Empirical Correction Model Research Articles

Improved building facade segmentation through digital twin-enabled RandLA-Net with empirical intensity correction model

The Architectural Engineering and Construction (AEC) industry can benefit from accurate building facade segmentation, which can provide valuable insights into building maintenance, urban planning, and security efforts. Light Detection and Ranging (LiDAR) sensors are effective in recognizing building facade components from (three-dimensional) 3D point clouds by registering 3D spatial coordinates and radiometric information, which reveal the spectral property of a scanned surface. Although the radiometric information (i.e., intensity feature) can be used for segmentation, its accuracy may be reduced by factors such as scanning geometry and external factors that affect the object’s radiometric information. To address this issue, this study proposes a robust and automated method for segmenting building facade components using LiDAR point cloud data and an empirical-based intensity correction model to ensure proper segmentation. The proposed method employs RandLA-Net, a deep learning model capable of effectively processing large-scale point cloud data, to classify building facade components based on their spatial features combined with corrected intensity features. By incorporating the proposed method into a digital twin, it is possible to perform accurate building facade segmentation and generate valuable insights into the building’s physical condition, energy efficiency, and aesthetic value in real-time. The effectiveness of the proposed method was experimentally validated using a school building facade, which demonstrated significant improvements in the recognition of facade components and highlighted the potential of digital twin-enabled building facade segmentation for the AEC industry.

An Empirical Correction Model for Remote Sensing Data of Global Horizontal Irradiance in High-Cloudiness-Index Locations

Facing the energy transition, solar energy, whether thermal or electric, is currently one of the most viable alternatives, due to its technological maturity and its ease of operation and maintenance compared to other renewable energies. However, before its implementation, it is necessary to assess its potential. Remote sensing represents one of the low-cost solutions for solar energy assessment. Nevertheless, cloud cover is a main problem when validating the data. This study identifies satellite GHI profiles that cannot be used in energy production simulation. The validation is performed using parametric and non-parametric statistical tests. From the profile identified as invalid for simulation purposes, a site-adaptation methodology is proposed based on statistical learning using the machine learning algorithms “Best subset selection” and “Forward Stepwise Selection”. Linear and non-linear heuristic models are also proposed. The final AS7 model is selected through RMSE, MBE and adjusted R2 indicators and is valid for any sky condition. The results show an increase in R2 from 0.607 to 0.876.

Evaluation of the Moso Bamboo Age Determination Based on Laser Echo Intensity

Determination of bamboo age is an important task for bamboo forest management and bamboo utilization. However, the bamboo age is usually manually determined in the field, which is time-consuming and labor-intensive. Due to the ability to generate very high-density point clouds, terrestrial laser scanning (TLS) has been applied in forestry to acquire forest parameters. This study evaluated the potential of using the laser echo intensity data generated by TLS technology to determine the Moso bamboo age represented by “du.” The intensity data were first corrected for the distance and incidence angle effects using an intensity correction method that constructed an empirical correction model by fitting piecewise polynomials to the intensity data collected based on a reference target. Then the models expressing the relationship between intensity and bamboo culm section number were constructed for different bamboo du by fitting polynomials to the intensity data of individual bamboo culms through least-squares adjustment. For a bamboo plant whose age is determined, the bamboo du could be determined based on the constructed intensity-culm section models. The proposed bamboo age determination method was tested at a site in a managed Moso bamboo forest in Lin’an District, Hangzhou City, Zhejiang Province, China. From the test site, 56 and 120 bamboo plants with known bamboo ages were selected to construct the intensity-culm section models and to validate the bamboo age determination method, respectively. The bamboo age determination accuracies for each bamboo du were all above 90%. The result indicates a great potential for automatic determination of bamboo age in practice using TLS technology.

Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring.

This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors’ sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.

Empirical quenching correction in radiochromic silicone-based three-dimensional dosimetry of spot-scanning proton therapy.

Background and purposeThree-dimensional dosimetry of proton therapy (PT) with chemical dosimeters is challenged by signal quenching, which is a lower dose-response in regions with high ionization density due to high linear-energy-transfer (LET) and dose-rate. This study aimed to assess the viability of an empirical correction model for 3D radiochromic silicone-based dosimeters irradiated with spot-scanning PT, by parametrizing its LET and dose-rate dependency.Materials and methodsTen cylindrical radiochromic dosimeters (Ø50 and Ø75 mm) were produced in-house, and irradiated with different spot-scanning proton beam configurations and machine-set dose rates ranging from 56 to 145 Gy/min. Beams with incident energies of 75, 95 and 120 MeV, a spread-out Bragg peak and a plan optimized to an irregular target volume were included. Five of the dosimeters, irradiated with 120 MeV beams, were used to estimate the quenching correction factors. Monte Carlo simulations were used to obtain dose and dose-averaged-LET (LETd) maps. Additionally, a local dose-rate map was estimated, using the simulated dose maps and the machine-set dose-rate information retrieved from the irradiation log-files. Finally, the correction factor was estimated as a function of LETd and local dose-rate and tested on the different fields.ResultsGamma-pass-rates of the corrected measurements were >94% using a 3%-3 mm gamma analysis and >88% using 2%-2 mm, with a dose deviation of <5.6 ± 1.8%. Larger dosimeters showed a 20% systematic increase in dose-response, but the same quenching in signal when compared to the smaller dosimeters.ConclusionThe quenching correction model was valid for different dosimeter sizes to obtain relative dosimetric maps of complex dose distributions in PT.

Acoustic performance of overlapping micro-gapped strips

Acoustic performance of an absorber without perforating holes, overlapping micro-gapped strips (OMGS), is studied in this paper. OMGS is made by overlapping and staggering two layers of plates, each layer of which is constituted by arranging an array of strip-shaped sheets separated by a micro gap. Micro slits are formed between those strips and the upper layer of slits intersects with the lower one forming micro apertures. The aperture sandwiched between the slits is just a layer of cross profile with zero geometrical thickness. Thermoviscous acoustic simulations of OMGS demonstrate the distribution of the pressure, velocity, and power dissipation at the cross profile and along the axial direction of the aperture. Empirical impedance correction models for the cross profile are proposed based on numerical simulations. Experimental examples validate that the proposed models offer an accurate prediction for the acoustic impedance and sound absorption coefficients of OMGS.

The air quality index trend forecasting based on improved error correction model and data preprocessing for 17 port cities in China

Air pollution are known to have negative impacts on human health and the ecosystem, and it also contributes to climate change. Hence, prevention and control of air pollution is an urgent need in China, and air pollution prediction can provide reliable information for this process. Therefore, it is essential to establish effective air pollution prediction with an early warning model. Currently, one widely used air pollution prediction technology is the error correction model. However, this traditional method does not use data preprocessing technology. Therefoere, this paper presents an improved hybrid model named CEEMD-SLM-ECM (Complementary Set Empirical Mode Decomposition-Statistical Learning Model-Error Correction Model), which used the CEEMD data preprocessing technology together with statistical learning models. Furthermore, selected AQI (air quality index) data of 17 port cities in the 21st Century Maritime Silk Road Economic Belt were selected to test the forecasting ability of the proposed model. Data analysis shows that the CEEMD-SLM-ECM model has much higher accuracy compared with the traditional error correction model. So, the CEEMD-SLM-ECM is a very effective predictive model that can provide accurate prediction for air quality early warning.

Precise Point Positioning on the Reliable Detection of Tropospheric Model Errors.

Precise point positioning (PPP) is one of the well-known applications of Global Navigation Satellite System (GNSS) and provides precise positioning solutions using accurate satellite orbit and clock products. The tropospheric delay due to the neutral atmosphere for microwave signals is one of the main sources of measurement error in PPP. As one component of this delay, the hydrostatic delay is usually compensated by using an empirical correction model. However, how to eliminate the effects of the wet delay during a weather event is a challenge because current troposphere models are not capable of considering the complex atmosphere around the receiver during situations such as typhoons, storms, heavy rainfall, et cetera. Thus, how positioning results can be improved if the residual wet delays are taken into account needs to be investigated . In this contribution, a real-time procedure of recursive detection, identification and adaptation (DIA) is applied to detect the model errors which have the same effects on both phase and code observables; e.g., the model error caused by the tropospheric delay. Once the model errors are identified, additional parameters are added to the functional model to account for the measurement residuals. This approach is evaluated with Global Positioning System (GPS) data during two rainfall events in Darwin, Australia, proving the usefulness of compensated residual slant wet delay for positioning results. Comparisons with the standard approach show that the precision of the up component is improved significantly during the periods of the weather events; for the two case studies, and improvements of root mean squared error (RMS) resulted, and the precision of the horizontal component obtained by the proposed approach is also improved more than compared to the standard approach. The results also show that the identified model errors are concentrated at the beginning of both heavy rainfall processes when the front causes significant spatial and temporal gradients of the integrated water vapor above the receiver.

Research on empirical correction models of GPS Block IIF and BDS satellite inter-frequency clock bias

Triple-frequency observations will introduce an inter-frequency clock bias (IFCB) between the new frequency and the original dual-frequency observations. It has been verified that satellite IFCB can reach dozens of centimeters and several centimeters for GPS Block IIF satellite and BDS satellite, respectively. The existence of satellite IFCB will significantly affect undifferenced triple-frequency data processing. Based on 4-year data collected from 80 globally distributed stations, the long-term characteristics of IFCB coefficients obtained by using harmonic analysis have been studied. The results demonstrate that the coefficients of IFCB periodic model cannot be well fitted only by using sun elevation angle. Also, coefficients have obvious periodic characteristics and their periods differ among different satellites. Thus, a new linear-plus-periodic model is proposed to fit the long-term coefficients. Then, IFCB empirical correction models for 12 GPS Block IIF satellites and BDS GEO and IGSO satellites are built. In order to validate the correction model, IFCB standard deviation (STD), triple-frequency precise point positioning (PPP) and undifferenced extra-wide-lane (EWL) ambiguity resolution are employed. The results based on more than 4-year observations show that, with correction model applied, the average IFCB STD decreases by about 65.5% and 45.5% for GPS and BDS satellites, respectively. Compared to triple-frequency PPP without IFCB correction, triple-frequency PPP results with IFCB correction show that Up, North and East components accuracy are improved by 12.3%, 16.0% and 13.2%, respectively. Besides, IFCB correction will greatly improve the consistence of EWL fractional cycle bias among different stations and improve the success rate of EWL ambiguity resolution.

Development of Global Tropospheric Empirical Correction Model with High Temporal Resolution

The accuracy of global tropospheric empirical models depends on the model expression and the modeling data sources. Although the current temporal resolution of available models is usually one day, it is anticipated that this will be improved in the future. To achieve compatibility with future high temporal-resolution data sources, this study develops a new global tropospheric correction model, the Wuhan-University Global Tropospheric Empirical Model (WGTEM). Evaluation of WGTEM model expression determines that it has better precision than other models, and this is attributed to its ability to consider diurnal variations in meteorological parameters and the double-peak daily variation in air pressure, which are not concerned in other models. The external accuracy of the WGTEM was evaluated after modeling with the European Centre for Medium-range Weather Forecasts (ECMWF) ERA-Interim products, and results show its accuracy exceeds that of the current ITG model and its Zenith Tropospheric Delay (ZTD) performance is also superior.

Comparison of ATCOR Atmospheric and ELM Linear Empirical Correction Models Applied to WorldView-2 Images

The use of remote sensing images for the characterization of the coastal marine ecosystems requires the prior removal of the atmospheric effects, which can be done in a semi-automated manner, by the use of algorithms based on alternative assumptions contained in the processing tools for different software packages. The main objective of this study was to statistically compare the spectral behavior of the coverages contained in an high-resolution WorldView-2 image atmospherically corrected according to the ATCOR and empirical linear models (ELM), using field spectroradiometry conducted in the insular areas of the archipelago of San Andres and Providence. The ATCOR correction model was applied through the PCI 2015 Geomatics software; regarding the ELM model, the ENVI 5.2 software was used. For the spectral comparison four (4) types of coverage were selected (vegetation, reef formations, beach sand and submerged sandbank), with twenty (20) replicas each, for a total of eighty (80) sampling points distributed in a stratified way in the image. The statistical results showed a linear correlation greater than 0.9 between the reflectance values for each of the bands (Blue, Green, Red and NIR-1) and indicate that both models of the atmospheric correction have a high capacity to eliminate the atmospheric effects present in this type of images. However, there are minor significant differences between the middle quadratic errors in the reflectance values for each band of the corrected images.

Acoustic impedance of microperforated plates with stepwise apertures

Microperforated plates (MPPs) are efficient sound absorbers typically made of thin panels, which restricts practical application in engineering. This paper investigates MPPs with stepwise apertures on thick panels to enhance acoustic performance and overcome the lack of appropriate strength. Thermoviscous acoustic simulations of the MPPs demonstrate that the acoustic pressure, local velocity, and the power dissipation change abruptly at the step edges, similar as the behaviors at the inlet and outlet ends of the uniform perforations. The step generates additional acoustic impedance, which has a strong relationship with cross section ratio. Empirical impedance correction models for sharp-edged circular holes located concentrically on square or circular end panel are derived based on numerical simulations. Experimental data validate that the proposed models offer accurate prediction for acoustic impedance of MPPs with stepwise apertures.

Analysis of the systematic force-transmission error of the magnetic-suspension coupling in single-sinker densimeters and commercial gravimetric sorption analyzers

Here we present an analysis of the force-transmission error for a commercial gravimetric sorption analyzer that applies equally to single-sinker densimeters. Gravimetric sorption analyzers are commonly used for the investigation of gas adsorption on porous materials (e.g., zeolites) with a simultaneous density measurement of the sample gas. The key component of the instrument is a magnetic-suspension coupling; this coupling transmits, without contact, the weight of the “density sinker” and of the sample container with the porous sample (which are both inside a pressurized measuring cell) to a balance at ambient pressure. However, since neither the coupling housing nor the sample gas are magnetically neutral, a small, systematic force-transmission error (FTE) occurs. For the correction of this FTE, an empirical correction model was developed. We show that the FTE can be subdivided into two parts: an apparatus contribution, and a fluid contribution. In the current paper we describe the effect of the FTE on the accuracy of the density measurements; the effect of the FTE on the accuracy of sorption measurements on porous and non-porous materials will be presented in a companion paper. The magnitude of the FTE in case of density measurement is shown by comparing the results of density measurements of four pure gases with values calculated from reference equations of state. The apparatus contribution of the FTE is typically (0.23 kg m−3 + 50 × 10−6·ρfluid), and the fluid contribution can reach values up to 500 × 10−6·ρfluid for diamagnetic fluids; for oxygen-containing gas mixtures it can be much greater.

Toward a global model for correction of bottomhole temperature data: Progress and limitations

Static formation temperature (SFT) can be estimated from temperatures measured during wire-line logging (Tm). A large number of correction models for obtaining SFT from Tm have been suggested. Several studies have shown that SFTs yielded by such models are off by an average of 6°C–10°C (43°F–50°F) at burial depths of 1.5–3.5 km (0.9–2.2 mi) and thus have the potential to cause serious issues in thermal and hydrocarbon generation models. This paper explores the causes for erroneous SFT predictions generated from Tm measurements and identifies factors that should be addressed to generate a globally applicable correction model. We also present an improved empirical correction model for Tm data from eight oil and gas fields, located on the Norwegian continental shelf. The new empirical model was designed to give correct average SFT predictions and is applicable to single Tm measurements. It has been validated against temperatures recorded during drill-stem testing, which closely represent local SFTs. The expression yields improved results compared with other correction models applied to the data set. However, the average error in computed SFT values varies by up to 10°C (18°F) between the investigated hydrocarbon fields. We conclude that these variations result from differences in operational practices such as fluid circulation and drilling velocities. Therefore, current empirical and physical models for SFT prediction from Tm require local calibration. It is also suggested that more accurate compilations and analyses of operational data could lead to improved and more globally applicable models.

Influence of metallicity on the near-surface effect on oscillation frequencies

Context. The CoRoT and Kepler missions have provided high-quality measurements of the frequency spectra of solar-like pulsators, enabling us to probe stellar interiors with a very high degree of accuracy by comparing the observed and modelled frequencies. However, the frequencies computed with 1D models suffer from systematic errors related to the poor modelling of the uppermost layers of stars. These biases are what is commonly named the near-surface effect. The dominant effect is thought to be related to the turbulent pressure that modifies the hydrostatic equilibrium and thus the frequencies. This has already been investigated using grids of 3D hydrodynamical simulations, which also were used to constrain the parameters of the empirical correction models. However, the effect of metallicity has not been considered so far. Aims. We aim to study the impact of metallicity on the surface effect, investigating its influence across the Hertzsprung-Russell diagram, and providing a method for accounting for it when using the empirical correction models. Methods. We computed a grid of patched 1D stellar models with the stellar evolution code CESTAM in which poorly modelled surface layers have been replaced by averaged stratification computed with the 3D hydrodynamical code CO5BOLD. It allowed us to investigate the dependence of both the surface effect and the empirical correction functions on the metallicity. Results. We found that metallicity has a strong impact on the surface effect: keeping Teff and log g constant, the frequency residuals can vary by up to a factor of two (for instance from [Fe/H] = + 0.0 to [Fe/H] = + 0.5). Therefore, the influence of metallicity cannot be neglected. We found that the correct way of accounting for it is to consider the surface Rosseland mean opacity. It allowed us to give a physically grounded justification as well as a scaling relation for the frequency differences at νmax as a function of Teff, log g and κ. Finally, we provide prescriptions for the fitting parameters of the most commonly used correction functions. Conclusions. We show that the impact of metallicity through the Rosseland mean opacity must be taken into account when studying and correcting the surface effect.

Slip Velocity of Methane Flow in Nanopores With Kerogen and Quartz Surfaces

Summary Slip phenomenon is one of the major characteristics of gas flow through porous media—in particular, in unconventional gas reservoirs with small pore throats, such as tight sands, coal seams, and shale formations. Consequently, a permeability correction needs to be considered to evaluate the gas-flow ability in these reservoirs. Various analytically derived and empirical correction models exist for engineering applications. However, it is not well-understood which one should be implemented in real-shale-reservoir problems. In this paper, slip velocity and permeability for gas flow in nanopores are studied by molecular-dynamics (MD) simulations. For simplicity, the system considered is methane gas flow in a parallel-plate channel of quartz and kerogen. The fluid flow is characterized by the Knudsen number (Kn), which is defined as the ratio between the mean free path and the representative length of the pores. Studies with various Knudsen numbers were conducted by changing (1) the methane density (the mean free path) or (2) the plate-spacing (pore size). Simulation results show that the relationships between slip velocity and Knudsen number and between the permeability-correction factors and Knudsen number agree well with the Beskok and Karniadakis (1994) analytical solution (BK model) for large nanopores (12–34 nm) in both quartz and kerogen cases. This model considered rarefaction and compressibility effects on gas microflows, and was tested experimentally with characteristic dimensions of one-micrometer order. Our simulation results indicate that this model can be extended to nanoflows existing in unconventional reservoirs. Under temperature and pressure conditions that we studied, deviation from the BK model is noted for small nanopores (&amp;lt;12 nm), but for a pore size smaller than 6 nm, it converges to a constant value in the quartz slit pore. In contrast, a radical increase of slip velocity is observed in the kerogen pore. The deviation from the BK model for a pore size smaller than 12 nm is ascribed to the fact that the overall fluid is no longer homogeneous (i.e., the fluid at the interface region plays a crucial role in the overall flow behavior). An adsorption structure is observed in the proximity of the solid walls because of the interaction from the wall molecules. Moreover, it is found that the effect of roughness becomes significant in an extremely small kerogen nanopore.

Global model of zenith tropospheric delay proposed based on EOF analysis

Tropospheric delay is one of the main error budgets in Global Navigation Satellite System (GNSS) measurements. Many empirical correction models have been developed to compensate this delay, and models which do not require meteorological parameters have received the most attention. This study established a global troposphere zenith total delay (ZTD) model, called Global Empirical Orthogonal Function Troposphere (GEOFT), based on the empirical orthogonal function (EOF, also known as geographically weighted PCAs) analysis method and the Global Geodetic Observing System (GGOS) Atmosphere data from 2012 to 2015. The results showed that ZTD variation could be well represented by the characteristics of the EOF base function Ek and associated coefficients Pk. Here, E1 mainly signifies the equatorial anomaly; E2 represents north–south asymmetry, and E3 and E4 reflects regional variation. Moreover, P1 mainly reflects annual and semiannual variation components; P2 and P3 mainly contains annual variation components, and P4 displays semiannual variation components. We validated the proposed GEOFT model using tropospheric delay data of GGOS ZTD grid data and the tropospheric product of the International GNSS Service (IGS) over the year 2016. The results showed that GEOFT model has high accuracy with bias and RMS of −0.3 and 3.9cm, respectively, with respect to the GGOS ZTD data, and of −0.8 and 4.1cm, respectively, with respect to the global IGS tropospheric product. The accuracy of GEOFT demonstrating that the use of the EOF analysis method to characterize ZTD variation is reasonable.

An empirical thermal correction model for Moon Mineralogy Mapper data constrained by laboratory spectra and Diviner temperatures

AbstractRadiance measured by the Moon Mineralogy Mapper (M3) at wavelengths beyond ~2 µm commonly includes both solar reflected and thermally emitted contributions from the lunar surface. Insufficient correction (removal) of the thermal contribution can modify and even mask absorptions at these wavelengths in derived surface reflectance spectra, an effect that precludes accurate identification and analysis of OH and/or H2O absorptions. This study characterized thermal effects in M3 data by evaluating surface temperatures measured independently by the Lunar Reconnaissance Orbiter Diviner radiometer, and results confirm that M3 data (Level 2) currently available in the Planetary Data System often contain significant thermal contributions. It is impractical to use independent Diviner measurements to correct all M3 images for the Moon because not every M3 pixel has a corresponding Diviner measurement acquired at the same local time of lunar day. Therefore, a new empirical model, constrained by Diviner data, has been developed based on the correlation of reflectance at 1.55 µm and at 2.54 µm observed in laboratory reflectance spectra of Apollo and Luna soil and glass‐rich samples. Reflectance values at these wavelengths follow a clear power law, , for a wide range of lunar sample compositions and maturity. A nearly identical power law is observed in M3 reflectance data that have been independently corrected by using Diviner‐based temperatures, confirming that this is a general reflectance property of materials that typify the lunar surface. These results demonstrate that reflectance at a thermally affected wavelength (2.54 µm) can be predicted within 2% (absolute) based on reflectance values at shorter wavelengths where thermal contributions are negligible and reflectance is dominant. Radiance at 2.54 µm that is in excess of the expected amount is assumed to be due to thermal emission and is removed during conversion of at‐sensor radiance to reflectance or I/F. Removal of this thermal contribution by using this empirically based model provides a more accurate view of surface reflectance properties at wavelengths &gt;2 µm, with the benefit that it does not require independent measurements or modeling of surface temperatures at the same local time as M3 data were acquired. It is demonstrated that this model is appropriate for common lunar surface compositions (e.g., mare and highlands soils and pyroclastic deposits), but surface compositions with reflectance properties that deviate strongly from these cases (e.g., pyroxene‐, olivine‐, or spinel‐rich locations with minimal space weathering) may require the use of more sophisticated thermal correction models or overlapping Diviner temperature estimates.

Comparison of the lifting-line free vortex wake method and the blade-element-momentum theory regarding the simulated loads of multi-MW wind turbines

Design load simulations for wind turbines are traditionally based on the blade- element-momentum theory (BEM). The BEM approach is derived from a simplified representation of the rotor aerodynamics and several semi-empirical correction models. A more sophisticated approach to account for the complex flow phenomena on wind turbine rotors can be found in the lifting-line free vortex wake method. This approach is based on a more physics based representation, especially for global flow effects. This theory relies on empirical correction models only for the local flow effects, which are associated with the boundary layer of the rotor blades. In this paper the lifting-line free vortex wake method is compared to a state- of-the-art BEM formulation with regard to aerodynamic and aeroelastic load simulations of the 5MW UpWind reference wind turbine. Different aerodynamic load situations as well as standardised design load cases that are sensitive to the aeroelastic modelling are evaluated in detail. This benchmark makes use of the AeroModule developed by ECN, which has been coupled to the multibody simulation code SIMPACK.

High-Quality Thermochemistry Data on Polycyclic Aromatic Hydrocarbons via Quantum Chemistry

In this article, recent work on calculating high-quality enthalpies of formation for polycyclic aromatic hydrocarbons (PAHs) based on both density functional theory (DFT) and Gaussian-3 (G3) model chemistry methods is discussed. It is shown that through the use of an empirical correction model, the systematic errors in low-level DFT calculations can be controlled to produce reliable thermochemistry. It is further shown that the G3 results have a more regular systematic error and as a consequence a simpler model may be used to correct for systematic deviations. It is seen that the resulting enthalpy of formation values are in good agreement with the available experimental data, and that the predictions are sufficiently robust to point out certain errors in experimental determinations. This work was done as part of a larger effort to create a curated data set of property data for a large set of PAH molecules. In furtherance of this goal, UV/Vis spectra have been computed using time-dependent DFT. The collection of PAH data is being made publicly available through a web-based database that is briefly described.