Search NASA⌕ Search

SEARCH · Search NASA

Results for “complexity analysis”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

TRUST-EABM Contact Thermal Conductance (CTC) Report

(U) Single Feature Testbeds to Reduce Uncertainty in Simulations and Tests [3] provided an overview for the need of experiments, with accompanying models and simulations, specifically designed to reduce uncertainties and build confidence in complex testing and analysis applications. The Contact Thermal Conductance (CTC) testbed is a joint effort between W-13 (formerly E-13) and MST-8. The objective of this study was to design a testbed, with accompanying finite element models, to quantify, reduce, and propagate measurement uncertainties in contact thermal conductance measurements between two mating components in WR-like thermal environments. The knowledge gained through this simplified experiment would educate more complex assessments and interaction conditions with WR-like materials and geometries.

42 ENGINEERING↗
DOE OSTI2015

Crystallization and X-ray diffraction analysis of the HMG domain of the chondrogenesis master regulator Sox9 in complex with a ChIP-Seq-identified DNA element

Sox9 is a fundamental sex-determining gene and the master regulator of chondrogenesis, and is involved in the development of various vital organs such as testes, kidney, heart and brain, and in skeletal development. Similar to other known Sox transcription factors, Sox9 recognizes and binds DNA with the consensus sequence C(T/A)TTG(T/A)(T/A) through the highly conserved HMG domain. Nonetheless, the molecular basis of the functional specificity of Sox9 in key developmental processes is still unclear. As an initial step towards a mechanistic understanding of Sox9 transcriptional regulation, the current work describes the details of the purification of the mouse Sox9 HMG domain (mSox9HMG), its crystallization in complex with a ChIP-Seq-identified FOXP2 promoter DNA element and the X-ray diffraction data analysis of this complex. The mSox9HMG–FOXP2 promoter DNA complex was crystallized by the hanging-drop vapour-diffusion method using 20% PEG 3350 in 200 m M sodium/potassium phosphate with 100 m M bis-tris propane at pH 8.5. The crystals diffracted to 2.7 Å resolution and the complex crystallized in the tetragonal space group P 4 1 2 1 2, with unit-cell parameters a = b = 99.49, c = 45.89 Å. Crystal-packing parameters revealed that asymmetric unit contained one mSox9HMG–FOXP2 promoter DNA complex with an estimated solvent content of 64%.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

iClick synthesis of network metallopolymers

Described is an approach to preparing the first iClick network metallopolymers with porous properties. Treating digoldazido complex 2-AuN 3 with trigoldacetylide 3-AuPPh 3 or 3-AuPEt 3 , trialkyne 3-H, tetragoldacetylide 4-AuPPh 3 , or tetraalkyne 4-H in CH 2 Cl 2 affords five iClick network metallopolymers 5-AuPPh 3 , 5-AuPEt 3 , 5-H, 6-AuPPh 3 , and 6-H. Additionally, confirmation of the iClick network metallopolymers comes from FTIR, 13 C solid-state cross-coupling magic angle spinning (CPMAS) NMR spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and nitrogen and CO 2 sorption analysis. Employing model complexes 7-AuPPh 3 , 7-AuPEt 3 , 7-H, 8-AuPPh 3 , and 8-H provides structural insights due to the insolubility of iClick network metallopolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Testosterone meets albumin – the molecular mechanism of sex hormone transport by serum albumins

Serum albumin is the most abundant protein in mammalian blood plasma and is responsible for the transport of metals, drugs, and various metabolites, including hormones. We report the first albumin structure in complex with testosterone, the primary male sex hormone. Testosterone is bound in two sites, neither of which overlaps with the previously suggested Sudlow site I. We determined the binding constant of testosterone to equine and human albumins by two different methods: tryptophan fluorescence quenching and ultrafast affinity extraction. The binding studies and similarities between residues comprising the binding sites on serum albumins suggest that testosterone binds to the same sites on both proteins. Our comparative analysis of albumin complexes with hormones, drugs, and other biologically relevant compounds strongly suggests interference between a number of compounds present in blood and testosterone transport by serum albumin. We discuss a possible link between our findings and some phenomena observed in human patients, such as low testosterone levels in diabetic patients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides

Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultralow-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electropherographic time scales. Here, we address these two challenges as applied to singlecell- equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phaseextraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fitfor- purpose applications in single-cell-equivalent phosphoproteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning

We report building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation codes are used to model ICF implosions, incomplete physics and the need for approximations deteriorate their predictive capability. Identification of relationships between controllable design inputs and measurable outcomes can help guide the future design of experiments and development of simulation codes, which can potentially improve the accuracy of the computational models used to simulate ICF implosions. In this article, we leverage developments in machine learning (ML) and methods for ML feature importance/sensitivity analysis to identify complex relationships in ways that are difficult to process using expert judgment alone. We present work using random forest (RF) regression for prediction of yield, velocity, and other experimental outcomes given a suite of design parameters, along with an assessment of important relationships and uncertainties in the prediction model. We show that RF models are capable of learning and predicting on ICF experimental data with high accuracy, and we extract feature importance metrics that provide insight into the physical significance of different controllable design inputs for various ICF design configurations. These results can be used to augment expert intuition and simulation results for optimal design of future ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Structure in the 3D Galaxy Distribution. III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform of finely binned galaxy positions. In both cases, deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multipoint hierarchy. We identify some threads of modern large-scale inference methodology that will presumably yield detections in new wider and deeper surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗
DOE OSTI2017

Local Error Analysis and Comparison of the Swept- and Intersection-Based Remapping Methods

Abstract In this paper, the numerical error of two widely used methods for remapping of discrete quantities from one computational mesh to another is investigated. We compare the intuitive, but resource intensive method utilizing intersections of computational cells with the faster and simpler swept-region-based method. Both algorithms are formally second order accurate, however, they are known to produce slightly different quantity profiles in practical applications. The second-order estimate of the error formula is constructed algebraically for both algorithms so that their local accuracy can be evaluated. This general estimate is then used to assess the dependence of the performance of both methods on parameters such as the second derivatives of the remapped distribution, mesh geometry or mesh movement. Due to the complexity of such analysis, it is performed on a set of simplified elementary mesh patterns such as cell corner expansion, rotation or shear. On selected numerical tests it is demonstrated that the swept-based method can distort a symmetric quantity distribution more substantially than the intersection-based approach when the computational mesh moves in an unsuitable direction.

Klima, Matej↗
DOE OSTI2015

Core–shell Ag@SiO{sub 2} nanoparticles of different silica shell thicknesses: Preparation and their effects on photoluminescence of lanthanide complexes

Highlights: • Ag@SiO{sub 2} nanoparticles of different silica shell thicknesses were prepared via the Stöber process. • Sm and Dy complexes with benzoate, 1,10-phenanthroline and 2,2′-bipyridine were synthesized. • The complex-doped Ag@SiO{sub 2} composites show stronger luminescent intensities than pure complexes. • The luminescent intensities of the composites strongly depend on the SiO{sub 2} shell thickness. - Abstract: Three kinds of almost spherical core–shell Ag@SiO{sub 2} nanoparticles of different silica shell thicknesses (10, 25 and 80 nm) were prepared via the Stöber process. The Ag core nanoparticles were prepared by reducing silver nitrate with sodium citrate. The size, morphology and structure of core–shell Ag@SiO{sub 2} nanoparticles were characterized by transmission electron microscopy. Subsequently, eight kinds of lanthanide complexes with benzoate, 1,10-phenanthroline and 2,2′-bipyridine were synthesized. The composition of the lanthanide complexes was characterized by elemental analysis, IR and UV spectra. Finally, lanthanide complexes were attached to the surface of Ag@SiO{sub 2} nanoparticles to form lanthanide-complex-doped Ag@SiO{sub 2} nanocomposites. The results show that the complex-doped Ag@SiO{sub 2} nanocomposites display much stronger luminescence intensities than the lanthanide complexes. Furthermore, the luminescence intensities of the lanthanide-complex-doped Ag@SiO{sub 2} nanocomposites with SiO{sub 2} shell thickness of 25 nm are stronger than those of the nanocomposites with SiO{sub 2} shell thickness of 10 and 80 nm.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Functional assessment of human enhancer activities using whole-genome STARR-sequencing

Background: Genome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome. Results: In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements. In conclusion, WHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗
DOE OSTI2024

To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation

The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring manipulation of multiple primary variables and generating derived data that needs to be handled efficiently, creating challenges for applications that need to parse many large datasets. Relying on individual applications to handle all intermediate data generally leads to redundant computations across studies and unnecessary data transfers. In this paper, we investigate the performance of different approaches where applications define derived variables as quantities of interest (QoIs) and offload the computation and transfer of these QoIs to the I/O library. This significantly reduces redundancy and optimizes data movement across the distributed storage and processing infrastructure by allowing control over when and where derived variables are computed. We present a detailed analysis of the performance-storage trade-offs associated with different solutions and showcase results for our study on two large-scale datasets created from climate and combustion simulations.

Gainaru, Ana↗
DOE OSTI2023

Methodology for Thermodynamic Analysis Coupled with Computational Fluid Dynamics Modeling for Casting a Novel Aluminum–Cerium Alloy

In this paper, we present the results of computational fluid dynamics (CFD) analysis to assess castability, porosity, molten metal fluidity and other technological properties of a new Al-Ce alloy. A thermodynamic analysis of a new Al-Ce alloy is done to obtain the physical properties as a function of temperature across both solid and liquid phases. These properties are then used to build the CFD of model the full casting process from initial pouring through to final solidification of the part, here an example of a heavy duty mor mount is used. While several excellent commercial CFD codes exists this process shows that CFD can be used to assess the capability of the alloy to properly fill the mold, as well as give predictions where scattered porosity or large-scale defects may occur in the casting. Further, unlike the commercially available software (e.g., ProCAST, SOLIDCast , MAGMASOFT®) the complex 3D-analysis of the stress / strain fields in cast parts is not performed at this time. However, the availability of free software for assessing the required thermodynamic / thermo-physical properties of new alloys (OpenCALPHAD) and CFD codes such as OpenFOAM® makes the developed option attractive and economical, especially for the analysis of new Al-Ce alloys, for which the available data does not exist.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Development of the XFP beamline for x-ray footprinting at NSLS-II

For over a decade, synchrotron-based footprinting studies at the NSLS X28C beamline have provided unique insights and approaches for examining the solution-state structures of large macromolecular assemblies, membrane proteins, and soluble proteins, for time-resolved studies of macromolecular dynamics, and most recently for in vivo studies of RNA-protein complexes. The transition from NSLS to NSLS-II has provided the opportunity to create an upgraded facility for the study of increasingly complex systems; progress on the development of the XFP (X-ray Footprinting for In Vitro and In Vivo Structural Studies of Biological Macromolecules) beamline at NSLS-II is presented here. The XFP beamline will utilize a focused 3-pole wiggler source to deliver a high flux density x-ray beam, where dynamics can be studied on the microsecond to millisecond timescales appropriate for probing biological macromolecules while minimizing sample perturbation. The beamline optics and diagnostics enable adaptation of the beam size and shape to accommodate a variety of sample morphologies with accurate measurement of the incident beam, and the upgrades in sample handling and environment control will allow study of highly sensitive or unstable samples. The XFP beamline is expected to enhance relevant flux densities more than an order of magnitude from that previously available at X28C, allowing static and time-resolved structural analysis of highly complex samples that have previously pushed the boundaries of x-ray footprinting technology. XFP, located at NSLS-II 17-BM, is anticipated to become available for users in 2016.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

The study of Arctic ice and mixed-phase clouds, which are characterized by a variety of ice particle types in the same cloudy volume, is challenging research. This study illustrates a new approach to qualitative and quantitative analysis of the complexity of ice and mixed-phase microphysical processes in Arctic deep precipitating systems using the combination of Ka-band zenith-pointing radar Doppler spectra and quasi-vertical profiles of polarimetric radar variables measured by a Ka/W-band scanning radar. The results illustrate the frequent occurrence of multimodal Doppler spectra in the dendritic/planar growth layer, where locally generated, slower-falling particle populations are well separated from faster-falling populations in terms of Doppler velocity. The slower-falling particle populations contribute to an increase of differential reflectivity (Z DR ), while an enhanced specific differential phase (K DP ) in this dendritic growth temperature range is caused by both the slower and faster-falling particle populations. Another area with frequent occurrence of multimodal Doppler spectra is in mixed-phase layers, where both populations produce Z DR and K DP values close to 0, suggesting the occurrence of a riming process. A Joint analysis of the Doppler spectra and the polarimetric radar variables provides important insight into the microphysics of snow formation and allows the separation of the contributions of ice of different habits to the values of reflectivity and Z DR .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Multi-probe microstructure tracking during heat treatment without an in-situ setup: Case studies on martensitic steel, dual phase steel and β-Ti alloy

In-situ scanning electron microscopy observations of the microstructure evolution during heat treatments are increasingly demanded due to the growing number of alloys with complex microstructures. Post-mortem characterization of the as-processed microstructures rarely provides sufficient insight on the exact route of the microstructure formation. On the other hand, in-situ SEM approaches are often limited due to the arising challenges upon using an in-situ heating setup, e.g. in (i) employing different detectors, (ii) preventing specimen surface degradation, or (iii) controlling and measuring the temperature precisely. Here, we explore and expand the capabilities of the “mid-way” solution by step-wise microstructure tracking, ex-situ, at selected steps of heat treatment. This approach circumvents the limitations above, as it involves an atmosphere and temperature well-controlled dilatometer, and high resolution microstructure characterization (using electron channeling contrast imaging, electron backscatter diffraction, atom probe tomography, etc.). We demonstrate the capabilities of this approach by focusing on three cases: (i) nano-scale carbide precipitation during low-temperature tempering of martensitic steels, (ii) formation of transformation-induced geometrically necessary dislocations in a dual-phase steel during intercritical annealing, and (iii) the partial recrystallization of a metastable β-Ti alloy. - Highlights: • A multi-probe method to track microstructures during heat treatment is developed. • It enables the analysis of various complex phenomena, even those at atomistic scale. • It circumvents some of the free surface effects of classical in-situ experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Raman Spectroscopy Coupled with Chemometric Analysis for Speciation and Quantitative Analysis of Aqueous Phosphoric Acid Systems

Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize on-line and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer’s law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as pH is varied. Locally Weighted Regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with Multivariate Curve Resolution modeling, provide direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations to compensate for activity coefficients and non-idealities associated with high ionic strength systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗