TMCP工艺下Ti-Mg氧化物冶金钢轧态组织性能

摘要：为研究轧制过程中氧化物粒子对母材组织性能的影响，提出了一种只在再结晶区进行轧制的新工艺路线，利用常规冶炼及氧化物冶炼的实验钢分析其轧态显微组织、力学性能及相变过程。结果表明：在新轧制工艺下，氧化物冶金钢母材显微组织由常规的贝氏体板条束变为针状铁素体，其基体具有良好的力学性能，-80℃冲击韧性达149J；热轧工艺下的组织转变分两阶段进行，初期是针状铁素体的形核和晶粒细化，之后贝氏体相变被限制在针状铁素体板条间构成的区域内。     

A design method of data analytics process for condition based maintenance

Many condition monitoring systems use data analytics processes such as anomaly detection to understand machine conditions. Such data analytics processes have been designed by data scientists. However, domain knowledge is indispensable for designing the process, and data scientists have difficulty in acquiring such knowledge from domain engineers. This paper proposes a design method of data analytics processes and an engineering tool. In this method, data scientists propose hypotheses about each step of the process to domain engineers. Then, data scientists update the process on the basis of feedback from domain engineers. The engineering tool helps data scientists to interact with domain engineers.     

A practical data-flow verification scheme for business processes

Data in business processes becomes more and more important. Current standard languages for process modeling like BPMN 2.0 which include the data flow reflect this. Ensuring the correctness of the data flow in processes is challenging. Model checking, i.e., verifying properties of process models, is a well-known technique to this end. An important part of model checking is the construction of the state space of the model. However, state-space explosion typically is in the way of an effective verification. We study how to overcome this problem in our context by means of reduction. More specifically, we propose a reduction on the level of the process model. To our knowledge, this is new for the data-flow analysis of processes. The core of our approach are so-called regions of the process model that are relevant for the verification of properties describing the data flow. Non-relevant regions are candidates for reduction of the process model, yielding a smaller state space. Our evaluation shows that our approach works well on industrial process models.     

A similarity hybrid harmony search algorithm for the Team Orienteering Problem

The Harmony Search (HS) is a metaheuristic algorithm, which is inspired from the composition of music harmonies. The functionality and flexibility of HS contribute to the development of successful methodologies for different kind of scientific problems. The aim of this paper is to propose a variant of the classic HS algorithm in order to provide competitive solutions for the Team Orienteering Problem (TOP). We introduce the Similarity Hybrid Harmony Search (SHHS) algorithm as an alternative and innovative optimization method. The SHHS follows the standard procedure of HS with some modifications and includes a new strategy called “similarity process”. Two versions of the proposed method have been developed, the static version with predefined values for the parameters of the method and the dynamic one with dynamic adjustment of the parameters. The SHHS algorithm is applied to the known benchmark instances of TOP. The dynamic of the algorithm is tested through a complete solution analysis which gives the superiority of the dynamic version compared to the static one. The results of both versions of the proposed algorithm indicate the positive performance against other effective and robust optimization algorithms from the literature.     

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.     

A side-sensitive synthetic coefficient of variation chart

Control charts for monitoring the coefficient of variation (γ) are useful for processes with an inconsistent mean (μ) and a standard deviation (σ) which changes with μ, by monitoring the consistency in the ratio σ over μ. The synthetic-γ chart is one of the charts proposed to monitor γ, and its attractiveness lie in waiting until a second point to fall outside the control limits before a decision is made. However, existing synthetic-γ charts do not differentiate between the points falling outside the upper control limit (UCL) and lower control limit (LCL). Hence, this paper proposes a side-sensitive synthetic-γ chart, where successive nonconforming samples must either fall above the UCL or below the LCL. Formulae to compute the average run length (ARL), the standard deviation of the run length (SDRL) and expected average run length (EARL) are derived using the Markov chain approach, and the algorithms to obtain the optimal charting parameters are proposed. Subsequently, the optimal charting parameters, ARL, SDRL and EARL values for various numerical examples are shown. Comparisons show that the side-sensitive synthetic-γ chart consistently outperforms the existing synthetic-γ chart, especially for small shifts. The proposed chart also consistently outperforms the Shewhart-γ chart, while showing comparable or better performance than the Exponentially Weighted Moving Average (EWMA) chart for most shift sizes, except for very small shifts. Finally, this paper shows the implementation of the proposed chart on an industrial example.     

Potential effects of ultrafiltration process and date powder on textural,sensory, bacterial viability,antioxidant properties and phenolic profile of dromedary Greek yogurt

The aim of this study was to improve textural and antioxidant capacity of dromedary yogurt using ultrafiltration process and date powder. Ultrafiltration increased total solids content of dromedary milk within the range considered optimal to develop yogurt. Texture profile of Greek yogurt fortified with date powder (GYD) improved considerably compared to control. Sample of GYD are more appealing to consumer than control. LC-ESI-MS analysis of GYD extracts allowed the identification of fifteen phenolic compounds, among which quinic acid and cirsiliol were found to be the major phenolic acid and flavonol, respectively. GYD exhibited the highest DPPH•-radical scavenging activity, Fe²⁺ chelating capacity and Fe³⁺ reducing power. The follow-up of physical and microbiological stability of GYD and control during cold storage showed that date powder significantly increased bacterial counts and decreased syneresis. Therefore, ultrafiltration and date powder could be valued as effective tool to solve the poor consistency of dromedary milk products.     

Multi-Functional Black Bioactive Glasses Prepared via Containerless Melting Process for Tumor Therapy and Tissue Regeneration

Tissue regeneration in complex lesions such as the site of tumors, bacterial infection, and sites lacking blood vessels, has been a huge challenge. Therefore, developing bioactive implantable materials with multi-functional properties such as tumor destruction, bacteria growth inhibition, and angiogenesis promotion is of great significance. In this study, black CaO-SiO₂-TiO₂ (CST) glasses are prepared through the containerless melting approach, by which heterogeneous nucleation can be avoided and thereby glass formation becomes possible via fast quenching. This approach enables the formation of trivalent titanium (Ti³⁺) without using a reducing atmosphere or reducing agents. The black CST glasses are found in this study to possess a strong ability to inhibit bacteria and tumors by their excellent photothermal and photocatalytic effects. Strikingly, these glasses also promote the formation of blood vessels and accelerate the healing of chronic wounds by the synergistic effects of the photothermal effect and Si ions. Thus, this glass system can be a promising multi-functional material for tissue regeneration in complex lesions.