Numerical study of plasmas start-up by electron cyclotron waves in NCST spherical tokamak and CN-H1 stellarator

According to the physics of tokamak start-up,this study constructs a zero-dimensional(0D)model applicable to electron cyclotron(EC)wave assisted start-up in NCST spherical torus(spherical tokamak)and CN-H1 stellarators.Using the constructed 0D model,the results obtained in this study under the same conditions are compared and validated against reference results for pure hydrogen plasma start-up in tokamak.The results are in good agreement,especially regarding electron temperature,ion temperature and plasma current.In the presence of finite Ohmic electric field in the spherical tokamak,a study on the EC wave assisted start-up of the NCST plasma at frequency of 28 GHz is conducted.The impact of the vertical magnetic field B_(v)on EC wave assisted start-up,the relationship between EC wave injection power P_(inj),Ohmic electric field E,and initial hydrogen atom density n_(H0)are explored separately.It is found that under conditions of Ohmic electric field lower than ITER(~0.3 V m^(-1)),EC wave can expand the operational space to achieve better plasma parameters.Simulating the process of28 GHz EC wave start-up in the CN-H1 stellarator plasma,the plasma current in the zerodimensional model is replaced with the current in the poloidal coil of the stellarator.Plasma startup can be successfully achieved at injection powers in the hundreds of kilowatts range,resulting in electron densities on the order of 10^(17)-10^(18)m^(-3).

A related degree-based frequent pattern mining algorithm for railway fault data

It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.

New algorithm of mining frequent closed itemsets

A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory and time consuming problems. This algorithm maps the transaction database by using a Hash table,gets the support of all frequent itemsets through operating the Hash table and forms a lexicographic subset tree including the frequent itemsets.Efficient pruning methods are used to get the FC-tree including all the minimum frequent closed itemsets through processing the lexicographic subset tree.Finally,frequent closed itemsets are generated from minimum frequent closed itemsets.The experimental results show that the mapping transaction database is introduced in the algorithm to reduce time consumption and to improve the efficiency of the program.Furthermore,the effective pruning strategy restrains the number of candidates,which saves space.The results show that the algorithm is effective.

Analysis on the Problems in Start-up and Debugging of Two 600 MW Generating Units in Yangzhou No.2 Thermal Power Plant

The problems including excessive flow of attemperating water for boiler, failure of butterfly valve at the outlet of circulating water pump, burnt-out of thyristor for excitation regulator, load variation rate of CCS not complying with the contract target, etc. occurred during start-up and debugging of two 600 MW generating units in Yangzhou No.2 Thermal Power Plant. Through analysis on these problems. the remedial measures were put forward, to which can be referred for similar units.

Start-up of anaerobic ammonia oxidation bioreactor with nitrifying activated sludge

The anaerobic ammonia oxidation(Anammox) bioreactor was successfully started up with the nitrifying activated sludge. After anaerobically operated for 105 d, the bioreactor reached a good performance with removal percentage of both ammonia and nitrite higher than 95% and volumetric total nitrogen removal as high as 149.55 mmol/(L·d). The soft padding made an important contribution to the high efficiency and stability because it held a large amount of biomass in the bioreactor.

Double-layer Bayesian Classifier Ensembles Based on Frequent Itemsets

Numerous models have been proposed to reduce the classification error of Naive Bayes by weakening its attribute independence assumption and some have demonstrated remarkable error performance. Considering that ensemble learning is an effective method of reducing the classifmation error of the classifier, this paper proposes a double-layer Bayesian classifier ensembles （DLBCE） algorithm based on frequent itemsets. DLBCE constructs a double-layer Bayesian classifier （DLBC） for each frequent itemset the new instance contained and finally ensembles all the classifiers by assigning different weight to different classifier according to the conditional mutual information. The experimental results show that the proposed algorithm outperforms other outstanding algorithms.

A method to refine the start-up scheme of compression and refrigeration systems in ethylene plants via dynamic simulation

Starting the cracking gas compressor and precooling the refrigeration system are keys to start-up of an ethylene plant and accounts for up to 50% of the total start-up time and plant flare emissions. Premature feeding of cracking furnaces can be avoided if the cracking gas compressor is started and the refrigeration system is precooled in advance using mixed gas as the start-up working medium(SWM). Start-up scenario with mixed gas as SWM could significantly reduce the emission loss and shorten the precooling time. Research shows that making appropriate start-up scheme is important not only to ensure operational safety and feasibility, but also to reduce energy consumption. In this paper, a method is proposed to select suitable start-up operational parameters of compression and refrigeration system with sufficient safe operating ranges and short precooling time. The complex interrelation among key parameters of start-up is analyzed. It is found that higher energy consumption, especially for super high-pressure steam(SS), can promote operational safety and shorten the precooling time during start-up.Based on steady-state and dynamic simulation, appropriate operating parameter ranges are determined with reasonable SS consumption. A real case study demonstrates that an appropriate start-up scheme will optimize the operation.

Accurate querying of frequent subgraphs in power grid graph data

With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have chosen different indexing methods in the filtering stage to obtain more optimized query results because currently there is no uniform and efficient indexing mechanism that achieves good query results. In the traditional algorithm, the hash table for index storage is prone to "collision" problems, which decrease the index construction efficiency. Aiming at the problem of quick index entry, based on the construction of frequent subgraph indexes, a method of serialized storage optimization based on multiple hash tables is proposed. This method mainly uses the exploration sequence to make the keywords evenly distributed; it avoids conflicts of the stored procedure and performs a quick search of the index. The proposed algorithm mainly adopts the "filterverify" mechanism; in the filtering stage, the index is first established offline, and then the frequent subgraphs are found using the "contains logic" rule to obtain the candidate set. Experimental results show that this method can reduce the time and scale of candidate set generation and improve query efficiency.

A New Algorithm for Mining Frequent Pattern

Mining frequent pattern in transaction database, time series databases, and many other kinds of databases have been studied popularly in data mining research. Most of the previous studies adopt Apriori like candidate set generation and test approach. However, candidate set generation is very costly. Han J. proposed a novel algorithm FP growth that could generate frequent pattern without candidate set. Based on the analysis of the algorithm FP growth, this paper proposes a concept of equivalent FP tree and proposes an improved algorithm, denoted as FP growth * , which is much faster in speed, and easy to realize. FP growth * adopts a modified structure of FP tree and header table, and only generates a header table in each recursive operation and projects the tree to the original FP tree. The two algorithms get the same frequent pattern set in the same transaction database, but the performance study on computer shows that the speed of the improved algorithm, FP growth * , is at least two times as fast as that of FP growth.

An Efficient Hybrid Algorithm for Mining Web Frequent Access Patterns

We propose an efficient hybrid algorithm WDHP in this paper for mining frequent access patterns. WDHP adopts the techniques of DHP to optimize its performance, which is using hash table to filter candidate set and trimming database. Whenever the database is trimmed to a size less than a specified threshold, the algorithm puts the database into main memory by constructing a tree, and finds frequent patterns on the tree. The experiment shows that WDHP outperform algorithm DHP and main memory based algorithm WAP in execution efficiency.

Model test and numerical simulation on the dynamic stability of the bedding rock slope under frequent microseisms

Shake table testing was performed to investigate the dynamic stability of a mid-dip bedding rock slope under frequent earthquakes. Then, numerical modelling was established to further study the slope dynamic stability under purely microseisms and the influence of five factors, including seismic amplitude, slope height, slope angle, strata inclination and strata thickness, were considered. The experimental results show that the natural frequency of the slope decreases and damping ratio increases as the earthquake loading times increase. The dynamic strength reduction method is adopted for the stability evaluation of the bedding rock slope in numerical simulation, and the slope stability decreases with the increase of seismic amplitude, increase of slope height, reduction of strata thickness and increase of slope angle. The failure mode of a mid-dip bedding rock slope in the shaking table test is integral slipping along the bedding surface with dipping tensile cracks at the slope rear edge going through the bedding surfaces. In the numerical simulation, the long-term stability of a mid-dip bedding slope is worst under frequent microseisms and the slope is at risk of integral sliding instability, whereas the slope rock mass is more broken than shown in the shaking table test. The research results are of practical significance to better understand the formation mechanism of reservoir landslides and prevent future landslide disasters.

On-site stormwater detention for Australian development projects: Does it meet frequent flow management objectives?

On-site stormwater detention (OSD) is a conventional component of urban drainage systems, designed with the intention of mitigating the increase to peak discharge of stormwater runoff that inevitably results from urbanization. In Australia, singular temporal patterns for design storms have governed the inputs of hydrograph generation and in turn the design process of OSD for the last three decades. This paper raises the concern that many existing OSD systems designed using the singular temporal pattern for design storms may not be achieving their stated objectives when they are assessed against a variety of alternative temporal patterns. The performance of twenty real OSD systems was investigated using two methods:(1) ensembles of design temporal patterns prescribed in the latest version of Australian Rainfall and Runoff, and (2) real recorded rainfall data taken from pluviograph stations modeled with continuous simulation. It is shown conclusively that the use of singular temporal patterns is ineffective in providing assurance that an OSD will mitigate the increase to peak discharge for all possible storm events. Ensemble analysis is shown to provide improved results. However, it also falls short of providing any guarantee in the face of naturally occurring rainfall.

A Novel Incremental Mining Algorithm of Frequent Patterns for Web Usage Mining

Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.

The start-up of biohydrogen-producing process by bioaugmentation in the EGSB reactor

Expanded granular sludge bed （EGSB） reactor and bioaugmentation were employed to investigate biohydrogen production with molasses wastewater. The start-up experiments consisted of two stages. In the first stage （0 - 24d） seeded with activated sludge, the butyric acid type-fermentation formed when the initial expanding rate, organic loading rate （OLR）, the initial redox potential （ORP） and hydraulic retention time （HRT） were 10%, 10.0 kg COD/（m^3·d）, -215 mV and 6.7 h, respectively. At the beginning of the second stage on day 25, the novel hydrogen-producing fermentative bacterial strain B49 （AF481148 in EMBL） were inoculated into the reactor under the condition of OLR 16. 0 kg COD/（m^3·d）, ORP and HRT about - 139 mV and 6.7 h, respectively, and then the reaction system transformed to ethanol-type fermentation gradually with the increase in OLR. When OLR, ORP and HRT were about 94.3 kg COD/（m^3·d）, -250 mV and 1.7 h, respectively, the system achieved the maximum hydrogen-producing rate of 282.6 mL H2/L reactor·h and hydrogen percentage of 51% -53% in the biogas.

The exact solution of Stokes' second problem including start-up process with fractional element

The start-up process of Stokes＇ second problem of a viscoelastic material with fractional element is studied. The fluid above an infinite flat plane is set in motion by a sudden acceleration of the plate to steady oscillation. Exact solutions are obtained by using Laplace transform and Fourier transform. It is found that the relationship between the first peak value and the one of equal-amplitude oscillations depends on the distance from the plate. The amplitude decreases for increasing frequency and increasing distance.

A novel algorithm for frequent itemset mining in data warehouses

Current technology for frequent itemset mining mostly applies to the data stored in a single transaction database. This paper presents a novel algorithm MultiClose for frequent itemset mining in data warehouses. MultiClose respectively computes the results in single dimension tables and merges the results with a very efficient approach. Close itemsets technique is used to improve the performance of the algorithm. The authors propose an efficient implementation for star schemas in which their al- gorithm outperforms state-of-the-art single-table algorithms.

Frequent item sets mining from high-dimensional dataset based on a novel binary particle swarm optimization

A novel binary particle swarm optimization for frequent item sets mining from high-dimensional dataset(BPSO-HD) was proposed, where two improvements were joined. Firstly, the dimensionality reduction of initial particles was designed to ensure the reasonable initial fitness, and then, the dynamically dimensionality cutting of dataset was built to decrease the search space. Based on four high-dimensional datasets, BPSO-HD was compared with Apriori to test its reliability, and was compared with the ordinary BPSO and quantum swarm evolutionary(QSE) to prove its advantages. The experiments show that the results given by BPSO-HD is reliable and better than the results generated by BPSO and QSE.

Start-up and Performance of a Novel Reactor----Jet Biogas Inter-loop Anaerobic Fluidized Bed

A novel anaerobic reactor, jet biogas inter-loop anaerobic fluidized bed （JBILAFB）, was designed and constructed. The start-up and performance of the reactor was investigated in the Process. of .artificial glucose wastewater treatment. With the wastewater recycle ratio of 2.5 ： 1, the recycled wastewater with biogas could mix sludge and wastewater in the JBILAFB reactor completely. The start-up of the JBILAFB reactor could be completed in less than 70 d through maintenance of hydraulic retention time （HR^I＂） and stepwise increase of feed total organic carbon （TOC） concentration. After the start-up, with the volumetric TOC loadings of 14.3 kg·m ^-3·d^-1, the TOC removal ratio, the effluent pH, and the volatile fatty acids （VFA）/alkalinity of the JBILAFB reactor were more than 80%, close to 7.0 and less than 0.4, respectively. Moreover, CH4 was produced at more than 70% of the theoretical value, The reactor exhibited high stability under the condition of high volumetric TOC loading. Sludge granules in the JBILAFB reactor were developed during the start-up and their sizes were enlarged with the stepwise increase of volumetric TOC loadings from 0.8 kg.m^-3.d ^-1 to 14.3 kg.m^-3.d^-1. Granules, an offwhite color and a similar spherical shape, were mainly comprised of global-like bacteria. These had good methanogenic activity and settleability, which were formed probably through adhesion of the bacteria. Some inorganic metal compounds such as Fe, Ca, Mg, Al, etc. were advantageous to the formation of the granules.

Experimental research on characteristic of start-up pressure wave propagation in gelled crude oil by large-scale flow loop

In order to research start-up pressure wave propagation mechanism and determine pressure wave speed in gelled crude oil pipelines accurately,experiment of Large-scale flow loop was carried out.In the experiment,start-up pressure wave speeds under various operation conditions were measured,and effects of correlative factors on pressure wave were analyzed.The experimental and theoretical analysis shows that thermal shrinkage and structural properties of gelled crude oils are key factors influencing on start-up pressure wave propagation.The quantitative analysis for these effects can be done by using volume expansion coefficient and structural property parameter of gelled crude oil.A new calculation model of pressure wave speed was developed on the basis of Large-scale flow loop experiment and theoretical analysis.