Using information engineering to understand the impact of train positioning uncertainties on railway subsystems

Many studies propose new advanced railway subsystems, such as Driver Advisory System (DAS), Automatic Door Operation (ADO) and Traffic Management System (TMS), designed to improve the overall performance of current railway systems. Real time train positioning information is one of the key pieces of input data for most of these new subsystems. Many studies presenting and examining the effectiveness of such subsystems assume the availability of very accurate train positioning data in real time. However, providing and using high accuracy positioning data may not always be the most cost-effective solution, nor is it always available. The accuracy of train position information is varied, based on the technological complexity of the positioning systems and the methods that are used. In reality, different subsystems, henceforth referred to as ‘applications’, need different minimum resolutions of train positioning data to work effectively, and uncertainty or inaccuracy in this data may reduce the effectiveness of the new applications. However, the trade-off between the accuracy of the positioning data and the required effectiveness of the proposed applications is so far not clear. A framework for assessing the impact of uncertainties in train positions against application performance has been developed. The required performance of the application is assessed based on the characteristics of the railway system, consisting of the infrastructure, rolling stock and operational data. The uncertainty in the train positioning data is considered based on the characteristics of the positioning system. The framework is applied to determine the impact of the positioning uncertainty on the application’s outcome. So, in that way, the desired position resolution associated with acceptable application performance can be characterised. In this thesis, the framework described above is implemented for DAS and TMS applications to understand the influence of positioning uncertainty on their fundamental functions compared to base case with high accuracy (actual position). A DAS system is modelled and implemented with uncertainty characteristic of a Global Navigation Satellite System (GNSS). The train energy consumption and journey time are used as performance measures to evaluate the impact of these uncertainties compared to a base case. A TMS is modelled and implemented with the uncertainties of an on-board low-cost low-accuracy positioning system. The impact of positioning uncertainty on the modelled TMS is evaluated in terms of arrival punctuality for different levels of capacity consumption. The implementation of the framework for DAS and TMS applications determines the following: • which of the application functions are influenced by positioning uncertainty; • how positioning uncertainty influences the application output variables; • how the impact of positioning uncertainties can be identified, through the application output variables, whilst considering the impact of other railway uncertainties; • what is the impact of the underperforming application, due to positioning uncertainty, on the whole railway system in terms of energy, punctuality and capacity

First Principle Study on Lead-Free CH3NH3GeI3 and CH3NH3GeBr3 Perovskite solar cell using FHI-aims Code

An Ab-initio calculation in the framework of Density Functional Theory (DFT), as implemented in the FHI-aims package within Generalized Gradient Approximation (GGA) with the pbe parameterization was carried out in this work. Although methyl ammonium lead iodide (CH3NH3PbI3) has proven to be an effective photovoltaic material, there remains a main concern about the toxicity of lead.  An investigation into the possible replacement of CH3NH3PbI3 with CH3NH3GeI3 and CH3NH3GeBr3 as the active layer in perovskite solar cell was carried out. The electronic band structure, band gap energy and dielectric constants were calculated for CH3NH3GeI3 and CH3NH3GeBr3. The effect of temperature on linear thermal expansion coefficient and temperature dependence of lattice constant were studied in the temperature range of 273 to 318 K. Band gap shift due to lattice expansion was also studied. The dielectric constants of these materials were also determined. The energy band gap calculated for CH3NH3GeI3 and CH3NH3GeBr3 at their respective equilibrium lattice constant are 1.606 and 1.925eV respectively. A numerical simulation with some of these materials as the active layer in a perovskite solar cell was performed using General-purpose Photovoltaic Device Model (GPVDM) and the conversion efficiency of the resulting solar cell was obtained. Conversion efficiency of 10% and 8.4% were obtained for CH3NH3GeI3 and CH3NH3GeBr3 respectively

The Shift in Bandgap and Dielectric Constant Due to lattice Expansion in CH3NH3SnI3 Using FHI-aims

Although methyl ammonium lead iodide, (CH3NH3PbI3) has proven to be an effective photovoltaic material, there remains a main concern about the toxicity of lead, therefore determination of a lead free halide perovskite is of outstanding interest.  Sn2+ metal cations are the most obvious substitute for Pb2+ in the perovskite structure because of the similar s2 valence electronic configuration to Pb2+. Sn2+ can form a perovskite with a basic formula ASnX3 (A= CH3NH3 and X = halide) because the ionic radius of Sn2+ is similar to that of Pb2+. With the above similarity, methyl ammonium tin iodide CH3NH3SnI3 is one of the common replacement for CH3NH3PbI3 in the fabrication of organic-inorganic perovskite solar cells. FHI-aims code was used to perform the simulation of CH3NH3SnI3 in this work. Geometry building, parameter optimization, determination of the best exchange functional, k-grid convergence test along with determination of equilibrium lattice constant and geometry relaxation for CH3NH3SnI3 were carried out. An energy direct band gap of 1.051 eV was obtained, with an underestimation of 0.249 eV which amount to 19.2% when compared with experimental value. The lattice constant obtained using phonopy with ZPE is close to experimental reported values with an underestimation of 3.01%. The temperature dependent of lattice constant was studied in the temperature range of 0 to 318 K. At the same temperature range, shift in energy bandgap and dielectric constant due to lattice expansion was also investigated

Indications for intravitreal anti vascular endothelial growth factor in Kano, North Western, Nigeria

Background: To review the common indications for intravitreal anti vascular endothelial growth factor (VEGF) medications given at the retinal unit of Makkah Specialist Eye Hospital, Kano, Nigeria from January 2014 to December 2015.Methods: The case records of all patients given intravitreal anti VEGF medications were reviewed and age, diagnosis and indication for injection were recorded. Results were analyzed using the PAWS statistics version 18.0 (SPSS Inc., Chicago, IL).Results: A total of 174 injections consisting of 170 bevacizumab and 4 ranibizumab injections were given in the study period. The common indications for intravitreal injections were diabetic macula edema (42.5%), retinal vein occlusion (25.9%) and vitreous heamorrhage (9.8%).Conclusions: Diabetic macula edema and retinal vein occlusions are the major indications for intravitreal anti VEGF injections in Kano

Geological influence on the terrestrial gamma radiation dose rate in Jos Plateau, Nigeria

Natural environmental terrestrial gamma radiation dose (TGRD) rate measurements have been carried out across the geological formations of Jos Plateau, Nigeria. External gamma radiation dose rates ranged between 11 and 714 nGy h-1 with a mean value of 204 nGy h-1. Relationship between TGRD levels and geological type was determined. Statistical comparative method one way analysis of variance (ANOVA) was used to compare the TGRD means for the various types. The statistical results revealed in some instances, significant differences among the mean values of TGRD rates for the different underlying geological structures. Annual effective dose and collective effective dose for the general public due to exposure to terrestrial gamma radiation were estimated at 0.25 mSv y-1 and 1.20x102 mSv y-1, respectively. Isodose map for exposure rate due to TGRD wasplotted using ArcGIS software. The results will serve as database for natural background radiation for the country.Keywords: Natural radiation; Terrestrial gamma radiation dose (TGRD); geological type; Analysis of variance (ANOVA

The Effect of Temperature and Active layer thickness on the Performance of CH3NH3PbI3 Perovskite Solar Cell: A Numerical Simulation Approach.

In this work, General-purpose Photovoltaic Device Model (GPVDM) software was used to investigate the performance of a perovskite solar cell with CH3NH3PbI3 as its active layer. GPVDM is a free general-purpose tool for simulation of light harvesting devices. The model solves both electrons and holes drift-diffusion, and carrier continuity equations in position space to describe the movement of charge within the device. The model also solves Poisson's equation to calculate the internal electrostatic potential. Recombination and carrier trapping are described within the model using a Shockley-Read-Hall (SRH) formalism, the distribution of trap states can be arbitrarily defined. The software gives an output that contains the Current-Voltage (I-V) characteristic curves. A study into the effect of active layer thickness and temperature on the performance of the solar cell device was carried out. The optimal active layer thickness was found to be 3 x 10-7m. When the thickness exceeds 3 x 10-7 m, then the efficiency drops. At the optimal thickness of 3 x 10-7m, the devices were found to have power conversion efficiency up to 14.7%. On other hand the fill factor (FF) decreases as the thickness increases. The FF is highest at active layer thickness of 1 x 10-7m. The effect of device temperature also studied and the optimal working temperature was found to be 300 K, where power conversion efficiency and FF are 15.4 % and 0.76 respectively

Epidemiological Study of Meningitis Cases Admitted to AL-Razi Hospital in Diyala Governorate for the Period 2000 – 2004

Background: Meningitis is an inflammation of the meninges (pia and arachnoids membranes) which covers the brain, it may be either a cute or chronic, purulent or a septic (sterile).  Meningitis  may be caused by  infection  with  viruses , bacteria or other microorganism Patients & method: A review of case  records of patients with meningitis admitted to Al_razi hospital in Diyala governorate  for the period the 1st of  january 2000 to the 31th of December 2004 inclusive .Data were collected from the case records according to especial designed questionnaire . Analysis of the collected data  was done and the results of this descriptive  study presented by numbers  and  percentages. Results: Meningitis was the first cause of admittion (56.6%),meningitis more in males  with M:F ratio 1.5:1,more than 85%cases  occurred in those  below 19 years age ,most cases were rural residents(53.8%),more than 50% of cases reported in spring and autumn, meningitis reported  mostly in students 72%,viral  meningitis form 54.5%,case fatality rate was 6.3%. Conclusion: Meningitis is the first cammon cause of admission and there  must be a  good efferts to decrease morbidity and mortality of this diseas

Modelling and simulation of battery electric vehicle by using MATLAB-Simulink

Electric vehicles (EVs) are likely to be an alternative energy mode of transportation for the future as it has shown a great ability to reduce the consumption of petroleum based and other high CO2 emitting transportations fuels. In this study, the components of the BEVs system were discussed and a model of BEV on the MATLAB-Simulink platform was simulated. Moreover, the relevant electrical system components as well as its corresponding equations for verification were identified. Furthermore, all simulation results were considered. This study presents a foundation for extra researches

Energy Management System in Battery Electric Vehicle Based on Fuzzy Logic Control to Optimize the Energy Consumption in HVAC System

This particular research has been conducted at University Putra Malaysia (UPM) to investigate the applicability of fuzzy logic technique in enhancing the energy management of battery-powered electric vehicle (BEV). Because of the increasing demand of BEVs, there is a need to increase the battery power while fulfilling the conflicting of battery power needs and power consuming needs for motor and auxiliaries (such as HVAC). The balance between keeping the comfort of HVAC use and increasing the battery range is complicated and the support of Artificial Intelligence can be useful. The study integrated an energy management system, which is using the designed Fuzzy Logic strategy, to enhance the drain of battery power capacity. The simple black box design of the EMS system has two inputs, State of Charge (SoC) and Speed, and three outputs, Heated Seats, Front HVAC, and Rear HVAC. The membership functions of output fuzzy of the Front HVAC, which shows that every output has three equal categories, 1/3, 2/3, 3/3, associated with low, mid, and high. The same approach of membership functions is applied for Rear HVAC, and Heated Seat. The three outputs of the HVAC system assumed to have a constant load of 1000 Watt each and have three equal categories, low, medium, and high. The fuzzy logic design uses a strategy of nine rules. The simulation is applied on MATLAB Simulink environment and the tests are using two driving cycles, the New European Driving Cycle (NEDC) and Japan 10-15.  The results show that using the managed HVAC strategy can increase the battery driving range by 9.8-20.4% compared with the full-unmanaged HVAC strategy