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A combined experimental and molecular dynamic simulation approach was used to examine the structure and interfacial properties of solute-saturated micelles. The properties of dodecylbenzenesulfonate (DBS) micelles were examined in dodecane and benzene hydrocarbon systems. Pyrene fluorescence was used to determine the aggregation number of surfactant monomers in the micelle systems. Molecular dynamic (MD) simulations using energy minimization applying the CHARMm force field with the TIP3P model for water. Comparison of the DBS/benzene and DBS/Dodecane micelles equilibrium structures via radial distribution function (RDF) and probability distribution function (PDF) analysis indicates that the area per head group for the DBS/Benzene micelle interface is significantly larger than that of the DBS/Dodecane at the interface. It was also determined that benzene molecules can move freely within the micelle while dodecane is strictly confined in the core of the micelle. The increased interfacial area per monomer caused by the insertion of benzene also reduces the effectiveness of the surfactant, which has implications for use in various environmental applications. However, the DBS/benzene micelle can solubilize many more hydrocarbon molecules in one micelle with less surfactant monomer (i.e., lower aggregation number) per micelle due to the increased available packing positions within the micelle. This, in turn, increases the efficiency of the surfactant in real-world applications which is consistent with previous laboratory results. Understanding the differing solubilization characteristics of surfactants against various classes of hydrocarbons in single solute systems is a necessary step to beginning to understand their solubilization properties in the mixed waste systems prevalent in most surfactant enhanced remediation (SEAR) strategies. [ABSTRACT FROM AUTHOR]

The paper proposes a method that analyses the dynamic damage probability of laser systems to address the shortcomings of the quantitative model for the damage probability of laser systems. Firstly, the far-field energy density distribution model is constructed according to the power spectrum inversion method. Then, the instantaneous on-target spot power density distribution is equivalently portrayed based on the combination of the far-field power density and the missile target characteristics. Next, the instantaneous on-target spot is combined with the tracking and aiming error to obtain the probability distribution of the energy density of the long-period on-target spot. Finally, the temperature probability distribution is obtained by analyzing the relation between the target energy density and the temperature of the inner wall of the warhead. Consequently, the damage probability was calculated. The simulation shows that there is a unique maximum damage probability when the target is flying in a straight line and the laser system strikes the missile sideways. The method can provide support for the shooting timing of high-energy laser systems. [ABSTRACT FROM AUTHOR]

Thermal conductivities of polybutadiene crosslinked with sulfur as a function of the heat flux autocorrelation function by using an equilibrium molecular dynamic (EMD) simulation were investigated. The Green–Kubo method was used to calculate thermal conductivities. All simulations were performed by applying the LAMMPS software (version 3 Mar 2020) package. The united-atom force field (OPLS-UA) from the Moltemplate software (version 2.20.3) was applied in the simulations. The influence of uniform and random distributions of sulfur in polybutadiene on the final value of thermal conductivities was studied by polymeric model structures with similar and variable degrees of crosslinking. The results showed that for identical degrees of crosslinking, the distribution of crosslinkers in the polymeric model structures significantly influenced the final value of thermal conductivity. Moreover, the influence of the crosslinking degree on the final value of thermal conductivity was studied by considering polymeric model structures with different degrees of crosslinking. The results demonstrate that by having a random distribution of sulfur, the thermal conductivity will be enhanced. However, by increasing the degree of crosslinking to the higher percentage in random crosslinked model structures, the value of thermal conductivity drops significantly due to possible higher crystallization of the model structures, which decrease the degree of freedom for phonon contributions. [ABSTRACT FROM AUTHOR]

The rigid-flexible coupling cable system under large deformation is studied, and the beam element from absolute node coordinate formulation is used to establish flexible cable body of the system. Different numerical integral algorithms are discussed for solving the rigid-flexible cable system and an integration strategy which combines Implicit Euler with Minimum Residual Method (MINRES) is proposed. The influence of the position and number of rigid components and different the lengths of the flexible elements on the system dynamics are analyzed. With constant total mass of the system, higher number of rigid components and their uniform distribution contribute to stabilization of the swing of the flexible cable body. When the total length of the cable is constant, increasing the number of beam elements enhances the nonlinear characteristics of the swing motion and damages the stability. The influence of different factors on the movement of large deformation flexible cable body is obtained through modeling and simulation of the rigid-flexible coupling cable system. [ABSTRACT FROM AUTHOR]

• To reduce the occurrence of alarm floods, improved rationalization strategies are introduced to evaluate the quality and effectiveness of multivariate alarm systems developed in recent research. • Strategies demonstrated on an exothermic CSTR result in a significant reduction in nuisance alarms. • Real-time risk of the rationalized alarm systems were evaluated using dynamic risk assessment by estimating their failure probabilities using multiple dynamic simulations. • The posterior distribution, constructed for the exothermic CSTR using Bayesian statistics, had much lower variance as compared to one developed using a flat prior. In this paper, improved alarm rationalization strategies are introduced to evaluate the quality of the multivariate alarm systems developed in previous work – with the alarm thresholds and response actions modified appropriately, based on key statistical metrics. For an exothermic CSTR, our strategies resulted in a significant reduction in the number of nuisance alarms, focusing on only quality alarms, which, if ignored, are more likely to result in an abnormal shift in operation to the undesirable regions. Next, their real-time performance is evaluated using dynamic risk analysis (DRAn), in which, the associated risk is analyzed by estimating the failure probabilities of the multivariate alarm systems using Bayesian statistics, based on multiple dynamic simulations for the process, inclusive of control, alarms and response actions. As expected, the failure probability distribution developed for the exothermic CSTR has a much lower variance as compared to one developed using a flat prior distribution. [ABSTRACT FROM AUTHOR]

• A CA-based model of slope soil erosion was constructed to simulate complex spatiotemporal dynamic behaviors and processes. • A simulation model was developed for the transition between various types of soil erosion intensity. • To predict the development trend of soil erosion in different regions under different rainfall conditions. • Based on transition probability matrix and suitability map, the future trend of slope soil erosion intensity was simulated. The study of soil erosion is significant to soil and water conservation and ecological construction planning. CA, a dynamic modeling method, has been widely used to simulate the future changes of soil erosion intensity. In this study, three slopes with different vegetation patterns (uniform distribution, aggregated distribution, and random distribution) and a bare slope in the Baojiagou watershed in the Pisha sandstone area were taken as the study objects. Based on the soil erosion intensity grade maps of slopes with different vegetation patterns under the three periods of rainfall, the soil erosion intensity grade maps of the four slopes were simulated by combining multi-criteria evaluation (MCE) and Markov chain (CA-Markov). Through tests, the Kappa coefficients of the simulated maps of uniform distribution, random distribution, aggregated distribution and a bare slope reached 80.15%, 75.41%, 75.92% and 76.48%, respectively. The results revealed that the soil erosion types on slopes with different vegetation patterns were transferred differently, and fewer erosion areas were generally transferred into highly eroded ones, with moderately and slightly eroded areas as the main transfer flows. After simulating the grade map of soil erosion intensity on slopes with different vegetation patterns, it was found that the slopes with uniform and random vegetation distribution primary displayed the transfer from highly eroded areas to less eroded ones, and the sedimentary area was enlarged, while the slope with aggregated vegetation distribution and the bare slope mainly presented the transfer from less eroded areas to highly eroded ones. The sedimentary area was diminished. Therefore, compared with the bare slope, the slopes with uniform and random vegetation distribution exerted a better inhibitory effect on the soil erosion degree of hydraulically eroded slopes, and the inhibitory effect of aggregated vegetation distribution-type slope was the weakest. The study results provide critical information for planning and implementing soil conservation measures in the study area. [ABSTRACT FROM AUTHOR]

We characterize the Gaia –Enceladus–Sausage kinematic structure recently discovered in the Galactic halo using photometric metallicities from the SkyMapper survey, and kinematics from Gaia  radial velocities measurements. By examining the metallicity distribution functions (MDFs) of stars binned in kinematic/action spaces, we find that the |$\sqrt{J_R}$| versus Lz space allows for the cleanest selection of Gaia –Enceladus–Sausage stars with minimal contamination from disc or halo stars formed in situ or in other past mergers. Stars with |$30 \le \sqrt{J_R} \le 50$| (kpc km s−1)1/2 and −500 ≤ Lz  ≤ 500 kpc km s−1 have a narrow MDF centred at [Fe/H] = −1.17 dex with a dispersion of 0.34 dex. This [Fe/H] estimate is more metal-rich than literature estimates by 0.1−0.3 dex. Based on the MDFs, we find that selection of Gaia –Enceladus–Sausage stars in other kinematic/action spaces without additional population information leads to contaminated samples. The clean Gaia –Enceladus–Sausage sample selected according to our criteria is slightly retrograde and lies along the blue sequence of the high V T halo colour magnitude diagram dual sequence. Using a galaxy mass–metallicity relation derived from cosmological simulations and assuming a mean stellar age of 10 Gyr, we estimate the mass of the Gaia –Enceladus–Sausage progenitor satellite to be 108.85–9.85 M⊙, which is consistent with literature estimates based on disc dynamic and simulations. Additional information on detailed abundances and ages would be needed for a more sophisticated selection of purely Gaia –Enceladus–Sausage stars. [ABSTRACT FROM AUTHOR]

Highlights • A Gaussian process based model is constructed to simulate a complex biological system. • Model accuracy and predictive capability is compared against the neural network model. • Dynamic optimisation under uncertainty is conducted to maximise algal lutein production. • A framework to build bioprocess models with Gaussian Processes is presented. Abstract Dynamic modeling is an important tool to gain better understanding of complex bioprocesses and to determine optimal operating conditions for process control. Currently, two modeling methodologies have been applied to biosystems: kinetic modeling, which necessitates deep mechanistic knowledge, and artificial neural networks (ANN), which in most cases cannot incorporate process uncertainty. The goal of this study is to introduce an alternative modeling strategy, namely Gaussian processes (GP), which incorporates uncertainty but does not require complicated kinetic information. To test the performance of this strategy, GPs were applied to model microalgae growth and lutein production based on existing experimental datasets and compared against the results of previous ANNs. Furthermore, a dynamic optimization under uncertainty is performed, avoiding over-optimistic optimization outside of the model's validity. The results show that GPs possess comparable prediction capabilities to ANNs for long-term dynamic bioprocess modeling, while accounting for model uncertainty. This strongly suggests their potential applications in bioprocess systems engineering. [ABSTRACT FROM AUTHOR]

This paper presents a model that incorporates the impact of islanding dynamics in reliability evaluation of active distribution networks. In order to do that, the effects of the islanding process in terms of voltage and frequency variations, as well as the impact of component failures, are taken into consideration in the reliability assessment. The proposed model is based on a combination of probabilistic reliability evaluation with the dynamic simulation of the islanding process. The reliability evaluation is performed by Non-Sequential Monte Carlo simulation, while the islanding process is evaluated by a transient stability simulation with complete models of synchronous machine and its voltage and speed regulators. Results are obtained for a MV distribution test system, where the influence of dynamics in the survivability rate of islanding is incorporated into the calculation of traditional reliability indices, leading to more realistic results. [ABSTRACT FROM AUTHOR]

Abstract: Discrete-particle simulations of a gas–solid fluidized bed are used to investigate the species segregation (de-mixing) behavior of systems with continuous particle size distributions. Both Gaussian and lognormal distributions are investigated over a range of distribution widths, restitution and friction coefficients, and gas velocities. The results indicate that: (i) the average particle diameter decreases as the height within the bed increases, (ii) the level of segregation increases with an increase in the width of the particle size distribution, and (iii) segregation is attenuated as bubbling becomes more vigorous. Furthermore, the shape of the local size distribution (i.e., Gaussian or lognormal) is found to mimic that of the overall size distribution in most regions of the fluidized bed. [Copyright &y& Elsevier]