Short Optimization Times Research Articles

Ultra-broadband and wide-angle reflective terahertz polarization conversion metasurface based on topological optimization

Abstract Terahertz polarization conversion devices have significant potential applications in various fields such as terahertz imaging and spectroscopy. In this paper, we utilize genetic algorithms to topologically optimize the metasurface unit cells and design a reflective linear polarization conversion metasurface with ultra-broadband and wide-angle characteristics. By partitioning the metallic pattern layer into quadrants, the encoding length is effectively reduced, resulting in a shorter optimization time. The research results indicate that the converter possesses a polarization conversion efficiency ratio higher than 90% and a relative bandwidth ratio of 125% in a range of 0.231–0.995 THz. Meanwhile, it can maintain excellent polarization conversion properties when the incident angle of terahertz waves is less than 45° and the polarization angle is less than 15°, demonstrating excellent practicality. New insights are provided for the design of terahertz wide-angle ultra-wideband polarization conversion devices, and the proposed metasurfce has potential applications in terahertz polarization imaging, spectroscopy and communication fields.

Fault Diagnosis of Wind Turbine Bolts based on ICEEMD-SSA-SVM Model

Background: Compared with traditional power generation systems, wind turbines have more units and work in a more harsh environment, and thus have a relatively high failure rate. Among blade faults, the faults of high-strength bolts are often difficult to detect and need to be analyzed with high-precision sensors and other equipment. However, there is still little research on blade faults. Methods: The improved complete ensemble empirical mode decomposition (ICEEMD) model is used to extract the fault features from the time series data, and then combined with the support vector machine optimized by sparrow search algorithm (SSA-SVM) to diagnose the bolt faults of different degrees, so as to achieve the purpose of early warning. Results: The results show that the ICEEMD model used in this paper can extract the bolt fault signals well, and the SSA-SVM model has a shorter optimization time and more accurate classification compared with models such as PSO-SVM. Conclusion: The hybrid model proposed in this paper is important for bolt fault diagnosis of operation monitoring class.

FIR digital filter design based on improved artificial bee colony algorithm

The traditional swarm intelligence optimization algorithm is prone to fall into local optimal solutions in finite impulse response (FIR) digital filter design and has slow convergence speed. In order to optimize the design of FIR filter, a FIR digital filter design method based on improved bee colony (ABC) algorithm is proposed. This improved ABC algorithm can adaptively adjust the step size of the selected neighborhood of nectar source location. At the same time, the information of the global optimal solution is used to guide the search of candidate solution, which improves the global search ability of the algorithm. The improved ABC algorithm can balance the conflict between local search ability and global search ability, so it can achieve better optimization effect. The time and space complexity of the algorithm is analyzed in detail. Then, the improved ABC algorithm is used to design three typical FIR digital filters, namely low-pass, band-pass and band-stop filter. The performance of the designed filter is tested by simulation experiments. The experimental results show that compared with other state-of-the-art optimization algorithms, the proposed FIR filter design method has achieved better effect and performance. Meanwhile, the proposed design method has shorter optimization time. The superiority of the proposed method is verified.

Optimization of the transmission characteristics of an HMCVT for a high-powered tractor based on an improved NSGA-II algorithm

The hydro-mechanical continuously variable transmission (HMCVT) is a critical component of the power transmission system in a tractor. However, the complexity of the operating conditions imposes high requirements on the transmission characteristics. To improve the powerful performance and economy of HMCVTs and satisfy the operational demands of high-powered tractors, a new optimization design method for the characteristic parameters of an HMCVT is proposed. First, the characteristics of an HMCVT are modeled, and the influence of the structural parameters on the transmission characteristics is analyzed. Then, HMCVT performance evaluation indexes are formulated. In accordance with the speed regulation of system, power performance, and economy characteristics, a multi-objective optimization mathematical model is established, and an improved fast non-dominated sorting genetic algorithm (INSGA-II) is designed. The introduction of a normal distribution crossover operator (NDX) and an improved adaptive adjustment mutation operator not only ensures the population diversity but also improves the Pareto solution convergence properties during the process of genetic evolution. The superiority of INSGA-II is verified by comparison with a traditional multi-objective genetic algorithm. Finally, the optimization results show that the torque ratio is increased by approximately 2.81%, 14.32%, 2.31%, and 15.07% in HM1, HM2, HM3, and HM4 respectively. The transmission efficiency is increased by approximately 3.48% and 1.97% in HM1 (HM3) and HM2 (HM4). Also, INSGA-II finds the optimal solution with a faster speed and shorter optimization time than MULGA. This research can serve as a reference for the design and optimization of HMCVTs for high-powered tractors.

Optimal design of 6-DOF vibration isolation platform based on transfer matrix method for multibody systems

The structure parameters of 6-degree of freedom (DOF) vibration isolation platform have a significant effect on its performance. To make the designed vibration isolation platform perform well, non-dominanted sorting genetic algorithm version II (NSGA-II) was applied to optimize its structure based on the transfer matrix method for multibody systems. Firstly, the Jacobian matrix of 6-DOF vibration isolation platform was solved based on kinematics. Secondly, the transfer equation of 6-DOF vibration isolation system was established by the linear transfer matrix method for multibody systems. And the formula of its natural frequency was derived according to the boundary conditions of the system. Thirdly, the manipulability index was constructed based on a dimensionless Jacobian matrix. And a new performance index function was established considering the influence of dynamic isotropic and legs mass. Fourthly, genetic algorithm (GA) and NSGA-II were used to optimize the structure of the 6-DOF vibration isolation platform under the same conditions, respectively. It showed that NSGA-II had higher optimization efficiency, better calculation accuracy and shorter optimization time than that of GA. Finally, NSGA-II was adopted for multi-objective optimization design of 6-DOF vibration isolation platform based on the constraint conditions. Optimal Pareto solutions were obtained, which provides structural parameters for subsequent design work. Therefore, the proposed optimization method and the performance index in this paper provide a theoretical basis for the optimal design of relevant vibration isolation mechanism.

Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm

Abstract To solve the problem of multi-objective performance optimization based on ant colony algorithm, a multi-objective performance optimization method of ORC cycle based on an improved ant colony algorithm is proposed. Through the analysis of the ORC cycle system, the thermodynamic model of the ORC system is constructed. Based on the first law of thermodynamics and the second law of thermodynamics, the ORC system evaluation model is established in a MATLAB environment. The sensitivity analysis of the system is carried out by using the system performance evaluation index, and the optimal working parameter combination is obtained. The ant colony algorithm is used to optimize the performance of the ORC system and obtain the optimal solution. Experimental results show that the proposed multi-objective performance optimization method based on the ant colony algorithm for the ORC cycle needs a shorter optimization time and has a higher optimization efficiency.

Space–time dynamics of optimal wavepackets for streaks in a channel entrance flow

The laminar–turbulent transition of a plane channel entrance flow is revisited using global linear optimization analyses and direct numerical simulations. The investigated case corresponds to uniform upstream velocity conditions and a moderate value of Reynolds number so that the two-dimensional developing flow is linearly stable under the parallel flow assumption. However, the boundary layers in the entry zone are capable of supporting the development of streaks, which may experience secondary instability and evolve to turbulence. In this study, global optimal linear perturbations are computed and studied in the nonlinear regime for different values of streak amplitude and optimization time. These optimal perturbations take the form of wavepackets having either varicose or sinuous symmetry. It is shown that, for short optimization times, varicose wavepackets grow through a combination of Orr and lift-up effects, whereas for longer target times, both sinuous and varicose wavepackets exhibit an instability mechanism driven by the presence of inflection points in the streaky flow. In addition, while the optimal varicose modes obtained for short optimization times are localized near the inlet, where the base flow is strongly three-dimensional, when the target time is increased, the sinuous and varicose optimal modes are displaced farther downstream, in the nearly parallel streaky flow. Finally, the optimal wavepackets are found to lead to turbulence for sufficiently high initial amplitudes. It is noticed that the resulting turbulent flows have the same wall-shear stress, whether the wavepackets have been obtained for short or for long time optimization.

Fast degree-distribution optimization for BATS codes

Batched sparse (BATS) codes have been proposed for communication through networks with packet loss. BATS codes include a matrix generalization of fountain codes as the outer code and random linear network coding at the intermediate network nodes as the inner code. BATS codes, however, do not possess a universal degree distribution that achieves an optimal rate for any distribution of the transfer matrix ranks. Therefore, it is important to have a fast degree-distribution optimization approach for finite-length BATS codes. In this paper, we propose the concept of batch release probability (BRP), and demonstrate some characteristics of BRPs from the degree distributions achieving nearly optimal performance. Based on these BRP characteristics, we propose a novel degree-distribution optimization approach that achieves the similar decoding performance with a much shorter optimization time, compared with the previous approach. Moreover, the universality of BRPs observed in this paper can further simplify the degree-distribution optimization of BATS codes.

A quantized water cycle optimization algorithm for antenna array synthesis by using digital phase shifters

In this article, a quantized water cycle algorithm (QWCA) is used for the antenna array pattern synthesis with low side-lobe levels (SLLs) and nulls at desired directions by using four-bit digital phase shifters. In addition to the standard features as a metaheuristic algorithm, QWCA has an internal quantization mechanism and a precalculated array factor method. The latter provides an accelerated procedure to QWCA under favour of the digitized values that can be stored in a three-dimensional array. This acceleration is based on the reality that the accessing data in the memory need less time than the usage of the mathematical functions throughout the optimization process. The internal quantization mechanism of QWCA is utilized to achieve digital values matching to the discrete values of the phase shifter instead of the simple rounding up/down routines after optimization. The numerical results showed that QWCA can obtain very good SLLs and null depth levels (NDLs) on the synthesized pattern. Moreover, the results are achieved in remarkably short optimization times. SLL and NDL values obtained by QWCA are also compared with the available literature values. The comparisons reveal that QWCA is able to produce better results than the other compared alternatives. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:21–29, 2015.

Properties of singular vectors using convective available potential energy as final time norm

We study the feasibility of using the singular vector technique to create initial condition perturbations for shortrange ensemble prediction systems (SREPS) focussing on predictability of severe local storms and in particular deep convection. For this a newfinal time semi-norm based on the convective available potential energy (CAPE) is introduced. We compare singular vectors using the CAPE-norm with SVs using the more common total energy (TE) norm for a 2-week summer period in 2007, which includes a case of mesoscale extreme rainfall in the south west of Finland. The CAPE singular vectors perturb the CAPE field by increasing the specific humidity and temperature of the parcel and increase the lapse rate above the parcel in the lower troposphere consistent with physical considerations. The CAPE-SVs are situated in the lower troposphere. This in contrast to TE-SVs with short optimization times which predominantly remain in the high troposphere. By examining the time evolution of the CAPE singular values we observe that the convective event in the south west of Finland is clearly associated with high CAPE singular values.

Global three-dimensional optimal disturbances in the Blasius boundary-layer flow using time-steppers

The global linear stability of the flat-plate boundary-layer flow to three-dimensional disturbances is studied by means of an optimization technique. We consider both the optimal initial condition leading to the largest growth at finite times and the optimal time-periodic forcing leading to the largest asymptotic response. Both optimization problems are solved using a Lagrange multiplier technique, where the objective function is the kinetic energy of the flow perturbations and the constraints involve the linearized Navier–Stokes equations. The approach proposed here is particularly suited to examine convectively unstable flows, where single global eigenmodes of the system do not capture the downstream growth of the disturbances. In addition, the use of matrix-free methods enables us to extend the present framework to any geometrical configuration. The optimal initial condition for spanwise wavelengths of the order of the boundary-layer thickness are finite-length streamwise vortices exploiting the lift-up mechanism to create streaks. For long spanwise wavelengths, it is the Orr mechanism combined with the amplification of oblique wave packets that is responsible for the disturbance growth. This mechanism is dominant for the long computational domain and thus for the relatively high Reynolds number considered here. Three-dimensional localized optimal initial conditions are also computed and the corresponding wave packets examined. For short optimization times, the optimal disturbances consist of streaky structures propagating and elongating in the downstream direction without significant spreading in the lateral direction. For long optimization times, we find the optimal disturbances with the largest energy amplification. These are wave packets of Tollmien–Schlichting waves with low streamwise propagation speed and faster spreading in the spanwise direction. The pseudo-spectrum of the system for real frequencies is also computed with matrix-free methods. The spatial structure of the optimal forcing is similar to that of the optimal initial condition, and the largest response to forcing is also associated with the Orr/oblique wave mechanism, however less so than in the case of the optimal initial condition. The lift-up mechanism is most efficient at zero frequency and degrades slowly for increasing frequencies. The response to localized upstream forcing is also discussed.

Two coding based adaptive parallel co-genetic algorithm with double agents structure

This paper systematically proposed a multi-population agent co-genetic algorithm with double chain-like agent structure (MPATCGA) to solve the problem of the low optimization precision and long optimization time of simple genetic algorithm in terms of two coding strategy. This algorithm adopted multi-population parallel searching mode, close chain-like agent structure, cycle chain-like agent structure, dynamic neighborhood competition, and improved crossover strategy to realize parallel optimization, and has the characteristics of high optimization precision and short optimization time. Besides, the size of each sub-population is adaptive. The characteristic is very competitive when dealing with imbalanced workload. In order to verify the optimization precision of this algorithm with binary coding, some popular benchmark test functions were used for comparing this algorithm and a popular agent genetic algorithm (MAGA). The experimental results show that MPATCGA has higher optimization precision and shorter optimization time than MAGA. Besides, in order to show the optimization performance of MPATCGA with real coding, the authors used it for feature selection problems as optimization algorithm and compared it with some other well-known GAs. The experimental results show that MPATCGA has higher optimization precision (feature selection precision). In order to show the performance of the adaptability of size of sub-populations, MPATCGA with sub-populations with same size and MPATCGA with sub-populations with different size are compared. The experimental results show that when the workload on different sub-populations becomes not same, the adaptability will adaptively change the size of different sub-population to obtain precision as high as possible.

Multi-population co-genetic algorithm with double chain-like agents structure for parallel global numerical optimization

For the low optimization precision and long optimization time of genetic algorithm, this paper proposed a multi-population agent co-genetic algorithm with chain-like agent structure (MPAGA). This algorithm adopted multi-population parallel searching mode, close chain-like agent structure, cycle chain-like agent structure, dynamic neighborhood competition and orthogonal crossover strategy to realize parallel optimization, and has the characteristics of high optimization precision and short optimization time. In order to verify the optimization precision of this algorithm, some popular benchmark test functions were used for comparing this algorithm and a popular agent genetic algorithm (MAGA). The experimental results show that MPAGA has higher optimization precision and shorter optimization time than MAGA.

Optimal Growth in Inertia–Gravity Wave Packets: Energetics, Long-Term Development, and Three-Dimensional Structure

Abstract Using a hierarchy of three models of increasing realism and complexity, and expanding on a previous study, optimal perturbations of inertia–gravity wave (IGW) packets are studied with respect to several aspects. It is shown that normal modes are comparatively less able to extract energy from the IGW over finite time due to their time-invariant structure, while singular vectors (SVs) can adjust their dynamical fields flexibly so as to optimize the statically enhanced roll and Orr mechanisms by which they grow. On longer time scales, where the time dependence of the IGW packet precludes a normal-mode analysis, optimal growth is found to further amplify suitable perturbations. The propagation characteristics of these exhibit critical layer interactions for horizontal propagation directions transverse with respect to the IGW, preventing significant vertical propagation, while parallel and obliquely propagating perturbations of sufficiently long horizontal scales are found to radiate gravity waves into altitudes not directly affected by the IGW. The SVs with shorter wavelengths, as found for short optimization times, stay confined via a linear wave duct near the altitude of least static stability where they are excited. At optimization times of the order of the IGW period the leading SVs, with an energy growth by about three orders of magnitude, propagate obliquely, possibly in correspondence to previous results by others from simulations of nonlinear IGW breakdown. The three-dimensional structure of SVs shows an amplitude modulation strictly confining the perturbations also to the horizontal location of least static stability, suggesting a picture of turbulence onset in IGW packets where local patches of growing perturbations initially dominate.

Optimal Perturbations in the Eady Model: Resonance versus PV Unshielding

Abstract Using a nonmodal decomposition technique based on the potential vorticity (PV) perspective, the optimal perturbation or singular vector (SV) of the Eady model without upper rigid lid is studied for a kinetic energy norm. Special emphasis is put on the role of the continuum modes (CMs) in the structure of the SV, and on the importance of resonance to the SV evolution. The basis for the SV is formed by a number of nonmodal structures, each consisting of a superposition of one CM and one edge wave, such that the initial surface potential temperature (PT) is zero. These nonmodal structures are used as PV building blocks to construct the SV. The motivation for using a nonmodal approach is that no attempt has been made so far to include the CM residing at the steering level of the surface edge wave in the perturbation, although it is known that this CM is in linear resonance with the surface edge wave. Experiments with one PV building block in the initial disturbance show that the SV growth is dominated by the resonance effect except for small optimization times (less than 1 day), in which case the unshielding of PV and surface PT dominates the growth of the SV. The PV–PT unshielding provides additional growth to the SV and this explains the observation that the PV resides above the resonant level. More PV building blocks are added to include PV unshielding as a third growth mechanism. Which of the three mechanisms dominates during the SV evolution depends on the region of interest (interior or surface), as well as on the optimization time and on the number of building blocks used. At the surface, resonance plays a dominant role even when a large number of building blocks is used and relatively small optimization times are used. For the interior of the domain, PV unshielding becomes the dominant growth mechanism when more than two PV building blocks are used. With increasing optimization times, the PV distribution of the SV becomes increasingly more concentrated near the steering level of the edge wave. This concentration of PV is explained by the enhanced importance of resonance for long optimization times as compared to short optimization times.

A Potential Vorticity and Wave Activity Diagnosis of Optimal Perturbation Evolution

A diagnosis of singular vector (SV) evolution (computed for the L2 streamfunction norm) in the Eady model using potential vorticity (PV) and Eliassen–Palm (E–P) flux diagnostics is performed. In addition, a partitioning of the vertical component of the E–P flux vector based on the results of the piecewise PV inversion is introduced to better elucidate the fundamental mechanisms for SV amplification. The initial PV structures of the Eady model SVs on both the long- and shortwave sides of the Eady model shortwave cutoff are characterized by initially upshear tilted interior PV anomalies. The results of the PV and the E–P flux diagnostics for optimal perturbations reveal a three-stage process for the SV evolution: 1) a superposition of interior PV anomalies (diagnosed by a positive vertical component of the E–P flux), 2) a subsequent intensification (characterized by maxima in the E–P flux near the boundaries) of the SV boundary potential temperature anomalies (BTAs) by winds attributed to interior PV, and 3) finally a transient or sustained mutual interaction between the BTAs (associated with a nearly nondivergent interior E–P flux). The PV inversion demonstrates that a significant fraction of the observed SV amplification may be attributed to the initially upshear tilted PV anomalies, and that the initial BTAs, while important in describing the initial SV structure, play a minimal role in the subsequent evolution. The results of the experiments in which the Eady model SV structures were altered by removing either the BTAs or the interior PV suggest that data assimilation schemes that more heavily weight targeted surface observations to targeted tropospheric wind and temperature observations may result in a forecast correction that is either excessive (for short optimization times) or insufficient for optimization times comparable to or larger than the time required for the PV to be rendered vertical by the shear flow. An analysis of SVs calculated about the time-varying basic state of an NWP model reveals that the SV PV initially consists of upshear tilted structures located beneath a depressed tropopause in a region of strong low-level thermal gradient (and concomitant vertical shear). The subsequent nonlinear evolution of the SV PV in the NWP model is congruous with that observed in the Eady model: The vertical superposition of SV PV, followed by amplification of a surface thermal ridge by winds attributed to the SV PV, characterize the SV amplification. These results suggest the relevance of the SV amplification mechanisms identified in the Eady model in more realistic flows, and indicate the potential utility of applying the aforementioned diagnostic techniques to understanding SV development in observed flows.