DSpace Collection:http://theses.ncl.ac.uk/jspui/handle/10443/902024-02-05T05:12:22Z2024-02-05T05:12:22ZSoftware package applications for designing rail freight interchangesDavid, Raphael Klinghttp://theses.ncl.ac.uk/jspui/handle/10443/51212021-10-22T14:30:29Z2020-01-01T00:00:00ZTitle: 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. Thesis2020-01-01T00:00:00ZThe use of linear motor technology to increase capacity in conventional railway systemsPowell, Jonathan Peterhttp://theses.ncl.ac.uk/jspui/handle/10443/44682019-09-04T14:31:34Z2016-01-01T00:00:00ZTitle: 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 Thesis2016-01-01T00:00:00ZDesign of an intelligent embedded system for condition monitoring of an industrial robotJaber, Alaa Abdulhadyhttp://theses.ncl.ac.uk/jspui/handle/10443/44292019-08-19T15:41:32Z2016-01-01T00:00:00ZTitle: 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 Thesis2016-01-01T00:00:00ZMethods to move to zero energy commercial building (ZECB) for the futureWan Mohd Nazi, Wan Iman bintihttp://theses.ncl.ac.uk/jspui/handle/10443/44062019-08-08T09:15:52Z2016-01-01T00:00:00ZTitle: 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 Thesis2016-01-01T00:00:00Z