Acceleration Method Research Articles

Porosity-dependent free vibration and transient responses of functionally graded composite plates employing higher order thickness stretching model

Tailoring the mechanical properties in hybrid materials, like functionally graded materials (FGMs), has become more pragmatic with the recent progress in material manufacturing and design. The porosities in FGMs, which develop during the manufacturing process, may become detrimental to armored plates or bulletproof designs. On the other hand, gradient-porosity distributions may have broad advantages in the design of lightweight and variable-stiffness aircraft components. The present study investigates the free vibration and transient responses of porosity-gradient FGM plates. A higher order theory, which considers the transverse shear and normal deformation, warping of the transverse cross-section, and higher order rotary inertia, is utilized for the first time to model the deformation of the porous FGM plate. The advantages of this model are (i) higher order kinematic terms for membrane and bending deformations due to the coupled membrane-bending behavior of FGMs in addition to the thickness-stretching effects, and (ii) the flexibility of applying external loads at different points along the thickness direction of the FGM plate. An analytical solution technique, popularly known as Navier’s approach, is adopted for the spatial solutions, and Newmark’s average acceleration method is utilized for the temporal solutions. The influence of the geometrical and porosity parameters on the structure’s vibration response is studied. Natural frequencies are affected significantly with uniform porosity distribution, while graded porosities can tweak vibration response in a small range but with better control. In the absence of the elasticity solutions, the present results may be considered the possible benchmark solutions for comparison of the other two-dimensional (2D) kinematic models.

Black-Box Acceleration of Monotone Convex Program Solvers

When and where was the study conducted: This work was done in 2018, 2019 and 2020 when Palma London was a PhD student at Caltech and Shai Vardi was a postdoc at Caltech. This work was also done in part while Palma London was visiting Purdue University, and while Reza Eghbali was a postdoctoral fellow the Simons Institute for the Theory of Computing. Adam Wierman is a professor at Caltech. Article Summary and Talking Points: Please describe the primary purpose/findings of your article in 3 sentences or less. This paper presents a framework for accelerating (speeding up) existing convex program solvers. Across engineering disciplines, a fundamental bottleneck is the availability of fast, efficient, accurate solvers. We present an acceleration method that speeds up linear programing solvers such as Gurobi and convex program solvers such as the Splitting Conic Solver by two orders of magnitude. Please include 3-5 short bullet points of “Need to Know” items regarding this research and your findings. - Optimizations problems arise in many engineering and science disciplines, and developing efficient optimization solvers is key to future innovation. - We speed up linear programing solver Gurobi by two orders of magnitude. - This work applies to optimization problems with monotone objective functions and packing constraints, which is a common problem formulation across many disciplines. Please identify 2 pull quotes from your article that best capture the novelty and impact of your research. “We propose a framework for accelerating exact and approximate convex programming solvers for packing linear programming problems and a family of convex programming problems with linear constraints. Analytically, we provide worst-case guarantees on the run time and the quality of the solution produced. Numerically, we demonstrate that our framework speeds up Gurobi and the Splitting Conic Solver by two orders of magnitude, while maintaining a near-optimal solution.” “Our focus in this paper is on a class of packing problems for which data is either very costly or hard to obtain. In these situations, the number of data points available is much smaller than the number of variables. In a machine-learning setting, this regime is increasingly prevalent because it is often advantageous to consider larger and larger feature spaces, while not necessarily obtaining proportionally more data.” Article Implications - Please describe in 5 sentences or less the innovative takeaway(s) of your research. This framework applies to optimization problems with monotone objective functions and packing constraints, which is a common problem formulation across many disciplines, including machine learning, inference, and resource allocation. Providing fast solvers for these problems is crucial. We exploit characteristics of the problem structure and leverage statistical properties of the problem constraints to allow us to speed up optimization solvers. We present worst-case guarantees on run-time, and empirically demonstrate speedups of two orders of magnitude. - Please describe in 5 sentences or less why your findings would be of interest to the general public. Many problems in engineering, science, math, and machine learning involve solving an optimization problem. Fast, efficient optimization solvers are key to future innovation in science and engineering. This work presents a tool to accelerate existing convex solvers, and thus can also be applied to future solvers. As the size of datasets grow it is even more crucial to have fast solvers. - Who would be the most impacted by your research (i.e. by industry, job title, consumer category). Our work impacts machine-learning researchers and optimization researchers, in industry or academia.

Assessment of Patient-Centered Outcomes When Treating Palatally Impacted Canines Using Conventional Versus Accelerated Minimally Invasive Corticotomy-Assisted Orthodontic Treatment: A Randomized Controlled Trial.

ObjectiveThis study aimed to investigate whether there were any differences in pain levels, discomfort, and functional impairments when treating palatally impacted canines (PICs) using the conventional treatment method compared to the accelerated minimally invasive corticotomy-assisted method.Materials and methodsFifty-two patients (11 males and 41 females) with unilateral PICs were included. The patients were randomly assigned to the conventional traction group (26 patients, mean age of 20.37 ± 2.15 years) or the minimally-invasive corticotomy-assisted group (26 patients, mean age of 20.18 ± 2.18 years). The levels of pain, discomfort, and functional difficulties were assessed using a visual analog scale (VAS) after 24 hours (T1), four days (T2), seven days (T3), 14 days (T4), and 28 days (T5) following the surgical exposure procedure.ResultsThere were no statistically significant differences between the two treatment groups for any patient-centered outcome at all assessment times (P>0.01). The levels of pain and discomfort were slightly greater in the conventional group than in the corticotomy-assisted group on the first day after surgical exposure, with no significant difference between the two groups (mean pain: 4.11, P=0.481; mean discomfort: 9.00, P=0.223). Pain and discomfort required seven days to reach low levels and four weeks to reach the lowest levels in both study groups. The levels of swelling, mastication difficulties, swallowing difficulties, limitation in jaw movements and speech changes were mild to moderate on the first postoperative day and the recovery time was four days postoperatively for swallowing difficulties and speech changes. In comparison, the recovery time was seven days for the other three outcomes in both study groups.ConclusionsAfter one day of the surgical intervention, either by conventional or corticotomy-assisted methods, the patients reported mild to moderate pain, discomfort, and functional impairments. These disabilities gradually reached low levels during the first and second weeks to reach their lowest levels four weeks postoperatively in both study groups. The similarity between the conventional and the acceleration methods in pain levels and other oral disabilities may make corticotomy-assisted treatment a comfortable and effective method when treating adult patients with PICs. In addition, patient satisfaction with the corticotomy-assisted procedure was high.

Model Compression and Acceleration: Lip Recognition Based on Channel-Level Structured Pruning

In recent years, with the rapid development of deep learning, the requirements for the performance of the corresponding real-time recognition system are getting higher and higher. However, the rapid expansion of data volume means that time delay, power consumption, and cost have become problems that cannot be ignored. In this case, the traditional neural network is almost impossible to use to achieve productization. In order to improve the potential problems of a neural network facing a huge number of datasets without affecting the recognition effect, the model compression method has gradually entered people’s vision. However, the existing model compression methods still have some shortcomings in some aspects, such as low rank decomposition, transfer/compact convolution filter, knowledge distillation, etc. These problems enable the traditional model compression to cope with the huge amount of computation brought by large datasets to a certain extent, but also make the results unstable on some datasets, and the system performance has not been improved satisfactorily. To address this, we proposed a structured network compression and acceleration method for the convolutional neural network, which integrates the pruned convolutional neural network and the recurrent neural network, and applied it to the lip-recognition system in this paper.

Pendugaan Umur Simpan Ikan Patin Salai Menggunakan Metode Akselerasi Dengan Kemasan HDPE dan Teknik Pengemasan Aluminium Foil

The goal of this research was to estimate the shelf life of salai catfish using the ASLT (Accelerated Shelf-Life Testing) method with high-density polyethylene (HDPE) plastic, vacuum aluminum foil, and non-vacuum aluminum foil. By storing the salai catfish for thirty days at different temperature levels, namely 30, 35, and 40°C, the acceleration method was used to predict the shelf life. Changes in rancidity sensory and thiobarbituric acid (TBA) levels were observed. The obtained data were analyzed using linear regression to show the relationship between storage time and the measured variables. Furthermore, the Arrhenius method was used to calculate the shelf life of salai catfish in order to compare the quality degradation of salai catfish. The best result was obtained in the treatment of salai catfish with vacuum aluminum foil was 32,56 days at 30°C based on the TBA test. The regression equation were y= -2875,7x + 5,2812, R2= 0,9855.

Hyperpower least squares progressive iterative approximation

Geometric iterative methods (GIMs) generate curves or surfaces that fit (interpolate or approximate) given sets of data points. Standard GIMs use the Richardson iteration or gradient descent method, so they converge relatively slowly. This paper investigates the GIMs acceleration method, which is based on the use of more efficient methods for the matrix inverse approximation. That is, the possibility to use hyperpower iterative methods is being explored. As a result, a novel GIM named hyperpower least squares progressive iterative approximation (HPLSPIA) is proposed. The convergence of the HPLSPIA method is analyzed, and the computational complexity is briefly discussed. The method is then applied to tensor product B-spline surface fitting. Several HPLSPIA methods utilizing different hyperpower methods for the matrix inverse approximation are experimentally compared. It is shown that polynomial factorizations used in the hyperpower iterative methods significantly affect the efficiency of the HPLSPIA methods.

The high-order smooth interpolated reproducing kernel particle method for elastodynamics problems

Combining the interpolation reproducing kernel particle method (IRKPM) with the integral weak form of elastodynamics, we present a high-order smooth interpolated reproducing kernel particle method for an elastodynamics plane problem. The shape function of IRKPM not only has the interpolation property at any point but also has a high-order smoothness not lower than that of the kernel function. This new method overcomes the difficulties of most meshless methods in dealing with essential boundary conditions and ensures high numerical accuracy. For time domain integration, we use the classical Newmark average acceleration method. By numerical examples we demonstrate that the proposed method has the advantages of higher accuracy, smaller scale of solving problem, and direct application of boundary conditions.

Linear stability analysis via simulated annealing and accelerated relaxation

Simulated annealing (SA) is a kind of relaxation method for finding equilibria of Hamiltonian systems. A set of evolution equations is solved with SA, which is derived from the original Hamiltonian system so that the energy of the system changes monotonically while preserving Casimir invariants inherent to noncanonical Hamiltonian systems. The energy extremum reached by SA is an equilibrium. Since SA searches for an energy extremum, it can also be used for stability analysis when initiated from a state where a perturbation is added to an equilibrium. The procedure of the stability analysis is explained, and some examples are shown. Because the time evolution is computationally time consuming, efficient relaxation is necessary for SA to be practically useful. An acceleration method is developed by introducing time dependence in the symmetric kernel used in the double bracket, which is part of the SA formulation described here. An explicit formulation for low-beta reduced magnetohydrodynamics (MHD) in cylindrical geometry is presented. Since SA for low-beta reduced MHD has two advection fields that relax, it is important to balance the orders of magnitude of these advection fields.

Sensor network control based on randomized and multi-agent approaches

In this paper, a development of randomized and multiagent algorithms is presented. The examples and their advantages are discussed. Different combined algorithms which are applicable for the multi-sensor multitarget tracking problem are shown. These algorithms belong to the class of methods used in derivative-free optimization and has proven efficacy in the problems including significant non-statistical uncertainties. The new algorithm which is an Accelerated consensus-based SPSA algorithm is validated through simulation.The main feature of that algorithm, combining the SPSA techniques, iterative averaging (“Local Voting Protocol”) and Nesterov Acceleration Method, is the ability to solve distributed optimization problems in the presence of signals with fully uncertain distribution; the only assumption is the signal’s limitation.

A fully explicit staggered algorithm for near‐field wave propagation of fluid‐saturated porous media based on u‐p dynamic formulation

AbstractNear‐field wave propagation of the fluid‐saturated porous media (FSPM) is an important issue in soil dynamics and geotechnical earthquake engineering. In the current study, a fully explicit staggered algorithm for the near‐field wave propagation analysis of the FSPM in the time domain is developed based on the u‐p dynamic formulation. The decoupling of dynamic formulation is implemented by the diagonalization of the mass matrix and pore fluid compressibility matrix. The central difference method and Newmark constant average acceleration method are used for the solution of the displacement and velocity of solid skeleton, and the backward difference method is used for the solution of pore fluid pressure in the time domain. The effectiveness and feasibility of the matrix diagonalization are verified by the comparison with the classical numerical algorithm. The proposed algorithm is also validated by the comparison of the numerical results with the corresponding analytical solution results. Combing with the transmitting artificial boundary condition, the proposed algorithm is then applied to investigate the seismic response of a FSPM free field, and its applicability to the typical near‐field wave propagation problems of the FSPM is indicated. The stability analysis of the proposed algorithm is finally conducted, and the corresponding stability criterion is presented. For the proposed algorithm, all the dynamic variables of the FSPM are solved in an iterative way and the coupling dynamic equations need not to be solved at each time step. The computational effort can be reduced considerably, and the computational efficiency can be improved remarkably.

Anderson acceleration and linear diffusion for accelerating the [formula omitted]-eigenvalue problem for the transport equation

This work focuses on the k-eigenvalue problem of the neutron transport equation to solve for the largest eigenvalue (keff) and the corresponding eigenmode, called the fundamental mode. This problem is usually solved using the power iteration method. However, the convergence of this algorithm can be very slow, especially if the dominance ratio is high as is the case in reactor physics applications. Thus, the power iteration method has to be accelerated in some ways to improve its convergence.One such acceleration is the Chebyshev acceleration method which has been widely applied to legacy codes. In recent years, nonlinear methods have been applied to solve the k-eigenvalue problem. Nevertheless, they are often compared to the unaccelerated power iteration. Past works have compared and contrasted the benefits of the Anderson acceleration method for the neutron transport equation, and the analysis is improved in this work by studying the impact of preconditioning acceleration techniques on the overall performance.In this work, the transport operator is inverted using the source iteration method with the discrete ordinates (Sn) method. Therefore, keeping in mind the need for improving the power iteration algorithm, we also focus on a different type of acceleration which is the diffusion synthetic acceleration (DSA) usually employed for improving the inner iterations. In this research effort, DSA is applied to the power iteration. Besides, Anderson and Chebyshev accelerations are combined with this external DSA scheme to evaluate the computational gain.All these methods have been applied to a benchmark case of a small pressurised water reactor, KAIST 3A.

Anderson Acceleration for Nonsmooth Fixed Point Problems

We give new convergence results of Anderson acceleration for the composite $\max$ fixed point problem. We prove that Anderson(1) and EDIIS(1) are q-linear convergent with a smaller q-factor than existing q-factors. Moreover, we propose a smoothing approximation of the composite max function in the contractive fixed point problem. We show that the smoothing approximation is a contraction mapping with the same fixed point as the composite $\max$ fixed point problem. Our results rigorously confirm that the nonsmoothness does not affect the convergence rate of the Anderson acceleration method when we use the proposed smoothing approximation for the composite $\max$ fixed point problem. Numerical results for constrained minimax problems, complementarity problems, and nonsmooth differential equations are presented to show the efficiency and good performance of the proposed Anderson acceleration method with smoothing approximation.

A novel capacity expansion and recognition acceleration method for dot-dispersing coded targets in photogrammetry

In close-range photogrammetry, some improved designs have been developed to increase the coding capacity of Schneider-like concentric circular coded targets. However, another typical type, Hattori-like dot-dispersing coded targets (HCTs), is rarely expanded. In this paper, we give our detailed solution to recognize a kind of non-public HCT used in video-simultaneous triangulation and resection systems. Then, an advanced HCT (AHCT) with multiple templates and simplified -Invariant is proposed, which achieves capacity expansion and recognition acceleration. First, the cross-ratio invariant is used in template recognition, and then the affine transformation is used in decoding. During the template recognition process, multiple templates are designed to expand the coding capacity, and a simplified -Invariant is adopted to accelerate the recognition. Experiments are carried out with different shooting angles ranging from 0° to 80°, with smaller coded targets, with mixed coded targets of different sizes and with large outdoor scenes, and the results show that AHCTs can not only preserve the stability of the HCTs, but also achieve the capacity growth of coded targets at a faster recognition rate by 14.6%. The AHCTs with large capacity can be applied in scenarios with a large size or complex structure, and the acceleration advantage can be considered in real-time dynamic domains.

Monte Carlo Source Convergence Acceleration by Hybrid Multigroup and Continuous Energy Neutron Transport

A novel source convergence acceleration method for Monte Carlo eigenvalue calculations is proposed in this paper. The method consists of simulating the bulk of the inactive cycles with online-generated multigroup cross sections. Then the active cycles are simulated with continuous-energy cross sections to preserve full fidelity. The method was implemented in the Monte Carlo code SCONE and tested on several three-dimensional full-length assembly models. In some cases, the same multigroup cross sections were used for several spatially separated materials in order to limit statistical uncertainties. The method was shown to accelerate calculations by a factor of 2.5 to 5 at the cost of a slightly increased standard deviation in the flux distribution estimated across several independent simulations. The memory usage due to storing multigroup cross sections does not seem to be prohibitive for practical applications.

Development and verification of the hexagonal core simulation capability of the NECP-X code

The whole-core high-fidelity calculation capability for hexagonal cores is developed in the NECP-X code for VVER and other hexagonal reactors, including the 2D/1D based transport and Global-Local resonance calculation methods. Furthermore, the spatial domain decomposition-based parallel strategy and the unstructured coarse-mesh finite difference (CMFD) acceleration method is developed to improve the efficiency, which can realize rectangular, hexagonal, and other polygon grid-based pin-by-pin acceleration. The C5G7 3D hexagonal benchmark problem is calculated to test the performance of the transport solver. The results agree well with the Monte Carlo solutions and demonstrate good acceleration performance. The code is then applied to the “X-2” VVER-1000 benchmark, and the results show that the bias of eigenvalue is less than 30pcm, and the maximum bias of assembly power is 0.61 %.

Development of look-ahead NURBS interpolation based on the exponential function

Aiming at the problem of large number of points and complex calculation of NURBS pre-interpolation, this paper puts forward a look-ahead interpolation with offline feedrate optimization. The NURBS interpolator is divided into two stages: pre-interpolation and real-time interpolation. The pre-interpolation preprocesses the curve segment by segment according to the curvature characteristics, at the same time the exponential function method is adopted during the pre-interpolation in the look-ahead module. This method makes the step increment of interpolation parameters change exponentially in the area with gentle curvature, and greatly reduces the number of pre-interpolation points, which reduces the amount of calculation and improves the real-time performance. The real-time interpolation stage adopts the bidirectional adaptive acceleration and deceleration control method to realize speed smoothing without needing to calculate the deceleration point. The simulation results show that the real-time performance of the algorithm is greatly improved.

An Effective Iterated Greedy Algorithm for a Robust Distributed Permutation Flowshop Problem With Carryover Sequence-Dependent Setup Time

A new scheduling problem, the distributed permutation flowshop scheduling problem with uncertain processing times and carryover sequence-dependent setup time (DPUC), is addressed. The DPUC is an important application problem in modern electronics manufacturing. A robust model is established for the DPUC with makespan criterion. A counter-intuitive paradox is found, that is, adding a new job to one of the production lines can reduce the completion time of the production line. Two acceleration methods are provided to save computational efforts. An iterated greedy algorithm called IG_FS is proposed to solve the DPUC. A heuristic based on the well-known NEH is proposed to generate the initial solution for the IG_FS. In the destruction phase of the IG_FS, dynamic sizes based on both adaptability and randomness are provided to improve the exploration capability. During the local search phase of the IG_FS, a hybrid local search method consisting of shift and swap operators is presented to exploit more diverse search areas. Extensive experiments show that the proposed IG_FS performs significantly better than the six competing algorithms adapted from the closely related scheduling literature.

Flow Estimation by Flow Induced Vibration of Bluff Bodies

The study confirms the feasibility of using information from flow-induced vibration generated by bluff bodies for measurement of flow. The proposed methodology is based on experiments conducted for recording acceleration signals from vibration sensors embedded along with bluff bodies in cross flow. The studies were undertaken in a wide Reynolds number range of 4700 to 5.655x105, with five different geometries of bluff bodies for shape optimization. Resonance and vortex shedding frequencies of samples are determined experimentally. The recorded acceleration signals are analysed using three different techniques such as frequency shift method, resonance amplitude method and overall acceleration estimation method. In this, the frequency shift method shows correlation at low flow velocities. In the resonance amplitude method and overall acceleration method, acceleration levels show a cubic relation with the flow rate. In the resonance amplitude method, obtained R2 values are from 0.93 to 0.99. Overall acceleration estimation method has shown better correlation with flow rate and its R2 values were above 0.99. The study confirms that application of all three methods together yields reasonably good estimation for a wide range of flow.

Robust Standard Gradient Descent Algorithm for ARX Models Using Aitken Acceleration Technique.

A robust standard gradient descent (SGD) algorithm for ARX models using the Aitken acceleration method is developed. Considering that the SGD algorithm has slow convergence rates and is sensitive to the step size, a robust and accelerative SGD (RA-SGD) algorithm is derived. This algorithm is based on the Aitken acceleration method, and its convergence rate is improved from linear convergence to at least quadratic convergence in general. Furthermore, the RA-SGD algorithm is always convergent with no limitation of the step size. Both the convergence analysis and the simulation examples demonstrate that the presented algorithm is effective.

Human Interleukin-1β Profile and Self-Reported Pain Monitoring Using Clear Aligners with or without Acceleration Techniques: A Case Report and Investigational Study.

There is a growing demand for more aesthetic, comfortable, and faster orthodontic treatments, and clear aligners emerged as a solution to fulfill this need. However, the effectiveness of clear aligners to treat complex malocclusions is yet contentious. The use of acceleration methods could improve the efficacy of clear aligners by stimulating cells' mechanobiology through numerous pathways, but this hypothesis is still poorly explored. We aimed to monitor the release profile of an inflammatory marker-the interleukin-1β-and to evaluate its relationship with self-reported pain scores with and without the use of acceleration techniques during an orthodontic treatment requiring difficult tooth movements with clear aligners. Case Report. Here, we report a case of a 46-year-old female patient who presented functional and aesthetic complaints. Intraoral examination revealed a diminished overjet and overbite, rotation of teeth 45 and 24, absence of teeth 25, 35, and 36, buccolingual dislocation of tooth 21, a tendency to a Class III malocclusion, and a 2 mm left deviation of the lower midline. This study is divided into three stimulation phases: no stimulation, mechanical vibration stimulation, and photobiomodulation. Interleukin-1β levels in gingival crevicular fluid samples from the pressure side of six selected teeth were evaluated at four time points after the orthodontic treatment onset. Pain monitoring in those teeth was performed using a visual analogue scale at the same time points. Interleukin-1β protein production peaked 24 h after treatment onset. Complex movements were associated with increased self-reported pain. Clear aligners show limitations in solving complex tooth movements, even when combined with acceleration. The development of customized and programmable stimulation microdevices integrated into "smart aligners," which could be designed to specifically stimulate the direction of movement and stimulation parameters and could constitute a solution to optimize the orthodontic tooth movement with clear aligners.