Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM_(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

Reality-based interaction affecting mental workload in virtual reality mental arithmetic training

ABSTRACT

The concept of digital game-based learning (DGBL) evolves rapidly together with technological enhancements of virtual reality (VR) and smart phones. However, the mental workload (MWL) that VR-training applications demand and motivational qualities originating from user experience (UX) should be identified in order to create effective and enjoyable training/learning challenges that fit with individual users’ capabilities. This study examined the effects of reality-based interaction (RBI) and VR on measures of student motivation and MWL, in a mental arithmetic game for secondary school pupils. In a randomised controlled trial with sixty school children, a mental arithmetic game was tested with three different interaction and two different presentation methods – VR RBI, VR head-mounted-display tapping and tablet flick-gesture. Results found a significant effect of RBI on MWL but no differences in enjoyment of training were found between VR-experience and tablet training-experience. In fact, adding the gaming-context to the mental arithmetic task created an enjoyable, motivating experience regardless of presentation or interaction-style.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Process and joint quality of ultrasonic vibration enhanced friction stir lap welding

In order to improve the process effectiveness and joint quality, ultrasonic vibrations were integrated with friction stir lap welding. Effect of ultrasonic exertion on the process and joint quality of AA 6061-T6 were investigated. Upon ultrasonic exertion, joints owned larger effective lap width, shorter hooks and improved strength. Weld fracture mode changed from a ductile–brittle mixed mode to a more ductile mode while the fracture path shifted from lap interface to beyond the stir zone. Material flow and interface defects were characterised using lap welded dissimilar aluminium alloy joints. Ultrasonic vibration improved the material flow and reduced the interfacial defects. Variations in failure load of joints were found in accordance with the variations in material flow and interfacial defects.     

Improving weld formability by a novel dual-rotation bobbin tool friction stir welding

A novel dual-rotation bobbin tool friction stir welding (DBT-FSW) was developed, in which the upper shoulder (US) and lower shoulder (LS) have different rotational speeds. This process was tried to weld 3.2 mm thick aluminum-lithium alloy sheets. The metallographic analysis and torque measurement were carried out to characterize the weld formability. Experimental results show that compared to conventional bobbin tool friction stir welding, the DBT-FSW has an excellent process stability, and can produce the defect-free joints in a wider range of welding parameters. These can be attributed to the significant improvement of material flow caused by the formation of a staggered layer structure and the unbalanced force between the US and LS during the DBT-FSW process.     

DFIT测试在长庆气田开发中的应用

与常规的小型测试压裂不同，流体注入诊断测试（DFIT）是通过关井阶段出现的拟线性流或拟径向流阶段求取储层压力，采用改进的梅耶霍夫方法（M-method）解释储层渗透率。以长庆榆林气田一口开发井为例，依据DFIT的技术原理和测试步骤，对该井测试压降数据进行解释分析，结果可信度较高，证明了该项工艺在长庆低压低渗油气田的可行性。     

番禺30-1砂岩强水驱气藏储层非均质性研究

针对垂向非均质性严重且边底水能量强的番禺30-1气田面临的潜在开发问题，通过岩心分析及测井二次解释，对其夹层特征及储层非均质性等进行了研究，划分出19个流动单元并定量描述了各流动单元的特征参数，建立了该气田的精细地质模型。综合评价表明，新建的地质模型具有较高的精度，为该气藏合理开发提供了坚实的地质基础。     

软件集成测试技术研究

首先分析了集成测试的原理和特点，并指出了集成测试的重要性。然后结合传统软件与面向对象软件开发的方法和技术，详细介绍了传统软件的集成测试方法和策略，并深入分析了面向对象软件集成测试的原理和方法。     

非稳定井流模型的半解析解

为了提高非稳定渗流计算的计算精度 ,通过数学分析得到了水位传导系数随时间变化时 ,一类非稳定渗流井流模型的半解析解 ,并进行了计算比较