35,530 research outputs found
Corrections to the thermodynamics of Schwarzschild-Tangherlini black hole and the generalized uncertainty principle
We investigate the thermodynamics of Schwarzschild-Tangherlini black hole in
the context of the generalized uncertainty principle. The corrections to the
Hawking temperature, entropy and the heat capacity are obtained via the
modified Hamilton-Jacobi equation. These modifications show that the GUP
changes the evolution of Schwarzschild-Tangherlini black hole. Specially, the
GUP effect becomes susceptible when the radius or mass of black hole approach
to the order of Planck scale, it stops radiating and leads to black hole
remnant. Meanwhile, the Planck scale remnant can be confirmed through the
analysis of the heat capacity. Those phenomenons imply that the GUP may give a
way to solve the information paradox. Besides, we also investigate the
possibilities to observe the black hole at LHC, the results demonstrate that
the black hole can not be produced in the recent LHC.Comment: 12 pages, 6 figure
Possible Way to Synthesize Superheavy Element Z=117
Within the framework of the dinuclear system model, the production of
superheavy element Z=117 in possible projectile-target combinations is analyzed
systematically. The calculated results show that the production cross sections
are strongly dependent on the reaction systems. Optimal combinations,
corresponding excitation energies and evaporation channels are proposed in this
letter, such as the isotopes ^{248,249}Bk in ^{48}Ca induced reactions in 3n
evaporation channels and the reactions ^{45}Sc+^{246,248}Cm in 3n and 4n
channels, and the system ^{51}V+^{244}Pu in 3n channel.Comment: 10 pages, 4 figures, 1 tabl
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Preliminary experimental comparison and feasibility analysis of CO2/R134a mixture in Organic Rankine Cycle for waste heat recovery from diesel engines
This paper presents results of a preliminary experimental study of the Organic Rankine Cycle (ORC) using CO2/R134a mixture based on an expansion valve. The goal of the research was to examine the feasibility and effectiveness of using CO2 mixtures to improve system performance and expand the range of condensation temperature for ORC system. The mixture of CO2/R134a (0.6/0.4) on a mass basis was selected for comparison with pure CO2 in both the preheating ORC (P-ORC) and the preheating regenerative ORC (PR-ORC). Then, the feasibility and application potential of CO2/R134a (0.6/0.4) mixture for waste heat recovery from engines was tested under ambient cooling conditions. Preliminary experimental results using an expansion valve indicate that CO2/R134a (0.6/0.4) mixture exhibits better system performance than pure CO2. For PR-ORC using CO2/R134a (0.6/0.4) mixture, assuming a turbine isentropic efficiency of 0.7, the net power output estimation, thermal efficiency and exergy efficiency reached up to 5.30 kW, 10.14% and 24.34%, respectively. For the fitting value at an expansion inlet pressure of 10 MPa, the net power output estimation, thermal efficiency and exergy efficiency using CO2/R134a (0.6/0.4) mixture achieved increases of 23.3%, 16.4% and 23.7%, respectively, versus results using pure CO2 as the working fluid. Finally, experiments showed that the ORC system using CO2/R134a (0.6/0.4) mixture is capable of operating stably under ambient cooling conditions (25.2–31.5 °C), demonstrating that CO2/R134a mixture can expand the range of condensation temperature and alleviate the low-temperature condensation issue encountered with CO2. Under the ambient cooling source, it is expected that ORC using CO2/R134a (0.6/0.4) mixture will improve the thermal efficiency of a diesel engine by 1.9%
NMF-Based Comprehensive Latent Factor Learning with Multiview da
Multiview representations reveal the latent information of the data from different perspectives, consistency and complementarity. Unlike most multiview learning approaches, which focus only one perspective, in this paper, we propose a novel unsupervised multiview learning algorithm, called comprehensive latent factor learning (CLFL), which jointly exploits both consistent and complementary information among multiple views. CLFL adopts a non-negative matrix factorization based formulation to learn the latent factors. It learns the weights of different views automatically which makes the representation more accurate. Experiment results on a synthetic and several real datasets demonstrate the effectiveness of our approach
Non-contact online thickness measurement system for metal films based on eddy current sensing with distance tracking technique
This paper proposes an online, non-contact metal film thickness measurement system based on eddy current sensing. The slope of the lift-off curve (LOC) is used for characterizing target thickness. Theoretical derivation was conducted to prove that the slope is independent of the lift-off variation. In practice, the measurement has some immunity to the lift-off, but not perfect. The slope of LOC is still affected at some extent by the lift-off. Hence, a height tracking system was also proposed, which could stabilize the distance between the sensor and the target and significantly reduce the lift-off effect. The height tracking system contains a specially designed probe, which could vibrate rapidly to obtain a fast measurement speed, and its height can be adjusted up and down continuously to stabilize the lift-off. The sensorcoil in the thickness measurement system was also used as the height sensor in the height tracking system. Several experiments were conducted to test the system performances under static and dynamic conditions. This measurement system demonstrated significant advantages, such as simple and clear conversion between the slope of LOC and target thickness, high resolution and stability, and minimized effect of lift-off variation
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