scholarly journals Replicating $$\textsc {Restart}$$ with Prolonged Retrials: An Experimental Report

2021 ◽  
pp. 373-380
Author(s):  
Carlos E. Budde ◽  
Arnd Hartmanns
Keyword(s):  
Monte Carlo Simulation ◽  
Original Work ◽  
Ad Hoc ◽  
Rare Event ◽  
Statistical Model Checking ◽  
State Space Explosion ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Independent Replication ◽  
Improved Performance

AbstractStatistical model checking uses Monte Carlo simulation to analyse stochastic formal models. It avoids state space explosion, but requires rare event simulation techniques to efficiently estimate very low probabilities. One such technique is $$\textsc {Restart}$$ R E S T A R T . Villén-Altamirano recently showed—by way of a theoretical study and ad-hoc implementation—that a generalisation of $$\textsc {Restart}$$ R E S T A R T to prolonged retrials offers improved performance. In this paper, we demonstrate our independent replication of the original experimental results. We implemented $$\textsc {Restart}$$ R E S T A R T with prolonged retrials in the and tools, and apply them to the models used originally. To do so, we had to resolve ambiguities in the original work, and refine our setup multiple times. We ultimately confirm the previous results, but our experience also highlights the need for precise documentation of experiments to enable replicability in computer science.

Rare event simulation

2017 ◽  
Author(s):  
Michael P. Allen ◽  
Dominic J. Tildesley
Keyword(s):  
Rare Event ◽  
Path Sampling ◽  
Rapid Progress ◽  
Computationally Efficient ◽  
Transition Path ◽  
Transition Path Sampling ◽  
Event Simulation ◽  
Reaction Coordinates ◽  
Simulation Techniques ◽  
Transition Interface

The development of techniques to simulate infrequent events has been an area of rapid progress in recent years. In this chapter, we shall discuss some of the simulation techniques developed to study the dynamics of rare events. A basic summary of the statistical mechanics of barrier crossing is followed by a discussion of approaches based on the identification of reaction coordinates, and those which seek to avoid prior assumptions about the transition path. The demanding technique of transition path sampling is introduced and forward flux sampling and transition interface sampling are considered as rigorous but computationally efficient approaches.

scholarly journals Ion dissolution mechanism and kinetics at kink sites on NaCl surfaces

2018 ◽  
Vol 115 (4) ◽  
pp. 656-661 ◽  
Author(s):  
Mark N. Joswiak ◽  
Michael F. Doherty ◽  
Baron Peters
Keyword(s):  
Rare Event ◽  
Alkali Halides ◽  
Collective Variable ◽  
Independent Study ◽  
Reaction Coordinate ◽  
Dissolution Mechanism ◽  
Enzyme Active Site ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Desolvation Mechanism

Desolvation barriers are present for solute–solvent exchange events, such as ligand binding to an enzyme active site, during protein folding, and at battery electrodes. For solution-grown crystals, desolvation at kink sites can be the rate-limiting step for growth. However, desolvation and the associated kinetic barriers are poorly understood. In this work, we use rare-event simulation techniques to investigate attachment/detachment events at kink sites of a NaCl crystal in water. We elucidate the desolvation mechanism and present an optimized reaction coordinate, which involves one solute collective variable and one solvent collective variable. The attachment/detachment pathways for Na+ and Cl− are qualitatively similar, with quantitative differences that we attribute to different ion sizes and solvent coordination. The attachment barriers primarily result from kink site desolvation, while detachment barriers largely result from breaking ion–crystal bonds. We compute ion detachment rates from kink sites and compare with results from an independent study. We anticipate that the reaction coordinate and desolvation mechanism identified in this work may be applicable to other alkali halides.

Lattice mold technique for the calculation of crystal nucleation rates

2016 ◽  
Vol 195 ◽  
pp. 569-582 ◽  
Author(s):  
Jorge R. Espinosa ◽  
Pablo Sampedro ◽  
Chantal Valeriani ◽  
Carlos Vega ◽  
Eduardo Sanz
Keyword(s):  
Rare Event ◽  
Simulation Method ◽  
Crystal Nucleation ◽  
Second Step ◽  
Complex Structures ◽  
Continuous Version ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Dynamics Simulations ◽  
Good Agreement

We present a new simulation method for the calculation of crystal nucleation rates by computer simulation. The method is based on the use of molds to induce crystallization in state points where nucleation is a rare event. The mold is a cluster of potential energy wells placed in the lattice positions of the solid. The method has two distinct steps. In the first one the probability per unit volume of forming a sub-critical crystal cluster in the fluid is computed by means of thermodynamic integration. The thermodynamic route consists in gradually switching on an attractive interaction between the wells and the fluid particles. In the second step, the frequency with which such cluster becomes post-critical is computed in Molecular Dynamics simulations with the mold switched on. We validate our method with a continuous version of the hard sphere potential and with the sodium chloride Tosi–Fumi model. In all studied state points we obtain a good agreement with literature data obtained from other rare event simulation techniques. Our method is quite suitable for the study of both crystal nucleation of arbitrarily complex structures and the competition between different polymorphs in the nucleation stage.

A study on appropriate investment of pipeline rehabilitation for water distribution network

2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Water Distribution ◽  
Ad Hoc ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Basis ◽  
Model Case

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.

scholarly journals SAT modulo discrete event simulation applied to railway design capacity analysis

2021 ◽  
Author(s):  
Bjørnar Luteberget ◽  
Koen Claessen ◽  
Christian Johansen ◽  
Martin Steffen
Keyword(s):  
Discrete Event Simulation ◽  
Construction Projects ◽  
Software Verification ◽  
Ad Hoc ◽  
Discrete Event ◽  
Capacity Analysis ◽  
Railway Network ◽  
Event Simulation ◽  
Design Engineers ◽  
Railway Capacity

AbstractThis paper proposes a new method of combining SAT with discrete event simulation. This new integration proved useful for designing a solver for capacity analysis in early phase railway construction design. Railway capacity is complex to define and analyze, and existing tools and methods used in practice require comprehensive models of the railway network and its timetables. Design engineers working within the limited scope of construction projects report that only ad-hoc, experience-based methods of capacity analysis are available to them. Designs often have subtle capacity pitfalls which are discovered too late, only when network-wide timetables are made—there is a mismatch between the scope of construction projects and the scope of capacity analysis, as currently practiced. We suggest a language for capacity specifications suited for construction projects, expressing properties such as running time, train frequency, overtaking and crossing. Such specifications can be used as contracts in the interface between construction projects and network-wide capacity analysis. We show how these properties can be verified fully automatically by building a special-purpose solver which splits the problem into two: an abstracted SAT-based dispatch planning, and a continuous-domain dynamics with timing constraints evaluated using discrete event simulation. The two components communicate in a CEGAR loop (counterexample-guided abstraction refinement). This architecture is beneficial because it clearly distinguishes the combinatorial choices on the one hand from continuous calculations on the other, so that the simulation can be extended by relevant details as needed. We describe how loops in the infrastructure can be handled to eliminate repeating dispatch plans, and use case studies based on data from existing infrastructure and ongoing construction projects to show that our method is fast enough at relevant scales to provide agile verification in a design setting. Similar SAT modulo discrete event simulation combinations could also be useful elsewhere where one or both of these methods are already applicable such as in bioinformatics or hardware/software verification.

A multi-level splitting algorithm based on differential evolution

2018 ◽  
Vol 09 (02) ◽  
pp. 1850021
Author(s):  
Liping Wang ◽  
Wenhui Fan
Keyword(s):  
Differential Evolution ◽  
Rare Event ◽  
Sampling Strategy ◽  
Splitting Algorithm ◽  
Algorithm Efficiency ◽  
Event Simulation ◽  
Sample Paths ◽  
Level Splitting ◽  
Key Factor ◽  
Multi Level

Multi-level splitting algorithm is a famous rare event simulation (RES) method which reaches rare set through splitting samples during simulation. Since choosing sample paths is a key factor of the method, this paper embeds differential evolution in multi-level splitting mechanism to improve the sampling strategy and precision, so as to improve the algorithm efficiency. Examples of rare event probability estimation demonstrate that the new proposed algorithm performs well in convergence rate and precision for a set of benchmark cases.

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