Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “partial correlation”

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 505 records · Page 28

The nature and origins of decametre-scale porosity in Ordovician carbonate rocks, Halahatang oilfield, Tarim Basin, China

At >7 km depths in the Tarim Basin, hydrocarbon reservoirs in Ordovician rocks of the Yijianfang Formation contain large cavities ( c . 10 m or more), vugs, fractures and porous fault rocks. Although some Yijianfang Formation outcrops contain shallow (formed near surface) palaeokarst features, cores from the Halahatang oilfield lack penetrative palaeokarst evidence. Outcrop palaeokarst cavities and opening-mode fractures are mostly mineral filled but some show evidence of secondary dissolution and fault rocks are locally highly ( c . 30%) porous. Cores contain textural evidence of repeated formation of dissolution cavities and subsequent filling by cement. Calcite isotopic analyses indicate depths between c . 220 and 2000 m. Correlation of core and image logs shows abundant cement-filled vugs associated with decametre-scale fractured zones with open cavities that host hydrocarbons. A Sm–Nd isochron age of 400 ± 37 Ma for fracture-filling fluorite indicates that cavities in core formed and were partially cemented prior to the Carboniferous, predating Permian oil emplacement. Repeated creation and filling of vugs, timing constraints and the association of vugs with large cavities suggest dissolution related to fractures and faults. In the current high-strain-rate regime, corroborated by velocity gradient tensor analysis of global positioning system (GPS) data, rapid horizontal extension could promote connection of porous and/or solution-enlarged fault rock, fractures and cavities. Supplementary material: Stable isotopic analyses and the velocity gradient tensor and principal direction and magnitude calculation are available at https://doi.org/10.6084/m9.figshare.c.4946046 Thematic collection: This article is part of the The Geology of Fractured Reservoirs collection available at: https://www.lyellcollection.org/cc/the-geology-of-fractured-reservoirs

Geology↗

Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)

This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluating Effects of Shear Processing on 2D Crystalline Materials in 3D Metal Matrices: Atomistic Understanding of High Shear Deformation of Copper Graphene Composites

Composites made of copper and graphene demonstrate high strength, lubricity and enhanced electrical and thermal conductivity compared pure copper. However, manufacturing these composites at bulk volumes for industrial applications has been a big challenge. Shear deformation assisted processing is an effective method for manufacturing materials such as copper-graphene composites demonstrating ultra-fine grain structures and compositional homogeneity. Nevertheless, microstructural evolution of the composites and their property development under such conditions is not clearly understood currently. To rectify this gap in literature, high strain shear deformation of copper coated graphene foils was performed using a tribometer pin in this study. Changes in microstructure of the composite as well as the constituent components under shear deformation was correlated to process conditions. A sharp increase in the coefficient of friction attributed to rupture and smearing of graphene layer into copper substrate was observed during the shear processing. The coefficient of friction of the sheared copper/graphene composite was lower than that of pure copper, suggesting that partially worn graphene is effectively lubricious at the macroscale. A multimodal characterization of the processed region further revealed a shear deformation-induced ultrafine two-phase grain-structure consisting of copper and graphitic domains. Shear deformation reduced the copper grain size from around 50 – 100 µm to ~200 nm on an average and ~2 – 5 nm in some locations. The semicrystalline graphene films were observed to fracture into 10 – 50 µm size flakes. Oxygen enrichment was observed in the processed region. Finally, graphitic domain were identified for the first time in the copper matrix and not just at the grain boundaries providing evidence for a metastable composite microstructure as a result of solid phase processing at room temperature.

36 MATERIALS SCIENCE↗

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗

The effects of random path fluctuations on the accuracy of laser ranging systems

The precision of satellite ranging systems, limited in part by atmospheric refraction and scattering, is examined. The effects of atmospheric turbulence on the accuracy of single color and multicolor ranging systems is discussed. The statistical characteristics of the random path length fluctuations induced by turbulence are examined. Correlation and structure functions are derived using several proposed models for the variations of the optical path length. For single color systems it is shown that the random path length fluctuations can limit the accuracy of a range measurement to a few centimeters. Two color systems can partially correct for the random path fluctuations so that in most cases their accuracy is limited to a few millimeters. However, at low elevation angles and over long horizontal paths two color systems can also have errors approaching a few centimeters.

Gardner, C. S.↗

Geologic structure of shallow maria

Isopach maps and structural contour maps of the eastern mare basins (30 deg N to 30 deg S; 0 deg to 100 deg E), constructed from measurements of partially buried craters, are presented and discussed. The data, which are sufficiently scattered to yield gross thickness variations, are restricted to shallow maria with less than 1500-2000 m of mare basalts. The average thickness of basalt in the irregular maria is between 200 and 400 m. Correlations between surface topography, basalt thickness, and basin floor structure are apparent in most of the basins that were studied. The mare surface is commonly depressed in regions of thick mare basalts; mare ridges are typically located in regions of pronounced thickness changes; and arcuate mare rilles are confined to thin mare basalts. Most surface structures are attributed to shallow stresses developed within the mare basalts during consolidation and volume reduction.

Dehon, R. A.↗

The Effects of Experimentally Induced Zircon Annealing on Melt Inclusion-Zircon Geochemistry: A Case Study of Archean Zircon From the Barberton Complex

Crystalline melt inclusions (MIs) in Archean zircons can potentially constrain the evolution of magmatic processes. However, to obtain a homogeneous glassy MI representative of the parent melt, devitrified MIs must be heated at temperatures above the liquidus. Although, it is well known that radiation damaged domains in MI-host zircon undergo temperature-time dependent annealing, the effects of annealing on zircon stable isotope and trace element compositions has received less attention. In this study, we heated multiple aliquots of low-magnetism zircons with relatively low levels of radiation damage (Deff<9.6x1014 α-events/mg) from a 3.304 Ga tonalite gneiss xenolith from the Barberton greenstone belt (sample B87-18; Kamo and Davis, 1994) in an internally-heated pressure vessel at 0.4GPa and 1000–1200°C. Zircons were imaged by SEM (CL, BSE) to determine the zoning patterns around the MIs. The radiation damage preserved in the heated and unheated zircons was determined by measuring broadening of the 3(SiO4) Raman stretching band of zircon (FWHM). Oxygen isotope ratios (δ18O), OH/O ratios, and trace and rare earth element (TREE) concentrations were measured in the zircons and MIs using SIMS. The FWHM and Raman shift of the zircon 3(SiO4) band show a systematic increase of zircon crystallinity with increasing experimental temperature. Despite increasing crystallinity, the 3(SiO4) FWHM is not correlated with δ18O(Zrn) values in the heated or unheated zircons, suggesting that δ18O was not altered by laboratory heating in these low initial radiation damage zircons. FWHM and OH/O are positively correlated in both heated and unheated zircons. The unheated zircons have the largest FWHM and OH/O (OH/OMAX=3.5×10-4) suggesting that H2O was lost during experimental heating due to the progressive annealing of radiation-damaged domains in the zircons. Zircon TREE concentrations and FWHM values are not correlated despite the presence of TREE altered domains in both the heated and unheated zircons. Our results demonstrate that pre-experimental zircon TREE concentrations and δ18O(Zrn) remain intact during laboratory heating of crystalline MIs in zircon, while secondary H2O hosted in radiation damaged domains is partially lost. Thus, MIs in low initial radiation damage Archean zircon are a potentially viable tool for constraining melt compositions.

Joseph P. Gonzalez↗

Searching for correlations between vibrational spectral features and structural parameters of silicate glass network

Infrared (IR) and Raman spectroscopic features of silicate glasses are usually interpreted based on the analogy with those of smaller molecules, molecular clusters, or crystalline counterparts; this study tests the accuracy and validity of these widely cited peak assignment schemes by comparing vibrational spectral features with bond parameters of the glass network created by molecular dynamics (MD) simulations. A series of sodium silicate glasses with compositions of [Na 2 O] x [Al 2 O 3 ] 2 [SiO 2 ] 98- x with x = 7, 12, 17, and 22 were synthesized and analyzed with IR and Raman. A silica glass substrate and a crystalline quartz were also analyzed for comparison. Glass structures with the same compositions were generated with MD simulations using three types of potentials: fixed partial charge pairwise (Teter), partial diffuse charge potential (MGFF), and bond order-based charge transfer potential (ReaxFF). The comparison of simulated and experimental IR spectra showed that, among these three potentials tested, ReaxFF reproduces the concentration dependence of spectral features closest to the experimentally observed trend. Hence, the bond length and angle distributions as well as Si– Q n species and ring size distributions of silica and sodium silicate glasses were obtained from ReaxFF-MD simulations and further compared with the peak assignment or deconvolution schemes—which have been widely used since 1970s and 1980s—(a) correlation between the IR peak position in the Si–O stretch region (1050-1120 cm -1 ) and the Si–O–Si bond angle; (b) deconvolution of the Raman bands in the Si–O stretch region with the Q n speciation; and (c) assignment of the Raman bands in the 420-600 cm -1 region to the bending modes of (SiO) n rings with different sizes (typically, n = 3-6). The comparisons showed that none of these widely used methods is congruent with the bond parameters or structures of silicate glass networks produced via ReaxFF-MD simulations. This result invokes that the adequacy of these spectral interpretation methods must be questioned. Alternative interpretations are proposed, which are to be tested independently in future studies.

36 MATERIALS SCIENCE↗

Evaluating the bond strength and fracture mechanisms of cold-sprayed zinc coating on AZ91 magnesium substrate via a combined experimental and computational approach

Magnesium (Mg) alloys are ideal candidates for automotive applications due to their high strength to weight ratio, castability, recyclability etc., however, they lack corrosion and oxidation resistance. Solid-state deposition techniques, such as cold spray, have been demonstrated to enhance their corrosion resistance as it relies on the severe plastic deformation of powder particles upon impact with the substrate to form a metallurgical bond with the substrate and within the coating. At cold sprayed interfaces, a heterogeneous microstructure is formed that includes some porosity, oxides and intermetallics which can significantly affect coating performance. Thus, establishing a direct correlation between the interface microstructure and its properties can aid in designing optimal cold spray parameters. In this study, we investigated the microstructure and mechanical properties of a zinc (Zn) coating deposited on a high pressure die cast (HPDC) AZ91 Mg substrate via high resolution scanning transmission electron microscopy, in situ micro-tensile testing, and finite element method (FEM) modeling. Micro-tensile pillars fabricated using the plasma focused ion beam (PFIB) successfully isolates the coating-substrate interface within the gauge length. The average bond strength of Zn-Mg interface was determined to be ∼140 MPa with failure occurring partially at the interface and mostly into the coatings. A detailed microstructural characterization revealed evidence of a strong metallurgical bonding at the Zn-Mg interface and formation of the C14 MgZn 2 laves phase interlayer resulting in a mixed mode of fracture during the micro-tensile experiments. FEM modeling reveals the stress distribution along the interfaces and suggests that a MgZn 2 layer thickness between 200–400 nm is optimum to increase the bond strength and minimize the triaxiality. Such a site-specific interfacial analysis with correlative computational modeling provides crucial insight into the overall performance of cold spray interfaces.

Bond strength↗

A flexible polymer-based luminescent ink for combined thermographic phosphors and digital image correlation (TP+DIC)

Recent work on the development of integrated thermographic phosphors and digital image correlation (TP+DIC) for combined thermal–mechanical measurements has revealed the need for a flexible, stretchable phosphor coating for metal surfaces. Herein, we coat stainless steel substrates with a polymer-based phosphor ink in a DIC speckle pattern and demonstrate that the ink remains well bonded under substrate deformation. In contrast, a binderless phosphor DIC coating produced via aerosol deposition (AD) partially debonded from the substrate. DIC calculations reveal that the strain on the ink coating matches the strain on the substrate within 4% error at the highest substrate loads (0.05 mm/mm applied substrate strain), while the strain on the AD coating remains near 0 mm/mm as the substrate deforms. Spectrally resolved emission from the phosphor is measured through the transparent binder throughout testing, and the ratio method is used to infer temperature with an uncertainty of 1.7 °C. In conclusion, this phosphor ink coating will allow for accurate, non-contact strain and temperature measurements of a deforming surface.

36 MATERIALS SCIENCE↗

Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy

The photosynthetic capacity or the CO 2 -saturated photosynthetic rate (Vmax), chlorophyll, and nitrogen are closely linked leaf traits that determine C 4 crop photosynthesis and yield. Accurate, timely, rapid, and non-destructive approaches to predict leaf photosynthetic traits from hyperspectral reflectance are urgently needed for high-throughput crop monitoring to ensure food and bioenergy security. Therefore, this study thoroughly evaluated the state-of-the-art physically based radiative transfer models (RTMs), data-driven partial least squares regression (PLSR), and generalized PLSR (gPLSR) models to estimate leaf traits from leaf-clip hyperspectral reflectance, which was collected from maize (Zea mays L.) bioenergy plots with diverse genotypes, growth stages, treatments with nitrogen fertilizers, and ozone stresses in three growing seasons. The results show that leaf RTMs considering bidirectional effects can give accurate estimates of chlorophyll content (Pearson correlation r=0.95), while gPLSR enabled retrieval of leaf nitrogen concentration (r=0.85). Using PLSR with field measurements for training, the cross-validation indicates that V max can be well predicted from spectra (r=0.81). Here, the integration of chlorophyll content (strongly related to visible spectra) and nitrogen concentration (linked to shortwave infrared signals) can provide better predictions of V max (r=0.71) than only using either chlorophyll or nitrogen individually. This study highlights that leaf chlorophyll content and nitrogen concentration have key and unique contributions to V max prediction.

59 BASIC BIOLOGICAL SCIENCES↗

Deep Electric Field Predictions by Drift-Reduced Braginskii Theory with Plasma-Neutral Interactions Based on Experimental Images of Boundary Turbulence

We present 2-dimensional turbulent electric field calculations via physics-informed deep learning consistent with (i) drift-reduced Braginskii theory under the framework of an axisymmetric fusion plasma with purely toroidal field and (ii) experimental estimates of the fluctuating electron density and temperature on open field lines obtained from analysis of gas puff imaging of a discharge on the Alcator C-Mod tokamak. The inclusion of effects from the locally puffed atomic helium on particle and energy sources within the reduced plasma turbulence model are found to strengthen correlations between the electric field and electron pressure. The neutrals are also directly associated with broadening the distribution of turbulent field amplitudes and increasing ${\bf E \times B}$ shearing rates. As a result, this demonstrates a novel approach in plasma experiments by solving for nonlinear dynamics consistent with partial differential equations and data without encoding explicit boundary nor initial conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Serum bile acid and unsaturated fatty acid profiles of non-alcoholic fatty liver disease in type 2 diabetic patients

The understanding of bile acid (BA) and unsaturated fatty acid (UFA) profiles, as well as their dysregulation, remains elusive in individuals with type 2 diabetes mellitus (T2DM) coexisting with non-alcoholic fatty liver disease (NAFLD). Investigating these metabolites could offer valuable insights into the pathophy-siology of NAFLD in T2DM. Our aim is to identify potential metabolite biomarkers capable of distinguishing between NAFLD and T2DM. A training model was developed involving 399 participants, comprising 113 healthy controls (HCs), 134 individuals with T2DM without NAFLD, and 152 individuals with T2DM and NAFLD. External validation encompassed 172 participants. NAFLD patients were divided based on liver fibrosis scores. The analytical approach employed univariate testing, orthogonal partial least squares-discriminant analysis, logistic regression, receiver operating characteristic curve analysis, and decision curve analysis to pinpoint and assess the diagnostic value of serum biomarkers. Compared to HCs, both T2DM and NAFLD groups exhibited diminished levels of specific BAs. In UFAs, particular acids exhibited a positive correlation with NAFLD risk in T2DM, while the ω-6:ω-3 UFA ratio demonstrated a negative correlation. Levels of α-linolenic acid and γ-linolenic acid were linked to significant liver fibrosis in NAFLD. The validation cohort substantiated the predictive efficacy of these biomarkers for assessing NAFLD risk in T2DM patients. This study underscores the connection between altered BA and UFA profiles and the presence of NAFLD in individuals with T2DM, proposing their potential as biomarkers in the pathogenesis of NAFLD.

60 APPLIED LIFE SCIENCES↗

Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?

Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (~-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (~-0.5ms-1) offshore and a slight positive bias (~+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

17 WIND ENERGY↗

Concentration of carbon dioxide by a high-temperature electrochemical membrane cell

The performance of a molten carbonate carbon dioxide concentrator (MCCDC) cell, as a device for removal of CO2 from manned spacecraft cabins without fuel expenditure, is investigated. The test system consists of an electrochemical cell (with an Li2CO3-38 mol pct K2CO3 membrane contained in a LiAlO2 matrix), a furnace, and a flow IR analyzer for monitoring CO2. Operation of the MCCDC-driven cell was found to be suitable for the task of CO2 removal: the cell performed at extremely low CO2 partial pressures (at or above 0.1 mm Hg); cathode CO2 efficiencies of 97 percent were achieved with 0.25 CO2 inlet concentration at 19 mA sq cm, at temperatures near 873 K. Anode concentrations of up to 5.8 percent were obtained. Simple cathode and anode performance equations applied to correlate cell performance agreed well with those measured experimentally. A flow diagram for the process is included.

Kang, M. P.↗

Respiratory modulation of human autonomic rhythms

We studied the influence of three types of breathing [spontaneous, frequency controlled (0.25 Hz), and hyperventilation with 100% oxygen] and apnea on R-R interval, photoplethysmographic arterial pressure, and muscle sympathetic rhythms in nine healthy young adults. We integrated fast Fourier transform power spectra over low (0.05-0.15 Hz) and respiratory (0.15-0.3 Hz) frequencies; estimated vagal baroreceptor-cardiac reflex gain at low frequencies with cross-spectral techniques; and used partial coherence analysis to remove the influence of breathing from the R-R interval, systolic pressure, and muscle sympathetic nerve spectra. Coherence among signals varied as functions of both frequency and time. Partialization abolished the coherence among these signals at respiratory but not at low frequencies. The mode of breathing did not influence low-frequency oscillations, and they persisted during apnea. Our study documents the independence of low-frequency rhythms from respiratory activity and suggests that the close correlations that may exist among arterial pressures, R-R intervals, and muscle sympathetic nerve activity at respiratory frequencies result from the influence of respiration on these measures rather than from arterial baroreflex physiology. Most importantly, our results indicate that correlations among autonomic and hemodynamic rhythms vary over time and frequency, and, thus, are facultative rather than fixed.

Non-NASA Center↗

An in-silico NMR laboratory for nuclear magnetic shieldings computed via finite fields: Exploring nucleus-specific renormalizations of MP2 and MP3

Here we developed and implemented a method-independent, fully numerical, finite difference approach to calculating nuclear magnetic resonance shieldings, using gauge-including atomic orbitals. The resulting capability can be used to explore non-standard methods, given only the energy as a function of finite-applied magnetic fields and nuclear spins. For example, standard second-order Møller-Plesset theory (MP2) has well-known efficacy for 1H and 13C shieldings and known limitations for other nuclei such as 15N and 17O. It is, therefore, interesting to seek methods that offer good accuracy for 15N and 17O shieldings without greatly increased compute costs, as well as exploring whether such methods can further improve 1H and 13C shieldings. Using a small molecule test set of 28 species, we assessed two alternatives: κ regularized MP2 (κ-MP2), which provides energy-dependent damping of large amplitudes, and MP2.X, which includes a variable fraction, X, of third-order correlation (MP3). The aug-cc-pVTZ basis was used, and coupled cluster with singles and doubles and perturbative triples [CCSD(T)] results were taken as reference values. Our κ-MP2 results reveal significant improvements over MP2 for 13C and 15N, with the optimal κ value being element-specific. κ-MP2 with κ = 2 offers a 30% rms error reduction over MP2. For 15N, κ-MP2 with κ = 1.1 provides a 90% error reduction vs MP2 and a 60% error reduction vs CCSD. On the other hand, MP2.X with a scaling factor of 0.6 outperformed CCSD for all heavy nuclei. These results can be understood as providing renormalization of doubles amplitudes to partially account for neglected triple and higher substitutions and offer promising opportunities for future applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Short-term traffic state prediction from latent structures: Accuracy vs. efficiency

Recently, deep learning models have shown promising performances in many research areas, including traffic states prediction, due to their ability to model complex nonlinear relationships. However, deep learning models also have drawbacks that make them less preferable for certain short-term traffic prediction applications. For example, they require a large amount of data for model training, which is also computationally expensive. Moreover, deep learning models lack interpretability of the results. This paper develops a short-term traffic states forecasting algorithm based on partial least square (PLS) to help enhance real-time decision-making and build better insights into traffic data. The proposed model is capable of predicting short-term traffic states accurately and efficiently by capturing dominant spatiotemporal features and day-to-day variations from collinear and correlated traffic data. Three case studies are developed to demonstrate the proposed model in short-term traffic prediction applications.

99 GENERAL AND MISCELLANEOUS↗