Monte Carlo Statistics Research Articles

Scheduling Analysis with Monte Carlo Simulation and Statistic Method on a Building Construction Project

In the construction of an office building in Indonesia, a delay occurred in the first-floor concrete work. The project was planned to be completed in 161 days but it took 168 days to complete. This study analyzed the issues that arose by doing a scheduling analysis and by comparing the Monte Carlo Simulation and the Statistic method. A comparison between these methods was carried out to determine the project duration scheduling probability level from each method. The data included in the study were the project’s Time Schedule and the interview data from respondents who were directly related to the office building construction project. Monte Carlo Simulation analysis showed that to get a 100% probability level, the duration can only be accelerated by two days, from 168 days to 166 days, while the Statistical method analysis showed that to get a 99.99% probability level the duration can only be accelerated by 4,2 days, from 168 days to 163.8 days. From the results above, it can be concluded that the Monte Carlo Simulation has a more accurate calculation than the Statistic Method because the result from the Monte Carlo Simulation was 166 days with a 100% probability level. It is close to the project realization duration which was 168 days.
 Keywords: construction delay analysis, monte carlo simulation, statistic method comparison

Relative attitude stability analysis of double satellite formation for gravity field exploration in space debris environment

Spacecraft operating in low orbit are at risk of being hit by space debris. In the debris environment, the impact of debris is likely to cause the double satellite formation to exit science mode or even lead to the divergence of the control system, thus affecting the scientific exploration mission. In this paper, the attitude stability of the double satellite formation for gravity field in the near circular and polar orbit in the space debris environment is studied. Firstly, based on Lyapunov control and LQR, two sets of control models of stochastic collision for two satellites aligned with each other were proposed, and the actuators were modelled and assigned. Secondly, models of collision probability and momentum are developed. The distribution law of space debris is obtained according to the international common debris software. Meanwhile, probability density function of two independent collisions is gained. Finally, through Monte Carlo simulation and statistics, the changes of relative attitude and thrust torque are simulated when the satellite obtains the angular momentum for a short period of time due to being impacted by space debris. During the 10-year mission period, the number of times that the space debris impact makes the satellite attitude out of the science mode and the number of times that the control system diverges are obtained, which provides a reference for the normal manner of the double satellite formation for gravity field exploration.

CALCULATION OF NUCLEAR FUEL CLADDING INTERNAL COATING THICKNESS FOR EMERGENCY RESISTANT NUCLEAR FUEL ELEMENT

CALCULATION OF NUCLEAR FUEL CLADDING INTERNAL COATING THICKNESS FOR EMERGENCY RESISTANT NUCLEAR FUEL ELEMENT

Spatial helicity response metric to quantify particle size and turbidity of heterogeneous media through circular polarization imaging

Backscattered circularly polarized light from turbid media consists of helicity-flipped and helicity-preserved photon sub-populations (i.e., photons of perpendicular and parallel circular handedness). Their intensities and spatial distributions are found to be acutely sensitive to average scatterer size and modestly sensitive to the scattering coefficient (medium turbidity) through an interplay of single and multiple scattering effects. Using a highly sensitive intensified-CCD camera, helicity-based images of backscattered light are captured, which, with the aid of corroborating Monte Carlo simulation images and statistics, enable (1) investigation of subsurface photonic pathways and (2) development of the novel ‘spatial helicity response’ metric to quantify average scatterer size and turbidity of tissue-like samples. An exciting potential application of this work is noninvasive early cancer detection since malignant tissues exhibit alterations in scatterer size (larger nuclei) and turbidity (increased cell density).

Hadronic interaction model dependence in cosmic Gamma-ray flux estimation using an extensive air shower array with a muon detector

Observation techniques of high-energy gamma rays using air showers have remarkably progressed via the Tibet ASγ, HAWC, and LHAASO experiments. These observations have significantly contributed to gamma-ray astronomy in the northern sky’s sub-PeV region. Moreover, in the southern sky, the ALPACA experiment is underway at 4,740 m altitude on the Chacaltaya plateau in Bolivia. This experiment estimates the gamma-ray flux from the difference between the number of on-source and off-source events by real data, utilizing the gamma-ray detection efficiency calculated through Monte Carlo simulations, which in turn depends on the hadronic interaction models. Even though the number of cosmic-ray background events can be experimentally estimated, this model dependence affects the estimation of gamma-ray detection efficiency. However, previous reports have assumed that the model dependence is negligible and have not included it in the error of gamma-ray flux estimation. Using ALPAQUITA, the prototype experiment of ALPACA, we quantitatively evaluated the model dependence on hadronic interaction models for the first time. We evaluate the model dependence on hadronic interactions as less than 3.6 % in the typical gamma-ray flux estimation performed by ALPAQUITA; this is negligible compared with other uncertainties such as energy scale uncertainty in the energy range from 6 to 300 TeV, which is dominated by the Monte Carlo statistics. This upper limit of 3.6 % model dependence is expected to apply to ALPACA.

Footprints of impurity quantum phase transitions in quantum Monte Carlo statistics

Interacting single-level quantum dot connected to BCS superconducting leads represents a well-controllable system to study the interplay between the correlation effects and the electron pairing that can result in a $0-\pi$ (singlet-doublet) quantum phase transition. The physics of this system can be well described by the impurity Anderson model. We present an analysis of the statistics of the perturbation expansion order of the continuous-time hybridization expansion quantum Monte Carlo algorithm in the vicinity of such a first-order impurity quantum phase transition. By calculating the moments of the histograms of the expansion order which deviate from the ideal Gaussian shape, we provide an insight into the thermodynamic mixing of the two phases at low but finite temperatures which is reflected in the bimodal nature of the histograms.

Production of light nuclei in heavy ion collisions via hagedorn resonances

The physical processes behind the production of light nuclei in heavy ion collisions are unclear. The successful theoretical description of experimental yields by thermal models conflicts with the very small binding energies of the observed states, being fragile in such a hot and dense environment. Other available ideas are delayed production via coalescence, or a cooling of the system after the chemical freeze-out according to a Saha equation, or a ‘quench’ instead of a thermal freeze-out. A recently derived prescription of an (interacting) Hagedorn gas is applied to consolidate the above pictures. The tabulation of decay rates of Hagedorn states into light nuclei allows to calculate yields usually inaccessible due to very poor Monte Carlo statistics. Decay yields of stable hadrons and light nuclei are calculated. While the scale-free decays of Hagedorn states alone are not compatible with the experimental data, a thermalized hadron and Hagedorn state gas is able to describe the experimental data. Applying a cooling of the system according to a Saha-equation with conservation of nucleon and anti-nucleon numbers leads to (nearly) temperature independent yields, thus a production of the light nuclei at temperatures much lower than the chemical freeze-out temperature is compatible with experimental data and with the statistical hadronization model.

Kinetic Monte Carlo statistics of curvature integration by HACA growth and bay closure reactions for PAH growth in a counterflow diffusion flame

This paper uses a Kinetic Monte Carlo model that includes processes to integrate curvature due to the formation of five- and seven-member rings to simulate polycyclic aromatic hydrocarbons (PAHs) growing in lightly sooting ethylene and acetylene counterflow diffusion flames. The model includes new processes to form seven-member rings via hydrogen-abstraction-acetylene-addition and bay closure reactions on sites containing partially embedded five-member rings. The model additionally includes bay closure and HACA bay capping reactions for the integration of five-member rings. The mass spectra of PAHs predicted by the model are assessed against experimental data, and the distribution of embedded five-member rings and seven-member rings is studied as a function of spatial location, molecule size and frequency of events sampled in the simulation. The simulations show that the formation of seven-member rings and the embedding of five-member rings is a competitive process. Both types of rings are observed more frequently as the simulation proceeds from the fuel outlet towards the stagnation plane. Approximately 15% of the events that integrate curvature resulted in the formation of a seven-member ring coupled to an embedded five-member ring, and the remaining 85% of events embedded five-member rings via the formation of six-member rings. The proportion of PAHs containing embedded five-member rings and/or seven-member rings is observed to be a function of PAH size, passing through a maximum for PAHs containing 15–20 six-member rings. However, the proportion of PAHs containing both types of ring increases with PAH size, where upwards of 10% of PAHs containing at least one five-member ring and 15 or more six-member rings also contain a seven-member ring.

Write-Efficient STT/SOT Hybrid Triple-Level Cell for High-Density MRAM

Spin-transfer torque magnetic random access memory (STT-MRAM) offers nonvolatility, good scalability, high speed, and low-power benefits. Multilevel cell (MLC) is an efficient technology to boost the storage density of the STT-MRAM. However, the conventional MLC structure is not suitable for more than 2-b storage due to inefficient multistep read/write operations. In this article, combining the emerging spin-orbit torque (SOT) and STT mechanisms, we propose a novel STT/SOT hybrid triple-level cell (TLC) MRAM cell structure. Corresponding write and read schemes are designed for this hybrid bit-cell to achieve low-cost operations. Unlike the regular stacked TLC, 3-b data can be written in two steps in the proposed cell structure, and be read in parallel with the assistance of SOT. Simulation results show that the proposed structure achieves 32% and 43% savings on write delay and energy consumption, respectively. Monte Carlo statistic simulation results indicate $1.4\times $ improvement in sensing margin as well.

Fast Calorimeter Simulation in ATLAS

The ATLAS physics program at the LHC relies on very large samples of simulated events. Most of these samples are produced with Geant4, which provides a highly detailed and accurate simulation of the ATLAS detector. However, this accuracy comes with a high price in CPU, and the sensitivity of many physics analyses is already limited by the available Monte Carlo statistics and will be even more so in the future as datasets grow. To solve this problem, sophisticated fast simulation tools are developed, and they will become the default tools in ATLAS production in Run 3 and beyond. The slowest component is the simulation of the calorimeter showers. Those are replaced by a new parametrised description of the longitudinal and lateral energy deposits, including machine learning approaches, achieving a fast but accurate description. In this talk we will describe the new tool for fast calorimeter simulation that has been developed by ATLAS, review its technical and physics performance, and demonstrate its potential to transform physics analyses.

Fast simulation methods in ATLAS: from classical to generative models

The ATLAS physics program relies on very large samples of Geant4 simulated events, which provide a highly detailed and accurate simulation of the ATLAS detector. However, this accuracy comes with a high price in CPU, and the sensitivity of many physics analyses is already limited by the available Monte Carlo statistics and will be even more so in the future. Therefore, sophisticated fast simulation tools have been developed. In Run 3 we aim to replace the calorimeter shower simulation for most samples with a new parametrised description of longitudinal and lateral energy deposits, including machine learning approaches, to achieve a fast and accurate description. Looking further ahead, prototypes are being developed using cutting edge machine learning approaches to learn the appropriate calorimeter response, which are expected to improve modeling of correlations within showers. Two different approaches, using Variational Auto-Encoders (VAEs) or Generative Adversarial Networks (GANs), are trained to model the shower simulation. Additional fast simulation tools will replace the inner detector simulation, as well as digitization and reconstruction algorithms, achieving up to two orders of magnitude improvement in speed. In this talk, we will describe the new tools for fast production of simulated events and an exploratory analysis of the deep learning methods.

Design and fabrication of three-dimensional single-mode waveguide arrays in bulk diamond through direct focused proton beam implantation

We demonstrate the feasibility of creating three-dimensional photonic devices through the realization of multi-level waveguides inside diamond by a series of systematic combined simulations grounded on Monte-Carlo statistics and Maxwell solver algorithms. Further, we have fabricated the counterparts of the multi-level waveguides buried in single crystalline diamond using a process based on several proton beam irradiation steps with different energies and fluences. On top of that, we draw a thorough comparison between the simulation results and the experimental observations, and find that they are in a good agreement with each other. Moreover, the simulation results also provide additional information such as the working fluence range of single-mode light (1550 nm) wave-guiding, the effective refractive index, and the polarization direction. The proof-of-concept of producing three-dimensional optical and photonic structures by direct focused proton beam implantation would open up a variety of new opportunities in designing and fabricating optical modulators, photonic components and quantum-computing related functional devices in bulk diamond, thus further promoting the development of three-dimensional diamond photonics.

Estimation of the Effects of the Cross-Head Speed and Temperature on the Mechanical Strength of Kenaf Bast Fibers Using Weibull and Monte-Carlo Statistics

Methods used by different researchers to evaluate plant fibers’ (PFs) mechanical performance, show great variance in results. In this work, 320 single kenaf fibers of gage lengths 10 and 20 mm were tensile-tested using four speed levels (0.05; 0.5; 1 and 5 mm·min−1). Sixty-three other specimens were also tested under three temperature levels (50, 100, and 150 °C). Mechanical characteristics, namely Young’s modulus, tensile strength, and failure strain were determined. Estimation of the dispersion on the data was performed using Weibull and Monte-Carlo statistics. Results showed a low scatter for cross-head speeds of 0.05, 0.5, and 1 mm·min−1, compared to 5 mm·min−1 for the two gage lengths used. Monte-Carlo average failure strength values were found to be close to the experimental values. A drastic drop in the tensile strength was observed for the temperature of 150 °C for varying hold times. The reported findings are likely to be used in the elaboration of a tensile test standard on PFs.

Modeling sensitivity and uncertainties in platelet activation models applied on centrifugal pumps for extracorporeal life support

Two platelet activation models were studied with respect to uncertainties of model parameters and variables. The sensitivity was assessed using two direct/deterministic approaches as well as the statistical Monte Carlo method. The first two, are linear in character whereas the latter is non-linear. The platelet activation models were applied on platelets moving within an extracorporeal centrifugal blood pump. The phenomenological, Lagrangian stress- and time-based power law-based models under consideration, have experimentally calibrated parameters and the stress expressed in a scalar form. The sensitivity of the model with respect to model parameters and the expression of the scalar stress was examined focusing on a smaller group of platelets associated with an elevated risk of activation. The results showed a high disparity between the models in terms of platelet activation state, found to depend on the platelets’ trajectory in the pump and the expression used for the scalar stress. Monte Carlo statistics was applied to the platelets at risk for activation and not to the entire platelet population. The method reveals the non-linear sensitivity of the activation models. The results imply that power-law based models have a restricted range of validity. The conclusions of this study apply to both platelet activation and hemolysis models.

Coherent State-Based Path Integral Methodology for Computing the Wigner Phase Space Distribution.

The accurate evaluation of the Wigner phase space density for multidimensional system remains a challenging task. Path integral Monte Carlo methods offer a numerically exact approach for obtaining the Boltzmann density in coordinate space, but the Fourier-type integral required to construct the Wigner distribution generally leads to poor convergence. This paper describes a path integral method for constructing the Wigner density which substantially mitigates the Monte Carlo sign problem and thus is applicable to systems with many degrees of freedom. The starting point is the path integral representation of the coherent state density, which does not involve a Fourier integral and thus converges rapidly. We then use the relation between the coherent state and Wigner densities to construct the Wigner function, taking advantage of destructive phase cancellation to truncate the infinite series and thus confine the integrand, avoiding highly oscillatory regions. We also describe the use of information-guided noise reduction (IGNoR) to improve the Monte Carlo statistics in the most challenging regimes. The method is applied to strongly anharmonic one-dimensional models, a system-bath Hamiltonian, as well as the formamide molecule within an ab initio quartic potential, and the results are compared to those obtained by various approximate methods. These calculations suggest that the coherent state-based path integral method described in this paper offers an efficient, numerically exact approach for constructing the Wigner phase space density in systems of many degrees of freedom, and thus will be useful for quantizing the initial condition in classical trajectory-based simulations of dynamical properties.

Influence of the Ply Angle Deviation on the Out-of-Plane Deformation of the Composite Space Mirror

In order to discuss the influence of the ply angle deviation, six symmetric quasi-isotropic layup sequences imposed the fixed or random angle deviation were studied based on the numerical analysis, such as Monte Carlo stochastic finite element method and statistic analysis. The out-of-plane deformation was observed in spite of the symmetric quasi-isotropic sequences subjected to a temperature change due to the ply angle deviation in the space mirror. The surface peak-to-valley (PV), which is one kind of out-of-plane deformation, is proportional to the magnitude of the fixed angle deviation, and the mean of PVs is also proportional to the standard deviation of the random angle deviation. The out-of-plane deformation resulting from two-ply angle deviation indirectly satisfies the parallelogram law, and if each ply angle deviation is random independently, the probability density of that satisfies the Rayleigh distribution. In this paper, it is found that the most effective method to improve the surface accuracy of the space mirror is decreasing the standard deviation of the angle deviation, next to decreasing ply thickness and optimizing layup sequence, which is useful for application in the space mirror.

Analysis of Pitot Tube Static Probe Angle in the Experimental Chamber Conditions

This article comes out from the series of articles devoted to the issue of pumping in the differentially pumped chamber. This article is based on a study of Dr. Danilatos, where pumping of the differential pumped chamber is solved using the Monte Carlo statistic method. To solve the problem we use the mechanics of continuum with experimental verification. The article deals with a construction of the conic tip of the static probe.

Using the Ideal and Real Gas Model for the Mathematical – Physics Analysis of the Experimental Chambre

This article comes out from the series of articles devoted to the issue of pumping in the differentially pumped chamber. This article is based on a study of Dr. Danilatos, where pumping of the differential pumped chamber is solved using the Monte Carlo statistic method. To solve the problem we use the mechanics of continuum with experimental verification. The article deals with a construction of the conic tip of the static probe.

Flow Evaluation in the Experimental Chamber for Supersonic Flow in Low Pressures

This article comes out from the series of articles devoted to the issue of pumping in the differentially pumped chamber. This article is based on a study of Dr. Danilatos, where pumping of the differential pumped chamber is solved using the Monte Carlo statistic method. To solve the problem we use the mechanics of continuum with experimental verification. In the article is mentioned the evaluation of the mathematical- physics model as a background for preparing experimental measuring dealing with a construction of the conic tip of the static probe.

Reliability-Enhanced Hybrid CMOS/MTJ Logic Circuit Architecture

Benefitting from its non-volatility, nearly infinite endurance, good scalability, and great CMOS compatibility, magnetic tunnel junction (MTJ) embedded in conventional CMOS logic circuits has been proposed as one potentially powerful solution to introduce non-volatility in today’s programmable logic circuits, which is envisioned to achieve low power and high area efficiency. However, the recently proposed hybrid CMOS/MTJ logic circuits and prototypes based on such a logic-in-memory architecture suffers from a severe reliability issue, which is the precise transformation from MTJ resistance to electric signals due to its limited tunnel magnetoresistance ratio (TMR $\leq$ 150%), i.e., the requirement of nearly zero sensing error for logic applications. In this paper, to overcome this sensing reliability issue, a novel sense amplifier (SA) with high sensing margin is proposed for such hybrid CMOS/MTJ logic circuit architecture. By using a commercial CMOS 40 nm design kit and a physics-based MTJ compact model, hybrid CMOS/MTJ transient and Monte Carlo statistic simulations have been conducted to demonstrate the functionality of the proposed SA and evaluate its performance, respectively.