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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analytic Sensitivity Coefficients for General Multigroup Infinite Medium k-Eigenvalue Problems

This work presents a general set of equations that can be used to rapidly generate new benchmarks to verify nuclear data sensitivity calculations. The general multigroup infinite medium k-eigenvalue neutron transport equation is used to derive analytic expressions for the infinite medium k-eigenvalue, the scalar neutron flux and adjoint flux, and the sensitivity of k∞ to perturbations in the multigroup nuclear data of a single species, isotropic and elastic scattering, material. The multigroup nuclear data for U-235 and U-238 is presented along with their corresponding k-eigenvalues, forward flux, adjoint flux, and sensitivity profiles, which include the sensitivity of k∞ to the total, fission, capture, and scattering macroscopic cross sections as well as to the group-to-group scattering cross section matrix, group-wise fission neutron production, and the unconstrained and constrained fission neutron energy distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Surface Doping Boosts Triplet Generation Yield in Perovskite-Sensitized Upconversion

Triplet–triplet annihilation-based photon upconversion (TTA-UC) can efficiently generate higher energy photons at low relative fluences. Bulk metal halide perovskites have offered promise in efficiently sensitizing molecular triplet states in the solid state, necessary for the integration of TTA-UC into device-based applications. Recent work focused on TTA-UC from a rubrene triplet annihilator sensitized by perovskite thin films has established relatively efficient charge extraction from the perovskite, forming the triplet exciton in rubrene. Yet, the specifics underpinning charge transfer at the perovskite/rubrene interface are not fully elucidated. Here, to improve device performance and study the properties governing charge transfer at the interface, various organic solvents are explored to treat the perovskite surface. Scanning tunneling microscopy and spectroscopy show a difference in the electronic band structure, where both n- and p-type terminated perovskite surfaces are observed depending on the solvent used. Supported by optical spectroscopy, the impact of the perovskite electronic structure is monitored, indicating that n-type perovskite sensitizers feature higher TTA-UC efficiencies due to favorable band bending resulting in efficient hole-mediated triplet formation. Overall, the tuning of the electronic structure of the perovskite sensitizer through solvent treatment is shown to be a key force in tuning the mechanism of efficient triplet generation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Explicitly determined sea ice emissivity and emission temperature over the Arctic for surface–sensitive microwave channels

Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface-sensitive microwave-sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e., snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically-driven snow/ice growth model. Here we conducted 1-D Var experiments in order to examine whether this approach can help to use the surface-sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface-sensitive microwave channels can be used in the 1-D Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface-sensitive microwave-sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature.

1-D Var retrieval↗
DOE OSTI2024

Benchmarking of X‐Ray Fluorescence Microscopy with Ion Beam Implanted Samples Showing Detection Sensitivity of Hundreds of Atoms

Abstract Single impurities in insulators are now often used for quantum sensors and single photon sources, while nanoscale semiconductor doping features are being constructed for electrical contacts in quantum technology devices, implying that new methods for sensitive, non‐destructive imaging of single‐ or few‐atom structures are needed. X‐ray fluorescence (XRF) can provide nanoscale imaging with chemical specificity, and features comprising as few as 100 000 atoms have been detected without any need for specialized or destructive sample preparation. Presently, the ultimate limits of sensitivity of XRF are unknown – here, gallium dopants in silicon are investigated using a high brilliance, synchrotron source collimated to a small spot. It is demonstrated that with a single‐pixel integration time of 1 s, the sensitivity is sufficient to identify a single isolated feature of only 3000 Ga impurities (a mass of just 350 zg). With increased integration (25 s), 650 impurities can be detected. The results are quantified using a calibration sample consisting of precisely controlled numbers of implanted atoms in nanometer‐sized structures. The results show that such features can now be mapped quantitatively when calibration samples are used, and suggest that, in the near future, planned upgrades to XRF facilities might achieve single‐atom sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sensitivity of the NEXT experiment to Xe-124 double electron capture

Double electron capture by proton-rich nuclei is a second-order nuclear process analogous to double beta decay. Despite their similarities, the decay signature is quite different, potentially providing a new channel to measure the hypothesized neutrinoless mode of these decays. The Standard-Model-allowed two-neutrino double electron capture (2$\nu$EC EC) has been predicted for a number of isotopes, but only observed in 78 Kr, 130 Ba and, recently, 124 Xe. The sensitivity to this decay establishes a benchmark for the ultimate experimental goal, namely the potential to discover also the lepton-number-violating neutrinoless version of this process, 0$\nu$EC EC. Here we report on the current sensitivity of the NEXT-White detector to 124 Xe 2$\nu$EC EC and on the extrapolation to NEXT-100. Using simulated data for the 2$\nu$EC EC signal and real data from NEXT-White operated with 124 Xe-depleted gas as background, we define an optimal event selection that maximizes the NEXT-White sensitivity. We estimate that, for NEXT-100 operated with xenon gas isotopically enriched with 1 kg of 124 Xe and for a 5-year run, a sensitivity to the 2$\nu$EC EC half-life of 6 × 10 22 y (at 90% confidence level) or better can be reached.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Sensitivity Analysis of an Electrospray Dehumidification System

Electrically enhanced condensation achieved by an electrospray system can enhance dehumidification in HVAC applications if successfully scaled up. The first step towards scale-up is identifying critical design and operating parameters that significantly impact dehumidification for the electrospray system. Sensitivity analysis is one approach for identifying critical parameters. This paper presents a methodology that can efficiently perform quantitative sensitivity analysis on a computationally expensive high fidelity simulation model, which is a computational fluid dynamics (CFD) model of the electrospray system. The methodology employs surrogate modeling and Sobol sensitivity analysis. We estimate the main and total effect Sobol sensitivity indices of four operating parameters of the electrospray system. The results reveal that the most important parameter is the size of the sprayed droplets, followed by the volumetric flow rate of the bulk air and injected water in the system. The water injection velocity of the spray was found to have little to no impact on dehumidification.

Young, David↗
DOE OSTI2020

Assessing the sensitivity of land-atmosphere coupling strength to boundary and surface layer parameters in the WRF model over Amazon

Modeling tools can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations, but subject to uncertainties associated with parameters in model physical parameterizations. Different sensitivity analysis (SA) approaches may lead to different conclusions about the underlying sensitivities. In this study, we quantify simulation uncertainties related to parameter perturbations, and use different approaches to conduct parameter SA on the WRF model pertaining to L-A coupling strength for simulations over the Amazon region. A total of twenty parameters from the Yonsei University (YSU) planetary boundary layer (PBL) and the revised MM5 surface layer (SL) schemes were selected in this analysis. Three different SA methods, the Morris One-at-A-Time (MOAT) method, the Multivariate Adaptive Regression Splines (MARS) method, and the Sobol’ method, were employed to analyze seven WRF-simulated variables and five L-A coupling metrics. Results show that 1) parameter perturbations cause large simulation uncertainties which are comparable to those in the observations; 2) three different SA methods give consistent L-A coupling strength outcomes; 3) six out of the twenty parameters contribute 80%–95% of the total variance in the metrics analyzed, and first-order effects dominate over interaction effects; 4) the twelve variables/metrics of interest show similar sensitivity patterns to the selected parameters, which is consistent across all the methods used. Physical mechanisms for how the sensitive parameters act in determining the L-A coupling strength and associated variables also are illustrated. Our results will help quantifying L-A coupling strength and establishing a basis for parameter calibration over the Amazon region.

Wang, Chen↗
DOE OSTI2021

An experimental and kinetic modeling study of NO x sensitization on methane autoignition and oxidation

An experimental and kinetic modeling study of the influence of NO x (i.e. NO 2 , NO and N 2 O) addition on the ignition behavior of methane/‘air’ mixtures is performed. Ignition delay time measurements are taken in a rapid compression machine (RCM) and in a shock tube (ST) at temperatures and pressures ranging from 900–1500 K and 1.5–3.0 MPa, respectively for equivalence ratios of 0.5–2.0 in ‘air’. The conditions chosen are relevant to spark ignition and homogeneous charge compression ignition engine operating conditions where exhaust gas recirculation can potentially add NO x to the premixed charge. The RCM measurements show that the addition of 200 ppm NO 2 to the stoichiometric CH 4 /oxidizer mixture results in a factor of three increase in reactivity compared to the baseline case without NOx for temperatures in the range 600–1000 K. However, adding up to 1000 ppm N 2 O does not show any appreciable effect on the measurements. The promoting effect of NO 2 was found to increase with temperature in the range 950–1150 K, while the sensitization effect decreases at higher pressures. The experimental results measured are simulated using NUIGMech1.2 comprising an updated NO x sub-chemistry in this work. A kinetic analysis indicates that the competition between the reactions ĊH 3 + NO 2 ↔ CH 3 Ȯ + NO and ĊH 3 + NO 2 (+M) ↔ CH 3 NO 2 (+M), the former being a propagation reaction and the latter being a termination reaction governs NO x sensitization on CH 4 ignition. Recent calculations by Matsugi and Shiina (A. Matsugi, H. Shiina, J. Phys. Chem. A. 121 (2017) 4218–4224) for the nitromethane formation reaction CH 3 + NO 2 (+M) ↔ CH 3 NO 2 (+M), together with the recently calculated rate constants for HONO/HNO 2 reactions significantly improve ignition delay time predictions in the temperature range 600–1000 K. Furthermore, the experiments with NO addition reveal a non-monotonous sensitization impact on CH 4 ignition at lower temperatures with NO initially acting as an inhibitor at low NO concentrations and then as a promoter as NO concentrations increase in the mixture. This non-monotonous trend is attributed to the role of the chain-termination reaction ĊH 3 + NO 2 (+M) ↔ CH 3 NO 2 (+M) and the impact of NO on the transition to the chain-branching steps CH 2 O + HȮ 2 ↔ HĊO + H 2 O 2 , H 2 O 2 (+M) ↔ ȮH + ȮH (+M), HĊO ↔ CO + Ḣ followed by CO + O 2 ↔ CO 2 + Ö and Ḣ + O 2 ↔ Ö + ȮH. NUIGMech1.2 is systematically validated against the new ignition delay measurements taken here together with species measurements and high temperature ignition delay time data available in the literature for CH 4 /oxidizer mixtures diluted with NO 2 /N 2 O/NO and is observed to accurately capture the sensitization trends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chemical kinetic interactions and sensitivity analyses for 2-ethylhexyl nitrate-doped PRF91 using a reduced mechanism

A numerical and experimental investigation about the chemical kinetic interactions between 2-ethylhexylnitrate (EHN) and PRF91 was performed in this study. Rapid compression machine experiments were conducted to investigate the effect of EHN on the autoignition reactivity of the fuel, and a reduced chemical kinetic mechanism was developed including an EHN sub-model. Experiments showed that the ignition delay decreases as the fuel is doped with EHN, but the effect of the doping level of EHN on the ignition is highly non-linear. Moreover, experiments showed that the EHN effectiveness is lowest during the transition between the low-temperature regime and the negative temperature coefficient (NTC) regime, and it rapidly increases as the temperature increases. Both detailed and (developed) reduced mechanisms were validated against the experimental results, allowing a more in-depth EHN-fuel chemistry study. Additionally, ignition delay sensitivity and EHN effectiveness sensitivity analyses were performed with the reduced mechanism to identify the reactions that control the interaction between EHN and the fuel. As the result, EHN thermal decomposition is only relevant for very low temperatures. The chemistry of EHN-doped fuel is more sensitive to intermediate temperature reactions than that of straight fuel, especially at lower temperatures, due to the effect of EHN on the NTC behavior of the fuel. Finally, the chemistry of EHN-doped fuel is very sensitive to NO 2 -to-NO reactions, especially at high temperatures, because these reactions transform the NO 2 generated by EHN into NO, which is a very effective fuel reactivity enhancer.

2-ethylhexyl nitrate↗
DOE OSTI2022

Electrochemically decorated gold nanoparticles on CVD graphene ChemFET sensor for the highly sensitive detection of As(III)

Here, in this paper, we report a novel reusable receptor-free chemically sensitive field-effect transistor (ChemFET) sensor for the sensitive detection of As(III) using electrochemical doping of Au nanoparticles (AuNPs)-chemical vapour deposition (CVD) graphene (Gr) sensing film (AuNPs-Gr). The sensor consists of a single-gap gold electrode and a single layer of CVD graphene as a conducting/sensing channel decorated with a thin layer of electrochemically deposited AuNPs to catalyze the electroreduction of As(III) ions onto the sensing channel. A new detection strategy was proposed by measuring the resistance change rate of the AuNPs-Gr sensing channel modified between the source electrode and drain electrode, wherein the resistance change was caused by the electrochemical doping of As(0). The results indicated that the electrochemical doping of As(0) onto the sensing channel led to an increase in resistance through the doping interaction among As(0), AuNPs and graphene, enabling the proposed sensor to have an extraordinary detection performance with a high sensitivity. Moreover, the proposed sensor can be recycled by removing the As(0) deposited on the sensing film with the aid of a simple electrochemical oxidization process. Additionally, the mechanism of the sensing strategy based on the electrochemical n-doping of As(0) into the AuNPs-Gr sensing film was investigated using a top liquid gate electrode. The As(III) concentration detected by the AuNPs-Gr ChemFET sensor was as low as 0.001 μg/L, demonstrating that such sensors with a compatible sensing strategy can be used to detect As(III) with high sensitivity, easy fabrication, fast response and can be recycled.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Perovskite-Sensitized Upconversion under Operando Conditions

Perovskite-sensitized upconversion (UC) has resulted in near-infrared-to-visible UC at solar-relevant fluxes. However, the successful implementation of UC devices into operating solar cells will result in exposure to similar environmental stressors as for the commercial photovoltaics (PVs), mainly elevated temperatures, and continuous irradiation. In this article, we investigated the effects of these two stressors, heat and light, on the triplet generation process at the perovskite/rubrene interface. Following exposure to both stressors, local discrepancies across the upconversion device were discovered. Here, the first region showed changes to the morphology, and no detectable upconverted emission was observed. Through the combination of optical microscopy and spectroscopy, crystallization of the organic semiconductor layer, degradation of dibenzotetraphenylperiflanthene, and concurrent degradation of the perovskite sensitizer were found. These effects culminate in a reduction in both triplet generation and triplet–triplet annihilation. In the second region, no changes to the morphology were present and visible UC emission was observed following exposure to both stressors. To probe the triplet sensitization process at elevated temperatures, transient absorption spectroscopy was performed. The presence of the excited spin-triplet state of rubrene at 60 °C highlighted successful triplet generation even at elevated temperatures. This work emphasizes the challenges and continued potential for the integration of perovskite-sensitized UC into commercial photovoltaic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Excited Carrier Dynamics in a Dye-Sensitized Niobate Nanosheet Photocatalyst for Visible-Light Hydrogen Evolution

Dye-sensitized photocatalysts that consist of a light-absorbing dye and a wide gap oxide semiconductor have been studied extensively as components of solar energy conversion systems. Although surface modification by a metal and/or metal oxide has a significant impact on the photocatalytic efficiency, the mechanism by which these modifications increase the activity has not been fully understood. Here a dye-sensitized H 2 evolution system was constructed by using Pt-intercalated HCa 2 Nb 3 O 10 nanosheets, Ru(II) complex photosensitizers ([Ru(4,4’-(CH 3 ) 2- bpy) 2 (4,4’-(PO 3 H 2 ) 2- bpy)] 2+ and [Ru(4,4’-(CH 3 ) 2- bpy) 2 (4,4’-(CH 2 PO 3 H 2 ) 2- bpy)] 2+ , abbreviated as RuP 2+ and RuCP 2+ ; bpy = 2,2'-bipyridine), and amorphous Al 2 O 3 as building blocks. In the presence of iodide as the electron donor, the H 2 evolution rate from Pt/HCa 2 Nb 3 O 10 nanosheets sensitized by RuP 2+ was increased by modification of the nanosheets with Al 2 O 3 . On the other hand, Al 2 O 3 had a negative impact on the H 2 evolution rate when RuCP 2+ was employed. These hybrid materials were studied by transient diffuse reflectance spectroscopy and steady-state emission spectroscopy. A detailed analysis of the transient absorption profiles of the adsorbed Ru(II) complexes revealed that there are at least three states of the complexes on the nanosheet surface. The transient bleaching of the ground state absorbance had different lifetime components ranging from a few μs to several hundred μs, which mainly reflect back electron transfer rates from HCa 2 Nb 3 O 10 to the oxidized Ru(II) complexes. Here, the Al 2 O 3 modifier could inhibit not only the back electron transfer events but also electron injection from the excited state photosensitizer. Interestingly, the negative effect of Al 2 O 3 on the electron injection rate was negligible in the case of RuP 2+ , which also had a higher H 2 evolution rate. This work highlights that suppressing fast back electron transfer from Pt/HCa 2 Nb 3 O 10 to the oxidized Ru(II) complex, which occurs on a time scale of a few μs, and maximizing the electron injection efficiency are both necessary for improving dye-sensitized H 2 evolution.

14 SOLAR ENERGY↗
DOE OSTI2025

An Integral Activity-Based Protein Profiling Method for Higher Throughput Determination of Protein Target Sensitivity to Small Molecules

Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses small molecule probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across diverse biological samples, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern (CoC), a wide range of concentrations may be needed, particularly for chemicals that lack potency or toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity determination for different organophosphate (OP) pesticides as model toxicants. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving samples at discrete paraoxon concentrations to pooled samples across that same concentration range. We then expanded our approach to compare protein target sensitivities toward two additional OP pesticides, chlorpyrifos oxon and malaoxon. The results showed that differences in integral intensities for the pooled competition sample can be used to evaluate the relative sensitivity of specific proteins without increasing the overall number of samples. For 8 CoC concentrations of interest, this strategy reduced the number of TMT plexes and the corresponding number of LC–MS/MS analyses 3-fold. In conclusion, we envision the integral ABPP (IABPP) method will provide a means to screen diverse chemicals more rapidly to identify both high and low sensitivity protein targets.

activity-based probes↗
DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗
DOE OSTI2021

Sensitivity of Grass Fires Burning in Marginal Conditions to Atmospheric Turbulence

Abstract Atmospheric forcing and interactions between the fire and atmosphere are primary drivers of wildland fire behavior. The atmosphere is known to be a chaotic system that, although deterministic, is very sensitive to small perturbations to initial conditions. We assume that as a result of the tight coupling between fire and atmosphere; wildland fire behavior, in turn, should also be sensitive to perturbations in atmospheric initial conditions. Observations suggest that low intensity prescribed fire, in particular, is susceptible to small perturbations in the wind field, which can significantly alter fire spread. Here, we employ a computational fluid dynamics model of coupled fire‐atmosphere interactions to answer the question: How sensitive is fire behavior to small variations in atmospheric turbulence? We perform ensemble simulations of fires in homogenous grass fuels. The only difference between ensemble members is the state of the turbulent atmosphere provided to the model throughout the simulation. The atmospheric state is a function of the initial conditions applied at the start of the simulation and boundary conditions applied throughout the simulation. We find a wide range of outcomes, with area burned ranging from 2,212 to 11,236 m 2 (>400% change), driven primarily by sensitivity to initial conditions, with nonnegligible contributions from boundary condition variability during the initial 30 s of simulation. Our results highlight the need for ensemble simulations, especially when considering fire behavior in marginal burning conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Understanding the eco-geomorphologic feedback of coastal marsh under sea level rise: vegetation dynamic representations, processes interaction, and parametric sensitivity

A growing number of coastal eco-geomorphologic modeling studies have been conducted to understand coastal marsh evolution under sea-level rise (SLR). Although these models quantify marsh topographic change as a function of sedimentation and erosion, their representations of vegetation dynamics that control organic sedimentation differ. How vegetation dynamic schemes contribute to simulation outcomes is not well quantified. Additionally, the sensitivity of modeling outcomes to parameter selection in the available formulations has not been rigorously tested to date, especially under the influence of an accelerating SLR. In this paper, we used a coastal eco-geomorphologic model with different vegetation dynamic schemes to investigate the eco-geomorphologic feedbacks of coastal marshes and parametric sensitivity under SLR scenarios. We found that marsh platform relief increased with sea level rise rate. The simulations with different vegetation schemes exhibited different spatial-temporal variations in elevation and biomass. The nonlinear Spartina scheme presented the most resilient prediction with generally the highest marsh accretion and vegetation biomass, and the least elevation relief under SLR. But the linear Spartina scheme predicts the lowest unvegetated-vegetated ratio. We also found that vegetation-related parameters and sediment diffusivity, which were not well measured or discussed in previous studies, were identified as some of the most critical parameters. Additionally, the model sensitivity to vegetation-related parameters increased with SLR rates. The identified most sensitive parameters may inform how to appropriately choose modeling representations of key processes and parameters for different coastal marsh landscapes under SLR, and demonstrate the importance of future field measurements of these key parameters.

58 GEOSCIENCES↗