Lossy compression of TPC data and trajectory tracking efficiency for the ALICE experiment

In this paper a quasi-lossless algorithm for the on-line compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN is described. The algorithm is based on a lossy source code modeling technique, i.e. it is based on a source model which is lossy if samples of the TPC signal are considered one by one; conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse, representing the pulse charge and the time localization of the pulse.

So as to evaluate the consequences of the error introduced by the lossy compression process, the results of the trajectory tracking algorithms that process data off-line after the experiment are analyzed, in particular, versus their sensibility to the noise introduced by the compression. Two different versions of these off-line algorithms are described, performing cluster finding and particle tracking. The results on how these algorithms are affected by the lossy compression are reported.

Entropy coding can be applied to the set of events defined by the source model to reduce the bit rate to the corresponding source entropy. Using TPC simulated data according to the expected ALICE TPC performance, the compression algorithm achieves a data reduction in the range of 34.2% down to 23.7% of the original data rate depending on the desired precision on the pulse center of mass.

The number of operations per input symbol required to implement the algorithm is relatively low, so that a real-time implementation of the compression process embedded in the TPC data acquisition chain using low-cost integrated electronics is a realistic option to effectively reduce the data storing cost of ALICE experiment.     

Heavy-ion physics with the ALICE experiment at the CERN Large Hadron Collider

After close to 20 years of preparation, the dedicated heavy-ion experiment A Large Ion Collider Experiment (ALICE) took first data at the CERN Large Hadron Collider (LHC) accelerator with proton collisions at the end of 2009 and with lead nuclei at the end of 2010. After a short introduction into the physics of ultra-relativistic heavy-ion collisions, this article recalls the main design choices made for the detector and summarizes the initial operation and performance of ALICE. Physics results from this first year of operation concentrate on characterizing the global properties of typical, average collisions, both in proton-proton (pp) and nucleus-nucleus reactions, in the new energy regime of the LHC. The pp results differ, to a varying degree, from most quantum chromodynamics-inspired phenomenological models and provide the input needed to fine tune their parameters. First results from Pb-Pb are broadly consistent with expectations based on lower energy data, indicating that high-density matter created at the LHC, while much hotter and larger, still behaves like a very strongly interacting, almost perfect liquid.     

Fatigue crack initiation life prediction for aluminium alloy 7075 using crystal plasticity finite element simulations

An experimentally-validated approach for predicting fatigue crack initiation life of polycrystalline metals is developed based on crystal plasticity finite element (CPFE) simulations. In this approach, the microstructure used in the simulations possesses statistically the same grain size and crystallographic orientations as those obtained from electron back-scatter diffraction experiments. A backstress model is incorporated into the CP constitutive model to describe the mechanical behaviour of aluminium alloy (AA) 7075 under cyclic loading. The key variables of the prediction model, the energy efficiency factor and plastic strain energy density, are calibrated using a fatigue test on a round-notched AA7075 specimen at room temperature. The proposed approach is then validated by using another fatigue test to predict 69.1–87.3% of the experimentally measured fatigue crack initiation life. The effects of the microstructure and texture on the energy efficiency factor and fatigue life prediction are quantitatively determined. It is shown that for a given range of energy efficiency factors a similar range of life prediction is obtained. Since the proposed approach considers the heterogeneity of the microstructure, it can well capture the grain scale deformation localisation and therefore improve the precision of fatigue life prediction.     

A multisurface constitutive model for highly cross-linked polymers with yield data obtained from molecular dynamics simulations

Constitutive properties for highly cross-linked glassy polymers are currently determined by molecular dynamics (MD) simulations. This avoids the need for ad-hoc experimentation. Constitutive data in functional form, such as yield surfaces, still require identification and correspondence to an existing function. In addition, loss of information occurs with fitting procedures. The present alternative consists in directly defining piecewise-linear yield functions from a set of points obtained by MD simulations. To prevent the algorithmic issues of multisurface plasticity, we propose an alternative to active-set strategies by simultaneously including all yield functions regardless of being active. We smooth the complementarity conditions using the Chen–Mangasarian function. In addition, extrapolation is proposed for slowly-evolving quantities such as the effective plastic strain while fully implicit integration is adopted for rapidly-evolving constitutive quantities. Since polymers exhibit finite-strain behavior, we propose a semi-implicit integration algorithm which allows a small number of steps to be used up to very large strains. Experimentally-observed effects herein considered are: thermal effects on strain (i.e. thermal expansion), Young’s modulus dependence on temperature and the effects of strain rate and temperature on the yield stress. A prototype model is first studied to assess the performance of the integration algorithm, followed by a experimental validation and a fully-featured, thermally-coupled 2D example.     

Acid-labile isotope-coded extractants: a class of reagents for quantitative mass spectrometric analysis of complex protein mixtures

Quantitative mass spectrometry using stable isotope-labeled tagging reagents such as isotope-coded affinity tags has emerged as a powerful tool for identification and relative quantitation of proteins in current proteomic studies. Here we describe an integrated approach using both automated two-dimensional liquid chromatography/ mass spectrometry (2D-LC/MS) and a novel class of chemically modified resins, termed acid-labile isotope-coded extractants (ALICE), for quantitative mass spectrometric analysis of protein mixtures. ALICE contains a thiol-reactive group that is used to capture all cysteine (Cys)-containing peptides from peptide mixtures, an acid-labile linker, and a nonbiological polymer. The acid-labile linker is synthesized in both heavy and light isotope-coded forms and therefore enables the direct relative quantitation of peptides/proteins through mass spectrometric analysis. To test the ALICE method for quantitative protein analysis, two model protein mixtures were fully reduced, alkylated, and digested in solution separately and then Cys-containing peptides covalently captured by either light or heavy ALICE. The reacted light and heavy ALICE were mixed and washed extensively under rigorous conditions and the Cys-containing peptides retrieved by mild acid-catalyzed elution. Finally, the eluted peptides were directly subjected to automated 2D-LC/MS for protein identification and LC/MS for accurate relative quantitation. Our initial study showed that quantitation of protein mixtures using ALICE was accurate. In addition, isolation of Cys-containing peptides by the ALICE method was robust and specific and thus yielded very low background in mass spectrometric studies. Overall, the use of ALICE provides improved dynamic range and sensitivity for quantitative mass spectrometric analysis of peptide or protein mixtures.     

Energy dissipation in collision of two balls covered by fine particles

A new fine particle impact damper (FPID) is composed of a spherical impactor and a small quantity of fine particles as damping agent. The model of energy dissipation in the collision between two balls covered by fine particles is necessary to investigate the mechanism and performance of FPID. In this study, a simplified model verified by FEA simulations is proposed to estimate the energy dissipation in collision between two balls covered by fine particles. In addition, the energy dissipation in the collision between two balls covered by fine particles is compared with that in the impact between two balls without fine particles, by means of theoretical predictions. FEA simulations are also carried out to discuss the effects of diameter ratio of particle to ball, particle material and particle amount on the energetic expression of the elastic–plastic loading (EPL) index (EPL_E). The results from the FEA simulations agree well with the estimations from the model proposed in this paper. It is concluded that the energy dissipation in the collision between two balls covered by fine particles can be predicted by classical collision models of two particles through the substitution of several parameters from balls; the plastic deformation of fine particles affixed on balls can exhaust much more energy than that of the two balls without particles, which is the reason for the good performance of FPID; the diameter ratio of particle to ball and the material of particles do not have significant effects on the EPL_E when the ratio is limited to the range of [1/200 – 1/10]. A correlation of the EPL_E and dimensionless initial relative velocity is also found for the collisions between two balls, which is independent not only of the particle size and material properties but also of the particles presence.     

Relation between grain boundary segregation and grain boundary character in FCC alloys

An analytical model of segregation at grain boundaries, which takes into account all five macroscopic parameters of grain boundary character, has been developed. The model is based on a combination of previous bond energy treatments of grain boundary energy and of segregation to free surfaces. It is tested by comparing its predictions against previous computations of segregation to symmetrical twist grain boundaries in simple fcc alloys obtained by Monte Carlo simulations in conjunction with embedded atom method potentials. The comparison shows good agreement with the previous computer simulations. Examples of model predictions in the case of asymmetric grain boundaries are also provided.     

The role of electronic energy loss in ion beam modification of materials

The interaction of energetic ions with solids results in energy loss to both atomic nuclei and electrons in the solid. In this article, recent advances in understanding and modeling the additive and competitive effects of nuclear and electronic energy loss on the response of materials to ion irradiation are reviewed. Experimental methods and large-scale atomistic simulations are used to study the separate and combined effects of nuclear and electronic energy loss on ion beam modification of materials. The results demonstrate that nuclear and electronic energy loss can lead to additive effects on irradiation damage production in some materials; while in other materials, the competitive effects of electronic energy loss leads to recovery of damage induced by elastic collision cascades. These results have significant implications for ion beam modification of materials, non-thermal recovery of ion implantation damage, and the response of materials to extreme radiation environments.     

Simulation of crack growth in ductile materials

During crack growth of real materials, the total energy released can be partitioned into elastic and dissipative terms. By analyzing material models with mechanisms for dissipating energy and tracking all energy terms during crack growth, it is proposed that computer simulations of fracture can model crack growth by a total energy balance condition. One approach for developing fracture simulations is illustrated by analysis of elastic-plastic fracture. General equations were derived to predict crack growth and crack stability in terms of global energy release rate and irreversible energy effects. To distinguish plastic fracture from non-linear elastic fracture, it was necessary to imply an extra irreversible energy term. A key component of fracture simulations is to model this extra work. A model used here was to assume that the extra irreversible energy is proportional to the plastic work in a plastic-flow analysis. This idea was used to develop a virtual material based on Dugdale yield zones at the crack tips. A Dugdale virtual material was subjected to computer fracture experiments that showed it has many fracture properties in common with real ductile materials. A Dugdale material can serve as a model material for new simulations with the goal of studying the role of structure in the fracture properties of composites. One sample calculation showed that the toughness of a Dugdale material in an adhesive joint mimics the effect of joint thickness on the toughness of real adhesives. It is expected, however, that better virtual materials will be required before fracture simulations will be a viable approach to studying composite fracture. The approach of this paper is extensible to more advanced plasticity models and therefore to the development of better virtual materials.     

硅灰石晶体在三元氧化物熔体中的生长行为研究

利用耦合FACTSage Toxide 热力学数据库的定量相场模型, 本研究模拟了硅灰石(CaSiO₃)在CaO-Al₂O₃-SiO₂体系中的恒温晶体生长过程, 并研究了熔体组分和温度对CaSiO₃结晶过程的影响。结果表明, 硅灰石的形貌主要由其表面能的各向异性所决定, 而几乎不受界面动力学的各向异性所影响。此外, 随着温度的降低, 析出的硅灰石的生长方式由平面生长向枝晶生长方式转变, 于此同时, 更加精细的枝晶结构也逐渐呈现出来。模拟所得的枝晶生长速度和尖端半径与Ivanstov理论所得结果一致, 和实验测得的数据也处于同一数量级。