CFD-Based Method of Determining Form Factor k for Different Ship Types and Different Drafts

The value of form factor k at different drafts is important in predicting full-scale total resistance and speed for different types of ships. In the ITTC community, most organizations predict form factor k using a low-speed model test. However, this method is problematic for ships with bulbous bows and transom. In this article, a Computational Fluid Dynamics(CFD)-based method is introduced to obtain k for different type of ships at different drafts, and a comparison is made between the CFD method and the model test. The results show that the CFD method produces reasonable k values. A grid generating method and turbulence model are briefly discussed in the context of obtaining a consistent k using CFD.

The Material Deformation and Internal Structure Development of Granular Materials under Different Cyclic Loadings

Common structures in engineering such as slopes,roadbeds,ballasts,etc.,are closely related to granular materials.They are usually subjected to long-term cyclic loads.This study mainly focused on the mechanical behaviors of randomly arranged granular materials before they reach a stable state under different cyclic loads.The variation of the maximum axial strain and the influence of CSR(cyclic stress ratio)were analyzed.The energy consumed in each cycle under constant confining stress loading condition is significantly greater than that of the fixed wall loading condition.The internal deformation evolution of granular materials is studied in detail.The deformation mode of granular material under cyclic loading at different positions inside the material is different according to the strain variation.In addition,the strain,force chain structure and contact force magnitude are combined to explore their effects on local deformation of granular materials under cyclic loading.From the perspective of the deformation form,the material sample can be divided into several regions,and the ability to adjust particle positions determines the deformation mode of different regions.The changes of local strain with the cyclic loading also reflect the contribution of particle displacements to the evolution ofmicrostructure.This research will provide insights into the understanding of granular materials behaviors under cyclic loading.

Analytical solution of time fractional Cattaneo heat equation for finite slab under pulse heat flux

A fractional Cattaneo model is derived for studying the heat transfer in a finite slab irradiated by a short pulse laser. The analytical solutions for the fractional Cattaneo model, the classical Cattaneo-Vernotte model, and the Fourier model are obtained with finite Fourier and Laplace transforms. The effects of the fractional order parameter and the relaxation time on the temperature fields in the finite slab are investigated.The results show that the larger the fractional order parameter, the slower the thermal wave. Moreover, the higher the relaxation time, the slower the heat flux propagates. By comparing the fractional order Cattaneo model with the classical Cattaneo-Vernotte and Fourier models, it can be found that the heat flux predicted using the fractional Cattaneo model always transports from the high temperature to the low one, which is in accord with the second law of thermodynamics. However, the classical Cattaneo-Vernotte model shows that the unphysical heat flux sometimes transports from the low temperature to the high one.

Feeding Effect of Growing-Finishing Pigs under Fine Division of Feeding Stages

In order to study the feeding effect of fine division of feeding stages on the growing-finishing pigs,96 healthy Duroc × Landrace ×Yorkshire hybrid commercial pigs with similar age in days,size,and body weight about 15 kg,half boars and half sows,randomly divided into3 treatments( each treatment repeated 4 times,and each repetition 8 pigs). According to the body weight division standard,three stages,four stages,and five stages of feeding were adopted separately. The daily ration of with different nutrition levels was used,body weight and feed consumption were measured,and effects of different feeding methods on body weight increase,feed utilization,and economic benefits of growing-finishing pigs. The results showed that compared with the three-stage feeding,the body weight of five-stage and four-stage feeding increased by 4. 18%( P < 0. 01) and 2. 41%( P < 0. 05),respectively,and the body weight of five-stage feeding increased by 1. 74%( P < 0. 05) compared with that of four-stage feeding; the daily feed consumption of five-stage and four-stage feeding increased 3. 10%( P < 0. 01) and 1. 70%(P <0. 01),respectively,and the daily feed consumption of five-stage feeding was 1. 37% higher than that of four-stage feeding. The feed cost of five-stage feeding and four-stage feeding increased 3. 32%( P < 0. 01) and 1. 61%( P < 0. 05) separately,and the feed cost of five-stage feeding was 1. 69% higher than that of four-stage feeding( P < 0. 01). The income from average body weight increase of five-stage and fourstage feeding increased by 5. 47%( P < 0. 01) and 3. 59%( P < 0. 01) respectively,and the benefit of average body weight increase of fivestage feeding was 1. 81% higher than that of four-stage feeding( P > 0. 05). The crude protein consumption from average body weight increase of five-stage and four-stage feeding decreased by 2. 28%( P < 0. 01) and 1. 68%( P < 0. 01),respectively; the crude protein consumption from average body weight increase of five-stage feeding was 0. 67% lower than that of four-stage feeding; the feed conversion ratio of five-stage feeding,four-stage feeding,and three-stage feeding was 2. 92,2. 93,and 2. 95 respectively. The results showed that compared with the threestage feeding,the four-stage and five-stage feeding could significantly increase the body weight of the growing-finishing pigs,improve the feed utilization level and improve the economic benefits,and the effect of five-stage feeding was better than the four-stage feeding.

Efficient String Similarity Search on Disks

String similarity search is a basic operation for various applications,such as data cleaning, spell checking, bioinformatics and information integration. Memory based q-gram inverted indexes fail to support string similarity search over large scale string datasets due to the memory limitation, and it can no longer work if the data size grows beyond the memory size. In the era of big data, large string dataset are quite common. Existing external memory method, Behm-Index, only supports length-filter and prefix filter. This paper proposes LPA-Index to reduce I/O cost for better query response time, and LPA-Index is a disk resident index which suffers no limitation on data size compared to memory size. LPA-Index supports multiple filters to reduce query candidates effectively, and it adaptively reads inverted lists during query processing for better I/O performance. Experiment results demonstrate the efficiency of LPA-Index and its advantages over existing state-of-art disk index Behm-Index with regard to I/O cost and query response time.

Deep Industrial Image Anomaly Detection: A Survey

The recent rapid development of deep learning has laid a milestone in industrial image anomaly detection(IAD).In this pa-per,we provide a comprehensive review of deep learning-based image anomaly detection techniques,from the perspectives of neural net-work architectures,levels of supervision,loss functions,metrics and datasets.In addition,we extract the promising setting from indus-trial manufacturing and review the current IAD approaches under our proposed setting.Moreover,we highlight several opening chal-lenges for image anomaly detection.The merits and downsides of representative network architectures under varying supervision are discussed.Finally,we summarize the research findings and point out future research directions.More resources are available at https://github.com/M-3LAB/awesome-industrial-anomaly-detection.

Efficient Top/Bottom-k Fraction Estimation in Spatial Databases Using Bounded Main Memory

Spatial databases store objects with their locations and certain types of attached items.A variety of modern applications have been developed by leveraging the utilization of locations and items in spatial objects,such as searching points of interest,hot topics,or users’attitude in specified spatial regions.In many scenarios,the high and low-frequency items in a spatial region are worth noticing,considering they represent the majority’s interest or eccentric users’opinion.However,existing works have yet to identify such items in an interactive manner,despite the significance of the endeavor in decision-making systems.This study recognizes a novel type of analytical query,called top/bottom-k fraction query,to discover such items in spatial databases.To achieve fast query response,we propose a multilayered data summary that is spread out across the main memory and external memory.A memory-based estimation method for top/bottom-k fraction queries is proposed.To maximize the use of the main memory space,we design a data summary tuning method to dynamically allocate memory space among different spatial partitions.The proposed approach is evaluated with real-life datasets and synthetic datasets in terms of estimation accuracy.Evaluation results demonstrate the effectiveness of the proposed data summary and corresponding estimation and tuning algorithms.