scholarly journals Accurate definition of control strategies using cross validated stepwise regression and Monte Carlo simulation

2019 ◽  
Vol 2 ◽  
pp. 100006
Author(s):  
Patrick Y. Yang ◽  
Cerintha J. Hui ◽  
Daniel J. Tien ◽  
Andrew W. Snowden ◽  
Gayle E. Derfus ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stepwise Regression ◽  
Control Strategies ◽  
Accurate Definition ◽  
Definition Of

Deriving Proven Oil Reserves Comments on the Monte Carlo Simulation Procedure

1993 ◽  
Vol 11 (1) ◽  
pp. 62-65
Author(s):  
Mark Wallace
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Basic Principles ◽  
Oil Reserves ◽  
Confidence Levels ◽  
Simulation Procedure ◽  
Probabilistic Distribution ◽  
Reservoir Description ◽  
Definition Of

The definition of reserves categories is frequently related directly back to the probabilistic distribution of reserves in the field. Most developments are planned around the P50 or “most likely” expectation for the field a level which incorporates the Proven plus Probable categories. The Proven category is usually backed out from the resulting reserves distribution by assuming an arbitrary P90 or P80 value, similarly upside or the Reserves including the Possible category are allocated a P20 or P10 value. This approach provides an “accepted” range to the reserves but is essentially reliant upon applying a range to a set of deterministric parameters. This approach assumes the basic principles of reservoir description are correct and can be applied at all confidence levels (P90-P10). In complex reservoirs this is less of a valid assumption, and running deterministic cases using pessimistic and optimistic data interpretations is the realistic way to determine the reserves range for the field.

Systematic Vibration Reliability Analysis of Random Parametered Gear Sets With Analytic and Multi-Crossing Monte Carlo Simulation Methods

2017 ◽  
Author(s):  
Ma Yupeng ◽  
Zhang Jianguo ◽  
Qiu Jiwei
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Vibration Response ◽  
Reliability Estimation ◽  
Driven Systems ◽  
Vibration Responses ◽  
Vibration Reliability ◽  
Definition Of ◽  
Nonstationary Stochastic Processes

Vibration reliability analysis of gear sets considering various kinds of nonlinear random factors is essential for the safety of gear driven systems. In this paper, a rational definition of gear sets vibration reliability was presented at first by taking all kinds of vibration responses including displacement, velocity and acceleration into account uniformly by treating them as a series system with statistically independent components. According to the given definition, a systematic analyzing scheme for the vibration reliability of gear sets was proposed. Vibration reliability estimated via the analyzing scheme would make it conservative but more safely in design of gear driven systems. Subsequently, both analytic and numerical methods for gear sets vibration response reliability estimation were carried out based on the proposed analyzing scheme. The analytic method is suitable for the situations that the vibration responses of gears sets under random circumstances are stationary stochastic responses. While, the numerical method named Multi-crossing Monte Carlo Simulation (MULCMCS) can well solve the reliability estimating problems even when the vibration responses of gear sets are nonstationary stochastic processes. Finally, for illustration, a numerical case of analyzing the vibration response reliability of a single degree-of-freedom (DOF) gear set was given to demonstrate the effectiveness of the MULCMCS method.

Chemometrics and Monte-Carlo Simulation Assisted RP-LC Method for Estimation of Cinacalcet Hydro- chloride in Pharmaceutical Products

2021 ◽  
Vol 14 (2) ◽  
pp. 5436-5447
Author(s):  
Ravi Kumar Venkata Varaha Bera ◽  
Sagar Suman Panda
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Drug Product ◽  
Control Strategies ◽  
Scientific Information ◽  
Pharmaceutical Products ◽  
Method Performance ◽  
Pharmaceutical Dosage Form ◽  
Relative Standard ◽  
Cinacalcet Hydrochloride

Cinacalcet hydrochloride (CNT) is a novel calcimimetic agent widely used in the treatment of hyperparathy- roidism. For the first time, the authors utilized the novel concept of analytical procedure development employing several unique scientific tools for quantification CNT from its pharmaceutical dosage form. The objective behind the present work was to establish a scientifically sound and systematic work frame that overcomes the drawbacks of the earlier reported method for estimating CNT level in samples and ensuring superior method performance throughout the analytical life-cycle. In this  process, at first, the risky method variables were earmarked and were subjected to a response surface methodology, followed by Monte-Carlo simulation (MCS) based robust- ness-cum-optimization studies. The inclusion of the MCS approach assessed the method performance with no additional laboratory experimentation  and  established the innovative hyphenation's aptness with chemometrics tools. The control strategies were established based on analytical design space and method performance evaluation results by a simulative approach. The study revealed that methanol %, flow rate, and pH are the three critical method variables influencing analytical attributes: retention time, the number of plates, and tailing. The analytical conditions include a C18 column (150mm × 4.6mm, 5μm) with an isocratic mobile phase (80:20, % v/v) of methanol and 0.01M KH2PO4 buffer (pH maintained at 3.5 using orthophosphoric acid) flowing at 1.1ml/min. Diode array detection was performed at 282 nm. Method validation was befitting to federal needs as linearity (0.5-160 μg/ml), accuracy (>99%), and precision below 1% of relative standard deviation are indicative of method suitability for the purpose. In a nutshell, the present method describes a typical analytical workflow with the significant advantage of  obtaining  more excellent scientific information with less systematized experimentation. It was found suitable for routine quality control of CNT in drug substance and drug product.

A generalized Monte Carlo simulation model for decision risk analysis illustrated with a Dutch elm disease control example

1981 ◽  
Vol 11 (2) ◽  
pp. 343-351
Author(s):  
David R. Betters ◽  
James C. Schaefer
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Control Strategies ◽  
Basic Structure ◽  
Probability Density Functions ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Dutch Elm Disease ◽  
Monte Carlo Simulation Model

Decision making is often performed under conditions of uncertainty and risk. A Monte Carlo simulation model is described which can help analyze alternatives where these conditions exist. The simulation model has a generalized format so that it may be easily applied to a number of different situations. The basic structure of the simulation model is discussed, and then the model is applied to a problem involving two Dutch elm disease (DED) control strategies. The simulation results, including probability density functions and cumulative distribution functions, are described.

scholarly journals Comparison of different control strategies for classical swine fever using emergency vaccination and rapid PCR testing by using a Monte-Carlo simulation model

2013 ◽  
Vol 56 (1) ◽  
pp. 988-1004 ◽  
Author(s):  
J. Brosig ◽  
I. Traulsen ◽  
S. Blome ◽  
K. Depner ◽  
J. Krieter
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Control Strategies ◽  
Control Measure ◽  
Classical Swine Fever ◽  
Current Control ◽  
Control Measures ◽  
Alternative Control ◽  
Monte Carlo Simulation Model

Abstract. Whenever an outbreak of classical swine fever has occurred in the European Union (EU), the basic control measures have usually been supplemented by preventive culling. This strategy has led to a great number of culled pigs and is discussed by general public and politics from both ethical and economic points of view. Emergency vaccination has been deemed to be an alternative control measure for some time now. PCR testing also provides a possible future strategy, since this method would allow a rapid and reliable testing of pigs in the vicinity of an outbreak farm. In this study, a spatial and temporal Monte-Carlo simulation model was used to compare alternative control strategies based upon these two measures (»Emergency Vaccination«, »Test To Slaughter«, »Test To Control« and »Vaccination in conjunction with Rapid Testing«) with the current control strategy. Two regions for investigation with different farm densities were used in the model. In a region with a low farm density, the basic EU control measures seemed to be sufficient to control an epidemic. In a region with a high farm density, additional measures would be necessary. »Emergency Vaccination« in a 3 km application zone and »Traditional Control« reached the same level of infected farms. Both »Test To Slaughter« and »Test To Control« combined with preventive culling led to a lower number of infected farms compared to the sole preventive culling strategy. The alternative control measures can reduce the number of culled farms significantly compared to »Traditional Control«.

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.

Resolution and measurement in the scanning electron microscope

1987 ◽  
Vol 45 ◽  
pp. 534-537 ◽  
Author(s):  
Michael T. Postek
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Engineering Design ◽  
Resolving Power ◽  
Practical Applications ◽  
Instrument Resolution ◽  
Accurate Definition ◽  
Definition Of ◽  
Scanning Electron ◽  
Better Than

The term ultimate resolution or resolving power is the very best performance that can be obtained from a scanning electron microscope (SEM) given the optimum instrumental conditions and sample. However, as it relates to SEM users, the conventional definitions of this figure are ambiguous. The numbers quoted for the resolution of an instrument are not only theoretically derived, but are also verified through the direct measurement of images on micrographs. However, the samples commonly used for this purpose are specifically optimized for the measurement of instrument resolution and are most often not typical of the sample used in practical applications.SEM RESOLUTION. Some instruments resolve better than others either due to engineering design or other reasons. There is no definitively accurate definition of how to quantify instrument resolution and its measurement in the SEM.

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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