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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SCORCH. I. The galaxy–halo connection in the first billion years

SCORCH (Simulations and Constructions of the Reionization of Cosmic Hydrogen) is a new project to study the Epoch of Reionization (EoR). In this first paper, we probe the connection between observed high-redshift galaxies and simulated dark matter halos to better understand the primary source of ionizing radiation. High-resolution N-body simulations are run to quantify the abundance of dark matter halos as a function of mass M, accretion rate M-dot , and redshift z. A new fit for the halo mass function dn/dM is ≈20% more accurate at the high-mass end. A novel approach is used to fit the halo accretion rate function dn/d M-dot in terms of the halo mass function. Abundance matching against the observed galaxy luminosity function is used to estimate the luminosity–mass relation and the luminosity–accretion-rate relation. The inferred star formation efficiency is not monotonic with M nor M-dot , but reaches a maximum value at a characteristic mass ∼2×10{sup 11} M{sub ⊙} and a characteristic accretion rate ∼6×10{sup 2} M{sub ⊙} yr{sup −1} at z ≈ 6. We find a universal EoR luminosity–accretion-rate relation and construct a fiducial model for the galaxy luminosity function. The Schechter parameters evolve such that ϕ{sub ⋆} decreases, M{sub ⋆} is fainter, and α is steeper at higher redshifts. We forecast for the upcoming James Webb Space Telescope and show that with apparent magnitude limit m{sub AB}≈31 (32), it can observe ≳11 (24) unlensed galaxies per square degree per unit redshift at least down to M{sub ⋆} at z ≲ 13 (14).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Evaluation of average leaf inclination angle quantified by indirect optical instruments in crop fields

Average leaf inclination angle ($\overline{θ}$ L ) is an important canopy structure variable that influences light regime, photosynthesis, and evapotranspiration of plants. $\overline{θ}$ L can be measured through direct methods (e.g., protractor), which are labor-intensive and time-consuming, or through indirect optical instruments, which are more efficient than the direct methods. However, uncertainties of different indirect optical instruments for quantifying $\overline{θ}$ L remain largely unquantified. In this study, we evaluated and compared the performances of three major indirect optical instruments: (1) LAI-2200, (2) 30°-tilted camera, and (3) digital hemispherical photography (DHP), in different crop fields over a growing season, benchmarked with direct measurements. LAI-2200 and 30°-tilted camera showed higher agreement with direct $\overline{θ}$ measurements (R 2 = 0.54, RMSE = 7.37°; R 2 = 0.58, RMSE = 8.08°) than DHP (R 2 = 0.14, RMSE = 13.96°). Different performances of indirect optical instruments could be attributed to the accuracy of gap fraction measurement and the performance of the $\overline{θ}$ L quantification algorithms. When using the LAI-2200 algorithm, larger gap fraction gradients over view zenith angles led to larger $\overline{θ}$ L values, and smaller gap fraction gradients led to smaller $\overline{θ}$ L values. Such error propagation was larger in sparse canopy than in dense canopy. The Wilson G function of the LAI-2200 algorithm performed better in estimating $\overline{θ}$ L than the G function based on the ellipsoidal LAD function used by the CAN_EYE algorithm. We also proposed a modification of the LAI-2200 algorithm, which further improved the performance of LAI-2200 and 30°-tilted cameras in estimating $\overline{θ}$ L . We envision that the low-cost 30°-tilted cameras provide a promising sensor solution to continuously monitor canopy structure for various ecosystems.

30°-tilted camera↗
DOE OSTI2023

Size-Dependent Energy and Adhesion of Pd Nanoparticles on Graphene on Ni(111) by Pd Vapor Adsorption Calorimetry

Carbon-supported late transition-metal nanoparticles are promising catalysts and electrocatalysts for wide-ranging applications. However, experimental investigations of the bonding energetics of metal nanoparticles on carbon supports are very limited. Here, in this work, we report heats of adsorption of Pd vapor deposited onto single-layer graphene(0001) supported on Ni(111) at 100 and 300 K as Pd grows particles of well-defined size in the range from three atom clusters to 6 nm diameter. Sizes were determined from He + low-energy ion scattering (LEIS). In this size range, the differential heat of Pd adsorption increases from 228 kJ/mol to within 10 kJ/mol of the heat of sublimation of bulk Pd (377 kJ/mol). The chemical potential of metal atoms in these nanoparticles as a function of average particle size was determined from these results. The adhesion energy at the Pd/graphene(0001)/Ni(111) interface was extracted from these data and found to be 3.5 J/m 2 for the largest Pd particles. For the three metal elements that have now been studied (Pd, Ni, and Ag), we found an increase in metal/graphene(0001)/Ni(111) adhesion energy with metal carbophilicity, which we defined here as the heat of C atom adsorption on that metal’s (111) surface estimated from published density functional theory calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Low-energy collective modes of deformed superfluid nuclei within the finite-amplitude method

The major challenge for nuclear theory is to describe and predict global properties and collective modes of atomic nuclei. Of particular interest is the response of the nucleus to a time-dependent external field that impacts the low-energy multipole and β -decay strength, as well as individual nuclear excitations. We propose a method to compute low-lying collective modes in deformed nuclei within the finite-amplitude method (FAM) based on the quasiparticle random-phase approximation (QRPA). By using the analytic property of the response function, we find the QRPA amplitudes by computing the residua of the FAM amplitudes by means of a contour integration around the QRPA poles in a complex frequency plane. We use superfluid nuclear density functional theory with Skyrme energy density functionals, the FAM-QRPA approach, and the conventional matrix formulation of the QRPA. We demonstrate that the complex-energy FAM-QRPA method reproduces low-lying collective states obtained within the conventional matrix formulation of the QRPA theory. Illustrative calculations are performed for the isoscalar monopole strength in deformed 24 Mg and for low-lying $K = 0$ quadrupole vibrational modes of deformed Yb and Er isotopes. The proposed FAM-QRPA approach, in addition to providing a quick estimate of various strength functions, allows one to efficiently calculate the individual QRPA amplitudes of the low-lying collective modes in spherical and deformed nuclei throughout the entire nuclear landscape, in particular shape-vibrational and pairing-vibrational modes and β -decay rates. It can also be employed in microscopic approaches to large-amplitude nuclear collective motion based on the adiabatic self-consistent collective coordinate method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Fault detection and analysis in nuclear research facility using artificial intelligence methods

In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.

42 ENGINEERING↗
DOE OSTI2018

A new computational approach for the solutions of generalized pantograph-delay differential equations

In this study, a new computational approach is presented to solve the generalized pantograph-delay differential equations (PDDEs). The solutions obtained by our scheme represent by a linear combination of a special kind of basis functions, and can be deduced in a straightforward manner. Firstly, using the least squares approximation method and the Lagrange-multiplier method, the given PDDE is converted to a linear system of algebraic equations, and those unknown coefficients of the solution of the problem are determined by solving this linear system. Secondly, a PDDE related to the error function of the approximate solution is constructed based on the residual error function technique, and error estimation is presented for the suggested method. The convergence of the approximate solution is proved. Several numerical examples are given to demonstrate the accuracy and efficiency. Comparisons are made between the proposed method and other existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The luminosity function at z ∼ 8 from 97 Y-band dropouts: Inferences about reionization

We present the largest search to date for Y-band dropout galaxies (z ∼ 8 Lyman break galaxies, LBGs) based on 350 arcmin{sup 2} of Hubble Space Telescope observations in the V, Y, J, and H bands from the Brightest of Reionizing Galaxies (BoRG) survey. In addition to previously published data, the BoRG13 data set presented here includes approximately 50 arcmin{sup 2} of new data and deeper observations of two previous BoRG pointings, from which we present 9 new z ∼ 8 LBG candidates, bringing the total number of BoRG Y-band dropouts to 38 with 25.5 ≤ m{sub J} ≤ 27.6 (AB system). We introduce a new Bayesian formalism for estimating the galaxy luminosity function, which does not require binning (and thus smearing) of the data and includes a likelihood based on the formally correct binomial distribution as opposed to the often-used approximate Poisson distribution. We demonstrate the utility of the new method on a sample of 97 Y-band dropouts that combines the bright BoRG galaxies with the fainter sources published in Bouwens et al. from the Hubble Ultra Deep Field and Early Release Science programs. We show that the z ∼ 8 luminosity function is well described by a Schechter function over its full dynamic range with a characteristic magnitude M{sup ⋆}=−20.15{sub −0.38}{sup +0.29}, a faint-end slope of α=−1.87{sub −0.26}{sup +0.26}, and a number density of log{sub 10} ϕ{sup ⋆}[Mpc{sup −3}]=−3.24{sub −0.24}{sup +0.25}. Integrated down to M = –17.7, this luminosity function yields a luminosity density log{sub 10} ϵ[erg s{sup −1} Hz{sup −1} Mpc{sup −3}]=25.52{sub −0.05}{sup +0.05}. Our luminosity function analysis is consistent with previously published determinations within 1σ. The error analysis suggests that uncertainties on the faint-end slope are still too large to draw a firm conclusion about its evolution with redshift. We use our statistical framework to discuss the implication of our study for the physics of reionization. By assuming theoretically motivated priors on the clumping factor and the photon escape fraction we show that the UV luminosity density from galaxy samples down to M = –17.7 can ionize only 10%-50% of the neutral hydrogen at z ∼ 8. Full reionization would require extending the luminosity function down to M = –15. The data are consistent with a substantial fraction of neutral hydrogen at z > 7, in agreement with recent suggestions based on deep spectroscopy of z ∼ 8 LBGs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-E-QI-13: Predictable Models for Radio-Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy

Purpose: Iodine-enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x-rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow-up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time. Methods: 12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady-state infusion to ensure stable intra-tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi-slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady-state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data. Results: The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error. Conclusion: The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Goal-based angular adaptivity applied to a wavelet-based discretisation of the neutral particle transport equation

A method for applying goal-based adaptive methods to the angular resolution of the neutral particle transport equation is presented. The methods are applied to an octahedral wavelet discretisation of the spherical angular domain which allows for anisotropic resolution. The angular resolution is adapted across both the spatial and energy dimensions. The spatial domain is discretised using an inner-element sub-grid scale finite element method. The goal-based adaptive methods optimise the angular discretisation to minimise the error in a specific functional of the solution. The goal-based error estimators require the solution of an adjoint system to determine the importance to the specified functional. The error estimators and the novel methods to calculate them are described. Several examples are presented to demonstrate the effectiveness of the methods. It is shown that the methods can significantly reduce the number of unknowns and computational time required to obtain a given error. The novelty of the work is the use of goal-based adaptive methods to obtain anisotropic resolution in the angular domain for solving the transport equation. -- Highlights: •Wavelet angular discretisation used to solve transport equation. •Adaptive method developed for the wavelet discretisation. •Anisotropic angular resolution demonstrated through the adaptive method. •Adaptive method provides improvements in computational efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Photometric redshifts probability density estimation from recurrent neural networks in the DECam local volume exploration survey data release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5 σ point-source depth of g = 24.3, r = 23 . 9 , i = 23.5, and z = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of − 0 . 0013 , a scatter of 0.0293, and an outlier fraction of 5.1%. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters.We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

CHAOTIC ZONES AROUND GRAVITATING BINARIES

The extent of the continuous zone of chaotic orbits of a small-mass tertiary around a system of two gravitationally bound primaries of comparable masses (a binary star, a binary black hole, a binary asteroid, etc.) is estimated analytically, as a function of the tertiary's orbital eccentricity. The separatrix map theory is used to demonstrate that the central continuous chaos zone emerges (above a threshold in the primaries' mass ratio) due to overlapping of the orbital resonances corresponding to the integer ratios p:1 between the tertiary and the central binary periods. In this zone, the unlimited chaotic orbital diffusion of the tertiary takes place, up to its ejection from the system. The primaries' mass ratio, above which such a chaotic zone is universally present at all initial eccentricities of the tertiary, is estimated. The diversity of the observed orbital configurations of biplanetary and circumbinary exosystems is shown to be in accord with the existence of the primaries' mass parameter threshold.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Data-Centric Approach to Capture Non-Polynomial Nonlinear Dynamics

We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral properties of the Koopman operator. The choice of observable functions is fundamental for applying EDMD to nonlinear problems arising in systems and control. Existing methods either start from a set of dictionary functions and look for the subset that best fits the underlying nonlinear dynamics or rely on machine learning algorithms to “learn” observable functions. Conversely, in this paper, we start from the dynamical system model and lift it through the Lie derivatives, rendering it into a polynomial form. This proposed transformation into a polynomial form is exact and provides an adequate set of observable functions. The strength of the proposed approach is its applicability to a broader class of nonlinear dynamical systems, particularly those with nonpolynomial functions and compositions thereof. Moreover, it retains the physical interpretability of the underlying dynamical system and can be readily integrated into existing numerical libraries. We demonstrate the proposed approach with an application to electric power systems. The modeled system consists of a single generator connected to an infinite bus, where nonlinear terms include sine and cosine functions. The results demonstrate the effectiveness of the proposed procedure in off-attractor nonlinear dynamics for estimation and prediction; the observable functions obtained from the proposed construction outperform methods that use dictionary functions comprising monomials or radial basis functions.

extended dynamic mode decomposition↗
DOE OSTI2019

Satellite-based monitoring of groundwater depletion in California’s Central Valley

Abstract Range change data, obtained from Synthetic Aperture Radar satellites, form the basis for estimates of aquifer volume change in California’s Central Valley. The estimation algorithm incorporates a function penalizing changes far from known well locations, linking the aquifer volume changes to agricultural, industrial, and municipal pumping within the Tulare basin. We show that the range changes are compatible with the hypothesis that the source of aquifer volume changes are variations in effective pressure around documented wells. Specifically, inclusion of the well distance penalty does not degrade the fit to the observations, inversions with and without it both give variance reductions of 99.6%. The patterns of aquifer volume change vary significantly from the drought year, between October 2015 and October 2016, to a wet year in 2017, and into 2018, a year with near average rainfall. The 2.3 million acre-feet of estimated volume reduction, a lower bound on the amount of water extracted from the basin between October 2015 and 2016, agrees with independent estimates of 1.8 and 2.3 million acre-feet. The aquifer volume reduction is also compatible with a loss of 3.1 km 3 (2.5 million acre-feet) in groundwater volume derived from Gravity Recovery and Climate Experiment (GRACE) satellite data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

The local black hole mass function derived from the M{sub BH}–P and the M{sub BH}–n relations

We present a determination of the supermassive black hole (SMBH) mass function for early- and late-type galaxies in the nearby universe (z < 0.0057), established from a volume-limited sample consisting of a statistically complete collection of the brightest spiral galaxies in the southern hemisphere. The sample is defined by limiting luminosity (redshift-independent) distance, D {sub L} = 25.4 Mpc, and a limiting absolute B-band magnitude, M{sub B}=−19.12. These limits define a sample of 140 spiral, 30 elliptical (E), and 38 lenticular (S0) galaxies. We established the Sérsic index distribution for early-type (E/S0) galaxies in our sample. Davis et al. established the pitch angle distribution for their sample, which is identical to our late-type (spiral) galaxy sample. We then used the pitch angle and the Sérsic index distributions in order to estimate the SMBH mass function for our volume-limited sample. The observational simplicity of our approach relies on the empirical relation between the mass of the central SMBH and the Sérsic index for an early-type galaxy or the logarithmic spiral-arm pitch angle for a spiral galaxy. Our SMBH mass function agrees well at the high-mass end with previous values in the literature. At the low-mass end, although inconsistencies exist in previous works that still need to be resolved, our work is more in line with expectations based on modeling of black hole evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Is Dynamic Autocrine Insulin Signaling Possible? A Mathematical Model Predicts Picomolar Concentrations of Extracellular Monomeric Insulin within Human Pancreatic Islets

Insulin signaling is essential for β-cell survival and proliferation in vivo. Insulin also has potent mitogenic and anti-apoptotic actions on cultured β-cells, with maximum effect in the high picomolar range and diminishing effect at high nanomolar doses. In order to understand whether these effects of insulin are constitutive or can be subjected to physiological modulation, it is essential to estimate the extracellular concentration of monomeric insulin within an intact islet. Unfortunately, the in vivo concentration of insulin monomers within the islet cannot be measured directly with current technology. Here, we present the first mathematical model designed to estimate the levels of monomeric insulin within the islet extracellular space. Insulin is released as insoluble crystals that exhibit a delayed dissociation into hexamers, dimers, and eventually monomers, which only then can act as signaling ligands. The rates at which different forms of insulin dissolve in vivo have been estimated from studies of peripheral insulin injection sites. We used this and other information to formulate a mathematical model to estimate the local insulin concentration within a single islet as a function of glucose. Model parameters were estimated from existing literature. Components of the model were validated using experimental data, if available. Model analysis predicted that the majority of monomeric insulin in the islet is that which has been returned from the periphery, and the concentration of intra-islet monomeric insulin varies from β50–300 pM when glucose is in the physiological range. Thus, our results suggest that the local concentration of monomeric insulin within the islet is in the picomolar ‘sweet spot’ range of insulin doses that activate the insulin receptor and have the most potent effects on β-cells in vitro. Together with experimental data, these estimations support the concept that autocrine/paracrine insulin signalling within the islet is dynamic, rather than constitutive and saturated.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Density estimation via measure transport: Outlook for applications in the biological sciences

Abstract One among several advantages of measure transport methods is that they allow or a unified framework for processing and analysis of data distributed according to a wide class of probability measures. Within this context, we present results from computational studies aimed at assessing the potential of measure transport techniques, specifically, the use of triangular transport maps, as part of a workflow intended to support research in the biological sciences. Scenarios characterized by the availability of limited amount of sample data, which are common in domains such as radiation biology, are of particular interest. We find that when estimating a distribution density function given limited amount of sample data, adaptive transport maps are advantageous. In particular, statistics gathered from computing series of adaptive transport maps, trained on a series of randomly chosen subsets of the set of available data samples, leads to uncovering information hidden in the data. As a result, in the radiation biology application considered here, this approach provides a tool for generating hypotheses about gene relationships and their dynamics under radiation exposure.

gene expression data↗
DOE OSTI2022

Catalyst design to direct high-octane gasoline fuel properties for improved engine efficiency

The paraffin-to-olefin (P/O) ratio in gasoline fuel is a critical metric affecting fuel properties and engine efficiency. In the conversion of dimethyl ether (DME) to high-octane hydrocarbons over BEA zeolite catalysts, the P/O ratio can be controlled through catalyst design. Here, we report bimetallic catalysts that balance the net hydrogenation and dehydrogenation activity during DME homologation. The Cu-Zn/BEA catalyst exhibited greater relative dehydrogenation activity attributed to higher ionic site density, resulting in a lower P/O ratio (6.6) versus the benchmark Cu/BEA (9.4). The Cu-Ni/BEA catalyst exhibited increased hydrogenation due to reduced Ni species, resulting in a higher P/O ratio (19). The product fuel properties were estimated with an efficiency merit function and compared against finished gasolines and a typical alkylate blendstock. Merit values for the hydrocarbon product from all three BEA catalysts exceeded those of the comparison fuels (0–5.3), with the product from Cu-Zn/BEA exhibiting the highest merit value (9.7).

Catalyst design↗
DOE OSTI2015

Study of structural and electronic properties of ScN and ScAs in rocksalt and zincblende structure: A DFT approach

In this paper, we have studied the structural and electronic properties of ScN and ScAs in zincblende (ZB) and rocksalt (RS) phases. We have employed the full potential linearized augmented plane wave (FP-APW) method within the density functional theory (DFT). Generalized gradient approximation (GGA), due to Perdew-Burke-Ernzerhof (PBE) has been used to estimate the exchange-correlation functional. Our band structure results for ScN shows the metallic nature, whereas ScAs shows the semiconducting behavior. The obtained results are in excellent agreement with earlier reported data.

36 MATERIALS SCIENCE↗