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- Al-Douri, Yamur K.
(författare)
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Two-Level Multi-Objective Genetic Algorithm for Risk-Based Life Cycle Cost Analysis
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Artificial intelligence (AI) is one of the fields in science and engineering and encompasses a wide variety of subfields, ranging from general areas (learning and perception) to specific topics, such as mathematical theorems. AI and, specifically, multi-objective genetic algorithms (MOGAs) for risk-based life cycle cost (LCC) analysis should be performed to estimate the optimal replacement time of tunnel fan systems, with a view towards reducing the ownership cost and the risk cost and increasing company profitability from an economic point of view. MOGA can create systems that are capable of solving problems that AI and LCC analyses cannot accomplish alone.The purpose of this thesis is to develop a two-level MOGA method for optimizing the replacement time of reparable system. MOGA should be useful for machinery in general and specifically for reparable system. This objective will be achieved by developing a system that includes a smart combination of techniques by integrating MOGA to yield the optimized replacement time. Another measure to achieve this purpose is implementing MOGA in clustering and imputing missing data to obtain cost data, which could help to provide proper data to forecast cost data for optimization and to identify the optimal replacement time.In the first stage, a two-level MOGA is proposed to optimize clustering to reduce and impute missing cost data. Level one uses a MOGA based on fuzzy c-means to cluster cost data objects based on three main indices. The first is cluster centre outliers; the second is the compactness and separation ( ) of the data points and cluster centres; the third is the intensity of data points belonging to the derived clusters. Level two uses MOGA to impute the missing cost data by using a valid data period from that are reduced data in size. In the second stage, a two-level MOGA is proposed to optimize time series forecasting. Level one implements MOGA based on either an autoregressive integrated moving average (ARIMA) model or a dynamic regression (DR) model. Level two utilizes a MOGA based on different forecasting error rates to identify proper forecasting. These models are applied to simulated data for evaluation since there is no control of the influenced parameters in all of the real cost data. In the final stage, a two-level MOGA is employed to optimize risk-based LCC analysis to find the optimal replacement time for reparable system. Level one uses a MOGA based on a risk model to provide a variation of risk percentages, while level two uses a MOGA based on an LCC model to estimate the optimal reparable system replacement time.The results of the first stage show the best cluster centre optimization for data clustering with low and high intensity. Three cluster centres were selected because these centres have a geometry that is suitable for the highest data reduction of 27%. The best optimized interval is used for imputing missing data. The results of the second stage show the drawbacks of time series forecasting using a MOGA based on the DR model. The MOGA based on the ARIMA model yields better forecasting results. The results of the final stage show the drawbacks of the MOGA based on a risk-based LCC model regarding its estimation. However, the risk-based LCC model offers the possibility of optimizing the replacement schedule.However, MOGA is highly promising for allowing optimization compared with other methods that were investigated in the present thesis.
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| 2. |
- Khan, Saad Ahmed, 1987-
(författare)
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Effects of top-of-rail friction modifiers on the friction, wear and cracks of railway rails
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The railway is an economical and environmentally friendly mode of transport for long distances and heavy loads. The demands on the operators are increasing with increased competition in the market, and therefore they are currently demanding more track capacity. In the short term, the existing network is expected to deliver the increased capacity. In order to achieve increased capacity without introducing double track, either the axle load or the number of trains (i.e. the annual gross tonnage) needs to be increased, which will decrease the life of the rail and thus increase the maintenance cost. To increase the lifetime of the rails without compromising with regard to the axle load and speed, one must increase the strength of the rails, decrease the traction forces between the rails and wheels, or introduce a third body with anti-wear and anti-crack properties that can reduce the wear and rolling contact fatigue (RCF) without reducing the traction forces below the safety limit.The traction forces depend on several variables, for example third bodies in the wheel-rail interface, the train dynamics, the wheel and rail profiles, etc. Third bodies in the wheel-rail interface are one of the important influencing factors. The additive third bodies with anti-wear properties and friction reduction capabilities reduces both the wear and the RCF. However, a friction coefficient in the wheel tread and the top of the rail below 0.3 can cause slippage and a long braking distance. To reduce the degree of utilised friction to a value close to 0.35 from dry conditions with a value of 0.55, and thereby reduce the wear, a product known as top-of-rail friction modifier (TOR-FM) was developed in North America and presented in 2003 at the heavy haul conference. The TOR-FM manufacturers claim that their products provide a fixed range of friction coefficients (μ) and Kalker’s coefficients in the wheel-rail interface. Kalker’s coefficient considers the tendency of creepage between the rail and wheel as a function of the traction forces at lower creepage levels. Field and laboratory tests in the USA, Canada and China have determined the benefits of using friction control products, which include the reduction of RCF, wear, corrugation, bogie hunting, noise, and fuel consumption without any side effects. In contrast, researchers at Luleå University of Technology (LTU) have found that such products in certain conditions give unacceptably low friction that can cause long braking distances and slippage. Initial measurements performed using a wayside TOR-FM system on the Iron Ore Line (IOL – “Malmbanan” in Swedish) could not find any benefits of implementing such systems.Trafikverket is considering the implementation of the TOR-FM technology on the IOL. Directly implementing such technology can be inappropriate and expensive, because the reliability of a TOR-FM system has never been assessed for the conditions of the IOL. The IOL is the northernmost railway line in Sweden and is experiencing the problem of RCF, especially on its curves. This railway line is a single track and is mainly utilised by the ore freight trains operated by the Swedish mining company LKAB. The freight trains run by LKAB have an axle load of 30 tonnes, which is the heaviest in Europe. At present LKAB is planning to increase the axle load of their heavy haul trains to 32.5 tonnes, which will increase the RCF and wear issues.The present research investigated the effects of TOR-FMs using computer-based simulations, laboratory tests and field tests. The results from all the tests and simulations were used to calculate the life cycle cost of wayside and on-board systems. The simulation results have shown that by reducing the friction, the RCF can be reduced. This reduction in the RCF is greater on narrow curves than on larger curves as the traction forces decrease with an increase in the curve radius. Curves with a radius larger than m are not prone to RCF. The damage index method used in the simulation has also shown that on circular curves with a radius smaller than 300 m, the so-called “magic wear” rate can be achieved. Magic wear means that the wear rate due to normal operation is equal to the crack generation rate. The field results obtained using a handheld tribometer have shown that by using a TOR-FM, both the wear and the friction coefficients can be reduced. The content of the TOR-FM can have a significant effect on the carry distance and, generally, non-drying FMs have a longer carry distance. Excessive use of TOR-FM may cause unacceptably low friction and a high operational cost, and only result in an insignificant increase in the carry distance. In addition, it was also concluded that in the case of the wayside system during extreme winters, the equipment could have maintenance issues and thus a high operational cost. The on-board system is an economical alternative to the wayside system, as it has lower operation and maintenance costs. The results have also shown that snow and ice formation in the winter act as a lubricant. However, further investigations are needed to provide knowledge of the efficiency of such natural lubricants and their retention on the rail. The present research has taken the IOL as a case study, but the results will be applicable all over the world.
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