Aging response of the young’s modulus and mechanical properties of Ti-29Nb-13Ta-4.6Zr for biomedical applications

Alloys for implant devices require improved strength but a reduced Young’s modulus, in order to become mechanically more compatible with adjacent bone tissues. In this study, a new metastable β-type titanium alloy, Ti-29Nb-13Ta-4.6Zr (wt pct), was subjected to aging treatment to produce different microstructures, and the resulting mechanical properties, including the Young’s modulus, were measured. The Young’s modulus of this alloy is found to be sensitive to microstructures generated by various heat treatments. For microstructures varying from (α + β) to (α + β + ω) and (β + ω), the Young’s modulus increases with an accompanying increase in tensile strength and hardness, but decreases in ductility. The (β + ω) microstructure has a low strength, high modulus, and poor ductility and cannot be used for biomedical applications. For an (α + β) microstructure, the volume fraction of the phases is shown to be the main factor that determines the mechanical properties.     

Unsteady effects and heat-transfer when starting up power plant

The results of experimental study of unsteady effects on local heat transfer coefficients caused by abruptly increasing of the gas flow temperature in the inlet section of a cylindrical channel are presented.     

Specific features of optical orientation and relaxation of electron spins in quantum wells with a large spin splitting

The processes of optical spin orientation and spin relaxation of electrons are treated theoretically for semiconductor quantum wells, in which the spin splitting of the energy spectrum is comparable with the characteristic energy of charge carriers. The density matrix of photoexcited electrons at the instant of optical excitation is obtained in explicit form. A system of kinetic equations describing the behavior of the spin density matrix at an arbitrary relation between the average energy of charge carriers and the spin splitting is derived. It is demonstrated that, upon photoexcitation, a noticeable degree of orientation can be attained only in the pulse mode of operation, when the photoexcitation pulse duration is comparable with the period of spin precession in the field of spin splitting. It is shown that the total spin of the ensemble of electrons exhibits oscillations damping with time; the shape and damping time of the oscillations are sensitive to the parameters of photoexcitation and the spin splitting.     

Radio sensing of a cometary nucleus: Possibilities for investigating the surface layer

The possibility for determining the structure of the surface layer of a cometary nucleus from the data of bistatic radar sensing is investigated. A rigorous solution formulated for this problem on the basis of vector equations of the electromagnetic field is presented.     

Carbon nanofibers as hydrogen adsorbing materials for power sources

Porous carbon nanofibers are synthesized by CVD method from acetylene with use of iron-containing catalysts. Activation of the nanofibers in melted potassium hydroxide results in increasing surface area from initial 300–400 m² g⁻¹ to 1700 m² g⁻¹. As follows from XRD data, activated nanofibers do not contain regular packages of graphene layers, but retain high electric conductivity. Deposition of copper improves electrochemical hydrogen storing characteristics of carbon nanofibers. Carbon nanomaterials obtained can be used as hydrogen storing materials in batteries instead of hydride forming metals.     

Ultrasonic treatment restores the photoelectric parameters of silicon solar cells degraded under the action of <Superscript>60</Superscript>Co gamma radiation

The photoelectric parameters of silicon solar cells degraded under the action of ⁶⁰Co gamma-radiation can be partly restored using an ultrasonic treatment (UST). The growth of the maximum output power of solar cells after the UST is related to a redistribution of the radiation defects and an increase in the homogeneity of a semiconductor crystal structure.     

Phase states of a two-dimensional non-Heisenberg ferromagnet

The effects of a biquadratic exchange and an external magnetic field on the phase states of a twodimensional non-Heisenberg ferromagnet have been studied with allowance for magnetoelastic and magnetodipolar interactions.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Manifold mapping: a two-level optimization technique

In this paper, we analyze in some detail the manifold-mapping optimization technique introduced recently [Echeverría and Hemker in space mapping and defect correction. Comput Methods Appl Math 5(2): 107—136, 2005]. Manifold mapping aims at accelerating optimal design procedures that otherwise require many evaluations of time-expensive cost functions. We give a proof of convergence for the manifold-mapping iteration. By means of two simple optimization problems we illustrate the convergence results derived. Finally, the performances of several variants of the method are compared for some design problems from electromagnetics.     

Sensor Selection in Arbitrary Dimensions

We address the sensor selection problem which arises in tracking and localization applications. In sensor selection, the goal is to select a small number of sensors whose measurements provide a good estimate of a target's state (such as location). We focus on the bounded uncertainty sensing model where the target is a point in the d -dimensional Euclidean space. Each sensor measurement corresponds to a convex polyhedral subset of the space. The measurements are merged by intersecting corresponding sets. We show that, on the plane, four sensors are sufficient (and sometimes necessary) to obtain an estimate whose area is at most twice the area of the best possible estimate (obtained by intersecting all measurements). We also extend this result to arbitrary dimensions and show that a constant number of sensors suffice for a constant factor approximation in arbitrary dimensions. Both constants depend on the dimensionality of the space but are independent of the total number of sensors in the network.