Network design and flow problems with cross-arc costs

Network design and flow problems appear in a wide variety of transportation applications. We consider a new variation to this important class of problems, in which the cost associated with an arc depends not only on the amount of flow moving across that arc, but on the amount of flow on other arcs in the network as well. We formulate an integer program to address this problem, discuss a real-world application in which cross-arc costs are found, and conduct computational experiments on a broad class of problems to analyze how the model performs as network characteristics vary.     

Silicon–air batteries

A new “metal”–air battery based on silicon–oxygen couple is described. Silicon–air battery employing EMI·2.3HF·F room temperature ionic liquid (RTIL) as an electrolyte and highly-doped silicon wafers as anodes (fuels) has an undetectable self-discharge rate and high tolerance to the environment (extreme moisture/dry conditions). Such a battery yields an effectively infinite shelf life with an average working voltage of 1–1.2 V. Silicon–air battery can support relatively high current densities (up to 0.3 mA/cm²) drawn from flat polished silicon wafers anodes. Such batteries may find immediate applications, as they can provide an internal, built-in autonomous and self sustained energy source.     

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Micro and Macro Characterization of PEO-PPO-PEO Triblocks Hydrogels

Summary: Amphiphilic poly(ethylene oxide) - poly(propylene oxide) triblock copolymers are very appealing materials for biomedical application since they can be easily injected as liquid at room temperature while they produce a gel when in the body. On the other hand, these materials no longer hold the gel state when in presence of solvent (as physiological solutions) due to the dilution of the system. To overcome these limitations Cohn and coworkers 1 have synthesized a novel thermo-responsive systems by extending the chain of the commercially available PEO-PPO copolymer named F127. The aim of this study was to evaluate the effect of the chemical modification on the macroscopic, rheological, and microscopic, transport, properties of these new materials.     

Shakedown Analysis of Elastoplastic Arches

Abstract

The use of mathematical programming methods proves to be of interest in the formulation and the solution of some rather tedious problems of structural plasticity. This paper extends the application of linear programming techniques to elastoplastic arches under variable repeated loadings by adopting linearized models for the arch shape and the yield criteria of its sections. The concept of M and M + N mechanisms proves convenient in formulating the equilibrium equations by the static approach. With nonlinear yield conditions the formulations presented will still hold, but the solution of corresponding nonlinear programming problems will likely become more complex. In addition to their practical applications, the linear programming approaches suggested and illustrated have the advantage of allowing the incremental collapse load to be derived by a direct, algorithmic procedure, rather than by the trial and error procedures suggested in earlier investigations.     

A factored implicit scheme for numerical weather prediction

The nonlinear partial differential equations of atmospheric dynamics govern motion on two time scales, a fast one and a slow one. Only the slow-scale motions are relevant in predicting the evolution of large weather patterns. Implicit numerical methods are therefore attractive for weather prediction, since they permit a large time step chosen to resolve only the slow motions. To develop an implicit method which is efficient for problems in more than one spatial dimension, one must approximate the problem by smaller, usually one-dimensional problems. A popular way to do so is to approximately factor the multidimensional implicit operator into one-dimensional operators. The factorization error incurred in such methods, however, is often unacceptably large for problems with multiple time scales. We propose a new factorization method for numerical weather prediction which is based on factoring separately the fast and slow parts of the implicit operator. We show analytically that the new method has small factorization error, which is comparable to other discretization errors of the overall scheme. The analysis is based on properties of the shallow water equations, a simple two-dimensional version of the fully three-dimensional equations of atmospheric dynamics.