Variations In Input Parameters Research Articles

Achieving higher taxi outflows from a drop-off lane: A simulation-based study

Lanes used by taxis and other shared-ride vehicles at airports and rail terminals are often congested. The present paper examines congestion-mitigating strategies for a special type of lane inside of which taxis are prohibited from overtaking each other while dropping-off patrons. Taxis must therefore often wait in first-in-first-out (FIFO) queues that form in the lane during busy periods. Patrons may be discharged from taxis upon reaching a desired area near the terminal entrance. When wait times grow long, however, some taxis discharge their patrons in advance of that desired area.The Nanjing South Railway Station in China is selected as a case study. Its FIFO drop-off lane is presently managed by police officers who allow taxis to enter the lane in batched fashion. Inefficiencies are observed because curb space near the upstream and downstream ends of the lane often goes unused.A microscopic simulation model is developed in-house, and is painstakingly calibrated to data measured in the study site’s FIFO lane. Simulation experiments indicate that rescinding the lane’s present batching strategy can increase taxi outflow by more than 25%. Further experiments show that even greater gains can be achieved by requiring taxis to discharge patrons when forced by downstream queues to stop a prescribed distance in advance of a desired drop-off area. Further gains were predicted by requiring the lead taxi in each batch to discharge its patron(s) only after travelling a prescribed distance beyond a desired location. The above findings are confirmed for scenarios calibrated with field data collected on two different days, and for hypothetical scenarios with varying input parameters. Roles that technology can play in implementing these new lane-management strategies are discussed. So are their practical implications in light of the present boom in shared-ride services.

Parametric Analysis of a Plain-Fin Compact Heat Exchanger for a Small-Scale Gas Turbine

The influence of the thermal parameters of a Plain-Fin Compact Heat Exchanger on its performance is examined in this paper. The objective of this work is to analyse the effect of the different flow and geometric parameters on the output performance of a plain fin compact heat exchanger (PFCHE) designed to be used on a small-scale gas turbine and how these parameters can be used for the optimisation of PFCHEs.In this work, we examined the effects of the variation of input parameters of a plain-fin compact heat exchanger (fin length, fin height, fin thickness, mass flow rate of air and turbine exhaust gas) on the output performance of the heat exchanger (Overall heat exchanger efficiency, fin heat transfer efficiency and the outlet temperatures). The analytical expressions for the outlet temperatures and heat exchanger efficiencies were derived and analysed. Then the derived model was designed and simulated using CFD codes. Also, from the derived expressions, the performance model of the heat exchanger was programmed for analysis. From the results, it shows that the effectiveness (e-value), fin length, fin height and mass flow rates of the gases influence performance of a plain-fin compact heat exchanger. A 50% reduction in fin height can cause as much as an 18% increase in the fin efficiency of the heat exchanger. While a 50% increase in the effectiveness value can cause as much as a 40% increase in the outlet temperature.

Вариационные алгоритмы идентификации мощности импульсного источника загрязнения в модели переноса примеси

To solve the problems of monitoring the environmental situation it is necessary to create computer systems that allow assessing the state of the environment. Such systems should allow for rapid assessment of the effects of pollution in the areas under investigation, especially in the areas of traditional shipping lanes and intensive construction of various communications. To solve such problems, it is necessary to have mathematical models and methods for solving inverse problems, when the input parameters of the model are determined using the measurement data due to their rapid assimilation. Variational algorithms for assimilation of incoming information are based on iterative minimization of the quadratic prediction quality function that characterizes deviations of the solution obtained from the used model from the measurement data. In this case, the mathematical model is a constraint on the variation of input parameters while minimizing the forecast quality functional. In this paper we propose the use of such procedures for the assimilation of data distributed in space and time. Based on the passive impurity transfer model, various approaches are considered to solve the problem of identifying the power of a point instantaneous source of pollution from time and space distributed measurement data. In this paper, we consider a variational method for identifying the power of a point instantaneous source of pollution based on solving adjoint  problems and the problem in variations. The proposed algorithm is obtained for the case when the measurement data is received at different times. In addition, the method of estimation and the variational method of filtering linear systems of equations are considered for searching for the required values. The initial values of the power of the pollution source are determined in the result of solving the redefined system of equations. The result obtained is consistent with all available information about the impurity concentration. The considered algorithms for identifying the power of the pollution source in relation to the passive impurity transfer model can be used to solve various environmental problems when studying the impact of anthropogenic pollution sources.

Formalization of the waste management task in Ukraine for ensuring the environmental stability of Eastern Europe

The article outlines the current problems and contradictions in the waste management system in Ukraine from the standpoint of ensuring the ecological stability of the Eastern European region. The accepted paradigm of creating a recirculating economy is provided by a territorially balanced waste management system in the regions of Ukraine. The coefficient of territorial provision of utilization capacities has been proposed and tested, which allowed the evaluation of their existing potential integrally, and determined the formed regional disproportions between waste generation and utilization. In order to solve the existing imbalances in Ukraine in a comprehensive way, the stage of transition to recirculating recycling technologies of waste is proposed. The mathematical formalization of the problem of waste management in Ukraine specifies the space-time parameters of solving the problem of the system balance and provides the variability of input and output parameters for solving empirical problems.

Addressing Ambiguities in Constrained Sensitivity Analysis for Reactor Physics Problems

This paper presents an algorithm for completing sensitivity analysis that respects linear constraints placed on the associated model’s input parameters. Any sensitivity analysis (linear or nonlinear, local or global) focuses on measuring the impact of input parameter variations on model responses of interest, which may require the analyst to execute the model numerous times with different model parameter perturbations. With the constraints present, the degrees of freedom available for input parameter variations are reduced, and hence any analysis that changes model parameters must respect these constraints. Focusing here on linear constraints, earlier work has shown that constraints may be respected in many ways, causing ambiguities, i.e., nonuniqueness, in the results of a sensitivity analysis, forcing the analyst to introduce dependencies with downstream analyses, e.g., uncertainty quantification, that employ the sensitivity analysis results. This paper develops the theoretical details for a new algorithm to select model parameter variations that automatically satisfy linear constraints resulting in unique results for the sensitivity analysis, thereby removing any custom dependencies with downstream analyses. To demonstrate the performance of the algorithm, it is applied to solve the multigroup eigenvalue problem for the multiplication factor in a representative CANDU core-wide model. The model parameters analyzed are the group prompt neutron fractions, whose summation must be equal to one over all energy groups. The results indicate that the new algorithm identifies the gradient direction uniquely which represents the direction of maximum change while satisfying the constraints, thus removing any ambiguities resulting from the constraints as identified by earlier work.

Dispatch strategies based performance analysis of a hybrid renewable energy system for a remote rural area in India

A significant Indian population lives in villages and some live in remote areas disconnected from the grid connectivity. Extension of grid connection to provide power supply to these villages is not feasible, but stand-alone hybrid renewable energy system may be a feasible option. In this perspective, dispatch strategy based performance analysis has been carried out to provide power supply using the hybrid renewable energy system for a remote rural area in the state of Karnataka (India). The effect of load following, cycle charging and combined dispatch strategies on Lead Acid and Lithium-Ion batteries with Photovoltaic/Hydro/Battery and Photovoltaic/Wind/Hydro/Diesel Generator/Battery configurations has been studied using Hybrid Optimization Model for Electric Renewable (HOMER Pro®). The feasible Cost of Energy and Net Present Cost obtained for the proposed hybrid system are found in the range of 0.1 $/kWh – 0.162 $/kWh, $4,65,790 – $7,16,658 under the proposed dispatch strategies. The Cost of Energy and Net Present Cost of Lithium-Ion battery based system are found to be 30% and 35% lesser than Lead Acid battery based system. Using Lithium-Ion batteries, the Cost of Energy is reduced by 34%, 25% and 37% under Load Following, Cycle Charging and Combined Dispatch strategies. From the results obtained, it is found that under Combined Dispatch strategy, Lithium-Ion battery based hybrid renewable energy system delivers the most optimal operational costs. The study is also extended to perform sensitivity analysis on varying input parameters such as discount rate, Photovoltaic cost, battery cost, fuel cost, wind speed and design flow rate. Variation of discount rate and fuel cost affect the Cost of Energy and Net Present Cost significantly.

Parametric uncertainty quantification in natural frequency of sandwich plates using polynomial neural network

In this paper, uncertainty quantification in natural frequencies for laminated soft core sandwich plates is presented by employing finite element (FE) coupled polynomial neural network (PNN) approach. The computational efficiency and accuracy is achieved by using PNN as surrogate model. Latin hypercube sampling method is employed for training of data in PNN model. The stochastic first three natural frequencies of sandwich plates are studied for individual variation in input parameters. The stochasticity in individual input parameters are considered in order to assess their influence on global response of the structure. The algorithm discussed in this article is observed to be converging with the previously published literature (for deterministic case) and validated with full scale Monte Carlo simulation (MCS) i.e. original finite element approach (for stochastic case). The computational time and cost reduced significantly by employing the present surrogate based FE approach compared to that of conventional Monte Carlo simulation approach.

The Effect of the Variation of Input Parameters on the Onset of Corrosion of the Bridge Deck Exposed to Chlorides Considering Selected Reinforcement Protection

The contribution focuses on the effect of selected input parameters on probabilistic estimation of chloride induced reinforced concrete bridge deck corrosion initiation. The reinforced concrete bridge deck with steel protected by epoxy-coating is considered. A finite element diffusion model in conjunction with a probabilistic method using Monte Carlo technique is used to address the inherited randomness of input variables. Presented parametric study shows the sensitivity of estimation of the corrosion initiation likelihood on variation of input parameters.

Efficient computational modelling of low loaded bearings of turbocharger rotors

The overall efficiency of turbochargers is a strictly monitored variable in all applications. Increasing the overall efficiency is closely related to the mechanical efficiency and hence the rotor bearing system. This paper presents a new computational model describing the behaviour of the thrust bearings of the turbocharger rotor under different operating conditions. The model assumes steady state turbulent flow of lubricant through a thin lubrication gap in the form of a two-phase fluid. Fluid flow is affected by centrifugal forces due to high rotor speeds and by the change in lubricant properties due to pressure, temperature and shear rate. The model is designed to allow a very fast and efficient steady state solution for many input parameter variations, while maintaining a sustainable physical depth of description of the reality. The new computational model is confronted with three-dimensional higher-level models and verified by technical experiments on a real combustion engine turbocharger.

Assessment of the direct economic losses associated with hydatid disease (Echinococcus granulosus sensu stricto) in beef cattle slaughtered at an Australian abattoir

Bovine hydatid disease, characterised by fluid-filled hydatid cysts, is regularly found in the offal of beef cattle at slaughter. Organs found to be infected at slaughter are removed to preclude them from entering the human food chain. The organs are either downgraded to pet food or condemned. Previous studies have focussed on total economic losses, but have not calculated the cost of disease per animal, which would be useful information for producers when determining how best to manage hydatid disease. This study estimated the direct losses associated with hydatid disease in beef cattle slaughtered at an Australian beef abattoir both at the population (all cattle slaughtered) and individual animal level.Data on annual prevalence of hydatid disease in beef cattle were obtained from an Australian abattoir for the years 2011–2017. The direct losses resulting from the condemnation and downgrading of offal infected with hydatid cysts at the abattoir were estimated using data stratified by age, sex and feed-type. Official and literature-based sources of organ weight and price were used to estimate direct losses associated with hydatid disease in beef cattle slaughtered at the abattoir. Uncertainty and variability in input parameters were represented using uniform distributions and Monte Carlo sampling was used to model output parameter uncertainty.Out of 1,097,958 beef cattle slaughtered between January 2011 and December 2017, 97,832 (8.9%) were reported infected with hydatid disease. The median estimated direct loss to the abattoir for the duration of the study period was AU$655,560 (95% confidence interval [CI] AU$544,366–787,235). This equated to approximately AU$6.70 (95% CI AU$5.56–8.05) lost per infected animal. The annual median estimated direct losses due to hydatid disease at the abattoir were AU$93,651 (95% CI AU$77,767–112,462). Direct losses varied each year of the study and ranged from AU$38,683 in 2016 to AU$163,006 in 2014.This estimate of the direct losses associated with bovine hydatid disease most likely underestimates the true extent of the overall losses because indirect losses such as reduced carcass weights were not estimated in this study. Nevertheless, these estimates illustrate the negative economic impact of bovine hydatid disease and demonstrate that improved surveillance to enable control of hydatid disease should be considered both in Australia and globally. It would be worthwhile to estimate the losses in other beef abattoirs for the same time period to compare results, and to investigate the cost-benefit of control programs for bovine hydatid disease.

Probabilistic slope stability analysis in Kahrizak landfill: effect of spatial variation of MSW’s geotechnical properties

The geotechnical properties of municipal solid waste (MSW) in landfills vary considerably depending on the composition, time, and the rate of waste density. This variability in geotechnical properties leads to many uncertainties in the analysis of landfill slope stability. This study, using probabilistic methods investigates the slope stability and the probability of failure of a Kahrizak landfill under the conditions of spatial variability of physical and geotechnical properties of MSW. To achieve this goal, the random field theory has been used with a finite difference numerical method in the framework of the Monte Carlo simulation. MSW’s shear strength parameters such as cohesion and friction angle as well as the unit weight of layers are considered as random variables. An extensive literature review was conducted to address the probable variation of above-mentioned parameters in Kahrizak landfill. The results of several different laboratory researches on MSW samples collected from Kahrizak landfill were also employed in the modelings. Output results are presented in the form of probability distributions of the factor of safety as well as the probability of failure corresponding to these distributions. Moreover, the effect of various parameters such as coefficient of variation and correlation distance of input parameters on these output results has been investigated. The results show that considering the spatial variability in probabilistic methods would help to determine the various mechanisms affecting the performance and the probability of failure of the landfill slope. In addition, the output of such probabilistic analyses can be used as guidance for engineers to design safe and reliable landfill.

Modeling of surface roughness in abrasive water jet machining of AZ91 magnesium alloy using Fuzzy logic and Regression analysis

Surface irregularity of machined parts is one of the major machining characteristics that play an important role in determining the quality of engineering components. Abrasive water jet cutting has been proven to be an effective technology for processing various engineering materials. This work deals with the abrasive water jet machining of magnesium alloy (AZ 91). The abrasive water jet experiment was designed using response surface methodology (RSM). Surface roughness was measured on the machined magnesium alloy. Three variable input parameters such as water pressure (WP), Traverse speed (TS), and Stand-off distance (SOD) were selected as process parameters. Surface roughness was predicted fuzzy logic. Regression equation was used for predicting the SR value. From this investigation, it was observed that maximum pressure and minimum stand-off distance caused reduction in the surface roughness in the abrasive water jet machining of AZ91 magnesium alloy. Further, the developed fuzzy model was used to validate the results and it was found that the predicted values were in good agreement with a 95% confidence level. It was also evident that the fuzzy technique is helpful for better prediction of the experimental.

Radiological safety analysis of Rooppur Nuclear Power Plant site using atmospheric dispersion model

The purpose of this work is to estimate dose received in case of release of radionuclide into the atmosphere from the under-construction Rooppur Nuclear power plant (NPP) due to a hypothetical accident with the help of an atmospheric dispersion model. A generic source term code has also been developed using MATLAB by following NUREG-1228. The sensitivity analysis is based on variation of the received total effective dose equivalent (TEDE) corresponding to the variation of the uncertain input parameters. The sensitivity was seen to be higher at stable conditions with the change of high wind speed. Estimated TEDE dose results for Xe-133 at different downwind distances from Rooppur NPP site in different atmospheric stability classes. The maximum TEDE of 6.40E-06 Sv was estimated at maximum distance of 0.7 km from the site for stability class A, whereas, in case of unstable stability class B, it was 5.70E-05.

Radiological safety analysis of Rooppur Nuclear Power Plant site using atmospheric dispersion model

The purpose of this work is to estimate dose received in case of release of radionuclide into the atmosphere from the under-construction Rooppur Nuclear power plant (NPP) due to a hypothetical accident with the help of an atmospheric dispersion model. A generic source term code has also been developed using MATLAB by following NUREG-1228. The sensitivity analysis is based on variation of the received total effective dose equivalent (TEDE) corresponding to the variation of the uncertain input parameters. The sensitivity was seen to be higher at stable conditions with the change of high wind speed. Estimated TEDE dose results for Xe-133 at different downwind distances from Rooppur NPP site in different atmospheric stability classes. The maximum TEDE of 6.40E-06 Sv was estimated at maximum distance of 0.7 km from the site for stability class A, whereas, in case of unstable stability class B, it was 5.70E-05.

Surface morphology investigation of miniature gears manufactured by abrasive water jet machining

In this paper, surface morphology investigation of miniature spur gears manufactured by abrasive water jet machining is discussed. Water jet pressure, abrasive flow rate and stand-off-distance are the varying input parameters to study the surface morphology (surface roughness and topography) of the machined gears. From the investigation, the water jet pressure has highly influenced (with 47% contribution) the surface quality and found as a predominant process parameter. SEM micrograph study found that wear scars and clinging effects are the major surface defects found over the machined surfaces of the gear teeth. Maximum and minimum peaks of the wear tracks are observed with white light spectroscope. The best surface morphology with average surface roughness value 1.08 μm was achieved at 350 MPa water jet pressure, 225 g/min abrasive mass flow rate, and 1mm stand-off distance. The present work identifies the potential of AWJM process for manufacturing of high quality miniature gears.

Microstructural analysis of friction stir welded Mg AZ31 alloy

Magnesium alloys are the lightest of all structural metals and are in great demand in various automotive and aerospace industry. The current research work focusses on evaluating the effects of input process parameters on the metallurgical properties of friction stir welded magnesium alloys. The variable input parameters chosen are tool rpm, travel speed and the plunge depth. Microstructural studies revealed three distinct zones in the welded specimen, viz: stir zone also known as the weld nugget, thermo mechanical affected zone and the unaffected base material. Large sized grains were observed at the top surface of the welded specimens due to more heat input at the top. The microhardness of the workpiece was measured in the traverse direction and maximum hardness observed in the stir zone is about 16% higher than the parent material.

Decentralized rainwater harvesting program for rural cities considering tax incentive schemes under stakeholder interests and purchasing power restrictions

Abstract This paper focuses on implementing a decentralized rainwater harvesting (DRH) program for rural cities under stakeholder interests and purchasing power restrictions. The study is conducted by considering: (1) a no tax incentive scheme (NTIS); (2) a flat rate tax incentive scheme (FTIS); and (3) a progressive tax incentive scheme (PTIS). A three-stage decision framework is proposed. In the first stage, a water balance simulation model is developed to estimate the amount of rainwater that can be collected at individual households using different capacity rain barrels and to determine the threshold rain barrel capacity. In the second stage, the water balance simulation model is run multiple times with varying input parameters to obtain the probability distributions for rainwater used and water demand for different households using different capacity rain barrels, which are then used to generate scenarios for the third stage optimization model. In the third stage, a multi-objective stochastic mixed integer linear programming (Mo-SMILP) model is proposed that aims to determine the household participation rate and cumulative city-wide DRH capacity considering tax incentive schemes, stakeholder interests, and purchasing power restrictions. The proposed Mo-SMILP model is solved by using an improved augmented epsilon constraint method (AUGMECON 2) in order to understand the trade-off between city-wide household reliability, city-wide household savings, and city government savings. A case study of a small rural city in the State of Texas in the US is used to illustrate the effectiveness of the proposed decision framework. The results shows a significant decrease in city-wide household reliability when stakeholder interests and purchasing power are considered. In addition, the PTIS is best at improving city-wide household reliability and savings. NTIS and FTIS are best at improving city government savings depending on the household preference for reliability and savings.

Sensitivity of Thermoelectric Properties from the EPA Method and Its Variants on Variations in Phonon Frequencies

The electron–phonon coupling phenomenon is an important scattering source of charge carriers in thermoelectric materials. As the result, consideration of the scattering mechanism due to electron–phonon coupling is an essential part of the first-principles prediction methods for thermoelectric properties of materials, i.e., the Seebeck coefficient and electrical conductivity. However, a direct, high-resolution treatment of electron–phonon coupling in a realistic situation is too expensive for practical purposes, and approximation methods have been developed for the phenomena at a reasonable level of computational cost. The electron–phonon averaged (EPA) method and its variants have been recently introduced as such approximation methods. These methods comprise two major approximations. First, the electron–phonon coupling matrix elements, which are explicitly dependent on the momentum of charge carriers and that of scattering phonons, are approximated as a function of two energies only, i.e., the energy of the incoming charge carrier before scattering and that of the outgoing charge carrier after scattering. Second, the phonon frequencies in the formula of scattering rate are replaced with their averages in the Brillouin zone. Although these methods have achieved remarkable successes in predicting thermoelectric properties of materials, uncertainty introduced by these approximations and sensitivity of the results to variations of input parameters in these approximations have not been assessed completely. In this study, the uncertainty and sensitivity of thermoelectric properties, predicted with the EPA method and its variants, on variations in phonon frequencies are investigated. A thermoelectric p-type half-Heusler compound, HfCoSb, is used as an example. An empirical bootstrap method is employed to assess the impact of sampled phonon frequencies during the averaging process, whose results show that the impact of variations in phonon frequencies induces a minor but detectable change in predicted thermoelectric properties.

Spatial variability modeling and reliability analysis of flexible pavement through mechanistic–empirical model

Purpose The present study aims to demonstrate the performance assessment of flexible pavement structure in probabilistic framework with due consideration of spatial variability modeling of input parameter. Design/methodology/approach The analysis incorporates mechanistic–empirical approach in which numerical analysis with spatial variability modeling of input parameters, Monte Carlo simulations (MCS) and First Order Reliability Method (FORM) are combined together for the reliability analysis of the flexible pavement. Random field concept along with Cholesky decomposition technique is used for the spatial variability modeling of the input parameter and implemented in commercially available finite difference code FLAC for the numerical analysis of pavement structure. Findings Results of the reliability analysis, with spatial variability modeling of input parameter, are compared with the corresponding results obtained without considering spatial variability of parameters. Analyzing a particular three-layered flexible pavement structure, it is demonstrated that spatial variability modeling of input parameter provides more realistic treatment to property variations in space and influences the response of the pavement structure, as well as its performance assessment. Originality/value Research is based on reliability analysis approach, which can also be used in decision-making for quality control and flexible pavement design in a given environment of uncertainty and extent of spatially varying input parameters in a space.

Cost-effectiveness of insulin degludec versus insulin glargine U100 in adults with type 1 and type 2 diabetes mellitus in Bulgaria

BackgroundThis analysis evaluates the cost-effectiveness of insulin degludec (degludec) versus biosimilar insulin glargine U100 (glargine U100) in patients with type 1 (T1DM) and type 2 diabetes mellitus (T2DM) in Bulgaria.MethodsA simple, short-term model was used to compare the treatment costs and outcomes associated with hypoglycaemic events with degludec versus glargine U100 in patients with T1DM and T2DM from the perspective of the Bulgarian National Health Insurance Fund. Cost-effectiveness was analysed over a 1-year time horizon using data from clinical trials. The incremental cost-effectiveness ratio (ICER) was the main outcome measure.ResultsIn Bulgaria, degludec was highly cost-effective versus glargine U100 in people with T1DM and T2DM. The ICERs were estimated to be 4493.68 BGN/quality-adjusted life year (QALY) in T1DM, 399.11 BGN/QALY in T2DM on basal oral therapy (T2DMBOT) and 7365.22 BGN/QALY in T2DM on basal bolus therapy (T2DMB/B), which are below the cost-effectiveness threshold of 39,619 BGN in Bulgaria. Degludec was associated with higher insulin costs in all three patient groups; however, savings from a reduction in hypoglycaemic events with degludec versus glargine U100 partially offset these costs. Sensitivity analysis demonstrated that the results were robust and largely insensitive to variations in input parameters. At a willingness-to-pay threshold of 39,619 BGN/QALY, the probability of degludec being cost-effective versus glargine U100 was 60.0% in T1DM, 99.4% in T2DMBOT and 91.3% in T2DMB/B.ConclusionDegludec is a cost-effective alternative to biosimilar glargine U100 for patients with T1DM and T2DM in Bulgaria. Degludec could be of particular benefit to those patients suffering recurrent hypoglycaemia and those who require additional flexibility in the dosing of insulin.