Nonlinear Method Research Articles

Impact of Obesity on Cardiac Autonomic System Functioning in Military Police Officers.

Cardiac autonomic system functioning may be altered by obesity leading to cardiovascular diseases and associated complications. Military police officers are exposed to traditional and occupational risk factors for the development of CVD, however data on the cardiovascular health in this population is still scarce. In this cross-sectional study, we investigated the impact of obesity on cardiac autonomic modulation and the hemodynamic profile in male active-duty military police officers. The body composition of the volunteers was assessed by octapolar electrical bioimpedance. Participants were classified as non-obese or obese in accordance with their body fat, with further subgroups as physically active obese or insufficiently active obese using International Physical Activity Questionnaire (IPAQ). Cardiac autonomic modulation was assessed by heart rate variability and the automatic oscillometric method allowed us to assess hemodynamic features. 102 military police officers from the state of São Paulo participated in the study. Cardiac autonomic modulation revealed significant impairment in time and frequency domains and non-linear methods in the obese group compared to the non-obese (p < 0.05). A higher physical activity level did not alter these results in the obese group. However, no significant differences in the hemodynamic profile were observed between groups (p > 0.05). These findings suggest a negative association between obesity and cardiac autonomic modulation in military police officers, unaffected by increased physical activity.

The establishment of a performance evaluation model using education informatization to evaluate teacher morality construction in colleges and universities

Abstract To improve the effectiveness of the construction of teacher morality in colleges and universities, this article employs the performance evaluation model of education informatization to construct an evaluation system for the construction of teacher morality in colleges and universities. The evaluation of the construction effect of teacher morality is carried out through intelligent data analysis, and the significant error is used as the parameter of the teacher’s morality to make estimations. Moreover, a binary variable is introduced to judge whether the data have a significant error. Mixed integer linear and nonlinear programming methods are employed to detect significant errors. In addition, the idea of synchronizing teachers’ moral data is added. The effectiveness of the proposed method is verified by a simulation study using MATLAB 2017. The results show that it is necessary to establish and improve the talent flow mechanism that conforms to the requirements to promote the rational flow of teachers.

Multi-objective reinforcement learning based on nonlinear scalarization and long-short-term optimization

Purpose Many practical control problems require achieving multiple objectives, and these objectives often conflict with each other. The existing multi-objective evolutionary reinforcement learning algorithms cannot achieve good search results when solving such problems. It is necessary to design a new multi-objective evolutionary reinforcement learning algorithm with a stronger searchability. Design/methodology/approach The multi-objective reinforcement learning algorithm proposed in this paper is based on the evolutionary computation framework. In each generation, this study uses the long-short-term selection method to select parent policies. The long-term selection is based on the improvement of policy along the predefined optimization direction in the previous generation. The short-term selection uses a prediction model to predict the optimization direction that may have the greatest improvement on overall population performance. In the evolutionary stage, the penalty-based nonlinear scalarization method is used to scalarize the multi-dimensional advantage functions, and the nonlinear multi-objective policy gradient is designed to optimize the parent policies along the predefined directions. Findings The penalty-based nonlinear scalarization method can force policies to improve along the predefined optimization directions. The long-short-term optimization method can alleviate the exploration-exploitation problem, enabling the algorithm to explore unknown regions while ensuring that potential policies are fully optimized. The combination of these designs can effectively improve the performance of the final population. Originality/value A multi-objective evolutionary reinforcement learning algorithm with stronger searchability has been proposed. This algorithm can find a Pareto policy set with better convergence, diversity and density.

Nitrofurazone biodegradation kinetics by batch fermentation of Aspergillus tamarii

Nitrofurazone (NFZ) compound contains a 5-nitrofuran ring structure that has been widely used as feed additives in animal husbandry. Due to the benzene ring structure, the residues are highly toxic to humans and animals. A kinetics study of NFZ biodegradation in batch fermentation with Aspergillus tamarii KX610719.1 was conducted. The main objectives were to determine the kinetic parameters of fungal growth, glucose consumption, protein production, and biodegradation of NFZ using fungal biomass. Kinetic parameters were determined using Polymath 6.0 software, and regression analysis was done using linear and non-linear methods. After 168 hours of batch fermentation, the maximum specific growth rate (µmax), and maximum cell concentration (Xmax) for cultivation without NFZ were 0.062 h-1, and 0.529 g L-1, respectively. The maximum specific growth rate (µmax), and maximum cell concentration (Xmax) for cultivation with NFZ were 0.092 h-1, and 0.327 g L-1, respectively. For glucose consumption, kinetic parameters of Yield of biomass over the substrate (YXS) and cell maintenance (mS) were estimated at 0.139 g g-1 and 0.239 h-1, respectively. Based on the Luedeking Piret model, the estimated growth-associated (α) and non-growth-associated (β) constants were 1.142×10-2 g g-1 and 5.680×10-5 h-1, respectively. The rate constant (k1) of NFZ biodegradation was estimated at 2.696×10-2 h-1 following the first-order model where the rate constant of NFZ removal is dependent on the NFZ concentration. The application of A. tamarii batch fermentation in the removal of NFZ compound was sufficient with a total percentage removal of 85.9 % or 0.430 g L-1 recorded.

Investigating the Z-scan technique for quantifying circulating cell-free DNA (ccfDNA) extracted from blood plasma as a potential biomarker for various cancers.

Abstract&#xD;The Z-scan technique is a nonlinear optical method that has found applications in characterizing various materials, particularly those exhibiting nonlinear optical response (NLOR). This study applies the continuous wave (CW) Z-scan technique to examine the NLOR in terms of the nonlinear optical phase shifts (ΔΦ_0) exhibited by the ccfDNA extracted from blood plasma samples collected from a group constituting 30 cancer-diagnosed patients and another group constituting 30 non-diagnosed individuals. The cancer group exhibited significantly higher ΔΦ_0vs. incident power slopes compared to the non-cancer group (0.34 vs 0.12) providing a clear distinction between the two groups. The receiver operating characteristic (ROC) curve analysis of the results indicates a clear separation between cancer and non-cancer groups, along with a 94% accuracy rate of the data. The Z-scan results are corroborated by spectrophotometric analysis, revealing a consistent trend in the concentration values of ccfDNA samples extracted from both cancerous and non-cancerous samples, measuring 3.24 and 1.41 respectively. Additionally, more sensitive fluorometric analyses of the respective samples demonstrate significantly higher concentrations of ccfDNA in the cancer group, further affirming the correlation with the Z-scan results. The study suggests that the Z-scan technique holds promise as an effective method for cancer detection, potentially contributing to improved oncology diagnosis and prognosis in the future.&#xD.

Nonlinear electromechanical topology optimization method for stretchable electronic interconnect structures

Nonlinear electromechanical topology optimization method for stretchable electronic interconnect structures

A Nonlinear Mixed Finite Element Method for the Analysis of Flexoelectric Semiconductors

Abstract In this paper, we develop a nonlinear mixed finite element method for flexoelectric semiconductors and analyze the mechanically tuned redistributions of free carriers and electric currents through flexoelectric polarization in typical structures. We first present a macroscopic theory for flexoelectric semiconductors by combining flexoelectricity and nonlinear drift-diffusion theory. To use C0 continuous elements, we derive an incremental constrained weak form by introducing Langrage multipliers, in which the kinematic constraints between the displacement and its gradient are guaranteed. Based on the weak form, we established a mixed C0 continuous nine-node quadrilateral finite element as well as an iterative process for solving nonlinear boundary-value problems. The accuracy and convergence of the proposed element are validated by comparing linear finite element method results against analytical solutions for the bending of a beam. Finally, the nonlinear element method is applied to more complex problems, such as a circular ring, a plate with a hole, and an isosceles trapezoid. Results indicate that mechanical loads and doping levels have distinct influences on electric properties.

Numerical simulation of composite swirl/film double-wall cooling structures and chamber designs for enhanced overall cooling effectiveness

A novel double-wall with composite swirl/film cooling structure is proposed in this work to enhance the cooling effectiveness of contemporary gas turbine blades. The influence of different shaped chambers and Biot numbers on the overall cooling effectiveness (OCE) are investigated by Reynolds time-averaged Navier-Stokes simulations and conjugate heat transfer analysis. The results suggest that the proposed composite cooling configuration exhibits outstanding OCE in the simulated range. When the Rm is 1.00 and the Biot number is 0.11, the OCE of the composite structure is improved by 8.92 % over the conventional double-wall structure, and the distribution is more uniform. In addition, the optimal flow and cooling performance of the composite swirl/film cooling structure at high Rm conditions are obtained. The OCE is very sensitive to the variation of the Biot number. Finally, the empirical correlations obtained by the multivariate nonlinear regression fitting method are in good agreement with the simulations, with errors within 10 %. The results also provide important guidance for the development of advanced gas turbine blades double-wall cooling structures.

Learnable faster kernel-PCA for nonlinear fault detection: Deep autoencoder-based realization

Kernel principal component analysis (KPCA) is a well-recognized nonlinear dimensionality reduction method that has been widely used in nonlinear fault detection tasks. As a kernel trick-based method, KPCA inherits two major problems. First, the form and the parameters of the kernel function are usually selected blindly, depending seriously on trial-and-error. As a result, there may be serious performance degradation in case of inappropriate selections. Second, at the online monitoring stage, KPCA has much computational burden and poor real-time performance, because the kernel method requires to leverage all the offline training data. In this work, to deal with the two drawbacks, a learnable faster realization of the conventional KPCA is proposed. The core idea is to parameterize all feasible kernel functions using the novel nonlinear DAE-FE (deep autoencoder based feature extraction) framework and propose DAE-PCA (deep autoencoder based principal component analysis) approach in detail. The proposed DAE-PCA method is proved to be equivalent to KPCA but has more advantage in terms of automatic searching of the most suitable nonlinear high-dimensional space according to the inputs, which helps to improve the accuracy of fault detection. Furthermore, the online computational efficiency improves by many times compared with the conventional KPCA. Finally, the Tennessee Eastman (TE) process benchmark and wastewater treatment plant (WWTP) benchmark are employed to illustrate the effectiveness of the proposed method, where the average fault detection rates of DAE-PCA are at least 0.27% and 4.69% higher than those of other methods, and its online computational efficiency is faster 90.48% and 24.57% times than that of KPCA respectively.

Excitation and manipulation of recurring rogue waves via nonlinear compression

We theoretically propose a feasible scheme to generate high-density waves and manipulate them quantitatively. We show that a wave with greater density compression called “recurring rogue wave” can be excited by first generating a rogue wave via quenching and Gaussian space modulation techniques followed by employing a nonlinear compression method. The formation of recurring rogue wave is verified to be a consequence of the combined interaction of nonlinear compression and “self compression”. We find that the maximal density of recurring rogue wave exhibits a nonmonotonic dependence on compression time, which allows us to manipulate recurring rogue waves quantitatively through changing compression time and modulation parameters within a certain range. The analytical results based on variational method qualitatively support the numerical simulation results. Our study provides potential strategies for efficiently generating high-density waves in Bose–Einstein condensate experiments.

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Purpose To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems. Design/methodology/approach The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs. Findings In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis. Research limitations/implications Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task. Practical implications The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots. Social implications The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent. Originality/value A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

Research and verification on parameter solution of mixed shock model for common cause failure based on particle swarm algorithm

AbstractMixed shock model is an explicit construction method of failure probability model based on component independent failure, system nonfatal shock, and fatal shock failure, which considers common cause failure (CCF) in redundant system. For aerospace systems, a modified mixed shock model is proposed, which considers several components may fail independently and simultaneously in operation. In order to solve the issue that the parameters of the mixed shock model cannot be solved directly based on the failure probability data, a parameter solving method based on particle swarm optimization (PSO) algorithm is proposed. Additionally, the relationship between the failure probability and the gradient of the parameter change is deduced, and the reduced‐order (RO) solution based on the gradient of the parameter change is proposed to improve the efficiency of the solution. A fitness function construction method based on the relative error of the solution probability and the true probability is proposed to improve the probability solution accuracy of multicomponent failure. The nonlinear inertia factor optimization method combined with fitness change is studied to improve the particle swarm dynamics. The accuracy of the results of different parameters solving sequence and different PSO methods are compared, and the effectiveness of the RO solution is verified. The results of the mixed shock model before and after modification are compared with the different CCF data, which verifies the effectiveness and wide applicability of the modified mixed shock model. The results show that the modified mixed shock model for CCF and its parameter solution method can significantly improve the probability solution accuracy of all components failure, and also provide a new theoretical basis and solution method for the quantitative analysis of multiredundant system failure.

An Adaptive Extended Kalman Filter With Passivity-Based Control for DC-DC Converter in DC Microgrids Supplying Constant Power Loads

This paper proposes an adaptive nonlinear control strategy to eliminate the instability problem of buck converters in DC microgrids (DCMG) considering constant power load (CPL). The strategy includes an Adaptive Passivity-Based Controller (PBC) and an Adaptive Extended Kalman Filter (AEKF). The proposed AEKF performs faster and more accurately than the conventional EKF and adjusts the covariance matrices adaptively. Furthermore, this AEKF directly estimates the unknown CPL power supplied by the converter and prevents the number of measurement sensors from increasing. Hence, PBC ensures system stability alongside AEKF. The controller guarantees Lyapunov stability and fast dynamic response in the presence of uncertainties and perturbations compared to other nonlinear methods. MATLAB simulations and laboratory implementation are provided to confirm the performance and robustness of the proposed control strategy and validate the analysis.

High-efficiency anti-stokes Raman blue laser in CO2 enables high-luminance RGB laser-driven white light

Stimulated Raman scattering (SRS) is an efficient nonlinear frequency conversion method, enabling simultaneous generation of red, green, and blue (RGB) lasers. In order to synthesize a white light source for laser display by SRS, a 532 nm laser was used as pump source, and high purity gaseous carbon dioxide (CO2) was used as the Raman active medium. First, by optimizing experimental parameters, with an f = 1.5 m focal lens, in 0.8 atm CO2 pumped at 304 mJ, a first-order anti-Stokes (AS1) 495 nm blue laser was achieved, with an energy of 31.9 mJ, peak power of 10.9 MW and conversion efficiency (CE) of 10.5 %. Then, Then, the second-order Stokes light (S2) at 624 nm, residual pump laser (S0) at 532 nm, and AS1 laser were utilized as RGB primary colors. By the variation of pressure below 1 atmosphere (atm), the laser-driven white light (LDWL) with adjustable correlated color temperature (CCT) below 4700 K were simulated. Finally, LDWL up to 2.6 × 1018cd/m2 of a CCT of 3300 K could be synthesized at an RGB power ratio of PR: PG: PB = 0.447:0.094:0.459, resulting in a white light power CE of 44.4 % and luminous efficacy of 113.7 lm/W. In addition, use of the 574 nm yellow Raman light is expected to realize a four-primary (RGBY) laser display scheme with higher Luminance and broader color gamut. Moreover, the feasibility of using a 515 nm Yb: YAG laser as pump source to widen the range of CCT and improve the brightness of LDWL was discussed.

Performance of double-arch tunnels under internal BLEVE

Double-arch tunnels, as one of the popular forms of tunnels, might be exposed to boiling liquid expanding vapour explosions (BLEVEs) associated with transported liquified petroleum gas (LPG), which could cause damage to the tunnel and even catastrophic collapse of the tunnel in extreme cases. However, very limited study has investigated the performance of double-arch tunnels when exposed to internal BLEVEs and in most analyses of tunnel responses to accidental explosions. The TNT-equivalence method was used to approximate the explosion load, which may lead to inaccurate tunnel response predictions. This study numerically investigates the response of typical double-arch tunnels to an internal BLEVE resulting from the instantaneous rupture of a 20 m3 LPG tank. Effects of various factors, including in-situ stresses, BLEVE locations, and lining configurations on tunnel responses are examined. The results show that the double-arch tunnels at their early-operation ages are more vulnerable to severe damage when exposed to the BLEVE due to the low action of in-situ stress of rock mass on the response of early-age tunnels. It is also found that directing the LPG tank to different driving lanes inside tunnels can affect the BLEVE-induced tunnel response more significantly than varying the configurations of tunnel lining. Moreover, installing section-steel arches in the mid-wall can effectively improve the blast resistance of the double-arch tunnels against the internal BLEVE. In addition, the prediction models based on multi-variate nonlinear regressions and machine learning methods are developed to predict the BLEVE-induced damage levels of the double-arch tunnels without and with section-steel arches.

Study on Flow Pattern Transition of Cuttings Transport in Extended-Reach Drilling

Inadequate hole cleaning is one of the major challenges in extended-reach drilling, especially prominent in large-sized hole sections, such as 121/4-in. section. As the drilling parameters including flow rate, ROP and rotational speed change, the cuttings flow pattern converts between fully suspended flow, two-layer flow, and three-layer flow. However, most existing cuttings transport models only study the problem of cuttings transport under a certain flow pattern and do not consider the dynamic conversion of different cuttings flow patterns. Pipe rotation plays a key role in cuttings transport in rotary drilling, but the existing studies have not fully revealed the effect of pipe rotation on the conversion of cuttings transport patterns. In this paper, a stirring diffusion factor is presented to quantify the effect of pipe rotation on cuttings transport, and the mathematical expression of the stirring diffusion factor is obtained through numerical simulations and the nonlinear regression method. Secondly, the critical conditions for the conversion of cuttings flow patterns are obtained by combining mechanical analysis and numerical simulation results, clarifying the applicable scope of different cuttings flow patterns. According to the comparison with experimental results, the prediction error of the new model considering the conversion of cuttings flow patterns is not higher than 11.1%, and the minimum prediction error is only 3.07%. Thirdly, the flow pattern maps for cuttings transport under different drilling parameters are drawn to provide guidance for the identification of cuttings transport pattern and optimization of drilling parameters. Finally, the flow pattern maps are applied to a case study of an extended-reach drilling. The results show that there is a delay effect in the conversion of cuttings flow patterns due to the nonlinear characteristics of annular geometry. Furthermore, the effects of flow rate, ROP and rotational speed on cuttings transport patterns are not independent, but mutually reinforcing and constraining each other. Inappropriate selection of drilling parameters will result in three-layer flow of cuttings transport, and then pipe sticking is likely to occur. The cuttings transport pattern can be converted from three-layer flow to two-layer flow by optimizing drilling parameters, which can significantly improve the hole cleaning effect.

Stability and nonlinear vibration characteristics of cantilevered fluid-conveying pipe with nonlinear energy sink

Considering the midline non-expansion theory and nonlinear coordinate method, this paper mainly investigates the stability and nonlinear vibration characteristics of cantilevered fluid-conveying pipe with energy sink. Based on Hamilton 's variational principle, the dynamic equation of a cantilevered pipe conveying fluid with nonlinear energy sink (NES) under pulsating flow is established. The system equation is processed by Galerkin method, a novel matrix equations of single-degree-of-freedom and multi-degree-of-freedom coupling system is established. The results show that the physical factors in the flow pipe system have a great influence on the critical flow velocity of the whole system, comparing with the case of adding NES. Increasing the proportion of the mass of the fluid will have a greater impact on the real part frequency, thereby increasing the critical velocity of the fluid-conveying pipe system. Addition of nonlinear energy sink can significantly suppress the amplitude and decrease the unstable vibration of the pipe.

Anomaly detection using large-scale multimode industrial data: An integration method of nonstationary kernel and autoencoder

Kernel methods and neural networks (NNs) are two mainstream nonlinear data modeling methods and have been widely applied to industrial process monitoring. However, they both present imperfect properties, so the relevant applications are limited. On the one hand, kernels are not so reconstructable, scalable, and robust to hyperparameters that they suffer performance degradation for large-scale data modeling and monitoring. On the other hand, the high-dimensional parameter space of NNs that is sorted to parameter initialization presents severe anomaly detection performance inconsistency, which makes the industry cautious about using NNs. Motivated by these facts, we propose to integrate kernels and NNs, forming a new model structure that is scalable, reconstructable, and performance-consistent. Specifically, a novel autoencoder-based nonstationary pattern selection kernel (AE-NPSK) is proposed by (1) selecting from the training set the critical edges and interior data as the centers of the radial basis functions in the hidden layers and (2) adaptively adjusting the kernel width in the training procedure. Also, the new NN has strong performance consistency, which facilitates the search for optimal parameters. Finally, we test the performance of the proposed method on the challenging multimode processes. The results validate the efficacy of the proposed method.

A nonlinear analytical method for pipeline strain under soil thaw subsidence load in permafrost region

In frozen terrain, the transportation of heated oil triggers thermal soil thaw and collapse, leading to pipeline distortion and breakdown. During substantial ground settlement in such terrains, current strain prediction techniques for pipelines fall short, neglecting significant pipeline bending, non-linear material behaviors, or detailed pipeline-permafrost interplay. To address this, a model focusing on pipeline-soil dynamics is devised, incorporating material non-linearity and pronounced pipeline distortion. This model derives analytical strain solutions for pipelines by aggregating incremental distortions of pipeline components via a strain iteration technique. Concurrently, a three-dimensional solid finite element model is crafted, assessing pipeline strains across varying subsidence zone dimensions, factoring in the complicated permafrost environment. The model's efficiency is affirmed by its less than 3% discrepancy from finite element method results, showcasing its enhanced accuracy and dependability in predicting pipeline strains under extensive soil settlement scenarios.

Nonlinear Fast Modeling Method of Flux Linkage and Torque for a 12/8 Switched Reluctance Motors

Nonlinear Fast Modeling Method of Flux Linkage and Torque for a 12/8 Switched Reluctance Motors