52,542 research outputs found
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Coal mine low power laser methane detection and alarm instrument
At present, the portable carrier catalytic methane detection and alarm instrument for coal mine generally has many problems, such as high power consumption, short standby time, low detection accuracy, few parameters and single function, which can not meet the rapid development needs of mine safety. In this paper, a low power portable laser methane detection and alarm instrument based on tunable laser absorption spectroscopy (TDLAS) is designed. The instrument can detect methane concentration, ambient temperature and ambient pressure at the same time. It has the functions of sound and light alarm, historical data storage and query, and integrates Wi-Fi to realize data wireless transmission. The instrument can work continuously for 36 hours, and the response time is less than 15 seconds. It has the function of self-diagnosis. The overall performance of the instrument has been greatly improved compared with the traditional mine methane portable instrument. A mobile methane alarm Internet of things(IOT) system for coal mine based on portable instrument has been developed, which realizes real-time upload of data and cloud analysis, makes the traditional mine gas monitoring and control system powerfully supplemented, greatly improves the detection level of coal mine gas, and has broad application prospects
Monte Carlo Algorithm for Simulating Reversible Aggregation of Multisite Particles
We present an efficient and exact Monte Carlo algorithm to simulate
reversible aggregation of particles with dedicated binding sites. This method
introduces a novel data structure of dynamic bond tree to record clusters and
sequences of bond formations. The algorithm achieves a constant time cost for
processing cluster association and a cost between and
for processing bond dissociation in clusters with bonds.
The algorithm is statistically exact and can reproduce results obtained by the
standard method. We applied the method to simulate a trivalent ligand and a
bivalent receptor clustering system and obtained an average scaling of
for processing bond dissociation in acyclic
aggregation, compared to a linear scaling with the cluster size in standard
methods. The algorithm also demands substantially less memory than the
conventional method.Comment: 8 pages, 3 figure
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Application and research of wireless laser methane sensor in drainage pipeline monitoring
Laser methane sensor has been widely promoted and successfully applied in coal mines as a new and effective technology building on the approach of laser-based absorption detection. Compared with the traditional catalytic methane sensor, the laser methane sensor discussed offers the important advantages of a long calibration period, high detection precision, the absence of zero drift and low power consumption, all of which are significant advantages for use in coal mining applications. By compensating for the temperature and pressure of the gases present, the accuracy of the methane sensor is evident across a wide range of temperatures and pressures, making it suitable for gas detection, including methane, in pipelines as well. The wireless laser approach which is incorporated into the methane sensor allows wireless transmission and data uploading to a cloud server through NB-IoT. This tackles the problem in gas pipeline monitoring of the length of many pipelines and thus the wide distribution of the sensors, avoiding complicated wiring and thus high associated cost. Further, remote data management can then be achieved, all of which greatly improves the flexibility and security of the management of the pipeline and the data generated
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Research on VCSEL interference analysis and elimination method
Laser methane gas sensors have been increasingly accepted in coal mine safety monitoring. Most laser spectroscopic methane gas sensors are based in BFB lasers at around 1650nm. However, they suffer from high power consumption and high cost due to temperature control is required for laser diode operation at constant temperature. VCSEL lasers have offered low operation current and low power consumption when operating at non-TEC mode. However, it is found that the interference noise is critical for laser methane detection. This paper report typical results of the laser diode ripple characterization method and methods of noise reduction methods are discussed
Elastic-Net Regularization: Error estimates and Active Set Methods
This paper investigates theoretical properties and efficient numerical
algorithms for the so-called elastic-net regularization originating from
statistics, which enforces simultaneously l^1 and l^2 regularization. The
stability of the minimizer and its consistency are studied, and convergence
rates for both a priori and a posteriori parameter choice rules are
established. Two iterative numerical algorithms of active set type are
proposed, and their convergence properties are discussed. Numerical results are
presented to illustrate the features of the functional and algorithms
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Research progress on coal mine laser methane sensor
This paper discusses the research progress of low-power technology of laser methane sensors for coal mine. On the basis of environment of coal mines, such as ultra-long-distance transmission and high stability, a series of studies have been carried out. The preliminary results have been achieved in the research of low power consumption, temperature and pressure compensation and reliability design. The technology is applied to various products in coal mines, and achieves high stability and high reliability in products such as laser methane sensor, laser methane detection alarm device, wireless laser methane detection alarm device, and optic fiber multichannel laser methane sensor. Experimental testing and analysis of the characteristics of laser methane sensors, combined with the actual application
Semi-Inclusive B\to K(K^*) X Decays with Initial Bound State Effects
The effects of initial quark bound state for the semi-inclusive decays
are studied using light cone expansion and heavy quark
effective theory methods. We find that the initial bound state effects on the
branching ratios and CP asymmetries are small. In the light cone expansion
approach, the CP-averaged branching ratios are increased by about 2% with
respect to the free -quark decay. For , the
CP-averaged branching ratios are sensitive to the phase and the CP
asymmetry can be as large as 7% (14%), whereas for the CP-averaged branching ratios are not sensitive to and
the CP asymmetries are small (). The CP-averaged branching ratios are
predicted to be in the ranges [] for and [] for , depending on the value of the CP violating phase . In
the heavy quark effective theory approach, we find that the branching ratios
are decreased by about 10% and the CP asymmetries are not affected. These
predictions can be tested in the near future.Comment: 29 pages, 12 ps figure
Benchmark generator for CEC 2009 competition on dynamic optimization
Evolutionary algorithms(EAs) have been widely applied to solve stationary optimization problems. However, many real-world applications are actually dynamic. In order to study the performance of EAs in dynamic environments, one important task is to develop proper dynamic benchmark problems. Over the years, researchers have applied a number of dynamic test problems to compare the performance of EAs in dynamic environments, e.g., the “moving peaks ” benchmark (MPB) proposed by Branke [1], the DF1 generator introduced by Morrison and De Jong [6], the singleand multi-objective dynamic test problem generator by dynamically combining different objective functions of exiting stationary multi-objective benchmark problems suggested by Jin and Sendhoff [2], Yang and Yao’s exclusive-or (XOR) operator [10, 11, 12], Kang’s dynamic traveling salesman problem (DTSP) [3] and dynamic multi knapsack problem (DKP), etc. Though a number of DOP generators exist in the literature, there is no unified approach of constructing dynamic problems across the binary space, real space and combinatorial space so far. This report uses the generalized dynamic benchmark generator (GDBG) proposed in [4], which construct dynamic environments for all the three solution spaces. Especially, in the rea
Thermal expansion in carbon nanotubes and graphene: nonequilibrium Green's function approach
The nonequilibrium Green's function method is applied to investigate the
coefficient of thermal expansion (CTE) in single-walled carbon nanotubes
(SWCNT) and graphene. It is found that atoms deviate about 1% from equilibrium
positions at T=0 K, resulting from the interplay between quantum zero-point
motion and nonlinear interaction. The CTE in SWCNT of different sizes is
studied and analyzed in terms of the competition between various vibration
modes. As a result of this competition, the axial CTE is positive in the whole
temperature range, while the radial CTE is negative at low temperatures. In
graphene, the CTE is very sensitive to the substrate. Without substrate, CTE
has large negative region at low temperature and very small value at high
temperature limit, and the value of CTE at T=300 K is
K which is very close to recent experimental result,
K (Nat. Nanotechnol. \textbf{10}, 1038 (2009)). A very weak substrate
interaction (about 0.06% of the in-plane interaction) can largely reduce the
negative CTE region and greatly enhance the value of CTE. If the substrate
interaction is strong enough, the CTE will be positive in whole temperature
range and the saturate value at high temperature reaches
K.Comment: final version, to appear in PR
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