光化学蚀刻在增益发生器加工中的应用前景

增益发生器是化学激光器的关键部件之一。为了提高激光光束的质量和激光器的工作性能,本文从增益发生器的加工工艺出发,简单的介绍了传统工艺及其优势与劣势,在此基础上提出了光化学蚀刻与扩散焊结合的新工艺及其优势。重点总结了光蚀刻工艺效果的影响因素及其解决方案。     

基于Petri网的现代造船车间工作流建模研究

面向生产过程控制,分析了现代造船车间生产作业流程与作业活动,提出以工作流管理系统为集成平台的车间生产过程管理,应用模块化着色网MCPN建立系统过程模型.动态适应性的系统过程模型是以基本子流程为模块,以作业任务为核心,自下而上建立的模块化Petri网结构,可体系化、参数化描述现代造船车间生产物流与作业流.     

基于三维CAD的船体集成装焊工艺设计与分析系统

根据集成化和工艺优化的设计思想,针对目前国内造船企业生产工艺设计手段水平不高和工艺可靠性分析不够规范的现状,设计开发了基于三维CAD的船体集成装焊工艺准备系统.实现了该系统与焊接工艺FMEA系统的集成,达到了集成焊接工艺设计与分析的目的,从而促进了船体快速工艺设计和工艺可靠性分析,提高了工艺准备的效率和质量.并给出了验证实例.     

废弃甲壳资源化利用制备天然高分子絮凝剂

论述了壳聚糖生产工艺的改进以及壳聚糖在重金属离子处理方面的应用.在稀酸脱钙阶段加入少量的助剂A,使传统工艺室温浸泡16 h～24 h变为在30℃下搅拌3 h,并确定助剂A的最佳投量比及反应的最佳时间.在浓碱脱乙酰阶段加入少量的助剂B,使传统工艺115℃下反应6 h变为105℃下反应2 h,并确定助剂B的最佳投量比及反应的最佳时间.红外光谱结果表明壳聚糖的主要性能参数均为合格,而生产成本则降低将近一半.应用壳聚糖处理重金属离子也取得较好的效果.     

聚氨酯复合改性沥青的制备与性能研究

为改善聚氨酯(PU)改性沥青的性能,实现其在道路工程领域的应用,将PU、岩沥青(RA)和基质沥青(BA)按照自定的室内工艺流程制备得到PU复合改性沥青,并探讨了制备工艺参数的适宜性.采用针入度、软化点、延度和旋转黏度试验优化了PU和RA的掺配方案,基于胶体理论分析了PU复合改性沥青的温度敏感性;利用动态剪切流变(DSR...     

Key criteria influencing the choice of Arctic shipping: a fuzzy analytic hierarchy process model

As Arctic sea ice shrinks due to global warming, the Northern Sea Route (NSR) and the Northwest Passage (NWP) offer a substantial reduction in shipping distance between Asia and the European and North American continents, respectively, when compared to conventional routes through the Suez and Panama Canals. However, Arctic shipping routes have many problems associated with their use. The main objective of this paper is to identify the key criteria that influence the decisions of shipping operators with respect to using Arctic shipping routes. A multi-criteria decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank four potential categories of criteria (‘economic’, ‘technical’, ‘political’ and ‘safety’ factors) and their sub-criteria.

The results of the analysis suggest that, on aggregate, ‘economic’ is the most important category of influential factors, followed by ‘safety’, ‘technical’ and ‘political’ factors. The paper concludes, however, that the most influential specific sub-criteria relate to risks that lie mainly within the ‘safety’ and ‘political’ domains and that, especially in combination, these overwhelm the importance which is attached to ‘economic’ factors such as reduced fuel use. Finally, the implications of these findings for the future development of Arctic shipping are addressed at a strategic level.     

基于HMM-SVR的船舶动力设备故障模式识别与状态预测研究

船舶动力设备因故障监测信号样本少、变化缓慢且数据特征呈非线性,使得设备故障模式的准确识别和状态预测比较难。鉴于此,文章研究了基于隐马尔科夫模型的故障模式识别方法,利用该模型将微弱变化的信号特征转换为变化较大的对数似然概率对故障模式实现有效识别。在此基础上进一步提出基于HMM-SVR的设备状态预测模型,将遗传算法用于支持向量回归模型参数寻优,并结合隐马尔科夫模型,实现对设备状态的预测。对船用柴油机进行仿真,结果表明上述模型具有较高的识别率,能准确预测船舶动力设备的当前状态。     

基于粗糙-模糊软计算的船板线加热成形加工参数预报方法

提出一种基于粗糙-模糊软计算的建模方法,构造一种基于贴近方向修正的高精度模糊推理算法,通过有限元分析(FEA)建立板材线加热成形工艺信息系统,根据粗糙集软计算获取线加热成形的工艺规律,运用模糊推理实现加工参数的快速准确预报。粗糙-模糊建模适用于线加热成形过程的静态或动态模型的构建,为实现该工艺的智能建模与控制提供一种新的技术手段。     

Situation analysis forecasting: the case of European maritime clusters

Within the literature concerned with aspects of competitiveness, innovation and strategic management of industrial clusters, the body regarding forecasting of strategic management is still nascent. This work aspires to render a contribution within the domain of strategic management forecasting, through the indicative case of European maritime clusters. For this end, a two-tier model is formulated. A quantitative strengths, weaknesses, opportunities, and threats (SWOT) methodology that derives from the fusion of a quondam situation analysis and crosstabs’ theory is generated. This leads to the utilization of the crosstab’s conditional probabilities as transition probabilities; the latter are called to compile the transition matrix of a Markov chain. Through this methodology, and the successive Markov chain’s transition matrices, strategic forecasts are extracted for a devised European maritime cluster case. This work relinquishes a novel application with respect to strategic management forecasting, that provides a dichotomy of practical interpretations and scenarios for quantitative situation analysis. Thus, it may enable effective real-time decision-making for strategic management and/or policy drafting. The situation analysis forecasting model may find applicability in a plethora of practical and theoretical cases, wherein forecasting may be desirable. It may as well pertain to an intrinsic methodology for situation analysis forecasting of maritime clusters.     

Shaping the Coast with Permits: Making the State Regulatory Permitting Process Transparent with Text Mining

This paper examines the California Coastal Commission's permitting process. Using several text mining techniques, including web scraping, information extraction, and supervised classification, I demonstrate how to retrieve empirical data from unstructured texts, namely public meeting agendas and staff reports. Contrary to the concern that the Commission routinely delays or rejects permitting requests, the data reveal that outright rejection of permit applications is rare. On average, eight of ten applications were approved. Single-family homes and commercial development projects were approved about 80% of the time; the rates were about 70% for seawalls and retaining walls, and 60% for land-use changes. Most applications were processed swiftly, with a median application length of 3 months. The agency's influence comes primarily from negotiating each application. Qualitative study of 50 cases pertaining to single-family home construction reveals that the agency adopts a “managed development” approach, that is, allowing development but scrupulously managing various aspects of development. These case studies illustrate how the agency interprets the broad, abstract state laws and translates the mandates into enforceable actions as permitting conditions. In areas where the state mandates conflict, particularly over development in receding shorelines, the agency has the largest leverage in creating and implementing its preferred policies. The text mining techniques demonstrated in this paper can be applied to study any governmental agency. These techniques help to extract information from a massive volume of papers and organize them into a database for analyses. The empirical data extracted from texts can significantly increase bureaucratic transparency.