Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

基于RGV轨导柔性线环境离散型零件生产过程管理与实践

为满足航空中小型结构件快速交付的需要,以提升航空中小型结构件制造高精度、自动化和高效率为目标,通过对航空中小型结构件加工现状进行梳理分析,搭建柔性生产线自动排程与调度平台,实现柔性生产线工艺设计与准备过程管理,简化工艺准备流程,推进快换工装的应用并进行自动化程序管理;在柔性生产线加工运行过程中采用可视化管理方法,推动自动化环境下加工过程资源保障集中化管理。最终使该管理方法在某项目中进行成功实践,取得了良好的经济效益。     

基于BIM技术和有限元的检测与分析在PC结构中的应用研究

本文建立了PC结构施工全过程的BIM模型及有限元分析模型,对施工过程进行数值模拟与动态、静态监测,对装配式结构进行了结构性能评价,为结构可视化施工监测提供了技术支持。     

Selection of risk response actions with consideration of secondary risks

Secondary risk in project risk management refers to the risk that arises as a direct result of implementing a risk response action (RRA). It is important for project managers (PMs) to consider the effects caused by the secondary risks in the process of RRA selection. The purpose of this paper is to propose an optimization method to address the problem of selecting risk response actions (RRAs) with consideration of secondary risk which is seldom considered in the existing studies. The optimization model aims to minimize the total risk costs with time constraint being placed on the project makespan. By solving the model, an optimal set of RRAs along with the earliest start time for each activity can both be obtained. The results show that secondary risk plays an important role in the process of RRA selection. Project managers should allocate more budget for responding the project risk when the secondary risk is considered, and consider all factors relating to both time and cost so as to select appropriate RRAs to mitigate primary risk and secondary risk.     

Reduced basis method for managed pressure drilling based on a model with local nonlinearities

To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single-phase flow processes can be modeled as a feedback interconnection of a high-order linear system and a low-order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real-time purposes (eg, online model-based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced-order model can be used for efficient online simulation and controller design for drilling systems with MPD.     

宁夏红寺堡盆地隐伏古隆起成因机制及其对区域沙漠化的影响

目前对于青藏高原东北缘活动构造研究多集中于活动断裂带的活动性,而对夹持于其间的沉积盆地构造格架及活动性研究甚少。以夹持于烟筒山断裂与牛首山—罗山断裂之间的宁夏红寺堡盆地为研究对象,采用重力资料重处理解译、音频大地电磁测深(AMT)和地震勘探相结合,揭示红寺堡盆地隐伏构造特征,并进一步采用盆山一体化思路分析隐伏构造的成因机制及其对区域沙漠化的控制作用。结果表明:青藏高原在中新世末发生强烈的NE向推挤、扩展和隆升,红寺堡盆地由坳陷盆地转变为挠曲盆地; 在青藏高原NE向扩展的影响下,烟筒山断裂发生强烈的逆冲作用,古生代—中生代基底逆冲于古近系—新近系之上,受构造变形影响的最新地层为中新统彰恩堡组; 红寺堡盆地内的隐伏古隆起呈NW—SE向,与烟筒山构造带具有相同的构造动力学背景,受青藏高原NE向扩展影响形成于中新世末,并且至今仍具有活动性; 隐伏古隆起周缘断裂的活动破坏了地表稳定性、蓄水能力和地表植被,导致区域沙漠化呈现有规律的NW—SE向带状展布。该研究成果对于宁夏红寺堡盆地区域稳定性评价及沙漠化的综合治理具有现实指导意义。     

起重机械防碰装置试验系统的设计

防碰装置是起重机械重要的安全防护装置,其性能质量直接关系到人员和设备安全。常规的防碰装置性能试验方法难以保证试验数据的精度和可靠性。针对防碰装置的工作特点和试验要求,从试验原理、系统结构、运行逻辑等方面入手,设计一套能模拟防碰装置实际运行工况,自动进行性能试验和数据采集处理,精度高、重复性好的试验系统,可以有效提升防碰装置检测能力。     

小型特种精细化工过程自动化和信息化研究发展趋势探讨

针对采取小批量间歇性批次生产方式、工艺介质腐蚀性强、危险性大的小型特种精细化工生产工艺研究试验过程自动化、信息化程度不高，导致工艺研究试验中获取数据较少、过程机理研究不够透彻、人工操作多、安全风险高、研究试验消耗大及效率不高等问题，综述了期待通过智能控制、在线分析、模拟仿真和虚拟制造、工况监测及预测性维护以及信息管理和生产调度等关键技术的研究和应用，提高小型特种精细化工生产工艺过程的自动化和信息化程度，实现小型特种精细化工生产工艺过程的数字化、虚拟化和智能化，降低生产安全风险和试验消耗，提高小型特种精细化工生产工艺研究试验的成功率和效率，达到小型特种精细化工生产工艺过程的数字化设计和精准生产的目标。     

预压力对压电驱动履带移动系统的性能影响

为了提高夹心式压电驱动移动系统的机械输出性能，提出了一种U型预压力调节机构，并开展了预压力对夹心式压电驱动履带移动系统输出性能影响关系的实验研究。首先，针对U型预压力调节机构的安装对夹心式压电振子的振动特性影响关系开展了有限元仿真分析，发现U型预压力调节机构始终处在夹心式压电振子的两相工作模态振动节点位置；其次，开展了夹心式压电驱动履带移动系统的原理样机的预压力调节测试实验，确定了系统的最大输出牵引力及其所对应的最佳预压力；最后，在最佳预压力工作状态下，开展了原理样机的牵引力特性、越障性能以及模拟月壤环境下的运动特性实验。研究结果表明，在最佳预压力工作状态下，夹心式压电驱动履带移动系统的机械输出性能最佳，为其进一步在月面巡视器上的应用提供了技术支持和试验基础。