Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

Forging furnace with thermochemical waste-heat recuperation by natural gas reforming: Fuel saving and heat balance

This paper considers thermochemical recuperation (TCR) of waste-heat using natural gas reforming by steam and combustion products. Combustion products contain steam (H₂O), carbon dioxide (CO₂), and ballast nitrogen (N₂). Because endothermic chemical reactions take place, methane steam-dry reforming creates new synthetic fuel that contains valuable combustion components: hydrogen (H₂), carbon monoxide (CO), and unreformed methane (CH₄). There are several advantages to performing TCR in the industrial furnaces: high energy efficiency, high regeneration rate (rate of waste-heat recovery), and low emission of greenhouse gases (CO₂, NO_x). As will be shown, the use of TCR is significantly increasing the efficiency of industrial furnaces – it has been observed that TCR is capable of reducing fuel consumption by nearly 25%. Additionally, increased energy efficiency has a beneficial effect on the environment as it leads to a reduction in greenhouse gas emissions.     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

Computational modelling of water flow inside laboratory Knelson concentrator bowl

Enhanced gravity concentrators such as Knelson concentrator (KC) are extensively used in the mineral processing industry. The complexities of KC bowl geometry and variation of feed characteristics have forced process engineers to design empirically new units using laboratory and pilot-scale Knelson concentrators. However, numerical modelling methods such as computational fluid dynamics (CFD) and discrete element method (DEM) provide a better insight of flow behaviour of fluid and particulate solid phases inside these processing units. This article reports findings of CFD simulations for single-phase water flow inside the laboratory KC. An available standard 7.5-cm laboratory KC bowl was numerically simulated using realisable k-ε turbulence model to resolve the turbulence dispersion of existing transitional flow regime. The effects of relative centrifugal force (RCF) intensity and bed fluidisation water flow rate on the water velocity and pressure distributions were studied. Simulations confirmed the swirling flow pattern governing inside the bowl. The results revealed that the impact of RCF intensity on the water field values is greater than that of bed fluidisation water flow rate. Both velocity and pressure variations inside the bowl rings followed a linear trend.     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

Why do small business butcher shops fail to fully implement HACCP?

This study aims to assess the degree of HACCP implementation in small business butcher shops and understand which factors most influence butchers' intention to fully implement it, through the application of the Theory of Planned Behaviour. One hundred and one butchers managing or owning small butcher's responded to the interview regarding their Attitudes, Subjective Norm, Perceived Behavioural Control, Personal Norm, and Knowledge with regard to their Intention to fully implement a HACCP system in their shops. Before the interviews, a certified veterinarian visited all the shops. Visits included an inspection of the establishments using the Official Portuguese Control Plan checklist for meat retailers. Conformance level measured past performance regarding food safety practices. Based on past performance, butchers were divided into “high performers” and “low performers”. “High performers” yielded high values of Attitude and Intention towards the Behaviour. For these, Attitude and Personal Norm emerge as predictors of the Intention to fully implement a HACCP system. For “low performers”, Personal Norm was the strongest predictor of Intention, with results pointing to the need for an intervention from the authorities to promote increased conformance to food safety practices. For both groups, neither Social Norm nor Perceived Behavioural Control acted as significant predictors of Intention.     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data

This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.     

Ga-doped IZO films obtained by magnetron sputtering as transparent conductors for visible and solar applications

C-axis textured thin films of gallium-doped indium zinc oxide (GIZO) with a 2% ratio of Ga/Zn, were obtained via RF-magnetron sputtering with high transparency and electrical conductivity. A Box-Behnken response surface design was used to evaluate the effects of the deposition parameters (In₂O₃ target power, deposition time, and substrate temperature) on the chemical composition, optical, electrical, and structural properties of the GIZO films. The optical constants and the electrical properties were obtained using optical models. The GIZO stoichiometry, and therefore the In/Zn atomic ratio, affected the crystallinity, crystalline parameters, band gap, and charge carrier mobility of the GIZO films. The charge carrier density was related to the change in the crystalline parameters of the hexagonal structure and the In/Zn atomic ratio. The best electrical conductivity values (1.75?×?10³ Ω^?1 cm^?1) were obtained for GIZO films with In/Zn ratio ≥?1. Several figures of merit (FOM) defined for the visible and solar regions were comparatively used to select the optimal In/Zn atomic ratio that provided the best balance between the conductivity and the transparency. The optimal In/Zn ratio was in a range of 0.85–0.90 for the GIZO films.     

Digital image correlation strain measurement of thick adherend shear test specimen joined with an epoxy film adhesive

Structural bonding and bonded repairs of composite materials become more and more important. Understanding the strain within the bondline leads to suitable bonding design. For new design approaches the strain distribution within the bondline has to be analyzed. Thus, often finite element analysis (FE) are used. However, a huge challenge is the availability of reliable material properties for the adhesives and their validation. Previous work has shown that it is possible to measure the small displacements resulting within thin epoxy film adhesives using high resolution digital image correlation (DIC). In this work a 2D DIC setup with a high resolution consumer camera is used to visualize the strain distribution within the bondline over the length of the joint as well as over the adhesive thickness. Therefore, single lap joints with thick aluminum adherends according to ASTM D 5656 are manufactured and tested. Local 2D DIC strain measurements are performed and analyzed. Two different camera setups are used and compared. The evaluation provides reliable material data and enables a look insight the bondline. The results of the full field strain data measured with DIC are compared with numerical simulations. Thus, material models as well as chosen parameters for the adhesive are validated. Compared to extensometers, giving only point-wise information for fixed measuring points, the DIC allows a virtual point-wise inspection along the complete bondline. Furthermore, it allows measuring close to the bondline to reduce the influence of adherend deformation.