scholarly journals The initialization of initial generating equipment maintenance schedules while a heuristic method is used

2021 ◽  
Vol 29 (2) ◽  
pp. 6-23
Author(s):  
Pavel Yu. Gubin ◽  
Vladislav P. Oboskalov
Keyword(s):  
Power Systems ◽  
Heuristic Method ◽  
Directed Search ◽  
Equipment Maintenance ◽  
Maintenance Schedule ◽  
Normal Probability ◽  
Normal Probability Distribution ◽  
Feasible Solutions ◽  
Generating Equipment ◽  
Maintenance Schedules

Currently, heuristic methods based on iterative changing of feasible solutions set provide a perspective tool for generation equipment maintenance scheduling in power systems. Wherein effectiveness of a heuristic method depends significantly on the initial set of possible schedules or in other words quality of the method initialization. In this case, a widely used methodology of building the initial array of solutions on the basis of pseudorandom uniform generation of control variables seems to be only palliative way to access the problem. This paper proposes alternative initialization procedure drawing on the example of generating units maintenance planning with heuristic differential evolution method. The principle of this method is to get initial set of solutions utilizing normal probability distribution to generate pseudorandom deviations from the suboptimal maintenance schedule which is to be preliminarily formed using directed search method. Following this approach allows to improve probabilistic characteristics of resultant maintenance schedule in particular to decrease median value of an objective function and its coefficient of variation, and to maximize probability to get the combination of units outage moments completely suiting operational constraints.

Gas bubble induced scalings in geothermal systems

2021 ◽  
Author(s):  
Lilly Zacherl ◽  
Thomas Baumann
Keyword(s):  
Ph Value ◽  
Saturation Index ◽  
Gas Bubbles ◽  
Gas Bubble ◽  
Geothermal Systems ◽  
Injection Wells ◽  
Term Operation ◽  
Maintenance Schedule ◽  
Local Experience ◽  
Maintenance Schedules

<p>Scalings in geothermal systems are affecting the efficiency and safety of geothermal systems. An operate-until-fail maintenance scheme might seem appropriate for subsurface installations where the replacement of pumps and production pipes is costly and regular maintenance comprises a complete overhaul of the installations. The situation is different for surface level installations and injection wells. Here, monitoring of the thickness of precipitates is the key to optimized maintenance schedules and long-term operation.</p><p>A questionnaire revealed that operators of geothermal facilities start with a standardized maintenance schedule which is adjusted based on local experience. Sensor networks, numerical modelling and predictive maintenance are not yet applied. In this project we are aiming to close this gap with the development of a non-invasive sensor system coupled to innovative data acquisition and evaluation and an expert system to quantitatively predict the development of precipitations in geothermal systems and open cooling towers.</p><p>Previous investigations of scalings in the lower part of production pipes of a geothermal facility suggest that the disruption of the carbonate equilibrium is triggered by the formation of gas bubbles in the pump and subsequent stripping of CO<sub>2</sub>. Although small in it's overall effect on pH-value and saturation index, significant amounts of precipitates are forming at high volumetric flow rates. To assess the kinetics of gas bubble induced precipitations laboratory experiments were run. The experiment addresses precipitations at surfaces and at the gas bubbles themselves.</p>

scholarly journals STUDY AND APPLY ACO ALGORITHM IN TIME-COST OPTIMIZATION OF CONSTRUCTION PROJECT

2010 ◽  
Vol 13 (1) ◽  
pp. 17-30
Author(s):  
Luan Hong Pham ◽  
Nhan Thanh Duong
Keyword(s):  
Cost Optimization ◽  
Construction Project ◽  
Heuristic Method ◽  
Ant Colony ◽  
Ant Colony System ◽  
Time Cost ◽  
Project Duration ◽  
Proposed Model ◽  
Feasible Solutions ◽  
Computational Resources

Time-cost optimization problem is one of the most important aspects of construction project management. In order to maximize the return, construction planners would strive to optimize the project duration and cost concurrently. Over the years, many researches have been conducted to model the time-cost relationships; the modeling techniques range from the heuristic method and mathematical approach to genetic algorithm. In this paper, an evolutionary-based optimization algorithm known as ant colony optimization (ACO) is applied to solve the multi-objective time-cost problem. By incorporating with the modified adaptive weight approach (MAWA), the proposed model will find out the most feasible solutions. The concept of the ACO-TCO model is developed by a computer program in the Visual Basic platforms. An example was analyzed to illustrate the capabilities of the proposed model and to compare against GA-based TCO model. The results indicate that ant colony system approach is able to generate better solutions without making the most of computational resources which can provide a useful means to support construction planners and managers in efficiently making better time-cost decisions.

Partitioning and Guided Search: A Generalized Approach to Problem Solving in Preliminary Design

1989 ◽  
Author(s):  
S. Srinivasan ◽  
R. H. Allen
Keyword(s):  
Problem Solving ◽  
Expert Systems ◽  
Directed Search ◽  
Preliminary Design ◽  
Levels Of Abstraction ◽  
Guided Search ◽  
Structure Information ◽  
Design Variables ◽  
Minimum Number ◽  
Feasible Solutions

Abstract We report on using problem partitioning and constraint-guided search as a generalized approach to problem-solving in preliminary design. Specifically, a generic design template has been created as a tool to structure information to facilitate problem-solving in three different domains. The approach has been tested through the implementation of knowledge-based systems for the preliminary design of mechanical springs, composite sublaminates and expert systems. Information in each implementation has been partitioned as hierarchical levels of abstraction related through constraints. Function identifies the top level design goals to reduce the search involved for feasible solutions. Goal-directed search, driven by the design application and top-down refinement, reduces the number of possible alternatives. The commonalities extant in the domains have been represented as design goals at three levels of abstraction in the design template. Similar frame-based knowledge representations with inheritance hierarchies and mixed reasoning have been developed for the KEE™-based implementations in each domain. Distinctions among the domains have been modelled as low level slots in the frame hierarchy. Parametric studies in the domains of mechanical springs, composite sublaminates and expert systems indicate that the minimum number of decision levels required to characterize the preliminary design process in these domains is three; fewer levels would be insufficient to fundamentally characterize the designs. Further, it is observed hierarchical structuring of design information facilitates capturing the interactions among design variables at different levels of abstraction. By using the template representation and reasoning in other divisible domains, the effectiveness of our approach can be further investigated.

Modeling the development of rail corrugation to schedule a more economical rail grinding

2019 ◽  
Vol 234 (4) ◽  
pp. 370-380 ◽  
Author(s):  
Hirofumi Tanaka ◽  
Masashi Miwa
Keyword(s):  
Surface Roughness ◽  
Growth Curves ◽  
Minimum Cost ◽  
Maintenance Cost ◽  
Rail Corrugation ◽  
Maintenance Schedule ◽  
Rail Grinding ◽  
Noise Vibration ◽  
Maintenance Schedules ◽  
The Cost

Rail corrugation should be managed appropriately, as it causes noise, vibration, and degradation of track components and materials. Generally, rail corrugation is managed with the removal of rail surface roughness by rail grinding. However, in many cases, rail corrugation will reoccur after the rail is ground, thereby making the management of the phenomenon difficult for railway operators. For the proper management of rail corrugation, it is necessary to understand the development of rail corrugation and model it mathematically. However, this effort has not been made in previous studies. This paper investigates an efficient method for scheduling a regular grinding maintenance to manage rail corrugation. Using regularly measured data about rail surface roughness on a commercial line, a mathematical model was developed to estimate the growth of rail corrugation. This model was utilized to estimate the effects of the remaining roughness after rail grinding on the maintenance cost and to optimize the maintenance schedule. First, it was confirmed that the development of rail surface roughness of rail corrugation can be expressed in three phases and can be modeled by fitting the functions of growth curves to measurements of rail surface roughness recorded over a long period. Next, the rail grinding strategy was examined by applying this model to realize both effective and economical strategies for the maintenance of rail corrugation. This study confirmed that maintenance costs can be reduced by rail grinding that removes almost all of rail corrugation. In the case of ballasted tracks, it has been found that the optimal grinding schedule can reduce the cost of rail grinding as well as the cost of tamping. These findings can be applied by railway operators tasked with managing maintenance schedules for railway lines at a minimum cost.

Reliability Analysis for Link Mechanism under Influence of Multiple Factors Based on Support Vector Machine

2013 ◽  
Vol 753-755 ◽  
pp. 2904-2907 ◽  
Author(s):  
Xue Wei Ke ◽  
Jian Hou ◽  
Ting Feng Chen
Keyword(s):  
Support Vector Machine ◽  
Reliability Analysis ◽  
Support Vector ◽  
Computational Costs ◽  
Link Mechanism ◽  
Normal Probability ◽  
Normal Probability Distribution ◽  
Dimensional Errors ◽  
Multi Body ◽  
External Loads

Considering the influence of dimensional errors,clearances,friction coefficients,external loads and flex of part comprehensively,a multi-body dynamic model of link mechanism is established by using commercial software.Assuming that the above factors follow normal probability distribution are independent with each other,a mechanism reliability analysis method by combining simulation technology and support vector machine (SVM) are proposed to reduce the computational costs. The obtained results show that the computational costs of the proposed methods are much less than the computational costs of Monte Carlo Simulation (MCS).Therefore, the proposed methods might be efficient and valuable for the reliability analysis of complex mechanism.

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