Inhibition of Lithium Dendrite Growth with Highly Concentrated Ions: Cellular Automaton Simulation and Surrogate Model with Ensemble Neural Networks

We have developed a lattice Monte Carlo (MC) simulation based on the diffusion-limited aggregation model that accounts for the effect of the physical properties of small ions such as inorganic...

Life Cycle Inventory (LCI) Stochastic Approach Used for Rare Earth Elements (REEs), Considering Uncertainty

The purpose of the paper is to present the results of the stochastic modelling with uncertaintyperformed with the use of Monte Carlo (MC) simulation with 10,000 cycles and a confidence interval of95 %, as recommended. Analysed REEs were fitted by lognormal distributions by using the Crystal Ball®(CB) spreadsheet-based software after defining the geometric mean value (μg) and the standard deviation(σg), automatically calculated (matches) the lower, as well as, upper boundaries of lognormal distribution.The number of replications of a simulation affects the quality of the results. The principal output reportprovided by CB and presented in this study consists of the graphical representation in the form of thefrequency chart, percentiles summary, and statistics summary. Additional CB options provide a sensitivityanalysis with tornado diagrams. The data that was used for MC simulation of the LCI model includesavailable and published data concerning associated with the REEs. This paper discusses the results andshow that the adopted approach is applicable for any REEs used in the LCI studies under uncertainty. Theresults obtained from this study can be used as the first step in performing a full LCA analysis and helppractitioners as well as decision-makers in the environmental engineering and management.

Development of a hardware-accelerated simulation kernel for ultra-high vacuum with Nvidia RTX GPUs

Molflow+ is a Monte Carlo (MC) simulation software for ultra-high vacuum, mainly used to simulate pressure in particle accelerators. In this article, we present and discuss the design choices arising in a new implementation of its ray-tracing–based simulation unit for Nvidia RTX Graphics Processing Units (GPUs). The GPU simulation kernel was designed with Nvidia’s OptiX 7 API to make use of modern hardware-accelerated ray-tracing units, found in recent RTX series GPUs based on the Turing and Ampere architectures. Even with the challenges posed by switching to 32 bit computations, our kernel runs much faster than on comparable CPUs at the expense of a marginal drop in calculation precision.

Investigation of field output factors using IAEA-AAPM TRS-483 code of practice recommendations and Monte Carlo simulation for 6 MV photon beams

Introduction: This study aims to experimentally determine field output factors using the methodologies suggested by the IAEA-AAPM TRS-483 for small field dosimetry and compare with the calculation from Monte Carlo (MC) simulation. Methods: The IBA-CC01, Sun Nuclear EDGE and IBA-SFD detectors were employed to determine the uncorrected and the corrected field output factors for 6 MV photon beams. Measurements were performed at 100 cm source to axis distance, 10 cm depth in water, and the field sizes ranged from 1 × 1 to 10 × 10 cm2. The use of field output correction factors proposed by the TRS-483 was utilised to determine field output factors. The measured field output factors were compared to that calculated using the egs_chamber user code. Results: The decrease in the percentage standard deviation of the measured three detectors was observed after applying the field output correction factors. Measured field output factors using CC01 and EDGE detectors agreed with MC values within 3% for field sizes down to 1 × 1 cm2, except the SFD detector. Conclusions: The corrected field output factors agree with the calculation from MC, except the SFD detector. CC01 and EDGE are suitable for determining field output factors, while the SFD may need more implementation of the intermediate field method.

Investigating Tourists’ Willingness to Walk (WTW) to Attractions within Scenic Areas: A Case Study of Tongli Ancient Town, China

This paper aims to quantify tourists’ willingness to walk (WTW) in the intra-destination choice in pedestrian scenic areas. The case study presented is the Tongli Ancient Town (Jiangsu Province, China), which has a significant number of heritage sites, but tourism management has been weak. The main objective was achieved by surveying sequential destination choices in the site, with a total of 272 interviewed tourists. A Multi-Stop Behavior Model (MBM) was constructed to identify the factors that influence tourists’ intra-destination choice and willingness to walk (WTW). On the whole, the evidence showed that tourists prefer core-area attractions to peripheral attractions. Walking distance is the most important variable in tourists’ attraction choice. Moreover, WTWs of tourist segments showed both similarities and disparities, inspiring more pertinent strategies in line with tourists’ preferences. Policy and management implications are drawn based on the empirical findings and their effects are predicted using Monte Carlo (MC) simulation.

Effect of the Interrelation between CYP3A5 Genotype, Concentration/Dose Ratio and Intrapatient Variability of Tacrolimus on Kidney Graft Function: Monte Carlo Simulation Approach

Background: Tacrolimus (Tac) is characterized by large between- and within-patient (IPV) variability in pharmacokinetics and exposure. Aim: This study aimed to assess and validate the effect of Tac IPV and trough concentration-to-dose ratio (C0/D) over 6–12 months on reduced estimated glomerular filtration rate (eGFR) values in the late period after kidney transplantation (Tx), applying Monte Carlo (MC) simulation. Methods: The previously published linear regression was the basis for MC simulation, performed to determine how variations in significant predictors affect the distribution of eGFR from 13 to 36 months post-transplantation. The input C0/D values were derived from CYP3A5 genotype subgroups. Results: Patients characterized by high Tac IPV and low mean C0/D over 6–12 months could have been at greater risk of lower eGFR values in a three-year period following Tx compared to the other patient groups. This effect was more pronounced in patients with a lower eGFR at the 6th month and a history of acute rejection. The proven contribution of CYP3A5 expresser genotype to low C0/D values may suggest its indirect effect on long-term graft function. Conclusion: The findings indicate that simultaneous assessment of Tac IPV, C0/D, and CYP3A5 genotype may identify patients at risk of deterioration of graft function in the long-term post-transplantation period.

Simulation-Optimization Approach for the Production and Distribution Planning Problem in the Green Closed-Loop Supply Chain

With the growth of multinational companies, increasing international and domestic competition between companies, upgrading information technology, and increasing customer expectations, accurate supply chain (SC) planning is essential. In such an environment, pollution has become more severe in recent decades, and with the weakening of the environment and global warming, green SC management (GSCM) strategies have become more attention in recent decades. In this research, we consider the integrated production and distribution (PD) planning problem of a multi-level green closed-loop SC (GCLSC) system, which includes multiple recycling, manufacturing/ remanufacturing, and distribution centers. We present a three-level bi-objective programming model to maximize profit and minimize the amount of greenhouse gas emissions. A hierarchical iterative approach utilizing the LP-metric method and the non-dominated sorting genetic algorithm (NSGA-II) is introduced to solve the proposed model. Also, the Taguchi approach is applied to find optimum control parameters of NSGA-II. Moreover, Monte Carlo (MC) simulation is applied to tackle uncertainty in demand, and the NSGA-II algorithm is fusioned with MC simulation (MCNSGA-II). The results obtained show that the simulation-optimization approach presented better results than the deterministic approach.

Diaryl Sulfide Derivatives as Potential Iron Corrosion Inhibitors: A Computational Study

The present work aimed to assess six diaryl sulfide derivatives as potential corrosion inhibitors. These derivatives were compared with dapsone (4,4′-diaminodiphenyl sulfone), a common leprosy antibiotic that has been shown to resist the corrosion of mild steel in acidic media with a corrosion efficiency exceeding 90%. Since all the studied compounds possess a common molecular backbone (diphenyl sulfide), dapsone was taken as the reference compound to evaluate the efficiency of the remainder. In this respect, two structural factors were examined, namely, (i) the effect of replacement of the S-atom of diaryl sulfide by SO or SO2 group, (ii) the effect of the introduction of an electron-withdrawing or an electron-donating group in the aryl moiety. Two computational chemical approaches were used to achieve the objectives: the density functional theory (DFT) and the Monto Carlo (MC) simulation. First, B3LYP/6-311+G(d,p) model chemistry was employed to calculate quantum chemical descriptors of the studied molecules and their geometric and electronic structures. Additionally, the mode of adsorption of the tested molecules was investigated using MC simulation. In general, the adsorption process was favorable for molecules with a lower dipole moment. Based on the adsorption energy results, five diaryl sulfide derivatives are expected to act as better corrosion inhibitors than dapsone.

Dose calculation accuracy for photon small fields in treatment planning systems with comparison by Monte Carlo simulations

Purpose: Advanced radiation therapy techniques use small fields in treatment planning and delivery. Small fields have the advantage of more accurate dose delivery, but with the cost of some complications in dosimetry. Different dose calculation algorithms imported in various treatment planning systems (TPSs) which each of them has different accuracy. Monte Carlo (MC) simulation has been reported as one of the accurate methods for calculating dose distribution in radiation therapy. The aim of this study was the evaluation of TPS dose calculation algorithms in small fields against 2 MC codes. Methods: A linac head was simulated in 2 MC codes, MCNPX, and GATE. Then three small fields (0.5×0.5, 1×1 and 1.5×1.5 cm2) were simulated with 2 MC codes, and also these fields were planned with different dose calculation algorithms in Isogray and Monaco TPS. PDDs and lateral dose profiles were extracted and compared between MC simulations and dose calculation algorithms. Results: For 0.5×0.5 cm2 field mean differences in PDDs with MCNPX were 2.28, 4.6, 5.3, and 7.4% and with GATE were -0.29, 2.3, 3 and 5% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1×1 cm2 field mean differences in PDDs with MCNPX were 1.58, 0.6, 1.1 and 1.4% and with GATE were 0.77, 0.1, 0.6 and 0.9% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1.5×1.5 cm2 field mean differences in PDDs with MCNPX were 0.82, 0.4, 0.6 and -0.4% and with GATE were 2.38, 2.5, 2.7 and 1.7% for CCC, superposition, FFT and Clarkson algorithms respectively. Conclusions: Different dose calculation algorithms were evaluated and compared with MC simulation in small fields. Mean differences with MC simulation decreased with the increase of field sizes for all algorithms.

Fuzzy Fault Tree Reliability Analysis Based on Improved T–S Model with Application to NC Turret

In Takagi and Sugeno (T–S) fuzzy fault tree analysis (FFTA), the construction of T-S fuzzy gates relies too much on expert experience, which will result in inevitable subjective errors. In order to overcome this disadvantage, a new method was proposed which combined importance index with T-S fuzzy fault tree model to evaluate reliability of the events. The importance index of components can be solved through Monte Carlo (MC) simulation. The proposed method is suitable for systems where exact information on the fault probabilities of the components and the magnitude of failure and effect on system are not available. The concept and calculation method of T-S probability importance was presented. Finally, the feasibility of the method is verified by analyzing the reliability of the sealing subsystem of the NC turret and the weak links of the system are obtained by the importance analysis, which will provide data for system fault diagnosis and preventive maintenance.