Showing papers on "Parametric statistics published in 2023"
TL;DR: In this article , a phased array focusing method was proposed for the damage localization of curved plates, where different damage scenarios and phase-array focusing schemes were investigated in the finite element plate models with different radii.
31 citations
TL;DR: In this article , a probabilistic assessment is performed using different seismic fragility analysis approaches for structures under non-stationary stochastic ground motions, including least squares regression (LSR), maximum likelihood estimation (MLE), kernel density estimation (KDE), and Monte Carlo simulation (MCS).
30 citations
TL;DR: In this paper , the authors proposed an efficient optimization algorithm based on the physical phenomenon of rime-ice, called the RIME algorithm, which implements the exploration and exploitation behaviors in the optimization methods by simulating the soft-rime and hard rime growth process.
28 citations
TL;DR: In this paper , an innovative self-centring damper equipped with shape memory alloy elements and wedge-shaped friction plates was developed, and an analytical model enabling quantification of the hysteretic behaviour of the damper was derived.
23 citations
TL;DR: In this paper , a hydrogen-fueled micro planar combustor with cavity was designed for thermophotovoltaic applications to obtain high energy output power and energy conversion efficiency.
18 citations
TL;DR: In this paper , an experimental and numerical investigation on the behavior of concrete-filled cold-formed steel elliptical stub columns was performed on four elliptical hollow sections infilled with concrete of three different grades (C40, C70 and C100).
18 citations
TL;DR: In this paper , a complex fractional order (CFO) linear quadratic integral regulator (LQIR) is proposed to enhance the robustness of inverted pendulum-type robotic mechanisms against bounded exogenous disturbances.
Abstract: This article presents a systematic approach to formulate and experimentally validate a novel Complex Fractional Order (CFO) Linear Quadratic Integral Regulator (LQIR) design to enhance the robustness of inverted-pendulum-type robotic mechanisms against bounded exogenous disturbances. The CFO controllers, an enhanced variant of the conventional fractional-order controllers, are realised by assigning pre-calibrated complex numbers to the order of the integral and differential operators in the control law. This arrangement significantly improves the structural flexibility of the control law, and hence, subsequently strengthens its robustness against the parametric uncertainties and nonlinear disturbances encountered by the aforementioned under-actuated system. The proposed control procedure uses the ubiquitous LQIR as the baseline controller that is augmented with CFO differential and integral operators. The fractional complex orders in LQIR are calibrated offline by minimising an objective function that aims at attenuating the position-regulation error while economising the control activity. The effectiveness of the CFO-LQIR is benchmarked against its integer and fractional-order counterparts. The ability of each controller to mitigate the disturbances in inverted-pendulum-type robotic systems is rigorously tested by conducting real-time experiments on Quanser single-link rotary pendulum system. The experimental outcomes validate the superior disturbance rejection capability of the CFO-LQIR by yielding rapid transits and strong damping against disturbances while preserving the control input economy and closed-loop stability of the system.
16 citations
TL;DR: In this article , artificial intelligence algorithms are proposed for estimating the compressive strength of hollow concrete block masonry prisms, including neural networks (ANN), combinatorial methods of group data handling (GMDH-Combi), and gene expression programming (GEP).
16 citations
TL;DR: In this article , the authors developed an analytical framework to evaluate the 3D active earth pressure considering the presence of cracks and steady-infiltration effects within unsaturated backfills.
Abstract: Traditional analyses for active earth pressures considered soils dry or saturated by the application of a two-dimensional (2D) failure pattern. However, soils are usually unsaturated in nature, and the collapse of backfills presents a three-dimensional (3D) characteristic. The extant studies proved that the existence of cracks and seepage flow encountered in backfills would impact active earth pressures but are still limited to 2D conditions. To this end, this study developed an analytical framework to evaluate the 3D active earth pressure considering the presence of cracks and steady-infiltration effects within unsaturated backfills. Based on the kinematic approach of limit analysis, a suction-induced effective method is introduced into a 3D failure mechanism to characterize the collapse of unsaturated backfills. By means of the work rate balance equation, the most adverse location of cracks and the explicit expression of active thrust under steady seepage conditions can be obtained through the incorporation of the suction stress profile. The presented method is verified by comparison with the exact cases in previous studies and comparison with the results of numerical simulation. A systematic parametric study is conducted to reveal the impacts of width-to-height ratio, air-entry value, pore-size distribution, vertical discharge, and cracks on the active earth pressure variations. The results show that considering 3D effects is significant because it leads to a lower economic cost for the design of retaining walls; the presence of cracks and the effect of steady infiltration encountered in unsaturated backfills would increase the lateral force of earthen structures. This study presented a more realistic understanding of the service state behavior of retaining walls and a useful strategy for evaluating the 3D active earth pressure.
14 citations
TL;DR: In this paper , the structural behavior of concrete-filled cold-formed steel stub columns with semi-oval cross sections was investigated via experimental and numerical studies, and a finite element model was developed to emulate the compressive behavior observed from tests and then used to derive more numerical data via parametric analyses.
Abstract: This paper is an attempt to investigate the structural behavior of concrete-filled cold-formed steel stub columns with semi-oval cross sections via experimental and numerical studies. The test campaign included thirteen stub columns tests on four semi-oval sections infilled with both normal and high strength concrete. The details of test campaign and key observations are described and discussed. Validated against the test data obtained from this study, finite element model was developed to emulate the compressive behavior observed from tests and then used to derive more numerical data via parametric analyses. It is worth noting that the current codified design provisions for concrete-filled steel tubular columns do not explicitly include the semi-oval sections investigated herein. The acquired results from the test campaign and numerical analyses were employed to evaluate the applicability of the American Specifications (ANSI/AISC 360 and ACI318) as well as the European Code (EN1994-1-1). The evaluation results indicate that the aforementioned design rules are generally conservative for compressive strength predictions, among which the predictions by the European Code are the most accurate. Design method considering strength enhancement and confinement effect was proposed with improved accuracy. It is suggested to use the proposed design method for the compressive design of concrete-filled cold-formed steel semi-oval stub columns.
14 citations
TL;DR: Wang et al. as discussed by the authors presented a coupled dynamic interaction model between the unsaturated surrounding soil and partially embedded pile under combined loads based on the three-dimensional multiphase viscoelastic continuum and one-dimensional beam theory.
TL;DR: In this paper , a performance-based design strategy for designing viscous dampers to control the structural floor acceleration (FA) responses of the self-centering braced frames (SCBFs) was proposed.
Abstract: The self-centering braced frames (SCBFs) have been widely investigated for enhancing the building structures’ post-earthquake repairability by reducing or even eliminating the residual inter-story drifts. Nevertheless, it has been highlighted in recent research that the flag-shaped hysteretic behavior of SCBFs amplifies structural floor acceleration (FA) responses, which may lead to severe nonstructural damage. This paper intends to overcome this critical shortcoming of SCBFs by controlling FA responses using viscous dampers. This paper focuses on proposing a practical performance-based design strategy for designing viscous dampers to control the FA responses of the SCBF to the targeted level. To this end, the parametric dynamic analyses of a single-degree-of-freedom (SDOF) system were conducted to investigate the influence of the hysteretic parameters of self-centering braces (SCBs) and the contribution of viscous dampers (VDs) on the peak acceleration control in the SCBFs. Based on the results from the parametric dynamic analysis, the prediction models of inelastic displacement and acceleration ratios of the SCBF with VDs (denoted as the hybrid self-centering braced frame, HSCBF) were developed using the artificial neural network (ANN). The design steps included in the proposed method were presented, where a formula was proposed for predicting the absolute FAs of the HSCBF. Four demonstration buildings with 3, 6, 9, and 12 stories were designed and simulated to verify the developed performance-based design method. The analysis results show that the VDs can effectively control the FA responses of the SCBFs and the mean FAs of the designed systems can reach the desired performance level. Moreover, the reasons why VDs can reduce the accelerations of self-centering building structures are preliminarily discussed from the perspectives of frequency domain and higher mode effects. The analysis results indicate that compared to the original SCBFs, the HSCBF tends to vibrate with a lower frequency and show smaller high-mode responses.
TL;DR: In this article , the amplitude-phase characteristics of parametric circuits were examined in order to determine the possibility of their application to control thyristors in the construction of new, simple and reliable voltage stabilizers.
Abstract: This article examines the expansion of the falling section, the amplitude-phase characteristics of parametric circuits in order to determine the possibility of their application to control thyristors in the construction of new, simple and reliable voltage stabilizers. In parametric circuits connected to a voltage source with a low internal resistance, with a certain combination of parameters, the excitation of oscillations at the fundamental frequency is observed, the initial phase of which has a shift with respect to the phase of the applied voltage. Moreover, the phase of the excited oscillations depends on the magnitude of the applied electromotive force. By combining the connection circuits of linear and nonlinear elements, amplitude-phase characteristics of various shapes are obtained. This article reveals the general patterns in the change in the shape of the amplitude-phase relationships when varying various parameters, discusses the stability of stationary oscillations and their harmonic composition. The study reveals the feasibility of using a resonant circuit to control thyristors voltage stabilizers.
TL;DR: In this article , a decision-making approach with the combined compromise solution under intuitionistic fuzzy sets (IFSs) named as the IF-CoCoSo method based on proposed divergence measures and score function was introduced.
Abstract: The present study introduces a decision-making approach with the combined compromise solution (CoCoSo) under intuitionistic fuzzy sets (IFSs) named as the IF-CoCoSo method based on proposed divergence measures and score function. The aim of the presented approach is to obtain an effective solution for multi-criteria decision-making problems on IFSs context. In this line, a new procedure is presented to derive the criteria weights using generalized score function and parametric divergence measures of IFSs. To compute the criteria weight, a generalized score function and parametric divergence measures are developed on IFSs and discussed some interesting properties. Further, the presented approach is applied to rank and evaluate the therapies for medical decision making problems, which demonstrates its applicability and feasibility. Finally, comparative and sensitivity analyses are discussed for validating the developed method.
TL;DR: In this article , the authors present a survey of the evolution and application of these important techniques for marine vehicles, particularly torpedo-shaped AUVs, done over the past more than 75 years.
TL;DR: Recently, AlphaPose as mentioned in this paper proposed a system that can perform accurate whole-body pose estimation and tracking jointly while running in real-time, using Symmetric Integral Keypoint Regression (SIKR) for fast and fine localization, Parametric Pose Non-Maximum-Suppression (P-NMS) for eliminating redundant human detections and Pose Aware Identity Embedding for jointly estimate and track.
Abstract: Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision. To capture the subtle actions of humans for complex behavior analysis, whole-body pose estimation including the face, body, hand and foot is essential over conventional body-only pose estimation. In this article, we present AlphaPose, a system that can perform accurate whole-body pose estimation and tracking jointly while running in realtime. To this end, we propose several new techniques: Symmetric Integral Keypoint Regression (SIKR) for fast and fine localization, Parametric Pose Non-Maximum-Suppression (P-NMS) for eliminating redundant human detections and Pose Aware Identity Embedding for jointly pose estimation and tracking. During training, we resort to Part-Guided Proposal Generator (PGPG) and multi-domain knowledge distillation to further improve the accuracy. Our method is able to localize whole-body keypoints accurately and tracks humans simultaneously given inaccurate bounding boxes and redundant detections. We show a significant improvement over current state-of-the-art methods in both speed and accuracy on COCO-wholebody, COCO, PoseTrack, and our proposed Halpe-FullBody pose estimation dataset. Our model, source codes and dataset are made publicly available at https://github.com/MVIG-SJTU/AlphaPose .
TL;DR: In this article , a robust adaptive finite-time event-triggered control scheme is presented for trajectory tracking control of underactuated surface vessels (USVs) affected by input saturation, parametric uncertainties, time-varying marine environmental disturbances, and limited transmission resources.
TL;DR: In this article , a novel fabrication methodology based on assembling plates and tubes is presented, where inexpensive commonly-used materials were assembled by adhesive in a portable way, and the proposed structures are not only favorable in mechanical performance in terms of multi-stage densification and programmable stiffness and strength, but also promising in low-cost and large scale fabrication.
Abstract: A costly and inefficient manufacturing process significantly impedes broad applications of auxetics. Herein, a novel fabrication methodology based on assembling plates and tubes is presented. Instead of fabricating auxetic structures by regularly-used 3D printing and laser cutting techniques, inexpensive commonly-used materials were assembled by adhesive in a portable way. Quasi-static compression test was carried out experimentally and numerically. Based on reliable finite element models, parametric study and gradient design were conducted for structural optimization. Numerical results reveal the significance of each geometric parameter and give evidence of the advantages of gradient design. The proposed structures are not only favorable in mechanical performance in terms of multi-stage densification and programmable stiffness and strength, but also promising in low-cost and large-scale fabrication. Such a fabrication methodology has great potential in applications of auxetic structures in protective equipment and smart energy absorbers.
01 Jun 2023
TL;DR: In this article , a multi-pass parametric optimisation based on deep reinforcement learning (DRL) is proposed to boost energy efficiency under the changing deformation limits in each pass.
Abstract: Cutting parameters play a major role in improving the energy efficiency of the manufacturing industry. As the main processing method for aviation parts, flank milling usually adopts multi-pass constant and conservative cutting parameters to prevent workpiece deformation but degrades energy efficiency. To address the issue, this paper proposes a novel multi-pass parametric optimisation based on deep reinforcement learning (DRL), allowing parameters to vary to boost energy efficiency under the changing deformation limits in each pass. Firstly, it designs a variable workpiece deformation const.raint on the principle of stiffness decreasing along the passes, based on which it constructs an energy-efficient parametric optimisation model, giving suitable decisions that respond to the varying cutting conditions. Secondly, it transforms the model into a Markov Decision Process and Soft Actor Critic is applied as the DRL agent to cope with the dynamics in multi-pass machining. Among them, an artificial neural network-enabled surrogate model is applied to approximate the real-world machining, facilitating enough explorations of DRL. Experimental results show that, compared with the conventional method, the proposed method improves 45.71% of material removal rate and 32.27% of specific cutting energy while meeting deformation tolerance, which substantiates the benefits of the energy-efficient parametric optimisation, significantly contributing to sustainable manufacturing.
TL;DR: In this paper , a concurrent optimization procedure was presented for composite laminates under the low-velocity impact, where both the micro-structure and macrostructure layout parameters have been optimized simultaneously.
TL;DR: In this paper , a distributed optimization algorithm for solving online personalized optimization problems over a network of computing and communicating nodes, each of which linked to a specific user, is presented, where the local objective functions are assumed to have a composite structure and to consist of a known time-varying (engineering) part and an unknown (user-specific) part.
Abstract: We present a distributed optimization algorithm for solving online personalized optimization problems over a network of computing and communicating nodes, each of which linked to a specific user. The local objective functions are assumed to have a composite structure and to consist of a known time-varying (engineering) part and an unknown (user-specific) part. Regarding the unknown part, it is assumed to have a known parametric (e.g., quadratic) structure a priori , whose parameters are to be learned along with the evolution of the algorithm. The algorithm is composed of two intertwined components: 1) a dynamic gradient tracking scheme for finding local solution estimates and 2) a recursive least squares scheme for estimating the unknown parameters via user’s noisy feedback on the local solution estimates. The algorithm is shown to exhibit a bounded regret under suitable assumptions. Finally, a numerical example corroborates the theoretical analysis.
TL;DR: In this article , the authors proposed a probabilistic data self-clustering method for damage detection of large-scale civil structures by getting an idea from semi-parametric extreme value theory.
TL;DR: In this paper , two real-time methods, YOLOv3-tiny-KLT, are proposed to track structural motions in a two-storey steel structure.
TL;DR: In this paper , the authors presented machine learning methods for predicting flow condensing heat transfer coefficients (HTCs) inside horizontal tubes based on an assembled database, which contains 6064 experimental data of 28 pure fluids and covers broad operating conditions.
TL;DR: In this paper , an extension of the state-observer-based finite-control-set model-predictive control framework for power converter systems with parametric uncertainties is presented.
Abstract: An event-triggered control technique has been developed recently. This technique explicitly reduced the signal transmission by introducing a flexible design of threshold inequalities. It was later extended to event-triggered model-predictive control for power converter systems. In this letter, by incorporating this control technique into an extended state-observer-based finite-control-set model-predictive control framework, we have developed a new model-predictive control architecture for power converter systems with parametric uncertainties. Meanwhile, a novel cost function with respect to the angle minimization term is embedded into this proposal. The novelty of our development lies not only in integrating the event-triggered mechanism with the suggested finite-control-set model-predictive control architecture for facilitating the alleviation of performance deterioration caused by parameter variations and model uncertainties, but also in a multiobjective optimization design that allows the switching frequency in a low value. Finally, extensive simulative and experimental investigations for a modular multilevel converter confirm the interest and the viability of the proposed design methodology.
TL;DR: In this paper , a dynamic model of a pipe without fluid, with fixed-fixed ends and restrained by a middle clip is established, where the clip is modeled as a rigid body with a certain width, which is elastically connected to the base.
TL;DR: In this article , the effects of water depth, exterior and interior hydrodynamic pressure, the depth of embedment as well as axial loads on the kinematic response and deformation performance of offshore pipe piles are discussed in a parametric study.
TL;DR: In this article , a physics-data combined machine learning (PDCML) method for non-intrusive parametric reduced-order modeling in small-data regimes is presented.
TL;DR: In this paper , a new iterative learning control (ILC) scheme for trajectory tracking of pneumatic muscle actuators with state constraints is proposed, where the barrier Lyapunov function (BLF) is used in the analysis, which reaches infinity when some of its arguments approach limits.
Abstract: In this article, we propose a new iterative learning control (ILC) scheme for trajectory tracking of pneumatic muscle (PM) actuators with state constraints. A PM model is constructed in three-element form with both parametric and nonparametric uncertainties, while full state constraints are considered for enhancing operational safety. To ensure that system states are within the predefined bounds, the barrier Lyapunov function (BLF) is used in the analysis, which reaches infinity when some of its arguments approach limits. The proposed ILC incorporates the BLF with the composite energy function (CEF) approach and ensures the boundedness of CEF in the closed-loop, thus, assuring that those limits are not transgressed. Through rigorous analysis, we show that under the proposed ILC scheme, uniform convergences of PM state tracking errors are guaranteed. Simulation studies and experimental validations are conducted to illustrate the efficacy of the proposed scheme. Experimental results show that the proposed ILC satisfies the state constraint requirements and the tracking error is less than 2.5% of the desired trajectory.