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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Switchgrass Genomic Diversity, Ploidy, and Evolution: Novel Insights from a Network-Based SNP Discovery Protocol

Switchgrass (Panicum virgatum L.) is a perennial grass that has been designated as an herbaceous model biofuel crop for the United States of America. To facilitate accelerated breeding programs of switchgrass, we developed both an association panel and linkage populations for genome-wide association study (GWAS) and genomic selection (GS). All of the 840 individuals were then genotyped using genotyping by sequencing (GBS), generating 350 GB of sequence in total. As a highly heterozygous polyploid (tetraploid and octoploid) species lacking a reference genome, switchgrass is highly intractable with earlier methodologies of single nucleotide polymorphism (SNP) discovery. To access the genetic diversity of species like switchgrass, we developed a SNP discovery pipeline based on a network approach called the Universal Network-Enabled Analysis Kit (UNEAK). Complexities that hinder single nucleotide polymorphism discovery, such as repeats, paralogs, and sequencing errors, are easily resolved with UNEAK. Here, 1.2 million putative SNPs were discovered in a diverse collection of primarily upland, northern-adapted switchgrass populations. Further analysis of this data set revealed the fundamentally diploid nature of tetraploid switchgrass. Taking advantage of the high conservation of genome structure between switchgrass and foxtail millet (Setaria italica (L.) P. Beauv.), two parent-specific, synteny-based, ultra high-density linkage maps containing a total of 88,217 SNPs were constructed. Also, our results showed clear patterns of isolation-by-distance and isolation-by-ploidy in natural populations of switchgrass. Phylogenetic analysis supported a general south-to-north migration path of switchgrass. In addition, this analysis suggested that upland tetraploid arose from upland octoploid. All together, this study provides unparalleled insights into the diversity, genomic complexity, population structure, phylogeny, phylogeography, ploidy, and evolutionary dynamics of switchgrass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Report on Hydrologic Flow in Low-Permeability Media

We demonstrate that under normal conditions (under which there are no intersections between tunnels/drifts and conductive geological structures, such as faults), the water flow velocity in the damage zone, as a result of non-Darcian flow behavior, is extremely small such that solute transport is dominated by diffusion, rather than advection. We show that unless non-Darcian flow behavior is considered, significant errors can occur in the “measured” relative-permeability values. We propose a hypothesis to consider the temperature impact based on limited test results from the petroleum literature. To consider the bedding effects, we present an empirical relationship between water flux and hydraulic gradient for non-Darcian water flow in anisotropic cases.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗
DOE OSTI2020

The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Probing jet base emission of M87* with the 2021 Event Horizon Telescope observations

We investigate the presence and spatial characteristics of the jet base emission in M87* at 230 GHz, enabled by the significantly enhanced (u,v) coverage in the 2021 Event Horizon Telescope (EHT) observations. The integration of the 12−m Kitt Peak Telescope (USA) and NOEMA (France) stations into the array introduces two critical intermediate-length baselines to SMT (USA) and IRAM 30−m (Spain), providing sensitivity to emission structures at spatial scales of ∼250 μas and ∼2500 μas (∼ 0.02 pc and ∼ 0.02 pc). Without these new baselines, previous EHT observations of the source in 2017 and 2018 lacked the capability to constrain emission on large scales, where a “missing flux” of order ∼1 Jy is expected to reside. To probe these scales, we analyzed closure phases–robust against station-based gain calibration errors–and model the jet base emission using a simple Gaussian component offset from the compact ring emission at spatial separations > 100 μas. Our analysis revealed a Gaussian feature centered at (ΔRA ≈ 320 μ as, ΔDec. ≈ 60 μ as), projected separation of ≈ 5500 AU, with an estimated flux density of only ∼60 mJy, implying that most of the missing flux identified in previous EHT studies had to originate from different, larger scales. Brighter emission at the relevant spatial scales is firmly ruled out, and the data do not favor more complex models. This component aligns with the inferred position of the large-scale jet and is therefore physically consistent with the emission of the jet base. While our findings point to detectable jet base emission at 230 GHz, the limited coverage provided by only two intermediate baselines limits our ability to robustly reconstruct its morphology. Consequently, we treated the recovered Gaussian as an upper limit on the jet base flux density. Future EHT observations with expanded intermediate baseline coverage will be essential to constrain the structure and nature of this component with higher precision.

accretion, accretion disks↗
DOE OSTI2024

Cross Correlating Cosmological Probes for LSST & CMB-S4

The upcoming years will be populated with state-of-the-art Stage-IV cosmological surveys. This paper forecasts the cosmological information we expect to constrain using probes from the Rubin Observatory Legacy Survey of Space and Time (LSST) and CMB-S4. We explore the effectiveness of different large-scale-structure probes, including the power spectra of galaxy weak lensing, galaxy position, Cosmic Microwave Background (CMB) lensing, and their cross-correlations. We use correlated lognormal simulations with the expected redshift distributions, galaxy number densities, and noise levels of the LSST survey. For CMB weak lensing, we use CMB-S4 lensing simulations with anticipated noise levels to obtain the expected error bars of each probe. We investigate the constraining power of the cosmological parameters for the individual probes and their combinations in an idealized scenario. We do not take into account astrophysical and observational parameters such as galaxy bias variations and photometric redshift un- certainties. Overall, we find the auto-correlated probes hold stronger constraints on cosmological parameters than the cross-correlated probes due to kernel differences. However, the cross-correlation of galaxy clustering and CMB lensing is very comparable to the auto-correlation of galaxy clustering with only an 8% stronger constraint in S8. It will be important for future surveys to use these auto and cross probes in combination due to the different astrophysical and systematic effects involved in CMB and late-time galaxy data. When systematics are added to this analysis, the cross probes will serve as a check for systematic biases in individual probes. In addition, we find a significant increase in constraint using all four probes in combination. This can be illustrated by the increase in constraint of S8 by 93.2% comparing galaxy clustering auto-correlation to a combination of all probes. Our study is a first step toward forecasting the high-precision cosmological constraints we expect to obtain using the next generation of large-scale structure probes.

Gibbins, Grace↗
DOE OSTI2015

Elasticity of crystalline molecular explosives

Crystalline molecular explosives are key components of engineered explosive formulations. In precision applications a high degree of consistency and predictability is desired under a range of conditions to a variety of stimuli. Prediction of behaviors from mechanical response and failure to detonation initiation and detonation performance of the material is linked to accurate knowledge of the material structure and first stage of deformation: elasticity. The elastic response of pentaerythritol tetranitrate (PETN), cyclotrimethylene trinitramine (RDX), and cyclotetramethylene tetranitramine (HMX), including aspects of material and measurement variability, and computational methods are described in detail. Experimental determinations of elastic tensors are compared, and an evaluation of sources of error is presented. Furthermore, computed elastic constants are also compared for these materials and for triaminotrinitrobenzene (TATB), for which there are no measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Complete and Accurate Description of Superconductivity of AlB{sub 2}-Type Structures from Phonon Dispersion Calculations

A predictive tool for the design of new, higher-temperature superconductors requires a simple, first-principles technique based on well-established axioms as embodied in density functional theory (DFT), without post-calculation corrections or increased levels of complexity. We show that anomalies in the calculated phonon dispersions of compounds with AlB{sub 2}-type structures are good descriptors of their superconducting transition temperatures. This ab initio methodology has proven robust for descriptions of the superconductivity of MgB{sub 2} and other related AlB{sub 2}-type structures, the different isotopic forms of MgB{sub 2}, a series of substituted MgB{sub 2} compositions with Al and with transition metals, the pressure dependence of the superconductivity of MgB{sub 2}, and various temperature effects. Calculated values are well correlated with experimentally determined values within experimental errors, when sufficiently fine k-grids are used to resolve Fermi surface details. This methodology provides invaluable insight on the mechanisms of superconductivity, can be extended to other crystal systems, and has been used to predict superconducting T{sub c} for new compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Sub-additivity in combining infiltration with mechanical ventilation for single zone buildings

We report that in determining ventilation rates, it is often necessary to combine naturally-driven infiltration, with air flows from mechanical systems. When there are balanced mechanical systems, the solution is simple additivity, because a balanced system does not impact the internal pressure of the space or the air flows through the building envelope. Unbalanced systems, however, change internal pressures and therefore can impact natural ventilation non-linearly in such a way as to make it sub-additive. Several sub-additive approaches are found in the literature, but they are not robust across the full spectrum from tight to leaky buildings and ranges of mechanical ventilation air flow rates. There are two approaches for combining natural infiltration with mechanical ventilation that require different solutions. The forward problem is to find the total air flow when adding mechanical ventilation to natural infiltration, and this application has been investigated in previous studies. The inverse problem finds the required mechanical ventilation in order to meet a total ventilation rate given a known amount of natural infiltration. This article presents the results of millions of hours of simulations of the physically correct solution, which span a broad range of climates, air leakage and structural conditions. This large dataset allows for the comparison with three literature models and the development of new robust sub-additivity models. These improved models are for use with unbalanced systems appropriate for consensus standards and guidelines for both the forward and inverse problem. Finally, they reduce errors to 1% or less and work across the air tightness spectrum.

42 ENGINEERING↗
DOE OSTI2023

Operator inference with roll outs for learning reduced models from scarce and low-quality data

Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, often polluted with noise and affected by measurement errors and other perturbations, which makes learning the dynamics of systems challenging. Here, in this work, we propose to combine data-driven modeling via operator inference with the dynamic training via roll outs of neural ordinary differential equations. Operator inference with roll outs inherits interpretability, scalability, and structure preservation of traditional operator inference while leveraging the dynamic training via roll outs over multiple time steps to increase stability and robustness for learning from low-quality and noisy data. Numerical experiments with data describing shallow water waves and surface quasi-geostrophic dynamics demonstrate that operator inference with roll outs provides predictive models from training trajectories even if data are sampled sparsely in time and polluted with noise of up to 10%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven Whitney forms for structure-preserving control volume analysis

Control volume analysis models physics via the exchange of generalized fluxes between subdomains. Here, we introduce a scientific machine learning framework adopting a partition of unity architecture to identify physically-relevant control volumes, with generalized fluxes between subdomains encoded via Whitney forms. The approach provides a differentiable parameterization of geometry which may be trained in an end-to-end fashion to extract reduced models from full field data while exactly preserving physics. The architecture admits a data-driven finite element exterior calculus allowing discovery of mixed finite element spaces with closed form quadrature rules. An equivalence between Whitney forms and graph networks reveals that the geometric problem of control volume learning is equivalent to an unsupervised graph discovery problem. The framework is developed for manifolds in arbitrary dimension, with examples provided for H(div) problems in $\mathbb{R}$ establishing convergence and structure preservation properties. Finally, we consider a lithium-ion battery problem where we discover a reduced finite element space encoding transport pathways from high-fidelity microstructure resolved simulations. The approach reduces the 5.89M finite element simulation to 136 elements while reproducing pressure to under 0.1% error and preserving conservation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude

Abstract Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Benchmark oxygen-oxygen pair-distribution function of ambient water from x-ray diffraction measurements with a wide Q-range

Four recent x-ray diffraction measurements of ambient liquid water are reviewed here. Each of these measurements represents a significant development of the x-ray diffraction technique applied to the study of liquid water. Sources of uncertainty from statistical noise, Q-range, Compton scattering, and self-scattering are discussed. The oxygen-hydrogen contribution to the measured x-ray scattering pattern was subtracted using literature data to yield an experimental determination, with error bars, of the oxygen-oxygen pair-distribution function, g{sub OO}(r), which essentially describes the distribution of molecular centers. The extended Q-range and low statistical noise of these measurements has significantly reduced truncation effects and related errors in the g{sub OO}(r) functions obtained. From these measurements and error analysis, the position and height of the nearest neighbor maximum in g{sub OO}(r) were found to be 2.80(1) A and 2.57(5) respectively. Numerical data for the coherent differential x-ray scattering cross-section I{sub X}(Q), the oxygen-oxygen structure factor S{sub OO}(Q), and the derived g{sub OO}(r) are provided as benchmarks for calibrating force-fields for water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stochastic modelling of intermittent fluctuations in the scrape-off layer: Correlations, distributions, level crossings, and moment estimation

A stochastic model is presented for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas. The fluctuations in the plasma density are modeled by a super-position of uncorrelated pulses with fixed shape and duration, describing radial motion of blob-like structures. In the case of an exponential pulse shape and exponentially distributed pulse amplitudes, predictions are given for the lowest order moments, probability density function, auto-correlation function, level crossings, and average times for periods spent above and below a given threshold level. Also, the mean squared errors on estimators of sample mean and variance for realizations of the process by finite time series are obtained. These results are discussed in the context of single-point measurements of fluctuations in the scrape-off layer, broad density profiles, and implications for plasma–wall interactions due to the transient transport events in fusion grade plasmas. The results may also have wide applications for modelling fluctuations in other magnetized plasmas such as basic laboratory experiments and ionospheric irregularities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Accurate lattice geometrical parameters and bulk moduli from a semilocal density functional

Accurate prediction of lattice constants is very important in applications of density functional theory. In this work, we assess the efficacy of a non-empirical meta-generalized gradient approximation proposed by Tao and Mo (TM) by calculating the lattice constants as well as bulk moduli of 33 crystalline semiconductors within the TM scheme. We find that the TM functional is able to produce very accurate lattice constants, with a mean absolute error of 0.038 Å, and bulk moduli with a mean absolute error of 3.2 GPa, improving upon commonly-used semilocal density functionals, such as the LSDA, PBE, SOGGA, PBEsol, TPSS, M06L, and SCAN. The high computational efficiency and remarkable agreements with the corresponding experimental values suggest that the TM functional can be a very competitive candidate in electronic structure theory. We attribute the accuracy of the TM functional to be the result of its satisfaction of many exact or nearly-exact conditions related to the exchange-correlation energy and the associated hole, leading to an improved description of the short- as well as intermediate-range van der Waals interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Improved quality of intrafraction kilovoltage images by triggered readout of unexposed frames

Purpose: The gantry-mounted kilovoltage (kV) imager of modern linear accelerators can be used for real-time tumor localization during radiation treatment delivery. However, the kV image quality often suffers from cross-scatter from the megavoltage (MV) treatment beam. This study investigates readout of unexposed kV frames as a means to improve the kV image quality in a series of experiments and a theoretical model of the observed image quality improvements. Methods: A series of fluoroscopic images were acquired of a solid water phantom with an embedded gold marker and an air cavity with and without simultaneous radiation of the phantom with a 6 MV beam delivered perpendicular to the kV beam with 300 and 600 monitor units per minute (MU/min). An in-house built device triggered readout of zero, one, or multiple unexposed frames between the kV exposures. The unexposed frames contained part of the MV scatter, consequently reducing the amount of MV scatter accumulated in the exposed frames. The image quality with and without unexposed frame readout was quantified as the contrast-to-noise ratio (CNR) of the gold marker and air cavity for a range of imaging frequencies from 1 to 15 Hz. To gain more insight into the observed CNR changes, the image lag of the kV imager was measured and used as input in a simple model that describes the CNR with unexposed frame readout in terms of the contrast, kV noise, and MV noise measured without readout of unexposed frames. Results: Without readout of unexposed kV frames, the quality of intratreatment kV images decreased dramatically with reduced kV frequencies due to MV scatter. The gold marker was only visible for imaging frequencies ≥3 Hz at 300 MU/min and ≥5 Hz for 600 MU/min. Visibility of the air cavity required even higher imaging frequencies. Readout of multiple unexposed frames ensured visibility of both structures at all imaging frequencies and a CNR that was independent of the kV frame rate. The image lag was 12.2%, 2.2%, and 0.9% in the first, second, and third frame after an exposure. The CNR model predicted the CNR with triggered image readout with a mean absolute error of 2.0% for the gold marker. Conclusions: A device that triggers readout of unexposed frames during kV fluoroscopy was built and shown to greatly improve the quality of intratreatment kV images. A simple theoretical model successfully described the CNR improvements with the device.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

In-situ X-ray Nanocharacterization of Defect Kinetics in Chalcogenide Solar Cell Materials

For decades the optimization of polycrystalline absorbers has been done using an Edisonian approach, where trial and error and complex design of experiments in large parameter spaces have driven efficiencies to the record values we see today – CIGS at 22.5%, 22.1% for CdTe, 21.3% for high purity multi-crystalline silicon. Appropriate growth parameters are critical to ensure good quality crystals with low concentration of structural defects - low dislocation density and large grain sizes. However, to bridge the gap between the efficiencies today and the fundamental Shockley-Queisser limit for these materials a much more fundamental understanding of the role and interaction between composition, structure, defect density and electrical properties is required. In recent years multiple novel characterization techniques have shown the potential that nanoscale characterization can have in deciphering the composition of grain boundaries in materials like CIGS and CdTe. However, high resolution has come at the cost of small sampling areas and number of specimens, making it extremely difficult to draw conclusions based on the characteristic small sampling sizes. The missing links thus far have been: (1) the lack of statistical meaningfulness of the nanosclae studies and (2) the direct correlation of compositional variations to electrical performance with nanoscale resolution. In this work we present the use of synchrotron-based nano-X-ray fluorescence microscopy (nano-XRF), x-ray absorption nanospectroscopy (nano-XAS) coupled with nano-x-ray beam induced current (nano-XBIC) as ideal tools for investigating elemental, chemical and electrical properties of large areas of solar cell materials at the sub-micron scale with very high sensitivity. We show how the technique can provide statistical valuable information regarding the elemental segregation in CIGS and the direct correlation to current collection. For example, we demonstrate that Cu and Ga (and with that, CGI and GGI) correlate positively, and In negatively with charge collection efficiency for cells with low Ga content, both at grain boundaries and in grain cores. For cells with high Ga content, the charge collection efficiency depends to much lesser extent on the elemental distribution. The objective is three folded: (1) develop an x-ray in-situ microscopy capability to simulate growth and processing conditions, (2) apply it to elucidate performance-governing defect kinetics in chalcogenide solar cell materials, and (3) to study approaches to engineer materials from the nanoscale up. The development of these capabilities will enable experimental characterization to take place under actual processing and operating conditions and it will have impact well beyond the proposed research, enabling future studies on a large variety of materials system where electronic properties depend on underlying structural or chemical inhomogeneities.

14 SOLAR ENERGY↗
DOE OSTI2022

The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0

Hurricanes commonly disturb and damage tropical forests. Hurricane frequency and intensity are predicted to change under the changing climate. The short-term impacts of hurricane disturbances to tropical forests have been widely studied, but the long-term impacts are rarely investigated. Modeling is critical to investigate the potential response of forests to future disturbances, particularly if the nature of the disturbances is changing with climate. Unfortunately, existing models of forest dynamics are not presently able to account for hurricane disturbances. Therefore, we implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model – Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimation (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of –21 %, –12 %, and –15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1 %, –8 %, –2 %, and +9 % differences in the percentages of “Early”, “Mid”, “Late”, and “Palm” PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (<1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

54 ENVIRONMENTAL SCIENCES↗