Nonlinear Simulation Research Articles

Characterization of Microstructural and Mechanical Properties of 17-4 PH Stainless Steel by Cold Rolled and Machining vs. DMLS Additive Manufacturing

The 17-4 PH stainless steel is widely used in the aerospace, petrochemical, chemical, food, and general metallurgical industries. The present study was conducted to analyze the mechanical properties of two types of 17-4 PH stainless steel—commercial cold-rolled and direct metal laser sintering (DMLS) manufactured. This study employed linear and nonlinear tensile FEM simulations, combined with various materials characterization techniques such as tensile testing and nanoindentation. Moreover, microstructural analysis was performed using metallographic techniques, optical microscopy, scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD). The results on the microstructure for 17-4 PH DMLS stainless steel reveal the layers of melting due to the laser process characterized by complex directional columnar structures parallel to the DMLS build direction. The mechanical properties obtained from the simple tension test decreased by 17% for the elastic modulus, 7.8% for the yield strength, and 7% for the ultimate strength for 17-4 PH DMLS compared with rolled 17-4 PH stainless steel. The FEM simulation using the experimental tension test data revealed that the 17-4 PH DMLS stainless steel experienced a decrease in the yield strength of ~8% and in the ultimate strength of ~11%. A reduction of the yield strength of the material was obtained as the grain size increased.

Nonlinear Magneto-Quasistatic Simulation of Superconducting Tapes With a-ψ Algebraic Formulation

Nonlinear Magneto-Quasistatic Simulation of Superconducting Tapes With <i>a-ψ</i> Algebraic Formulation

Research of turbulent transport due to dissipative trapped electron mode in tokamak plasmas

The purpose of this article is to study turbulent transport for laboratory plasmas in toroidal devices by gyrokinetic analyses. Linear analysis is performed to clarify the dominant mode for tokamak plasmas. The dissipative trapped electron mode (d-TEM) and the ion temperature gradient (ITG) mode are predicted using the Sugama collision model operator [Sugama et al., Phys. Plasmas 16, 112503 (2009)]. Nonlinear gyrokinetic analysis is used to quantify turbulent transport. The nonlinear simulation results show the levels of particle and energy transport, where the d-TEM and ITG mode are unstable. The effect of zonal flows is studied by the linear and nonlinear simulation results. The results of the analysis are compared when two types of model collision operator, which are the Sugama and Lenard–Bernstein [Phys. Rev. 112, 1456 (1958)] collision model operators, are used. In this study, the simulation results using the Sugama collision operator show a stronger effect of the zonal flows on the turbulent transport than those using the Lenard–Bernstein collision operator, as predicted by the linear simulation result such as the zonal flow decay time.

Designing a benign prostatic hyperplasia dual-mode cavitation cloud and boiling histotripsy therapy transducer

Benign prostatic hyperplasia (BPH) is a condition that causes an enlarged prostate leading to lower urinary tract symptoms (LUTS), affecting quality of life. Histotripsy is a non-invasive focused ultrasound technique that mechanically disintegrates tissue wherein cavitation cloud (CH) and boiling histotripsy (BH) are the two commonly used therapy modes. Recent studies have shown successful ablation of BPH tissue in vitro by transducers that were designed for a transabdominal approach. However, this approach may not be successful in treating tissue in vivo, as evidenced in some of the clinical studies, due to challenges with the anatomical position of prostate within humans. Therefore, a need exists in treating it transrectally with a transducer that can perform both CH and BH for efficient ablation. Initial design studies were performed to determine the appropriate source parameters and materials needed for fabricating the combinational therapy transducer for in vivo use. A 3 MHz multi-element source with a focal length of 40 mm and gain of 64 was chosen. The equivalent aperture is 48.5 mm with a 10 mm central opening for image guidance. Non-linear simulations show sufficient peak positive and negative pressures can be achieved for performing both regimes. Further details on the fabrication and characterization of the transducer with benchtop results will be presented.

Non-Linear Simulation by Harmonic Balance Techniques of Load Modulated Power Amplifier Driven by Random Modulated Signals

The simulation of the steady state and the non-linear stability of a load modulated power amplifier (LMPA) driven by a random modulated generator, fully performed in the frequency domain by harmonic balance (HB) techniques, is presented. The non-linear microwave circuit and the driving pseudo-random modulated (PRM) generator are integrally defined in the frequency domain. The simulation is implemented and performed using commercially available circuit simulation software. The demodulation of the output signal of the LMPA is implemented with optimally matched filters as software-defined demodulation. The simulated dynamic results of a Quasi-MMIC GaN Doherty power amplifier (DPA) are shown and compared to the measured results with a 16-QAM driving signal at 10 MS/s. The time-domain measurement allows the validation of the new simulation technique through the comparison of both the measured and the simulated error vector magnitude (EVM), the left and right adjacent channel power ratios (ACPRs) versus the average output power. This new simulation is then called pseudo-random modulated harmonic balance (PRM-HB) simulation. The full PRM-HB simulation of an LMPA driven by a random modulated signal, performed in the frequency domain at the design circuit level, results in an advanced simulation tool in the frame of the design of RF circuits and subsystems for telecommunication applications.

Uncertainty quantification in logistic regression using random fuzzy sets and belief functions

Evidential likelihood-based inference is a new approach to statistical inference in which the relative likelihood function is interpreted as a possibility distribution. By expressing new data as a function of the parameter and a random variable with known probability distribution, one then defines a random fuzzy set and an associated predictive belief function representing uncertain knowledge about future observations. In this paper, this approach is applied to binomial and multinomial regression. In the binomial case, the predictive belief function can be computed by numerically integrating the possibility distribution of the posterior probability. In the multinomial case, the solution is obtained by a combination of constrained nonlinear optimization and Monte Carlo simulation. In both cases, computations can be considerably simplified using a normal approximation to the relative likelihood. Numerical experiments show that decision rules based on predictive belief functions make it possible to reach lower error rates for different rejection rates, as compared to decisions based on posterior probabilities.

High Aspect Ratio Composite Wings: Geometrically Nonlinear Aeroelasticity, Multi-Disciplinary Design Optimization, Manufacturing, and Experimental Testing

In the field of aerospace engineering, the design and manufacturing of high aspect ratio composite wings has become a focal point of innovation and efficiency. These long, slender wings, constructed with advanced materials such as carbon fiber and employing efficient manufacturing methods such as vacuum bagging, hold the promise of significantly lighter aircraft, reduced fuel consumption, and enhanced overall performance. However, to fully realize these benefits, it is imperative to address a multitude of structural and aeroelastic constraints. This research presents a novel aeroelastically tailored Multi-objective, Multi-disciplinary Design Optimization (MMDO) approach that seamlessly integrates numerical optimization techniques to minimize weight and ensure structural integrity. The optimized wing configuration is then manufactured, and a Ground Vibration Test (GVT) and static deflection analysis using the Digital Image Correlation (DIC) system are used to validate and correlate with the numerical model. Within the fully automated in-house Nonlinear Aeroelastic Simulation Software (NAS2) package (version v1.0), the integration of analytical tools offers a robust numerical approach for enhancing aeroelastic and structural performance in the design of composite wings. Nonlinear aeroelastic analyses and tailoring are included, and a population-based stochastic optimization is used to determine the optimum design within NAS2. These analytical tools contribute to a comprehensive and efficient methodology for designing composite wings with improved aeroelastic and structural characteristics. This comprehensive methodology aims to produce composite wings that not only meet rigorous safety and performance standards but also drive cost-efficiency in the aerospace industry. Through this multidisciplinary approach, the authors seek to underscore the pivotal role of tailoring aeroelastic solutions in the advanced design and manufacturing of high aspect ratio composite wings, thereby contributing to the continued evolution of aerospace technology.

A control architecture for fixed-wing aircraft based on the convolutional neural networks

This paper develops a nonlinear architecture to control different fixed-wing aircraft. This architecture has inner and outer loops. The inner loops, designed based on the convolutional neural networks, control the internal dynamics of the aircraft, and the outer loops, which use linear controllers, are designed to control the kinematic states, which are the same for all aircraft. So, the inner loops are designed to have adaptation mechanisms based on the convolutional neural networks to control the internal dynamics of different aircraft. The networks are trained offline based on a generated database to avoid time-consuming online procedures. The database is created by simulating simple linear training models. Then, the input-output data of these training models are preprocessed and mapped to an appropriate form to be fed to convolutional neural networks. After that, an appropriate network structure is selected, and the networks are trained based on the mapped database. These trained networks, along with linear controllers in a cascade form, are applied to control nonlinear simulations of 15 different fixed-wing aircraft. Then, the performance of the represented controller is compared to two adaptive controllers. The promising results show that the controller can sufficiently be utilized in controlling fixed-wing aircraft, even in slow or sudden changes in aircraft dynamics.

Nonlinear dynamics simulation of the helical gear transmission system for high-speed train

Considering the bending-torsional-axial-coupled vibration of the helical gear transmission system, a 10 degrees of freedom high-speed train gear transmission system model, including motor and load, is established based on the lumped parameter method. In addition, the potential energy method based on the slicing principle is used to accurately calculate the time-varying meshing stiffness of helical gears. Furthermore, the influence of geometric parameters of helical gears on the time-varying meshing stiffness is studied, and the impact of time-varying meshing stiffness on the system is further investigated. Meanwhile, by analyzing the dynamic phenomena of the system under different parameter excitations under different parameter excitations, the influence of internal and external excitation parameters such as gear speed, wheel rail creep force, support stiffness, and support damping on the stability of high-speed train gear transmission system is deeply studied.

Enhancing the Versatility and Performance of Soft Robotic Grippers, Hands, and Crawling Robots Through Three-Dimensional-Printed Multifunctional Buckling Joints.

Soft robotic grippers and hands offer adaptability, lightweight construction, and enhanced safety in human-robot interactions. In this study, we introduce vacuum-actuated soft robotic finger joints to overcome their limitations in stiffness, response, and load-carrying capability. Our design-optimized through parametric design and three-dimensional (3D) printing-achieves high stiffness using vacuum pressure and a buckling mechanism for large bending angles (>90°) and rapid response times (0.24 s). We develop a theoretical model and nonlinear finite-element simulations to validate the experimental results and provide valuable insights into the underlying mechanics and visualization of the deformation and stress field. We showcase versatile applications of the buckling joints: a three-finger gripper with a large lifting ratio (∼96), a five-finger robotic hand capable of replicating human gestures and adeptly grasping objects of various characteristics in static and dynamic scenarios, and a planar-crawling robot carrying loads 30 times its weight at 0.89 body length per second (BL/s). In addition, a jellyfish-inspired robot crawls in circular pipes at 0.47 BL/s. By enhancing soft robotic grippers' functionality and performance, our study expands their applications and paves the way for innovation through 3D-printed multifunctional buckling joints.

Some remarks on load modeling in nonlinear structural analysis–Statics with large deformations–Consistent treatment of follower load effects and load control

AbstractLoad modeling in nonlinear statics, particularly incorporating large deformations differs significantly from the treatment in linear analysis. As in structural dynamics masses in a gravity field generate the loading, their location, and their modifications within the deformation process must be considered in a nonlinear simulation. A specific view besides loading by masses is on gas and fluid interaction with structures. In addition, load control using specifically designed algorithms is evaluated with respect to realistic applications. Within the load modeling an unavoidable, however side aspect, is the general discussion about the so‐called follower forces and non‐conservative loading. As an example of real‐world applications, the specifics of inflated rubber dams are presented.

Global linear and nonlinear gyrokinetic simulations of tearing modes

To better understand multi-scale interactions between global tearing modes and microturbulence in the Madison Symmetric Torus (MST) reversed-field pinch (RFP), the global gyrokinetic code Gene is modified to describe global tearing mode instability via a shifted Maxwellian (SM) distribution consistent with experimental equilibria. The implementation of the SM is tested and benchmarked by comparisons with different codes and models. Good agreement is obtained in code-code and code-theory comparisons. Linear stability of tearing modes of a non-reversed MST discharge is studied. A collisionality scan is performed to the lowest order unstable modes (n = 5, n = 6) and shown to behave consistently with theoretical scaling. The nonlinear evolution is simulated, and saturation is found to arise from mode coupling and transfer of energy from the most unstable tearing mode to small-scale stable modes mediated by the m = 2 tearing mode. The work described herein lays the foundation for nonlinear simulation and analysis of the interaction of tearing modes and gyroradius-scale instabilities in RFP plasmas.

Development and implementation of shear wall finite element in OpenSees

Shear walls are widely used as lateral load-resisting systems in high-rise building structures. The design and nonlinear analysis of shear walls under seismic loads for recoverability are complicated and challenging, which demands nonlinear computer modeling procedures. This paper presents a novel finite element named Double Vertical Beam-column with Shell Element (DVBSE) for the nonlinear analysis of complex reinforced concrete shear walls with columns. The DVBSE is implemented in the open-source finite element program OpenSees. The theoretical formulations of DVBSE are described in detail. The accuracy of the developed DVBSE is established by comparing the finite element analysis results with existing experimental data on recoverable steel-GFRP composite bar reinforced concrete shear walls. The comparative study demonstrates that the proposed DVBSE is superior to the commonly used finite element model in simulating the responses of recoverable complex shear walls under seismic loads. These research findings contribute to further advancements in the development of new shear wall elements and lay a solid foundation for the nonlinear numerical simulation of innovative shear walls.

Development of a tokamak magnetohydrodynamic code with the discontinuous Galerkin and Weighted Essentially Non-Oscillatory methods

In this study, we present the development of a new initial-value magnetohydrodynamic (MHD) code for toroidal geometry using discontinuous Galerkin (DG) and Weighted Essentially Non-Oscillatory (WENO) methods. The code utilizes a triangular mesh based on the flux of the fixed boundary equilibrium in the poloidal plane, which is uniformly divided in the toroidal direction. By solving the conservative perturbed generalized Lagrange multiplier (GLM) MHD model, the code can simulate both ideal and resistive toroidal plasmas. We validate the code by performing the linear calculations of the internal kink mode and tearing mode, and our results show good agreement with calculations conducted using an eigen-value MHD code. Furthermore, nonlinear simulations of the resistive internal kink mode and tearing mode are also carried out. We discuss the challenges and limitations of the code, as well as the future efforts to improve its performance. The development of this new initial-value MHD code opens up new possibilities for studying and understanding the dynamics of toroidal plasmas, contributing to the advancement of fusion research.

A new quasilinear model for turbulent momentum transport in tokamaks with flow shear and plasma shaping

In tokamak experiments, sufficiently strong E × B flow shear reduces turbulent transport, thereby improving the prospects for fusion power plants. It is therefore of great importance to efficiently explore parameter space to find where strong plasma flow can be achieved. To this end, we propose a new, physically motivated quasi-linear model for estimating momentum transport from turbulence in the presence of toroidal flow shear and plasma shaping. The method gives good estimates of momentum transport for up–down asymmetric geometries as well as low magnetic shear and tight aspect ratio. The results are benchmarked with high-fidelity nonlinear GENE simulations, demonstrating that it provides a fast and accurate estimate of momentum transport.

Performance analysis of real-time multi-wavelength nonlinear DRA for the next-generation photonic network

A new disintegrated channelization approach for the backward pumped nonlinear distributed Raman amplifier is proposed by enacting the differential coupled equations of Raman amplification, in fiber, trailing by the solution of NLSE using the first integral method first time to the best of our knowledge. A nonlinear channel modeling-based simulation is adapted for the approximation of the Raman gain profile. To realize the real-time dynamic system, 16 multiplexed channels of prime C-band are employed in a QPSK/NRZ modulation environment with a 100 Gbps bit rate for optical network reconfiguration. A non-uniform gain is reported while the disparity in BER is observed from 10−12 to 10−8.

Simulation of 0–7.5 Hz physics-based nonlinear ground motions for maximum credible earthquake scenarios at the Long Valley Dam, CA

We have conducted three-dimensional (3D) 0–7.5 Hz physics-based wave propagation simulations to model the seismic response of the Long Valley Dam (LVD), which has formed Lake Crowley in Central California, to estimate peak ground motions and settlement of the dam expected during maximum credible earthquake (MCE) scenarios on the nearby Hilton Creek Fault (HCF). We calibrated the velocity structure, anelastic attenuation model, and the overall elastic properties of the dam via linear simulations of a Mw 3.7 event as well as the Mw 6.2 Chalfant Valley earthquake of 1986, constrained by observed ground motions on and nearby the LVD. The Statewide California Earthquake Center (SCEC) Community Velocity Model CVM-S4.26.M01 superimposed with a geotechnical layer using [Formula: see text] information tapered from the surface to a 700-m depth was used in the simulations. We found optimal fit of simulated and observed ground motions at the LVD using frequency-independent attenuation of [Formula: see text] ([Formula: see text] in m/s). Using the calibrated model, we simulated 3D nonlinear ground motions at the LVD for Mw 6.6 rupture scenarios on the HCF using an Iwan-type, multi-yield-surface technique. We use a two-step method where the computationally expensive nonlinear calculations were carried out in a small domain with the plane wave excitation along the bottom boundary obtained from a full-domain 3D linear finite-fault simulation. Our nonlinear MCE simulation results show that peak ground velocities (PGVs) and peak ground accelerations (PGAs) as high as 72 cm/s and 0.55 g, respectively, can be expected at the crest of the LVD. Compared with linear ground motion simulation results, our results show that Iwan nonlinear damping reduces PGAs on the dam crest by up to a factor of 8 and increasingly depletes the high-frequency content of the waves toward the dam crest. We find horizontal relative displacements of the material inside the dam of up to [Formula: see text] and up to [Formula: see text] of vertical subsidence, equivalent to 1% of the dam height.

Self-Organized Evolution of the Internal Transport Barrier in Ion-Temperature-Gradient Driven Gyrokinetic Turbulence.

Understanding the self-organization of the most promising internal transport barrier in fusion plasmas needs a long-time nonlinear gyrokinetic global simulation. The neighboring equilibrium update method is proposed, which solves the secularity problem in a perturbative simulation and speeds up the numerical computation by more than 10 times. It is found that the internal transport barrier emerges at the magnetic axis due to inward propagated turbulence avalanche, and its outward expansion is the catastrophe of self-organized structure induced by outward propagated avalanche.

A Numerical Method for the Dynamics Analysis of Blade Fracture Faults in Wind Turbines Using Geometrically Exact Beam Theory and Its Validation

In pursuit of China’s goals for carbon peak and carbon neutrality, wind turbines are continually evolving to achieve a lower levelized cost of energy. The primary technological focus in the wind power industry is on large-scale, lightweight designs for entire turbines to enhance cost competitiveness. However, this advancement has led to an increased risk of blade fractures under extreme operating conditions. This paper addresses this challenging issue by using geometrically exact beam theory to develop a nonlinear simulation model for long, flexible blades. The model accounts for sudden changes in blade properties at the moment of failure, covering both the extensive motions and deformations of the fractured blade. The validation of the proposed model is carried out by comparing the results from power production cases with bladed simulations and further validating the simulations of blade fracture load cases against measurement data. The methodologies and findings presented in this study offer valuable insights for diagnosing faults in wind turbines.

An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian

The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for the state prediction covariance matrix. The system state and noise parameter posterior distributions are then iteratively updated for adaptive estimation. Furthermore, we make adaptive adjustments to the IEKF filter parameters to enhance sensitivity and filtering accuracy, thus ensuring robust prediction estimation. A two-dimensional target tracking and nonlinear numerical UNGM simulation validated our algorithm. Compared to existing algorithms RKF-ML and GA-VB, our method showed significant improvements in RMSEpos and RMSEvel, with increases of 21.81% and 22.11% respectively, and a 49.04% faster convergence speed. These results highlight the method’s reliability and adaptability.