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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Synthesizing 3D Surfaces from Parameterized Strip Charts

We believe 3D information visualization has the power to unlock new levels of productivity in the monitoring and control of complex processes. Our goal is to provide visual methods to allow for rapid human insight into systems consisting of thousands to millions of parameters. We explore this hypothesis in two complex domains: NASA program management and NASA International Space Station (ISS) spacecraft computer operations. We seek to extend a common form of visualization called the strip chart from 2D to 3D. A strip chart can display the time series progression of a parameter and allows for trends and events to be identified. Strip charts can be overlayed when multiple parameters need to visualized in order to correlate their events. When many parameters are involved, the direct overlaying of strip charts can become confusing and may not fully utilize the graphing area to convey the relationships between the parameters. We provide a solution to this problem by generating 3D surfaces from parameterized strip charts. The 3D surface utilizes significantly more screen area to illustrate the differences in the parameters and the overlayed strip charts, and it can rapidly be scanned by humans to gain insight. The selection of the third dimension must be a parallel or parameterized homogenous resource in the target domain, defined using a finite, ordered, enumerated type, and not a heterogeneous type. We demonstrate our concepts with examples from the NASA program management domain (assessing the state of many plans) and the computers of the ISS (assessing the state of many computers). We identify 2D strip charts in each domain and show how to construct the corresponding 3D surfaces. The user can navigate the surface, zooming in on regions of interest, setting a mark and drilling down to source documents from which the data points have been derived. We close by discussing design issues, related work, and implementation challenges.

Robinson, Peter I.↗
DOE OSTI2017

Room temperature mechanical properties of electron beam welded zircaloy-4 sheet

Room temperature mechanical properties of electron beam welded and plain Zircaloy-4 sheet (1.6mm thick) have been measured and compared. Various welding parameters were utilized to join sheet material. Electron beam welded specimens and as-received sheet specimens show comparable mechanical properties. Zr-4 sheet displays anisotropy; tensile properties measured for transverse display higher elastic modulus, yield strength, reduction of area and slightly lower ductility than for the longitudinal (rolling direction). Higher welding power increases the alloy’s hardness, elastic modulus and yield strength, with a corresponding decrease in tensile strength and ductility. The hardness measured at weld is comparable to the parent metal hardness. Hardness at heat-affected-zone is slightly higher. Electron microscopic examination shows distinct microstructure morphology and grain size at the weld zone, HAZ and parent metal. A correlation between welding parameters, mechanical properties and microstructural features was established for electron beam welded Zircaloy-4 sheet material.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Cosmic shear results from the deep lens survey. II. Full cosmological parameter constraints from tomography

We present a tomographic cosmic shear study from the Deep Lens Survey (DLS), which, providing a limiting magnitude r{sub lim}∼27 (5σ), is designed as a precursor Large Synoptic Survey Telescope (LSST) survey with an emphasis on depth. Using five tomographic redshift bins, we study their auto- and cross-correlations to constrain cosmological parameters. We use a luminosity-dependent nonlinear model to account for the astrophysical systematics originating from intrinsic alignments of galaxy shapes. We find that the cosmological leverage of the DLS is among the highest among existing >10 deg{sup 2} cosmic shear surveys. Combining the DLS tomography with the 9 yr results of the Wilkinson Microwave Anisotropy Probe (WMAP9) gives Ω{sub m}=0.293{sub −0.014}{sup +0.012}, σ{sub 8}=0.833{sub −0.018}{sup +0.011}, H{sub 0}=68.6{sub −1.2}{sup +1.4} km s{sup −1} Mpc{sup −1}, and Ω{sub b}=0.0475±0.0012 for ΛCDM, reducing the uncertainties of the WMAP9-only constraints by ∼50%. When we do not assume flatness for ΛCDM, we obtain the curvature constraint Ω{sub k}=−0.010{sub −0.015}{sup +0.013} from the DLS+WMAP9 combination, which, however, is not well constrained when WMAP9 is used alone. The dark energy equation-of-state parameter w is tightly constrained when baryonic acoustic oscillation (BAO) data are added, yielding w=−1.02{sub −0.09}{sup +0.10} with the DLS+WMAP9+BAO joint probe. The addition of supernova constraints further tightens the parameter to w=−1.03±0.03. Our joint constraints are fully consistent with the final Planck results and also with the predictions of a ΛCDM universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Overexpression of DBC1, correlated with poor prognosis, is a potential therapeutic target for hepatocellular carcinoma

Highlights: • DBC1 was upregulated in HCC tissues and cell lines. • Overexpression of DBC1 was correlated with clinicopathological parameters in HCC. • Overexpression of DBC1 predicts poor disease-free survival (DFS) and overall survival (OS) in HCC. • Knockdown of DBC1 inhibits HCC cell lines proliferation. Deleted in Breast Cancer 1 (DBC1) is a regulatory protein involved in cell metabolism and cancer progression. Nevertheless, the expression and prognostic values of DBC1 in hepatocellular carcinoma (HCC) are still not well understood. The following study investigated the clinical significance and biological function of DBC1 in HCC. Briefly, overexpression of DBC1 at transcriptional and translational levels in human HCC tissues compared to adjacent normal tissues was observed using quantitative real-time polymerase chain reaction (qRT-PCR), western blot (WB) and immunohistochemistry (IHC) approach. Furthermore, upregulated DBC1 was significantly correlated with tumor size (p = 0.005), N stage (p = 0.016), M stage (p = 0.011), tumor differentiation (p in vitro. To conclude, these findings demonstrated that DBC1 was essential in tumorigenesis and proliferation. Moreover, it was identified as a potential therapeutic target for HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Influence of Galvanizing Parameters on the Structural Development of Zn-Al-Based Coatings

The evolution of some layers’ characteristics, deposited by galvanization, was monitored according to the technological parameters of the process. Two types of alloys from the Zn-Al and Zn-Al-Ti-B systems were used for deposition. The structure of the deposited layers was analyzed by optical and electron microscopy. The chemical composition, phases and compounds in the structures were identified. The mechanical properties of the structural constituents of the layers were determined by nanoindentation. These techniques highlighted the typical non-uniformities in terms of composition and properties in the layers, mainly due to the diffusion and distribution of iron from the steel substrate in the deposited layers. The evaluation of iron diffusion in the deposited layer was done by differential thermal analysis. The values of the critical temperatures (melting temperature, eutectic temperature and solidification temperature) were correlated with the parameters used during deposition. It was observed that the structure of the coatings is layered, with a specific order from the steel substrate to the edge. In these layers, the constituents are mixtures of soft solid solutions of Al in Zn (η and β) and hard intermetallic compounds. Moreover, increasing the immersion time in the galvanizing bath and the bath temperature leads to an increase in iron diffusion in the coating layer, which contributes to lower coating thickness, thus reducing its durability in operation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Generation of lognormal synthetic Lyman-α forest spectra for P 1 D analysis

The one-dimensional flux power spectrum (P 1 D ) of the Lyman-α forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include the amplitude and shape of the matter power spectrum, the thermal history of the IGM, the sum of neutrino masses, and potential small-scale fluctuations due to the nature of dark matter. However, P 1 D is also highly sensitive to observational and instrumental systematics, making accurate synthetic spectra essential for validating analyses and quantifying these effects, especially in high-volume surveys like the Dark Energy Spectroscopic Instrument (DESI). We present an efficient lognormal mock framework for generating one-dimensional Lyman-α forest spectra tailored for P 1 D analysis. Our method captures the redshift evolution of the mean transmitted flux and the scale-dependent shape and amplitude of the one-dimensional flux power spectrum by tuning Gaussian field correlations and transformation parameters. Across the DESI Early Data Release (EDR) redshift range (2.0 ≤ z ≤ 3.8), and a wide range of scales (10 -4 s km -1 ≤ k ≤ 1.0 s km -1 ), our mocks recover the mean flux evolution with redshift to sub-percent accuracy, and the P 1 D at the percent level. Additionally, we discuss potential extensions of this framework, such as the incorporation of astrophysical contaminants, continuum uncertainties, and instrumental effects. Such improvements would expand its utility in ongoing and upcoming surveys and enable a broader range of validation efforts and systematics studies for P 1 D inference and precision cosmology.

Lyman alpha forest↗
DOE OSTI2017

Monte Carlo sampling and correlation coefficients of critical experiments

We study the influence of calculation parameters on Monte-Carlo generated correlation coefficients of k{sub eff} values for a data set of critical experiments. The correlation coefficients can be used e.g. to reduce conservatism in bias estimations, but generally must be treated correctly if a data set includes correlations. We find that the actual value of the correlation coefficient for a given data set depends on the number of samples and the ratio of the sampling uncertainty to the Monte-Carlo uncertainty of the individual k{sub eff} calculation. We also discuss that the number of input parameters of the model to calculate the k{sub eff} values do not necessarily impact the convergence of the correlation coefficient with increasing sample number. However, we explain how varying the aforementioned parameters lead to different converged results for the correlation coefficients. The conclusion is that a correlation coefficient should not be discussed isolated but with the underlying uncertainties of both, the k{sub eff} estimation and the Monte Carlo sampling approach. The underlying modelling approach of the experimental data has to be described in detail. This should include a sensitivity analysis of the impact of input parameters on the k{sub eff} uncertainty with respect to the modelling approach.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Revealing Variable Dependences in Hexagonal Boron Nitride Synthesis via Machine Learning

Wafer-scale monolayer two-dimensional (2D) materials have been realized by epitaxial chemical vapor deposition (CVD) in recent years. To scale up the synthesis of 2D materials, a systematic analysis of how the growth dynamics depend on the growth parameters is essential to unravel its mechanisms. However, the studies of CVD-grown 2D materials mostly adopted the control variate method and considered each parameter as an independent variable, which is not comprehensive for 2D materials growth optimization. Herein, we synthesized a representative 2D material, monolayer hexagonal boron nitride (hBN), on single-crystalline Cu (111) by epitaxial chemical vapor deposition and varied the growth parameters to regulate the hBN domain sizes. Furthermore, we explored the correlation between two growth parameters and provided the growth windows for large flake sizes by the Gaussian process. Here, this new analysis approach based on machine learning provides a more comprehensive understanding of the growth mechanism for 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structure-Activity Relationships of Hydrothermally Aged Titania-Supported Vanadium-Tungsten Oxide Catalysts for SCR of NOx Emissions with NH3

Supported V2O5-WO3/TiO2 materials employed as selective catalytic reduction (SCR) catalysts for NOx emission control from power plants. Fresh SCR catalysts usually receive exposure to harsh treatments in industry to accelerate catalyst activation (calcination in air at 650oC) and catalyst aging (hydrothermal aging at 650oC) in a way that represents various points in the catalyst/product lifetime. The present study investigates the catalyst structural and chemical changes occurring during such harsh treatments. Three series of supported V2O5-WO3/TiO2 catalysts were prepared by incipient-wetness impregnation of aqueous ammonium metavanadate and metatungstate precursors. The catalysts were subsequently dried and calcined at 550oC in O2, 650oC in O2, and hydrothermal conditions (10% O2, 8% H2O, 7% CO2 and 75% N2) at 650oC. The resulting catalysts were physically characterized by numerous techniques (in situ Raman, in situ IR, in situ High Field-High Spinning solid-state 51V MAS NMR, in situ EPR, XRD, BET surface area and ICP) and chemically probed with adsorbed ammonia, SCR-TPSR, and the SCR reaction. The surface WOx sites on the TiO2 support behave as a textural promoter that stabilizes the TiO2 (anatase) phase from sintering and transforming to the undesirable crystalline TiO2 (rutile) phase that can lead to formation of a Ti1-xVxO2 (rutile) solid solution with reduced V4+ cations (~7-15%). The surface VOx sites are mostly oligomerized as surface V+5Ox sites (~50-85% oligomers) and the extent of oligomerization tends to increase with surface WOx coverage and calcination temperature. A major difference between the calcined and hydrothermally treated catalysts was the low concentration of surface NH3* species on Lewis acid sites for the hydrothermally treated catalysts, yet the SCR activity was almost comparable for both catalysts. This finding suggests that surface NH4+*, primarily associated with the surface VOx sites, are able to efficiently perform the SCR reaction. Given that multiple catalyst parameters were simultaneously varying during these treatments, it was difficult to correlate the SCR activity with any single catalyst parameter. A correlation, however, was found between the SCR TOF/activity and the sum of the surface NH3* and NH4+* species, which is dominated by the surface NH4+* species.

SCR, NO, NH3, catalyst, V2O5, WO3, TiO2, promotion↗
DOE OSTI2021

Electron correlations in the cubic paramagnetic perovskite Sr ( V , Mn ) O 3 : Results from fully self-consistent self-energy embedding calculations

In this study, we use the thermodynamically consistent and conserving self-energy embedding theory (SEET) to study the spectra of the prototypical undistorted cubic perovskites SrVO 3 and SrMnO 3 . In the strongly correlated metallic SrVO 3 we find that the usual attribution of the satellite peaks at –1.8 eV to Hund or Hubbard physics in the t 2 g orbitals is inconsistent with our calculations. In the strongly correlated insulator SrMnO 3 we recover insulating behavior due to a feedback effect between the strongly correlated orbitals and the weakly correlated environment. Our calculation shows a systematic convergence of spectral features as the space of strongly correlated orbitals is enlarged, paving the way to a systematic parameter-free study of correlated perovskites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Thermal Transport and Fracture Behavior of Sintered Fuel Pellets: Experimental Validation of NEAMS Tool MARMOT

The project targets at experimental validation of NEAMS tool MARMOT for predicting thermal transport and fuel fracture. The key components of the project include: (1) sintering UO 2 samples with well-controlled microstructures (grain size, pore, fission bubble, porosity and pore distribution either in intra- or inter-granular pores); (2) thermal conductivity measurements of these wellcharacterized polycrystalline samples; (3) indentation testing of sintered UO 2 with various grain size, porosity and stoichiometry to obtain fracture and crack propagation mechanisms (inter or intragranular fracture); and (4) validation and uncertainty quantification of the MARMOT thermal transport and fracture models. The high quality experimental data will be used to validate the predictions of MARMOT for thermal transport and fracture, using average data and local microstructure information. In this work, UO 2 fuels with controlled microstructure (grain size, pore size/structure and fuel chemistry) were successfully prepared by high energy ball milling of the hyper-stoichiometric UO 2+x powders purchased commercially, and consolidated by spark plasma sintering. Dense nano-sized UO 2 fuel pellets with controlled stoichiometry were sintered by SPS. The effects of different SPS sintering parameters on the pore size and distribution were investigated, and the correlation among the SPS parameter – microstructure control – stoichiometry/defect structure was established. To further control the pore structure and fuel chemistry, systematic thermal annealing of the sintered fuels with the controlled pore structure was performed in a reduced. The controlled microstructure and fuel chemistry enable the investigation of the separate effects of pore structure and fuel chemistry on thermal transport behavior. The mechanical properties of the sintered UO 2 fuels were tested by nanoindentation and microindentation testing at different temperatures. The fracture behavior of the sintered fuels as functions of grain structure and temperature was investigated. Nanocrystalline UO 2 display higher hardness than microcrystalline counterpart, consistent with the Hall-Petch strengthening mechanism. Greater Young’s modulus and fracture toughness are also identified for the nanocrystalline UO 2 , and hardness and Young’s modulus decrease with temperature, suggesting better ductility of oxide fuels at greater temperature at small length scale. Hyper-stoichiometric UO 2 specimen displays higher hardness and fracture toughness than stoichiometric UO 2 , due to the impediment of the crack propagation by the oxygen interstitial atoms. These results are useful in understanding the mechanical properties of the high burn-up structure (HBS) formed in nuclear fuels during reactor operation, and also provide critical experimental data as the input for the development and validation of the MARMOT fracture model of nuclear fuels. The thermal properties of the sintered UO 2 fuel pellets with controlled grain structure, fuel chemistry and pore structures are measured by laser flash and the impact of the microstructure characteristics on the thermal transport properties is elucidated. Through a close collaboration with the MARMOT team at Idaho National Laboratory, the thermal properties of the sintered oxide fuel pellets with controlled microstructures are measured experimentally, and modeled using the developed MARMOT thermal transport models for a joint effort of demonstrating high spatial resolution measurements at the microstructural level on as-fabricated nuclear fuels and materials and obtain critical experimental data for model validation and properties predictions. In this work, we also conducted sensitivity analysis and uncertainty quantification (UQ) on a mesoscale simulation that has been applied to understand the effective thermal conductivity of UO 2 reactor fuel using the MARMOT tool. We also conduced UQ on mechanistic macroscale models that have been developed to predict the effective thermal conductivity. The most sensitive parameter is the thermal conductivity of bulk UO 2 for the thermal conductivity models. In the future, the predicted simulation distributions need to be compared to experimental data for validation of the models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1976

Evaluation of water samples collected during LANDSAT-1 overpasses of the lower Chesapeake Bay area

Water samples were collected on 18 days when the LANDSAT-1 satellite was passing over the lower Chesapeake Bay area. A correlation between the various water parameters has been performed for the more than 300 surface samples. Six days were sufficiently cloudless that MSS digital tapes were useful for analysis. Correlation of radiance values with the water parameters revealed a low correlation for chlorophyll and good correlations with particles and sediment. The relation of total particles to sediment was linear, but varied from day to day.

Bowker, D. E.↗
DOE OSTI2019

Future prospects for constraining nuclear matter parameters with gravitational waves

The gravitational wave emission from the merging binary neutron star system GW170817 arrived full of tidal information which can be used to probe the fundamental ultradense nuclear physics residing in these stars. In previous work, we used two-dimensional correlations between nuclear matter parameters and tidal deformabilities of neutron stars applying specifically to GW170817 to derive constraints on the former. Here, we extend this analysis by finding similar correlations for varying chirp masses, the dominant determining factor in the frequency evolution of the inspiral, such that one can apply the same method to future detections. We estimate how accurately one can measure nuclear parameters with future gravitational wave interferometers and show how such measurements can be improved by combining multiple events. We find that bounds on the nuclear parameters with future observations can improve from the current one with GW170817 only by ~30% due to the existence of systematic errors caused mainly by the remaining uncertainty in the equation of state near and just above the nuclear saturation density. As a result, we show that such systematic errors can be reduced by considering multidimensional correlations among nuclear parameters and tidal deformabilities with various neutron star masses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

Development of base pressure similarity parameters for application to space shuttle launch vehicle power-on aerodynamic testing

A base pressure data correlation study was conducted to define exhaust plume similarity parameters for use in Space Shuttle power-on launch vehicle aerodynamic test programs. Data correlations were performed for single bodies having, respectively, single and triple nozzle configurations and for a triple body configuration with single nozzles on each of the outside bodies. Base pressure similarity parameters were found to differ for the single nozzle and triple nozzle configurations. However, the correlation parameter for each was found to be a strong function of the nozzle exit momentum. Results of the data base evaluation are presented indicating an assessment of all data points. Analytical/experimental data comparisons were made for nozzle calibrations and correction factors derived, where indicated for use in nozzle exit plane data calculations.

Sulyma, P. R.↗
DOE OSTI2026

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗
DOE OSTI2022

Enhanced Multi-Dimensional Inversion Through Target-Specific Inversion Parameter Bounds With an Application to Crosswell Electromagnetic for Sequestration Monitoring

In geophysical inversions, lower and upper model parameter bounds are a means of solution stabilization. Further, constraints that intend to let only geologically plausible inverse solutions pass are amenable to lower and upper bounds. Reliable prior information is paramount to construct such bound constraints. It is common practice to narrow and widen bound intervals for regions of, respectively, more and less certain prior information. Contrary to this practice, we experiment with widened bound intervals in zones that are poorly resolved by a given survey configuration but where prior information would suggest structural anomalies of interest. The purpose of enlarged parameter bounds that correlate spatially with predefined targets is to let the inversion explore a larger solution space, thus increasing the potential to resolve otherwise hidden anomalies. Application of the method is based on a carbon-sequestration baseline (pre-injection) crosswell electromagnetic (EM) field survey at the Containment and Monitoring Institute Field Research Station (Alberta, Canada), where impeded measurements led to generally reduced sensitivities for the interwell region. Synthetic-data proofs of concept use augmented bounds designed to boost the resolution of artificial plume targets, indicating an enhanced illumination compared to constant bounds. Comparative field data inversions with spatially variable bounds constructed from prior resistivity and velocity information highlight non-horizontal baseline structures.

3-D electrical resistivity imaging↗
DOE OSTI2016

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

Huang, Maoyi↗