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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Constraints on Λ CDM extensions from the SPT-3G 2018 $EE$ and $TE$ power spectra

Here, we present constraints on extensions to the Λ CDM cosmological model from measurements of the E-mode polarization autopower spectrum and the temperature-E-mode cross-power spectrum of the cosmic microwave background (CMB) made using 2018 SPT-3G data. The extensions considered vary the primordial helium abundance, the effective number of relativistic degrees of freedom, the sum of neutrino masses, the relativistic energy density and mass of a sterile neutrino, and the mean spatial curvature. We do not find clear evidence for any of these extensions, from either the SPT-3G 2018 dataset alone or in combination with baryon acoustic oscillation and Planck data. None of these model extensions significantly relax the tension between Hubble-constant, H 0 , constraints from the CMB and from distance-ladder measurements using Cepheids and supernovae. The addition of the SPT-3G 2018 data to Planck reduces the square-root of the determinants of the parameter covariance matrices by factors of 1.3–2.0 across these models, signaling a substantial reduction in the allowed parameter volume. We also explore CMB-based constraints on H 0 from combined SPT, Planck, and ACT DR4 datasets. While individual experiments see some indications of different H 0 values between the TT, TE, and EE spectra, the combined H 0 constraints are consistent between the three spectra. For the full combined datasets, we report H 0 = 67.49 ± 0.53 km s -1 Mpc -1 , which is the tightest constraint on H0 from CMB power spectra to date and in 4.1σ tension with the most precise distance-ladder-based measurement of H 0 . The SPT-3G survey is planned to continue through at least 2023, with existing maps of combined 2019 and 2020 data already having ~ 3.5 x lower noise than the maps used in this analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Accelerating flux balance calculations in genome-scale metabolic models by localizing the application of loopless constraints

Abstract Background Genome-scale metabolic network models and constraint-based modeling techniques have become important tools for analyzing cellular metabolism. Thermodynamically infeasible cycles (TICs) causing unbounded metabolic flux ranges are often encountered. TICs satisfy the mass balance and directionality constraints but violate the second law of thermodynamics. Current practices involve implementing additional constraints to ensure not only optimal but also loopless flux distributions. However, the mixed integer linear programming problems required to solve become computationally intractable for genome-scale metabolic models. Results We aimed to identify the fewest needed constraints sufficient for optimality under the loopless requirement. We found that loopless constraints are required only for the reactions that share elementary flux modes representing TICs with reactions that are part of the objective function. We put forth the concept of localized loopless constraints (LLCs) to enforce this minimal required set of loopless constraints. By combining with a novel procedure for minimal null-space calculation, the computational time for loopless flux variability analysis (ll-FVA) is reduced by a factor of 10–150 compared to the original loopless constraints and by 4–20 times compared to the current fastest method Fast-SNP with the percent improvement increasing with model size. Importantly, LLCs offer a scalable strategy for loopless flux calculations for multi-compartment/multi-organism models of large sizes, for example, shortening the CPU time for ll-FVA from 35 h to less than 2 h for a model with more than104 reactions. Availability and implementation Matlab functions are available in the Supplementary Material or at https://github.com/maranasgroup/lll-FVA Supplementary information Supplementary data are available at Bioinformatics online.

Chan, Siu H. J. (ORCID:000000027707656X)↗
DOE OSTI2017

Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating

Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21 cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21 cm statistics to the underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high-dimensional and weakly constrained parameter space. In this work, we use machine learning algorithms to build a fast emulator that can accurately mimic an expensive simulation of the 21 cm signal across a wide parameter space. We embed our emulator within a Markov Chain Monte Carlo framework in order to perform Bayesian parameter constraints over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21 cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on σ{sub 8}. We provide both our generalized emulator code and its implementation specifically for 21 cm parameter constraints as publicly available software.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks

Generative Adversarial Networks (GANs) are becoming popular choices for unsupervised learning. At the same time there is a concerted effort in the machine learning community to expand the range of tasks in which learning can be applied as well as to utilize methods from other disciplines to accelerate learning. With this in mind, in the current work we suggest ways to enforce given constraints in the output of a GAN both for interpolation and extrapolation. The two cases need to be treated differently. For the case of interpolation, the incorporation of constraints is built into the training of the GAN. The incorporation of the constraints respects the primary game-theoretic setup of a GAN so it can be combined with existing algorithms. However, it can exacerbate the problem of instability during training that is well-known for GANs. We suggest adding small noise to the constraints as a simple remedy that has performed well in our numerical experiments. The case of extrapolation (prediction) is more involved. First, we employ a modified interpolation training process that uses noisy data but does {\it not} necessarily enforce the constraints during training. Second, the resulting modified interpolator is used for extrapolation where the constraints are enforced after each step through projection on the space of constraints.

Stinis, Panagiotis↗
DOE OSTI2017

Efficient Simulation of Welding Distortion in Large Structures and Its Reduction by Jig Constraints

Two large construction machinery structures were welded separately with and without jig constraints. The welding distortion of the entire structure was measured by a 3D coordinate measuring system and simulated by elastic FEM using the inherent deformation method. To obtain an accurate inherent deformation, a thermal elastoplastic FE analysis of simple one-side fillet joints with and without jig constraints was performed. Efficient simulation of welding distortion in large structures was accomplished by applying inherent deformation in a localized region, and the effect of jig constraint on the reduction of welding distortion was clarified. The computation of inherent deformation, the weld zone definition and the conversion of inherent deformation into inherent strain were automated. Measured and computed welding distortions in large structures had a good correspondence with respect to both tendency and magnitude. Further investigation of jig configuration was performed for enhanced reduction of welding distortion. Alternative controlling techniques for common welded structures were also addressed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and P l a n c k . II. Cross-correlation measurements and cosmological constraints

Cross-correlations of galaxy positions and galaxy shears with maps of gravitational lensing of the cosmic microwave background (CMB) are sensitive to the distribution of large-scale structure in the Universe. Such cross-correlations are also expected to be immune to some of the systematic effects that complicate correlation measurements internal to galaxy surveys. We present measurements and modeling of the cross-correlations between galaxy positions and galaxy lensing measured in the first three years of data from the Dark Energy Survey with CMB lensing maps derived from a combination of data from the 2500 deg 2 SPT-SZ survey conducted with the South Pole Telescope and full-sky data from the Planck satellite. The CMB lensing maps used in this analysis have been constructed in a way that minimizes biases from the thermal Sunyaev Zel’dovich effect, making them well suited for cross-correlation studies. The total signal-to-noise of the cross-correlation measurements is 23.9 (25.7) when using a choice of angular scales optimized for a linear (nonlinear) galaxy bias model. Here we use the cross-correlation measurements to obtain constraints on cosmological parameters. For our fiducial galaxy sample, which consist of four bins of magnitude-selected galaxies, we find constraints of Ω m =0.272$^{+0.032}_{-0.052}$ and S 8 ≡σ8$\sqrt{Ω_m/0.3}$=0.736$^{+0.032}_{-0.028}$ (Ω m =0.245$^{+0.026}_{-0.044}$ and S 8 =0.734$^{+0.035}_{-0.028}$) when assuming linear (nonlinear) galaxy bias in our modeling. Considering only the cross-correlation of galaxy shear with CMB lensing, we find Ω m =0.270$^{+0.043}_{-0.061}$ and S 8 =0.740$^{+0.034}_{-0.029}$. Our constraints on S8 are consistent with recent cosmic shear measurements, but lower than the values preferred by primary CMB measurements from Planck.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dark Energy Survey year 1 results: Constraints on extended cosmological models from galaxy clustering and weak lensing

We present constraints on extensions of the minimal cosmological models dominated by dark matter and dark energy, Lambda CDM and wCDM, by using a combined analysis of galaxy clustering and weak gravitational lensing from the first-year data of the Dark Energy Survey (DES Y1) in combination with external data. We consider four extensions of the minimal dark energy-dominated scenarios: (1) nonzero curvature Omega(k), (2) number of relativistic species N-eff different from the standard value of 3.046, (3) time-varying equation-of-state of dark energy described by the parameters w(0) and w(a) (alternatively quoted by the values at the pivot redshift, w(p), and w(a)), and (4) modified gravity described by the parameters is mu(0) and Sigma(0) that modify the metric potentials. We also consider external information from Planck cosmic microwave background measurements; baryon acoustic oscillation measurements from SDSS, 6dF, and BOSS; redshift-space distortion measurements from BOSS; and type Ia supernova information from the Pantheon compilation of datasets. Constraints on curvature and the number of relativistic species are dominated by the external data; when these are combined with DES Y1, we find Omega(k) = 0.0020(-0.0032)(+0.0037) at the 68% confidence level, and the upper limit N-eff < 3.28(3.55) at 68% (95%) confidence, assuming a hard prior N-eff > 3.0. For the time-varying equation-of-state, we find the pivot value (w(p), w(a)) = (-0.91(-0.23)(+0.19), -0.57(-1.11)(+0.93)) at pivot redshift z(p )= 0.27 from DES alone, and (w(p), w(a)) = (-1.01(-0.04)(+0.04), -0.28(-0.48)(+0.37)) at z(p) = 0.20 from DES Y1 combined with external data; in either case we find no evidence for the temporal variation of the equation of state. For modified gravity, we find the present-day value of the relevant parameters to be Sigma(0) = 0.43(-)(0.29)(+0.28) from DES Y1 alone, and (Sigma(0), mu(0)) = (0.06(-0.07)(+0.08), -0.11(-0.46)(+0.42)) from DES Y1 combined with external data. These modified-gravity constraints are consistent with predictions from general relativity.

Abbott, T. M. C.↗
DOE OSTI2019

Cosmological Constraints from Multiple Probes in the Dark Energy Survey

The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically confirmed type Ia supernova light curves, the baryon acoustic oscillation feature, weak gravitational lensing, and galaxy clustering. Here we present combined results from these probes, deriving constraints on the equation of state, w, of dark energy and its energy density in the Universe. Independently of other experiments, such as those that measure the cosmic microwave background, the probes from this single photometric survey rule out a Universe with no dark energy, finding w = -0.80(-0.11)(+0.09). The geometry is shown to be consistent with a spatially flat Universe, and we obtain a constraint on the baryon density of Omega(b) = 0.069(-0.012)(+0.009) that is independent of early Universe measurements. These results demonstrate the potential power of large multiprobe photometric surveys and pave the way for order of magnitude advances in our constraints on properties of dark energy and cosmology over the next decade.

Abbott, T. M. C.↗
DOE OSTI2019

Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB

We report direct-detection constraints on light dark matter particles interacting with electrons. The results are based on a method that exploits the extremely low levels of leakage current of the DAMIC detector at SNOLAB of 2–6×10-22 A cm^-2. We evaluate the charge distribution of pixels that collect < 10 e- for contributions beyond the leakage current that may be attributed to dark matter interactions. Constraints are placed on so-far unexplored parameter space for dark matter masses between 0.6 and 100 MeV c^-2. We also present new constraints on hidden-photon dark matter with masses in the range 1.2–30 eV c^-2.

Dark Matter, DAMIC, SNOLAB↗
DOE OSTI2018

Early-Universe constraints on dark matter-baryon scattering and their implications for a global 21 cm signal

Here we present and compare several cosmological constraints on the cross section for elastic scattering between dark matter (DM) and baryons, for cross sections with a range of power-law dependences on the DM-baryon relative velocity v , especially focusing on the case of σ ∝ v - 4 . We study constraints spanning a wide range of epochs in cosmological history, from prerecombination distortions to the blackbody spectrum and anisotropies of the cosmic microwave background (CMB), to modifications to the intergalactic medium temperature and the resulting 21 cm signal, and discuss the allowed signals in the latter channels given the constraints from the former. Furthermore, we improve previous constraints on DM-baryon scattering from the CMB anisotropies, demonstrate via principal component analysis that the effect on the CMB can be written as a simple function of DM mass for v - 4 scattering, and map out the redshifts dominating this signal. We show that given high-redshift constraints on DM-baryon scattering, a v - 4 scaling of the cross section for light DM would be sufficient to explain the deep 21 cm absorption trough recently claimed by the Experiment to Detect the Reionization Step, if 100% of the DM scatters with baryons; we estimate the minimal necessary velocity scaling and find that it is close to v - 4 . For millicharged DM models proposed to explain the observation, where only a small fraction of the DM interacts, we estimate that a PIXIE-like future experiment measuring CMB spectral distortion could test the relevant parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Cosmological Constraints from Gas Mass Fractions of Massive, Relaxed Galaxy Clusters

We present updated cosmological constraints from measurements of the gas mass fractions (f(gas)) of massive, dynamically relaxed galaxy clusters. Our new data set has greater leverage on models of dark energy, thanks to the addition of the Perseus cluster at low redshifts, two new clusters at redshifts z greater than or similar to 1, and significantly longer observations of four clusters at 0.6 < z < 0.9. Our low-redshift (z < 0.16) f(gas) data, combined with the cosmic baryon fraction measured from the cosmic microwave background (CMB), imply a Hubble constant of h = 0.722 +/- 0.067. Combining the full f(gas) data set with priors on the cosmic baryon density and the Hubble constant, we constrain the dark energy density to be Omega(Lambda) = 0.865 +/- 0.119 in non-flat Lambda cold dark matter (cosmological constant) models, and its equation of state to be in flat, constant-w models, respectively 41percent and 29percent tighter than our previous work, and comparable to the best constraints available from other probes. Combining f(gas), CMB, supernova, and baryon acoustic oscillation data, we also constrain models with global curvature and evolving dark energy. For the massive, relaxed clusters employed here, we find the scaling of f(gas) with mass to be consistent with a constant, with an intrinsic scatter that corresponds to just similar to 3percent in distance.

clusters: general – X-rays:↗
DOE OSTI2021

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

We present the first joint analysis of cluster abundances and auto or cross-correlations of three cosmic tracer fields: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis (4×2pt+N) of cluster abundances, three cluster cross-correlations, and the auto correlations of the galaxy density measured from the first year data of the Dark Energy Survey, we obtain Ωm=0.305-0.038+0.055 and σ8=0.783-0.054+0.064. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat νΛCDM model. Consequently, we combine cluster abundances and all two-point correlations from across all three cosmic tracer fields (6×2pt+N) and find improved constraints on cosmological parameters as well as on the cluster observable-mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multiprobe analyses of upcoming wide imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters

We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe. Ia from the first three years of DES-SN, combined with a low-redshift sample of 122 SNe from the literature. Our "DES-SN3YR" result from these 329 SNe. Ia is based on a series of companion analyses and improvements covering SN. Ia discovery, spectroscopic selection, photometry, calibration, distance bias corrections, and evaluation of systematic uncertainties. For a flat Lambda CDM model we find a matter density Omega(m) = 0.331 +/- 0.038. For a flat wCDM model, and combining our SN. Ia constraints with those from the cosmic microwave background (CMB), we find a dark energy equation of state w = -0.978 +/- 0.059, and Omega(m) = 0.321 +/- 0.018. For a flat w(0)w(a)CDM model, and combining probes from SN. Ia, CMB and baryon acoustic oscillations, we find w(0) = -0.885 +/- 0.114 and w(a) = -0.387 +/- 0.430. These results are in agreement with a cosmological constant and with previous constraints using SNe. Ia (Pantheon, JLA).

dark energy↗
DOE OSTI2020

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Environmental Constraints that Limit Methanogenesis

Methanogens are active in many different ecosystems, including habitats with biologically-derived organic matter as substrates such as aquatic sediments, wetlands, agricultural or natural soils subject to inundation, sewage digesters, and the anoxic portions of animal digestive tracts. Methanogens are also present in habitats with geochemically-supplied substrates such as hot springs, hydrothermal vents, volcanically-influenced habitats, and, potentially, the deep crustal subsurface. Methanogens as a group tolerate a broad range of physicochemical conditions, including temperatures from -2 to 122°C, pH values of 3.0 to 10.2, salinities up to halite saturation, and pressures of at least 75 MPa. Globally, variations in methane emissions can be explained to a large degree by variations in temperature and water availability. The distribution and activity of methanogens are constrained by ecological interactions that can be stimulatory or competitive, and by physicochemical factors that act at the biochemical or bioenergetic levels. In addition to the constraints placed on methanogens by physicochemical extremes, methanogen distribution and activity are constrained by the availability of energy and nutrients, the presence of inhibitory molecules (most notably oxygen), and the seawater anion, sulfate, due to competitive ecological interactions. Although methanogen tolerances to individual extremes are documented in culture, and the corresponding biochemical adaptations are understood to varying degrees, the natural environment frequently presents combinations of extreme conditions and energy limitations that may limit methanogen distribution to less than the optimally tolerated range of a single parameter. Little is understood about the compound effects of such extremes, nor the commonalities among them that will ultimately form the basis for predictive models of environmental methanogen population distribution. Future work that targets these questions, through a combination of culture work, “omic” analyses, in situ studies, and conceptual and quantitative models, will be needed to better understand the physiological ecology of methanogens.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Moving beyond the constraints of chemistry via crystal structure discovery with isotropic multiwell pair potentials

The rigid constraints of chemistry-dictated by quantum mechanics and the discrete nature of the atom-limit the set of observable atomic crystal structures. What structures are possible in the absence of these constraints? Here, we systematically crystallize one-component systems of particles interacting with isotropic multiwell pair potentials. We investigate two tunable families of pairwise interaction potentials. Our simulations self-assemble a multitude of crystal structures ranging from basic lattices to complex networks. Sixteen of the structures have natural analogs spanning all coordination numbers found in inorganic chemistry. Fifteen more are hitherto unknown and occupy the space between covalent and metallic coordination environments. The discovered crystal structures constitute targets for self-assembly and expand our understanding of what a crystal structure can look like.

crystal structures↗