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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of unfolding methods using RooFitUnfold

In this study we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interface to these algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. In this paper we exploit this common interface of RooFitUnfold to compare the performance of unfolding with the Richardson–Lucy, Iterative Dynamically Stabilized, Tikhonov, Gaussian Process, bin-by-bin and inversion methods on several example problems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Unified Wind-Wave Growth and Spectrum Functions for All Water Depths: Field Observations and Model Results

Abstract Wind-wave development is governed by the fetch- or duration-limited growth principle that is expressed as a pair of similarity functions relating the dimensionless elevation variance (wave energy) and spectral peak frequency to fetch or duration. Combining the pair of similarity functions, the fetch or duration variable can be removed to form a dimensionless function of elevation variance and spectral peak frequency, which is interpreted as the wave energy evolution with wave age. The relationship is initially developed for quasi-neural stability and quasi-steady wind forcing conditions. Further analyses show that the same fetch, duration, and wave-age similarity functions are applicable to unsteady wind forcing conditions, including rapidly accelerating and decelerating mountain gap wind episodes and tropical cyclone (TC) wind fields. Here it is shown that with the dimensionless frequency converted to dimensionless wavenumber using the surface wave dispersion relationship, the same similarity function is applicable in all water depths. Field data collected in shallow to deep waters and mild to TC wind conditions and synthetic data generated by spectrum model computations are assembled to illustrate the applicability. For the simulation work, the finite-depth wind-wave spectrum model and its shoaling function are formulated for variable spectral slopes. Given wind speed, wave age, and water depth, the measured and spectrum-computed significant wave heights and the associated growth parameters are in good agreement in forcing conditions from mild to TC winds and in all depths from deep ocean to shallow lake. Significance Statement This paper presents a growth function and spectrum model to describe wind-wave development in all water depths. Their applicability covers a wide range of wind forcing conditions including steady, accelerating, decelerating, and tropical cyclone events. Support for the unified spectrum model and growth function is presented with field observations and numerical computations.

Hwang, Paul A.↗
DOE OSTI2017

Tracing the Cosmological Evolution of Stars and Cold Gas with CMB Spectral Surveys

A full account of galaxy evolution in the context of ΛCDM cosmology requires measurements of the average star-formation rate (SFR) and cold gas abundance across cosmic time. Emission from the CO ladder traces cold gas, and [C ii] fine structure emission at 158 μm traces the SFR. Intensity mapping surveys the cumulative surface brightness of emitting lines as a function of redshift, rather than individual galaxies. CMB spectral distortion instruments are sensitive to both the mean and anisotropy of the intensity of redshifted CO and [C ii] emission. Large-scale anisotropy is proportional to the product of the mean surface brightness and the line luminosity-weighted bias. The bias provides a connection between galaxy evolution and its cosmological context, and is a unique asset of intensity mapping. Cross-correlation with galaxy redshift surveys allows unambiguous measurements of redshifted line brightness despite residual continuum contamination and interlopers. Measurement of line brightness through cross-correlation also evades cosmic variance and suggests new observation strategies. Galactic foreground emission is ≈10{sup 3} times larger than the expected signals, and this places stringent requirements on instrument calibration and stability. Under a range of assumptions, a linear combination of bands cleans continuum contamination sufficiently that residuals produce a modest penalty over the instrumental noise. For PIXIE, the 2σ sensitivity to CO and [C ii] emission scales from ≈5×10{sup −2} kJy sr{sup −1} at low redshift to ≈2 kJy sr{sup −1} by reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Investigating wind turbine impacts on near-wake flow using profiling Lidar data and large-eddy simulations with an actuator disk model

In this study, wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σ u , likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σ u , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.

17 WIND ENERGY↗
DOE OSTI2020

Long-range Doppler lidar measurements of wind turbine wakes and their interaction with turbulent atmospheric boundary-layer flow at Perdigao 2017

As part of the Perdigão 2017 campaign, vertical RHI (range-height indicator) scans with long-range pulsed Doppler wind lidars were performed aligned with the main wind direction and a wind turbine (WT) located on a mountain ridge. The measurements are used to not only retrieve flow velocities, but also their variance and - by using the turbulent broadening of the Doppler spectrum - also turbulent kinetic energy (TKE) dissipation rate. The study shows that turbulence in the WT wake is dependent on the turbulence of the inflow, but also on atmospheric stability. In stable atmospheric conditions, wakes could be analyzed up to five rotor diameters downstream (D) and showed the maximum turbulence in the wake at 2-3 D, whereas in unstable conditions, the maximum was found at 2 D and the wake could not be detected further than 3 D. A clear dependency of wake turbulence enhancement on inflow turbulence intensity is found, which levels out to no further enhancement at turbulence intensities of 30%.

17 WIND ENERGY↗
DOE OSTI2017

Effects of Fuel Laminar Flame Speed Compared to Engine Tumble Ratio, Ignition Energy, and Injection Strategy on Lean and EGR Dilute Spark Ignition Combustion

Previously we show that fuels with higher laminar flame speed also have increased tolerance to EGR dilution. In this work, the effects of fuel laminar flame speed on both lean and EGR dilute spark ignition combustion stability were examined. Fuels blends of pure components (iso-octane, n-heptane, toluene, ethanol, and methanol) were derived at two levels of laminar flame speed. Each fuel blend was tested in a single-cylinder spark-ignition engine under both lean-out and EGR dilution sweeps until the coefficient of variance of indicated mean effective pressure increased above thresholds of 3% and 5%. The relative importance of fuel laminar flame speed to changes to engine design parameters (spark ignition energy, tumble ratio, and port vs. direct injection) was also assessed. Our results showed that fuel laminar flame speed can have as big an effect on lean or EGR dilute engine operation as engine design parameters, with the largest effects seen during EGR dilute operation and when changes were made to cylinder charge motion.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Long‐Term Observations of Turbulence Vertical Velocity Spectra in a Convective Mixed Layer: Dependence on Land‐Surface Forcing in the U.S. Southern Great Plains

Doppler lidar vertical velocity retrievals were analyzed for the scale and structure of mixed-layer turbulence over a 7-year period, on fair-weather warm season days (442 cases) in the U.S. Southern Great Plains. Based on the hypothesized influence of land-surface forcing and updraft size on convective boundary layer clouds, a spectral analysis was performed to quantify effects of surface forcing (surface buoyancy flux, friction velocity, and evaporative fraction) on turbulence scale. Significant (order-of-magnitude) variations in spectral density were found in the energy-production subrange and mesoscale regimes. Integral scale decreased with increasing buoyancy flux (and Monin-Obukhov stability parameter), while spectral density in the energy-production subrange increased, implying a transition to buoyancy-driven cellular structures with narrower updrafts. The influence of stability parameter was limited to the neutral to convective transition, and could not explain the wide variation in spectral density in the mesoscale regime. However, high friction velocity (u* > 0.5 m s –1 ) was associated with larger integral scale (updraft width), and a greater portion of spectral density in the mesoscale regime. Lidar profiles and radar reflectivity for individual cases revealed evidence of roll and wave-like structures contributing to mesoscale variability on high friction velocity days, suggesting shear instabilities on days with wetter land surface conditions and smaller buoyancy flux. The role of friction velocity emphasizes the multivariate nature of surface influences on turbulence, and implies that variance-based turbulence closures may not be adequate for capturing effects of surface forcing on updraft size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Uncertainty quantification of graph convolution neural network models of evolving processes

The application of neural network models to scientific machine learning tasks has proliferated in recent years. In particular, neural networks have proved to be adept at modeling processes with spatial–temporal complexity. Nevertheless, these highly parameterized models have garnered skepticism in their ability to produce outputs with quantified error bounds over the regimes of interest. Hence there is a need to find uncertainty quantification methods that are suitable for neural networks. In this work we present comparisons of the parametric uncertainty quantification of neural networks modeling complex spatial–temporal processes with Hamiltonian Monte Carlo and Stein variational gradient descent and its projected variant. Specifically we apply these methods to graph convolutional neural network models of evolving systems modeled with recurrent neural network and neural ordinary differential equations architectures. We show that Stein variational inference is a viable alternative to Monte Carlo methods with some clear advantages for complex neural network models. For our exemplars, Stein variational interference gave similar pushed forward uncertainty profiles through time compared to Hamiltonian Monte Carlo, albeit with generally more generous variance. As a result, projected Stein variational gradient descent also produced similar uncertainty profiles to the non-projected counterpart, but large reductions in the active weight space were confounded by the stability of the neural network predictions and the convoluted likelihood landscape.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Detection and Production of Methane Hydrate

This project seeks to understand regional differences in gas hydrate systems from the perspective of as an energy resource, geohazard, and long-term climate influence. Specifically, the effort will: (1) collect data and conceptual models that targets causes of gas hydrate variance, (2) construct numerical models that explain and predict regional-scale gas hydrate differences in 2-dimensions with minimal 'free parameters', (3) simulate hydrocarbon production from various gas hydrate systems to establish promising resource characteristics, (4) perturb different gas hydrate systems to assess potential impacts of hot fluids on seafloor stability and well stability, and (5) develop geophysical approaches that enable remote quantification of gas hydrate heterogeneities so that they can be characterized with minimal costly drilling. Our integrated program takes advantage of the fact that we have a close working team comprised of experts in distinct disciplines. The expected outcomes of this project are improved exploration and production technology for production of natural gas from methane hydrates and improved safety through understanding of seafloor and well bore stability in the presence of hydrates. The scope of this project was to more fully characterize, understand, and appreciate fundamental differences in the amount and distribution of gas hydrate and how this would affect the production potential of a hydrate accumulation in the marine environment. The effort combines existing information from locations in the ocean that are dominated by low permeability sediments with small amounts of high permeability sediments, one permafrost location where extensive hydrates exist in reservoir quality rocks and other locations deemed by mutual agreement of DOE and Rice to be appropriate. The initial ocean locations were Blake Ridge, Hydrate Ridge, Peru Margin and GOM. The permafrost location was Mallik. Although the ultimate goal of the project was to understand processes that control production potential of hydrates in marine settings, Mallik was included because of the extensive data collected in a producible hydrate accumulation. To date, such a location had not been studied in the oceanic environment. The project worked closely with ongoing projects (e.g. GOM JIP and offshore India) that are actively investigating potentially economic hydrate accumulations in marine settings. The overall approach was fivefold: (1) collect key data concerning hydrocarbon fluxes which is currently missing at all locations to be included in the study, (2) use this and existing data to build numerical models that can explain gas hydrate variance at all four locations, (3) simulate how natural gas could be produced from each location with different production strategies, (4) collect new sediment property data at these locations that are required for constraining fluxes, production simulations and assessing sediment stability, and (5) develop a method for remotely quantifying heterogeneities in gas hydrate and free gas distributions. While we generally restricted our efforts to the locations where key parameters can be measured or constrained, our ultimate aim was to make our efforts universally applicable to any hydrate accumulation.

03 NATURAL GAS↗
DOE OSTI2017

Ultrasound-assisted facile synthesis of a new tantalum(V) metal-organic framework nanostructure: Design, characterization, systematic study, and CO{sub 2} adsorption performance

This work presents a fast route for the preparation of a new Ta(V) metal-organic framework nanostructure with high surface area, significant porosity, and small size distribution. X-ray diffraction (XRD), scanning electron microscopy (SEM), Transition electron microscopy (TEM), energy dispersive spectrometer (EDS), thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FTIR), CHNS/O elemental analyser, and Brunauer-Emmett-Teller (BET) surface area analysis were applied to characterize the synthesized product. Moreover, the influences of ultrasonic irradiation including temperature, time, and power on different features of the final products were systematically studied using 2{sup k-1} factorial design experiments, and the response surface optimization was used for determining the best welding parameter combination. The results obtained from analyses of variances showed that ultrasonic parameters affected the size distribution, thermal behaviour, and surface area of Ta-MOF samples. Based on response surface methodology, Ta-MOF could be obtained with mean diameter of 55 nm, thermal stability of 228 °C, and high surface area of 2100 m{sup 2}/g. The results revealed that the synthesized products could be utilized in various applications such as a novel candidate for CO{sub 2} adsorption. - Graphical abstract: A facile route was used for fabrication of a new metal -organic framework based on tantalum nanostructures that have high surface area, considerable porosity, homogenous morphology, and small size distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Orbital degree of freedom in high entropy oxides

The spin, charge, and lattice degrees of freedom and their interplay in high entropy oxides were intensively investigated in recent years. However, how the orbital degree of freedom is affected by the extreme disorder in high entropy oxides has not been studied. In this work, using perovskite structured RVO 3 as a materials playground, we report how the disorder arising from mixing different rare earth ions at the rare earth site affects the orbital ordering of V 3+ t 2g -electrons. Since each member of RVO 3 (R = rare earth and Y) crystallizes into the same orthorhombic Pbnm structure, the configurational entropy should not be critical for the stability of (R 1,..., Rn)VO 3 . The spin and orbital ordering was studied by measuring magnetic properties and specific heat of single crystals. Rather than the number and type of rare earth ions, the average and variance of ionic radius are the key factors determining the spin and orbital order in (R 1,..., Rn)VO 3 . When the size variance is small, the average ionic radius takes precedence in dictating spin and orbital order. Increasing size variance suppresses the G-type orbital order (G-OO) and C-type antiferromagnetic order (C-AF) but favors the C-OO/G-AF state and spin-orbital entanglement. In conclusion, these findings suggest that the extreme disorder introduced by mixing multiple rare earth ions in high entropy perovskites might be employed to preserve the orbital degree of freedom to near the magnetic order, which is necessary for the electronic driven orbital ordering in a Kugel-Khomskii compound.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Role of bond coat processing methods on the durability of plasma sprayed thermal barrier systems

Metallic alloy bond coats are used as an interlayer to promote adhesion of ceramic Thermal Barrier Coatings (TBCs) to the superalloy substrates. These bond coats can be applied through a variety of processing means such as Air Plasma Spray (APS), High-Velocity Oxy Fuel spray (HVOF), and Vacuum Plasma Spray (VPS). While widely adopted in the industry, some uncertainties remain as to the specific microstructural attributes which are influenced by the processing routes and their implications on durability. This paper seeks to elucidate these subtleties between bond coat deposition processing routes through an integrated study of processing to connect to furnace cycle durability on a single bond coat chemistry of NiCoCrAlYHfSi. A standard porous APS TBC top coating based on yttria stabilized zirconia (7YSZ) was consistently applied on these distinct bond coats and tested for durability in cyclic furnace testing at 1100 °C. The results point to substantial differences in durability which are not readily explained only by the variances in coating roughness. Detailed assessment of deposited bond coat properties (modulus, thermal expansion, chemistry) provided some explanation relative to durability. Here, the results suggest a complex interplay among roughness, compliance, aluminum diffusion pathway, and thermal expansion mismatch. Photo-stimulated luminescence piezospectroscopy (PLPS) provided additional insights enabling a comprehensive assessment of processing-performance linkages.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Determination of Thermal Expansion, Defect Formation Energy, and Defect-Induced Strain of α-U Via ab Initio Molecular Dynamics

Uranium (U) is often alloyed with molybdenum (Mo) or zirconium (Zr) in order to stabilize its high-temperature body-centered cubic phase for use in nuclear reactors. However, in all metallic fuel forms, the α phase of U remains in some fraction. This phase decomposition due to temperature or compositional variance can play an outsized role on fuel performance and microstructural evolution. Relatively little is known about fundamental point defect properties in α -U at non-zero temperatures, from either computational or experimental studies. This work performs the first thorough evaluation of the α phase of U via ab initio molecular dynamics (AIMD). A number of thermophysical properties are calculated as a function of temperature, including equilibrium lattice parameters, thermal expansion, and heat capacity. These results indicate a two-region behavior, with the transition at 400 K. The thermal expansion/contraction in the a / b direction occurs rapidly from 100 up to 400 K, after which a more linear and gradual change in the lattice constant takes place. The volumetric expansion matches experiments quantitatively, but the individual lattice constant expansion only matches experiments qualitatively. Point defect formation energies and induced lattice strains are also determined as a function of temperature, providing insight on defect populations and the fundamentals of irradiation growth in α -U. Interstitials induce significantly more strain than vacancies, and the nature of that strain is highly dependent on the individual lattice directions. The direction of point defect-induced lattice strain is contrary to the irradiation growth behavior of α -U. This work shows that isolated point defects cannot be the primary driving force responsible for the significant irradiation-induced growth of α -U observed experimentally.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Growth performance and stability of hybrid poplar clones in simultaneous tests on six sites

Growth, stability, and genotype x environment (GxE) interaction were investigated for 69 clones after five years at six sites in Minnesota. Fifty-three clones were Populus deltoides x Populus nigra (DxN) crosses, nine were P. deltoides x P. maximowiczi, ten other crosses. Most clones were previously screened for growth and disease resistance in Minnesota. Five-year diameter (DBH) and basal area (BA) at 1.38 m averaged 93.5 mm and 72.11 cm 2 , respectively, over the six sites. DBH site means varied from 109.0 to 79.4 mm. The fastest-growing clone BA was 64% and 49% larger than the mean of the two commercial standards and the mean of the population, respectively. Site, clone, and clone x site effects were highly significant in the ANOVA. The variance component for clone was over twice that of clone x site (GxE), indicating a relatively small reduction in genetic gain due to GxE. Clonal rank did not change between sites. GxE interaction was dominated by relative performance differences of clones on the different sites. Twenty-six percent of clones were stable (little change in growth between sites), 74% unstable. Stability coefficients of the unstable clones varied over a 99% range, indicating the population had high and variable phenotypic plasticity. Only 15% of clones were both stable and fast growing. Seven putatively superior clones, all DxN, were selected for future testing under near-commercial conditions. The results, if representative of other inter-specific Populus populations, indicate it will be difficult, and probably impractical, to reduce GxE with standard quantitative genetics methods in hybrid poplar tree improvement programs without sacrificing productivity gains.

09 BIOMASS FUELS↗
DOE OSTI2015

Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica . The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2014

Fracture toughness of plasma-sprayed thermal barrier ceramics: Influence of processing, microstructure, and thermal aging

Fracture toughness has become one of the dominant design parameters that dictates the selection of materials and their microstructure to obtain durable thermal barrier coatings (TBCs). Much progress has been made in characterizing the fracture toughness of relevant TBC compositions in bulk form, and it has become apparent that this property is significantly affected by process-induced microstructural defects. In this investigation, a systematic study of the influence of coating microstructure on the fracture toughness of atmospheric plasma sprayed (APS) TBCs has been carried out. Yttria partially stabilized zirconia (YSZ) coatings were fabricated under different spray process conditions inducing different levels of porosity and interfacial defects. Fracture toughness was measured on free standing coatings in as-processed and thermally aged conditions using the double torsion technique. Results indicate significant variance in fracture toughness among coatings with different microstructures including changes induced by thermal aging. Comparative studies were also conducted on an alternative TBC composition, Gd 2 Zr 2 O 7 (GDZ), which as anticipated shows significantly lower fracture toughness compared to YSZ. Furthermore, the results from these studies not only point towards a need for process and microstructure optimization for enhanced TBC performance but also a framework for establishing performance metrics for promising new TBC compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structural complexity and primary production resistance are coupled in a temperate forest

The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.

lidar—remote sensing↗