bluuebunny/crossref_metadata_2025 huggingface dataset:
Reduction of write current with improved thermal stability in GeSe2 doped Sb2Te3 films for phase change memory applications
Authors: Bhatt Nidhi , Parveen Shahin , Whab Abdul , munga Pumlian
Published: June 2024

Chalcogenide alloy-based semiconductors have gained significant attention in recent decades due to its applications in phase change memory (PCM). Sb2Te3 has proven to be an alternative to Static and Dynamic Random Access Memory and can be a suitable candidate for commercial memory devices due to their fast switching speed. However, Sb2Te3 suffers from low amorphous phase stability and high RESET current, which needs further improvement for high power efficiency. In this work, we have prepared (Sb2Te3)1−x
(GeSe2)
x
(x = 0.06, 0.12, 0.18, 0.24, 0.3) films to investigate their PCM properties. The films showed a rise in transition temperature to transform from high resistive amorphous (RESET) to low resistive crystalline (SET) states with doping that leads to significant enhancement in amorphous phase stability. For 30% doping of GeSe2 in Sb2Te3, the data retention temperature increases from 20.2 °C to 84.6 °C, and the resistance contrast also increases from 102 to 105. The rise in electrical resistance with doping in the amorphous as well as crystalline states leads to a drop in threshold current (I
th) from 3.5 to 0.8 mA. This also reduces the RESET and SET currents. By analyzing the samples using finite element method, it was found out that the high resistance materials produce more heat, resulting in a lower write current in an energy efficient PCM device.
Top-quark FCNC decays, LFVs, lepton g − 2, and W mass anomaly with inert charged Higgses
Authors: Chen Chuan-Hung , Chiang Cheng-Wei , Su Chun-Wei
Published: June 2024

The observed flavor-changing neutral-current (FCNC) processes in the standard model (SM) arise from the loop diagrams involving the weak charged currents mediated by the W-gauge boson. Nevertheless, the top-quark FCNCs and lepton flavor-violating processes resulting from the same mechanism are highly suppressed. We investigate possible new physics effects that can enhance the suppressed FCNC processes, such as a top quark decaying into a light quark with a Higgs or gauge boson in the final state, i.e. t → q(h, V) with V = γ, Z, g,

h
→
ℓ
ℓ
′

, and

ℓ
→
ℓ
′
γ

. To achieve the assumption that the induced FCNCs are all from quantum loops, we consider the scotogenic mechanism, where a Z
2 symmetry is introduced and only new particles carry an odd Z
2 parity. With the extension of the SM to include an inert Higgs doublet, an inert charged Higgs singlet, a vector-like singlet quark, and two neutral leptons, it is found that, with relevant constraints taken into account, the t → c(h, Z), h → μ
τ, and τ → ℓ
γ decays can be enhanced up to the expected sensitivities in experiments. The branching ratios of h → μ
+
μ
−/τ
+
τ
− from only new physics effects can reach up to

O
(

10

−
3

)

. Intriguingly, the resulting muon g − 2 can fit the combined data within 2 standard deviations, whereas the electron g − 2 can have either sign with a magnitude of

O

(

10

−
13

−

10

−
12

)

. In addition, we examine the oblique parameters in the model and find that the resulting W-mass anomaly observed by CDF II can be accommodated.
A Monte Carlo simulation study of a Janus discotic liquid crystal droplet
Authors: Llanas-García Andrea H , Salgado-Blanco Daniel
Published: June 2024

The study of discotic liquid crystals (DLCs) under spherical confinement has gained considerable significance due to its relevance in the design and optimization of advanced materials with tailored properties. The unique characteristics of DLC fluids, coupled with confinement within a spherical Janus surface, offer a compelling avenue for exploring novel behaviors and emergent phenomena. In this study, Monte Carlo simulations within the NpT ensemble are employed to investigate the behavior of a DLC fluid confined by a spherical Janus surface. The Janus surface is characterized by distinct hemispheres, with one promoting homeotropic (face-on) anchoring and the other planar (edge-on) anchoring. Our analysis reveals the emergence of two topological defects: one exclusively on the edge-anchoring hemisphere and the other at the boundary of both anchorings. Each topological defect possessing a topological charge of k = +1/2. We observe that as the temperature transitions the central region of the droplet into a nematic phase, a disclination line forms, linking the two surface defects. By investigating droplets of three different sizes, we confirm that the isotropic-nematic transition is first-order for the larger droplet studied. However, this transition becomes continuous under strong confinement conditions. In contrast, the nematic-columnar transition remains first order even for smaller systems.
TFASOT for bearing damage feature extraction and enhancement under complex working conditions
Authors: Wang Kun , Huang Yukun , Luo Huageng
Published: June 2024

In some complex working conditions, such as variable speeds and variable loadings, events like bearing skidding and/or contact angle changing may happen during the operations. In such cases, order tracking based on the shaft speed, i.e. the first order tracking (FOT), can no longer completely eliminate the smearing effect on spectrum, and thus affects the bearing damage detection precision and accuracy. The existing second order tracking is unable to resolve these issues either in some cases. To resolve these problems, a new approach called time frequency analysis based second order tracking is developed in this paper. Based on the FOT, short-time Fourier transform and synchro-reassigning transform are used to obtain the actual fault characteristic order (FCO) information. Then the FCO is extracted by ridge searching approach to set new synchronous resampling clock. Finally, synchronous resampling and order tracking are combined to correct and enhance the bearing damage feature, resulting in more accurate damage feature extraction. The effectiveness of proposed method is verified by numerical simulations and practical examples as well. The results show that the proposed method can effectively correct the dispersion and deviation of the FCO induced by speed variations as well as operation condition variations, and thus significantly improve the damage feature extraction.
An integrated navigation algorithm assisted by CNN-Informer during short-time GNSS outages
Authors: Hu Yuan , Fan Zhe , Liu Wei , Wu Linjin
Published: June 2024

Inertial Navigation System (INS) and Global Navigation Satellite System (GNSSs) are commonly used in integrated navigation systems. The GNSS navigation system, however, is not autonomous, and its signals are susceptible to environmental influences leading to poor navigation results. In order to improve the positioning accuracy of the INS/GNSS integrated navigation system during GNSS outages, a hybrid algorithm of Convolutional Neural Network (CNN)-Informer model-assisted INS is proposed. The CNN-Informer model combines the advantages of each of the CNN and the Informer network. It utilizes CNN to rapidly extract spatial features from input data, employs the Informer network to establish relationships between inputs and outputs, and acquires pseudo-GNSS signals to compensate for position errors in the INS. Lastly, we evaluate the proposed algorithm through six sets of experiments conducted on public datasets and real road scenarios. The comparative results demonstrate that the proposed method offers a more accurate and reliable solution during GNSS outages. Specifically, CNN-Informer can improve navigation accuracy by 81.46% over MLP and by 58.91% over LSTM during 20-s GNSS outages.
A rotor bearing system fault diagnosis method based on FSASCA-VMD and GraphSAGE-SA
Authors: Wang Yaping , Zhang Qisong , Zhang Sheng , Li Shengbiao , Fan Yuqi
Published: June 2024

In complex environments, signals from rotor bearing systems can easily be drowned out by strong noise, leading to low fault diagnosis accuracy. In order to reduce noise and improve diagnostic accuracy, this paper proposes a rotor bearing system fault diagnosis method based on future search algorithm based on sine cosine algorithm-variational mode decomposition (FSASCA-VMD) and Graph SAmple and aggreGatE-self attention (GraphSAGE-SA). First, the FSASCA optimization algorithm is used to determine two parameters in VMD. The best combination found is then input into VMD to decompose the original signal. Then, filter the intrinsic mode function (IMF) components with high correlation to the original signal using cumulative percentage kurtosis. Reconstruct the filtered IMF components to complete signal denoising. Finally, this paper utilizes graph theory and time series correlation to uncover the hidden relationships within the data. Utilizing the Euclidean distance as the edge weight between nodes, a graph model is established based on the topological structure of the PathGraph, and a GraphSAGE-SA fault diagnosis framework is constructed. Utilizing a self-attention mechanism to aggregate nodes enhances the weight allocation of important information. The experimental results indicate that the method proposed in this paper can effectively remove most of the noise in the signal while preserving a significant amount of useful information. In rotor bearing system fault diagnosis, the diagnostic accuracies of this method for simulated and laboratory signals are 98.33% and 98.56%, respectively, surpassing those of other methods.
A review on synthesis, properties, and biomedical applications of graphene quantum dots (GQDs)
Authors: Bae Gaeun , Cho Hyeonwoo , Hong Byung Hee
Published: June 2024

A new type of 0-dimensional carbon-based materials called graphene quantum dots (GQDs) is gaining significant attention as a non-toxic and eco-friendly nanomaterial. GQDs are nanomaterials composed of sp2 hybridized carbon domains and functional groups, with their lateral size less than 10 nm. The unique and exceptional physical, chemical, and optical properties arising from the combination of graphene structure and quantum confinement effect due to their nano-size make GQDs more intriguing than other nanomaterials. Particularly, the low toxicity and high solubility derived from the carbon core and abundant edge functional groups offer significant advantages for the application of GQDs in the biomedical field. In this review, we summarize various synthetic methods for preparing GQDs and important factors influencing the physical, chemical, optical, and biological properties of GQDs. Furthermore, the recent application of GQDs in the biomedical field, including biosensor, bioimaging, drug delivery, and therapeutics are discussed. Through this, we provide a brief insight on the tremendous potential of GQDs in biomedical applications and the challenges that need to be overcome in the future.
Tracing quantum correlations back to collective interferences
Authors: Ji Ming , Hance Jonte R , Hofmann Holger F
Published: June 2024

In this paper, we investigate the possibility of explaining nonclassical correlations between two quantum systems in terms of quantum interferences between collective states of the two systems. We achieve this by mapping the relations between different measurement contexts in the product Hilbert space of a pair of two-level systems onto an analogous sequence of interferences between paths in a single-particle interferometer. The relations between different measurement outcomes are then traced to the distribution of probability currents in the interferometer, where paradoxical relations between the outcomes are identified with currents connecting two states that are orthogonal and should therefore exclude each other. We show that the relation between probability currents and correlations can be represented by continuous conditional (quasi)probability currents through the interferometer, given by weak values; the violation of the noncontextual assumption is expressed by negative conditional currents in some of the paths. Since negative conditional currents correspond to the assignment of negative conditional probabilities to measurements results in different measurement contexts, the necessity of such negative probability currents represents a failure of noncontextual local realism. Our results help to explain the meaning of nonlocal correlations in quantum mechanics, and support Feynman’s claim that interference is the origin of all quantum phenomena.
Direct & efficient detection of x-ray radiation using thermally evaporated 2D hybrid lead halide perovskite (BA2PbBr4)(BA=n-Butylammonium=C4H9NH3) film
Authors: Mitra Saikat , Majhi Parushottam , Maity Avisek , Hazra Snehamoyee , Chowdhury Avijit , Ghosh Barnali
Published: June 2024

This report demonstrates fast response and direct detection of x-ray radiation by thermally evaporated 2D hybrid halide perovskite (BA2PbBr4)(n-BA=Butylammonium=C4H9NH3) based film. A highly efficient pin-hole free/compact film (thickness∼1 μm), via a controlled evaporation process, has been grown to fabricate solid-state x-ray radiation detector film (typical dimension ∼1 × 1 cm2) of 2D hybrid halide perovskite BA2PbBr4 ( BAPB) material. Direct detection of x-rays is possible using this detector by simple electrical readout method, where a change in resistance occurs while exposed to x-ray radiation at ambient temperature. The detector current increases when an x-ray impinges on it and exhibits the highest sensitivity ∼1000 μC/Gy/cm2. The detector film shows fast response, exhibiting quick response-recovery time ∼

ms

towards x-ray. The detector film exhibits reasonably high dark resistivity ∼

10

10

Ω
−
cm

and good mobility-lifetime (

μ
τ
)

product

3.308
×

10

−
6

c

m

2

/
s
.

The 2D hybrid halide perovskite (BA2PbBr4) based detector can sustain an effective high electric field ∼5000 V cm−1 corresponding to 40 V operational bias. It shows very good radiation resistant towards x-ray and retains its crystal structure, as confirmed from structural data under sustained x-ray exposure. The 2D halide perovskite detector (BAPB) shows long-term stability or shelf life (∼4 months) and response is highly repeatable with less than

5
%

fluctuation, which is an important key performance metric for any radiation detector. This detector has good application potential in several areas like, medical imaging, security checking, etc.
Study on trap sensitivity for single material gate and double material gate nano-ribbon FETs
Authors: Rai Shashank , Sharma Ritu , Saha Rajesh , Bhowmick Brinda , Goswami Rupam
Published: June 2024

In this work, the trap sensitivity of single material gate (SMG) and dual material gate (DMG) nano ribbon FETs (NRFETs) are reported using TCAD Sentaurus Device simulator. The trap sensitivity is extracted for Gaussian trap distribution of both acceptor and donor type traps. We have reported the trap sensitivity for the variation in trap concentration, energy peak position, work function of metal gate, and temperature for both the NRFETs. It is realized that trap sensitivity is greater and lesser than 100% for acceptor type trap in SMG and DMG NRFETs, respectively, whereas, such sensitivity is 147% and 123% for donor type trap concentration, respectively. Temperature also shows a significant variation in trap sensitivity for both the NRFETs. The increase in work function leads to the reduction in trap sensitivity for both NRFETs in existence of acceptor and donor trap charges. The maximum sensitivity in trap are 400% and 275% for SMG and DMG NRFETs, respectively, in presence of donor trap concentration. Moreover, the trap sensitivity is very insignificant at high gate bias for donor type trap concentration with wide variation in parameters.
Transformer based deep learning hybrid architecture for phase unwrapping
Authors: Bujagouni Karthik Goud , Pradhan Swarupananda
Published: June 2024

A deep learning Hybrid architecture for phase unwrapping has been proposed. The hybrid architecture is based on integration of Convolutional Neural Networks (CNN) with Vision Transformer. The performance of Hybrid architecture/network in phase unwrapping is compared against CNN based standard UNET network. Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE) have been used as performance metrics to assess the performance of these deep learning networks for phase unwrapping. To train and test the networks, dataset with high mean Entropy has been generated using Gaussian filtering of random noise in Fourier plane. The Hybrid architecture is tested on test dataset and is found to have superior performance metrics against the UNET network. Their performance is also tested in noisy environment with various noise levels and Hybrid architecture demonstrated better anti-noise capability than UNET network. Hybrid architecture was successfully validated in real world scenario using experimental data from custom built Digital Holographic Microscope. With the advent of newer architectures and hardware, Deep learning networks can further improve the performance in solving inverse problems.
Dynamical analysis and circuit realization of a high complexity fourth-order double-wing chaotic system with transient chaos and its application in image encryption
Authors: Zhang Jie , Bi Jingshun , Guo Yan , Wang Pengyuan
Published: June 2024

This paper proposes a fourth-order double-wing chaotic system with high complexity. After conducting a dynamic analysis, it is found that the system exhibits transient chaos and a rare inverse period-doubling bifurcation phenomenon in the bifurcation diagram. The system also exhibits attractor coexistence, with periodic, quasi-periodic, indicating high sensitivity to initial values. These phenomena sufficiently demonstrate the rich dynamical characteristics of chaotic systems. By introducing an impulse function with a cosine function in the foundation of the proposed system, it is found that controllable wing number and staircase burst oscillations occur. Furthermore, the number of wings and oscillation periods vary with changes in parameters, which has significant implications in engineering applications. The circuit design and construction are carried out using the Multisim simulation software, and the digital circuit is realized by using a Field-Programmable Gate Array (FPGA). It is found that the simulation results and the actual implementation results are highly consistent with the phase portrait of the system, thus demonstrating the feasibility of the circuit. Finally, by combining the proposed system with a DNA encryption algorithm, a novel image encryption algorithm with multiple layers of encryption is designed, greatly enhancing the security of encrypted images. The security of this encryption algorithm is analyzed in terms of information entropy, key space, correlation, and resistance to attacks. It is found that the proposed encryption algorithm exhibits high confidentiality and resistance to attacks. The proposed system has significant reference value in secure communication when applied to image encryption.
Perturbed conjugate gradient method: controlling semi-convergence, enforcing non-negativity, and accelerating iterations in tomographic imaging
Authors: Nikazad Touraj
Published: June 2024

We regulate the semi-convergence behaviour, impose non-negativity on the iterations, reduce total variation, and enhance the conjugate gradient (CG) method by introducing a perturbed version of the CG method. We provide a convergence analysis for this perturbed version. We also demonstrate its performance using examples taken from tomographic imaging and compare it with CG and its projected version, superiorized conjugate gradient (S-CG-CD), and non-negative flexible CGLS (NN-FCGLS).
Analytic computation of the entanglement of formation for bipartite isotropic states using their symmetry
Authors: Akbari-Kourbolagh Y , Shahhoseini E
Published: June 2024

It is well-known that computing the entanglement of formation of a general bipartite state is a difficult task. We use the local symmetry of bipartite isotropic states in arbitrary dimensions to compute their entanglement of formation analytically. Our computation is an explicit and detailed version of the computation performed by Terhal et al [B. M. Terhal and K. G. H. Vollbrecht, Phys. Rev. Lett. 85, 2625 (2000)]. However, it is not just a review but we also have our contribution and novelty. For instance, we provide a rigorous proof for the entanglement of formation of two qutrit isotropic states and notably we give a proof supporting the conjecture proposed by Terhal et al about the entanglement of formation of bipartite isotropic states for the last range of allowed parameter values.
Dynamical analysis of a new memristive map with offset boosting and extreme multistability
Authors: Han Zhitang , Cao Yinghong , Xu Xianying , Mou Jun
Published: June 2024

In this paper, a memristive circuit is designed based on a charge-controlled memristor, and the Hamilton energy function is obtained from the Helmholtz theorem. The system equation of memristive circuit is discretized by redefining the variables to obtain a three-dimensional memristive map and the corresponding energy function. Then, the effects of parameters and initial values on the memristive map are analyzed using conventional dynamical analysis. There are multiple types of quasi-periodic and chaotic states of the memristive map under different parameters, and the energy evolution of different states is shown. In addition, offset boosting and homogeneous extreme multistability are found in the map, which can be controlled to offset the attractor by changing specific parameters and initial values. The complexity of the chaotic sequence is also analyzed as the parameters and initial values are varied over the chosen range. Finally, the map is implemented on PSIM circuit simulation and digital signal processor (DSP) respectively. This research will provide a reference for secure communication.
Study on the influence of intermediate airshafts on the aerodynamic effect of urban rapid rail transit
Authors: Zhu Xinyi , Weng Miaocheng
Published: June 2024

This study explores how intermediate airshafts affect the aerodynamics of urban rapid transit trains in tunnels. It employs a three-dimensional turbulence model to simulate train-tunnel interactions, specifically examining airshafts’ impact on transient pressure variations along surfaces. The model’s accuracy and reliability are confirmed by comparing results with full-scale experimental data. The results show that airshafts effectively mitigate peak tunnel wall pressures, with the lowest peak overpressure observed at the airshaft location. With the airshaft-reflected expansion wave arriving ahead of the train, the pressure between the train front and tunnel wall decreases compared to scenarios without airshafts. Similar transient pressure changes at the tunnel entrance and rear half suggest the emergence of a “secondary compression wave” due to the train’s transit.
Design and application of a testing device for solar reflective materials
Authors: Guo Senyuan , Fang Yueyun
Published: June 2024

Using white polyvinyl chloride pipes, gray polyvinyl chloride pipes, natural rubber foam sheets, and nylon 6 as experimental materials, this article designed a sandwich structure solar reflective material testing device. By testing the thermal conductivity of various materials and the thermal conductivity of the composite materials in the device and conducting thermal insulation verification experiments on the solar reflective material testing device, it was found that the overall thermal conductivity of the device was small and the internal temperature of the device was less affected by the external environmental temperature. The results indicated that the solar reflective material testing device has good insulation performance.
Double roller negative stiffness mechanism seat suspension optimization design and vibration analysis
Authors: Zuo Xidong , Chen Qingzhang , Li Youshi
Published: June 2024

To further improve the vibration isolation performance of automobile seat suspension and the riding comfort of automobiles, this paper uses the double roller negative stiffness mechanism (NSM) to calculate the seat suspension with quasi-zero stiffness (QZS) characteristics. The influence of the structural parameters on the QZS characteristics is simulated and analyzed, and the structural parameters are optimized by the orthogonal design method. The effectiveness of the optimization was verified by analyzing the dynamic response of the seat suspension system. The results show that the natural frequency of the vibration isolation system of the seat suspension decreases, the vibration isolation band widens after the introduction of the double roller NSM, and the vibration isolation effect is improved under low-frequency excitation.
Simulation study on the damage behavior of tantalum target plates under high-velocity projectile impact
Authors: Wang Yuntian , Yang Min , Hu Danping , Wei Qiujie , Zhang Ying , Guo Yuzhu
Published: June 2024

This study aims to explore the damage behavior of tantalum target plates under high-velocity projectile impact, addressing the threats of damage in the aerospace field due to debris and other factors. With the advent of low-cost space launches and large satellite projects, spacecraft such as space stations are facing increasingly severe collision risks. The research utilizes numerical simulation techniques, based on ANSYS/AUTODYN software and the Smoothed Particle Hydrodynamics (SPH) method, to simulate the impact process of projectiles of different velocities (1 ∼ 10 km/s) and materials (aluminum and steel) on tantalum target plates. The results are intended to provide theoretical support for the design of spacecraft protection structures and contribute data support for establishing a millimeter-level space debris impact database.
Comparison of Drivetrain Vibration Response During Field Operation and on a Nacelle Test Bench
Authors: Siddiqui Muhammad Omer , Eustorgi Karin , Feja Paul
Published: June 2024

Nacelle test benches offer the chance to identify any possible issues in the system design before conducting mandatory field testing for type certification. This can potentially reduce costs and time to market. However, nacelle system testing is an abstraction of the real system, as several interactions and interfaces between the nacelle and its environment are absent. Consequently, this has initiated research studies in recent years to fully understand the influence of these abstractions on the device under test. Extensive research has been conducted on the recently completed project Testfeld BHV to understand the influence of abstractions on the vibration response of the drivetrain. In this project, the Adwen AD8-180 has been the wind turbine under study that was tested first at a nacelle test bench, followed by field tests at a site in Germany. This paper presents the findings of these studies with regards to the drivetrain vibration response during nacelle tests and field tests. The similarities and differences observed in the drivetrain vibration response are highlighted, and reasons that lead to deviations in the vibration response are discussed. Furthermore, the work also presents a simulative framework that can aid the test bench’s ability to predict the correct field-like drivetrain vibration response prior to field tests.
The challenge of cycle-to-cycle variability in dynamic stall modelling
Authors: Damiola Luca , Runacres Mark C. , De Troyer Tim
Published: June 2024

This research explores cycle-to-cycle variability in dynamic stall through wind tunnel experiments conducted on a pitching NACA 0018 aerofoil at a Reynolds number of 2.8×105. Multiple cycles are considered, and different clusters are identified based on inspection of the lift time series. Experiments reveal that the blind application of a conventional phase-averaging approach can produce inadequate results, which do not represent the underlying physics; instead, it is recommended to analyse each cycle individually and use a clustering approach. The available wind tunnel measurements are employed to build two distinct aerodynamic models, i.e. a semi-empirical Goman-Khrabrov dynamic stall model and a purely data-driven model based on artificial neural networks. The work highlights that cycle-to-cycle variability in dynamic stall represents a huge challenge from a modelling perspective. The Goman-Khrabrov model cannot capture the bifurcations in the data, while the more sophisticated data-driven model is accurate but prone to instability. The paper proposes to enhance the accuracy of the models by dynamically assimilating experimental measurements using an Extended Kalman Filter. Results demonstrate that this methodology represents a valuable and versatile tool, which allows to effectively combine imperfect model predictions with experimental observations.
Tuning the Actuator Line Method to Properly Modelling Tip Effects in Finite-Length Blades
Authors: Melani Pier Francesco , Mohamed Omar Sherif , Cioni Stefano , Balduzzi Francesco , Bianchini Alessandro
Published: June 2024

The Actuator Line Method (ALM) is gaining popularity in wind turbine simulations, as it can better handle some of the challenging operating conditions experienced by modern machines, such as highly turbulent inflows, severe aero-elastic forcing, and complex rotor-to-rotor interactions. However, it still falls behind other medium-fidelity methods such as the Lifting Line Free Vortex Wake (LLFVW) when it comes to resolving tip vortices and their effect on the blade spanwise load profile. The reason for such behavior is still unclear. A recent study suggested that this issue can be solved by reducing the scale of the angle of attack (α) sampling and force insertion towards the tip, without the need of additional corrections. This study builds on these findings to further investigate how the ALM base formulation - in terms of α sampling and force insertion - can be tuned to properly describe tip effects. An in-house ALM tool was employed to simulate a finite, constant-chord, NACA0018 wing, for which high-fidelity blade-resolved CFD (BR-CFD) data are available as benchmark. In the first part of the work, different strategies are outlined, including a novel approach for the de-coupling of the angle of attack sampling step from the force projection one, here called DE-coupled LineAverage (DELA). Their accuracy and sensitivity to ALM numerical settings are assessed at a fixed wing pitch angle of 6°. The analysis is then extended to a wider range of blade pitch angles, benchmarking the new ALM formulation against BR-CFD, ALM with the Dağ and Sørensen correction, and LLFVW in terms of blade loads, tip vortex structure, and computational effort.
Potential for large-scale deployment of offshore wind-to-hydrogen systems in the United States
Authors: Brunik K , Thomas J J , Clark C E , Duffy P , Kotarbinski M , Kee J , Grant E , Starke G M , Riccobono N , Koleva M N , Reznicek E P , Barker A , King J
Published: June 2024

This study explores the role of producing low-carbon hydrogen using water electrolysis powered by offshore wind in facilitating the United States’ transition to a net-zero emissions economy by 2050. This research introduces an open-source scenario analysis tool for offshore wind-to-hydrogen systems, aiming to assess the impact of technology, regional considerations, and policy incentives on the cost of producing low-carbon hydrogen through offshore wind. Conducting a regional techno-economic analysis at four U.S. coastal sites, the study evaluates two energy transmission configurations and examines associated costs for the years 2025, 2030, and 2035. The results highlight that locations using fixed-bottom technology may achieve cost-competitive water electrolysis hydrogen production by 2030 through leveraging geologic hydrogen storage and federal policy incentives. Furthermore, floating technology locations are expected to see an average 38% reduction in the levelized cost of hydrogen from 2025 to 2035.
A virtual wind tunnel for deforming airborne wind energy kites
Authors: Wilhelm Poland Jelle Agatho , Schmehl Roland
Published: June 2024

This paper presents a quasi-steady simulation framework for soft-wing kites with suspended control unit employed for airborne wind energy. The kites are subject to actuation-induced and aero-elastic deformation and are described by a coupled aero-structural model in a virtual wind tunnel setup. Key contributions of the present work are a kinetic dynamic relaxation algorithm and a procedure to define a physically consistent initial state. For symmetric actuation, the kite is pitch-statically stable and the simulations converge to a static equilibrium state. Most soft-wing kites are not roll-statically stable and do not find a static equilibrium without a symmetry assumption, as this introduces non-zero roll- and yaw moments. Another important contribution is the introduction of a steady circular flight state that enables convergence without a symmetry assumption. By neglecting gravity, the kite can fly in a perfectly circular turning motion around the wind vector with a constant radius and constant rotational velocity without requiring active control input. In an idealized wind-aligned tether case, the difference in aerodynamic- and centrifugal force application centers makes it impossible to achieve both a force- and moment equilibrium. This was resolved by including an elevation angle that introduces a radial tether force component, which introduces a centrifugal and aerodynamic force difference. Therefore, an operating point with roll equilibrium can be found where the kite finds a static equilibrium, enabling the first quasi-steady simulations of turning flights. Simulated quantifications of soft-wing kite turning behavior, i.e., turning laws, contribute to better kite- and control design.
Lessons learned from the sustainable recycling process of a wind blade made with a new thermoplastic resin
Authors: Carnicero Rafael , Cano Luis , Cruz Ignacio
Published: June 2024

The use of thermoplastic resins instead of thermoset ones in wind turbine blade manufacturing is being investigated and validated in a global scale due to some theoretical improvements such as costs saving during production, shorter cycle’s time and a better circular recovery of the raw materials at the End of Life. The initial objective of this paper was to manufacture and test a small wind turbine blade (SWTB) glass fiber-reinforced thermoplastic (GFRT) resin composites, recycle it, and use the products obtained from the recycling process (fibers and resin) to remanufacture a new thermoplastic SWTB. But loss of fibers higher than estimated during the recycling process made to get away from the original aim of testing both blades (1st and 2nd recyclable blades). At least, some lessons learned were obtained to improve future developments. Nevertheless, this study provides an example of how to recycle a small WT blade and to remanufacture it using the same raw materials.
Numerical study on wake recovery of vertical-axis wind turbines through fixed blade pitch offsets: H vs X rotors
Authors: Ajay Adhyanth Giri , Ferreira Carlos Simao
Published: June 2024

This study assesses the wake recovery mechanism between an H-type Darrieus and an X-type vertical-axis wind turbine, named H-Rotor and X-Rotor respectively for different blade pitch offset configurations. The analysis is conducted in OpenFOAM using the actuator line method to model the turbines to present qualitative (velocity and vorticity contours) and quantitative (available power) studies for three different fixed blade pitch offsets. The results demonstrate that the H-Rotor recovers the wake much faster than the X-Rotor at positive pitch offsets. Overall, applying fixed pitch offsets to VAWT blades helps recover the wake faster than having no blade pitch offset.
Modelling of a Floating-Type Hybrid Wind-Wave System with Oscillating Water Column Wave Energy Converters: A Study Towards Floater Motion Reduction
Authors: Zhu H , Hu C , Yoshida S
Published: June 2024

The integration of floating offshore wind turbines with wave energy converters is regarded as a promising solution for offshore renewable energy development. Given the early stage of wave energy conversion technologies and the substantial influence of control methods on overall system dynamics, a faithful aero-hydro-thermo-elastic-servo-mooring coupled model, along with an engineering environment offering high flexibility for control implementations, is essential. To address the requirement, a numerical modeling framework is developed in this study based on Simulink, known for its superiority in control design and implementation, and OpenFAST, which offers a reliable floating wind turbine model. The model incorporates the thermodynamics of the air in chambers, power take-off dynamics, and oscillating water column dynamics. Furthermore, bypass valves are utilized for the wave energy converters to adjust chamber pressure and reduce floater motion, with a control law proposed to regulate the valve opening ratio. A case study is conducted under harsh ocean conditions to validate the model. The numerical results not only demonstrate the feasibility of the model but also underscore the effectiveness of the control law in improving floater motion performance.
A reduced order/simplified method for uncertainty quantification on the floating wind turbine design basis
Authors: Yildirim B , Dimitrov N , Abrahamsen A B , Kolios A
Published: June 2024

The cost of floating wind turbines (FWTs) is currently higher than onshore and bottom fixed offshore wind turbines. An important step towards more cost-efficient FWT structures is understanding the uncertainties and how they affect the design performance. On the path towards developing a fully probabilistic design approach, an important initial step is defining the variables and uncertainties that significantly impact the final design performance. This study aims to conduct a design sensitivity analysis on a FWT system consisting of the VolturnUS Semisubmersible floater coupled with an IEA 15 MW turbine. First, a Python-based design evaluation framework is implemented that computes operational limit states as a function of design input parameters defining the floater design. The system responses and the loads are obtained using Horizontal Axis Wind turbine simulation Code 2nd generation (HAWC2). Time domain outputs of the design evaluation framework are compared to a frequency domain response using Quick Load Analysis of Floating Wind Turbines (QuLAF). Initial results provide that buoyancy column diameter and the floater radius have the highest effects on the general floater response.
Exploring the Interdependence of Vertical Extrapolation Uncertainties in Repowering Wind Farms
Authors: Mazoyer P , Duc T , Bechmann A , Kariniotakis G
Published: June 2024

Assessing a wind farm’s annual energy production (AEP) involves modelling the wind resource and the wind-to-power conversion at the site. The greenfield pre-construction phase generally comprises the installation of wind measurement devices. For repowering projects, the wind data from the pre-construction phase of the existing farm can be used as wind input to assess the energy yield of the repowered wind farm. Indeed, one study demonstrates that when the modelling error correlations are known, the AEP prediction uncertainty of the repowered farm can be reduced by combining the energy production records of the existing farm with the AEP assessment for both farms. Previous studies have successfully identified the correlation structure for certain errors, especially for horizontal flow modelling, but not for vertical flow modelling. However, vertical extrapolation is essential, as the wind measurement heights are generally lower than the hub height on the repowered farm. This paper bridges this research gap and demonstrates that the correlation structure of errors in vertical profile modelling is Gaussian, with parameters dependent on shear values and heights. The distribution is validated against site data from simple to moderately complex sites in France.
A critical insight into the most effective CFD settings to model atmospheric stability in wind energy applications
Authors: Travaglini Riccardo , Melani Pier Francesco , Balduzzi Francesco , Orlando Stephen , Viti Valerio , Bianchini Alessandro
Published: June 2024

An accurate reconstruction of the Atmospheric Boundary Layer (ABL) is key for the estimation of energy production and loads in modern wind turbines since, at current rotor heights, the vertical structure of the ABL is heavily influenced by thermal stratification effects. The wind power community usually accounts for these effects by semi-empirical modifications to the neutral ABL profile obtained using linear solvers such as WAsP; this approach, however, may not be suitable for sites with complex terrain, time-dependent thermal effects, or dense canopies. In these applications, methods with higher fidelity, such as Computational Fluid Dynamics (CFD) approaches based on steady or unsteady Reynolds Averaged Navier-Stokes (RANS) equations are needed. While CFD is recognized as providing more accurate results for these realistic cases, its use is still not a common best practice. In the current study, the WindModeller CFD tool by Ansys was employed to assess the effect of various inlet boundary conditions on the predicted wind speed profiles in unstable and stable atmospheric conditions. The test case is a wind farm in North Dakota, USA, characterized by a simple terrain but strong atmospheric stability effects and temperature fluctuations. The comparison of CFD results with experimental measurements and WAsP-CFD simulations reveals a high level of agreement between CFD and experimental data in stable conditions. In the case of unstable conditions, despite the good representation of the wind field, a high sensitivity to inlet boundary conditions is highlighted.
An improved statistical wake meandering model
Authors: Brugger Peter , Markfort Corey , Porté-Agel Fernando
Published: June 2024

A new statistical wake meandering (SWM) model is proposed that improves on existing models in the literature. Compared to the existing SWM models, the proposed model has a closed description that does not require simulations to create look-up tables while maintaining applicability to a wide range of flow conditions. The proposed SWM model is compared to the predictions of the Dynamic Wake Meandering (DWM) model and to wind speed measurements from a scanning Doppler lidar mounted on the nacelle of a utility-scale wind turbine for validation. The results show that the proposed model has a similar performance as the DWM model for the effect of wake meandering on the mean velocity deficit and the turbulence intensity, while being significantly faster to compute.
Site-specific production forecast through data-driven and engineering models
Authors: Braunbehrens R , Strecker K , Anand A , Felder M , Petzschmann J , Bottasso C L
Published: June 2024

The present study investigates the predictive capabilities of two site-specific wind power forecasting models. The two approaches make use of a machine learning ensemble model that combines forecasts from several numerical weather predictions (NWP) to match local observations. In the first approach, the training data consists of historical site power production recordings. This yields a black-box model that includes the wind farm behaviour. The second approach is a combination of data-driven and explicit modelling. In the first step, the machine learning ensemble model forecasts the site wind conditions. Then, this input is fed to a site-specific engineering wake model. This hybrid ”grey-box” approach explicitly resolves some farm flow effects.

The study shows that the performance of both methods differs over the wind speed range. The purely data-driven model performs better at medium wind speeds, which also occur more often. The hybrid method predictions agree better during periods of higher wind speeds. In the last part, the study showcases the capabilities of the forecasting methods when participating in the energy market. Additionally, the engineering wake model allows for power maximisation through wind farm control.
Floating wind farm design using social and environmental constraints
Authors: Yilmazlar Kutay , White Craig , Cacciola Stefano , Cândido José , Croce Alessandro
Published: June 2024

This work proposes a wind farm design methodology, integrating several design variables from different design aspects into an optimization problem, such as turbine power, number of turbines, cable types, wind farm layout and site location. A mixed integer genetic algorithm is employed to combine discrete and continuous design variables to find the design with minimum Levelized Cost of Energy (LCoE). The wind farm LCoE is calculated using a wind farm model, which combines detailed cost functions for different cost elements and engineering wake models to estimate Annual Energy Production. The design is constrained not only by technical aspects such as total power, farm area, but also by environmental and social constraints. These include the wind farm visibility, which is a popular concern among the people living along the coast of nearby wind farms, and availability, implying the compliance with the designated exclusion zones. To demonstrate the sensitivity of design constraints, two floating wind farms are sited and optimized as a case study, using different visibility constraints. The developed design tool within this study aims to bridge the gap between wind farm developers and local authorities who are responsible for permitting and zoning of development areas.
Characterisation and Integration of Piezoelectric Trimorph Actuators for Blade Active Surface Control on a Scaled Wind Turbine
Authors: Fuentes Holden J P , Gan L , Sims-Williams D , Gilbert J , Osborne P , Bastankhah M
Published: June 2024

The paper investigates the integration of piezoelectric bending actuators on trailing edge flaps (TEF). The characterisation of piezoelectric actuators is of great importance due to differences in performance resulting from sample variability, actuator construction, circuit type and equipment. For the application of trailing edge flaps in scaled turbines, the total deflection these actuators can produce determines the possible flap angles and, consequently, the potential effects on wake evolution downwind of the wind turbine. In this paper, we fully characterise the performance of the piezoelectric bending actuator under a variety of operating conditions. The bridged bi-polar circuit is used to drive the piezoelectric actuators with both a static and a dynamic signal. Deflection results demonstrate that the piezoelectric actuator is capable of achieving flap angles of β ± 3° with a static signal, and β = 2.3° and β = −3.2° angles with a dynamic signal. Experimental force measurements using a dynamic signal result in a force reduction of up to 33% when compared to a static signal. Force values at increasing frequencies do not show a depreciation in force. Additionally, initial aerodynamic loads exerted on TEF are presented based on XFoil simulations to ensure that the piezoelectric actuating force can overcome aerodynamic loads for future experiments. Experimental force measurements from the piezoelectric actuator demonstrate that aerodynamic forces can be overcome. This work serves as the first step towards implementing the TEF technology in lab-scaled wind turbine models.