Signals of primordial phase transitions on CMB maps

The analysis of the CMB anisotropies is a rich source of cosmological informations. In our study, we simulated the signals produced by the relics of a first order phase transition occured during an inflationary epoch in the early Universe. These relics are bubbles of true vacuum that leave a characteristic non-Gaussian imprint on the CMB. We use different statistical estimators in order to evaluate this non-Gaussianity. We obtain some limits on the allowed values of the bubble parameters comparing our results with the experimental data. We also predict the possibility to detect this signal with the next high resolution experiments.Comment: 2 pages, submitted to Proceedings of 9th Marcel Grossmann meetin

Present limits to cosmic bubbles from the COBE-DMR three point correlation function

The existence of large scale voids in several galaxy surveys suggests the occurence of an inflationary first order phase transition. This process generates primordial bubbles that, before evolving into the present voids, leave at decoupling a non-Gaussian imprint on the CMB. I this paper we evaluate an analytical expression of the collapsed three point correlation function from the bubble temperature fluctuations. Comparing the results with COBE-DMR measures, we obtain upper limits on the allowed non-Gaussianity and hence on the bubble parameters.Comment: 4 pages, 3 figures; submitted to MNRA

Detection of a dry-frozen boundary inside Martian regolith

The present work investigates the time oscillations of the temperature at several depths of a Martian soil analogue made of two layers of different physical properties. The maximum temperature-time oscillation inside the Martian soil analogue, DT, and its derivative with depth, d(DT)/dz or DDT, can be analysed to understand the presence of a boundary between dry and frozen soil. The maximum temperature-time oscillation, DT, reduces by about one order of magnitude at the boundary between dry and frozen soil if a frozen layer is present. The reduction of DT at the boundary between two dry soils with different porosity is much smaller. DDT decreases by more than one order of magnitude at the boundary between dry and frozen soil if a frozen layer is present. The reduction of DDT at the boundary between two dry soils with different porosity is much smaller. (C) 2008 Elsevier Ltd. All rights reserved

Theoretical prediction ofthe thermal conductivity and temperature variation inside mars soil analogues

Mars soil analogues, in dry and frozen conditions, are investigated, as far as the thermal conductivity prediction and the temperature variation, along its depth, are concerned. The thermal conductivity is theoretically predicted with the cubic cell model, which requires the knowledge ofthe thermal conductivity ofthe solid particle and ofthe materials present, i.e. atmospheric gas and/or frozen ice, and the porosity ofthe soil analogue. The soil mineral composition allows to evaluate the thermal conductivity ofthe solid particle. The heat capacity ofthe soil analogue is evaluated with the knowledge ofits physical properties, the porosity and the speci1c heats ofthe materials present. The thermal di2usivity is calculated as the ratio ofthe thermal conductivity and heat capacity and results to be a function ofthe porosity and the ice mass content ofthe soil analogue. The temperature variations, in dry and partially frozen soil analogues, are predicted during a Martian day. The temperature variation, at di2erent depth, is attenuated, as compared to the surface variation and a phase delay is present, depending on the soil thermal properties. The temperature variation, as well as the derivative ofthe temperature variation with the depth, is dependent on the thermal di2usivity ofthe soil analogue. In conclusion, the temperature measurement, along the depth ofa Martian soil analogue, can be used to verify its physical status, i.e. dry or partially frozen

Extension of soil thermal conductivity models to frozen meats with low and high fat content

Thermal conductivity models of frozen soils were analyzed and compared with similar models developed for frozen foods. In total, eight thermal conductivity models and 54 model versions were tested against experimental data of 13 meat products in the temperature range from 0 toK40 8C. The model by deVries, with waterCice (wi) as the continuous phase, showed overall the best predictions. The use of wi leads generally to improved predictions in comparison to ice; water as the continuous phase is beneficial only to deVries model, mostly from K1 to K20 8C; fat is advantageous only to meats with high fat content. The results of this work suggest that the more sophisticated way of estimating the thermal conductivity for a disperse phase in the deVries model might be more appropriate than the use of basic multi-phase models (geometric mean, parallel, and series). Overall, relatively small differences in predictions were observed between the best model versions by deVries, Levy, Mascheroni, Maxwell or Gori as applied to frozen meats with low content of fat. These differences could also be generated by uncertainty in meat composition, temperature dependence of thermal conductivity of ice, measurement errors, and limitation of predictive models

Introducing the Dark Energy Universe Simulation Series (DEUSS)

In this "Invisible Universe" proceedings, we introduce the Dark Energy Universe Simulation Series (DEUSS) which aim at investigating the imprints of realistic dark energy models on cosmic structure formation. It represents the largest dynamical dark energy simulation suite to date in term of spatial dynamics. We first present the 3 realistic dark energy models (calibrated on latest SNIa and CMB data): LambdaCDM, quintessence with Ratra-Peebles potential, and quintessence with Sugra potential. We then isolate various contributions for non-linear matter power spectra from a series of pre-DEUSS high-resolution simulations (130 million particles). Finally, we introduce DEUSS which consist in 9 Grand Challenge runs with 1 billion particles each thus probing scales from 4 Gpc down to 3 kpc at z=0. Our goal is to make these simulations available to the community through the "Dark Energy Universe Virtual Observatory" (DEUVO), and the "Dark Energy Universe Simulations" (DEUS) consortium.Comment: 6 pages, 3 figures, to appear in the AIP proceedings of the 'Invisible Universe International Conference', UNESCO-Paris, June 29-July 3, 200

Deployment of solar sails by joule effect: thermal analysis and experimental results

Space vehicles may be propelled by solar sails exploiting the radiation pressure coming from the sun and applied on their surfaces. This work deals with the adoption of Nickel-Titanium Shape Memory Alloy (SMA) elements in the sail deployment mechanism activated by the Joule Effect, i.e., using the same SMA elements as a resistance within suitable designed electrical circuits. Mathematical models were analyzed for the thermal analysis by implementing algorithms for the evaluation of the temperature trend depending on the design parameters. Several solar sail prototypes were built up and tested with different number, size, and arrangement of the SMA elements, as well as the type of the selected electrical circuit. The main parameters were discussed in the tested configurations and advantages discussed as well

Heat Conduction and Microconvection in Nanofluids: Comparison between Theoretical Models and Experimental Results

A nanofluid is a suspension consisting of a uniform distribution of nanoparticles in a base fluid, generally a liquid. Nanofluid can be used as a working fluid in heat exchangers to dissipate heat in the automotive, solar, aviation, aerospace industries. There are numerous physical phenomena that affect heat conduction in nanofluids: clusters, the formation of adsorbate nanolayers, scattering of phonons at the solid–liquid interface, Brownian motion of the base fluid and thermophoresis in the nanofluids. The predominance of one physical phenomenon over another depends on various parameters, such as temperature, size and volume fraction of the nanoparticles. Therefore, it is very difficult to develop a theoretical model for estimating the effective thermal conductivity of nanofluids that considers all these phenomena and is accurate for each value of the influencing parameters. The aim of this study is to promote a way to find the conditions (temperature, volume fraction) under which certain phenomena prevail over others in order to obtain a quantitative tool for the selection of the theoretical model to be used. For this purpose, two sets (SET-I, SET-II) of experimental data were analyzed; one was obtained from the literature, and the other was obtained through experimental tests. Different theoretical models, each considering some physical phenomena and neglecting others, were used to explain the experimental results. The results of the paper show that clusters, the formation of the adsorbate nanolayer and the scattering of phonons at the solid–liquid interface are the main phenomena to be considered when ϕ = 1 ÷ 3%. Instead, at a temperature of 50 ◦C and in the volume fraction range (0.04–0.22%), microconvection prevails over other phenomen

Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

The present review describes the up-to-date state of the evaluation of thermophysical prop erties (TP) of materials with three different procedures: modeling (also including inverse problems), measurements and analytical methods (e.g., through computing from other properties). Methods to measure specific heat and thermal conductivity are described in detail. Thermal diffusivity and thermal effusivity are a combination of the previously cited properties, but also for these proper ties, specific measurement and calculation methods are reported. Experiments can be carried out in steady-state, transient, and pulse regimes. For modeling, special focus is given to the inverse methods and parameter estimation procedures, because through them it is possible to evaluate the thermophysical property, assuring the best practices and supplying the measurement uncertainty. It is also cited when the most common data processing algorithms are used, e.g., the Gauss–Newton and Levenberg–Marquardt least squares minimization algorithms, and how it is possible to retrieve values of TP from other data. Optimization criteria for designing the experiments are also mentione

Quinstant Dark Energy Predictions for Structure Formation

We explore the predictions of a class of dark energy models, quinstant dark energy, concerning the structure formation in the Universe, both in the linear and non-linear regimes. Quinstant dark energy is considered to be formed by quintessence and a negative cosmological constant. We conclude that these models give good predictions for structure formation in the linear regime, but fail to do so in the non-linear one, for redshifts larger than one.Comment: 9 pages, 14 figures, "Accepted for publication in Astrophysics & Space Science