Selecting creep models using Bayesian methods

The development of creep prediction models has been a field of extensive research and many different models have already been proposed. This paper presents an evaluation method of the prediction quality of creep models for specific experimental data. Within the scope of this paper, the model according to Bockhold and the model according to Heidolf are examined. First, the parameters of the models are identified with respect to existing experimental data. This is done using a sampling based approach of Bayesian updating developed by Ba?ant and Chern. In extension to the method by Ba?ant and Chern, the uncertainty coming from inaccurate measurement data is taken into account in the definition of the likelihood function within the updating algorithm. The more inaccurate the measurements are, the more uncertain the estimated model parameters and model prognoses become. The identification is performed for different short- and long-term creep tests. The intension is not to validate these models intensively, but to evaluate their prognoses for the individually tested creep behavior. The results show that the identifiability of the models?? parameters is different for both models and consequently the models prognoses differ in their uncertainties. Second, the models are evaluated using two different strategies: the stochastic model selection according to MacKay, Beck and Yuen based on the Ockham factor, and a comparison of the uncertainties taking into account parameter and model uncertainties. The results of the evaluation of the creep models differ for various experimental tests. Model Heidolf is more flexible and gives a better fit to the data, however, it fails to predict reliable long-term creep deformations using only short-term measurements compared to model Bockhold. Comparing the evaluation methods, the analysis of uncertainties of the creep prognosis proofs to be more stable than the evaluation using the stochastic model selection.     

Future publication success in science is better predicted by traditional measures than by the <Emphasis Type="Italic">h</Emphasis> index

Although the use of bibliometric indicators for evaluations in science is becoming more and more ubiquitous, little is known about how future publication success can be predicted from past publication success. Here, we investigated how the post-2000 publication success of 85 researchers in oncology could be predicted from their previous publication record. Our main findings are: (i) Rates of past achievement were better predictors than measures of cumulative achievement. (ii) A combination of authors’ past productivity and the past citation rate of their average paper was most successful in predicting future publication success (R ² ≈ 0.60). (iii) This combination of traditional bibliographic indicators clearly outperformed predictions based on the rate of the h index (R ² between 0.37 and 0.52). We discuss implications of our findings for views on creativity and for science evaluation.     

Micro- and nanostructured Al2O3 surfaces for controlled vascular endothelial and smooth muscle cell adhesion and proliferation

The effect of the micro- and nanotopography on vascular cell-surface interaction is investigated using nano- and microstructured Al₂O₃ as model substrate. Two different nanostructured Al₂O₃ surfaces composed of low density (LD) and high density (HD) nanowires (NWs) were synthesized by chemical vapour deposition (CVD) and commercially available microstructured Al₂O₃ plates were used for comparison. A clear diverging response of human umbilical vein endothelial cells (HUVEC) and human umbilical vein smooth muscle cells (HUVSMC) was observed on these nano- and microstructured surfaces. LD Al₂O₃ NWs seem to enhance the proliferation of HUVECs selectively. This selective control of the cell-surface interaction by topography may represent a key issue for the future stent material design.     

Methodology of materials discovery in complex metal hydrides using experimental and computational tools

We present a review of the experimental and theoretical methods used in the discovery of new metal–hydrogen materials systems for hydrogen storage applications. Rather than a comprehensive review of all new materials and methods used in the metal hydride community, we focus on a specific subset of successful methods utilizing theoretical crystal structure prediction methods, computational approaches for screening large numbers of compound classes, and medium-throughput experimental methods for the preparation of such materials. Monte Carlo techniques paired with a simplified empirical Hamiltonian provide crystal structure candidates that are refined using density functional theory. First-principle methods using high-quality structural candidates are further screened for an estimate of reaction energetics, decomposition enthalpies, and determination of reaction pathways. Experimental synthesis utilizes a compacted-pellet sintering technique under high-pressure hydrogen at elevated temperatures. Crystal structure determination follows from a combination of Rietveld refinements of diffraction patterns and first-principles computation of total energies and dynamical stability of competing structures. The methods presented within are general and applicable to a wide class of materials for energy storage.     

Spectrally selective and adaptive surfaces for protection against radiative heating: ITO and VO2

Two surface materials for reducing absorptivity of heat radiation from fires have been investigated. The first is VO₂, which is a thermochromic material. When the temperature of a VO₂ surface increases over a certain temperature, it switches, ideally, from infrared (IR)‐absorbing to IR‐reflecting. VO₂ window coatings are still on a research level, yet to be commercialized. In this study, VO₂ powder available on the market was investigated. The thermochromic effect could be identified but was not large enough to significantly improve the fire properties of treated surfaces. Some thoughts concerning how to improve the performance of VO₂ are discussed. The second investigated material is indium tin oxide (ITO), which is a so called low‐e coating, which means that it has low emissivity and absorptivity in the IR part of the spectrum. ITO is spectrally selective in the sense that it transmits visible light while reflecting a large fraction of the IR radiation, which is a rare property for surfaces in general but a typical property of thin electrically conducting non‐metallic films. It is shown that the application of ITO to poly(methyl methacrylate) (PMMA) significantly improves its fire properties. ITO coating is a mature technology already in widespread use today in the electronics industry. Copyright © 2012 John Wiley & Sons, Ltd.     

Performance Study of a Closed-Type Heat Pump Tumble Dryer Using a Simulation Model and an Experimental Set-Up

In the interests of competitiveness, manufactures of tumble dryers are seeking to reduce both their electricity use and the drying time. This study examines how the cylinder volume of the compressor and the total heat transfer of the condenser influence the drying time and electricity use in a heat pump tumble dryer. A transient simulation model was developed and compared to an experimental set-up with good similarity. The simulations show that increasing the cylinder volume of the compressor by 50% decreases the drying time by 14% without using more electricity.     

Fundamental influences of particles on stirred and unstirred venting processes of foaming systems

Venting is the common safety measure to protect plant equipment against excessive overpressure. So far, scenarios in which particles were part of the system and should have been accounted for did ignore their presence; the scenarios were treated like a two-phase system. Current research shows that particles can have a major influence on the venting behaviour. Experimental results indicate that particles affect level swell and relief flow especially of foamy systems. Based on those results four different layers of influence of the particle have been identified and are presented in a first model. Based on this model recommendations for the development of new and more complex models are given.     

Experimental parameters during optical floating zone crystal growth of rare earth silicides

Optical floating zone（FZ） crystal growth involving growth stability and as-grown crystal perfection is affected by experimental conditions and the specific material. Referring to rare earth silicides, high purity of raw rare earth elements and ambient argon atmosphere are crucial to grow high-quality crystals; the maximum zone height is determined by equating the capillary forces of the surface tension; and asymmetric counter rotation of crystal and feed rod with convex（toward the melt） interfaces are favored to reach single crystals. Influences of several other growth parameters were also discussed in detail in this paper.     

Modeling uranium biosorption by Cystoseira sp. and application studies

The aim of the present work was to determine the applicability of raw and modified brown macroalga Cystoseira sp. as a biosorbent material for the sorption of uranium ions from aqueous solutions. Equilibrium of uranium biosorption was analyzed under isotherm models and thermodynamic parameters of the process. Recovery of uranium from acidic mine wastewater was also applied. The mechanism of biosorption was discussed considering experimental data and theoretical models. The bioremoval efficiency of modified biomass was higher than raw Cystoseira sp. and the theoretical biosorption capacity of modified biosorbent was calculated to be 468.01 mg U/g.     

Simulating the emergence of norms in different scenarios

This paper deals with EMIL-S, a software tool box which was designed during the EMIL project for the simulation of processes during which norms emerged in an agent society. This tool box implements the cognitive architecture of normative agents which was designed during the EMIL project which is also discussed in other papers in this issue. This implementation is described in necessary detail, and two examples of its application to several different scenarios are given, namely a scenario in which persons involved in micro finance are simulated and learn how to sanction free riders and how to learn from these sanctions, and a scenario in which simulated persons move through a simulated airport where they more often than not have to wait in queues and learn how to behave properly in queues.