Wind Field Research Articles

Investigation of observed dust trends over the Middle East region in NASA Goddard Earth Observing System (GEOS) model simulations

Abstract. Satellite observations and ground-based measurements have indicated a high variability in the aerosol optical depth (AOD) in the Middle East region in recent decades. In the period that extends from 2003 to 2012, observations show a positive AOD trend of 0.01–0.04 per year or a total increase of 0.1–0.4 per decade. This study aimed to investigate if the observed trend was also captured by the NASA Goddard Earth Observing System (GEOS) model. To this end, we examined changes in the simulated dust emissions and dust AOD during this period. To understand the factors driving the increase in AOD in this region we also examined meteorological and surface parameters important for dust emissions, such as wind fields and soil moisture. Two GEOS model simulations were used in this study: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis (with meteorological and aerosol AOD data assimilated) and MERRA-2 Global Modeling Initiative (GMI) Replay (with meteorology constrained by the MERRA-2 reanalysis but without aerosol assimilation). We did not find notable changes in the modeled 10 m wind speed and soil moisture. However, analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data did show an average decrease of 8 % per year in the region encompassing Syria and Iraq, which prompted us to quantify the effects of vegetation on dust emissions and AOD in the Middle East region. This was done by performing a sensitivity experiment in which we enhanced dust emissions in grid cells where the NDVI decreased. The simulation results supported our hypothesis that the loss of vegetation cover and the associated increase in dust emissions over Syria and Iraq can partially explain the increase in AOD downwind. The model simulations indicated dust emissions need to be 10-fold larger in those grid cells in order to reproduce the observed AOD and trend in the model.

Research on Short-Term Prediction Methods for Small-Scale Three-Dimensional Wind Fields

The accurate prediction of small-scale three-dimensional wind fields is of great practical significance for aviation safety, wind power generation, and related fields. This study proposes a novel method for predicting small-scale three-dimensional wind fields by combining the mesoscale Weather Research and Forecasting (WRF) model with Computational Fluid Dynamics (CFD). The method consists of three components: the WRF module, the hybrid neural network prediction module, and the CFD module. First, mesoscale meteorological fields are simulated using the WRF module to establish a historical inflow boundary dataset for the CFD domain. Next, deep separable convolutions are incorporated, and convolutional long short-term memory (ConvLSTM) is combined with a deep separable convolution-gated recurrent unit (DSConvGRU) to construct a hybrid neural network prediction module named ConvLSTM-DSConvGRU. This module is employed for predicting inflow boundary data. Finally, the predicted inflow boundary conditions drive the CFD module to predict small-scale three-dimensional wind fields. The effectiveness of the WRF and CFD downscaling coupling method was validated using observed data from meteorological stations within the simulated domain, along with statistical indicators of errors. Additionally, a comparative evaluation was conducted between the proposed hybrid network model and the four commonly used spatiotemporal prediction models to assess its prediction performance. The results demonstrate that our proposed wind field prediction method achieves accurate simulation and short-term prediction of small-scale three-dimensional wind fields, and the hybrid network model exhibits comprehensive advantages in terms of model complexity and prediction accuracy.

Research on the Terrain Characteristics of Changbai Mountain and Their Impact on Precipitation and Wind Distribution

The terrain of Changbai Mountain has great influence on the distribution of atmospheric flows and the occurrence and development of precipitation. However, quantitative studies on the real terrain characteristics and the terrain effect on precipitation distribution in this region are scant at present. This study quantitatively analyzes the regional characteristic of topographic perturbations and the relationship between terrain, wind, and precipitation in Changbai Mountain region by using a spectral analysis of the two-dimensional discrete cosine transform. Three domains with relatively heavy summer precipitation are selected as the study region. The results indicate that the overall terrain of the Changbai Mountain region exhibits anisotropic characteristics. The terrain spectra of domain B are less than those of domains A and C across the whole wavelength (λ) bands, indicating that the large-scale topographic perturbations of domain B are relatively weak. The largest topographic spectral peak of domain C shows the most pronounced undulation of terrain among the three domains. The dominant wavelengths of terrain height variance for domains A and C, both close to the respective maximum wavelengths, indicate more prominent large-scale topographic perturbations. For domain A, the variation of the precipitation spectra is consistent with that of the wind spectra at the wavelength bands of λ < 390 km, showing a high correlation between wind field and the occurrence of rainfall. The inverse relationship at larger wavelengths indicates that multiple factors contribute to the occurrence of rainfall. For domain B, there is consistency in the fluctuations of terrain spectra, precipitation spectra, and wind spectra at the wavelength bands of λ < 278.3 km, implying that the smaller-scale terrain has an important effect on the occurrence of summer precipitation. For domain C, the variations of terrain spectra, precipitation spectra, and wind spectra are almost consistent across the whole wavelength bands, indicating that the large-scale terrain and minor terrain both play a crucial role in atmospheric uplift and the occurrence and development of summer rainfall.

Impact of local plastic deformation on thermo-magnetic instability of high-J c Nb3Sn strand

The future fusion reactor devices built by Institute of Plasma Physics, Chinese Academy of Science will be a compact burning plasma facility to fill the gap between ITER and the China Fusion Engineering Test Reactor, with the mission of studying the deuterium–tritium plasma in steady-state operation. The winding-package (WP) of its toroidal field coil is graded into high-field WP and low-field WP, and the high critical current density (J c) Nb3Sn strand will be applied to the high-field WP based on the current design. The thermo-magnetic instability is the main issue in the application of high-J c Nb3Sn strand, which may induce premature quenching in the low field regions. This issue can be improved by reducing the effective filament diameter (d eff) to suppress flux jumps and increasing the residual resistivity ratio (RRR) to enhance the release of heat generated by flux jumps. However, in the conductor manufacturing process, local plastic deformations (indentation) of strands can impact the sub-element layout and degrade the RRR of the strand, which would increase again the risk on instability. In this study, magnetization measurements and V–I tests were performed on samples with different indentation depths. The hysteresis loss and d eff of the indented sample was obtained from the test results. The impact of local plastic deformation on the thermo-magnetic instability of two types of Nb3Sn strand was confirmed by cross-sectional metallographic observation and quantitative microstructure analysis. It was shown that flux jumps were suppressed at indentation depths below 0.3 mm. Further indentation increase leads to severe flux jumps.

NH3 Emissions and Lifetime Estimated by Satellite Observations with Differential Evolution Algorithm

As an important irritant trace gas in the atmosphere, ammonia (NH3) significantly impacts human health and environment. Bottom-up emission inventories are widely used to estimate ammonia emissions and their geographical distributions over China. However, high uncertainties are still associated with emission inventories due to inaccurate emission factors used. The Differential Evolution (DE) algorithm is a population-based stochastic optimization algorithm used to solve complicated optimization problems. We quantify NH3 emissions and lifetime from Infrared Atmospheric Sounding Interferometer (IASI) NH3 observations together with MERRA-2 wind fields based on the DE algorithm. Two inland cities, Urumchi and Golmud in China, are chosen to study of the NH3 emissions based on the distributions of NH3 total columns and wind fields. The NH3 emissions rate estimated is about 5.84 × 10−11 and 4.19 × 10−11 kg·m−2s−1 in Urumchi and in the Golmud area from May to September from 2008 to 2023, respectively. The lifetime of NH3 estimated in the two areas is 4.31 and 9.19 h, respectively. We compare the NH3 emissions and lifetime estimated in this study with the values in other studies, and the results show the reliability of the method used. This work is one of few quantitative studies of NH3 emissions from cities using satellite observations in China.

Simplified Current-Equivalent Circuit Models of Synchronous Reluctance Machines and Salient Pole Synchronous Machines Considering the Reluctance Torque

This paper describes a simplified one-phase equivalent circuit model of three-phase salient pole synchronous machines and synchronous reluctance machines. The model represents the pole saliency as a susceptance, with a magnitude based on the pole saliency and a phase angle based on twice the load angle. The reluctance torque itself is then modeled equivalent to a conductance. The model is made as an extension to Norton equivalents, where the internal inductance is connected as a shunt. This approach shares similarities to the magnetization shunt branch in circuit models of transformers and induction motors. The model is derived using the rotating dq-frame, using Park transform and two-reaction theory. The model is then rewritten to better fit one-phase equivalent circuit models, with the terminal voltage as the angular reference. The resulting two-pole model can then more easily be combined with basic circuit theory, thereby synthesizing dq-theory and phasor circuit models.

The vortex structure and near‐surface winds of Typhoon Faxai (2019) during landfall. Part II: Evaluation of WRF simulations

AbstractThis two‐part study presents a comprehensive analysis of (1) the vortex structure, (2) the inner core planetary boundary layer (PBL) wind profile, and (3) the overland surface winds of Typhoon Faxai(2019) during landfall observationally (Part I) and in high‐resolution Weather Research and Forecasting Model (WRF) simulations (Part II). Part II presents a framework for evaluating the wind field in the WRF simulations of Typhoon Faxai (2019) by comparing them with the observations presented in Part I. First, WRF simulations with two different surface roughness tables are presented. The simulation with the default table in WRF is shown to largely overestimate the surface wind speed. The overestimation is largely mitigated by using larger based on the climatology for urban and forest areas in Japan. Next, using the modified table, WRF simulations with three different PBL parametrizations, namely, Mellor–Yamada–Janjić, Yonsei University, and Mellor–Yamada–Nakanishi–Niino schemes are presented, and their impacts on the simulated vortex structure, inner core PBL wind profile, and overland surface winds are evaluated. In particular, the simulated surface winds are in good agreement with the observations outside the inner core of Typhoon Faxai. However, during the passage of the eyewall, the maximum surface winds are underestimated in the simulations. We show that the underestimation of the inertial stability, associated with the excessively large inner core of Typhoon Faxai in the simulations, led to the overestimation of the eyewall PBL jet height. This, in turn, caused the underestimation of the peak surface winds, as based on the empirical model of the wind reduction factor proposed in Part I.

Changing wind-generated waves in the Red Sea during 64 years

This study analyzes the wind-generated wave climate conditions in the Red Sea. A 64-year (1959–2022) wave hindcast is developed using the spectral wave model WAVEWATCH III forced with ERA5 wind fields. The study addresses the climatologies of the significant wave height (Hs), mean period (Tm), and wave power (P) parameters, as well as the wind-sea and swell distributions throughout the basin. Special interest has been paid on assessing the extreme climate conditions. Additionally, the climate variability at seasonal and inter-annual scales, and the long-term trends are analyzed. The relationship between the Red Sea wave climate and the large-scale teleconnection climate patterns is investigated. The model is calibrated for wind-wave growth and validated against buoy and altimeter measurements revealing higher performance than previous datasets. The root mean square errors of Hs and Tm are reduced by 25% and 37%, respectively. Results show that wind-seas dominate in the northern and southernmost Red Sea regions. We also detect that the 100-year return period of Hs reaches ∼5 m in the central basin. Furthermore, regional annual and seasonal variations of the wave climate show strong correlations with the circulation patterns described by the North Atlantic Oscillation at the northern Red Sea and both the Dipole Mode Index and El-Niño Southern Oscillation at the southern Red Sea. Finally, contrasting behaviours of negative and positive trends occur at the southern and northern regions, respectively, for Hs, and P with a contrary behavior for Tm. Trends under both mean and extreme conditions are mild, reaching 3 cm/decade, 0.016 s/decade, and 0.3 kW/m/decade for Hs, Tm, and P, respectively, in the northern basin in winter.

Conceptual design and supporting analysis of a double wall heat exchanger for an ARC-class fusion reactor Primary cooling system

In the fight against climate change through the progress of fusion technology, the Affordable, Robust and Compact (ARC) fusion reactor design is under development at Commonwealth Fusion Systems (CFS) and Massachusetts Institute of Technology (MIT)- Plasma Science and Fusion Center, in collaboration with the Ente Nazionale Idrocarburi (ENI) S.p.A. The reactor features demountable superconducting toroidal field coils and a replaceable vacuum vessel immersed in a Fluorine Lithium Beryllium (FLiBe) molten salt blanket. The low-pressure molten salt cools the divertors and the blanket, shields the magnets and acts as tritium breeder and tritium carrier. Tritium must be recovered efficiently from the salt to fuel the reactor, minimizing its inventory and its migration outside the FLiBe loop. The current work is aimed at presenting a preliminary design of a Double-Wall Heat eXchanger (DWHX) to be installed in an ARC-class reactor primary cooling system. The main feature is the presence of a flowing sweep gas gap which captures tritium and prevents its diffusion toward the secondary system. For the DWHX, thermal-hydraulic and tritium transport analyses were performed, considering a supercritical water Rankine power conversion system on the secondary side to carry out the calculations. To assess tritium extraction capabilities of the DWHX, the tritium extraction efficiency has been evaluated. Calculation results highlighted how the current configuration is not adequate to remove tritium, in fact the tritium extraction efficiency is very low. On the other side, it seems to act adequately as tritium permeation barrier.

SHyTCWaves: A stop-motion hybrid model to predict tropical cyclone induced waves

Waves produced by tropical cyclones (TCs) can be estimated using non-stationary wave models forced with time-varying wind fields. However, dynamical simulations are time and computationally demanding at regional-scale domains since high temporal and spatial resolutions are required to correctly simulate TC-induced wave propagation processes. Applications such as early warning systems, coastal risk assessments and future climate projections benefit from fast and accurate estimates of wave fields induced by close-to-real storm tracks geometry. The proposed SHyTCWaves methodology constitutes a novel tool capable of estimating the spatio-temporal variability of directional wave spectra produced by TCs in deep waters, using a hybrid approach and statistical techniques to reduce CPU time effort. This work demonstrates that TC-induced waves can be reconstructed using a stop-motion approach based on the addition of successive 6 h periods of time-varying storm conditions. The developed hybrid model reduces a TC track to a number of segments that are parameterized in terms of 10 representative TC features, and generates a library of cases dynamically pre-computed which allow to ensemble consecutive 6 h analog segments representing the original TC track. The metamodel has been compared and corrected with available satellite data, and its applicability is exemplified for TC Ofa in the South Pacific.

Inter-comparison study of wind measurement between the three-lidar-based virtual tower and four lidars using VAD techniques

ABSTRACT The accurate three-dimensional wind field obtained from a Doppler lidar not only helps to comprehend the refined structure of complex airflow but also provides important and valuable solutions for many fields. However, the underlying homogeneity assumption of the typical wind retrieval methods, such as Doppler Beam Swinging (DBS) and Velocity Azimuth Display (VAD) based on a single-lidar, will introduce the measurement uncertainty in complex terrain. In this paper, a new design of a wind measurement campaign involving seven lidars was carried out, which contained the three-lidar-based Virtual Tower (VT) using a time-space synchronization technique and four single-lidars with different elevation angles. This study investigates the performance of VT and VAD measurements under various conditions and evaluates the sensitivity of wind measurement uncertainty of VAD to the horizontal spatial- and probe volume-average effects associated with elevation angles of the laser beam. The inter-comparison results between VT and four VADs show consistent trends with small relative errors under neutral atmospheric conditions with weak wind velocity. Under convective or high Turbulence Intensity (TI) conditions, the relative errors between VT and VAD become larger and more fluctuant. Moreover, it is found that the measurement uncertainty of VAD increases at a given elevation angle with the increasing measurement heights, which is caused by the horizontal homogeneity associated with the conical scanning area. Additionally, the simulated and measured results of four VADs indicate that a larger elevation angle corresponds to a lower measurement uncertainty for a given height.

MATRESHCA: Microtesla Apparatus for Transfer of Resonance Enhancement of Spin Hyperpolarization via Chemical Exchange and Addition.

We present an integrated, open-source device for parahydrogen-based hyperpolarization processes in the microtesla field regime with a cost of components of less than $7000. The device is designed to produce a batch of 13C and 15N hyperpolarized (HP) compounds via hydrogenative or non-hydrogenative parahydrogen-induced polarization methods that employ microtesla magnetic fields for efficient polarization transfer of parahydrogen-derived spin order to X-nuclei (e.g., 13C and 15N). The apparatus employs a layered structure (reminiscent of a Russian doll "Matryoshka") that includes a nonmagnetic variable-temperature sample chamber, a microtesla magnetic field coil (operating in the range of 0.02-75 microtesla), a three-layered mu-metal shield (to attenuate the ambient magnetic field), and a magnetic shield degaussing coil placed in the overall device enclosure. The gas-handling manifold allows for parahydrogen-gas flow and pressure control (up to 9.2 bar of total parahydrogen pressure). The sample temperature can be varied either using a water bath or a PID-controlled heat exchanger in the range from -12 to 80 °C. This benchtop device measures 62 cm (length) × 47 cm (width) × 47 cm (height), weighs 30 kg, and requires only connections to a high-pressure parahydrogen gas supply and a single 110/220 VAC power source. The utility of the device has been demonstrated using an example of parahydrogen pairwise addition to form HP ethyl [1-13C]acetate (P13C = 7%, [c] = 1 M). Moreover, the Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei (SABRE-SHEATH) technique was employed to demonstrate efficient hyperpolarization of 13C and 15N spins in a wide range of biologically relevant molecules, including [1-13C]pyruvate (P13C = 14%, [c] = 27 mM), [1-13C]-α-ketoglutarate (P13C = 17%), [1-13C]ketoisocaproate (P13C = 18%), [15N3]metronidazole (P15N = 13%, [c] = 20 mM), and others. While the vast majority of the utility studies have been performed in standard 5 mm NMR tubes, the sample chamber of the device can accommodate a wide range of sample container sizes and geometries of up to 1 L sample volume. The device establishes an integrated, simple, inexpensive, and versatile equipment gateway needed to facilitate parahydrogen-based hyperpolarization experiments ranging from basic science to preclinical applications; indeed, detailed technical drawings and a bill of materials are provided to support the ready translation of this design to other laboratories.

Modeling climate change effects on transport and fate of pathogens in an urban coastal area of Lake Michigan

Abstract Infrastructure renewal and public health efforts require prediction of climate change effects on the occurrence of pathogens in the Great Lakes' urban coastal waters. This paper presents an investigation that addressed the climate change effects on transport and the fate of bacteria in Milwaukee's urban coastal area. This investigation was part of a study on climate change risks and impacts that included downscaling of climate change data for meteorological stations around Lake Michigan, and implementation of a hydrologic model that predicts tributary flows and bacteria loads. A method to select scenarios appropriate to link watershed and lake transport processes is presented. For the watershed, the sensitivity of bacterial loads with respect to changes in spring-season precipitation and air temperature is critical, while for lake transport, the most important driver is the wind field. Watershed and lake processes are linked by using spring-season watershed loading in the simulation of coastal transport. Scenarios for hydrodynamic modeling were developed by selecting climate projections that yielded high-and-low percentile projected spring-season wind speed. The patterns of bacteria transport showed significant changes under climate change conditions, and the changes in fecal coliform concentration at critical locations were explained by changes in current vector fields.

Relationship between magnetic field and tokamak size—a system engineering perspective and implications to fusion development

High temperature superconductors (HTSs) offer the promise of operating at higher magnetic field and temperature. Recently, the use of high field magnets (by adopting HTS) has been promoted by several groups around the world, including new start-up entries, both to substantially reduce the size of a fusion power reactor system and as a breakthrough innovation that could dramatically accelerate fusion power deployment. This paper describes the results of an assessment to understand the impact of using high field magnets in the design of DEMO in Europe, considering a comprehensive list of physics and engineering limitations together with the interdependencies with other important parameters. Based on the results, it is concluded that increasing the magnetic field does not lead to a reduction in device size with relevant nuclear performance requirements, because (i) large structures are needed to withstand the enormous electromagnetic forces, (ii) thick blanket and n-shield structures are needed to protect the coils from radiation damage effects, and (iii) new divertor solutions with performances well beyond today’s concepts are needed. Stronger structural materials allow for more compact tokamaks, but do not change the conclusion that scalability is not favourable when increasing the magnetic field, beyond a certain point, the machine size cannot be further reduced. More advanced structural support concepts for high-field coils have been explored and concluded that these solutions are either unfeasible or provide only marginal size reduction, by far not sufficient to account for the potential of operating at very high field provided by HTS. Additionally, the cost of high field coils is significant at today’s price levels and shows to scale roughly with the square of the field. Nevertheless, it is believed that even when not operated at high field and starting within conventional insulated coils, HTS can still offer certain benefits. These include the simplification of the magnet cooling scheme thanks to increased temperature margin (indirect conduction cooling). This in turn can greatly simplify coil construction and minimize high-voltage risks at the terminals.

A two-fold deep-learning strategy to correct and downscale winds over mountains

Abstract. Assessing wind fields at a local scale in mountainous terrain has long been a scientific challenge, partly because of the complex interaction between large-scale flows and local topography. Traditionally, the operational applications that require high-resolution wind forcings rely on downscaled outputs of numerical weather prediction systems. Downscaling models either proceed from a function that links large-scale wind fields to local observations (hence including a corrective step) or use operations that account for local-scale processes, through statistics or dynamical simulations and without prior knowledge of large-scale modeling errors. This work presents a strategy to first correct and then downscale the wind fields of the numerical weather prediction model AROME (Application of Research to Operations at Mesoscale) operating at 1300 m grid spacing by using a modular architecture composed of two artificial neural networks and the DEVINE downscaling model. We show that our method is able to first correct the wind direction and speed from the large-scale model (1300 m) and then accurately downscale it to a local scale (30 m) by using the DEVINE downscaling model. The innovative aspect of our method lies in its optimization scheme that accounts for the downscaling step in the computations of the corrections of the coarse-scale wind fields. This modular architecture yields competitive results without suppressing the versatility of the DEVINE downscaling model, which remains unbounded to any wind observations.

Multi-Indicator Fused Resilience Assessment of Power Grids Considering Wind-Photovoltaic Output Uncertainty during Typhoon Disasters

Extreme weather events such as typhoons pose a serious threat to the safe operation of power grids. In the field of power system resilience assessment during typhoon disasters, a parametric typhoon wind field model combined with actual historical meteorological data has not been well adopted, and the conventional renewable energy uncertainty modeling methods are not suitable for typhoon disaster periods. In this paper, a multi-indicator fused resilience assessment strategy considering wind-photovoltaic uncertainty and component failure during typhoon disasters is proposed. Firstly, based on the actual historical meteorological data of typhoons, an uncertainty model of typhoon wind speed is established by a rolling non-parametric Dirichlet process Gaussian mixture model. Then, a spatial–temporal contingency set is constructed by considering the best-fit wind field model and stress–strength interference model for failure probability of transmission lines. On this basis, a holistic resilience assessment framework is established from the perspectives of priority, robustness, rapidity, and sustainability, and the entropy weight method combined with the technology for order preference by similarity to an ideal solution is leveraged to obtain the comprehensive resilience indicator. Finally, numerical studies are performed on the IEEE-30 bus test system to identify vulnerable lines and improve system resilience during typhoon disasters.

An accurate calculation method for inductor air gap length in high power DC–DC converters

High-power inductors are fundamental components in high-power DC–DC converters, with their performance being a crucial metric of converter efficiency. This paper presents an in-depth analysis of a novel calculation method for the air gap length in such inductors. Taking into account the effects of air gap diffusion and the winding magnetic field, an expression for the air gap diffusion radius is derived, focusing on a distributed air gap structure. Furthermore, models for calculating the air gap and winding reluctance are developed, grounded in electromagnetic field theory. An equivalent magnetic circuit model, formulated based on Kirchhoff's second law, facilitates the proposed method for air gap length calculation. This study also involves the development of 3D models for both discrete and decoupled integrated inductors. The comparison between simulation outcomes and calculated air gap lengths indicates a maximum error of less than 8%, with the minimum error being as low as − 0.79%. Compared with traditional methods, the calculation method proposed in this paper has significant advantages. Additionally, the discrepancy between calculated values and experimental measurements is found to be 1.11%. These results validate the accuracy and applicability of the theoretical analysis and calculation method, underscoring their significance in the design and optimization of high-power DC–DC converters.

Research on attitude correction algorithm for mobile wind lidars

The laser wind measurement technology is remarkable for detecting clear-sky wind fields. The Doppler beam swinging algorithm for wind lidars has been developed to obtain vertical wind profiles based on fixed observation methods. However, the Doppler frequencies are superposed due to the self-motions of lidars caused by carrier motions when lidars are used on motion carrier platforms. Meanwhile, the emission directions of laser beams are uncertain due to changes in carriers’ motion directions and tilts. Thus, a new wind measurement correction model must be studied with lidar attitudes. This study considers the influences of the motion velocities, the carrier’s tilt angles, and the laser beams’ yaw angles at the 0° azimuth angle on the measured results under lidar motions, a correction model of motion attitudes for mobile wind lidars was designed. Sensitivity simulation tests for motion attitude parameters were carried out, and the influences of different attitude parameters of the carrier on the measured results were investigated to evaluate and verify the effects of the correction model. Results indicated that the wind measurement correction model could correct data errors caused by the carrier’s motion and tilts. The motion velocities, carrier directions, and the yaw angles of the laser beams at the 0° azimuth angle had an essential influence on the wind velocity measurements. Besides, the carrier’s pitch angles and the roll angles, which did not influence the wind velocity measurements, only affected the altitudes of the wind field data. Furthermore, the pitch angles exerted more significant influences on the data altitudes than the roll angles.

Complementary interstellar detections from the heliotail

The heliosphere is a protective shield around the solar system created by the Sun’s interaction with the local interstellar medium (LISM) through the solar wind, transients, and interplanetary magnetic field. The shape of the heliosphere is directly linked with interactions with the surrounding LISM, in turn affecting the space environment within the heliosphere. Understanding the shape of the heliosphere, the LISM properties, and their interactions is critical for understanding the impacts within the solar system and for understanding other astrospheres. Understanding the shape of the heliosphere requires an understanding of the heliotail, as the shape is highly dependent upon the heliotail and its LISM interactions. The heliotail additionally presents an opportunity for more direct in situ measurement of interstellar particles from within the heliosphere, given the likelihood of magnetic reconnection and turbulent mixing between the LISM and the heliotail. Measurements in the heliotail should be made of pickup ions, energetic neutral atoms, low energy neutrals, and cosmic rays, as well as interstellar ions that may be injected into the heliosphere through processes such as magnetic reconnection, which can create a direct magnetic link from the LISM into the heliosphere. The Interstellar Probe mission is an ideal opportunity for measurement either along a trajectory passing through the heliotail, via the flank, or by use of a pair of spacecraft that explore the heliosphere both tailward and noseward to yield a more complete picture of the shape of the heliosphere and to help us better understand its interactions with the LISM.

Development of a Load Model Validation Framework Applied to Synthetic Turbulent Wind Field Evaluation

The validation of aeroelastic load models used for load calculations on wind turbines substantially increases the confidence in the accuracy and correctness of these models. In this contribution, we introduce a framework for the validation of these models, integrating a normalized area metric as an objective, quantifiable validation metric that considers the entire statistical distribution of a model and a benchmark and additionally enables a comparison of model accuracy between sensors of different physical units. The framework is applied to test cases that evaluate varying synthetic turbulent wind fields. Two test cases with a focus on turbulence parameters and abnormal shear conditions based on comprehensive wind measurements at the Testfeld Bremerhaven are used to demonstrate the workflow with four different members using IEC-compliant and measurement-derived wind field parameters, respectively. Along with these measurements, an uncertainty model for synthetic wind fields is introduced to quantify propagated wind measurement uncertainties associated with the measured boundary conditions during a validation campaign. The framework is presented as a straightforward and concise methodology to not only find but also quantify mismatches of load models. Major mismatches are found for wind fields associated with larger uncertainties in the mean wind field due to a reduced spatial resolution of measurements.