Pay Factor Analysis for Highway Pavements through Percentage of Material within Specification Limits and Monte Carlo Simulation

2021 ◽  
pp. 036119812110255
Author(s):  
Yunpeng Zhao ◽  
Dimitrios Goulias
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Operating Characteristic ◽  
Production Quality ◽  
Specification Limits ◽  
State Highway ◽  
Long Run ◽  
Similar Materials ◽  
Pay Factor ◽  
State Highway Agencies

Many state highway agencies (SHAs) have adopted pay adjustment provisions in their acceptance plans for construction and materials. In these payment adjustment acceptance plans, the percentage of material within specification limits (PWL) has been selected as the quality measure to relate production quality to pay factors, and pay equations are used to determine a pay factor for a lot based on PWL. Various pay equations have been proposed by the highway community for adoption in SHAs’ specifications. However, the effectiveness of these pay equations has not been fully evaluated. Another issue concerning the pay adjustment acceptance plans is the risk associated with single and multiple pay factors. The purpose of this study was to evaluate the effects of different pay equations commonly used by SHAs and the risks associated with pay adjustment acceptance plans. This was achieved by developing operating characteristic curves associated with various pay factors and expected pay curves and Monte Carlo simulation for assessing the effects in the long run. The methodology suggested in this paper is transferable elsewhere where similar materials and specifications are used for the acceptance of pavements.

Evaluation of Acceptance Risks through Percent within Limit for Highway Materials and Pavement Construction

2021 ◽  
pp. 036119812110064
Author(s):  
Yunpeng Zhao ◽  
Dimitrios Goulias
Keyword(s):  
Construction Industry ◽  
Operating Characteristic ◽  
Production Quality ◽  
Type I ◽  
Associated Production ◽  
State Highway ◽  
Pavement Construction ◽  
High Level ◽  
State Highway Agencies ◽  
Type Ii Errors

The majority of State Highway Agencies now employ statistical-based specifications for the acceptance of highway materials and pavement construction. The parameters of these statistical acceptance plans are specified based on engineering judgment and may result in a high level of risk to both the agency and contractor. To appropriately apply such specifications to the pavement construction industry, the associated production quality (i.e., materials and construction variability) must be well understood by all parties involved, and its potential effects need to be assessed. To address this, the objective of this study is to quantify the risks to the agencies and contractors (i.e., Type I and Type II errors) associated with the use of both single and multiple acceptance quality characteristics through constructing operating characteristic curves. It is also the purpose of this study to provide guidelines to properly implement the key components of an acceptance plan and its associated statistics. The methodology and findings identified in this study can be applied elsewhere to evaluate the acceptance plans and the associated risks related to highway materials and pavement construction.

Testing for bubbles in housing markets: some evidence for Brazil

2018 ◽  
Vol 11 (5) ◽  
pp. 754-770 ◽  
Author(s):  
Cássio da Nóbrega Besarria ◽  
Nelson Leitão Paes ◽  
Marcelo Eduardo Alves Silva
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Housing Prices ◽  
Market Price ◽  
Housing Markets ◽  
Cointegration Analysis ◽  
Small Samples ◽  
Content Type ◽  
Long Run ◽  
Cointegration Tests

Purpose Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil. Design/methodology/approach Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary. Findings The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results. Research limitations/implications The results obtained from the cointegration analysis can be biased for small samples. Practical implications The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents. Social implications These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil. Originality/value The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.

Condition-Based Maintenance Policy under Imperfect Inspection Using Monte-Carlo Simulation

2012 ◽  
Vol 201-202 ◽  
pp. 955-958
Author(s):  
En Shun Ge ◽  
Qing Min Li ◽  
Guang Yu Zhang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Preventive Maintenance ◽  
Condition Based Maintenance ◽  
Gamma Process ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Numerical Example ◽  
Long Run

Condition-based Maintenance (CBM), which can efficiently improve the performance of the deteriorating system, would be influenced by imperfect inspection in practice. Aiming at this problem, a new CBM model under imperfect inspection is presented for deteriorating system, which described by Gamma process. The system is inspected periodically, and a preventive maintenance is performed if the degradation level exceeds a threhold. The inspection is imperfect, that means the measurements contain errors, and the CBM model should take these measure errors into account. The algorithm is shown to estimate the long run cost rate using Monte-Carlo method. Through numerical example, the influence of mesurement error over long run cost is analyzed. Therefore, the correctness and rationality of the model are proved.

Optimization of Condition-Based Maintenance Policy for Deteriorating System Based on Monte-Carlo Simulation

2012 ◽  
Vol 544 ◽  
pp. 44-48 ◽  
Author(s):  
En Shun Ge ◽  
Qing Min Li ◽  
Ao Lin Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Preventive Maintenance ◽  
Threshold Value ◽  
Condition Based Maintenance ◽  
System State ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Model And Simulation ◽  
Long Run

Condition-based Maintenance (CBM) can not only efficiently improve the performance of deteriorating system but also guarantee the system operation safety. This paper assumes that the system state is periodically inspected, and a preventive maintenance is performed if the degradation level exceeds a threshold. The effect of maintenance is imperfect, which means that maintenance can restore the system state to somewhere between as good as new and as bad as old. The algorithm is presented to get the solution of long run cost based on Monte-Carlo simulation, and the joint optimization of inspection rate, the threshold value and the number of preventive maintenance activities is investigated for the minimization of long run cost rate. A case study is given to show the procedure of the maintenance model and simulation. Therefore, the correctness and rationality of the model are proved.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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