SEARCH · Search NASA

Results for “constrained estimation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Higher-derivative corrections in M-theory from precision numerical bootstrap

We study higher-derivative corrections to the graviton scattering amplitude in M-theory, via the stress tensor correlator of 3d$\mathcal{N}$= 8 U(N) k × U(N) –k ABJM theory (dual to graviton scattering in M-theory on AdS 4 × S 7 /ℤ k ). We use the conformal bootstrap combined with an integral constraint derived from supersymmetric localization in order to constrain semishort OPE coefficients appearing in the stress tensor correlator. We obtain islands that are significantly more precise than those in previous studies that did not use the integral constraint. Using these islands, we can estimate the powers and coefficients in a large central charge expansion. This allows us to accurately read off the N 3 LO contribution, from the protected D 6 R 4 correction, and also estimate the N 4 LO contribution, from the unprotected D 8 R 4 correction.

AdS-CFT correspondence↗

DOE OSTI2021

Structural stability and artificial buckling modes in topology optimization

Abstract This paper demonstrates how a strain energy transition approach can be used to remove artificial buckling modes that often occur in stability constrained topology optimization problems. To simulate the structural response, a nonlinear large deformation hyperelastic simulation is performed, wherein the fundamental load path is traversed using Newton’s method and the critical buckling load levels are estimated by an eigenvalue analysis. The goal of the optimization is to minimize displacement, subject to constraints on the lowest critical buckling loads and maximum volume. The topology optimization problem is regularized via the Helmholtz PDE-filter and the method of moving asymptotes is used to update the design. The stability and sensitivity analyses are outlined in detail. The effectiveness of the energy transition scheme is demonstrated in numerical examples.

Dalklint, Anna (ORCID:0000000346195205)↗

DOE OSTI2021

Global Biodiversity Implications of Alternative Electrification Strategies Under the Shared Socioeconomic Pathways

Addressing climate mitigation while meeting global electrification goals will require major transitions from fossil-fuel dependence to large-scale renewable energy deployment. However, renewables require significant land assets per unit energy and could come at high cost to ecosystems, creating potential conflicts between global climate mitigation and biodiversity conservation. Here, we explore the potential biodiversity implications of alternative future global electrification pathways as depicted under the Shared Socioeconomic Scenarios (SSPs), i.e., alternative trends in societal development. We examined the intersection of high-resolution estimates of global energy densities for ten renewable and conventional technologies with global richness data to estimate technology-specific biodiversity footprints (species per GWh), whereas a Cumulative Biodiversity Impact (CBI) score was used to assess land and biodiversity outcomes of alternative scenarios. Downscaled electricity generation scenarios (2020-2100) were also constrained by alternative land conservation and energy development policies. Unexpectedly, variation among SSPs did not exhibit a clear tradeoff between global climate mitigation and CBI. Rather, CBIs were an outcome of total infrastructure development to meet electricity demand (from population growth and GDP) and the total magnitude of renewable energy development and storage technologies. Renewables assembled along a spectrum from land sharing to sparing. At the land sharing end, biomass-powered electricity from dedicated crops contributed the most to biodiversity impacts due to low energy density, whereas land-sparing technologies (solar) caused more-intense land degradation, but in smaller areas. Our results suggest that local land conservation practices and strategies promoting energy diversification could have greater implications for future biodiversity conflicts than global socioeconomic drivers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Observations suggest that North African dust absorbs less solar radiation than models estimate

Abstract Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Cosmological constraints from H ii starburst galaxy apparent magnitude and other cosmological measurements

ABSTRACT We use H ii starburst galaxy apparent magnitude measurements to constrain cosmological parameters in six cosmological models. A joint analysis of H ii galaxy, quasar angular size, baryon acoustic oscillations peak length scale, and Hubble parameter measurements result in relatively model-independent and restrictive estimates of the current values of the non-relativistic matter density parameter $\Omega _{\rm m_0}$ and the Hubble constant H0. These estimates favour a 2.0–3.4σ (depending on cosmological model) lower H0 than what is measured from the local expansion rate. The combined data are consistent with dark energy being a cosmological constant and with flat spatial hypersurfaces, but do not strongly rule out mild dark energy dynamics or slightly non-flat spatial geometries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey quasar sample: testing observational systematics on the Baryon Acoustic Oscillation measurement

ABSTRACT Baryon Acoustic Oscillations (BAO) are considered to be a very robust standard ruler against various systematics. This premise has been tested against observational systematics, but not to the level required for the next generation of galaxy surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid. In this paper, we investigate the effect of observational systematics on the BAO measurement of the final sample of quasars from the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in order to prepare and hone a similar analysis for upcoming surveys. We employ catalogues with various treatments of imaging systematic effects using linear and neural network-based non-linear approaches and consider how the BAO measurement changes. We also test how the variations to the BAO fitting model respond to the observational systematics. As expected, we confirm that the BAO measurements obtained from the DR16 quasar sample are robust against imaging systematics well within the statistical error, while reporting slightly modified constraints that shift the line-of-sight BAO signal by less than 1.1 per cent. We use realistic simulations with similar redshift and angular distributions as the DR16 sample to conduct statistical tests for validating the pipeline, quantifying the significance of differences, and estimating the expected bias on the BAO scale in future high-precision data sets. Although we find a marginal impact for the eBOSS QSO data, the work presented here is of vital importance for constraining the nature of dark energy with the BAO feature in the new era of big data cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Ionizing radiation from AGNs at z > 3.3 with the Subaru Hyper Suprime-Cam Survey and the CFHT Large Area U-band Deep Survey (CLAUDS)

ABSTRACT We use deep and wide imaging data from the CFHT Large Area U-band Deep Survey (CLAUDS) and the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) to constrain the ionizing radiation (Lyman Continuum, LyC) escape fraction from active galactic nuclei (AGNs) at z ∼ 3–4. For 94 AGNs with spectroscopic redshifts at 3.3 < z < 4.0, we use their U/i-band flux ratios to estimate LyC transmission of individual AGNs. The distribution of their LyC transmission shows values lower than the range of LyC transmission values for IGM of the same redshift range, which suggests that LyC escape fraction of AGNs at z > 3.3 is considerably lower than unity in most cases. We do not find any trend in LyC transmission values depending on their UV luminosities. Based on the photometry of stacked images we find the average flux ratio of LyC and non-ionizing UV photons escaping from the objects (fLyC/fUV)out = 0.182 ± 0.043 for AGNs at 3.3 < z < 3.6, which corresponds to LyC escape fraction fesc = 0.303 ± 0.072 if we assume a fiducial intrinsic SED of AGN. Based on the estimated LyC escape fraction and the UV luminosity function (UVLF) of AGNs, we argue that UV-selected AGNs’ contribution to the LyC emissivity at the epoch is minor, although the size of their contribution largely depends on the shape of the UVLF.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The Dark Energy Survey supernova program: cosmological biases from supernova photometric classification

ABSTRACT Cosmological analyses of samples of photometrically identified type Ia supernovae (SNe Ia) depend on understanding the effects of ‘contamination’ from core-collapse and peculiar SN Ia events. We employ a rigorous analysis using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark energy equation-of-state, w. Assuming a flat universe with Gaussian ΩM prior of 0.311 ± 0.010, we show that biases on w are <0.008 when using SuperNNova, with systematic uncertainties associated with contamination around 10 per cent of the statistical uncertainty on w for the DES-SN sample. An alternative approach of discarding contaminants using outlier rejection techniques (e.g. Chauvenet’s criterion) in place of SuperNNova leads to biases on w that are larger but still modest (0.015–0.03). Finally, we measure biases due to contamination on w0 and wa (assuming a flat universe), and find these to be <0.009 in w0 and <0.108 in wa, 5 to 10 times smaller than the statistical uncertainties for the DES-SN sample.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Assessing the Behavior of Moderately Volatile Elements on the Moon in Order to Constrain Processes of Magmatic Evolution and Planetary Accretion

Heterogeneous isotopic compositions of Zn and Ga in lunar basalts and highlands rocks indicate that secondary processing affected the stable isotopic composition of major lunar reservoirs. It follows that these fractionating processes must be identified and characterized in order to make robust estimates for the isotopic composition of the mare basalt source regions or the bulk silicate Moon (BSM). Contrary to previous assertions (e.g., Kato & Moynier, 2017), MVEs such as Zn and Ga do not behave similarly on the Moon, in line with differences in their chemical behavior and volatility. There is clear evidence that impact reworking fractionates zinc isotopes but, in addition, zinc isotopes are also highly sensitive to the formation of Ti-bearing oxides such as ilmenite. In contrast, gallium is far less susceptible to volatile reworking, but its isotopic composition is fractionated during incorporation into plagioclase (Wimpenny et al., 2022; Render et al., 2023). Based on these findings we conclude that current isotopic compositions of Zn and Ga in lunar rocks, such as those measured for the mare basalt suite, are unlikely to be representative of the bulk Moon when it accreted. As such, estimates for the MVE isotopic composition of the BSM derived from mare basalts may not be accurate, which may have implications for the incorporation of these data into dynamical models of the Moon’s formation. In the following, we discuss the main findings from this project in more detail, focusing on the behaviour of zinc and gallium isotopic systematics in lunar rocks and the processes that control their isotopic fractionation on the Moon.

58 GEOSCIENCES↗

DOE OSTI2024

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within $1\sigma$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Randomized measurement protocols for lattice gauge theories

Randomized measurement protocols, including classical shadows, entanglement tomography, and randomized benchmarking are powerful techniques to estimate observables, perform state tomography, or extract the entanglement properties of quantum states. While unraveling the intricate structure of quantum states is generally difficult and resource-intensive, quantum systems in nature are often tightly constrained by symmetries. Furthermore, this can be leveraged by the symmetry-conscious randomized measurement schemes we propose, yielding clear advantages over symmetry-blind randomization such as reducing measurement costs, enabling symmetry-based error mitigation in experiments, allowing differentiated measurement of (lattice) gauge theory entanglement structure, and, potentially, the verification of topologically ordered states in existing and near-term experiments. Crucially, unlike symmetry-blind randomized measurement protocols, these latter tasks can be performed without relearning symmetries via full reconstruction of the density matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Directly Determined Properties of HD 97658 from Interferometric Observations

We conducted interferometric observations with the CHARA Array of transiting super-Earth host HD 97658 and measured its limb-darkened angular diameter to be θ {sub LD} = 0.314 ± 0.004 mas. The combination of the angular diameter with the Gaia EDR3 parallax value with zero-point correction (π = 46.412 ± 0.022 mas, d =21.546 ± 0.011 pc) yields a physical radius of R {sub ·} = 0.728 ± 0.008 R {sub ⊙}. We also measured the bolometric flux of the star to be F {sub bol} = 2.42 ± 0.05 × 10{sup -8} erg s{sup -1} cm{sup -2}, which, together with angular size, allows a measurement of the effective temperature T {sub eƒƒ} = 5212 ± 43 K. Our directly determined physical stellar properties are in good agreement with previous estimates derived from spectroscopy. We used our measurements in combination with stellar evolutionary models and properties of the transit of HD 97658 b to determine the mass and age of HD 97658 as well as constrain the properties of the planet. Our results and our analysis of the TESS light curve on the planet (TOI-1821) corroborate previous studies of this system with tighter uncertainties.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Cloud Atlas: Unraveling the Vertical Cloud Structure with the Time-series Spectrophotometry of an Unusually Red Brown Dwarf

Rotational modulations of emission spectra in brown dwarf and exoplanet atmospheres show that clouds are often distributed non-uniformly in these ultracool atmospheres. The spatial heterogeneity in cloud distribution demonstrates the impact of atmospheric dynamics on cloud formation and evolution. In this study, we update the Hubble Space Telescope (HST) time-series data analysis of the previously reported rotational modulations of WISEP J004701+680352—an unusually red late-L brown dwarf with a spectrum similar to that of the directly imaged planet HR 8799e. We construct a self-consistent spatially heterogeneous cloud model to explain the HST and the Spitzer time-series observations, as well as the time-averaged spectra of WISE 0047. Additionally, in the heterogeneous cloud model, a cloud thickness variation of around one pressure scale height explains the wavelength dependence in the HST near-IR spectral variability. By including disequilibrium CO/CH 4 chemistry, our models also reproduce the redder $J-{K}_{{\rm{s}}}$ color of WISE 0047 compared to that of field brown dwarfs. We discuss the impact of vertical cloud structure on atmospheric profile and estimate the minimum eddy diffusivity coefficient for other objects with redder colors. Our data analysis and forward modeling results demonstrate that time-series spectrophotometry with a broad wavelength coverage is a powerful tool for constraining heterogeneous atmospheric structure.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Constraining long‐term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Monitoring Seasonal Shear Wave Velocity Changes in the Top 6 m at Garner Valley in Southern California With Borehole Data

Abstract Subsurface structures play important roles in seismic ground motion, crustal hydrology, stability of the built environment, and more. Constraining temporal changes of subsurface shear wave velocity ( V S ) can provide useful information to all these topics and the growing field of hydrological monitoring with seismic velocity. Using borehole records at Garner Valley, CA, we estimate seasonal subsurface V S variations from impulse response functions (IRFs) of earthquake data (2005–2018) along with IRFs and cross‐correlation of cross‐hole experiment data (2015–2018). The inferred V S variations are up to ∼25% in the top 6 m and ∼10% at 2–5 m in depth. The V S variations correlate strongly with the water table depth changes, suggesting that the changes are mostly due to fluctuations of pore pressure in the shallow material. The shallow velocity changes alter the near‐surface conditions, can affect seismic hazard estimation, and may be improperly attributed to deeper processes without careful analysis.

58 GEOSCIENCES↗

DOE OSTI2025

Stochastic Model Predictive Control With Gaussian Wind Direction Preview for Wake Steering

This article addresses the problem of wake steering control for wind farms that explicitly consider the tradeoff between farm-level power generation and yaw duty cycle under variable and uncertain wind conditions. A novel stochastic model predictive control (MPC) algorithm is presented, which utilizes a stochastic model of the freestream wind field components in a receding horizon framework to compute optimal yaw set points that maximize the expected value of the farm power while constraining the yaw actuation. Different configurations of the algorithm are evaluated using a steady-state wind farm simulator. The proposed stochastic MPC algorithm can plan control actions over a future prediction horizon based on probabilistic estimates of the incoming wind magnitude and direction.

17 WIND ENERGY↗