158 resultados para Nonlinear programming


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In this paper, we derive a new nonlinear two-sided space-fractional diffusion equation with variable coefficients from the fractional Fick’s law. A semi-implicit difference method (SIDM) for this equation is proposed. The stability and convergence of the SIDM are discussed. For the implementation, we develop a fast accurate iterative method for the SIDM by decomposing the dense coefficient matrix into a combination of Toeplitz-like matrices. This fast iterative method significantly reduces the storage requirement of O(n2)O(n2) and computational cost of O(n3)O(n3) down to n and O(nlogn)O(nlogn), where n is the number of grid points. The method retains the same accuracy as the underlying SIDM solved with Gaussian elimination. Finally, some numerical results are shown to verify the accuracy and efficiency of the new method.

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In this paper, a new alternating direction implicit Galerkin--Legendre spectral method for the two-dimensional Riesz space fractional nonlinear reaction-diffusion equation is developed. The temporal component is discretized by the Crank--Nicolson method. The detailed implementation of the method is presented. The stability and convergence analysis is strictly proven, which shows that the derived method is stable and convergent of order $2$ in time. An optimal error estimate in space is also obtained by introducing a new orthogonal projector. The present method is extended to solve the fractional FitzHugh--Nagumo model. Numerical results are provided to verify the theoretical analysis.

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Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

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This thesis articulates and examines public engagement programming in an emerging, non¬-traditional site. As a practice-led research project, the creative work proposes a site responsive, engagement centric, agile model for curatorial programming that developed out of the dynamic, new media/digital, curatorial practice at QUT's Creative Industries Precinct. The model and its accompanying exegetical framework, Curating in Uncharted Territories, offer a theoretically informed approach to programming, delivering and reporting for curatorial practices in a non¬-traditional sites of public engagement. The research provides the foundation for full development of the model and the basis for further research.

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A two-dimensional variable-order fractional nonlinear reaction-diffusion model is considered. A second-order spatial accurate semi-implicit alternating direction method for a two-dimensional variable-order fractional nonlinear reaction-diffusion model is proposed. Stability and convergence of the semi-implicit alternating direct method are established. Finally, some numerical examples are given to support our theoretical analysis. These numerical techniques can be used to simulate a two-dimensional variable order fractional FitzHugh-Nagumo model in a rectangular domain. This type of model can be used to describe how electrical currents flow through the heart, controlling its contractions, and are used to ascertain the effects of certain drugs designed to treat arrhythmia.

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Efficient and accurate geometric and material nonlinear analysis of the structures under ultimate loads is a backbone to the success of integrated analysis and design, performance-based design approach and progressive collapse analysis. This paper presents the advanced computational technique of a higher-order element formulation with the refined plastic hinge approach which can evaluate the concrete and steel-concrete structure prone to the nonlinear material effects (i.e. gradual yielding, full plasticity, strain-hardening effect when subjected to the interaction between axial and bending actions, and load redistribution) as well as the nonlinear geometric effects (i.e. second-order P-d effect and P-D effect, its associate strength and stiffness degradation). Further, this paper also presents the cross-section analysis useful to formulate the refined plastic hinge approach.

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Background: Providing motivationally supportive physical education experiences for learners is crucial since empirical evidence in sport and physical education research has associated intrinsic motivation with positive educational outcomes. Self-determination theory (SDT) provides a valuable framework for examining motivationally supportive physical education experiences through satisfaction of three basic psychological needs: autonomy, competence and relatedness. However, the capacity of the prescriptive teaching philosophy of the dominant traditional physical education teaching approach to effectively satisfy the psychological needs of students to engage in physical education has been questioned. The constraints-led approach (CLA) has been proposed as a viable alternative teaching approach that can effectively support students’ self-motivated engagement in physical education. Purpose: We sought to investigate whether adopting the learning design and delivery of the CLA, guided by key pedagogical principles of nonlinear pedagogy (NLP), would address basic psychological needs of learners, resulting in higher self-reported levels of intrinsic motivation. The claim was investigated using action research. The teacher/researcher delivered two lessons aimed at developing hurdling skills: one taught using the CLA and the other using the traditional approach. Participants and Setting: The main participant for this study was the primary researcher and lead author who is a PETE educator, with extensive physical education teaching experience. A sample of 54 pre-service PETE students undertaking a compulsory second year practical unit at an Australian university was recruited for the study, consisting of an equal number of volunteers from each of two practical classes. A repeated measures experimental design was adopted, with both practical class groups experiencing both teaching approaches in a counterbalanced order. Data collection and analysis: Immediately after participation in each lesson, participants completed a questionnaire consisting of 22 items chosen from validated motivation measures of basic psychological needs and indices of intrinsic motivation, enjoyment and effort. All questionnaire responses were indicated on a 7-point Likert scale. A two-tailed, paired-samples t-test was used to compare the groups’ motivation subscale mean scores for each teaching approach. The size of the effect for each group was calculated using Cohen’s d. To determine whether any significant differences between the subscale mean scores of the two groups was due to an order effect, a two-tailed, independent samples t test was used. Findings: Participants’ reported substantially higher levels of self-determination and intrinsic motivation during the CLA hurdles lesson compared to during the traditional hurdles lesson. Both groups reported significantly higher motivation subscale mean scores for competence, relatedness, autonomy, enjoyment and effort after experiencing the CLA than mean scores reported after experiencing the traditional approach. This significant difference was evident regardless of the order that each teaching approach was experienced. Conclusion: The theoretically based pedagogical principles of NLP that inform learning design and delivery of the CLA may provide teachers and coaches with tools to develop more functional pedagogical climates, which result in students exhibiting more intrinsically motivated behaviours during learning.

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The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the spatial nonlocality of the fractional differential operators. The dense coefficient matrices that arise from spatial discretisation of these operators mean that even one-dimensional problems can be difficult to solve using standard methods on grids comprising thousands of nodes or more. In this work we address this issue of efficiency for one-dimensional, nonlinear space-fractional reaction–diffusion equations with fractional Laplacian operators. We apply variable-order, variable-stepsize backward differentiation formulas in a Jacobian-free Newton–Krylov framework to advance the solution in time. A key advantage of this approach is the elimination of any requirement to form the dense matrix representation of the fractional Laplacian operator. We show how a banded approximation to this matrix, which can be formed and factorised efficiently, can be used as part of an effective preconditioner that accelerates convergence of the Krylov subspace iterative solver. Our approach also captures the full contribution from the nonlinear reaction term in the preconditioner, which is crucial for problems that exhibit stiff reactions. Numerical examples are presented to illustrate the overall effectiveness of the solver.

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This study implemented linear and nonlinear methods of measuring variability to determine differences in stability of two groups of skilled (n = 10) and unskilled (n = 10) participants performing 3m forward/backward shuttle agility drill. We also determined whether stability measures differed between the forward and backward segments of the drill. Finally, we sought to investigate whether local dynamic stability, measured using largest finite-time Lyapunov exponents, changed from distal to proximal lower extremity segments. Three-dimensional coordinates of five lower extremity markers data were recorded. Results revealed that the Lyapunov exponents were lower (P < 0.05) for skilled participants at all joint markers indicative of higher levels of local dynamic stability. Additionally, stability of motion did not differ between forward and backward segments of the drill (P > 0.05), signifying that almost the same control strategy was used in forward and backward directions by all participants, regardless of skill level. Furthermore, local dynamic stability increased from distal to proximal joints (P < 0.05) indicating that stability of proximal segments are prioritized by the neuromuscular control system. Finally, skilled participants displayed greater foot placement standard deviation values (P < 0.05), indicative of adaptation to task constraints. The results of this study provide new methods for sport scientists, coaches to characterize stability in agility drill performance.

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In this paper, we look at the concept of reversibility, that is, negating opposites, counterbalances, and actions that can be reversed. Piaget identified reversibility as an indicator of the ability to reason at a concrete operational level. We investigate to what degree novice programmers manifest the ability to work with this concept of reversibility by providing them with a small piece of code and then asking them to write code that undoes the effect of that code. On testing entire cohorts of students in their first year of learning to program, we found an overwhelming majority of them could not cope with such a concept. We then conducted think aloud studies of novices where we observed them working on this task and analyzed their contrasting abilities to deal with it. The results of this study demonstrate the need for better understanding our students' reasoning abilities, and a teaching model aimed at that level of reality.

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We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

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Stability analyses have been widely used to better understand the mechanism of traffic jam formation. In this paper, we consider the impact of cooperative systems (a.k.a. connected vehicles) on traffic dynamics and, more precisely, on flow stability. Cooperative systems are emerging technologies enabling communication between vehicles and/or with the infrastructure. In a distributed communication framework, equipped vehicles are able to send and receive information to/from other equipped vehicles. Here, the effects of cooperative traffic are modeled through a general bilateral multianticipative car-following law that improves cooperative drivers' perception of their surrounding traffic conditions within a given communication range. Linear stability analyses are performed for a broad class of car-following models. They point out different stability conditions in both multianticipative and nonmultianticipative situations. To better understand what happens in unstable conditions, information on the shock wave structure is studied in the weakly nonlinear regime by the mean of the reductive perturbation method. The shock wave equation is obtained for generic car-following models by deriving the Korteweg de Vries equations. We then derive traffic-state-dependent conditions for the sign of the solitary wave (soliton) amplitude. This analytical result is verified through simulations. Simulation results confirm the validity of the speed estimate. The variation of the soliton amplitude as a function of the communication range is provided. The performed linear and weakly nonlinear analyses help justify the potential benefits of vehicle-integrated communication systems and provide new insights supporting the future implementation of cooperative systems.