Complex Coupling Research Articles

Electromagnetic duality for line defect correlators in $$ \mathcal{N} $$ = 4 super Yang-Mills theory

Abstract We study particular integrated correlation functions of two superconformal primary operators of the stress tensor multiplet in the presence of a half-BPS line defect labelled by electromagnetic charges (p, q) in $$ \mathcal{N} $$ N = 4 supersymmetric Yang-Mills theory (SYM) with gauge group SU(N). An important consequence of SL(2, ℤ) electromagnetic duality in $$ \mathcal{N} $$ N = 4 SYM is that correlators of line defect operators with different charges (p, q) must be related in a non-trivial manner when the complex coupling τ = θ/(2π) + $$ 4\pi i/{g}_{\textrm{YM}}^2 $$ 4 πi / g YM 2 is transformed appropriately. In this work we introduce a novel class of real-analytic functions whose automorphic properties with respect to SL(2, ℤ) match the expected transformations of line defect operators in $$ \mathcal{N} $$ N = 4 SYM under electromagnetic duality. At large N and fixed τ, the correlation functions we consider are related to scattering amplitudes of two gravitons from extended (p, q)-strings in the holographic dual type IIB superstring theory. We show that the large-N expansion coefficients of the integrated two-point line defect correlators are given by finite linear combinations with rational coefficients of elements belonging to this class of automorphic functions. On the other hand, for any fixed value of N we conjecture that the line defect integrated correlators can be expressed as formal infinite series over such automorphic functions. The resummation of this series produces a simple lattice sum representation for the integrated line defect correlator that manifests its automorphic properties. We explicitly demonstrate this construction for the cases with gauge group SU(2) and SU(3). Our results give direct access to non-perturbative integrated correlators in the presence of an ’t Hooft-line defect, observables otherwise very difficult to compute by other means.

Magnetoelectric Coupling in a Mn4Na-Organic Complex under Pulsed Magnetic Fields up to 73 T.

Research on the magnetoelectric (ME) effect (or spin-electric coupling) in molecule-based magnetic materials is a relatively nascent but promising topic. Molecule-based magnetic materials have diverse magnetic functionalities that can be coupled to electrical properties. Here we investigate a realization of ME coupling that is fundamental but not heavily studied─the coupling of magnetic spin level crossings to changes in electric polarization. A mixed-valence Mn4Na complex with a total ground-state spin S = 5/2 under zero magnetic field and S = 17/2 under high magnetic field undergoes a cascade of ground-state level crossings of the Sz states with increasing magnetic field. Magnetization and electrical polarization measurements under pulsed magnetic fields up to 73 T show that each spin level crossing is accompanied by a significant change in electric polarization that is an even function of the applied magnetic field. A molecular Hamiltonian describing antiferromagnetic exchange in a distorted tetrahedron of three MnIII and one MnII ions matches the data well. We conclude that the ME coupling is caused by magnetostriction within the polar molecule as it distorts to lower its magnetic exchange energy.

Listening to heart sounds through the pressure waveform.

Non-invasive diagnostic modalities are integral to cardiovascular care; however, current systems primarily measure peripheral pressure, limiting the breadth of cardiovascular prognostication. We report a novel approach for extracting left side heart sounds using a brachial cuff device. The technique leverages brachial cuff device enhanced signal resolution to capture pressure fluctuations generated by cardiohemic system vibrations, the sound pressure waveform. We analyze left heart catheterization data alongside simultaneous brachial cuff device measurements to correlate sound pressure waveform features with left ventricle (LV) contractility. The extracted sound pressure waveform reveals two prominent oscillatory wave packets, termed WP1 and WP2, originating from cardiac structure vibrations associated with LV contractions and relaxation. We demonstrate that WP1 originates from LV contraction during systolic blood ejection through the aortic valve (AV) and is correlated with LV isovolumetric contraction, clinically measured by LV dPdt-max (Pearson-R = 0.65, p < 0.001). Additionally, we show that WP2 comes from LV elongation required for blood flow deceleration at the end of systole, causing AV closure, and is correlated with LV isovolumetric relaxation, measured by LV ndPdt-max (Pearson-R = 0.55, p < 0.001). These findings highlight the value of cuff sound pressure waveforms in providing insights about dynamic coupling of the LV-Aorta complex for non-invasive assessment of LV contractility.

Assessing running safety of high-speed trains on long-span cable-stayed bridges based on in-situ monitoring data

This paper presents a new method for assessing the running safety of high-speed trains passing through long-span cable-stayed bridges based on in-situ monitoring data. The monitoring data include the girder vertical deflection and girder-end rotation of bridges. Vertical deformation is utilized to derive the vertical acceleration formula of high-speed trains, and girder-end rotation is utilized to judge the arrival time of the train. According to the specified vertical acceleration limit of the train, the vertical deflection threshold of the bridge is derived from the vertical acceleration formula. The first derivative of the sinusoidal half-wave function of the side-span is utilized to obtain the girder-end rotation threshold, and the safety threshold system is established. The bridge deformation safety threshold system is then used to assess the running safety of the bridge. To verify the presented method, the bridge deformation thresholds calculated using the proposed method are compared with finite element analysis results. The proposed method avoids complex train-bridge coupling numerical simulation in acquiring the dynamic response of high-speed trains, largely improving computation efficiency and enabling real-time assessment of train safety.

Investigation of the aerodynamic performance of the dragonfly-inspired tandem wings considering the coupling between the stroke plane and phase difference

The dragonfly's tandem wings can make full use of the interference of various spatial vortices to obtain efficient flight capability. The complex coupling among multiple motion parameters will have an important influence on the interference between the forewing (FW) and hindwing (HW). In this paper, the aerodynamic performance of the dragonfly-inspired tandem wings is analyzed using the Computational Fluid Dynamics (CFD) method considering the coupling effect of the stroke plane and phase difference. The variation of the force coefficient, vortex structure and aerodynamic efficiency of the tandem wings in forward flight are analyzed, respectively. The results show that the stroke plane angle affects the distribution of the leading edge vortex (LEV) and trailing edge vortex (TEV), which primarily controls the trend of horizontal force variation. The phase difference of tandem wings will change the fluctuation of the horizontal force coefficient curve by affecting the meeting time of the forewing and hindwing. However, with the increase of stroke plane angle, the fluctuation of aerodynamic coefficient caused by phase difference will decrease. The propulsion efficiency(η) and power loading(PL) can be improved through increasing the stroke plane angle and selecting a reasonable phase difference. The conclusion can provide theoretical guidance for the design of the dragonfly-inspired tandem flapping wing aircraft (DTFWA) and the choice of motion parameters.

Dual‐port network‐based impedance modelling and AC‐port characteristic analysis of wound rotor synchronous machine for more electric aircraft

AbstractDue to the increasing variety of converters in more electric aircraft (MEA), the stability of the MEA power system has become a critical issue that receives wide concerns. As the primary power source for MEA, the wound rotor synchronous machine (WRSM) greatly affects the stability of the whole power system, and therefore accurate modelling of the WRSM serves as the basis for the analysis of system characteristics and even stability. Nevertheless, the complex structure and coupling of WRSM bring great challenges to small‐signal modelling methods. This paper introduces a novel method to model the WRSM in a modular and cascaded manner. Instead of deriving the complex transfer function, the proposed method uses a dual port to model each component. By connecting the dual port of each component from the rear stage to the front stage in a cascaded way, a dual‐port network can be built to describe the external impedance characteristics of the WRSM. Kirchhoff law can be applied to calculate the impedance by circumventing the complicated decoupling process. The proposed dual‐port network model has been validated on a hardware‐in‐loop platform. Furthermore, the output impedance characteristics of the AC port has also been analysed with the proposed model.

Evaporation, spreading, and possible uptake of droplets on sorghum (Sorghum bicolor) and cowpea (Vigna unguiculata) leaves using an imaging-based technology.

Sprayed agrochemical droplets have a dynamic evolution on the leaf surface, undergoing changes in shape and volume due to spreading, evaporation, and adsorption. To better understand these processes, an accessible imaging-based experimental methodology is presented to precisely measure droplet spreading, evaporation, and potential uptake by a leaf within a controlled relative humidity environment. Laboratory experiments were conducted to determine the effect of hydrocarbon surfactants, accelerators (light mineral oil), and humectants (high fructose corn syrup) on droplet spread, evaporation, and potential uptake when applied to sorghum (Sorghum bicolor 'Tricker') and cowpea (Vigna unguiculata) leaves. Experiments on cowpea leaves showed uniform spreading and no change in evaporation compared to the predicted rate. In contrast, on sorghum leaves, results suggest that the volume loss rate exceeds the predicted evaporation rate (up to 23%), indicating a potential uptake by the leaves. Some accelerated dynamics on sorghum can be attributed to the lateral spreading observed on hairy leaves along the veins, increasing the contact area by an average of 65%. However, samples containing light mineral oil, typically considered an accelerant to aid in uptake, demonstrated the highest rate but exhibited minimal spreading. The study demonstrates how droplet composition affects droplet dynamics on waxy and hairy leaves by using an imaging-based methodology to measure evaporation rates, volume loss, contact angle, wetted area, and spreading behavior. The findings highlight some of the complex coupling between the crop protection product composition and droplet life cycle on a leaf. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Holocene aeolian-fluvial interactions patterns and their response to climate changes in the Paiku Co basin, Southern Tibetan Plateau

Aeolian-fluvial processes are crucial in shaping landforms. Despite the advancements in understanding the sedimentary processes of aeolian-fluvial interactions, the sedimentary patterns of these interactions are complex in spatiotemporal scale, and the records of Holocene small-scale aeolian-fluvial interaction sedimentary is insufficient, especially in the Tibetan Plateau region. Therefore, this study focuses on analyzing the sedimentary patterns of aeolian-fluvial interactions and their response to climate change in the Paiku Co basin of the southern Tibetan Plateau (TP). Through the examination of aeolian-fluvial sequences, Optically Stimulated Luminescence (OSL) dating is utilized to establish a chronological framework. Furthermore, proxy indices are explored to identify potential sediment models and their reactions to climate change. The findings indicate that fluvial activity predominated during a relatively warm and wet period around 5.1–4.6 ka, while thicker aeolian sands accumulated extensively during 4.6–4.1 ka as the climate transitioned to cold and dry conditions. On a millennial scale, the aeolian-fluvial interaction sedimentation is characterized by alternating deposition of clay layers and medium to fine sand. This sedimentation pattern is predominantly influenced by climate change. Overall, the findings shed light on the complex coupling between aeolian and fluvial processes in response to past climate changes, which has important implications for understanding the landscape evolution and environmental changes in this sensitive high-altitude region.

Hierarchically‐Interlocked, Three‐Axis soft Iontronic Sensor for Omnidirectional Shear and Normal Forces

AbstractArtificial tactile sensing capable of measuring shear and normal forces is crucial for the diverse human‐machine interactions and dexterous robotic manipulations. However, existing soft multi‐axis force sensors usually suffer from limited detectable directions and complex coupling mechanisms, limiting their applications in realistic wearable and robotic systems. Here, a hierarchically‐interlocked, three‐axis soft iontronic sensor is presented with an asymmetrical electrode pattern that leverages the mortise‐and‐tenon structure and ultracapacitive principle to detect omnidirectional shear and normal forces. The designed sensor facilitates the decoupling process and achieves enhanced sensing performances including high accuracy, fast response ability, and mechanical robustness. Prototypical integration and application of the sensor are demonstrated to perform wearable telecontrol of virtual platforms and assist robot gripper through closed‐loop force feedback. A sensing array is further developed to construct a touch panel and identify handwriting based on the continuously measured directions of applied forces. This work may offer a potentially promising solution for the next‐generation intelligent electronic skins requiring multimodal tactile sensing information.

Research on operating characteristics of V-shaped ultrasonic motor based on improved electromechanical coupling model

Abstract As a complex electromechanical coupling system, evaluating the motion characteristics of an ultrasonic motor via an accurate theoretical model is challenging due to the strong coupling between its electrical and mechanical properties. To address this issue, the paper first establishes a complete dynamic model of the V-shaped ultrasonic motor (VUSM). In contrast to the traditional dynamic model, the proposed model incorporates the centroid vibration of the stator and applies the weighted residual method to reduce the computational complexity by simplifying the dynamic model from infinite-dimensional degrees of freedom to two degrees of freedom. Subsequently, the finite element method is employed to determine the vibration mode of the stator structure and derive the two-phase operational mode of the motor. Using these two-phase working modes, the model is then solved to predict the motor's output characteristics under any operational condition. Furthermore, an electrical model accounting for preload nonlinearity was developed based on the dynamic model and compared with the model without considering preload nonlinearity, supported by experimental verification. The findings demonstrate that the established dynamic model and electrical model can accurately simulate the changing laws of the input and output characteristics of the motor, which provides assistance for the subsequent operation status evaluation of the motor and fault diagnosis during operation.

Multiple Load Forecasting of Integrated Renewable Energy System Based on TCN-FECAM-Informer

In order to solve the problem of complex coupling characteristics between multivariate load sequences and the difficulty in accurate multiple load forecasting for integrated renewable energy systems (IRESs), which include low-carbon emission renewable energy sources, in this paper, the TCN-FECAM-Informer multivariate load forecasting model is proposed. First, the maximum information coefficient (MIC) is used to correlate the multivariate loads with the weather factors to filter the appropriate features. Then, effective information of the screened features is extracted and the frequency sequence is constructed using the frequency-enhanced channel attention mechanism (FECAM)-improved temporal convolutional network (TCN). Finally, the processed feature sequences are sent to the Informer network for multivariate load forecasting. Experiments are conducted with measured load data from the IRES of Arizona State University, and the experimental results show that the TCN and FECAM can greatly improve the multivariate load prediction accuracy and, at the same time, demonstrate the superiority of the Informer network, which is dominated by the attentional mechanism, compared with recurrent neural networks in multivariate load prediction.

Energy management with adaptive moving average filter and deep deterministic policy gradient reinforcement learning for fuel cell hybrid electric vehicles

Fuel cell hybrid electric vehicles (FCHEV) with battery (BAT) and supercapacitor (SC) advance in flexible configuration and high energy efficiency. However, the complex coupling relationship among various power sources poses a severe challenge to the design of the energy management system (EMS), including multi-degrees of freedom power allocation, fuel economy, and power sources lifespan of the FCHEV. This paper proposes an EMS based on a dual-layer power distribution structure. In the upper layer, adaptive moving average filter (AMAF) is designed to separate different frequency power, where the energy supply of the SC is managed to attenuate fluctuating power and simplifies the optimization problem and reduces computational costs. The lower layer is constructed by the deep deterministic policy gradient (DDPG) algorithm, where fuel cell system (FCS) hydrogen consumption and degradation rewards are designed to simultaneously enhance fuel efficiency and degradation performance by regulating the FCS real-time power variation. The proposed strategy has been evaluated regarding FCHEV fuel economy and FCS durability under combined driving cycle simulation, which shows AMAF + DDPG strategy reduces fuel consumption by 7.24 % and 1.3 %, also the degradation reduces by 0.04 % and 0.02 % compared with different EMS. Simulation results demonstrate that AMAF + DDPG optimizes the output characteristics of power sources.

A chiral limit for Chern-Simons-matter theories

Large N quasi-fermionic Chern-Simons-matter theories have an approximate higher-spin symmetry that strongly constrains their correlation functions. In particular, the 3-point functions for generic spins are combinations of 3 structures (with specific dependence on the positions and helicities), and the coupling-dependence of the coefficient of each structure is uniquely determined. In the past few years, several relations between different structures were found. In this paper we show that all the relations between the structures follow from (or, conversely, they imply) a specific form written by Skvortsov for the vertices of the dual higher-spin gravity theory on four-dimensional anti-de Sitter space, when written in spinor-helicity variables. The dual bulk theory has a specific limit where it simplifies and becomes a “chiral higher-spin gravity theory”, and we discuss what can be said about this limit in the dual Chern-Simons-matter theories, where it involves an analytic continuation to complex couplings.

Simulation of the pulsed streamer discharge in water considering the effect of hydrostatic pressure

Streamer discharge is a very complex multi-scale and multi-physics coupling process, and there is no accurate model that can describe its development. In this paper, a two-dimensional axisymmetric fluid model is established in COMSOL to simulate and study the effects of the applied voltage amplitude, the discharge gap distance, the rising edge of pulse voltage, and hydrostatic pressure on the development of the positive streamer discharge at a needle-plate electrode in water under a nanosecond pulse voltage. The results show that increasing the voltage amplitude, decreasing the pulse rise time, and narrowing the discharge gap all increase the electric field strength of the streamer, thereby affecting the electron density of the plasma channel, among which changing the discharge gap has the greatest effect on the electron density. And under the gap of 3 mm, the peak electron density can reach 3.76 × 1023 m−3; if the discharge gap is narrowed to 1 mm, the peak electron density is reduced to 1.20 × 1023 m−3. In addition, hydrostatic pressure and water molecule spacing are closely linked. Increasing the hydrostatic pressure decreases the electric field strength and the peak electron density in the plasma channel, and its effect on the peak electron density saturates with increasing hydrostatic pressure.

Defect classification and quantification method based on AC magnetic flux leakage time domain signal characteristics

Pipelines play a crucial role in industries such as petroleum and nuclear power, where non-destructive testing is essential. Magnetic flux leakage testing methods are widely used for pipeline inspection due to their ability to detect both internal and external defects. However, accurately classifying and evaluating the size of such defects poses challenges due to the complex coupling relationship between ferromagnetic materials and defect magnetic fields. This paper proposes a method for defect classification and quantification based on the time domain characteristics of AC magnetic flux leakage signals. Firstly, the paper explores the shielding effects caused by transient high magnetic permeability within the material on signals from internal defects. It analyzes the differences in signals between internal and external defects. Then, based on the nonlinear attributes of defect signals, the paper proposes a defect classification method based on derivatives analysis of the windowed time-domain signal. Moreover, the study finds that rising time and zero-crossing time can be used to assess the depth of internal and external defects separately, which can decouple the width and depth. Finally, experimental validation confirms the effectiveness of defects classification and quantification. This paper provides a feasible method for evaluating the defect of ferromagnetic materials.

Domain reinforcement feature adaptation methodology with correlation alignment for compound fault diagnosis of rolling bearing

In the long-term operation process, rolling bearings often have multiple single faults or cascade faults, which are coupled with each other to form the compound fault. The complex coupling components of compound fault lead to difficultly building a correlation between compound fault feature and fault class. Moreover, for the transfer learning based on domain adaptation, compound fault feature of source domain is pretty different from that of target domain, thus knowledge of source domain is hard to be transferred into the cross-domain unsupervised learning process of target domain. To solve above mentioned problems well, this paper proposes a domain reinforcement feature adaptation methodology with correlation alignment (CA-DRFA) to complete the cross-domain compound fault diagnosis of bearings. Specifically, a deep reinforcement learning model is improved by being combined with the domain adversarial training way, and meanwhile the correlation alignment metrics is adopted to enhance the generalization performance in feature alignment. In addition, a laboratory experiment and an engineering application are performed to demonstrate that CA-DRFA outperforms other popular cross-domain fault diagnosis methods in cross cutting condition and speed transfer tasks. Overall, CA-DRFA is able to implement cross-domain compound fault diagnosis with high accuracy, and effectively reduce the cost of labeling samples.

Efficient property-oriented design of composite layups via controllable latent features using generative VAE

Fiber-reinforced composites provide substantial tailoring potential, while the extensive parameters and complex coupling mechanisms pose formidable challenges to layup designs. This paper presents an efficient inverse design framework for composite layups utilizing a variational autoencoder (VAE), which is applicable to non-conventional laminates. By leveraging the VAE's exceptional feature extraction and generative capabilities, the decoder rapidly produces layups with desired properties through controllable feature vectors. Based on the stacking characteristics of layups, multi-scale one-dimensional convolutions precisely extract sequence features relevant to mechanical properties and specific manufacturing constraints. A customized loss function is formulated to constrain the latent features, while addressing the non-uniqueness problem for layups with certain mechanical properties. The developed property-oriented VAE can generate 100,000 layups in seconds, achieving an average success rate of 66.9% under comprehensive in-plane and bending stiffness design, and remains effective for 100-ply thick laminate. For comparison, the VAE model outperforms the genetic algorithm and the logic-based method in reinforced panel designs, reducing the retrieval error by 46.4% and 38.1%, respectively. The proposed approach demonstrates flexible and efficient design advantages using generative machine learning models, and is easily extendable to other inverse design scenarios.

Shorter Premature Atrial Complex Coupling Interval Leads to Mechanical Dysfunction, Fibrosis, and AF in Swine.

We have previously shown that dyssynchronous premature atrial complexes (PACs) from the lateral left atrium (LA) lead to greater atrial mechanical dysfunction, remodeling, and sustained atrial fibrillation (AF) than synchronous PACs from the interatrial septum. However, the impact of PAC coupling interval (CI) on atrial remodeling is unclear. This study sought to explore the effect of PAC CI on atrial mechanics and remodeling in the swine model. A 2-phase invivo study was conducted. In the phase 1 acute study, 5 swine underwent acute invasive hemodynamics and echocardiography while delivering single-paced atrial extrastimuli with CIs varying from 450ms to 200ms. Peak LA longitudinal strain and intra-LA dyssynchrony were assessed with 2-dimensional strain echocardiography while LA and aortic pressure were directly measured. In the phase 2 chronic study, a group exposed to paced bigeminy from the lateral LA for 16weeks with a short CI of 250ms (Short-PAC, n=10) was compared with groups with PACs at a long CI of 400ms (Long-PAC, n=5) and a nonpaced control group (CTRL, n=10). Detailed electrophysiology and echocardiography studies were performed with histologic quantification of LA fibrosis at baseline and prior to sacrifice. Phase 1 revealed that as PAC CI shortened, peak LA strain decreased (P = 0.003) and LA dyssynchrony increased (P< 0.001). Phase 2 showed that after 16weeks of PACs, the Short-PAC group had greater LA dilation (terminal baseline: 5.9 ± 1.2cm2 vs Long-PAC 3.9 ± 0.5cm2 vs CTRL 0.9 ± 0.4cm2; P< 0.001) and reduced peakLAstrain during sinus rhythm (terminal baseline:-17.3 ± 3.2% vs Long-PAC-12.1 ± 2.1% vs CTRL-0.7 ± 4.2%; P<0.001). The short-PAC group had a more LA fibrosis (8.6 ± 1.0% vs Long-PAC 6.8 ± 1.0% vs CTRL 4.0 ± 1.5%; P<0.001) and higher AF inducibility (terminal baseline: 49.3 ± 13.0% vs Long-PAC 29.0 ± 6.4% vs CTRL 2.2±16.2%; P< 0.001) than the other groups. In this swine model, shorter PAC CI led to increased acute atrial mechanical dysfunction and dyssynchrony. Chronically, short-CI PACs led to greater atrial fibrosis and induced AF, suggesting that frequent, short-coupled PACs pose the highest risk for LA myopathy and AF. These insights underscore the importance of understanding the impact of PAC characteristics on atrial remodeling and arrhythmogenesis.

The coordinated relationship and interactive response between urban quality of life and eco-efficiency in China

It is crucial to clarify the interaction mechanism between quality of life (QOL) and eco-efficiency (EE) to achieve high-quality urban development. This study investigated the complex and dynamic interaction and coupling process between QOL and EE. By constructing two evaluation index systems, this study obtained the values of QOL and EE levels in 282 cities from 2008 to 2020. Then, the interactive relationship between QOL and EE was investigated from two perspectives: static coupling and dynamic coupling. The different development types were classified according to the regional differences between them. The results show that: (1) From 2008 to 2020, the value of QOL gradually increased, while the EE exhibited a “V-shaped” change. Medium to high levels of QOL were located in cities in the eastern coastal area, while low levels were distributed in the western, central and northeastern regions. Furthermore, medium to high levels of EE were distributed in cities in the eastern coastal and southwestern regions, whereas low levels were found in the central and northwestern regions; (2) Overall, the coupled coordination of QOL and EE got better from 2008 to 2020, showing that the relationship between them was close and that the coordination gradually got better. Consequently, the spatial change of the coupled coordination was more pronounced, the number of mildly uncoordinated cities was gradually decreasing, urban development was shifting from uncoordinated to coordinated, and the clustering characteristics of the coupled coordination degree were consistent with the spatial change characteristics; (3) Moreover, there was a Granger causality relationship between QOL and EE. This means that the degree of their mutual influence increased over time, while their development became less dependent on inertia, with obvious interaction characteristics; and (4) The values of integrated QOL and EE were separately clustered and combined with the type of coupled and coordinated urban development based on their development stage. Therefore, the research area was divided into three types: “optimization and upgrading,” “continuous improvement,” and “cultivating development.”

Modeling and Analysis of Resistance-Sensing Characteristics for Two-Way Shape Memory Alloy-Based Deep-Sea Actuators

Deep-sea actuators based on shape memory alloys (SMAs) are an emerging frontier field of multidisciplinary crossover, and the resistive sensing characteristics are the basis for the drive control of SMA deep-sea actuators. The resistance and resistivity of SMAs are complex and highly dependent on temperature and stress, and there is no complete description of SMAs for extreme environments of high pressure, low temperature, and high salinity in the deep sea. In this study, the logistic function is introduced to improve the kinetic equation of phase transition, and the macromechanical model, the law of resistance, and the resistivity mixing rule are integrated to model and analyze the resistive self-awareness characteristics of two-way shape memory alloy deep-sea actuators. The complex coupling relationships among resistance, strain, stress, resistivity, and temperature under constant load conditions are investigated, and the validity of the resistance-sensing model is verified by the water bath cycling test. The results show that the predicted values of the model agree well with the measured values. The self-perceived relationship between the resistance and deformation of the two-way shape memory alloy can be effectively expressed, which provides theoretical model support for the design of memory alloy deep sea actuators and sensorless drive control.