http://theses.ncl.ac.uk/jspui/handle/10443/90 2026-02-03T23:05:17Z 2026-02-03T23:05:17Z David, Raphael Kling http://theses.ncl.ac.uk/jspui/handle/10443/5121 2021-10-22T14:30:29Z 2020-01-01T00:00:00Z

Title: Software package applications for designing rail freight interchanges Authors: David, Raphael Kling Abstract: Rail freight transport has a crucial role to play in the economy, delivering significant reductions in logistics costs, pollution, and congestion. Typically, the conventional architecture and layout of the rail freight interchange constrain the capacity and performance of the whole railway system. A well-designed rail freight interchange can enhance the system performance by maximizing vehicle usage and minimizing last mile distribution cost. Therefore, the study of rail freight interchange operation is considered crucial to understand how to increase and improve the attractiveness for rail freight transport. This thesis uses game engines to develop software packages that are used for the design of new rail freight interchanges, considering multistakeholder decisions drivers. A novel and modular approach has been applied with the purpose of developing and deploying simulation tools that can be used by multiple stakeholders to: -Understand the impact of multiple-criteria decision analysis on rail freight interchange layouts; -Use a genetic algorithm to identify the most suitable components of the future interchange to be designed, considering the multi-stakeholders’ priorities; - Quickly enable the design of a wide variety of rail freight interchanges from the information selected by a decision maker in a computer-based userfriendly interface. This research has proposed a framework for software development. Three case studies are used to illustrate adaptability of a number of applications for different scenarios. The findings of the research contribute to a better understanding of the impacts of the multiple stakeholder’s decisions on rail freight interchange designs. Key words: Rail Freight Interchanges, Multi stakeholders decision, genetic algorithm Description: Ph.D. Thesis

2020-01-01T00:00:00Z Powell, Jonathan Peter http://theses.ncl.ac.uk/jspui/handle/10443/4468 2019-09-04T14:31:34Z 2016-01-01T00:00:00Z

Title: The use of linear motor technology to increase capacity in conventional railway systems Authors: Powell, Jonathan Peter Abstract: Wheel/rail adhesion is an important constraint on the design and operation of conventional railways. The research question considered for this thesis is whether linear motor technology can improve the performance of railway systems by reducing the dependence of tractive and braking effort on the available wheel/rail adhesion. The two principal contributions of the research are an analysis of the influence of several different linear motor technologies on the capacity of conventional railways, and the development of a new design concept for train braking (named LEMUR – Linear Electromagnetic Machine Using Rails). Multi-train simulation of three different railway networks was used to investigate the capacity benefits and energy consumption of the LEMUR concept, along with four other existing or proposed implementations of linear induction motor technology with the running rail used as the secondary component of the motor. A model of each network was built using OpenTrack software, and Monte Carlo simulation with pseudorandom distributions of initial delays to train services was carried out to compare train movements under the influence of the delays typically encountered during day-to-day operation. An indication of the improvements in railway capacity possible with different linear motor technology options was then derived from these simulations. The results of the experiments indicate that the LEMUR concept provided the greatest increase in capacity and the lowest energy consumption of the five linear motor technology options tested. Although the limitations of the study do introduce some uncertainty into the precise values of capacity and energy consumption obtained, the experimental methods were considered sufficiently robust for this conclusion to remain valid. The most promising application in the study was suburban passenger services that are part of busy mixed-traffic networks. Here, the capacity benefits of the LEMUR concept appear to show sufficient promise to justify further development and application. Description: PhD Thesis

2016-01-01T00:00:00Z Jaber, Alaa Abdulhady http://theses.ncl.ac.uk/jspui/handle/10443/4429 2019-08-19T15:41:32Z 2016-01-01T00:00:00Z

Title: Design of an intelligent embedded system for condition monitoring of an industrial robot Authors: Jaber, Alaa Abdulhady Abstract: Industrial robots have long been used in production systems in order to improve productivity, quality and safety in automated manufacturing processes. There are significant implications for operator safety in the event of a robot malfunction or failure, and an unforeseen robot stoppage, due to different reasons, has the potential to cause an interruption in the entire production line, resulting in economic and production losses. Condition monitoring (CM) is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation, diagnose the causes of faults and thus reduce maintenance costs. So, the main focus of this research is to design and develop an online, intelligent CM system based on wireless embedded technology to detect and diagnose the most common faults in the transmission systems (gears and bearings) of the industrial robot joints using vibration signal analysis. To this end an old, but operational, PUMA 560 robot was utilized to synthesize a number of different transmission faults in one of the joints (3 - elbow), such as backlash between the gear pair, gear tooth and bearing faults. A two-stage condition monitoring algorithm is proposed for robot health assessment, incorporating fault detection and fault diagnosis. Signal processing techniques play a significant role in building any condition monitoring system, in order to determine fault-symptom relationships, and detect abnormalities in robot health. Fault detection stage is based on time-domain signal analysis and a statistical control chart (SCC) technique. For accurate fault diagnosis in the second stage, a novel implementation of a time-frequency signal analysis technique based on the discrete wavelet transform (DWT) is adopted. In this technique, vibration signals are decomposed into eight levels of wavelet coefficients and statistical features, such as standard deviation, kurtosis and skewness, are obtained at each level and analysed to extract the most salient feature related to faults; the artificial neural network (ANN) is then used for fault classification. A data acquisition system based on National Instruments (NI) software and hardware was initially developed for preliminary robot vibration analysis and feature extraction. The transmission faults induced in the robot can change the captured vibration spectra, and the robot’s natural frequencies were established using experimental modal analysis, and also the fundamental fault frequencies for the gear transmission and bearings were obtained and utilized for preliminary robot condition monitoring. In addition to simulation of different levels of backlash fault, gear tooth and bearing faults which have not been previously investigated in industrial robots, with several levels of ii severity, were successfully simulated and detected in the robot’s joint transmission. The vibration features extracted, which are related to the robot healthy state and different fault types, using the data acquisition system were subsequently used in building the SCC and ANN, which were trained using part of the measured data set that represents the robot operating range. Another set of data, not used within the training stage, was then utilized for validation. The results indicate the successful detection and diagnosis of faults using the key extracted parameters. A wireless embedded system based on the ZigBee communication protocol was designed for the application of the proposed CM algorithm in real-time, using an Arduino DUE as the core of the wireless sensor unit attached on the robot arm. A Texas Instruments digital signal processor (TMS320C6713 DSK board) was used as the base station of the wireless system on which the robot’s fault diagnosis algorithm is run. To implement the two stages of the proposed CM algorithm on the designed embedded system, software based on the C programming language has been developed. To demonstrate the reliability of the designed wireless CM system, experimental validations were performed, and high reliability was shown in the detection and diagnosis of several seeded faults in the robot. Optimistically, the established wireless embedded system could be envisaged for fault detection and diagnostics on any type of rotating machine, with the monitoring system realized using vibration signal analysis. Furthermore, with some modifications to the system’s hardware and software, different CM techniques such as acoustic emission (AE) analysis or motor current signature analysis (MCSA), can be applied. Description: PhD Thesis

2016-01-01T00:00:00Z Wan Mohd Nazi, Wan Iman binti http://theses.ncl.ac.uk/jspui/handle/10443/4406 2019-08-08T09:15:52Z 2016-01-01T00:00:00Z

Title: Methods to move to zero energy commercial building (ZECB) for the future Authors: Wan Mohd Nazi, Wan Iman binti Abstract: This study aims to develop methods to reduce energy demand in the building sector, which is one of the main energy consumers. An extensive literature review has been carried out to understand the behaviour of buildings’ energy consumption and investigate the previous methods proposed in tackling building’s energy consumption. This work mainly focused on cooling dominated buildings in a hot and humid region. A typical medium sized commercial office building located in South East Asia was chosen as the case study. The building was audited to analyse its energy performance and mapped out its end-use energy consumption. It was found that the building consumed 7,334,630 kWh energy a year where 87.5% of the energy were spent on supplying a good indoor comfort for the occupant (that involves air conditioning and lighting). A detail data from the building’s energy manager was used to build a baseline building model before thermal analysis, and further investigation was carried out to achieve ZECB. It was discovered that 84% of the building’s heat gain was emanated from internal sources and 16% from solar. In this study, a whole-building approach encompassing of all the three methods (passive cooling using phase change material, retrofitting procedure based on thermal analysis and combined heat power solar energy generation system) were applied to the target building as a retrofit means that resulted in a zero energy commercial building (ZECB). The methods if implemented is estimated to reduce 52.2% of the total energy consumption with the remaining energy requirement will be fully supplied by on-site solar energy generator. While 573,674.77 kWh excess electricity and 3,531,703 kWh excess cold energy will be supplied to the grid and neighbouring buildings. Parts of the suggested retrofit strategies were fully implemented by the case-study building in February 2016. It is found that the actual energy consumptions after retrofitting were reduced as predicted from the simulation. This proves that the developed methods from this research are applicable to the real world. Description: PhD Thesis

2016-01-01T00:00:00Z