In order to improve the safety performance of 18650 lithium battery in storage and transportation, the thermal runaway expansion research of nine-palace grid glass fiber partition packaging was studied by experiment a...
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In order to improve the safety performance of 18650 lithium battery in storage and transportation, the thermal runaway expansion research of nine-palace grid glass fiber partition packaging was studied by experiment and computational simulation. The results show that the glass fiber partition with a certain gap between the batteries and the partition can effectively inhibit the thermal runaway expansion of lithium battery. The optimal distance between the battery and the partition is 2.2 mm, and the thickness of the partition is 1.2 mm. Under the optimal condition, the highest temperature near the surface of the battery is only about 130. The safety and protection performance of a lithium battery can be significantly improved by using the optimized glass fiber partition packaging.
Planning a safe and dynamic flyable trajectory for unmanned aerial vehicle (UAV) is the precondition for autonomous flight. Considering environmental complexity and flight safety under limited motor speed, we proposed...
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Planning a safe and dynamic flyable trajectory for unmanned aerial vehicle (UAV) is the precondition for autonomous flight. Considering environmental complexity and flight safety under limited motor speed, we proposed a new time-segmented trajectory planning method, which can ensure motor speed within the allowable range and achieve safe flight. Firstly, the candidate trajectory for quadrotor UAV is expressed by high-order polynomials. Herein, polynomial is used as the expression of trajectory, and nonlinear programming (NLP) is used to calculate polynomial coefficient. Then, two strategies and an initial value calculation method are proposed to improve the efficiency of NLP. Furthermore, aiming at the problem that the initial trajectory of UAV motor cannot meet the current speed limit constraint after the motor speed drops, an adjustment strategy based on feasible trajectory is designed. The method presented in this paper not only enhances flexibility of the flight process, improves solving efficiency of the algorithm but also enables UAV to continue flying when the motor speed is limited. Finally, simulation analysis and comparison illustrate the effectiveness and superiority of the proposed method.
This letter presents a new and comprehensive approach to planning a smooth and optimal path in a planar channel. The algorithm generates a NURBS that traverses the channel, in turn defined by two bounding rational spl...
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This letter presents a new and comprehensive approach to planning a smooth and optimal path in a planar channel. The algorithm generates a NURBS that traverses the channel, in turn defined by two bounding rational splines, and stays inside. A nonlinearly constrained problem is solved to model the shape of the two-sided bounded path to optimise the objective function. The user can choose the degree of the curve that defines the resulting path and optionally add the interpolation of waypoints and orientations. The presented method expands the domain of feasible solutions compared to previous approaches based on nonrational splines, leading to improvements in terms of the objective function. Various examples are provided to illustrate and clarify the method.
We introduce a model for competing in daily fantasy sports competitions. Our approach combines modeling of players' fantasy points and subsequent lineup optimization. The distribution of fantasy points was estimat...
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We introduce a model for competing in daily fantasy sports competitions. Our approach combines modeling of players' fantasy points and subsequent lineup optimization. The distribution of fantasy points was estimated using an ensemble of generative models. We designed a mixed-integer quadratic program to optimize not only the average fantasy points but also the variance and covariance of players' fantasy points to exploit the top-heavy payout structures. We tested our approach on real-world data. Over eight weeks, the model generated a profit of euro2439 with an initial investment of euro7133, resulting in a return on investment of over 34%.
Hybrid conjugate gradient methods are considered as an efficient family of conjugate gradient methods to solve unconstrained optimization problems. In this work, based on the memoryless BFGS update, a convex hybridiza...
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Hybrid conjugate gradient methods are considered as an efficient family of conjugate gradient methods to solve unconstrained optimization problems. In this work, based on the memoryless BFGS update, a convex hybridization of the Hestenes-Stiefel and Dai-Yuan conjugate parameters is presented. To put in place safeguards to protect the sufficient descent property, the given search direction is projected to the orthogonal subspace to the gradient of the objective function. The convergence analysis of the proposed method is addressed under standard assumptions for general functions. The practical merits of the proposed method are computationally demonstrated on a set of CUTEr test functions as well as the well-known nonnegative matrix factorization problem.
With growing needs to develop and improve climate -friendly processes, optimization strategies are essential at all levels of decision -making in chemical and energy processes, including process development, process s...
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With growing needs to develop and improve climate -friendly processes, optimization strategies are essential at all levels of decision -making in chemical and energy processes, including process development, process synthesis and design, as well as process operations, control, scheduling, and planning. Challenges include the formulation of well -posed and well -conditioned process models, and development and application of efficient, reliable optimization algorithms. Here we describe a synthesis of optimization concepts and algorithms that enable large-scale nonlinear programming, nonintrusive decomposition strategies and the inclusion of a wide class of surrogate models. All of these are crucial to address challenging nonconvex, multi -scale problems in Computer Aided Process Engineering (CAPE). These elements are demonstrated through dynamic optimization strategies for novel energy generation, demand -based optimization for specialty chemicals, and optimization with integrated heterogeneous models for carbon capture processes.
Given a finite set of distinct points in R-n and a positive weight for each point, primal and dual algorithms are developed for finding the Euclidean ball of minimum radius so that the weighted Euclidean distance betw...
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Given a finite set of distinct points in R-n and a positive weight for each point, primal and dual algorithms are developed for finding the Euclidean ball of minimum radius so that the weighted Euclidean distance between the center of the ball and each point is less than or equal to the radius of the ball. Each algorithm is based on a directional search method in which the search path at each iteration is either a ray or a two-dimensional circular arc in R-n. At each iteration, a search path is constructed by intersecting bisectors of pairs of points, where the bisectors are either hyperplanes or n-dimensional spheres. Each search path preserves complementary slackness and primal (dual) feasibility for the primal (dual) algorithm. The step size along each search path is determined explicitly. Test problems up to 1000 dimensions and 10,000 points were solved to optimality by both primal and dual algorithms. Computational results also show that these algorithms outperform several open-source SOCP codes.
In the paper Torrealba et al. (2021) an augmented Lagrangian algorithm was proposed for resource allocation problems with the intriguing characteristic that instead of solving the box-constrained augmented Lagrangian ...
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In the paper Torrealba et al. (2021) an augmented Lagrangian algorithm was proposed for resource allocation problems with the intriguing characteristic that instead of solving the box-constrained augmented Lagrangian subproblem, they propose projecting the solution of the unconstrained subproblem onto such box. A global convergence result for the quadratic case was provided, however, this is somewhat counterintuitive, as in usual augmented Lagrangian theory, this strategy can fail in solving the augmented Lagrangian subproblems. In this note we investigate further this algorithm and we show that the proposed method may indeed fail when the Hessian of the quadratic is not a multiple of the identity. In the paper, it is not clear enough that two different projections are being used: one for obtaining their convergence results and other in their implementation. However, despite the lack of theoretical convergence, their strategy works remarkably well in some classes of problems;thus, we propose a hybrid method which uses their idea as a starting point heuristics, switching to a standard augmented Lagrangian method under certain conditions. Our contribution consists in presenting an efficient way of determining when the heuristics is failing to improve the KKT residual of the problem, suggesting that the heuristic procedure should be abandoned. Numerical results are provided showing that this strategy is successful in accelerating the standard method.
In work of Roman A. Polyak [R.A. Polyak, Math. Program. 92 (2002) 197-235.], the Modified Chen-Harker-Kanzow-Smale (CHKS) function was studied to relate a multiplier method and an Interior Prox method with the second ...
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In work of Roman A. Polyak [R.A. Polyak, Math. Program. 92 (2002) 197-235.], the Modified Chen-Harker-Kanzow-Smale (CHKS) function was studied to relate a multiplier method and an Interior Prox method with the second order distance function. Independently, the dislocated hyperbolic penalty function (DHPF) was proposed by A.E. Xavier (1992). DHPF was rewritten and studied in [L. Mallma Ramirez, N. Maculan, A.E. Xavier and V.L. Xavier, RAIRO:RO 57 (2023) 2941-2950.] and [L. Mallma Ramirez, N. Maculan, A.E. Xavier and V.L. Xavier, J. Convex Anal. To appear (2024).]. Thus, this function was called the dislocated hyperbolic function (DHF). In this work, we note that DHF is a particular case of CHKS function. Then we will call the DHF function as the dislocation hyperbolic transformation function.
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