Multiple Rotor Research Articles

A Hybridization of CSA DEA Approach for Detection of Multiple Transverse Crack Rotor Shaft Rotating in Fluid Environment under Axial and Bending Loading

A Hybridization of CSA DEA Approach for Detection of Multiple Transverse Crack Rotor Shaft Rotating in Fluid Environment under Axial and Bending Loading

Comprehensive Analysis of Pressure Drop Phenomena in Rotating Packed Bed Distillation: An In-Depth Investigation.

A rotating packed bed (RPB) is an innovative intensification technology that improves its separation capabilities in high-gravity conditions. This process increases efficiency with smaller equipment size and footprint than conventional packed columns. Although significant advancements have been made regarding RPBs, most studies only focused on single or dual rotor configurations in addressing dry pressure drop. Hence, multiple rotor systems in industrial settings can enhance economic efficiency by minimizing the necessity for numerous RPBs. This study investigated the pressure drops and holdup in a three-stage rotor-based RPB under actual process conditions using natural gas as the feed. A novel pressure drop correlation was introduced based on the nitrogen removal process from the natural gas in continuous RPB distillation operations. Consequently, the correlation between centrifugal acceleration, turbulent, and momentum effects demonstrated remarkable accuracy within ±15%. This outcome also highlighted the importance of meticulous design considerations in RPB-based applications due to the complex correlation between centrifugal forces, liquid holdup, and gas flow rates. The reflux feed ratio, liquid holdup, rotating speed, and F-factor effects were examined to comprehend the RPB distillation process. Overall, the correlations between the critical parameters offered crucial insights to prevent process upsets (such as flooding), contributing to advancing RPBs in practical industrial settings.

Multivariate iterative nonlinear chirp mode decomposition: principles and applications

Abstract The rotor-bearing system (RBS) of a hydroelectric unit includes multiple components such as the rotor, rotor shaft, coupling, turbine, and main shaft. There is a strong coupling relationship between the vibration signals of multiple bearing sections. At the same time, the vibration signal of the RBS contains rich frequency components, which can effectively reflect the operating state of the shaft system of the unit. Therefore, synchronous signal analysis across multiple rotor bearing sections is required to completely grasp the operating status of the unit. In this study, the Multivariate Iterative Nonlinear Chirp Mode Decomposition (MINCMD) is proposed to analyze signals on multiple sections simultaneously. MINCMD follows the step-by-step extraction idea of Adaptive Multivariate Chirp Mode Decomposition (AMCMD), but it adopts a new algorithm framework by modifying the objective function. Furthermore, AMCMD does not converge well without a good initial instantaneous frequency (IF). Therefore, a method based on parameterized demodulation (PD) is introduced in MINCMD to solve the multi-channel frequency initialization problem. The effectiveness of the proposed algorithm is verified through a simulation test and real data from hydroelectric units.

Dynamic wake conditions tailored by an active grid in the wind tunnel

Well characterized test environments are required for novel wind turbine and wind farm control concepts. Aeroelastic simulations are mostly used to model turbine aerodynamic and structural response. For wind farm control, also the wake behaviour needs to be represented, including the impacts of dynamic wind direction changes, wake meandering and the interaction of wakes with the atmospheric boundary layer. This paper shows how wake-like inflow conditions can be emulated with an active grid in a wind tunnel, exciting a broad band of turbulent scales. The artificial wake conditions can be used as inflow for an exposed model turbine. A focus is put on the meandering dynamics, which are driven by large transversal turbulence patterns in the atmospheric boundary layer. Following the conjecture of the Dynamic Wake Meandering (DWM) model, such turbulent scales must have the size of multiple rotor diameters, to impact the entire wake deficit like a passive tracer. In conventional wind tunnel experiments, such spatial scale ratios are hard to reach, since wind tunnel sizes are bounded while the model turbines must be sufficiently large to have appropriate aerodynamic scaling and instrumentation. In this work, quasi-stochastic meandering trajectories are created, using scaled Ornstein-Uhlenbeck processes. Thus, the intrinsically stochastic process of wake meandering is made repeatable. The paper focuses at a thorough characterization of the inflow conditions with both lidar and hot-wire measurements, considering wake shape and spectral features. The results show an approximately axi-symmetric Gaussian deficit, which meanders as a coherent structure while having spectral features similar to a turbine wake.

Triple Rotor Vertical Axis Wind Turbine for Low Wind Speed Range Energy Generation

A new triple rotor vertical axis wind turbine (VAWT) is presented to produce electricity efficiently in light winds. Rotors are designed to consume less consistent energy when moving to boost efficiency. The turbine comprises numerous adjustable dual blades, a frame component adjacent to the hub, and a revolving hub in the centre. Each blade has a serrated part and is joined to a frame component. The rotor shaft connects the hub and frame sections mechanically and can spin along its longitudinal axis. A connector also allows rotational movement by connecting multiple rotor components. The movement of the turbine is efficiently transferred to the generator using a magnetically propelled mechanism linked to the turbine.

A method of stall recognition using nonlinear feature extraction from the compressor outlet pressure

The paper presents a method for analysing the pressure signal at the compressor outlet, which allows to detect when the machine operating point approaches the area where a stall is about to occur. The signal analysis method is based on nonlinear feature extraction from the dynamic signal. The correlation dimension (dcorr) is used to quantify the complexity of the measured signal, its value decreasing if the analysed signal originates from deterministic processes. The results presented indicate that the correlation dimension of the signal decreases at flow rates approximately 10% above the flow rate at which negative effects on machine performance occur. This trend has been observed across multiple rotor speeds. These findings suggest that the perturbations associated with the onset of the stall can propagate to the compressor outlet, leading to less chaotic pressure behaviour that reflects the dynamics of these perturbations. The fact that stall can be identified from the pressure signal in the space between the rotor and the diffuser in its early stages is well known, but the possibility of identifying stall at the compressor outlet, where the perturbations are significantly attenuated, has not been documented in the literature.

Experimental investigations on aerodynamic and psychoacoustic characteristics of three-blade looprop propeller

Aeroacoustic noise in multiple rotor drones has been increasingly recognized as a crucial issue. This study focuses on addressing this challenge by introducing a novel low-noise looprop propeller design with three blades. Unlike traditional propellers, the looprop propeller utilizes three closed-loops to generate thrust. Through comprehensive experimental investigations conducted in an anechoic chamber using a hover stand test, we conducted an integrated study of the propeller's aerodynamic, aeroacoustic, and psychoacoustic characteristics. The results demonstrate that the three-blade looprop propeller achieves a notable reduction in the overall sound pressure level (OASPL), particularly in tonal noise at the blade passing frequency where the tone reduction amounts to approximately 15 dB. Additionally, we employed Zwicker psychoacoustic annoyance models to evaluate the propellers' psychoacoustic performance and discussed the environmental noise mask effect. The findings indicate that the three-blade looprop propeller exhibits an improved sound quality while maintaining aerodynamic performance comparable to that of conventional propellers. Overall, our study suggests that the looprop propeller design offers significant advancements in acoustic performance, particularly in terms of psychoacoustic characteristics. These findings hold promising implications for the field of drone technology and the potential for notable improvements in noise reduction.

Multi-fault classification of rotor systems based on phase feature of axis trajectory in noisy environments

As it is difficult to distinguish multiple rotor faults with similar dynamic phenomena in noisy environments, a multi-fault classification method is proposed by combining the extracted trajectory phase feature, a parameter-optimized variational mode decomposition (VMD) method and a light gradient boosting machine (LightGBM) model. The trajectory phase feature is extracted from an axis trajectory by fusing the frequency, amplitude, and phase information related to rotor motion and can comprehensively describe the dynamic characteristics induced by different rotor faults. First, the vibration displacement signals in two orthogonal directions are collected to construct the axis trajectories with 12 rotor states including healthy, unbalance, misalignment, single crack, multiple cracks, and a mixture of them. Second, the trajectory phase feature is extracted from the vectorized axis trajectories, and the frequency spectra of trajectory phase angles under different rotor faults are analyzed through Fourier transform. Finally, a parameter-optimized VMD method combined with a LightGBM model is applied to classify multiple faults of rotor systems in different noisy environments based on the extracted trajectory phase feature. The 12 rotor states can be classified into nine categories based on the harmonic information of 1X–7X components (X is the rotating frequency of a rotor system) and other components with smaller amplitudes in the frequency spectra of trajectory phase angles. The average classification accuracy of the 12 rotor states exceeds 93.0%, and the recognition rate for each kind of fault is greater than 77.5% in noisy environments. The simulated and experimental results demonstrate the effectiveness and adaptability of the proposed multi-fault classification method. This work can provide a reference for the condition monitoring and fault diagnosis of rotor systems in engineering.

Integrated Evaluation of the Aeroacoustics and Psychoacoustics of a Single Propeller.

Aeroacoustic noise in multiple rotor drones has been increasingly recognized as a crucial issue, while noise reduction is normally associated with a trade-off between aerodynamic performance and sound suppression as well as sound quality improvement. Here, we propose an integrated methodology to evaluate both aeroacoustics and psychoacoustics of a single propeller. For a loop-type propeller, an experimental investigation was conducted in association with its aerodynamic and acoustic characteristics via a hover stand test in an anechoic chamber; the psychoacoustic performance was then examined with psychoacoustic annoyance models to evaluate five psychoacoustic metrics comprising loudness, fluctuation strength, roughness, sharpness, and tonality. A comparison of the figure of merit (FM), the overall sound pressure level (OASPL) and psychoacoustic metrics was undertaken among a two-blade propeller, a four-blade propeller, the loop-type propeller, a wide chord loop-type propeller, and a DJI Phantom III propeller, indicating that the loop-type propeller enables a remarkable reduction in OASPL and a noticeable improvement in sound quality while achieving comparable aerodynamic performance. Furthermore, the psychoacoustic analysis demonstrates that the loop-type propeller can improve the psychological response to various noises in terms of the higher-level broadband and lower-level tonal noise components. It is thus verified that the integrated evaluation methodology of aeroacoustics and psychoacoustics can be a useful tool in the design of low-noise propellers in association with multirotor drones.

Effect of Stator Blades on the Startup Dynamics of a Vertical Axis Wind Turbine

Vertical Axis Wind Turbines (VAWTs) are omni-directional, low-cost, low-efficiency wind power extractors. A conventional drag-based VAWT consists of multiple thin rotor blades with a typical peak Tip Speed Ratio (λ) of < 1. Their lower cut-in speed and maintenance cost make them ideal for power generation in urban environments. Numerous studies have been carried out analysing steady operation of VAWTs and quantifying their performance characteristics, however, minimal attention has been paid to their start-up dynamics. There are a few recent studies in which start-up dynamics of lift-based VAWTs have been analysed but such studies for drag-based VAWTs are severely limited. In this study, start-up dynamics of a conventional multi-blade drag-based VAWT have been numerically investigated using a time-dependant Computational Fluid Dynamics (CFD) solver. In order to enhance the start-up characteristics of the drag-based VAWT, a stator has been integrated in the design assembly. The numerical results obtained in this study indicate that an appropriately designed stator can significantly enhance the start-up of a VAWT by directing the flow towards the rotor blades, leading to higher rotational velocity (ω) and λ. With the addition of a stator, the flow fields downstream the VAWT becomes more uniform.

Design and simulation of an Unmanned Aerial Vehicle based on a motor glider concept

Due to the miniaturization of optoelectronic devices, the increase in computing power, and the improvement of control systems and navigation systems, Unmanned Aerial Vehicles (UAVs) have become an indispensable tool in areas such as agriculture, industry (critical infrastructure inspection), and surveying. These systems are available in fixed-wing and rotary-wing (multiple rotors) configurations. The multiple rotor system is characterized by advantages such as vertical take-off and landing and simplicity of the structure design and control algorithm. Still, there are also disadvantages: the short flight time and very high energy consumption. Based on the requirement for a platform with high reliability and high flight range, the paper proposes a solution for fixed-wing UAVs with an extended flight time, self-launching, short landing, and optimized energy consumption. The presented solution is inspired by the model of the Romanian glider IS-28B2 produced by ICA Ghimbav, which has been redesigned and optimized to become a 1:10 scale UAV type glider. The paper presents the 3D model design, simulation, and optimal autopilot integration for this robotic aerial system.

Application of multi-base fusion generalized chirplet basis transform in vibration signal analysis of multiple rotor rotating machinery

In rotating machineries, there are many signals with multiple nonproportional fundamental frequencies such as the vibration response signal from a dual rotor aeroengine, where the speeds of the high-pressure turbine and the low-pressure turbine are not synchronized. The conventional Chirplet transform (CT) based time–frequency analysis (TFA) methods are capable of processing nonstationary signals mixed with multiple synchronous components, or proportional frequency components, but not suitable for processing the nonstationary signals with multiple nonproportional fundamental frequencies. This paper presents a novel nonstationary signal TFA method, referred to as General Chirplet Basis Transform (GCBT), which is designed for processing nonstationary signals with multiple nonproportional fundamental frequencies. In the proposed GCBT, the local maximum value search method is utilized to find out all the Chirplet basis function parameters matched with the fundamental frequencies of each harmonic group contained in the signal. Then, the time–frequency representation (TFR) fusion criterion is established to effectively combine the TFA results of all the discovered Chirplet basis functions. The effectiveness and superiority of the GCBT are demonstrated by analyzing a simulation signal, the vibration signals collected in the laboratory using two independently operated small rotors, and the vibration signals from an aeroengine test. All the results indicate that the proposed GCBT has the ability to handle multi-component signals with nonproportional fundamental frequencies, synchronous frequencies, closely-spaced frequencies, as well as the signals with sever noise backgrounds.

A Balancing Method for Multi-Disc Flexible Rotors without Trial Weights

Rotor dynamic balancing is a classical problem. Traditional balancing methods such as the influence coefficient method and the modal balancing method, have low balancing efficiency because they need to run many times to add trial weights. Although the model-based balancing method improves the balancing efficiency, it cannot accurately identify the position, amplitude and phase of each unbalance fault for rotors with multi-disc structures, so it is difficult to apply it to actual balancing. To solve the above problems, based on the traditional modal balancing theory, this paper deduces that the continuous and isolated unbalance in the rotor-bearing system can be represented by isolated unbalance on several balancing planes approximately. The model-based method is used to identify the above-mentioned equivalent isolated unbalances, and then the corrected mass is added to the balancing planes so as to complete the balance of multiple flexible rotor without trial weights. Considering the practical situation, the proposed balancing method includes two steps: low-speed balancing and high-speed balancing. The proposed balancing method is verified using three and four-disc rotors. The simulation results show that the balancing method can effectively reduce the vibration of the flexible rotor after low-speed and high-speed balancing, and the amplitude at the measurement point is reduced by 79.74~97.60%, respectively.

Transient nature of secondary vortices in an axial compressor stage with a tandem rotor

An efficient and compact design of a compressor continues to be a challenging area of research. The unavoidable streamwise adverse pressure gradient together with passage transverse pressure gradient restricts the maximum allowable blade turning. Tandem blading is an interesting concept for increasing the pressure rise by permitting a higher blade turning angle. The energized flow through the tandem blade nozzle gap helps to minimize the possibility of flow separation over the suction surface of the aft blade. However, a coherent transient analysis of a tandem rotor stage in an axial compressor is yet to be well explored. In the present paper, the complex flow field over a tandem rotor and the succeeding stator passage is analyzed in detail. Although the tandem rotor increases the flow turning and diffusion effect, the presence of separate trailing edge wakes and hub corner vortex causes early onset of flow separation over the stator suction. The flow structures developed within the rotor and the stator passages at different time instances are highlighted with the help of limiting streamlines and iso-surface Q-criterion superimposed with entropy contours. The results indicate that within the rotor passage, transient flow features are observed near the hub corner region close to the aft blade trailing edge rather than the tip region. When the rotor passes the stator leading edge, the rotor trailing edge leakage flow at the hub is entrained into the stator leading edge reverse flow region. This is then further circumferentially dragged into the mid-passage region. The interference of multiple rotor wakes with the stator leading edge leads to the formation of longitudinal and arch like separation vortices at the stator-hub and the stator-casing regions, respectively. These separation vortices grow in size while being convected downstream. Eventually, as time progresses, the vortices split and shed periodically from the stator surface. The present investigation highlights the requirement of a new stator design in a tandem rotor–conventional stator configuration. Such designs could further magnify the significant aerodynamic performance obtained using a tandem configuration.

Orthogonal vortices characteristic, performance evaluation and classification mechanism of a horizontal classifier with three rotor cages

Horizontal classifiers with multiple rotor cages have competitive advantages of larger process capacity and smaller cut size. This study represents the gas-solid simulation, performance evaluation and classification mechanism of a horizontal classifier with three rotor cages. The gas turbulence was modeled using the Reynolds stress model (RSM), and the particle flow was predicted by the dispersed phase model (DPM). More than fifty operating conditions were analyzed for the performance evaluation. A schematic map showing the gas-solid flow dynamics was constructed. It was found that three rotating gas screen are independently induced and evenly distributed around the rotor cages. The M-shaped axial and tangential velocities have strong shear and washing effect on the near-wall particle. The maximum particle residence time of the cut size can be hundreds of seconds. The experimental cut sizes range from 7.2 μm to 25.7 μm with high classifying sharpness index (>55%) and superfine particle yield (>71%).

Case studies on performance prediction of radial inflow turbine under multiple rotor structures and organic fluids

Due to the lack of selection criteria for the ORC radial inflow turbine's loss models, and information about the models' limitations. This paper presents a comprehensive analysis for performance prediction of the ORC radial inflow turbine, and a novel turbine performance prediction program is proposed. This study can be divided into two parts, during the analysis part, 125 cases of CFD simulation were conducted under 5 rotor structures and R245fa as the working fluid. The performance of 6 loss models and their 18 combinations were compared. And in the examination part, another three organic fluids from different categories were chosen to exam the reliability of the proposed prediction program. The results show that loss model combinations E, O, and Q have a good performance in rotor loss prediction. Besides, Δβ4 has an important influence on prediction reliability and turbine performance, it should be lower than a certain value (about 40° in this paper) during the analysis process to get relatively reliable results under different rotor structures. The proposed program can realize an acceptable accuracy for turbine performance prediction under multiple organic fluids and rotor structures, with an efficiency deviation within ±5% and an output power relative error within ±10%.

Reconceptualising Atrial Fibrillation Using Renewal Theory: A Novel Approach to the Assessment of Atrial Fibrillation Dynamics.

Despite a century of research, the mechanisms of AF remain unresolved. A universal motif within AF research has been unstable re-entry, but this remains poorly characterised, with competing key conceptual paradigms of multiple wavelets and more driving rotors. Understanding the mechanisms of AF is clinically relevant, especially with regard to treatment and ablation of the more persistent forms of AF. Here, the authors outline the surprising but reproducible finding that unstable re-entrant circuits are born and destroyed at quasi-stationary rates, a finding based on a branch of mathematics known as renewal theory. Renewal theory may be a way to potentially unify the multiple wavelet and rotor theories. The renewal rate constants are potentially attractive because they are temporally stable parameters of a defined probability distribution (the exponential distribution) and can be estimated with precision and accuracy due to the principles of renewal theory. In this perspective review, this new representational architecture for AF is explained and placed into context, and the clinical and mechanistic implications are discussed.

Dual-convolutional neural network based aerodynamic prediction and multi-objective optimization of a compact turbine rotor

With the development of neural network technology, surrogate models and dimensionality reduction strategies based on machine learning have become the research hotspots of aerodynamic shape optimization recently. In order to further improve the accuracy and interpretability of the traditional surrogate models, this research establishes a deep learning model, named Dual Convolutional Neural Network (Dual-CNN) for the aero-engine turbines. The aerodynamic performances are predicted and the pressure, temperature fields are reconstructed for multiple rotor profile conditions. The prediction of efficiency is compared with the accuracy of Gaussian Process Regression (GPR) and Artificial Neural Network (ANN) models. The results show that the proposed Dual-CNN model can accurately reconstruct the fields, thus interpreting the mechanism for the change of aerodynamic performance. Dual-CNN is more accurate than GPR and ANN in predicting efficiency and torque, whose error is within an acceptable range of optimization. Then, efficiency and torque are selected as the objective functions to perform a gradient-based multi-objective optimization by the automatic differentiation method and a Pareto solution is obtained. The trained Dual-CNN provides rapid and accurate prediction of performance without CFD calculation in the optimization. Finally, the sensitivity to train size is analyzed for the Dual-CNN model, which indicates that the sampling of 1500 cases for eight design variables in this dataset enables Dual-CNN to achieve favorable effect of field reconstruction and performance prediction.

Multiple rotor modes and how to trigger them: complex cation ordering in the family of relaxing hybrid formates.

A combination of structural, dielectric and calorimetric studies is used to describe a highly atypical behaviour of novel hybrid formate [NH3(CH2)3NH2(CH2)3NH3][Mn(HCOO)3]3, incorporating large triprotonated molecular cations. Two successive phase transitions, switching between fast multiple rotor modes, and the surprising probable coexistence of static and dynamic disorder are discussed for this compound.

A Study on Improvement of Performance of a Multiple Rotor Drone

A Study on Improvement of Performance of a Multiple Rotor Drone