Integrated energy system is an energy supply method that enables the complementary and efficient utilization of multiple energy sources. However, integrated energy system involves multiple stakeholders, including the ...
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Integrated energy system is an energy supply method that enables the complementary and efficient utilization of multiple energy sources. However, integrated energy system involves multiple stakeholders, including the integrated energy operator, energy storage system, and energy user. Their behaviors can lead to reduced system benefits, increased carbon emissions, and even violations. To address the above issues, an integrated energy system hybrid game model with the participation of the regulatory agency is constructed, and a divide-andconqueralgorithm is proposed to solve it. Firstly, this study establishes a Stackelberg game model to analyze the interactions among participants within the system and formulates a non-cooperative game model to investigate the relationship between integrated energy system and regulatory agency. Then, game theory is combined with the divide-and-conquer algorithm to solve the hybrid game model, evaluating the optimal strategies for the integrated energy operator as the leader, the energy storage system and energy user as followers under regulatory agency's interventions. Finally, a case study is conducted to analyze the regulatory agency's goal of maximizing overall system benefits and environmental benefits. By analyzing the impacts of various regulatory strategies on the system, this study provides actionable decision support and policy recommendations for the regulatory agency.
In addressing the significant influence of material dielectric parameters on outdoor three-dimensional ray tracing predictions, an algorithm based on divide-and-conquer strategy for calibrating the dielectric properti...
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ISBN:
(纸本)9798350353129;9798350353136
In addressing the significant influence of material dielectric parameters on outdoor three-dimensional ray tracing predictions, an algorithm based on divide-and-conquer strategy for calibrating the dielectric properties of materials is proposed. The algorithm segments the solution space for dielectric parameters into smaller sub-spaces, resolving each incrementally to arrive at the global optimal solution. It employs a prudent convergence strategy for the solution space, discarding those sub-spaces that have a low probability of containing the optimum. The results indicate that this algorithm not only maintains high accuracy but also facilitates rapid calibration of dielectric parameters.
In this paper, we consider networks with topologies described by some connected undirected graph G = (V, E) and with some agents (fusion centers) equipped with processing power and local peer-to-peer communication, an...
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In this paper, we consider networks with topologies described by some connected undirected graph G = (V, E) and with some agents (fusion centers) equipped with processing power and local peer-to-peer communication, and optimization problem mini {F(i) = n-ary sumation ������is an element of V f ������(i)} with local objective functions f ������ depending only on neighboring variables of the vertex ������ is an element of V. We introduce a divide-and-conquer algorithm to solve the above optimization problem in a distributed and decentralized manner. The proposed divide-and-conquer algorithm has exponential convergence, its computational cost is almost linear with respect to the size of the network, and it can be fully implemented at fusion centers of the network. In addition, our numerical demonstrations indicate that the proposed divide-and-conquer algorithm has superior performance than popular decentralized optimization methods in solving the least squares problem, both with and without the ������1 penalty, and exhibits great performance on networks equipped with asynchronous local peer-to-peer communication.
Reducing energy consumption in the energy-intensive production systems is of great significance and attracts more and more attention. Although a lot of efforts have been devoted to formulate and solve the energy consu...
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Reducing energy consumption in the energy-intensive production systems is of great significance and attracts more and more attention. Although a lot of efforts have been devoted to formulate and solve the energy consumption optimisation problem in the Bernoulli serial lines, existing methods for solving the problem in long Bernoulli lines either cannot obtain the optimal solution or are time-consuming. For this purpose, this paper divides the problem in the long line into a set of problems in two-machine lines and proposes a computationally efficient and globally convergent algorithm to solve it. Extensive numerical experiments show that the proposed algorithm not only can optimally (in the numerical way) solve the energy consumption optimisation problem in long Bernoulli serial lines, but also is orders of magnitude more efficient than existing algorithms.
Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse engineering. Splines such as Bezier, B-Spline and NURBS curv...
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Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse engineering. Splines such as Bezier, B-Spline and NURBS curves are usually employed in engineering applications and are intensively used for fitting purposes. The optimization of their shapes and localization parameters, however, is a very complex task. The literature presents many methods which empirically set some important parameters, such as the number of control points. As guessing such a value is difficult, this paper presents a new method to choose it through a multi-curve fitting method, based on linear least square optimizations, using a divide-and-conquer algorithm and an error tolerance threshold. Four prime procedures compose the method: the conquer step fits curves over subset point clouds;the combine step glues curve segments together with some selective continuity;the divide step splits subsets which are not properly fitted yet;and the merge step blends curve segments together. Several curve setups were tested in well-known benchmarks, using four-division strategies: bisection, error balance, point with the greatest curvature and point with the smallest curvature. The developed method allows for fast computation even for larger point clouds, and it was able to properly reconstruct each tested shape, even with the addition of synthetic noise. We also demonstrate that it can be significantly faster than a single-curve fitting using the same number of control points.(c) 2022 Elsevier Ltd. All rights reserved.
There has been a growing attention to efficient simulations of multibody systems, which is apparently seen in many areas of computer-aided engineering and design both in academia and in industry. The need for efficien...
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There has been a growing attention to efficient simulations of multibody systems, which is apparently seen in many areas of computer-aided engineering and design both in academia and in industry. The need for efficient or real-time simulations requires high-fidelity techniques and formulations that should significantly minimize computational time. Parallel computing is one of the approaches to achieve this objective. This paper presents a novel index-3 divide-and-conquer algorithm for efficient multibody dynamics simulations that elegantly handles multibody systems in generalized topologies through the application of the augmented Lagrangian method. The proposed algorithm exploits a redundant set of absolute coordinates. The trapezoidal integration rule is embedded into the formulation and a set of nonlinear equations need to be solved every time instant. Consequently, the Newton-Raphson iterative scheme is applied to find the system coordinates and joint constraint loads in an efficient and highly parallelizable manner. Two divide-and-conquer-based mass-orthogonal projections are performed then to circumvent the effect of constraint violation errors at the velocity and acceleration level. Sample open- and closed-loop multibody system test cases are investigated in the paper to confirm the validity of the approach. Challenging simulations of multibody systems featuring long kinematic chains are also performed in the work to demonstrate the robustness of the algorithm. The details of OpenMP-based parallel implementation on an eight-core shared memory computer are presented in the text and the parallel performance results are extensively discussed. Significant speedups are obtained for the simulations of small- to large-scale multibody open-loop systems. The mentioned features make the proposed algorithm a good general purpose approach for high-fidelity, efficient or real-time multibody dynamics simulations.
Multinomial logistic regression (MLR) is an effective classifier in spatial-spectral-based hyperspectral image (HSI) classification. However, in some typical scenarios, such as Gaussian regularized MLR (GSMLR) and Lap...
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Multinomial logistic regression (MLR) is an effective classifier in spatial-spectral-based hyperspectral image (HSI) classification. However, in some typical scenarios, such as Gaussian regularized MLR (GSMLR) and Laplacian graph regularized MLR (LPMLR), it hits a large (cd) x (cd) linear system during the regressors learning procedure that is unbearable in both space and time complexity (c is the number of classes and d is the length of feature). Even if using middle-sized features, it often runs out of memory. To this end, we propose two exact divide-and-conquer (DC) algorithms, DC-GSMLR and DC-LPMLR, to reduce the computation complexity. Both decompose the regressors learning problem into a series of equivalent smaller subproblems, each of which can be solved in closed form. Unlike the approximation ones available, they provide exact merged solutions instead. With the same accuracy, DC-LPMLR and DC-GSMLR only need to solve c + 1 and 2 d x d linear systems, respectively, significantly reducing the peak memory usage by almost O(c) and O(c(2)/2) times. For time, experiments on two popular HSI datasets indicate considerable speedup ratio as high as one or two orders of magnitude, showing the practicability in real applications. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
This paper presents a new mathematical framework to extend the Generalized divide-and-conquer algorithm (GDCA) for the inverse dynamics analysis of fully actuated constrained multibody systems. Inverse-GDCA (iGDCA) is...
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This paper presents a new mathematical framework to extend the Generalized divide-and-conquer algorithm (GDCA) for the inverse dynamics analysis of fully actuated constrained multibody systems. Inverse-GDCA (iGDCA) is a highly parallelizable method which does not create the mass and Jacobian matrices of the entire system. In this technique, generalized driving forces and constraint loads due to kinematic pairs are clearly and separately differentiated from each other in the equations of motion. As such, it can be easily used for control scheme purposes. iGDCA works based on a series of recursive assembly and disassembly passes to form and solve the equations governing the inverse dynamics of the system. Herein, the mathematical formulations to efficiently combine the dynamics of consecutive bodies in the assembly pass for the purpose of inverse dynamics analysis are presented. This is followed by generating the disassembly pass algorithm to efficiently compute generalized actuating forces. Furthermore, this paper presents necessary mathematical formulations to efficiently treat the inverse dynamics of multibody systems involving kinematic loops with various active and passive boundary conditions. This is followed by the design of a new strategy to efficiently perform the assembly-disassembly pass in these complex systems while avoiding unnecessary computations. Finally, the presented method is applied to selected open-chain and closed-chain multibody systems.
We present a new parallel divide-and-conquer (DC) algorithm based on an execution scheduling by batched kernels for solving real-symmetric tridiagonal eigenvalue problems on manycore systems. Our algorithm has higher ...
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ISBN:
(纸本)9783319780245;9783319780238
We present a new parallel divide-and-conquer (DC) algorithm based on an execution scheduling by batched kernels for solving real-symmetric tridiagonal eigenvalue problems on manycore systems. Our algorithm has higher parallelism and requires less global synchronizations than a conventional algorithm. We compared the performance of the solver based on our algorithm with that of Intel MKL's DC solver and PLASMA's one on Xeon E5, Xeon Phi Knights Corner, and Xeon Phi Knights Landing. The numerical tests show that the implementation of our algorithm is comparable to Intel MKL on Xeon E5 and outperforms Intel MKL and PLASMA on the two Xeon Phi systems.
A new algorithm is presented for the modeling and simulation of multi-flexible-body systems. This algorithm is built upon a divide-and-conquer-based multibody dynamics framework, and it is capable of handling arbitrar...
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A new algorithm is presented for the modeling and simulation of multi-flexible-body systems. This algorithm is built upon a divide-and-conquer-based multibody dynamics framework, and it is capable of handling arbitrary large rotations and deformations in articulated flexible bodies. As such, this work extends the current capabilities of the flexible divide-and-conquer algorithm (Mukherjee and Anderson in Comput. Nonlinear Dyn. 2(1):10-21, 2007), which is limited to the use of assumed modes in a floating frame of reference configuration. The present algorithm utilizes the existing finite element modeling techniques to construct the equations of motion at the element level, as well as at the body level. It is demonstrated that these equations can be assembled and solved using a divide-and-conquer type methodology. In this respect, the new algorithm is applied using the absolute nodal coordinate formulation (ANCF) (Shabana, 1996). The ANCF is selected because of its straightforward implementation and effectiveness in modeling large deformations. It is demonstrated that the present algorithm provides an efficient and robust method for modeling multi-flexible-body systems that employ highly deformable bodies. The new algorithm is tested using three example systems employing deformable bodies in two and three spatial dimensions. The current examples are limited to the ANCF line or cable elements, but the approach may be extended to higher order elements. In its basic form, the divide-and-conquer algorithm is time and processor optimal, yielding logarithmic complexity O(log(N (b) )) when implemented using O(N (b) ) processors, where N (b) is the number of bodies in the system.
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