scholarly journals A CASE STUDY OF THE IRANIAN NATIONAL RAILWAY AND ITS ABSOLUTE CAPACITY EXPANSION USING ANALYTICAL MODELS

Transport ◽  
2015 ◽  
Vol 32 (4) ◽  
pp. 398-414 ◽  
Author(s):  
Bayan Bevrani ◽  
Robert L. Burdett ◽  
Prasad K. D. V Yarlagadda
Keyword(s):  
Sensitivity Analysis ◽  
Traffic Flow ◽  
Upper Bounds ◽  
Analytical Models ◽  
Optimization Approach ◽  
Lower And Upper Bounds ◽  
Train Services ◽  
Railway Capacity ◽  
Capacity Determination

Identifying railway capacity is an important task that can identify ‘in principal’ whether the network can handle an intended traffic flow, and whether there is any free capacity left for additional train services. Capacity determination techniques can also be used to identify how best to improve an existing network, and at least cost. In this article, an optimization approach has been applied to a case study of the Iran national railway, in order to identify its current capacity and to optimally expand it given a variety of technical conditions. This railway is very important in Iran and will be upgraded extensively in the coming years. Hence, the conclusions in this article may help in that endeavor. A sensitivity analysis is recommended to evaluate a wider range of possible scenarios. Hence, more useful lower and upper bounds can be provided for the performance of the system.

Sensitivity Analysis of the Levelized Cost of Electricity for a Particle-Based CSP System

2021 ◽  
Author(s):  
Luis F. González-Portillo ◽  
Kevin J. Albrecht ◽  
Jeremy Sment ◽  
Brantley Mills ◽  
Clifford K. Ho
Keyword(s):  
Sensitivity Analysis ◽  
Heat Exchanger ◽  
Upper Bounds ◽  
Cumulative Distribution ◽  
Wind Effect ◽  
Lower And Upper Bounds ◽  
Levelized Cost Of Electricity ◽  
Receiver Model ◽  
Tower Height ◽  
And Storage

Abstract This study presents a sensitivity analysis of the LCOE for a particle-based system with the costs of the most current components. New models for the primary heat exchanger, thermal energy storage and tower are presented and used to establish lower and upper bounds for these three components. The rest of component costs such as particle cost, cavity cost, lift cost and balance of power are set to lower and upper bounds estimating a 25% of uncertainty. Some relevant parameters such as lift efficiency and storage thermal resistance are also included in the analysis with a 25% uncertainty. This study also includes an upgrade to the receiver model by including the wind effect in the efficiency, which was not included in previous publications. A parametric analysis shows the optimum values of solar multiple, storage hours, tower height and concentration ratio, and a probabilistic analysis provides a cumulative distribution function for a range of LCOE values. The results show that the LCOE could be below $0.06/kWh with a probability of 90%, where the highest uncertainty is on the primary heat exchanger cost.

scholarly journals A Sensitivity Analysis of Train Speed and its Effect on Railway Capacity

2014 ◽  
Vol 1061-1062 ◽  
pp. 1208-1212
Author(s):  
Bayan Bevrani ◽  
Robert Burdett ◽  
Prasad K.D.V. Yarlagadda
Keyword(s):  
Sensitivity Analysis ◽  
Cost Effective ◽  
Railway Network ◽  
Capacity Model ◽  
The Future ◽  
Railway System ◽  
Train Speed ◽  
The Absolute ◽  
Railway Capacity

Increasing train speeds is conceptually a simple and straight forward method to expand railway capacity, for example in comparison to other more extensive and elaborate alternatives. In this article an analytical capacity model has been investigated as a means of performing a sensitivity analysis of train speeds. The results of this sensitivity analysis can help improve the operation of this railway system and to help it cope with additional demands in the future. To test our approach a case study of the Rah Ahane Iran (RAI) national railway network has been selected. The absolute capacity levels for this railway network have been determined and the analysis shows that increasing trains speeds may not be entirely cost effective in all circumstances.

Small-amplitude supersolitons near supercritical plasma compositions

2017 ◽  
Vol 83 (4) ◽  
Author(s):  
Carel P. Olivier ◽  
Frank Verheest ◽  
Shimul K. Maharaj
Keyword(s):  
Electrostatic Potential ◽  
Taylor Series ◽  
Small Amplitude ◽  
Fluid Model ◽  
Taylor Series Expansion ◽  
Upper Bounds ◽  
Lower And Upper Bounds ◽  
Sagdeev Potential ◽  
Acoustic Speed

Supercritical plasma compositions in parameter space are considered for a general fluid model consisting of an arbitrary number of species. This is done by applying a Taylor series expansion of the Sagdeev potential about the acoustic speed and the equilibrium electrostatic potential. A novel finding in this study is the description of small-amplitude supersolitons. Our analysis allows us to determine the plasma compositional criteria for such structures, as well as lower and upper bounds of their velocities and amplitudes. We therefore establish an interesting link between supercritical plasma compositions and the existence of supersolitons. The results are illustrated via a case study where plasmas consisting of cold ions and two Boltzmann electron species are considered.

scholarly journals Estimation of Link Choice Probabilities Using Monte Carlo Simulation and Maximum Likelihood Estimation Method

2019 ◽  
Author(s):  
Mundher Ali Seger ◽  
Lajos Kisgyörgy
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Maximum Likelihood ◽  
Gaussian Process ◽  
Traffic Flow ◽  
Travel Demand ◽  
Choice Probabilities ◽  
Choice Set

Studying the uncertainty of traffic flow takes significant importance for the transport planners because of the variation and fluctuation of temporal traffic flow on all links of the transport network. Uncertainty analysis of traffic flow requires identifying and characterizing two sets of parameters. The first set is the link choice set, which involves the Origin-Destination pairs using this link. The second set is the link choice probabilities set, which includes proportions of the travel demand for the Origin-Destination pairs in the link choice set. For this study, we developed a new methodology based on Monte Carlo simulation for link choice set and link choice probabilities in the context of route choice modeling. This methodology consists of two algorithms: In the first algorithm, we used the sensitivity analysis technique the variance-based method to identify the set of Origin-Destination pairs in each link. In the second algorithm, we used a Gaussian process based on the Maximum Likelihood framework to estimate the link choice probabilities. Furthermore, we applied the proposed methodology in a case study over multiple scenarios representing different traffic flow conditions. The results of this case study show high precision results with low errors' variances.The key contributions of this paper: First, the link choice set can be detected by using sensitivity analysis. Second, the link choice probabilities can be determined by solving an optimization problem in the Maximum likelihood framework. Finally, the prediction errors' parameters of traffic assignment model can be modeled as a Gaussian process.

Sensitivity Analysis of the Levelized Cost of Electricity for a Particle-Based CSP System

2021 ◽  
pp. 1-19
Author(s):  
Luis F. González Portillo ◽  
Kevin Albrecht ◽  
Clifford K. Ho ◽  
Jeremy Sment ◽  
Brantley Mills
Keyword(s):  
Sensitivity Analysis ◽  
Heat Exchanger ◽  
Upper Bounds ◽  
Cumulative Distribution ◽  
Wind Effect ◽  
Lower And Upper Bounds ◽  
Levelized Cost Of Electricity ◽  
Receiver Model ◽  
Tower Height ◽  
And Storage

Abstract This study presents a sensitivity analysis of the LCOE for a particle-based system with the costs of the most current components. New models for the primary heat exchanger, thermal energy storage and tower are presented and used to establish lower and upper bounds for these three components. The rest of component costs such as particle cost, cavity cost and lift cost are set to lower and upper bounds estimating an uncertainty between 25% and 50%. Other relevant parameters related to lift and storage performance are also included in the analysis with the same uncertainty. This study also includes an upgrade to the receiver model by including the wind effect in the efficiency, which was not included in previous publications and may have a big impact in the system design. A parametric analysis shows the optimum values of solar multiple, storage hours, tower height and concentration ratio, and a probabilistic analysis provides a cumulative distribution function for a range of LCOE values. The results show that the LCOE could be below $0.06/kWh with a probability of between 80% and 90%, where the costs of primary heat exchanger, particles and lifts have largest contribution to the variance of the LCOE.

scholarly journals Optimum design of a spur gear using a two level optimization approach

Mechanika ◽  
2019 ◽  
Vol 25 (4) ◽  
pp. 304-312
Author(s):  
MAHIDDINI Brahim
Keyword(s):  
Design Methodology ◽  
Optimization Technique ◽  
Spur Gear ◽  
Analytical Models ◽  
Design Parameters ◽  
Optimization Approach ◽  
Computational Burden ◽  
Speed Reducer ◽  
Basic Functions

In this paper, we present a two level optimization approach in order to enhance the design process of a one-stage speed reducer. The proposed design methodology is performed using genetic algorithms which are judiciously combined with the use of :i) analytical models (1stlevel) and ii) Finite Element Method (FEM)based models ( 2nd level), to evaluate design candidates. Indeed, the use of CAD-CAE tools to develop higher fidelity FEM models allows to re-evaluate the attained first level designs, while accounting for new design parameters and advanced aspects which have been ignored in the first level. In order to minimize the computational burden, a metamodel based optimization technique is adopted at this second level. To illustrate the efficiency of the proposed approach, a case study of a spur gear based reducer is presented where the design of experiments is built using Hypercube Latin Sampling and surrogate models are constructed using Radial Basic Functions.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

Traffic Flow Management Impact on Delay and Fuel Consumption: an Atlanta Case Study

2012 ◽  
Vol 20 (3) ◽  
pp. 203-224 ◽  
Author(s):  
Shon R. Grabbe ◽  
Banavar Sridhar ◽  
Avijit Mukherjee ◽  
Alexander Morando
Keyword(s):  
Fuel Consumption ◽  
Traffic Flow ◽  
Flow Management ◽  
Traffic Flow Management

Energy of spherical fuzzy graphs

2020 ◽  
pp. 321-332
Author(s):  
S. Yahya Mohamed ◽  
A. Mohamed Ali
Keyword(s):  
Adjacency Matrix ◽  
Upper Bounds ◽  
Fuzzy Graph ◽  
Lower And Upper Bounds ◽  
Fuzzy Graphs

In this paper, the notion of energy extended to spherical fuzzy graph. The adjacency matrix of a spherical fuzzy graph is defined and we compute the energy of a spherical fuzzy graph as the sum of absolute values of eigenvalues of the adjacency matrix of the spherical fuzzy graph. Also, the lower and upper bounds for the energy of spherical fuzzy graphs are obtained.

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