Nonlinear Simulation Research Articles

An assessment of crucial structural contributors of HDAC6 inhibitors through fragment-based non-linear pattern recognition and molecular dynamics simulation approaches

Amidst the Zn2+-dependant isoforms of the HDAC family, HDAC6 has emerged as a potential target associated with an array of diseases, especially cancer and neuronal disorders like Rett’s Syndrome, Alzheimer’s disease, Huntington’s disease, etc. Also, despite the availability of a handful of HDAC inhibitors in the market, their non-selective nature has restricted their use in different disease conditions. In this situation, the development of selective and potent HDAC6 inhibitors will provide efficacious therapeutic agents to treat different diseases. In this context, this study has been carried out to evaluate the potential structural contributors of quinazoline-cap-containing HDAC6 inhibitors via machine learning (ML), conventional classification-dependant QSAR, and MD simulation-based binding mode of interaction analysis toward HDAC6 binding. This combined conventional and modern molecular modeling study has revealed the significance of the quinazoline moiety, substitutions present at the quinazoline cap group, as well as the importance of molecular property, number of hydrogen bond donor-acceptor functions, carbon-chlorine distance that significantly affects the HDAC6 binding of these inhibitors, subsequently affecting their potency . Interestingly, the study also revealed that the substitutions such as the chloroethyl group, and bulky quinazolinyl cap group can affect the binding of the cap function with the amino acid residues present in the loops proximal to the catalytic site of HDAC6. Such contributions of cap groups can lead to both stabilization and destabilization of the cap function after occupying the hydrophobic catalytic site by the aryl hydroxamate linker-ZBG functions.

Flow-shear destabilization of multiscale electron turbulence

The impact of sheared E×B flow on multiscale turbulence is studied with nonlinear gyrokinetic simulations. Simulations are based on DIII-D-like, high-confinement mode (H-mode) pedestal parameters in the regime of low ion temperature gradient drive, where there is a broad spectrum of electron temperature gradient (ETG)-driven turbulence. It is found that E×B shear can have a significant effect on ETG-driven electron transport, with an unexpected transition from a turbulence stabilization regime at moderate to large shearing rates γ E to a novel turbulence destabilization regime at low levels of γ E . In the turbulence stabilization regime, the electron energy flux decreases monotonically with γ E , even when γ E is small compared to electron mode growth rates. The stabilizing effect comes dominantly from the electron, not ion, gyrokinetic equation. In the novel destabilization regime, reduction of zonal energy results from the interaction of γ E -modulated nonlinear drive in the zonal ion gyrokinetic equation, increasing the electron transport over a broad range of shearing rates. Neither of these effects have been observed in previous electron-scale simulations.

Enhancing gust load alleviation performance in an optimized composite wing using passive wingtip devices: Folding and Twist approaches

This paper introduces an innovative numerical method for the design and optimization of high-aspect-ratio composite wings equipped with passive control systems, specifically, Folding WingTip (FWT) and Twist WingTip (TWT) devices. The aim is to enhance Gust Load Alleviation (GLA) performance in the baseline wing. Recent numerical studies have indicated that the inclusion of spring devices and wingtip modifications can offer additional benefits in alleviating gust loads during flight. The baseline wing is designed using a comprehensive multi-disciplinary optimization framework, taking into account aerostructural constraints and exploiting the anisotropic properties of composite materials. The proposed methodology integrates Finite Element (FE) software, an in-house Reduced Order Model (ROM) framework for nonlinear aeroelastic analyses, and Particle Swarm Optimization (PSO). This method, implemented in the Nonlinear Aeroelastic Simulation Software (NAS2) package, facilitated the streamlined design of composite wings with optimized aeroelastic and structural performance. The paper is divided into two main parts. Part 1 introduces a Multidisciplinary Design Optimization (MDO) approach for high-aspect-ratio composite wings, leading to the development of a baseline wing model. Part 2 evaluates the effectiveness of the FWT and TWT devices in alleviating gust loads on the baseline wing, with a focus on the Root Bending Moment (RBM) as a critical criterion for comparison. In wingtip modeling, geometrical nonlinearity is incorporated, and elastic trim is adjusted in each iteration to accommodate shape changes under load and aerodynamic panel movement is synchronized with structural adjustments.

Simultaneous reproduction of experimental profiles, fluxes, transport coefficients, and turbulence characteristics via nonlinear gyrokinetic profile predictions in a DIII-D ITER similar shape plasma

Experimental conditions obtained on the DIII-D tokamak in the ITER Similar Shape (ISS) have been compared extensively with nonlinear gyrokinetic simulation using the CGYRO code [Candy et al., J. Comput. Phys. 324, 73–93 (2016)] with comparisons spanning ion and electron heat fluxes, electron and impurity particle transport, and turbulent fluctuation levels and characteristics. Bayesian optimization techniques [Rodriguez-Fernandez et al., Nucl. Fusion 62(7), 076036 (2022)], combined with nonlinear gyrokinetics, have been used to obtain simultaneously Qi, Qe, and Γe flux-matched profiles that are found to be in good agreement with experimental profile measurements. Synthetic diagnostics were used to compare measured beam emission spectroscopy and correlation electron cyclotron emission turbulent fluctuations with nonlinear simulation. Although some disagreements exist, nonlinear simulations are found to be in generally good agreement with measured fluctuation levels, spectral shapes, and measured radial trends in low-k δne/ne and δTe/Te. Low (Li and C) and mid-Z (Ca) impurity transport was also compared with these flux-matched simulations. Fully stripped, low-Z impurities are well reproduced by the gyrokinetic modeling while clear disagreement exists in comparisons with mid-Z impurities. Nonlinear gyrokinetic investigation into the Z dependence of impurity transport in the ISS conditions is also performed, demonstrating clear trends of impurity diffusion with impurity Z (both D∝Z and D∝1/Z) that vary with the radial location studied. These trends are shown to result from the local dominance of ion temperature gradient or ∇n driven trapped electron mode turbulence and may contribute to the disagreement between simulation and experiment in mid-Z impurity transport. The results of this work represent one of the most complete validation studies of the gyrokinetic model performed to date and provide an example of new capabilities for predicting performance in future fusion devices.

Recipes for mixing vortices in a microchannel using electric field

Application of an electric field on the pressure-driven flow of a fluid inside a microchannel can create mixing vortices. The Coulombic force at electrode–fluid interface generates the additional stress to engender the instability. While the previous studies show the phenomena at the two-layer immiscible or miscible flows, we show the same for a single fluid system. Linear stability analysis (LSA), non-linear simulations, and experiments together uncover the conditions for onset and propagation of such instabilities with Reynolds (Re) and electric field Rayleigh (Raψ) numbers. The LSA uncover that a higher critical field (larger Racψ) is required to destabilize a flow with a higher flow rate (higher Re), highlighting the stabilizing nature of the inertia. Subsequently, the non-linear simulations and experiments uncover that such systems can develop localized steady or unsteady vortices with time in order to dissipate the excess localized electrical energy originating from the applied field. Example cases are shown wherein the size, number, and recirculation strength of the vortices have been tuned inside the microchannel with the variations in the external field intensity and the arrangements of the electrodes for a fixed Re. The study further unveils that while at lower Raψ only be steady vortices may show up for the fluids with higher viscosities, at the significantly higher Raψ the fluids with a lower viscosity may manifest an array of unsteady counter-rotating vortices. Such vortices may translate due to the flow of the fluid inside the confined microfluidic channel to eventually form a “vortex-street” inside the microchannel.

A comprehensive review on the modeling of tropical cyclone boundary layer wind field

Tropical cyclone (TC) wind field models are becoming increasingly sophisticated and complex. This review systematically discusses a range of models capable of simulating TCs in terms of modifications or simplifications of the governing equation, the Navier–Stokes equations, as a starting point. The discussion focuses on linear models, which include slab models, height-resolving models, and numerical simulation methods, respectively. The linear model offers quick calculations and insights into physical mechanisms, while slab models have limitations in capturing important processes and site conditions. The height-resolving model is widely used for Monte Carlo simulations, providing realistic three-dimensional wind structures. Nonlinear simulations yield reliable results for typhoon trajectory prediction, although they require specific boundary and initial conditions. Integration of nonlinear simulation with artificial intelligence and machine learning shows promise for faster typhoon prediction. However, challenges remain in terms of data training for machine learning models. Future advancements in these areas have the potential to enhance hazard assessment and weather forecasting.

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.