Modelling linered engine blocks

Factors that affect heat transfer in the linered aluminium engine block are examined to determine their importance. Conduction is found to be the dominant mode of heat transfer, and the interface is characterised as imperfect contact if there are no surface manufacturing defects larger than 139 microns. A model is proposed to estimate the effective conductivity for imperfect contact. This thermal conductance depends on the area of contact, macroscopic roughness, the contact pressure and the interstitial medium. The transfer of heat and the distribution of stress in line red engine blocks are coupled, and the problem is strongly non-linear. A finite element solution procedure for solving the heat transfer problem in the linered engine block is outlined

Relevance of Abelian Symmetry and Stochasticity in Directed Sandpiles

We provide a comprehensive view on the role of Abelian symmetry and stochasticity in the universality class of directed sandpile models, in context of the underlying spatial correlations of metastable patterns and scars. It is argued that the relevance of Abelian symmetry may depend on whether the dynamic rule is stochastic or deterministic, by means of the interaction of metastable patterns and avalanche flow. Based on the new scaling relations, we conjecture critical exponents for avalanche, which is confirmed reasonably well in large-scale numerical simulations.Comment: 4 pages, 3 figures; published versio

On the mechanism of ZDDP antiwear film formation

Zinc dialkyldithiophosphate additives are used to control wear and inhibit oxidation in almost all engine oils as well as many other types of lubricant. They limit wear primarily by forming a thick, protective, phosphate glass-based tribofilm on rubbing surfaces. This film formation can occur at low temperatures and is relatively indifferent to the chemical nature of the substrate. There has been considerable debate as to what drives ZDDP tribofilm formation, why it occurs only on surfaces that experience sliding and whether film formation is controlled primarily by temperature, pressure, triboemission or some other factor. This paper describes a novel approach to the problem by studying the formation of ZDDP films in full film EHD conditions from two lubricants having very different EHD friction properties. This shows that ZDDP film formation does not require solid-solid rubbing contact but is driven simply by applied shear stress, in accord with a stress-promoted thermal activation model. The shear stress present in a high pressure contact can reduce the thermal activation energy for ZDDP by at least half, greatly increasing the reaction rate. This mechanism explains the origins of many practically important features of ZDDP films; their topography, their thickness and the conditions under which they form. The insights that this study provides should prove valuable both in optimising ZDDP structure and in modelling ZDDP antiwear behaviour. The findings also highlight the importance of mechanochemistry to the behaviour of lubricant additives in general

Universality classes and crossover behaviors in non-Abelian directed sandpiles

We study universality classes and crossover behaviors in non-Abelian directed sandpile models, in terms of the metastable pattern analysis. The non-Abelian property induces spatially correlated metastable patterns, characterized by the algebraic decay of the grain density along the propagation direction of an avalanche. Crossover scaling behaviors are observed in the grain density due to the interplay between the toppling randomness and the parity of the threshold value. In the presence of such crossovers, we show that the broadness of the grain distribution plays a crucial role in resolving the ambiguity of the universality class. Finally, we claim that the metastable pattern analysis is important as much as the conventional analysis of avalanche dynamics.Comment: 10 pages, 7 figures, 1 table; published in PRE as the full paper of PRL v101, 218001 (2008

Challenges in cross-cultural/multilingual music information seeking

Understanding and meeting the needs of a broad range of music users across different cultures and languages are central in designing a global music digital library. This exploratory study examines cross-cultural/multilingual music information seeking behaviors and reveals some important characteristics of these behaviors by analyzing 107 authentic music information queries from a Korean knowledge search portal Naver (knowledge) iN and 150 queries from Google Answers website. We conclude that new sets of access points must be developed to accommodate music queries that cross cultural or language boundaries

Neutrino reactions on 138^{138}La and 180^{180}Ta via charged and neutral currents by the Quasi-particle Random Phase Approximation (QRPA)

Cosmological origins of the two heaviest odd-odd nuclei, $^{138}$La and $^{180}$Ta, are believed to be closely related to the neutrino-process. We investigate in detail neutrino-induced reactions on the nuclei. Charged current (CC) reactions, $^{138}$Ba$(\nu_e, e^{-}) ^{138}$La and $^{180}$Hf$(\nu_e, e^{-}) ^{180}$Ta, are calculated by the standard Quasi-particle Random Phase Approximation (QRPA) with neutron-proton pairing as well as neutron-neutron, proton-proton pairing correlations. For neutral current (NC) reactions, $^{139}$La$(\nu \nu^{'}) ^{139}${La}$^*$ and $^{181}$Ta$(\nu, \nu^{'}) ^{181}$Ta$^*$, we generate ground and excited states of odd-even target nuclei, $^{139}$La and $^{181}$Ta, by operating one quasi-particle to even-even nuclei, $^{138}$Ba and $^{180}$Hf, which are assumed as the BCS ground state. Numerical results for CC reactions are shown to be consistent with recent semi-empirical data deduced from the Gamow-Teller strength distributions measured in the ($^{3}$He, t) reaction. Results for NC reactions are estimated to be smaller by a factor about 4 $\sim$ 5 rather than those by CC reactions. Finally, cross sections weighted by the incident neutrino flux in the core collapsing supernova are presented for further applications to the network calculations for relevant nuclear abundances

Determining White Noise Forcing From Eulerian Observations in the Navier Stokes Equation

The Bayesian approach to inverse problems is of paramount importance in quantifying uncertainty about the input to and the state of a system of interest given noisy observations. Herein we consider the forward problem of the forced 2D Navier Stokes equation. The inverse problem is inference of the forcing, and possibly the initial condition, given noisy observations of the velocity field. We place a prior on the forcing which is in the form of a spatially correlated temporally white Gaussian process, and formulate the inverse problem for the posterior distribution. Given appropriate spatial regularity conditions, we show that the solution is a continuous function of the forcing. Hence, for appropriately chosen spatial regularity in the prior, the posterior distribution on the forcing is absolutely continuous with respect to the prior and is hence well-defined. Furthermore, the posterior distribution is a continuous function of the data. We complement this theoretical result with numerical simulation of the posterior distribution

ON DEMAND: CROSS-COUNTRY EVIDENCE FROM COMMERCIAL REAL ESTATE ASSET MARKETS

Using over 25 years of quarterly U.S. and Japanese time series data, this paper examines the determinants of demand for an important class of real assets: commercial real estate. We specify a structural model of market equilibrium that considers direct effects of real investment on built asset price. Our empirical findings are consistent across countries and produce several new results. First, we find that real investment exerts a significant positive direct effect on asset price, which in turn feeds back to impact investment decisions. Second, idiosyncratic risk is found to be strongly positively related to asset price, and to complement supply effects. Third, systematic risk is priced as expected, where the strength of the relation between asset price and systematic risk is found to be higher than in previous studies of capital asset prices. Fourth, lagged values of price determinants (of up to two years) are consistently important in real asset demand estimation. Alternative explanations for our findings are analyzed and discussed. Implications for asset pricing model specification and interpretation are also considered.equity REIT; IPO; interest-rate sensitivity; risk-adjusted return performance

The Neural Representation Benchmark and its Evaluation on Brain and Machine

A key requirement for the development of effective learning representations is their evaluation and comparison to representations we know to be effective. In natural sensory domains, the community has viewed the brain as a source of inspiration and as an implicit benchmark for success. However, it has not been possible to directly test representational learning algorithms directly against the representations contained in neural systems. Here, we propose a new benchmark for visual representations on which we have directly tested the neural representation in multiple visual cortical areas in macaque (utilizing data from [Majaj et al., 2012]), and on which any computer vision algorithm that produces a feature space can be tested. The benchmark measures the effectiveness of the neural or machine representation by computing the classification loss on the ordered eigendecomposition of a kernel matrix [Montavon et al., 2011]. In our analysis we find that the neural representation in visual area IT is superior to visual area V4. In our analysis of representational learning algorithms, we find that three-layer models approach the representational performance of V4 and the algorithm in [Le et al., 2012] surpasses the performance of V4. Impressively, we find that a recent supervised algorithm [Krizhevsky et al., 2012] achieves performance comparable to that of IT for an intermediate level of image variation difficulty, and surpasses IT at a higher difficulty level. We believe this result represents a major milestone: it is the first learning algorithm we have found that exceeds our current estimate of IT representation performance. We hope that this benchmark will assist the community in matching the representational performance of visual cortex and will serve as an initial rallying point for further correspondence between representations derived in brains and machines.Comment: The v1 version contained incorrectly computed kernel analysis curves and KA-AUC values for V4, IT, and the HT-L3 models. They have been corrected in this versio

A new superconducting open-framework allotrope of silicon at ambient pressure

Diamond Si is a semiconductor with an indirect band gap that is the basis of modern semiconductor technology. Although many metastable forms of Si were observed using diamond anvil cells for compression and chemical precursors for synthesis, no metallic phase at ambient conditions has been reported thus far. Here we report the prediction of pure metallic Si allotropes with open channels at ambient pressure, unlike a cubic diamond structure in covalent bonding networks. The metallic phase termed P6/m-Si6 can be obtained by removing Na after pressure release from a novel Na-Si clathrate called P6/m-NaSi6, which is discovered through first-principles study at high pressure. We confirm that both P6/m-NaSi6 and P6/m-Si6 are stable and superconducting with the critical temperatures of about 13 and 12 K at ambient pressure, respectively. The discovery of new Na-Si and Si clathrate structures presents the possibility of exploring new exotic allotropes useful for Si-based devices