Wear effects and mechanisms of soot-contaminated automotive lubricants

A study has been carried out to investigate the influence of soot-contaminated automotive lubricants in the wear process of a simulated engine valve train contact. Previous research on this topic has been mainly performed from a chemical point of view in fundamental studies, with insufficient relevance to real engine conditions, i.e. load and geometry. This study investigates the conditions under which wear occurs through specimen testing. The objective of the work was to understand the wear mechanisms that occur within the contaminated contact zone, to help in future development of a predictive wear model to assist in the valve-train design process. The effects of soot in lubricants have been tested using a reciprocating test-rig specifically designed for this application, where a steel disc is held in a bath of oil and a steel ball (replicating a valve train contact) is attached to a reciprocating arm. The materials, contact geometry and loading conditions are all related to specific conditions experienced within an engine's valve train. The testing was carried out under various contact conditions, using carbon black as a soot simulant. Wear measurements were taken during the tests and wear scar morphology was studied. The results have revealed how varying lubrication conditions changes the wear rate of engine components and determines the wear mechanism that dominates for specific situations

CMB lensing and primordial squeezed non-Gaussianity

Squeezed primordial non-Gaussianity can strongly constrain early-universe physics, but it can only be observed on the CMB after it has been gravitationally lensed. We give a new simple non-perturbative prescription for accurately calculating the effect of lensing on any squeezed primordial bispectrum shape, and test it with simulations. We give the generalization to polarization bispectra, and discuss the effect of lensing on the trispectrum. We explain why neglecting the lensing smoothing effect does not significantly bias estimators of local primordial non-Gaussianity, even though the change in shape can be >~10%. We also show how tau_NL trispectrum estimators can be well approximated by much simpler CMB temperature modulation estimators, and hence that there is potentially a ~10-30% bias due to very large-scale lensing modes, depending on the range of modulation scales included. Including dipole sky modulations can halve the tau_NL error bar if kinematic effects can be subtracted using known properties of the CMB temperature dipole. Lensing effects on the g_NL trispectrum are small compared to the error bar. In appendices we give the general result for lensing of any primordial bispectrum, and show how any full-sky squeezed bispectrum can be decomposed into orthogonal modes of distinct angular dependence.Comment: 22 pages, 6 figures; minor edits to match published versio

A Brachistochrone Approach to Reconstruct the Inflaton Potential

We propose a new way to implement an inflationary prior to a cosmological dataset that incorporates the inflationary observables at arbitrary order. This approach employs an exponential form for the Hubble parameter $H(\phi)$ without taking the slow-roll approximation. At lowest non-trivial order, this $H(\phi)$ has the unique property that it is the solution to the brachistochrone problem for inflation.Comment: 13 pages, 2 figures, version matches published versio

Invariants and Coherent States for Nonstationary Fermionic Forced Oscillator

The most general form of Hamiltonian that preserves fermionic coherent states stable in time is found in the form of nonstationary fermion oscillator. Invariant creation and annihilation operators and related Fock states and coherent states are built up for the more general system of nonstationary forced fermion oscillator.Comment: 13 pages, Latex, no figure

SAT-Based Synthesis Methods for Safety Specs

Automatic synthesis of hardware components from declarative specifications is an ambitious endeavor in computer aided design. Existing synthesis algorithms are often implemented with Binary Decision Diagrams (BDDs), inheriting their scalability limitations. Instead of BDDs, we propose several new methods to synthesize finite-state systems from safety specifications using decision procedures for the satisfiability of quantified and unquantified Boolean formulas (SAT-, QBF- and EPR-solvers). The presented approaches are based on computational learning, templates, or reduction to first-order logic. We also present an efficient parallelization, and optimizations to utilize reachability information and incremental solving. Finally, we compare all methods in an extensive case study. Our new methods outperform BDDs and other existing work on some classes of benchmarks, and our parallelization achieves a super-linear speedup. This is an extended version of [5], featuring an additional appendix.Comment: Extended version of a paper at VMCAI'1

On Nonlinear Functionals of Random Spherical Eigenfunctions

We prove Central Limit Theorems and Stein-like bounds for the asymptotic behaviour of nonlinear functionals of spherical Gaussian eigenfunctions. Our investigation combine asymptotic analysis of higher order moments for Legendre polynomials and, in addition, recent results on Malliavin calculus and Total Variation bounds for Gaussian subordinated fields. We discuss application to geometric functionals like the Defect and invariant statistics, e.g. polyspectra of isotropic spherical random fields. Both of these have relevance for applications, especially in an astrophysical environment.Comment: 24 page

Systematic Study of Electron Localization in an Amorphous Semiconductor

We investigate the electronic structure of gap and band tail states in amorphous silicon. Starting with two 216-atom models of amorphous silicon with defect concentration close to the experiments, we systematically study the dependence of electron localization on basis set, density functional and spin polarization using the first principles density functional code Siesta. We briefly compare three different schemes for characterizing localization: information entropy, inverse participation ratio and spatial variance. Our results show that to accurately describe defect structures within self consistent density functional theory, a rich basis set is necessary. Our study revealed that the localization of the wave function associated with the defect states decreases with larger basis sets and there is some enhancement of localization from GGA relative to LDA. Spin localization results obtained via LSDA calculations, are in reasonable agreement with experiment and with previous LSDA calculations on a-Si:H models.Comment: 16 pages, 11 Postscript figures, To appear in Phys. Rev.

Understanding person acquisition using an interactive activation and competition network

Face perception is one of the most developed visual skills that humans display, and recent work has attempted to examine the mechanisms involved in face perception through noting how neural networks achieve the same performance. The purpose of the present paper is to extend this approach to look not just at human face recognition, but also at human face acquisition. Experiment 1 presents empirical data to describe the acquisition over time of appropriate representations for newly encountered faces. These results are compared with those of Simulation 1, in which a modified IAC network capable of modelling the acquisition process is generated. Experiment 2 and Simulation 2 explore the mechanisms of learning further, and it is demonstrated that the acquisition of a set of associated new facts is easier than the acquisition of individual facts in isolation of one another. This is explained in terms of the advantage gained from additional inputs and mutual reinforcement of developing links within an interactive neural network system. <br/

Non-detection of a statistically anisotropic power spectrum in large-scale structure

We search a sample of photometric luminous red galaxies (LRGs) measured by the Sloan Digital Sky Survey (SDSS) for a quadrupolar anisotropy in the primordial power spectrum, in which P(\vec{k}) is an isotropic power spectrum P(k) multiplied by a quadrupolar modulation pattern. We first place limits on the 5 coefficients of a general quadrupole anisotropy. We also consider axisymmetric quadrupoles of the form P(\vec{k}) = P(k){1 + g_*[(\hat{k}\cdot\hat{n})^2-1/3]} where \hat{n} is the axis of the anisotropy. When we force the symmetry axis \hat{n} to be in the direction (l,b)=(94 degrees,26 degrees) identified in the recent Groeneboom et al. analysis of the cosmic microwave background, we find g_*=0.006+/-0.036 (1 sigma). With uniform priors on \hat{n} and g_* we find that -0.41<g_*<+0.38 with 95% probability, with the wide range due mainly to the large uncertainty of asymmetries aligned with the Galactic Plane. In none of these three analyses do we detect evidence for quadrupolar power anisotropy in large scale structure.Comment: 23 pages; 10 figures; 3 tables; replaced with version published in JCAP (added discussion of scale-varying quadrupolar anisotropy

The measurement of liner - piston skirt oil film thickness by an ultrasonic means

The paper presents a novel method for the measurement of lubricant film thickness in the piston-liner contact. Direct measurement of the film in this conjunction has always posed a problem, particularly under fired conditions. The principle is based on capturing and analysing the reflection of an ultrasonic pulse at the oil film. The proportion of the wave amplitude reflected can be related to the thickness of the oil film. A single cylinder 4-stroke engine on a dyno test platform was used for evaluation of the method. A piezo-electric transducer was bonded to the outside of the cylinder liner and used to emit high frequency short duration ultrasonic pulses. These pulses were used to determine the oil film thickness as the piston skirt passed over the sensor location. Oil films in the range 2 to 21 μm were recorded varying with engine speeds. The results have been shown to be in agreement with detailed numerical predictions