铜电解精炼添加剂生产实践与精细化管理探索

添加剂是铜电解精炼生产管理的最关键要素,合适的添加剂使用方案可以有效保障电解生产系统长期稳定。结合添加剂生产实践和其它电解厂添加剂管理优点,提出探索添加剂精细化管理,进一步保障和提升铜电解添加剂管理实效。     

浅谈工程总承包商对分包商的安全管理

分包商安全能力不足以及总包商安全管理薄弱,已成为导致工程建设项目事故多发的重要原因。将分包商的安全管理有效纳入到总承包商的安全管理体系内,做好分包商的安全管理,对提高总承包商的安全绩效、确保施工安全,具有极其重要的现实意义。从总承包商和分包商两个角度,研究分析分包安全管理中存在的问题及原因,得出分包安全管理各种问题的根源主要是经济利益,管理源头在总承包单位,站在总承包商的视角提出加强分包商安全管理的建议。     

石油化工项目建设管理数据平台的探讨

通过建立项目管理数据平台,让石油化工项目建设管理经验得到更好的传承和利用,数据平台可以实现管理经验数据化、建设数据共享化、数据结构模板化、数据编码标准化、收集数据流程化、数据操作平台化、数据计算集成化、数据更新动态化功能目标。结合石油化工项目建设特点,归纳了5类31种管理数据,介绍了每种数据的内容和用途,并对各种数据的字段设计、平台开发技术选择提出了建议,并对数据平台的未来价值进行了展望。     

基于二元水循环的水量-水质-水效联合调控模型开发与应用

为将我国最严格水资源管理制度的实践与二元水循环理论相结合，提高“三条红线”控制指标的科学性与合理性，本文以SWAT模型为基础，通过改进子流域划分方法、添加经济社会模块和人工用水模块，对其人工侧支循环模拟进行了系统的完善，开发了基于SWAT的水量-水质-水效联合调控模型SWAT_WAQER。以广西南流江流域为例，从国民经济用水量、河道径流与水质等方面对模型进行校验，并在此基础上划分了2030年“三条红线”控制指标。结果表明：该模型性能良好，能够用于不同节水情景下的国民经济用水量、污染物排放量、水功能区水质达标结果分析，可以作为科学制定“三条红线”控制指标的有力支撑工具。     

Framework to manage multiple goals in community-based energy sharing network in smart grid

Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.     

Project Risk Screening Matrix for River Management and Restoration

The ‘project risk screening matrix’ derives from a broader effort to assist US government agency staff in reviewing proposed stream management and restoration projects more efficiently and effectively. The River Restoration Analysis Tool (RiverRAT) developed through this effort provides a thorough, comprehensive and auditable approach to review and evaluate proposed stream actions and projects ( www.restorationreview.com ). The matrix was initially developed as the first step in applying the RiverRAT, its purpose being to assist reviewers in assessing the risk to natural resources associated with a particular proposal and matching the intensity of their review to the severity of that risk. Hence, the primary application of the matrix to date has been to identify and screen out low risk projects that may be dealt with expeditiously, so freeing the time and technical resources needed to allow deep reviews of higher risk projects. A second form of screening emerged from this primary function because the matrix proved adept at identifying the minimum level of site and project characterization required to support initial risk assessment. On this basis, proposals lacking adequate information can also be screened out, being referred back to the proponent with a request for additional information. More recently, new and novel versions of the matrix, featuring modification and refinement of one or both of the original axes, have emerged to widen and refine its application to linear infrastructure (e.g. pipelines, roads, and electrical transmission lines), in‐stream structures (e.g. large wood placement and culvert removal), and pre‐application, regulatory, decision‐support tools. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.     

An investigation into the cause of loss of containment from the supply of mini-bulk lubricants

An Intermediate Bulk Container (IBC) was punctured during its handling, releasing oil onto soil at an environmentally-sensitive region of Australia. The telehandler did not pierce the plastic of the IBC directly (as was expected) but rather one of the tynes had caught on the underside of the metal base plate, despite numerous controls being in place at time of spill, revealing a previously unreported mechanism for a fluid spill from handling of petroleum hydrocarbons. The diverse investigation team used a root cause analysis (RCA) technique to identify the underlying cause: the inspection process was inadequate with contributing factors of not using a spotter and design of IBC did not anticipate conditions. Engineering controls were put in place as part of the change management process to help prevent spills from occurring from piercing from telehandler tynes on the current project site.     

REST API技术及在移动通信网络管理中的应用

介绍了目前最炙手可热的REST架构风格，该风格顺应Web2.0的兴起，完美的匹配了云计算时代来临的可扩展要求，在各种应用场景中都得到了充分的表现。根据其技术特点，分析了该风格的API在移动通信网络管理中的应用，从网管系统内部、网管系统之间以及网管系统与上层APP应用之间等多方面对是否适用于REST风格以及如何在合适的位置使用REST API进行了分析。     

Automated network management and configuration using Probabilistic Trans-Algorithmic Search

Online configuration of large-scale systems such as networks requires parameter optimization within a limited amount of time, especially when configuration is needed as a response to recover from a failure in the system. To quickly configure such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It allocates an experiment budget to each available search algorithm and observes its performance on the system-at-hand. PTAS then probabilistically reallocates the experiment budget for the next round proportional to each algorithm’s performance relative to the rest of the algorithms. This “roulette wheel” approach probabilistically favors the more successful algorithm in the next round. Following each round, the PTAS framework “transfers” the best result(s) among the individual algorithms, making our framework a trans-algorithmic one. PTAS thus aims to systematize how to “search for the best search” and hybridize a set of search algorithms to attain a better search. We use three individual search algorithms, i.e., Recursive Random Search (RRS) (Ye and Kalyanaraman, 2004), Simulated Annealing (SA) (Laarhoven and Aarts, 1987), and Genetic Algorithm (GA) (Goldberg, 1989), and compare PTAS against the performance of RRS, GA, and SA. We show the performance of PTAS on well-known benchmark objective functions including scenarios where the objective function changes in the middle of the optimization process. To illustrate applicability of our framework to automated network management, we apply PTAS on the problem of optimizing link weights of an intra-domain routing protocol on three different topologies obtained from the Rocketfuel dataset. We also apply PTAS on the problem of optimizing aggregate throughput of a wireless ad hoc network by tuning datarates of traffic sources. Our experiments show that PTAS successfully picks the best performing algorithm, RRS or GA, and allocates the time wisely. Further, our results show that PTAS’ performance is not transient and steadily improves as more time is available for search.     

A non-parametric approach to demand forecasting in revenue management

In revenue management, the profitability of the inventory and pricing decisions rests on the accuracy of demand forecasts. However, whenever a product is no longer available, true demand may differ from registered bookings, thus inducing a negative bias in the estimation figures, as well as an artificial increase in demand for substitute products. In order to address these issues, we propose an original Mixed Integer Nonlinear Program (MINLP) to estimate product utilities as well as capturing seasonal effects. This behavioral model solely rests on daily registered bookings and product availabilities. Its outputs are the product utilities and daily potential demands, together with the expected demand of each product within any given time interval. Those are obtained via a tailored algorithm that outperforms two well-known generic software for global optimization.