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Uncertainty Quantification Analysis of Both Experimental and CFD Simulation Data of a Bench-scale Fluidized Bed Gasifier

Adequate assessment of the uncertainties in modeling and simulation is becoming an integral part of the simulation based engineering design. The goal of this study is to demonstrate the application of non-intrusive Bayesian uncertainty quantification (UQ) methodology in multiphase (gas-solid) flows with experimental and simulation data, as part of our research efforts to determine the most suited approach for UQ of a bench scale fluidized bed gasifier. UQ analysis was first performed on the available experimental data. Global sensitivity analysis performed as part of the UQ analysis shows that among the three operating factors, steam to oxygen ratio has the most influence on syngas composition in the bench-scale gasifier experiments. An analysis for forward propagation of uncertainties was performed and results show that an increase in steam to oxygen ratio leads to an increase in H2 mole fraction and a decrease in CO mole fraction. These findings are in agreement with the ANOVA analysis performed in the reference experimental study. Another contribution in addition to the UQ analysis is the optimization-based approach to guide to identify next best set of additional experimental samples, should the possibility arise for additional experiments. Hence, the surrogate models constructed as part of the UQ analysis is employed to improve the information gain and make incremental recommendation, should the possibility to add more experiments arise. In the second step, series of simulations were carried out with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was performed on the numerical results. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier. To improve quality of numerical models used, the effect that uncertainties in reaction models for gasification, char oxidation, carbon monoxide oxidation, and water gas shift will have on the syngas composition at different grid resolution, along with bed temperature were investigated. The global sensitivity analysis showed that among various reaction models employed for water gas shift, gasification, char oxidation, the choice of reaction model for water gas shift has the greatest influence on syngas composition, with gasification reaction model being second. Syngas composition also shows a small sensitivity to temperature of the bed. The hydrodynamic behavior of the bed did not change beyond grid spacing of 18 times the particle diameter. However, the syngas concentration continued to be affected by the grid resolution as low as 9 times the particle diameter. This is due to a better resolution of the phasic interface between the gases and solid that leads to stronger heterogeneous reactions. This report is a compilation of three manuscripts published in peer-reviewed journals for the series of studies mentioned above.

01 COAL, LIGNITE, AND PEAT↗

Development of a dynamic quality assurance testing protocol for multisite clinical trial DCE-CT accreditation

Purpose: Credentialing can have an impact on whether or not a clinical trial produces useful quality data that is comparable between various institutions and scanners. With the recent increase of dynamic contrast enhanced-computed tomography (DCE-CT) usage as a companion biomarker in clinical trials, effective quality assurance, and control methods are required to ensure there is minimal deviation in the results between different scanners and protocols at various institutions. This paper attempts to address this problem by utilizing a dynamic flow imaging phantom to develop and evaluate a DCE-CT quality assurance (QA) protocol.Methods: A previously designed flow phantom, capable of producing predictable and reproducible time concentration curves from contrast injection was fully validated and then utilized to design a DCE-CT QA protocol. The QA protocol involved a set of quantitative metrics including injected and total mass error, as well as goodness of fit comparison to the known truth concentration curves. An additional region of interest (ROI) sensitivity analysis was also developed to provide additional details on intrascanner variability and determine appropriate ROI sizes for quantitative analysis. Both the QA protocol and ROI sensitivity analysis were utilized to test variations in DCE-CT results using different imaging parameters (tube voltage and current) as well as alternate reconstruction methods and imaging techniques. The developed QA protocol and ROI sensitivity analysis was then applied at three institutions that were part of clinical trial involving DCE-CT and results were compared.Results: The inherent specificity of robustness of the phantom was determined through calculation of the total intraday variability and determined to be less than 2.2 ± 1.1% (total calculated output contrast mass error) with a goodness of fit (R{sup 2}) of greater than 0.99 ± 0.0035 (n= 10). The DCE-CT QA protocol was capable of detecting significant deviations from the expected phantom result when scanning at low mAs and low kVp in terms of quantitative metrics (Injected Mass Error 15.4%), goodness of fit (R{sup 2}) of 0.91, and ROI sensitivity (increase in minimum input function ROI radius by 146 ± 86%). These tests also confirmed that the ASIR reconstruction process was beneficial in reducing noise without substantially increasing partial volume effects and that vendor specific modes (e.g., axial shuttle) did not significantly affect the phantom results. The phantom and QA protocol were finally able to quickly (<90 min) and successfully validate the DCE-CT imaging protocol utilized at the three separate institutions of a multicenter clinical trial; thereby enhancing the confidence in the patient data collected.Conclusions: A DCE QA protocol was developed that, in combination with a dynamic multimodality flow phantom, allows the intrascanner variability to be separated from other sources of variability such as the impact of injection protocol and ROI selection. This provides a valuable resource that can be utilized at various clinical trial institutions to test conformance with imaging protocols and accuracy requirements as well as ensure that the scanners are performing as expected for dynamic scans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Application of multidisciplinary optimization methods to the design of a supersonic transport

An optimization design method is discussed. This method is based on integrating existing disciplinary analysis and sensitivity analysis techniques by means of generalized sensitivity equations. A generic design system implementing this method is described. The system is being used to design the configuration and internal structure of a supersonic transport wing for optimum performance. This problem combines the disciplines of linear aerodynamics, structures, and performance. Initial results which include the disciplines of aerodynamics and structures in a conventional minimum weight design under static aeroelastic constraints are presented.

Barthelemy, J.-F. M.↗

Application of multidisciplinary optimization methods to the design of a supersonic transport

A new optimization based design method is discussed. This method is based on integrating existing disciplinary analysis and sensitivity analysis techniques by means of generalized sensitivity equations. A generic design system implementing this method is described. The system is being used to design the configuration and internal structure of a supersonic transport wing for optimum performance. This problem combines the disciplines of linear aerodynamics, structures, and performance. Initial results which include the disciplines of aerodynamics and structures in a conventional minimum weight design under static aeroelastic constraints are presented.

Barthelemy, J.-F. M.↗

Development of a Multiobjective Optimization Procedure for Sonic Boom Minimization

A design optimization procedure for improved sonic boom and aerodynamic performance of high speed aircraft is presented. The multiobjective optimization procedure simultaneously minimizes the sonic boom at a given distance from the aircraft and the drag-to-lift ratio (C(sub D)/C(sub L)) Of the aircraft. Upper and lower bounds are also imposed on the lift coefficient. The Kreisselmeier - Steinhauser function is used for the multiobjective optimization formulation. A discrete semi-analytical aerodynamic sensitivity analysis procedure coupled with an analytical grid sensitivity analysis technique is used for evaluating design sensitivities. The use of the semi-analytical sensitivity analysis techniques results in significant computational savings. The flow equations are solved using a three-dimensional parabolized Navier-Stokes solver. Sonic boom analysis is performed using an extrapolation procedure. A nonlinear programming technique and an approximate analysis procedure are used for the optimization. The optimization procedure developed is applied to the design of two high speed configurations, namely, a doubly swept wing-body configuration and a delta wing-body configuration. For the two sweep case only, minimization of the first peak in the pressure signature is performed first by optimizing only the nose radius and length of the aircraft. Minimization of the second peak in the pressure signature is performed next by optimizing only the wing geometric parameters. Significant improvements are obtained in the sonic boom characteristics and the aerodynamic performance of the wing-body configurations.

Narayan, J. R.↗

Multidisciplinary design optimization using multiobjective formulation techniques

This report addresses the development of a multidisciplinary optimization procedure using an efficient semi-analytical sensitivity analysis technique and multilevel decomposition for the design of aerospace vehicles. A semi-analytical sensitivity analysis procedure is developed for calculating computational grid sensitivities and aerodynamic design sensitivities. Accuracy and efficiency of the sensitivity analysis procedure is established through comparison of the results with those obtained using a finite difference technique. The developed sensitivity analysis technique are then used within a multidisciplinary optimization procedure for designing aerospace vehicles. The optimization problem, with the integration of aerodynamics and structures, is decomposed into two levels. Optimization is performed for improved aerodynamic performance at the first level and improved structural performance at the second level. Aerodynamic analysis is performed by solving the three-dimensional parabolized Navier Stokes equations. A nonlinear programming technique and an approximate analysis procedure are used for optimization. The proceduredeveloped is applied to design the wing of a high speed aircraft. Results obtained show significant improvements in the aircraft aerodynamic and structural performance when compared to a reference or baseline configuration. The use of the semi-analytical sensitivity technique provides significant computational savings.

Chattopadhyay, Aditi↗

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.

Dai, Heng↗

Protons in Head-and-Neck Cancer: Bridging the Gap of Evidence

Purpose: To use Normal Tissue Complication Probability (NTCP) models and comparative planning studies to explore the (cost-)effectiveness of swallowing sparing intensity modulated proton radiotherapy (IMPT) compared with swallowing sparing intensity modulated radiotherapy with photons (IMRT) in head and neck cancer (HNC). Methods and Materials: A Markov model was constructed to examine and compare the costs and quality-adjusted life years (QALYs) of the following strategies: (1) IMPT for all patients; (2) IMRT for all patients; and (3) IMPT if efficient. The assumption of equal survival for IMPT and IMRT in the base case analysis was relaxed in a sensitivity analysis. Results: Intensity modulated proton radiation therapy and IMRT for all patients yielded 6.620 and 6.520 QALYs and cost €50,989 and €41,038, respectively. Intensity modulated proton radiation therapy if efficient yielded 6.563 QALYs and cost €43,650. The incremental cost-effectiveness ratio of IMPT if efficient versus IMRT for all patients was €60,278 per QALY gained. In the sensitivity analysis, IMRT was more effective (0.967 QALYs) and less expensive (€8218) and thus dominated IMPT for all patients. Conclusions: Cost-effectiveness analysis based on normal tissue complication probability models and planning studies proved feasible and informative and enables the analysis of individualized strategies. The increased effectiveness of IMPT does not seem to outweigh the higher costs for all head-and-neck cancer patients. However, when assuming equal survival among both modalities, there seems to be value in identifying those patients for whom IMPT is cost-effective.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Basic research for the geodynamics program

The mathematical models of space very long base interferometry (VLBI) observables suitable for least squares covariance analysis were derived and estimatability problems inherent in the space VLBI system were explored, including a detailed rank defect analysis and sensitivity analysis. An important aim is to carry out a comparative analysis of the mathematical models of the ground-based VLBI and space VLBI observables in order to describe the background in detail. Computer programs were developed in order to check the relations, assess errors, and analyze sensitivity. In order to investigate the estimatability of different geodetic and geodynamic parameters from the space VLBI observables, the mathematical models for time delay and time delay rate observables of space VLBI were analytically derived along with the partial derivatives with respect to the parameters. Rank defect analysis was carried out both by analytical and numerical testing of linear dependencies between the columns of the normal matrix thus formed. Definite conclusions were formed about the rank defects in the system.

Source record↗

Application of Anaerobic Digestion Model No. 1 for simulating anaerobic mesophilic sludge digestion

Highlights: • The behavior of a anaerobic reactor was evaluated through modeling. • Parametric sensitivity analysis was used to select most sensitive of the ADM1. • The results indicate that the ADM1 was able to predict the experimental results. • Organic load rate above of 35 kg/m{sup 3} day affects the performance of the process. - Abstract: Improving anaerobic digestion of sewage sludge by monitoring common indicators such as volatile fatty acids (VFAs), gas composition and pH is a suitable solution for better sludge management. Modeling is an important tool to assess and to predict process performance. The present study focuses on the application of the Anaerobic Digestion Model No. 1 (ADM1) to simulate the dynamic behavior of a reactor fed with sewage sludge under mesophilic conditions. Parametric sensitivity analysis is used to select the most sensitive ADM1 parameters for estimation using a numerical procedure while other parameters are applied without any modification to the original values presented in the ADM1 report. The results indicate that the ADM1 model after parameter estimation was able to predict the experimental results of effluent acetate, propionate, composites and biogas flows and pH with reasonable accuracy. The simulation of the effect of organic shock loading clearly showed that an organic shock loading rate above of 35 kg/m{sup 3} day affects the performance of the reactor. The results demonstrate that simulations can be helpful to support decisions on predicting the anaerobic digestion process of sewage sludge.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental and modeling studies of a biofuel surrogate compound: laminar burning velocities and jet-stirred reactor measurements of anisole

Lignocellulosic biomass is a promising alternative fuel source which can promote energy security, reduce greenhouse gas emissions, and minimize fuel consumption when paired with advanced combustion strategies. Pyrolysis is used to convert lignocellulosic biomass into a complex mixture of phenolic-rich species that can be used in a transportation fuel. Anisole (or methoxybenzene) can be used as a surrogate to represent these phenolic-rich species. Anisole also has attractive properties as a fuel component for use in advanced spark-ignition engines because of its high blending research octane number of 120. Presented in the current work are new measurements of laminar burning velocities, jet-stirred reactor (JSR) speciation of anisole/O 2 /N 2 mixtures, and the development and validation of a detailed chemical kinetic mechanism for anisole. Homogeneous, steady state, fixed gas temperature, perfectly stirred reactor CHEMKIN simulations were used to validate the mechanism against the current JSR measurements and published JSR experiments from CNRS-Nancy. Pyrolysis and oxidation simulations were based on the experimental reactant compositions and thermodynamic state conditions including P = 1 bar and T = 675–1275 K. The oxidation compositions studied in this work span fuel-lean (φ = 0.5), stoichiometric, and fuel rich (φ = 2.0) equivalence ratios. Laminar burning velocities were measured on a heat flux stabilized burner at an unburnt T = 358 K, P = 1 bar and simulated using the CHEMKIN premixed laminar flame speed module. Ignition delay times of anisole were then simulated at conditions relevant to advanced combustion strategies. Current laminar burning velocity measurements and predicted ignition delay times were compared to gasoline components (e.g., n-heptane, iso-octane, and toluene) and gasoline surrogates to highlight differences and similarities in behavior. Reaction path analysis and sensitivity analysis were used to explain the pathways relevant to the current studies. Under pyrolysis and oxidative conditions, unimolecular decomposition of anisole to phenoxy radicals and methyl radicals was found to be important due to the relatively low bond strength between the oxygen and methyl group, ~65 kcal/mol. Finally, reactions of these abundant phenoxy radicals with O 2 were found to be critical to accurately reproduce anisole's reactivity.

10 SYNTHETIC FUELS↗

Review and categorization of existing studies on the estimation of probabilistic failure metrics for Reactor Coolant Pressure Boundary piping and steam generator tubes in Nuclear Power Plants

This article presents the first output of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP), titled Methodology for Assessing Pipe Failure Rates in Advanced Water-Cooled Reactors (AWCRs), launched in 2018. This IAEA CRP is aimed at developing a good-practices document for estimating the probabilistic failure metrics of piping in AWCRs. The reliability of piping that comprise the Reactor Coolant Pressure Boundary (RCPB) is important for maintaining safe and stable operations of Nuclear Power Plants (NPPs) because failure of those piping components could lead to undesirable consequences, such as plant shutdown, costly repair, the occurrence of Loss-of-Coolant Accidents (LOCAs) and, possibly, subsequent core damage or large release events. Probabilistic failure metrics (e.g., failure rate, failure frequency, or failure probability) of RCPB components are the key inputs to the Probabilistic Safety/Risk Assessment (PSA/PRA) and risk management of NPPs. The estimation of probabilistic failure metrics, however, is challenging, especially for AWCRs, due to the lack of operating experience. Therefore, as the first step of the IAEA CRP activities, this paper is developed to provide a literature review of the existing studies (from 2000 to April 2019) on the estimation of probabilistic failure metrics for RCPB piping and Steam Generator (SG) tubes of NPPs and to categorize them based on four criteria: (1) explicitness of incorporation of physical failure mechanisms; (2) types of failure characterization; (3) types of physical models for degradation; and (4) explicitness of consideration of maintenance. The existing studies are also analyzed from the viewpoint of the following key aspects: (i) uncertainty analysis, (ii) sensitivity analysis, (iii) validation strategies, and (iv) the areas of applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Techno-economic analysis and life-cycle greenhouse gas mitigation cost of five routes to bio-jet fuel blendstocks

Decarbonizing the air transportation sector remains one of the most challenging hurdles to mitigating climate change. Lignocellulosic biomass-derived jet fuel blendstocks can contribute to the shift toward renewable, low-carbon energy sources for aircrafts. Producing these renewable jet fuel molecules from biomass requires advanced pathways with the potential for efficient and affordable conversion routes. Here, this paper presents a detailed techno-economic analysis and sensitivity analysis, including estimated minimum selling price (MSP), and life-cycle greenhouse gas (GHG) mitigation costs for five routes to four potential bio-jet fuel molecules – limonane via limonene, limonane via 1,8-cineole, tetrahydromethylcyclopentadiene dimer (RJ-4), bisabolane, and epi-isozizaane. The simulated biorefineries utilize biomass sorghum and an integrated high-gravity ionic liquid-based biomass deconstruction process. We present results reflecting the current state of the technology and potential future scenarios with improved yields. Among the conversion pathways and the fuel molecules evaluated in this study, limonane, bisabolane, and epi-isozizaane could reach an MSP of 0.73–0.91 dollars per L-Jet A (2.75–3.45 dollars per gal-Jet A) in optimized future cases, without a hypothetical lignin-derived co-product. RJ-4 requires a more costly upgrading process and catalysts, resulting in a comparatively higher MSP (1.33 dollars per L-Jet A or 5.04 dollars per gal-jet A). Based on the GHG footprints of each fuel, the minimum achievable carbon mitigation cost relative to conventional Jet-A is 29 dollars per metric ton CO 2e , which is just under double the current cap-and-trade market price in California. In the absence of any policy support, the economics could be improved through high-value uses for lignin. To reach a target selling price of 0.66 dollars per L-Jet A (2.50 dollars per gal), lignin-derived products would need to be sold for at least 1.9 dollars per kg. However, the higher energy density of these bio-based blendstocks offers valuable improvements in aircraft efficiency/range; we find that commercial airlines may be willing to pay a 4–14 cent per L premium for these bio-jet fuels. In conclusion, our results highlight the need for improvements beyond currently-reported yields for the biologically produced intermediates, identification of ideal microbial hosts, selection of metabolic pathways to achieve competitive production costs, and a focus on fuels with attractive properties that increase their value.

09 BIOMASS FUELS↗

The resilience value of residential solar + storage systems in the continental U.S.

Abstract Behind the meter rooftop solar plus storage (PVESS) has the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Whereas the bill reduction and environmental benefits of PVESS are well studied, its monetary resilience benefits are less understood. The increasing trend of power interruptions driven by extreme weather events heightens the need to understand these benefits. This study leverages various publicly available datasets to perform a cost benefit analysis of adding to determine the resilience value of PVESS for a typical single family home in each county in the continental U.S. We find that PVESS is very effective to technically mitigate interruptions across the country. However, the monetary benefits in the base case only cover about 14% of battery costs, with no county exceeding 60%. This is somewhat expected, given that PVESS provide other monetary benefits that are not part of this analysis. Through sensitivities, we find that higher frequency of extreme weather events roughly triples the resilience value of PVESS and that higher values of lost load double the same metric. Our sensitivity analysis shows that the benefit cost ratio of PVESS for customers living in areas with higher-than-average frequency of long duration interruptions and value of lost load is already above one even without considering other value streams. We conclude with recommendations that regulators and utilities could implement to enable customers to calculate and capture the resilience value of PVESS more efficiently.

Baik, Sunhee↗

Inferring small-sample-reactivity worth from oscillation experiment with auto-corrected local flux

To estimate reactivity changes as a function of time from the signal of detectors count rates, one usually uses point kinetic equations. However, when detectors are located inside the core, it is often necessary to compute a correction factor to account for the flux-shape deformation (i.e. the change of detector efficiency that may have been induced by neutron absorbers movements). Various simulation methods have been developed depending on transients observed. They range from the resolution of static equations up to full-time-dependent neutron transport in 3D. However, those methods require high computational-cost calculations of local reaction rates that rely on nuclear data evaluations. Therefore, a 'measured' reactivity is never determined through pure measurements. Taking advantage of the known oscillation movement of a small sample at the center of the MINERVE reactor, the innovative algorithm presented in this paper derives the correction factor needed to get no time drift on reactivity steps. Derived correction factors are in good agreement with those obtained independently with TRIPOLI-4 through sensitivity analysis. Low sensitivity to the sample composition and moderate sensitivity to the detectors position reinforce the reliability of those results. This application paves the way to almost pure nuclear data reactivity measurements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling the Integrated Expansion of the Canadian and U.S. Power Sectors with the Regional Energy Deployment System (ReEDS)

This document describes the development effort for creating a robust representation of the combined capacity expansion of the U.S. and Canadian electric sectors within the NREL ReEDS model. Thereafter, it demonstrates the newly established capability through an illustrative sensitivity analysis. In conducting the sensitivity analysis, we describe the value of an integrated modeling approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WRF-simulated low-level jets over Iowa: characterization and sensitivity studies

Abstract. Output from 6 months of high-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize local low-level jets (LLJs) over Iowa for winter and spring in the contemporary climate. Low-level jets affect rotor plane aerodynamic loading, turbine structural loading and turbine performance, and thus accurate characterization and identification are pertinent. Analyses using a detection algorithm wherein the wind speed above and below the jet maximum must be below 80 % of the jet wind speed within a vertical window of approximately 20–530 m a.g.l. (above ground level) indicate the presence of an LLJ in at least one of the 14 700 4 km×4 km grid cells over Iowa on 98 % of nights. Nocturnal LLJs are most frequently associated with stable stratification and low turbulent kinetic energy (TKE) and hence are more frequent during the winter months. The spatiotemporal mean LLJ maximum (jet core) wind speed is 9.55 m s−1, and the mean height is 182 m. Locations of high LLJ frequency and duration across the state are seasonally varying, with a mean duration of 3.5 h. The highest frequency occurs in the topographically complex northwest of the state in winter and in the flatter northeast of the state in spring. Sensitivity of LLJ characteristics to the (i) LLJ definition and (ii) vertical resolution at which the WRF output is sampled is examined. LLJ definitions commonly used in the literature are considered in the first sensitivity analysis. These sensitivity analyses indicate that LLJ characteristics are highly variable with definition. Use of different definitions identifies both different frequencies of LLJs and different LLJ events. Further, when the model output is down-sampled to lower vertical resolution, the mean jet core wind speed height decreases, but spatial distributions of regions of high frequency and duration are conserved. Implementation of a polynomial interpolation to extrapolate down-sampled output to full-resolution results in reduced sensitivity of LLJ characteristics to down-sampling.

17 WIND ENERGY↗