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Showing 1 to 20 of 23 for “"Monte Carlo Simulation (MCS)"”.
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On-Line Monitoring, Control, and Reliability of Structural Dynamical Systems
"Ideas for improving the efficiency of Monte Carlo simulation (MCS) is the subject of the final section. Determining the low failure probabilities of typical engineering systems is quite difficult without using millions of MCS realizations to characterize the probability distribution. Several links …
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Innovative Methods for Outcome-Based Pricing of Treatments from the US Payer Perspective (The Six Delta Platform)
… The price variations in each δ are simulated by Monte Carlo Simulation (MCS) methods to generate a price at the dimensional level (i.e., the dimension-specific price, DSP), and a price when all dimensions are integrated (i.e., the average of all dimensional prices, ADP). A proof-of-concept for …
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Quantitative risk assessment in drill casing design for oil and gas wells
… Order Reliability Method (FORM/SORM), Monte Carlo Simulation (MCS) to assess the efficiency and accuracy. It is shown that, for the examples considered, the proposed methods provide accurate and efficient results for the probability of failure. Another important characteristic of this …
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Reliability Analysis of Carbon Fiber Reinforced Polymer (CFRP) Strengthened Steel Beams
… Hart-Smith model. Reliability methods, namely, Monte Carlo Simulation (MCS) and First-Order Reliability Method (FORM) have been performed to calculate the resistance factors of DLS joints for different design scenarios. The sensitivity study quantifies the relative contribution of each design …
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Voltage calculation on low voltage feeders with distributed generation
… it against voltage calculation through Monte Carlo Simulation (MCS). The second step involves ammending and extending the HB algorithm for voltage calculation in active LV feeders with DG, testing and validation against voltage calculation through Monte Carlo Simulation (MCS). With the …
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The Fourier Spectrum Element Method For Vibration And Power Flow Analysis Of Complex Dynamic Systems
… efficacy, can be efficiently combined with the Monte Carlo Simulation (MCS) to predict the statistical characteristics of the dynamic responses of built-up structures in the presence of model uncertainties. Several examples are presented to demonstrate the mean behaviors of complex built-up …
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Probabilistic finite element analysis of the uncemented total hip replacement
… of an uncemented THR has been developed. Monte Carlo Simulation (MCS) was applied to various models with increasing complexity. In the pilot models, MCS was applied to a simplified finite element model (FE) of an uncemented total hip replacement (UTHR). The implant and bone stiffness, load …
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Reliability estimation and risk-cost optimisation of underground pipelines
… and Rackwitz-Fiessler (HL-RF) algorithm and Monte Carlo Simulation (MCS) have been used to estimate the reliability. Then Subset Simulation (SS) method is developed to enhance the applicability, especially for small failure probability prediction. Accuracy prediction method, Receiver …
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Risk Analysis and Reliability Improvement of Mechanistic-Empirical Pavement Design
… A robust reliability analysis can rely on Monte Carlo Simulation (MCS). The ultimate goal of this study was to improve the reliability model of the MEPDG using surrogate modeling techniques and Monte Carlo simulation.</p> <p>To achieve this goal, four tasks were accomplished in this …
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Reliability analyses of the collapse and burst of elastic/plastic tubes
… the developed shell finite element program, Monte Carlo simulation (MCS) can be applied to the burst/collapse reliability problems. However, the enormous computational effort makes MCS infeasible except as a check for selected cases. Unfortunately, the system reliability method does not apply …
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Uncertainty Quantification in Dynamic Problems With Large Uncertainties
… equations. The results are compared with Monte Carlo simulation (MCS). An improved method is developed using AMV, metamodel, and MCS. This new technique is applied to calculate sound power of a composite panel using FEM and Rayleigh Integral. The proposed methodology shows considerable …
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Reliability Impacts of Plug-in Hybrid Electric Vehicles on Power Systems
… in charging and driving behaviors using Monte Carlo Simulation (MCS) method. As PHEV sales are increased in response to environmental support, their impacts to system reliability will also increase. A range of reliability studies are carried out in the IEEE Reliability Test System …
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Terrestrial Laser Scanning for Quantifying Uncertainty in Fluvial Applications
… uncertainty analysis was performed with Monte Carlo Simulation (MCS) on a two-stage channel SRD for Stroubles Creek. Both knowledge errors (Manning's <i>n</i> and Shield's number) and natural stochasticity (bankfull discharge and grain size) were incorporated into the analysis. The …
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A Systematic Framework for Machine Learning-Based Robust Project Scheduling Under Uncertainty
… tested and validated through experiments using Monte-Carlo Simulation (MCS), and the results are compared to the Critical Chain Project Management (CCPM) approach, which is a well-known benchmark approach in the robust project scheduling field.<p></p>
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Flexural Behavior of CFRP-Pretensioned Girders
… a reliability analysis was conducted using the Monte-Carlo Simulation (MCS) approach to calibrate the strength reduction factor for CFRP prestressed beams considering the statistical variability of the model parameters and the modelling uncertainty. The reliability study suggested a strength …
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Uncertainty Analysis and Calibration of Water Distribution Quality Models
… steady and unsteady conditions was analyzed by Monte Carlo simulation (MCS). Sources of uncertainties for water quality include decay coefficients, pipe diameter and roughness, and nodal spatial and temporal demands. The effect of individual parameter is discussed, as well as the combined effect …
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Extending the Herman-Beta transform for probabilistic load flow analysis of radial feeders
… instance, numerical methods such as the renowned Monte-Carlo simulation (MCS), offer the most accuracy (within the limits of randomness) but are very computationally demanding and undesirable for practical applications. Usually, speed is coupled with loss of accuracy. Most approaches based on …
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Applying the Herman-Beta probabilistic method to MV feeders
… with the HB algorithm are tested against a Monte-Carlo Simulation (MCS) solution of the feeder with an accurate model (full representation of feeder impedance and load power factor). The approach is extended to include shunt capacitor connections and DG in voltage calculations using the HB …
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Modelling uncertainty of cost and time in infrastructure projects
… and triangular probability distributions; while Monte Carlo Simulation (MCS), Copula analysis technique, the Markov processes, and Adaptive Neuro-Fuzzy Inference System (ANFIS) analytical technique were used in modelling the variability of the cost and time activity, correlation between costs, …
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The impact of cormorants (Phalacrocorax carbo carbo and Phalacrocorax carbo sinensis) on inland fisheries in the UK
… a modelling system was designed, using a Monte Carlo Simulation (MCS), to estimate the number and mass of fish being removed from the site over the whole winter period. The fisheries data were collected by electric fishing, seine netting, hydro-acoustics and angler catch analysis. The …
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