Simulation-based Calculations Research Articles

Nanosilica-enhanced geopolymer cementitious materials: Mechanistic insights from experimental and computational simulations

To mitigate the pollution associated with municipal solid waste incineration fly ash (MSW-IFA), solidification/stabilization (S/S) techniques have garnered considerable attention. This study systematically investigates the modification effects of nanosilica (NS) on the properties of geopolymer functional cementitious materials (GFCM) derived from waste fly ash. By integrating experimental data with simulation-based calculations, the influence of NS on the macroscopic properties and microstructure of GFCM, including mechanical performance, heavy metal immobilization mechanisms, and hydration processes, was examined. The results indicate that NS enhances mineral phase and pore structure through pozzolanic and filling effects, promoting additional C-S-H gel formation and pore filling, which significantly accelerates the hydration process and improves mechanical properties. Furthermore, NS increases the proportion of heavy metals in a stable state, thereby reducing their leaching potential. Density functional theory (DFT) calculations further revealed that NS's modification effects primarily occur via filling, nucleation, and pozzolanic activity, which supported the construction of a geopolymer reaction network. This study offers a validated approach for advancing the understanding of NS modification mechanisms, the development of geopolymer reaction networks, and the mechanisms governing heavy metal S/S.

Parametric optimization for estimating beta detection efficiency in thin plastic scintillation detector

A condenser air removal system plays a crucial role in radiation monitoring within nuclear power plants, specifically for detecting potential leaks of radioactive material from primary-to-secondary systems. This system assesses the leakage rate (LR) by measuring the emission of β particles from noble gases using a thin plastic scintillation (TPS) detector, which is specifically designed for counting purposes. Among the factors used in LR calculation, the detection efficiency (k) must be experimentally determined in advance. However, this is challenging because of the limitations posed by radiation safety regulations. Moreover, simulation-based calculations are difficult to achieve because only a portion of the β-ray energy is transferred in the TPS detectors, resulting in a lack of prior energy information. To overcome these challenges, this study employed a multi-objective parameter optimization technique to simultaneously calculate the parameters required for the β-ray detection response function and energy calibration equation. Subsequently, k values were calculated using the optimization results. The optimization performance was demonstrated by comparing the measured spectra of the TPS detector with the spectra obtained from the Monte Carlo N-particle simulation. Furthermore, we confirmed that the calculated k values agreed with the reference values.

Hydrogen Line Shape Uncertainties in White Dwarf Model Atmospheres

For isolated white dwarf (WD) stars, fits to their observed spectra provide the most precise estimates of their effective temperatures and surface gravities. Even so, recent studies have shown that systematic offsets exist between such spectroscopic parameter determinations and those based on broadband photometry. These large discrepancies (10% inTeff, 0.1 M⊙in mass) provide scientific motivation for reconsidering the atomic physics employed in the model atmospheres of these stars. Recent simulation work of ours suggests that the most important remaining uncertainties in simulation-based calculations of line shapes are the treatment of 1) the electric field distribution and 2) the occupation probability (OP) prescription. We review the work that has been done in these areas and outline possible avenues for progress.

Monte Carlo Simulation-Based Calculations of Complex DNA Damage for Incidents of Environmental Ionizing Radiation Exposure

In this paper, we present a useful Monte Carlo (MC)-based methodology that can be utilized to calculate the absorbed dose and the initial levels of complex DNA damage (such as double strand breaks-DSBs) in the case of an environmental ionizing radiation (IR) exposure incident (REI) i.e., a nuclear accident. Our objective is to assess the doses and complex DNA damage by isolating only one component of the total radiation released in the environment after a REI that will affect the health of the exposed individual. More specifically, the radiation emitted by radionuclide 137Cs in the ground (under the individual’s feet). We use a merging of the Monte Carlo N-Particle Transport code (MCNP) with the Monte Carlo Damage Simulation (MCDS) code. The DNA lesions have been estimated through simulations for different surface activities of a 137Cs ground-based γ radiation source. The energy spectrum of the emitted secondary electrons and the absorbed dose in typical mammalian cells have been calculated using the MCNP code, and then these data are used as an input in the MCDS code for the estimation of critical DNA damage levels and types. As a realistic application, the calculated dose is also used to assess the Excess Lifetime Cancer Risk (ELCR) for eight hypothetical individuals, living in different zones around the Chernobyl Nuclear Power Plant, exposed to different time periods at the days of the accident in 1986. We conclude that any exposition of an individual in the near zone of Chernobyl increases the risk of cancer at a moderate to high grade, connected also with the induction of complex DNA damage by radiation. Generally, our methodology has proven to be useful for assessing γ rays-induced complex DNA damage levels of the exposed population, in the case of a REI and for better understanding the long-term health effects of exposure of the population to IR.

Palliation of Four-Wave Mixing in Optical Fibers Using Improved DSP Receiver

A long haul optical communication system (LHOCS) is one of the key resources to fulfill the higher capacity requirements in future communication networks. To launch LHOCS, the system mainly faces high order nonlinear effects. The four-wave mixing (FWM) is one of the major nonlinear effects, which limits the transmission distance. Therefore, in this paper, an advanced duo-binary (DB) modulation scheme-based system is evaluated by employing an improved digital signal processing (IDSP) approach at the receiver side to suppress the FWM effect. In addition, an analytical analysis is also performed for the proposed system. To observe the difference between the IDSP and conventional digital signal processing (DSP), the various performance metrics such as bit error rate (BER), Q-factor, and optical signal-to-noise ratio (OSNR) parameters are evaluated. Variable channel spacing along with polarization mode dispersion (PMD) are analyzed at several ranges of input powers and fiber lengths. The analytical and simulation-based calculations exhibit the effectiveness of the proposed model and hence, FWM effect are compensated to achieve 500 km optical fiber propagation range with a BER below 10−6.

Macroscopic Differentiators for Microscopic Structural Nonideality in Binary Ionic Liquid Mixtures.

Combining two ionic liquids to form a binary ionic liquid mixture is a simple yet effective strategy to not only expand the number of ionic liquids but also precisely control various physicochemical properties of resultant ionic liquid mixtures. From a fundamental thermodynamic point of view, it is not entirely clear whether such mixtures can be classified as ideal solutions. Given a large number of binary ionic liquid mixtures that emerge, the ability to predict the presence of nonideality in such mixtures a priori without the need for experimentation or molecular simulation-based calculations is immensely valuable for their rational design. In this research report, we demonstrate that the difference in the molar volumes (ΔV) of the pure ionic liquids and the difference in the hydrogen-bonding ability of anions (Δβ) are the primary determinants of nonideal behavior of binary ionic liquid mixtures containing a common cation and two anions. Our conclusion is derived from a comparison of microscopic structural properties expressed in terms of radial, spatial, and angular distributions for binary mixtures and those of the corresponding pure ionic liquids. Molecular dynamics simulations of 16 binary ionic liquid mixtures, containing a common cation 1-n-butyl-3-methylimidazolium [C4mim]+ and combinations of (less basic) fluorinated {trifluoromethylacetate [TFA]-, trifluoromethanesulfonate [TFS]-, bis(trifluoromethanesulfonyl)imide [NTf2]-, and tris (pentafluoroethyl) trifluorophosphate [eFAP]-} versus (more basic) nonfluorinated {chloride Cl-, acetate [OAC]-, methylsulfate [MeSO4]-, and dimethylphosphate [Me2PO4]-} anions, were conducted. The large number of binary ionic liquid mixtures examined here enabled us to span a broad range of ΔV and Δβ values. The results indicate that binary mixtures of two ionic liquids for which ΔV > 60 cm3/mol and Δβ > 0.4 are expected to be microscopically nonideal. On the other hand, ΔV < 60 cm3/mol and Δβ < 0.4 will lead to molecular structures that are not differentiated from those of their pure ionic liquid counterparts.

Micromagnetic simulations study of skyrmions in magnetic FePt nanoelements

The magnetization reversal in 330 nm triangular prismatic magnetic nanoelements with variable magnetocrystalline anisotropy similar to that of partially chemically ordered FePt is studied using micromagnetic simulations employing Finite Element discretizations. Several magnetic properties including the evaluation of the magnetic skyrmion number $S$ are computed in order to characterize magnetic configurations exhibiting vortex-like formations. Magnetic vortices and skyrmions are revealed in different systems generated by the variation of the magnitude and relative orientation of the magnetocrystalline anisotropy direction, with respect to the normal to the triangular prism base. Micromagnetic configurations with skyrmion number greater than one have been detected for the case where magnetocrystalline anisotropy was normal to nanoelement's base. For particular magnetocrystalline anisotropy values three distinct skyrmions are formed and persist for a range of external fields. The simulation-based calculations of the skyrmion number S revealed that skyrmions can be created for magnetic nanoparticle systems lacking of chiral interactions such as Dzyaloshinsky-Moriya, but by only varying the magnetocrystalline anisotropy.

Effects of cooling lubricant on the thermal regime in the working space of machine tools

Abstract The use of cooling lubricant is indispensable for many milling and grinding machining tasks, primarily to achieve the best possible cooling and lubricating effect in the cutting zone and to reduce wear. In addition, tempered cooling lubricant carries out the function of heat removal from the working space. A reduction due to resource-efficient or ecological efforts has a direct impact on the temperature regime in the working space, which affects the thermal behavior of the frame structures and can cause machining inaccuracies. In this article, these effects of cooling lubricant on the thermal behavior of exemplary assemblies are modeled. Experimental investigations, based on temperatures and displacements, are compared with simulation-based calculations. The results include the description of the environmental conditions that must be taken into account when modeling frame structures and the influencing variables such as coolant temperature, supplied volume flow and extracted air volume.

201Tl production through light charged-particle induced reactions on Tl and Hg isotopes: theoretical and simulation approaches

Investigation of the significant 201Tl diagnostic radionuclide production via protons and deuterons induced reactions by using the 203Tl, 201Hg and 202Hg isotope targets is the main goal of this study. The effect of three phenomenological and microscopic level density models utilizing the TALYS-1.8 code along with TENDL-2017 data were applied to excitation functions evaluations. Furthermore, simulation code was used for the above production processes. Subsequently the prediction of the production yield in each reaction was done. Finally, the comparison between EXFOR database experimental data and the theoretical and simulation-based calculations was implemented.

The rate of biocide leaching from porous renders

The leaching of biocides contained in renders occurs through the contact of the surfaces of the renders with water. In the majority of cases such contact occurs during rainfall, and therefore it is intermittent in nature. The work presents a mathematical model of the process of the transfer of mass (biocides) in a porous material (a render). The process consists of two stages which follow each other in a cyclical manner: the leaching stage, in which the surface of the render is wet, and the stage in which the surface of the render is dry. In the latter stage homogenization of the concentrations of the biocides in the render occurs. The coefficients of the diffusion of biocides in renders, which were determined in a previous work, were utilized in the simulation-related calculations, in which the dependencies of the average concentrations of biocides in the render since the time during the leachings performed in the subsequent cycles were determined. The consistence of the results of simulation-based calculations with the results of experimental research that was obtained confirms the correctness of the model that is presented. The biocides which were applied in the research: diuron, cybutryn and isoproturon are applied in practice as supplements to building materials. The purpose of these biocides is to ensure protection against the growth of microorganisms. The biocides which were mentioned constituted a supplement to the acrylic render and to the silicone render.

Some factors affecting statistical power of approximate tests in the linear mixed model for longitudinal data

ABSTRACTDifferent longitudinal study designs require different statistical analysis methods and different methods of sample size determination. Statistical power analysis is a flexible approach to sample size determination for longitudinal studies. However, different power analyses are required for different statistical tests which arises from the difference between different statistical methods. In this paper, the simulation-based power calculations of F-tests with Containment, Kenward-Roger or Satterthwaite approximation of degrees of freedom are examined for sample size determination in the context of a special case of linear mixed models (LMMs), which is frequently used in the analysis of longitudinal data. Essentially, the roles of some factors, such as variance–covariance structure of random effects [unstructured UN or factor analytic FA0], autocorrelation structure among errors over time [independent IND, first-order autoregressive AR1 or first-order moving average MA1], parameter estimation methods [maximum likelihood ML and restricted maximum likelihood REML] and iterative algorithms [ridge-stabilized Newton-Raphson and Quasi-Newton] on statistical power of approximate F-tests in the LMM are examined together, which has not been considered previously. The greatest factor affecting statistical power is found to be the variance–covariance structure of random effects in the LMM. It appears that the simulation-based analysis in this study gives an interesting insight into statistical power of approximate F-tests for fixed effects in LMMs for longitudinal data.

Calculating Power by Bootstrap, with an Application to Cluster-Randomized Trials.

Background:A key requirement for a useful power calculation is that the calculation mimic the data analysis that will be performed on the actual data, once that data is observed. Close approximations may be difficult to achieve using analytic solutions, however, and thus Monte Carlo approaches, including both simulation and bootstrap resampling, are often attractive. One setting in which this is particularly true is cluster-randomized trial designs. However, Monte Carlo approaches are useful in many additional settings as well. Calculating power for cluster-randomized trials using analytic or simulation-based methods is frequently unsatisfactory due to the complexity of the data analysis methods to be employed and to the sparseness of data to inform the choice of important parameters in these methods.Methods:We propose that among Monte Carlo methods, bootstrap approaches are most likely to generate data similar to the observed data. In bootstrap approaches, real data are resampled to build complete data sets based on real data that resemble the data for the intended analyses. In contrast, simulation methods would use the real data to estimate parameters for the data, and would then simulate data using these parameters. We describe means of implementing bootstrap power calculation.Results:We demonstrate bootstrap power calculation for a cluster-randomized trial with a censored survival outcome and a baseline observation period.Conclusions:Bootstrap power calculation is a natural application of resampling methods. It provides a relatively simple solution to power calculation that is likely to be more accurate than analytic solutions or simulation-based calculations, in the sense that the bootstrap approach does not rely on the assumptions inherent in analytic calculations. This method of calculation has several important strengths. Notably, it is simple to achieve great fidelity to the proposed data analysis method and there is no requirement for parameter estimates, or estimates of their variability, from outside settings. So, for example, for cluster-randomized trials, power calculations need not depend on intracluster correlation coefficient estimates from outside studies. In contrast, bootstrap power calculation requires initial data that resemble data that are to be used in the planned study. We are not aware of bootstrap power calculation being previously proposed or explored for cluster-randomized trials, but it can also be applied for other study designs. We show with a simulation study that bootstrap power calculation can replicate analytic power in cases where analytic power can be accurately calculated. We also demonstrate power calculations for correlated censored survival outcomes in a cluster-randomized trial setting, for which we are unaware of an analytic alternative. The method can easily be used when preliminary data are available, as is likely to be the case when research is performed in health delivery systems or other settings where electronic medical records can be obtained.

Feasibility of rigorous multi-objective optimization of wastewater management and treatment plants

The present paper describes a study on the feasibility of coupling rigorous dynamic modelling (DM) and its extended boundaries through Life Cycle Assessment (LCA) with an Efficient Multi-Objective Optimization (EMOO) tool. The combined framework (DM-LCA-EMOO) was then applied to a real-world dynamic system: the wastewater treatment. To give a global view of all environmental, economic and technological performance, three objectives were considered: Effluent Quality Index (EQI), Operational Cost Index (OCI) and environmental impacts quantified through Life Cycle Impact Assessment (LCIA). Legally imposed constraints, including total nitrogen, total phosphorus, total chemical oxygen demand, total suspended solids and ammonium ion were also taken into account. Given the contradictory nature of objectives, the presence of constraints and the time-consuming simulation-based calculations, an Efficient Multi-Objective Optimization framework, namely Archive-based Multi-Objective Evolutionary Algorithm with Memory-based Adaptive Partitioning of search space (AMOEA-MAP) was used. The practicality of such a combined DM-LCA-EMOO tool for the evaluation of wastewater management and treatment was then addressed and demonstrated through a case application.

SOLAR WIND COLLISIONAL AGE FROM A GLOBAL MAGNETOHYDRODYNAMICS SIMULATION

ABSTRACT Simple estimates of the number of Coulomb collisions experienced by the interplanetary plasma to the point of observation, i.e., the “collisional age”, can be usefully employed in the study of non-thermal features of the solar wind. Usually these estimates are based on local plasma properties at the point of observation. Here we improve the method of estimation of the collisional age by employing solutions obtained from global three-dimensional magnetohydrodynamics simulations. This enables evaluation of the complete analytical expression for the collisional age without using approximations. The improved estimation of the collisional timescale is compared with turbulence and expansion timescales to assess the relative importance of collisions. The collisional age computed using the approximate formula employed in previous work is compared with the improved simulation-based calculations to examine the validity of the simplified formula. We also develop an analytical expression for the evaluation of the collisional age and we find good agreement between the numerical and analytical results. Finally, we briefly discuss the implications for an improved estimation of collisionality along spacecraft trajectories, including Solar Probe Plus.

Pressure-induced emergence of unusually high-frequency transverse excitations in a liquid alkali metal: Evidence of two types of collective excitations contributing to the transverse dynamics at high pressures.

Unlike phonons in crystals, the collective excitations in liquids cannot be treated as propagation of harmonic displacements of atoms around stable local energy minima. The viscoelasticity of liquids, reflected in transition from the adiabatic to elastic high-frequency speed of sound and in absence of the long-wavelength transverse excitations, results in dispersions of longitudinal (L) and transverse (T) collective excitations essentially different from the typical phonon ones. Practically, nothing is known about the effect of high pressure on the dispersion of collective excitations in liquids, which causes strong changes in liquid structure. Here dispersions of L and T collective excitations in liquid Li in the range of pressures up to 186 GPa were studied by ab initio simulations. Two methodologies for dispersion calculations were used: direct estimation from the peak positions of the L/T current spectral functions and simulation-based calculations of wavenumber-dependent collective eigenmodes. It is found that at ambient pressure, the longitudinal and transverse dynamics are well separated, while at high pressures, the transverse current spectral functions, density of vibrational states, and dispersions of collective excitations yield evidence of two types of propagating modes that contribute strongly to transverse dynamics. Emergence of the unusually high-frequency transverse modes gives evidence of the breakdown of a regular viscoelastic theory of transverse dynamics, which is based on coupling of a single transverse propagating mode with shear relaxation. The explanation of the observed high-frequency shift above the viscoelastic value is given by the presence of another branch of collective excitations. With the pressure increasing, coupling between the two types of collective excitations is rationalized within a proposed extended viscoelastic model of transverse dynamics.

Five questions to consider before conducting a stepped wedge trial.

Researchers should consider five questions before starting a stepped wedge trial.Why are you planning one? Researchers sometimes think that stepped wedge trials are useful when there is little doubt about the benefit of the intervention being tested. However, if the primary reason for an intervention is to measure its effect, without equipoise there is no ethical justification for delaying implementation in some clusters. By contrast, if you are undertaking pragmatic research, where the primary reason for rolling out the intervention is for it to exert its benefits, and if phased implementation is inevitable, a stepped wedge trial is a valid option and provides better evidence than most non-randomized evaluations.What design will you use? Two common stepped wedge designs are based on the recruitment of a closed or open cohort. In both, individuals may experience both control and intervention conditions and you should be concerned about carry-over effects. In a third, continuous-recruitment, short-exposure design, individuals are recruited as they become eligible and experience either control or intervention condition, but not both.How will you conduct the primary analysis? In stepped wedge trials, control of confounding factors through secular variation is essential. ‘Vertical’ approaches preserve randomization and compare outcomes between randomized groups within periods. ‘Horizontal’ approaches compare outcomes before and after crossover to the intervention condition. Most analysis models used in practice combine both types of comparison. The appropriate analytic strategy should be considered on a case-by-case basis.How large will your trial be? Standard sample size calculations for cluster randomized trials do not accommodate the specific features of stepped wedge trials. Methods exist for many stepped wedge designs, but simulation-based calculations provide the greatest flexibility. In some scenarios, such as when the intracluster correlation coefficient is moderate or high, or the cluster size is large, a stepped wedge trial may require fewer clusters than a parallel cluster trial.How will you report your trial? Stepped wedge trials are currently challenging to report using CONSORT principles. Researchers should consider how to demonstrate balance achieved by randomization and how to describe trends for outcomes in both intervention and control clusters.

Structure of liquid Al and Al67Mg33 alloy: comparison between experiment and simulation

We report data on the structure of liquid Al and an Al67Mg33 alloy obtained from state-of-the-art X-ray diffraction experiments and ab initio molecular dynamics (AIMD) simulations. To facilitate a direct comparison between these data, we develop a method to elongate the AIMD pair correlation function in order to obtain reliable AIMD structure factors. The comparison reveals an appreciable level of discrepancy between experimental and AIMD liquid structures, with the latter being consistently more ordered than the former at the same temperature. The discrepancy noted in this study is estimated to have significant implications for simulation-based calculations of liquid transport properties and solid–liquid interface kinetic properties.

Simulation-based calculations of the proton dose in phase change memory cells

Monte Carlo simulations of proton irradiation on phase change memory cells were conducted and the proton dose, in both the whole memory cell and in its active layer, calculated. The memory cell was modeled by a multi-layer stack consisting of two TiW electrodes and ZnS-SiO2 films as insulators surrounding the active region. Materials considered for the active region were Ge2Sb2Te5, AgSbSe2, and Si2Sb2Te5. The effects of exposing phase change memory cells to proton beams were investigated for various thicknesses of phase change materials and different proton energies. Radiation-induced changes in the investigated memory cells are presented, including the accumulation of atomic displacements and the thermal heating of the active region. Possible effects of these changes on cell operation are discussed.

Sample size determination through power simulation; practical lessons from a stepped wedge cluster randomised trial (SW CRT)

Results Assuming the statistical power needs to be 80% or higher, a total of 6400 simulations will estimate the power to a standard error of 0.5%, In the present study, a total of 24 clusters and 5 time periods were required to give a study power of approximately 85% assuming a type I error rate of 5% and a 20% [RR=1.20] increase in lung cancer diagnosis rates attributable to the intervention within 6 months. Hence, 6 clusters will receive the intervention per each time period in a delayed intervention fashion and all clusters will act as controls during the first time period. Study power was insensitive to distributional assumptions under consideration in this case. Conclusions The stepped wedge CRT design is robust, flexible, offers a more practical alternative in evaluating intervention in routine practice than other designs and provides an opportunity to model time trends. Despite this, its implementation in routine practice is being hampered by complex statistical issues including sample size estimation. However, we have demonstrated that sample size calculation through power simulation is a simple and efficient approach when the use of routine formulae is impossible. Moreover, it is straightforward to assess sensitivity to issues such as heterogeneity across clusters, including the impact of design constraints such as centre or learning effects. We propose simulation-based power calculations should be considered routine practice in such circumstances. Finally, using a computer is easier than finding a book with the right formula.

The Environment and Trade

Reflecting the emphasis of recent work in the field of trade and the environment, this review focuses on empirical issues, primarily econometric estimates of the pollution haven effect and simulation-based calculations of carbon leakage. A brief discussion of the theory explains why intuition from partial equilibrium models may not carry over to a general equilibrium setting.