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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Probing modifications of general relativity using current cosmological observations

We test general relativity (GR) using current cosmological data: the CMB from WMAP5 [E. Komatsu et al. (WMAP Collaboration), Astrophys. J. Suppl. Ser. 180, 330 (2009)], the integrated Sachs-Wolfe (ISW) effect from the cross correlation of the CMB with six galaxy catalogs [T. Giannantonio et al., Phys. Rev. D 77, 123520 (2008)], a compilation of supernovae (SNe) type Ia including the latest Sloan Digital Sky Survey SNe [R. Kessler et al., Astrophys. J. Suppl. Ser. 185, 32 (2009).], and part of the weak lensing (WL) data from the Canada-Franco-Hawaii Telescope Legacy Survey [L. Fu et al., Astron. Astrophys. 479, 9 (2008); M. Kilbinger et al., Astron. Astrophys. 497, 677 (2009).] that probe linear and mildly nonlinear scales. We first test a model in which the effective Newtonian constant {mu} and the ratio of the two gravitational potentials, {eta}, transit from the GR value to another constant at late times; in this case, we find that GR is fully consistent with the combined data. The strongest constraint comes from the ISW effect which would arise from this gravitational transition; the observed ISW signal imposes a tight constraint on a combination of {mu} and {eta} that characterizes the lensing potential. Next, we consider four pixels in time and space for each function {mu} and {eta}, and perform a principal component analysis, finding that seven of the resulting eight eigenmodes are consistent with GR within the errors. Only one eigenmode shows a 2{sigma} deviation from the GR prediction, which is likely to be due to a systematic effect. However, the detection of such a deviation demonstrates the power of our time- and scale-dependent principal component analysis methodology when combining observations of structure formation and expansion history to test GR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the Viability of Video Imaging in Leak Rate Quantification: A Theoretical Error Analysis

Optical gas imaging through multispectral cameras is a promising technique for mitigation of methane emissions through localization and quantification of emissions sources. While more advanced cameras developed in recent years have led to lower uncertainties in measuring gas concentrations, a systematic analysis of the uncertainties associated with leak rate estimation have been overlooked. We present a systematic categorization of the involved uncertainties with a focus on a theoretical analysis of projection uncertainties that are inherent to this technique. The projection uncertainties are then quantified using Large Eddy Simulation experiments of a point source release into the atmosphere. Our results show that while projection uncertainties are typically about 5% of the emission rate, low acquisition times and observation of the gas plume at small distances from the emission source (<10 m) can amount to errors of about 20%. Further, we found that acquisition times on the order of tens of seconds are sufficient to significantly reduce (>50%) the projection uncertainties. These findings suggest robust procedures on how to reduce projection uncertainties, however, a balance between other sources of uncertainty due to operational conditions and the employed instrumentation are required to outline more practical guidelines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Validation of the NSRDB-SUNY global horizontal irradiance in California

Satellite derived global horizontal solar irradiance (GHI) from the SUNY modeled dataset in the National Solar Radiation Database (NSRDB) was compared to measurements from 27 weather stations in California during the years 1998-2005. The statistics of spatial and temporal differences between the two datasets were analyzed and related to meteorological phenomena. Overall mean bias errors (MBE) of the NSRDB-SUNY indicated a GHI overprediction of 5%, which is smaller than the sensor accuracy of ground stations. However, at coastal sites, year-round systematic positive MBEs in the NSRDB-SUNY data up to 18% were observed and monthly MBEs increased up to 54% in the summer months during the morning. These differences were explained by a tendency for the NSRDB-SUNY model to overestimate GHI under cloudy conditions at the coast during summer mornings. A persistent positive evening MBE which was independent of site location and cloudiness occurred at all stations and was explained by an error in the time-shifting method applied in the NSRDB-SUNY. A correction method was derived for these two errors to improve the accuracy of the NSRDB-SUNY data in California. (author)

14 SOLAR ENERGY↗
DOE OSTI2015

ESTIMATION OF DISTANCES TO STARS WITH STELLAR PARAMETERS FROM LAMOST

We present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star’s absolute magnitude. This technique is tailored specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ∼5° diameter “plate” that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and target selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ∼20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ∼40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

A SURVEY OF THE PARAMETER SPACE OF THE COMPRESSIBLE LIQUID DROP MODEL AS APPLIED TO THE NEUTRON STAR INNER CRUST

We present a systematic survey of the range of predictions of the neutron star inner crust composition, crust-core transition densities and pressures, and density range of the nuclear 'pasta' phases at the bottom of the crust provided by the compressible liquid drop model in light of the current experimental and theoretical constraints on model parameters. Using a Skyrme-like model for nuclear matter, we construct baseline sequences of crust models by consistently varying the density dependence of the bulk symmetry energy at nuclear saturation density, L, under two conditions: (1) that the magnitude of the symmetry energy at saturation density J is held constant, and (2) J correlates with L under the constraint that the pure neutron matter (PNM) equation of state (EoS) satisfies the results of ab initio calculations at low densities. Such baseline crust models facilitate consistent exploration of the L dependence of crustal properties. The remaining surface energy and symmetric nuclear matter parameters are systematically varied around the baseline, and different functional forms of the PNM EoS at sub-saturation densities implemented, to estimate theoretical 'error bars' for the baseline predictions. Inner crust composition and transition densities are shown to be most sensitive to the surface energy at very low proton fractions and to the behavior of the sub-saturation PNM EoS. Recent calculations of the energies of neutron drops suggest that the low-proton-fraction surface energy might be higher than predicted in Skyrme-like models, which our study suggests may result in a greatly reduced volume of pasta in the crust than conventionally predicted.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms

We present a comparison of methods for uncertainty quantification (UQ) in deep learning algorithms in the context of a simple physical system. Three of the most common uncertainty quantification methods - Bayesian Neural Networks (BNN), Concrete Dropout (CD), and Deep Ensembles (DE) - are compared to the standard analytic error propagation. We discuss this comparison in terms endemic to both machine learning ("epistemic" and "aleatoric") and the physical sciences ("statistical" and "systematic"). The comparisons are presented in terms of simulated experimental measurements of a single pendulum - a prototypical physical system for studying measurement and analysis techniques. Our results highlight some pitfalls that may occur when using these UQ methods. For example, when the variation of noise in the training set is small, all methods predicted the same relative uncertainty independently of the inputs. This issue is particularly hard to avoid in BNN. On the other hand, when the test set contains samples far from the training distribution, we found that no methods sufficiently increased the uncertainties associated to their predictions. This problem was particularly clear for CD. In light of these results, we make some recommendations for usage and interpretation of UQ methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Renormalization of heavy-light currents in moving nonrelativistic QCD

Heavy-light decays such as B{yields}{pi}l{nu}, B{yields}K*{gamma} and B{yields}K{sup (*)}ll can be used to constrain the parameters of the standard model and in indirect searches for new physics. While the precision of experimental results has improved over the last years this has still to be matched by equally precise theoretical predictions. The calculation of heavy-light form factors is currently carried out in lattice QCD. Because of its small Compton wavelength we discretize the heavy quark in an effective nonrelativistic theory. By formulating the theory in a moving frame of reference discretization errors in the final state are reduced at large recoil. Over the last years the formalism has been improved and tested extensively. Systematic uncertainties are reduced by renormalizing the m(oving) NRQCD action and heavy-light decay operators. The theory differs from QCD only for large loop momenta at the order of the lattice cutoff and the calculation can be carried out in perturbation theory as an expansion in the strong coupling constant. In this paper we calculate the one-loop corrections to the heavy-light vector and tensor operator. Because of the complexity of the action the generation of lattice Feynman rules is automated and loop integrals are solved by the adaptive Monte Carlo integrator VEGAS. We discuss the infrared and ultraviolet divergences in the loop integrals both in the continuum and on the lattice. The light quarks are discretized in the ASQTad and highly improved staggered quark (HISQ) action; the formalism is easily extended to other quark actions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

Background: Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device. Methods: Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland–Altman analysis. Results: Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323–362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353–464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland–Altman analysis. Conclusions: Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Target Formulation and Construction in Mesh Quality Improvement

In the Target-matrix Optimization Paradigm (TMOP), it’s long been understood that one must create a set of target matrices before the mesh can be optimized. But there is still no general method to create correct, effective targets in response to a specific mesh quality improvement goal. The TMOP literature describes how certain sets of target matrices can be used to control the shape or size of mesh elements, but those examples address only a fraction of the problems that can occur in mesh quality improvement and were not derived from a general framework for target matrix construction. In this work, a general method of target construction is introduced based on an independent set of geometric parameters which are intrinsic to the Jacobian matrices upon which TMOP is based. The parameters enable a systematic approach to target definition and construction. The approach entails two parts. The first part defines correspondences between available raw data (stuff about the mesh and/or the physical solution) and intermediate data (e.g., a field of error estimates). Once the correspondences are established, the raw data is processed into intermediate field data existing on mesh sample points. The second part is to create a model that represents the values of the geometric target parameters as functions of the intermediate data. The model is then tested numerically to establish model constants and effectiveness. This systematic approach to target construction is illustrated in a set of examples to show how it can be applied to common problems in mesh optimization such as equidistribution of geometric properties, preservation of existing good quality, and adaptation of the mesh to the solution. The result is a systematic method of target construction for TMOP which can be applied to a wide variety of planar and volume mesh quality improvement tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Informed total-error-minimizing priors: Interpretable cosmological parameter constraints despite complex nuisance effects

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, for example, when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of informed total-error-minimizing (ITEM) priors to address this problem. An ITEM prior is a prior distribution on a set of nuisance parameters, such as those describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters (e.g., cosmological parameters). Our method works as follows. For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut, we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we applied our method to the density split statistics measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and that they allow for sharpened yet robust constraints on the parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Primordial power spectrum from Planck

Using modified Richardson-Lucy algorithm we reconstruct the primordial power spectrum (PPS) from Planck Cosmic Microwave Background (CMB) temperature anisotropy data. In our analysis we use different combinations of angular power spectra from Planck to reconstruct the shape of the primordial power spectrum and locate possible features. Performing an extensive error analysis we found the dip near ℓ ∼ 750–850 represents the most prominent feature in the data. Feature near ℓ ∼ 1800–2000 is detectable with high confidence only in 217 GHz spectrum and is apparently consequence of a small systematic as described in the revised Planck 2013 papers. Fixing the background cosmological parameters and the foreground nuisance parameters to their best fit baseline values, we report that the best fit power law primordial power spectrum is consistent with the reconstructed form of the PPS at 2σ C.L. of the estimated errors (apart from the local features mentioned above). As a consistency test, we found the reconstructed primordial power spectrum from Planck temperature data can also substantially improve the fit to WMAP-9 angular power spectrum data (with respect to power-law form of the PPS) allowing an overall amplitude shift of ∼ 2.5%. In this context low-ℓ and 100 GHz spectrum from Planck which have proper overlap in the multipole range with WMAP data found to be completely consistent with WMAP-9 (allowing amplitude shift). As another important result of our analysis we do report the evidence of gravitational lensing through the reconstruction analysis. Finally we present two smooth form of the PPS containing only the important features. These smooth forms of PPS can provide significant improvements in fitting the data (with respect to the power law PPS) and can be helpful to give hints for inflationary model building.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A modified time-of-flight method for precise determination of high speed ratios in molecular beams

Time-of-flight (TOF) is a standard experimental technique for determining, among others, the speed ratio S (velocity spread) of a molecular beam. The speed ratio is a measure for the monochromaticity of the beam and an accurate determination of S is crucial for various applications, for example, for characterising chromatic aberrations in focussing experiments related to helium microscopy or for precise measurements of surface phonons and surface structures in molecular beam scattering experiments. For both of these applications, it is desirable to have as high a speed ratio as possible. Molecular beam TOF measurements are typically performed by chopping the beam using a rotating chopper with one or more slit openings. The TOF spectra are evaluated using a standard deconvolution method. However, for higher speed ratios, this method is very sensitive to errors related to the determination of the slit width and the beam diameter. The exact sensitivity depends on the beam diameter, the number of slits, the chopper radius, and the chopper rotation frequency. We present a modified method suitable for the evaluation of TOF measurements of high speed ratio beams. The modified method is based on a systematic variation of the chopper convolution parameters so that a set of independent measurements that can be fitted with an appropriate function are obtained. We show that with this modified method, it is possible to reduce the error by typically one order of magnitude compared to the standard method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

A study of the contribution of doubly excited ionic states to the properties of hot dense high-Z plasmas

The role of two-electron processes, i.e. dielectronic recombination and autoionization, in the ionization balance and X-ray emission of hot dense plasmas composed of various high-Z materials is explored. Tungsten, gold, lead and uranium are considered. It is shown that the average ion charge and the high-energy emissivity are both sensitive to the dielectronic recombination rate. A systematic study demonstrates the degree of this sensitivity. It is found that the complete neglect of these 2-electron processes introduces a large error but once included, the key physical properties are quite insensitive to the rate over the important 2–3 keV temperature range. The high-energy emissivity depends strongly on temperature, peaking at conditions corresponding to a closed shell system, and on the square of the electron density, as for a coronal system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control

Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris . This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Density functional theory of water with the machine-learned DM21 functional

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn–Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. Furthermore, we find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Quantum Monte Carlo Calculations in Solids with Downfolded Hamiltonians

We present a systematic downfolding many-body approach for extended systems. Many-body calculations operate on a simpler Hamiltonian which retains material-specific properties. The Hamiltonian is systematically improvable and allows one to dial, in principle, between the simplest model and the original Hamiltonian. As a by-product, pseudopotential errors are essentially eliminated using a frozen-core treatment. The computational cost of the many-body calculation is dramatically reduced without sacrificing accuracy. We use the auxiliary-field quantum Monte Carlo (AFQMC) method to solve the downfolded Hamiltonian. Excellent accuracy is achieved for a range of solids, including semiconductors, ionic insulators, and metals. We further test the method by determining the spin gap in NiO, a challenging prototypical material with strong electron correlation effects. This approach greatly extends the reach of general, ab initio many-body calculations in materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations

In this work, we evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, 5, and 6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the qobserved Northern Annular Mode (NAM), North Atlantic Oscillation (NAO), Pacific North America pattern (PNA), Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a Common Basis Function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and High-top vertical coordinate), however the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the post-dominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious post-dominant season amplitude errors found in many models can be addressed in an atmospheric-only framework making it more tractable to address in the model development process.

54 ENVIRONMENTAL SCIENCES↗