Transport and dynamical properties for a bouncing ball model with regular and stochastic perturbations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of the influence of baffles and shields on the cooling of a digital transmission equipment

In this work design criteria for cooling of electronic systems used in a digital transmission equipment are considered. An experimental study using a simulated electronic equipment in which vertically oriented circuit boards are aligned to form vertical channels is carried out. Resistors are used to simulate actual components. The temperature of several components in the printed circuit boards are measured and the influence of the baffles and shields on the cooling effect are discussed. It was observed that the use of the baffles reduce the temperature levels and, the use of shields, although protecting the components from magnetic effects, cause an increase in the temperature levels.

Medium effects in the pion-pole mechanism [gamma gamma ->pi(0)->nu(R)(nu)over-bar(L)(nu(L)(nu)over-bar(R))] of neutron star cooling

Nuclear medium effects in the neutrino cooling of neutron stars through the reaction channel γγ→π0 →ν Rν̄L(νLν̄R) are incorporated. Throughout the paper we discuss different possibilities of right-handed neutrinos, massive left-handed neutrinos, and standard massless left-handed neutrinos (reaction is then allowed only with medium modified vertices). It is demonstrated that multiparticle effects suppress the rate of this reaction channel in the dense hadron matter by 6-7 orders of magnitude that does not allow to decrease existing experimental upper limit on the corresponding π0νν̄ coupling. Other possibilities of the manifestation of the given reaction channel in different physical situations, e.g., in the quark color superconducting cores of the most massive neutron stars, are also discussed. We demonstrate that in the color-flavor-locked superconducting phase for temperatures T≲ 0.1-10 MeV (depending on the effective pion mass and the decay width) the process is feasibly the most efficient neutrino cooling process, although the absolute value of the reaction rate is rather small.

Ecological optimization of an irreversible Brayton cycle with regeneration, inter-cooling and reheating

A mathematical model is developed for an irreversible Brayton cycle with regeneration, inter-cooling and reheating. The irreversibility are from the thermal resistance in the heat exchangers, the pressure drops in pipes, the non-isentropic behavior in the adiabatic expansions and compressions and the heat leakage to the cold source. The cycle is optimized by maximizing the ecological function, which is achieved by the search for optimal values for the temperatures of the cycle and for the pressure ratios of the first stage compression and the first stage expansion. The advantages of using the regenerator, intercooler and reheater are presented by comparison with cycles that do not incorporate one or more of these processes. Optimization results are compared with those obtained by maximizing the power output and it is concluded that the point of maximum ecological function has major advantages with respect to the entropy generation rate and the thermal efficiency, at the cost of a small loss in power.

RB32-266 Cooling Milk on Nebraska Farms

The desire of Nebraska people to continue the improvement of living conditions and to secure more healthful foods has been responsible for many changes in methods of caring for milk. One of the important factors in keeping milk sweet and of good quality is the process of cooling and keeping it cool until used. Three of these processes are as follows: placing containers of warm milk in any quantity of still water or still air at temperatures ranging from freezing to within a few degrees of the temperature of the milk, placing the containers in such positions that air or water are circulated around them, and causing the milk to flow in such manner that a thin film comes in contact with a surface which is cooled by air or liquids varying in temperature from 10 degrees Fahrenheit to a few degrees below that of the milk. After some of the heat has been removed the milk is stored under conditions very similar to those found in cooling processes. This 1932 research bulletin discusses why milk is cooled, why milk sours, how bacteria grows, and the many ways that milk can be cooled.

Feasibility Study of Solar Driven Underground Cooling System

In the United States the peak electrical use occurs during the summer. In addition, the building sector consumes a major portion of the annual electrical energy consumption. One of the main energy consuming components in the building sector is the Heating, Ventilation, and Air-Conditioning (HVAC) systems. This research studies the feasibility of implementing a solar driven underground cooling system that could contribute to reducing building cooling loads. The developed system consists of an Earth-to-Air Heat Exchanger (EAHE) coupled with a solar chimney that provides a natural cool draft to the test facility building at the Solar Energy Research Test Facility in Omaha, Nebraska. Two sets of tests have been conducted: a natural passively driven airflow test and a forced fan assisted airflow test. The resulting data of the tests has been analyzed to study the thermal performance of the implemented system. Results show that: The underground soil proved to be a good heat sink at a depth of 9.5ft, where its temperature fluctuates yearly in the range of (46.5°F-58.2°F). Furthermore, the coupled system during the natural airflow modes can provide good thermal comfort conditions that comply with ASHRAE standard 55-2004. It provided 0.63 tons of cooling, which almost covered the building design cooling load (0.8 tons, extreme condition). On the other hand, although the coupled system during the forced airflow mode could not comply with ASHRAE standard 55-2004, it provided 1.27 tons of cooling which is even more than the building load requirements. Moreover, the underground soil experienced thermal saturation during the forced airflow mode due to the oversized fan, which extracted much more airflow than the EAHE ability for heat dissipation and the underground soil for heat absorption. In conclusion, the coupled system proved to be a feasible cooling system, which could be further improved with a few design recommendations.

Stochastic Partial Budgeting: A New Look at an Old Tool

Farm business managers are constantly making adjustments in their businesses for smoother operations and profitability. Many times, these choices involve actions to enhance the financial return of the farm business; while other times these decisions are made out of necessity to minimize the effects of unfavorable conditions or events such as drought or changes in the market conditions. Some of these decisions are relatively simple, requiring making choices among alternatives within an enterprise; while others are complex involving a total overhaul of the business and its enterprises. Alternative choices within an individual enterprise can have a differential impact on farm profitability. Therefore, making the best decision may make the difference between profit or loss for that enterprise. Partial budgeting is very useful in making such changes within an enterprise of a farm.

Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Stochastic gravito-inertial modes discovered by CoRoT in the hot Be star HD51452

Context. Be stars are rapidly rotating stars with a circumstellar decretion disk. They usually undergo pressure and/or gravity pulsation modes excited by the kappa-mechanism, i.e. an effect of the opacity of iron-peak elements in the envelope of the star. In the Milky Way, p-modes are observed in stars that are hotter than or equal to the B3 spectral type, while g-modes are observed at the B2 spectral type and cooler. Aims. We observed a B0IVe star, HD51452, with the high-precision, high-cadence photometric CoRoT satellite and high-resolution, ground-based HARPS and SOPHIE spectrographs to study its pulsations in great detail. We also used the lower resolution spectra available in the BeSS database. Methods. We analyzed the CoRoT and spectroscopic data with several methods: CLEAN-NG, FREQFIND, and a sliding window method. We also analyzed spectral quantities, such as the violet over red (V/R) emission variations, to obtain information about the variation in the circumstellar environment. We calculated a stellar structure model with the ESTER code to test the various interpretation of the results. Results. We detect 189 frequencies of variations in the CoRoT light curve in the range between 0 and 4.5 c d(-1). The main frequencies are also recovered in the spectroscopic data. In particular we find that HD51452 undergoes gravito-inertial modes that are not in the domain of those excited by the kappa-mechanism. We propose that these are stochastic modes excited in the convective zones and that at least some of them are a multiplet of r-modes (i.e. subinertial modes mainly driven by the Coriolis acceleration). Stochastically excited gravito-inertial modes had never been observed in any star, and theory predicted that their very low amplitudes would be undetectable even with CoRoT. We suggest that the amplitudes are enhanced in HD51452 because of the very rapid stellar rotation. In addition, we find that the amplitude variations of these modes are related to the occurrence of minor outbursts. Conclusions. Thanks to CoRoT data, we have detected a new kind of pulsations in HD51452, which are stochastically excited gravito-inertial modes, probably due to its very rapid rotation. These modes are probably also present in other rapidly rotating hot Be stars.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012