对流边界层顶部光学湍流的室内模拟研究

对流边界层顶部夹卷层是边界层和自由大气之间的过渡带,夹卷层的湍流结构是其主要特征之一。由于夹卷层的位置较高,进行精细结构观测很难,对此认识较少。利用尺寸为150 cm×150 cm×60 cm室内对流水槽模拟了大气对流边界层的发生和发展。将准直光通过模拟对流边界层,根据光在湍流介质中的传输理论得到混合层顶部夹卷层的温度结构常数的特点,在夹卷层内,归一化的温度结构常数满足相同的规律;在高度0.8zi处,温度结构常数最小,随着高度增加,温度结构常数增大,zi处达最大,然后又随着高度减逐渐小,在高度1.2zi处湍流消失。在边界层顶部zi处,归一化的温度结构常数处于一定的变化范围,归一化温度结构常数处于0.08~0.3之间,这可能与夹卷层的大尺度结构有关。     

聚偏氟乙烯膜三维离子传输通道的构建及其在全钒液流电池中的性能研究

随着新能源技术的不断发展, 大规模储能技术受到了广泛的关注. 全钒液流电池因其容量和功率设计灵活、安全可靠、寿命长等优势成为发展较快的储能电池之一. 离子膜作为液流电池的关键部件, 对电池的能量转化效率、寿命和成本具有显著影响. 本工作以高化学稳定性的聚偏氟乙烯作为膜材料, 利用聚乙二醇和聚乙烯吡咯烷酮分别作为模板和稳定剂, 在聚偏氟乙烯膜内成功构建了具有较好H/V离子选择性的三维离子传输通道. 电池性能测试表明, 该聚偏氟乙烯(PVDF)离子膜有着出色的化学稳定性, 在100 mA•cm^-2电流密度下, 具有98%以上的电流效率和83.5%的能量效率. 此外, 聚偏氟乙烯具有价格低的显著特点, 使其在全钒液流电池中有较好的应用前景.     

Self-consistent check of the validity of Gibbs calculus using dynamical variables

The high- and low-energy limits of a chain of coupled rotators are integrable and correspond respectively to a set of free rotators and to a chain of harmonic oscillators. For intermediate values of the energy, numerical calculations show the agreement of finite time averages of physical observables with their Gibbsian estimate. The boundaries between the two integrable limits and the statistical domain are analytically computed using the Gibbsian estimates of dynamical observables. For large energies the geometry of nonlinear resonances enables the definition of relevant 1.5-degree-of-freedom approximations of the dynamics. They provide resonance overlap parameters whose Gibbsian probability distribution may be computed. Requiring the support of this distribution to be right above the large-scale stochasticity threshold of the 1.5-degree-of-freedom dynamics yields the boundary at the large-energy limit. At the low-energy limit, the boundary is shown to correspond to the energy where the specific heat departs from that of the corresponding harmonic chain.     

An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling

Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems.     

Load balancing in the parallel optimization of block-angular linear programs

Decomposition algorithms for block-angular linear programs give rise to a natural, coarse-grained parallelism that can be exploited by processing the subproblems concurrently within a distributed-memory environment. The parallel efficiency of the distributed approach, however, is critically dependent on the duration of the inherently serial master phase relative to that of the bottleneck subproblem. This paper investigates strategies for improving efficiency in distributed Dantzig—Wolfe decomposition by better balancing the load between the master and subproblem processors. We report computational experience on an Intel iPSC/2 hypercube multiprocessor with test problems having dimensions up to about 30 000 rows, 87 000 columns, and 200 coupling constraints.This paper is dedicated to Phil Wolfe on the occasion of his 65th birthday.     

The Adjoint Newton Algorithm for Large-Scale Unconstrained Optimization in Meteorology Applications

A new algorithm is presented for carrying out large-scale unconstrained optimization required in variational data assimilation using the Newton method. The algorithm is referred to as the adjoint Newton algorithm. The adjoint Newton algorithm is based on the first- and second-order adjoint techniques allowing us to obtain the Newton line search direction by integrating a tangent linear equations model backwards in time (starting from a final condition with negative time steps). The error present in approximating the Hessian (the matrix of second-order derivatives) of the cost function with respect to the control variables in the quasi-Newton type algorithm is thus completely eliminated, while the storage problem related to the Hessian no longer exists since the explicit Hessian is not required in this algorithm. The adjoint Newton algorithm is applied to three one-dimensional models and to a two-dimensional limited-area shallow water equations model with both model generated and First Global Geophysical Experiment data. We compare the performance of the adjoint Newton algorithm with that of truncated Newton, adjoint truncated Newton, and LBFGS methods. Our numerical tests indicate that the adjoint Newton algorithm is very efficient and could find the minima within three or four iterations for problems tested here. In the case of the two-dimensional shallow water equations model, the adjoint Newton algorithm improves upon the efficiencies of the truncated Newton and LBFGS methods by a factor of at least 14 in terms of the CPU time required to satisfy the same convergence criterion.The Newton, truncated Newton and LBFGS methods are general purpose unconstrained minimization methods. The adjoint Newton algorithm is only useful for optimal control problems where the model equations serve as strong constraints and their corresponding tangent linear model may be integrated backwards in time. When the backwards integration of the tangent linear model is ill-posed in the sense of Hadamard, the adjoint Newton algorithm may not work. Thus, the adjoint Newton algorithm must be used with some caution. A possible solution to avoid the current weakness of the adjoint Newton algorithm is proposed.     

波纹圆孔光栏的衍射及其设计

详细研究了波纹光珠菲涅耳衍射特征，提出并论证了调幅正弦波纹光栏级在较大的菲涅耳数范围内有效地抑制光束中央部分的衍射调制，并给出这类波纹光栏用于高功率光系统的设计程序。     

ANP法在西部可持续发展战略体系调整中的应用

论述了在西部开发问题中应用 ANP法辅助决策的可行性和必要性 ,并构建了具体的模型 ,以说明如何应用 ANP法对西部开发的战略体系进行调整 .     

Designing Least-Cost Survivable Wireless Backhaul Networks

This paper presents a new heuristic algorithm for designing least-cost telecommunications networks to carry cell site traffic to wireless switches while meeting survivability, capacity, and technical compatibility constraints. This requires solving the following combinatorial optimization problems simultaneously: (1) Select a least-cost subset of locations (network nodes) as hubs where traffic is to be aggregated and switched, and choose the type of hub (high-capacity DS3 vs. lower-capacity DS1 hub) for each location; (2) Optimally assign traffic from other nodes to these hubs, so that the traffic entering the network at these nodes is routed to the assigned hubs while respecting capacity constraints on the links and routing-diversity constraints on the hubs to assure survivability; and (3) Optimally choose the types of links to be used in interconnecting the nodes and hubs based on the capacities and costs associated with each link type. Each of these optimization problems must be solved while accounting for its impacts on the other two. This paper introduces a short term Tabu Search (STTS) meta-heuristic, with embedded knapsack and network flow sub-problems, that has proved highly effective in designing such backhaul networks for carrying personal communications services (PCS) traffic. It solves problems that are challenging for conventional branch-and-bound solvers in minutes instead of hours and finds lower-cost solutions. Applied to real-world network design problems, the heuristic has successfully identified designs that save over 20% compared to the best previously known designs.     

A new result in the theory and computation of the least-norm solution of a linear program

By perturbing properly a linear program to a separable quadratic program, it is possible to solve the latter in its dual variable space by iterative techniques such as sparsity-preserving SOR (successive overrelaxation) algorithms. The main result of this paper gives an effective computational criterion to check whether the solutions of the perturbed quadratic programs provide the least-norm solution of the original linear program.This research was sponsored by the United States Army under Contract No. DAAG29-80-C-0041. This material is based upon work supported by the National Science Foundation, Grant Nos. DCR-84-20963 and DMS-82-109050, and by the Italian National Research Council (CNR).The author wishes to thank Professor O. L. Mangasarian for his helpful comments which helped to improve the paper.