Stiffness and strength of tridimensional periodic lattices

This paper presents a method for the linear analysis of the stiffness and strength of open and closed cell lattices with arbitrary topology. The method hinges on a multiscale approach that separates the analysis of the lattice in two scales. At the macroscopic level, the lattice is considered as a uniform material; at the microscopic scale, on the other hand, the cell microstructure is modelled in detail by means of an in-house finite element solver. The method allows determine the macroscopic stiffness, the internal forces in the edges and walls of the lattice, as well as the global periodic buckling loads, along with their buckling modes. Four cube-based lattices and nine cell topologies derived by Archimedean polyhedra are studied. Several of them are characterized here for the first time with a particular attention on the role that the cell wall plays on the stiffness and strength properties. The method, automated in a computational routine, has been used to develop material property charts that help to gain insight into the performance of the lattices under investigation. © 2012 Elsevier B.V.

Structural optimization of lattice materials

Lattice materials are characterized at the microscopic level by a regular pattern of voids confined by walls. Recent rapid prototyping techniques allow their manufacturing from a wide range of solid materials, ensuring high degrees of accuracy and limited costs. The microstructure of lattice material permits to obtain macroscopic properties and structural performance, such as very high stiffness to weight ratios, highly anisotropy, high specific energy dissipation capability and an extended elastic range, which cannot be attained by uniform materials. Among several applications, lattice materials are of special interest for the design of morphing structures, energy absorbing components and hard tissue scaffold for biomedical prostheses. Their macroscopic mechanical properties can be finely tuned by properly selecting the lattice topology and the material of the walls. Nevertheless, since the number of the design parameters involved is very high, and their correlation to the final macroscopic properties of the material is quite complex, reliable and robust multiscale mechanics analysis and design optimization tools are a necessary aid for their practical application. In this paper, the optimization of lattice materials parameters is illustrated with reference to the design of a bracket subjected to a point load. Given the geometric shape and the boundary conditions of the component, the parameters of four selected topologies have been optimized to concurrently maximize the component stiffness and minimize its mass. Copyright © 2011 by ASME.

Magnetocaloric and transport study of poly- and nanocrystalline composite manganites La 0.7Ca 0.3MnO 3/La 0.8Sr 0.2MnO 3

Magnetocaloric and transport properties are reported for novel poly- and nanocrystalline double composite manganites, La 0.8Sr 0.2MnO 3/La 0.7Ca 0.3MnO 3, prepared by the sol-gel method. Magnetic field dependence of magnetic entropy change is found to be stronger for the nano- than the polycrystalline composite. The remarkable broadening of the temperature interval, where the magnetocaloric effect occurs in poly- and nanocrystalline composites, causes the relative cooling power (RCP(S)) of the nanocrystalline composite to be reduced by only 10 compared to the Sr based polycrystalline phase. The RCP(S) of the polycrystalline composite becomes remarkably enhanced. The low temperature magnetoresistance is enhanced by 5 for the nanostructured composite. © 2012 American Institute of Physics.

Magnetocaloric effect in La0.75Sr0.25MnO3 manganite

The polycrystalline manganite La0.75Sr0.25MnO 3 prepared by an alternative carbonate precipitation route reveals the rhombohedral perovskite structure. Magnetization isotherms measured up to 2 T are used to determine Curie temperature of 332 K by means of Arrott plot. Maximum of magnetic entropy change is found at Curie temperature. The relative cooling power equal to 64 J/kg for 1.5 T magnetic field, is superior as compared to the manganite with the same chemical composition from the solgel method. © 2010 Elsevier B.V. All rights reserved.

Magnetocaloric effect and magnetic properties of Tb0.9 Sn0.1 MnO3

The magnetocaloric effect in magnetic materials is of great interest nowadays. In this article we present an investigation about the magnetic properties near the magnetic transition in a polycrystalline sample of a manganite Tb0.9 Sn0.1 MnO3. Particularly, we are interested in describing the nature of the magnetic interactions and the magnetocaloric effect in this compound. The temperature dependence of the magnetization was measured to determine the characteristics of the magnetic transition and the magnetic entropy change was calculated from magnetization curves at different temperatures. The magnetic solid is paramagnetic at high temperatures. We observe a dominant antiferromagnetic interaction below Tn =38 K for low applied magnetic fields; the presence of Sn doping in this compound decreases the Ńel temperature of the pure TbMnO3 system. A drastic increase in the magnetization as a function of temperature near the magnetic transition suggests a strong magnetocaloric effect. We found a large magnetic entropy change Δ SM (T) of about -4 J/kg K at H=3 T. We believe that the magnetic entropy change is associated with the magnetic transition and we interpret it as due to the coupling between the magnetic field and the spin ordering. This relatively large value and broad temperature interval (about 35 K) of the magnetocaloric effect make the present compound a promising candidate for magnetic refrigerators at low temperatures. © 2007 American Institute of Physics.

Magneto-transport study of Nb-doped Bi/Pb2223 superconductor

The magneto-transport properties of Bi1.5Pb0.4Nb0.1Sr2Ca2Cu 3O10-x polycrystalline, superconducting ceramic are reported. The material was found to be chemically homogeneous and partially textured. The mixed state properties were investigated by measuring the electrical resistivity, longitudinal and transverse (Nernst effect) thermoelectric power, and thermal conductivity. The magnetization and AC susceptibility measurements were also performed. The variation of these characteristics for magnetic fields up to 5 T are discussed and compared to those of the zero field case. The transport entropy and thermal Hall angle are extracted and quantitatively compared to previously reported data of closely related systems. © 2003 Elsevier Science B.V. All rights reserved.

Mechanical properties of hierarchical lattices

This paper focuses on the stiffness and strength of lattices with multiple hierarchical levels. We examine two-dimensional and three-dimensional lattices with up to three levels of structural hierarchy. At each level, the topology and the orientation of the lattice are prescribed, while the relative density is varied over a defined range. The properties of selected hierarchical lattices are obtained via a multiscale approach applied iteratively at each hierarchical level. The results help to quantify the effect that multiple orders of structural hierarchy produces on stretching and bending dominated lattices. Material charts for the macroscopic stiffness and strength illustrate how the property range of the lattices can expand as subsequent levels of hierarchy are added. The charts help to gain insight into the structural benefit that multiple hierarchies can impart to the macroscopic performance of a lattice. © 2013 Elsevier Ltd. All rights reserved.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Air quality and climate impacts of alternative bus technologies in Greater London.

The environmental impact of diesel-fueled buses can potentially be reduced by the adoption of alternative propulsion technologies such as lean-burn compressed natural gas (LB-CNG) or hybrid electric buses (HEB), and emissions control strategies such as a continuously regenerating trap (CRT), exhaust gas recirculation (EGR), or selective catalytic reduction with trap (SCRT). This study assessed the environmental costs and benefits of these bus technologies in Greater London relative to the existing fleet and characterized emissions changes due to alternative technologies. We found a >30% increase in CO2 equivalent (CO2e) emissions for CNG buses, a <5% change for exhaust treatment scenarios, and a 13% (90% confidence interval 3.8-20.9%) reduction for HEB relative to baseline CO2e emissions. A multiscale regional chemistry-transport model quantified the impact of alternative bus technologies on air quality, which was then related to premature mortality risk. We found the largest decrease in population exposure (about 83%) to particulate matter (PM2.5) occurred with LB-CNG buses. Monetized environmental and investment costs relative to the baseline gave estimated net present cost of LB-CNG or HEB conversion to be $187 million ($73 million to $301 million) or $36 million ($-25 million to $102 million), respectively, while EGR or SCRT estimated net present costs were $19 million ($7 million to $32 million) or $15 million ($8 million to $23 million), respectively.

Wetness loss prediction for a low pressure steam turbine using computational fluid dynamics

Two-phase computational fluid dynamics modelling is used to investigate the magnitude of different contributions to the wet steam losses in a three-stage model low pressure steam turbine. The thermodynamic losses (due to irreversible heat transfer across a finite temperature difference) and the kinematic relaxation losses (due to the frictional drag of the drops) are evaluated directly from the computational fluid dynamics simulation using a concept based on entropy production rates. The braking losses (due to the impact of large drops on the rotor) are investigated by a separate numerical prediction. The simulations show that in the present case, the dominant effect is the thermodynamic loss that accounts for over 90% of the wetness losses and that both the thermodynamic and the kinematic relaxation losses depend on the droplet diameter. The numerical results are brought into context with the well-known Baumann correlation, and a comparison with available measurement data in the literature is given. The ability of the numerical approach to predict the main wetness losses is confirmed, which permits the use of computational fluid dynamics for further studies on wetness loss correlations. © IMechE 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Guided self-organization in a dynamic embodied system based on attractor selection mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Co doping enhanced giant magnetocaloric effect in Mn1-xCoxAs films epitaxied on GaAs (001)

A giant magnetocaloric effect was found in series of Mn1-xCoxAs films epitaxied on GaAs (001). The maximum magnetic entropy change caused by a magnetic field of 4 T is as large as 25 J/kg K around room temperature, which is about twice the value of pure MnAs film. The observed small thermal hysteresis is more suitable for practical application. Growing of layered Mn1-xCoxAs films with Co concentration changing gradually may draw layered active magnetic regenerator refrigerators closer to practical application. Our experimental result may provide the possibility for the combination of magnetocaloric effect and microelectronic circuitry.

Quantum critical phenomena in the XY spin chain with the Dzyaloshinski-Moriya interaction (Retracted article. See vol 80, artn 019903, 2009)

We study the effects of the Dzyaloshinski-Moriya (DM) anisotropic interaction on the ground-state properties of the Heisenberg XY spin chain by means of the fidelity susceptibility, order parameter, and entanglement entropy. Our results show that the DM interaction could influence the distribution of the regions of quantum phase transitions and cause different critical regions in the XY spin model. Meanwhile, the DM interaction has effective influence on the degree of entanglement of the system and could be used to increase the entanglement of the spin system.

Lossless data compression scheme based on neural network and SVM

First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.