Self-Learning Algorithm for Coiling Temperature Controlling

In order to establish a mathematical model for strip laminar cooling, the self-learning algorithm was introduced with the level learning for obvious heat flux fluctuation and the pattern learning for small heat flux fluctuation. The short self-learning calculation steps of water cooling and air cooling, and the long self-learning formula were given with some results.     

Constrained Fuzzy c-Mean Clustering Algorithm for Determining Bridge Let Projects

Bridge engineers need to group bridges to determine adequate let projects based on their proximities, types of work, costs, and cost constraints for each clustered let project after bridges to be treated yearly are identified. This process is time-consuming and typically performed manually. First, this paper presents the formulation of a bridge clustering problem for determining let projects by considering the bridge proximity and type of work with preference membership functions to simulate the actual decision-making process. Second, a constrained fuzzy c-mean (FCM) clustering algorithm is presented to resolves this problem. A case study using the subset of bridges in the state of Georgia with the hypothetical treatments and costs was used to test the developed algorithm and to demonstrate its capability. The results show that the developed constrained FCM clustering algorithm can, in seconds, effectively determine adequate let projects by clustering bridges while meeting cost constraints. The presented formulation also allows incorporation of additional factors such as preference of clustering bridges with the same route number or same route type that are important to other state Departments of Transportation. Finally, conclusions about the benefits and characteristics of the developed algorithm are summarized, and recommendations for future research are discussed.     

Critical Path Scheduling under Resource Calendar Constraints

Resource calendars specify nonworking days of driving resources involved in construction projects. As part of the resource availability constraints in critical path method (CPM) scheduling, resource calendars may postpone activity start time, extend activity duration, and hence prolong the total project duration. Ultimately, resource calendars bring about changes to the critical path identification. Research has yet to address how to incorporate the effects of multiple resource calendars on the total float determination. In this research, the popular P3 software is used as a tool for investigating the current practice of CPM scheduling under resource limit and calendar constraints. We assess P3’s advanced resource scheduling functions (including resource leveling and resource calendars) and identify P3’s potential errors in total float determination. Further, we propose a new method based on the forward pass analysis alone for accurately evaluating activity total float subject to resource calendar constraints. The application of the new method is illustrated with an activity-on-node case and a precedence-diagram-method case, with the results compared against those produced from P3. Our research has elucidated on some critical issues of resource-constrained scheduling in the application domain of construction project management. The findings will provide useful input for the vendors and users of the CPM software—which is not limited to P3—to improve the scheduling methodology as well as the accuracy of the resulting project schedules.     

Efficient Hybrid Genetic Algorithm for Resource Leveling via Activity Splitting

Resource leveling problem is an attractive field of research in project management. Traditionally, a basic assumption of this problem is that network activities could not be split. However, in real-world projects, some activities can be interrupted and resumed in different time intervals but activity splitting involves some cost. The main contribution of this paper lies in developing a practical algorithm for resource leveling in large-scale projects. A novel hybrid genetic algorithm is proposed to tackle multiple resource-leveling problems allowing activity splitting. The proposed genetic algorithm is equipped with a novel local search heuristic and a repair mechanism. To evaluate the performance of the algorithm, we have generated and solved a new set of network instances containing up to 5,000 activities with multiple resources. For small instances, we have extended and solved an existing mixed integer programming model to provide a basis for comparison. Computational results demonstrate that, for large networks, the proposed algorithm improves the leveling criterion at least by 76% over the early schedule solutions. A case study on a tunnel construction project has also been examined.     

Exact Algorithm for Solving Project Scheduling Problems under Multiple Resource Constraints

This paper presents a new algorithm, called the enumerative branch-and-cut procedure (EBAC), for minimizing the total project duration of a construction project under multiple resource constraints based on an enumeration tree. The EBAC generates new branches to the tree corresponding to “better” feasible alternatives. It starts with all of the feasible schedule alternatives as the trial schedule alternatives at any node. The trial schedule alternatives are then evaluated to determine whether they are “worse” than any existing partial schedules in the tree by using the presented cut rules, and a worse alternative will be eliminated from the enumeration tree. In other words, the tree will contain only better feasible schedules. The presented algorithm has been coded in the VB6.0 language on a personal computer. It has been tested with the 110 scheduling problems, which have been widely used for validating a variety of schedule algorithms over the last 20?years. The EBAC can obtain the shortest project durations for all of the 110 problems.     

空气——乙炔火焰原子吸收法测定铬时铁的干扰及抑制方法

介绍了用空气－－乙炔火焰原子吸收法测定铬时铁的干扰状况以及抑制这种干扰的方法。本法应用于生铸铁，碳钢，低合金钢中铬量的测定，结果理想。     

完善现场联络单管理,合理确定和控制造价

在工程建设全过程中通过规范现场联络单签证的管理,并在执行过程中予以有效的实施,是合理确定和有效控制造价基础。     

XRF法测定含铁矿物原料主次成分过程控制的研究

采用X射线荧光光谱法在线测定铁矿石等矿物原料中主次成分,针对矿物原料的制样方式、样片制备方法、仪器分析条件等影响因素进行研究探讨,通过大量的实验和长期的生产实践,总结出分析过程中试样处理、仪器测量等操控因素和经验,应用到冶金生产的在线分析上,收到了较好的效果,满足了生产在线分析简便、快速、准确的需求。     

对提高有向图全路径穷举算法效率的研究

文章对复杂有向图全路径穷举问题的算法与算法效率作了较为详尽的研究和分析,提出了提高效率的办法,并提出了一种新的簇集搜索算法,同时对新算法的时间复杂度进行了分析计算,为更高效的算法研究提供了理论依据。     

模糊PID算法在锅炉汽包水位控制中的应用

文章针对包钢热电厂2#锅炉汽包水位的控制,采用模糊PID控制算法,给出仿真的具体实现方法,结果显示采用该算法具有良好的动态性能和抗干扰性能。     

Model Algorithm Research on Cooling Path Control of Hot-rolled Dual-phase Steel

With the development of advanced high strength steel,especially for dual-phase steel,the model algorithm for cooling control after hot rolling has to achieve the targeted coiling temperature control at the location of downcoiler whilst maintaining the cooling path control based on strip microstructure along the whole cooling section.A cooling path control algorithm was proposed for the laminar cooling process as a solution to practical difficulties associated with the realization of the thermal cycle during cooling process.The heat conduction equation coupled with the carbon diffusion equation with moving boundary was employed in order to simulate temperature change and phase transformation kinetics,making it possible to observe the temperature field and the phase fraction of the strip in real time.On this basis,an optimization method was utilized for valve settings to ensure the minimum deviations between the predicted and actual cooling path of the strip,taking into account the constraints of the cooling equipment′s specific capacity,cooling line length,etc.Results showed that the model algorithm was able to achieve the online cooling path control for dual-phase steel.     

Collision Free Path Planning of Cooperative Crane Manipulators Using Genetic Algorithm

This paper presents a new approach for automated path planning of cooperative crane manipulators using a genetic algorithm (GA). The inverse kinematic problem, i.e., determining the joint angle configuration for the cooperative crane manipulator system in moving the object from pick location to place location, is defined as an optimization problem and solved using GA. For generating the collision-free path, GA with an interference detection algorithm is employed and search is made in the manipulator joint angle space (configuration space). The effectiveness of the proposed approach for automated path planning is demonstrated by comparing the performance of the present approach with the earlier heuristic search proposed by Sivakumar et al. The GA approach finds a near-optimal path with lower path cost and less computational time than earlier heuristic searches.     

旋流器自动控制系统

影响旋流器工作的参数很多，合理控制操作参数是提高旋流器分级效率的关键，针对湖北二鑫公司选矿流程及旋流器的特点，设计了切合实际的控制系统，操作简单，维护方便。     

考虑侧填荷载的分离式基础涵洞地基承载力新算法和试验

为了研究涵侧填土对采用分离式基础涵洞地基承载力的提高效应,先结合基底土体的受力特点.进行受力分析,建立计算模型,构建求解分离式基础地基极限承载力的算法,给出承栽力表达式.然后在相似理论的指导下,设计了5组模型,试验模拟粉质黏土地基受荷变形直到破坏的全过程,绘出荷载一沉降曲线.测得涵侧填土高度为0、4、8、12、16 m时的地基极限承栽力.试验发现:随着侧填土高度的增加,承载力显著提高,当填土为12 m时已达到885 kPa;但提高幅度表现出非线性特性,先从18.42%增加到36.11%,然后减小到3.39%;当填土达到16 m时承载力达到915 kPa且不再增加;同时发现使用本文算法与试验实测值的误差小于10%,可以考虑用此算法计算分离式基础涵洞的地基极限承载力.继而得出结论:当涵洞地基沉降满足设计要求时,涵侧填土显著提高了地基承载力,节约工程造价,且提高的幅度先增加后减少,当达到16 m时地基承栽力便逐渐趋于915 kPa.     

距离幂次反比法品位估计公式中参数确定的遗传算法

应用遗传算法提出了自动确定距离幂次反比法品位估计公式中最优幂次的方法。该方法根据生存竞争的自然进化法则，对众多随机生成的幂次进行类似于生物进化时发生的复制、交换、变异等若干个改良操作，淘汰极不合理的幂次，改良较合理的幂次，最后优选出具有很高品位估计精度的幂次。该方法完全不依赖人，具有很好的客观性和通用性。