate biological samples affected by any type of radiation, and, more so, the cell-cycle classification can be used on any cell type with any nuclear DNA staining.

cellular imaging↗
DOE OSTI2017

An improved scaling procedure for analysis and simplification of process models

Systematic scaling analysis of model equations can be valuable as a tool for developing computationally tractable simulations of physical systems. The scaling analysis methods in literature pose difficulties in the calculation of scale and reference values, when nonlinear terms are involved in the model equations. Further, existing methods involve trial and error procedures in the scaling process. Here in this paper, a systematic approach for handling nonlinear terms is suggested, which results in appropriate scale and reference values that render the dimensionless variable variations to be of order one. Further, trial and error procedures are avoided through a new approach wherein a set of nonlinear algebraic equations are solved to identify the scale and reference values. The proposed scaling approach is common to any given model equations with fixed parameters. However, it is to be noted that the proposed procedure may not handle situations when model equations exhibit steady state multiplicity and have dynamic multi-mode regimes. The proposed scaling procedure is illustrated through various examples of different complexities. A 1D model of WGS reactor as a case study shows the effectiveness of the obtained scale and reference values in obtaining simplified model which represents the steady state and dynamic variations of the variables.

42 ENGINEERING↗
DOE OSTI2016

Inter-phase heat transfer and energy coupling in turbulent dispersed multiphase flows

Here, the present paper addresses important fundamental issues of inter-phase heat transfer and energy coupling in turbulent dispersed multiphase flows through scaling analysis. In typical point-particle or two-fluid approaches, the fluid motion and convective heat transfer at the particle scale are not resolved and the momentum and energy coupling between fluid and particles are provided by proper closure models. By examining the kinetic energy transfer due to the coupling forces from the macroscale to microscale fluid motion, closure models are obtained for the contributions of the coupling forces to the energy coupling. Due to the inviscid origin of the added-mass force, its contribution to the microscale kinetic energy does not contribute to dissipative transfer to fluid internal energy as was done by the quasi-steady force. Time scale analysis shows that when the particle is larger than a critical diameter, the diffusive-unsteady kernel decays at a time scale that is smaller than the Kolmogorov time scale. As a result, the computationally costly Basset-like integral form of diffusive-unsteady heat transfer can be simplified to a non-integral form. Conventionally, the fluid-to-particle volumetric heat capacity ratio is used to evaluate the relative importance of the unsteady heat transfer to the energy balance of the particles. Therefore, for gas-particle flows, where the fluid-to-particle volumetric heat capacity ratio is small, unsteady heat transfer is usually ignored. However, the present scaling analysis shows that for small fluid-to-particle volumetric heat capacity ratio, the importance of the unsteady heat transfer actually depends on the ratio between the particle size and the Kolmogorov scale. Furthermore, the particle mass loading multiplied by the heat capacity ratio is usually used to estimate the importance of the thermal two-way coupling effect. Through scaling argument, improved estimates are established for the energy coupling parameters of each energy exchange mechanism between the phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Application and refinement of scaling analyses for mild ignition

Thermal and compositional inhomogeneities may significantly affect outcomes in a variety of fundamental and practical systems, including shock tubes, rapid compression machines, and combustion engines. Even in idealized configurations, homogenous reactive mixtures can never be completely uniform. This can lead to premature ignition, undesired flame propagation, or even detonation. Such perturbations to reacting flows have been recently analyzed by the authors of this work using a novel scaling analysis. That analysis identified three competing processes that affect the influence of an inhomogeneity on the globally observed ignition. First, diffusive quenching of a locally perturbed hot-spot can compete with premature ignition of this reaction center. Next, the ignited flame may extinguish due to high stretch rate. Finally, compressive heating of the end-gas due to flame propagation can compete with homogeneous ignition of the unperturbed bulk gas. In the present work, this scaling analysis is applied to ignition delay measurements reported in the literature. In these experiments, ignition often occurs earlier than expected due to inhomogeneities in the mixture. The previously-developed framework is utilized to infer a representative hot-spot geometry which could lead to the observed early ignition, demonstrating the validity of the scaling analysis.

mild ignition↗
DOE OSTI2016

Scaling and Design Analysis of a Sub-Scale, Reduced Temperature Stratified Flow Separate Effects Test Facility for the Experimental Investigation of Air Ingress in a High Temperature Reactor System

High temperature gas reactors (HTGR) are poised to spearhead the next generation of nuclear reactors, due to their passive safety characteristics and their applications flexibility. Able to provide base load power or process heat for industrial applications, HGTRs may be a critical component to reducing greenhouse gas emissions in the United States and abroad. However, increased interest and development has also highlighted areas requiring further investigation, one of which being the air-ingress accident. Air ingress may occur following a break in the coaxial cross duct and pressure vessel depressurization. The initial mode of ingress is hypothesized to be density driven cross flow as the cold air enters the lower plenum, at which point molecular diffusion and/or local buoyancy phenomena will dominate until a global natural circulation current is established. While computational simulations support this progression, little or no experimental data exists to validate and support this phenomenology. Therefore, it is necessary to generate such data; this research seeks to do so through the use of a sub-scale separate effects test facility - the Stratified Flow Separate Effects Test Facility (SFSETF). The goal of this facility is more specifically to focus on the transition to global natural circulation starting from air ingress after a double-ended guillotine break (DEGB) while neglecting depressurization. This paper will provide analyses performed in the design of this facility, including the geometric and hydraulic scaling analyses, safety analysis and instrumentation selection. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Scaling patch analysis of planar turbulent wakes

In this work, a scaling patch approach is used to investigate the proper scales in planar turbulent wakes. A proper scale for the mean axial flow is the well-known maximum velocity deficit U ref = U ∞ –U ctr , where U ∞ is the free stream velocity and U ctr is the mean axial velocity at the wake centerline. From an admissible scaling of the mean continuity equation, a proper scale for the mean transverse flow is found as V ref = (dδ/dx)U ref , where dδ/dx is the growth rate of the wake width. From an admissible scaling of the mean momentum equation, a proper scale for the kinematic Reynolds shear stress is found as R uv,ref = U ∞ V ref , which is a mixed scale of the free stream velocity and the mean transverse flow scale. Expressions are derived for the scaled mean transverse velocity and Reynolds shear stress in the far field of planar turbulent wakes. Using a Gaussian function for the mean axial velocity deficit, approximate functions for the scaled mean transverse velocity and Reynolds shear stress are developed and found to agree well with experimental and simulation data. This work reveals that the mean transverse flow, despite its small magnitude, plays an important role in the scaling and understanding of the planar turbulent wake.

42 ENGINEERING↗
DOE OSTI2017

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses and empirically discuss their scalability, user friendliness, and postvisualization capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Measuring Chemical Likeness of Stars with Relevant Scaled Component Analysis

Identification of chemically similar stars using elemental abundances is core to many pursuits within Galactic archeology. However, measuring the chemical likeness of stars using abundances directly is limited by systematic imprints of imperfect synthetic spectra in abundance derivation. We present a novel data-driven model that is capable of identifying chemically similar stars from spectra alone. We call this relevant scaled component analysis (RSCA). RSCA finds a mapping from stellar spectra to a representation that optimizes recovery of known open clusters. By design, RSCA amplifies factors of chemical abundance variation and minimizes those of nonchemical parameters, such as instrument systematics. The resultant representation of stellar spectra can therefore be used for precise measurements of chemical similarity between stars. We validate RSCA using 185 cluster stars in 22 open clusters in the Apache Point Observatory Galactic Evolution Experiment survey. We quantify our performance in measuring chemical similarity using a reference set of 151,145 field stars. We find that our representation identifies known stellar siblings more effectively than stellar-abundance measurements. Using RSCA, 1.8% of pairs of field stars are as similar as birth siblings, compared to 2.3% when using stellar-abundance labels. We find that almost all of the information within spectra leveraged by RSCA fits into a two-dimensional basis, which we link to [Fe/H] and α-element abundances. We conclude that chemical tagging of stars to their birth clusters remains prohibitive. However, using the spectra has noticeable gain, and our approach is poised to benefit from larger data sets and improved algorithm designs.

79 ASTRONOMY AND ASTROPHYSICS↗