Optimization of Process Field Measurement GNSS-RTK for Railway Infrastructure

2016 ◽  
Vol 258 ◽  
pp. 481-484
Author(s):  
Dalibor Bartonek ◽  
Jiří Bures ◽  
Otakar Svabensky
Keyword(s):  
Field Measurement ◽  
Optimization Method ◽  
Heuristic Methods ◽  
Railroad Track ◽  
Time Intervals ◽  
Track Geometry ◽  
Railway Infrastructure ◽  
The Status ◽  
Dynamic Data Structure ◽  
Material Wear

The paper describes optimized measurements in field on points of railway control by the GNSS-RTK method. The purpose of measurement is to monitor the status of railroad track geometry. Good geometry extends the life of superstructure, reduces tracks and sleepers material wear during passing of the trains, and thus lowers the overall maintenance demands. In the model each of these points can be represented by node in graph and evaluation of graph edges corresponds to the distance between individual nodes. The task is to measure on every node even one times and to absolve the total route with minimal sum of distance. In fact it is searching of the Hamilton's path in a graph. The situation is complicated because the conditions for GNSS surveying in nodes are suitable only at certain time intervals during the day. Generally the above mentioned is difficult task, which is solved in the practice in many cases by heuristic methods. The authors proposed the optimization method based on Floyd algorithm and dynamic data structure - events list. The optimization of field measurement solves the time demands and brings economic effectiveness.

scholarly journals Developing an Enhanced Short-Range Railroad Track Condition Prediction Model for Optimal Maintenance Scheduling

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Prediction Method ◽  
Maintenance Scheduling ◽  
Railroad Track ◽  
Track Geometry ◽  
Track Maintenance ◽  
Track Condition ◽  
Optimal Maintenance ◽  
Process Work

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

scholarly journals Nature does not play Dice at the Planck scale

2020 ◽  
Vol 29 (14) ◽  
pp. 2043012
Author(s):  
Tejinder P. Singh
Keyword(s):  
Degrees Of Freedom ◽  
Large Scale ◽  
Planck Scale ◽  
Coarse Graining ◽  
Lagrangian Dynamics ◽  
Time Intervals ◽  
Spacetime Geometry ◽  
The Status ◽  
Planck Time ◽  
Matter Fields

We start from classical general relativity coupled to matter fields. Each configuration variable and its conjugate momentum, as also spacetime points are raised to the status of matrices [equivalently operators]. These matrices obey a deterministic Lagrangian dynamics at the Planck scale. By coarse-graining this matrix dynamics over time intervals much larger than Planck time, one derives quantum theory as a low energy emergent approximation. If a sufficiently large number of degrees of freedom get entangled, spontaneous localisation takes place, leading to the emergence of classical spacetime geometry and a classical universe. In our theory, dark energy is shown to be a large-scale quantum gravitational phenomenon. Quantum indeterminism is not fundamental, but results from our not probing physics at the Planck scale.

An integrated methodology for the prognosis of ballast degradation in railway turnouts

2019 ◽  
Vol 234 (8) ◽  
pp. 908-924
Author(s):  
Seyed Mohammad Asadzadeh ◽  
Roberto Galeazzi
Keyword(s):  
Bayesian Inference ◽  
Fractal Analysis ◽  
Degradation Rate ◽  
Analysis Method ◽  
Degradation Model ◽  
Track Geometry ◽  
Integrated Methodology ◽  
Railway Infrastructure ◽  
Rate Of Increase ◽  
Track Irregularities

This study proposes an integrated methodology for modelling and predicting ballast degradation in turnouts by exploiting loaded track geometry data. The rate of increase in track irregularities with respect to the cumulative loading of the track is the index of ballast degradation to be predicted. The methodology combines the fractal analysis method with probabilistic modeling and Bayesian inference to design a prognostic tool that forecasts the expected ballast degradation rate over a period of three months. The foundation of the proposed method is a universal degradation model for the ballast in turnouts, which fuses technological, operational, and environmental information to prognose the rate of ballast deterioration. The methodology has been verified on 15 different turnouts of the Danish railway infrastructure.

Optimization of Rail Transit Alignments considering Vehicle Dynamics

2012 ◽  
Vol 2275 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Xiaorong Lai ◽  
Paul Schonfeld
Keyword(s):  
Traffic Congestion ◽  
Vehicle Dynamics ◽  
Optimization Method ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Systems ◽  
Track Geometry ◽  
User Costs ◽  
Trade Offs ◽  
The Impact

Urban rail transit systems are being extended throughout the world because of their large capacities, avoidance of traffic congestion, and environmental advantages. Various optimization models can help design rail transit alignments satisfying various track geometry constraints, but none of these models can account for the impacts of vehicle dynamics on operational and user costs. This paper presents a practical rail transit alignment optimization method for designing track alignments that accounts for vehicle dynamics. The method can generate alignments that improve the balance between the initial cost and the operation and user costs recurring throughout the system's life cycle. A heuristic based on a genetic algorithm is developed to search for solutions efficiently while interacting with the supporting geographic information system. A hypothetical topography scenario is created to illustrate the impact of vehicle dynamics on the trade-offs among system costs. The Baltimore, Maryland, Red Line is used as a case study to demonstrate that the model can find good solutions in regions with complex topographies.

scholarly journals Non-destructive Photosynthetic Pigments Prediction using Multispectral Imagery and 2D-CNN

2021 ◽  
pp. 391-399
Author(s):  
Kestrilia Rega Prilianti ◽  
Syaiful Anam ◽  
Tatas Hardo Panintingjati Brotosudarmo ◽  
Agus Suryanto
Keyword(s):  
Photosynthetic Pigments ◽  
Rapid Assessment ◽  
Absolute Error ◽  
Optimization Method ◽  
Individual Plant ◽  
Multispectral Images ◽  
Validation Data ◽  
Plant Leaf ◽  
The Status ◽  
Non Destructive

Rapid assessment of plant photosynthetic pigments content is an essential issue in precise management farming. Such an assessment can represent the status of plants in their stages of growth. We have developed a new 2 Dimensional-Convolutional Neural Network (2D-CNN) architecture, the P3MNet. This architecture simultaneously predicts the content of 3 main photosynthetic pigments of a plant leaf in a non-destructive and real-time manner using multispectral images. Those pigments are chlorophyll, carotenoid, and anthocyanin. By illuminating with visible light, the reflectance of individual plant leaf at 10 different wavelengths – 350, 400, 450, 500, 550, 600, 650, 700, 750, and 800 nm – was captured in a form of 10 digital images. It was then used as the 2D-CNN input. Here, our result suggested that P3MNet outperformed AlexNet and VGG-9. After undergoing a training process using Adadelta optimization method for 1000 epochs, P3MNet has achieved superior MAE (Mean Absolute Error) in the average of 0.000778 ± 0.0001 for training and 0.000817 ± 0.0007 for validation (data range 0-1).

scholarly journals Optimization of Coalbed Methane Gathering System in China

2014 ◽  
Vol 6 ◽  
pp. 147381 ◽  
Author(s):  
Jun Zhou ◽  
Jing Gong ◽  
Xiaoping Li ◽  
Tong Tong ◽  
Mengya Cheng ◽  
...  
Keyword(s):  
Coalbed Methane ◽  
Energy Demand ◽  
Significant Proportion ◽  
Branch Pipe ◽  
Optimization Method ◽  
Pipe Network ◽  
Optimal Position ◽  
Process Characteristics ◽  
New Energy ◽  
The Status

Because of the increasing energy demand, coalbed methane (CBM) which is a high-quality, clean new energy gets more and more national attention. As one of the keys of CBM's successful development, the investment of surface gathering system accounts for a significant proportion of the entire field's investment. This paper studied the optimization of CBM gathering system, combined with system process characteristics and the status of extraction and production. We chose a phased optimization method such that the optimization of entire system was divided into several subproblems, including well group's optimal partition, determination of gathering valve set's optimal position, optimization of trunk and branch pipe network's layout, and optimization of pipe diameter. Then we established optimization model such that the least investment costs of each stage were to be as objective function. When solving the model, full consideration of the low pressure and high complexity by which the CBM gathering and transportation pipeline network was characterized should be given. Through an example calculation, compared with artificial design result, the total investment decreased by 9.56%. We proved that the method has a good optimization effect by comparably analyzing the investment and construction scale of the existing pipe network and optimal pipe network.

scholarly journals Optimization method for standards for working capital in the engineering enterprise.

2015 ◽  
Vol 2015 (2) ◽  
pp. 135-140
Author(s):  
Галина Коновалова ◽  
Galina Konovalova
Keyword(s):  
Quantitative Assessment ◽  
Optimization Method ◽  
Working Capital ◽  
Engineering Company ◽  
The Status ◽  
Engineering Enterprise

Proposed optimization method for calculating normative working capital at an engineering company, based on a comprehensive quantitative assessment of the status of the planned production.

Prediction of Track Geometry Status Based on Gray Forecast-Kalman Filter Analysis

2011 ◽  
Author(s):  
Chaolong Jia ◽  
Weixiang Xu ◽  
Hanning Wang
Keyword(s):  
Kalman Filter ◽  
Prediction Model ◽  
Recursive Algorithm ◽  
Status Change ◽  
Track Geometry ◽  
Real Change ◽  
The Status ◽  
Change Tendency ◽  
Filter Analysis ◽  
Track Status

Excellent condition of track geometry status is the foundation to ensure train travel security. The detection data of track inspection car contains many valuable features of the track status. The technique of gray forecast and Kalman filtering can be used to investigate the problem and predict the status change of the track geometry. In this paper, gray forecast is used in qualitative analysis of track geometry status changes, and we predict the development of track geometry status change using the Kalman filter prediction model and specific recursive algorithm, established prediction model of the track geometry to make an emulation experiment to analyze the data that track inspection car has detected, and predict changing trends of track geometry the state. Experiment results show that the application model of improved Kalman filter to predict the track geometry status changes gets a higher accuracy, and it can reflect the real change tendency of the track status.

Aristotelian Time

Metaphysica ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 35-49
Author(s):  
Dionysios A. Anapolitanos ◽  
Demetra Christopoulou
Keyword(s):  
Time Intervals ◽  
Existence Time ◽  
The Status ◽  
Critical Account ◽  
Mental Acts ◽  
Comparison Measures

Abstract In this paper we offer a critical account of Aristotelian theory of time. After a brief presentation of the main views of Aristotle on the infinite, we focus the attention to the status of points with respect to the potentiality-actuality distinction. Then we address Aristotle’s views on time on the basis of the Aristotelian notion of continuity. We construe the “nows” as potentialities awaiting to be actualized. We show that it is the intervention of an agent (soul), who, through finitely many unitary mental acts of noticing or perceiving, guarantees the actualization of particular “nows”, constructs or brings into existence time intervals and through their comparison measures them, so producing what Aristotle calls time.

Track geometry degradation and maintenance modelling: A review

2016 ◽  
Vol 232 (1) ◽  
pp. 73-102 ◽  
Author(s):  
Iman Soleimanmeigouni ◽  
Alireza Ahmadi ◽  
Uday Kumar
Keyword(s):  
Maintenance Scheduling ◽  
Railway Track ◽  
Railway Transportation ◽  
Degradation Behaviour ◽  
Maintenance Strategies ◽  
Track Geometry ◽  
Track Maintenance ◽  
Railway Infrastructure ◽  
Recovery Models ◽  
Scheduling Models

Increased demand for railway transportation is creating a need for higher train speeds and axle loads. These, in turn, increase the likelihood of track degradation and failures. Modelling the degradation behaviour of track geometry and development of applicable and effective maintenance strategies has become a challenging concern for railway infrastructure managers. During the last three decades, a number of track geometry degradation and maintenance modelling approaches have been developed to predict and improve the railway track geometry condition. In this paper, existing track geometry measures are identified and discussed. Available models for track geometry degradation are reviewed and classified. Tamping recovery models are also reviewed and discussed to identify the issues and challenges of different available methodologies and models. Existing track geometry maintenance models are reviewed and critical observations on each contribution are provided. The most important track maintenance scheduling models are identified and discussed. Finally, the paper provides directions for further research.

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