Transport processes in TlI and in the AgI-TlI-system

The transport properties of TlI and the system AgI-TlI were investigated by measuring the electrical conductivity, sigma, and the electronic and ionic transport numbers. A particularly high electronic conductivity was detected in beta-TlI, while the alpha phase showed a predominant anionic contribution, as in TlCl and TlBr. The intermediate compounds, AgTl 2I 3 and AgTlI 2 , are silver ion conductors, but they exhibit low sigma values. A comparison with other polyiodides, with a high silver ion conductivity, is suggested on the basis of the crystal bond ionicity

Thermoelectric power and electric conductivity of the (Ag,Na)Cl and (Ag,Na)Br solid solutions

The electric conductivity and the initial thermoelectric power are determined for the solid solutions (Ag,Na)X (X=Cl,Br) over the whole composition range. Data drawn from both kinds of measurements allow to approximately estimate the contributions of cation vacancies and interstitial Ag + to the transport process. Two composition regions are distinguished: 0les NNaXles0.6 and 0.7< NNaX<1 where interstitial Ag + and cation vacancies, respectively, are prevailin

Thermoelectric power of the molten systems (Ag+Me)I and (Cu+Me)I (Me=Na, K, Rb, Cs)

The systems (Ag+Me)I and (Cu+Me)I were investigated by measuring their initial thermoelectric power; mixtures containing AgI show a behaviour much closer to the ideality than mixtures containing CuI. Interesting conclusions are suggested about the heats of transport of silver and copper ions in the pure molten iodides

Parameterized thermal macromodeling for fast and effective design of electronic components and systems

We present a parameterized macromodeling approach to perform fast and effective dynamic thermal simulations of electronic components and systems where key design parameters vary. A decomposition of the frequency-domain data samples of the thermal impedance matrix is proposed to improve the accuracy of the model and reduce the number of the computationally costly thermal simulations needed to build the macromodel. The methodology is successfully applied to analyze the impact of layout variations on the dynamic thermal behavior of a state-of-the-art 8-finger AlGaN/GaN HEMT grown on a SiC substrate

Evaluation of project management practices in the automotive original equipment manufacturers

This paper aims at understanding the current perceptions related to the Project Management (PM) practices in the automotive sector. To this end, a questionnaire is administrated to professionals and data are analyzed via the Kruskal-Wallis test. Results show that the ICT function is poorly oriented to PM, especially for professionals with longer experience. On the contrary, the logistics function might exploit the benefits of PM tools. PM is also considered a lever for increasing the firm's reputation. This work demonstrates that PM is a challenge for future developments of organizations and it shows its importance in the automotive industry that involves increasingly complex projects

A Neural network based observation operator for coupled ocean acoustic variational data assimilation

Variational data assimilation requires implementing the tangent-linear and adjoint (TA/AD) version of any operator. This intrinsically hampers the use of complicated observations.Here, we assess a new data-driven approach to assimilate acoustic underwater propagation measurements [transmission loss (TL)] into a regional ocean forecasting system. TL measurements depend on the underlying sound speed fields, mostly temperature, and their inversion would require heavy coding of the TA/AD of an acoustic underwater propagation model. In this study, the nonlinear version of the acoustic model is applied to an ensemble of perturbed oceanic conditions. TL outputs are used to formulate both a statistical linear operator based on canonical correlation analysis (CCA), and a neural network based (NN) operator. For the latter, two linearization strategies are compared, the best-performing one relying on reverse-mode automatic differentiation. The new observation operator is applied in data assimilation experiments over the Ligurian Sea (Mediterranean Sea), using the observing system simulation experiments (OSSE) methodology to assess the impact of TL observations onto oceanic fields. TL observations are extracted from a nature run with perturbed surface boundary conditions and stochastic ocean physics. Sensitivity analyses indicate that theNNreconstruction of TL is significantly better than CCA. BothCCAandNNare able to improve the upper-ocean skill scores in forecast experiments, with NN outperforming CCA on the average. The use of the NN observation operator is computationally affordable, and its general formulation appears promising for the adjoint-free assimilation of any remote sensing observing network. SIGNIFICANCE STATEMENT: Deep learning algorithms are now widely spread in a diverse range of fields to help with solving automatic classification and regression problems. Here, we present and assess a strategy aimed at introducing an observation operator based on neural networks in data assimilation. Linearization of such an operator, required by variational schemes, is also discussed and implemented. The methodology is applied to the coupled oceanic acoustic data assimilation problem, and provides promising results. Our approach may be extended in the future to assimilate any remotely sensed type of observations

Technical Description of the implementation of IR7 section at LHC with the FLUKA transport code.

This document contains the technical description of the LHC IR7 FLUKA implementation. It has been written as a handbook to analyze, understand or modify the heat deposition Monte Carlo calculations performed for a wide variety of objects in the IR7 section of the LHC accelerator, in construction at CERN. The work includes references to the prototyping schemes and the implementation of a complex set-up for FLUKA, which deals with lists of objects and properties defined in the Twiss parameters through the use of the LATTICE concept and of a broad collection of user written subroutines

Thermoelectric power of the molten systems (Cu,Me)Cl and (Cu,Me)Br (Me=Na, K, Rb, Cs)

The initial thermoelectric power of the molten systems (Cu,Me)Cl and (Cu,Me)Br (Me=Na,K,Rb,Cs) was determined using copper electrodes. The results are compared with previous results obtained from the systems (Cu,Me)I and (Ag,Me)X (X=Cl,Br,I)