Calculation of three-phase methane-ethane binary clathrate hydrate phase equilibrium from Monte Carlo molecular simulations

Methane and ethane are the simplest hydrocarbon molecules that can form clathrate hydrates. Previous studies have reported methods for calculating the three-phase equilibrium using Monte Carlo simulation methods in systems with a single component in the gas phase. Here we extend those methods to a binary gas mixture of methane and ethane. Methane-ethane system is an interesting one in that the pure components form sII clathrate hydrate whereas a binary mixture of the two can form the sII clathrate. The phase equilibria computed from Monte Carlo simulations show a good agreement with experimental data and are also able to predict the sI-sII structural transition in the clathrate hydrate. This is attributed to the quality of the TIP4P/Ice and TRaPPE models used in the simulations. (C) 2014 Elsevier B.V. All rights reserved.

Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach.

Asymptotic scaling in the two-dimensional O(3) Nonlinear sigma model: a Monte Carlo study on parallel computers

We investigate the 2d O(3) model with the standard action by Monte Carlo simulation at couplings β up to 2.05. We measure the energy density, mass gap and susceptibility of the model, and gather high statistics on lattices of size L ≤ 1024 using the Floating Point Systems T-series vector hypercube and the Thinking Machines Corp.'s Connection Machine 2. Asymptotic scaling does not appear to set in for this action, even at β = 2.10, where the correlation length is 420. We observe a 20% difference between our estimate m/Λ^─_(Ms) = 3.52(6) at this β and the recent exact analytical result . We use the overrelaxation algorithm interleaved with Metropolis updates and show that decorrelation time scales with the correlation length and the number of overrelaxation steps per sweep. We determine its effective dynamical critical exponent to be z' = 1.079(10); thus critical slowing down is reduced significantly for this local algorithm that is vectorizable and parallelizable.

We also use the cluster Monte Carlo algorithms, which are non-local Monte Carlo update schemes which can greatly increase the efficiency of computer simulations of spin models. The major computational task in these algorithms is connected component labeling, to identify clusters of connected sites on a lattice. We have devised some new SIMD component labeling algorithms, and implemented them on the Connection Machine. We investigate their performance when applied to the cluster update of the two dimensional Ising spin model.

Finally we use a Monte Carlo Renormalization Group method to directly measure the couplings of block Hamiltonians at different blocking levels. For the usual averaging block transformation we confirm the renormalized trajectory (RT) observed by Okawa. For another improved probabilistic block transformation we find the RT, showing that it is much closer to the Standard Action. We then use this block transformation to obtain the discrete β-function of the model which we compare to the perturbative result. We do not see convergence, except when using a rescaled coupling β_E to effectively resum the series. For the latter case we see agreement for m/ Λ^─_(Ms) at , β = 2.14, 2.26, 2.38 and 2.50. To three loops m/Λ^─_(Ms) = 3.047(35) at β = 2.50, which is very close to the exact value m/ Λ^─_(Ms) = 2.943. Our last point at β = 2.62 disagrees with this estimate however.

高分子溶液中物理凝胶化的Monte Carlo模拟和小角中子散射研究

高分子凝胶广泛地存在于自然界以及日常生活中，按其形成作用力不同分为化学凝胶和物理凝胶两大类。由于高分子物理凝胶具有凝胶化的可逆性及其对环境条件强烈的响应性，因此，在近半个世纪的研究与应用中受到极大的关注。高分子溶液中的物理凝胶因其结构及形成机制复杂，在实验方面，除了散射技术及流变技术能够有效地揭示它的部分信息外，其它的实验手段很难用于这个领域的研究；在理论方面，化学凝胶的理论已经比较成熟，而物理凝胶的粘弹性质以及凝胶化是一个远离平衡态的松弛过程，除了一些特征的标度指数外，人们还没有得到适用于高分子物理凝胶的普适规律。当前，由于计算机模拟理论及模拟方法的发展，使得计算机模拟成为除了实验和理论研究方法之外的第三个重要的研究方法。但是，由于物理凝胶化行为的复杂性，用实验和理论获得的信息很难较好地描述凝胶化过程，而计算机模拟的高度透明性及反映信息的完整性，有助于理解这一复杂过程中所涉及的物理本质。因此，利用计算机模拟结合实验及理论方法深入研究高分子物理凝胶的形成机制、结构与性能关系已成为目前最有效的手段之一。 本论文主要运用Monte Carlo模拟方法，并结合小角中子散射（Small-Angle Neutron Scattering, SANS）和流变（Rheology）等实验手段从多个角度探讨了以下几类典型的高分子溶液物理凝胶化行为。 1. 温度对遥爪型三嵌段共聚物在选择性溶剂中的自组装及凝胶化行为影响的研究：采用二维简单方格子Monte Carlo模拟方法，结合逾渗（Percolation）理论，建立了溶胶－凝胶转变相图在统计热力学中的确定方法；甄别了具有特征构象的链，讨论了链及胶束的聚集，明晰了相互作用（体现为约化温度）、构象转变、聚集与凝胶化的一致的关联关系；提出了构象转变模型，进而明确了此体系的凝胶化过程，在微观尺度上表现为桥型链和环型链之间的竞争。 2. 模拟模型改进及其应用到持续长度对稀溶液中高分子链构象影响的研究：考虑到原始八位置键涨落模型效率低，实现复杂且不能应用到复杂的高分子体系，对该模型进行了改进，使其实现简单、效率高，并拓宽了该模型的应用范围。然后，以刚性对均聚物构象的影响为例，发现随着刚性增加，均聚物构象从球形椭球到棒状椭球的转变，并对比了自由连接链（Free Joint Chain, FJC）模型和蠕虫链（Wormlike Chain, WLC）模型在不同刚性范围内对高分子链末端距预测的偏差，首次给出了这两个经典模型的半定量的适用边界。 3. 溶剂尺寸对遥爪型三嵌段共聚物在选择性溶剂中的自组装及凝胶化行为影响的研究：用改进后的八位置键涨落Monte Carlo模型，研究了遥爪型三嵌段共聚物在选择性溶剂条件下的聚集和凝胶化对溶剂尺寸的依赖性，发现溶剂尺寸效应对凝胶化的作用是非单调的。由一个均聚物体系的对比模拟证明这种作用主要是由熵驱动的，并给出了中分子溶剂的半定量定义。在均聚物和嵌段共聚物溶液中，不同尺寸的溶剂分子可以使溶液由于高分子聚集不同而具有不同的微结构，并影响高分子链构象和溶液的性质。从多个角度研究了三嵌段共聚物在不同尺寸溶剂的溶液中所遵循的三种不同的凝胶化机理。 4. 聚氧化乙烯－氧化丙稀－氧化乙烯三嵌段共聚物（poly(ethylene oxide)-poly (propylene oxide)-poly-(ethylene oxide), PEO-PPO-PEO）重水溶液凝胶化的小角中子散射（SANS）和Monte Carlo研究：结合Pluronic F127（EO65PO99EO65）/D2O三嵌段共聚物溶液的特征，对照SANS数据，用改进后的八位置键涨落模型成功地从模拟中获得了F127/D2O的溶胶－凝胶转变相图。详细地考察了体系的微观结构，提出此类高分子溶液中形成的物理凝胶包含高分子逾渗网络的生成，以及被束缚溶剂（Bound Solvent）必须超过离散组分体系逾渗的临界体积分数的机理。着重研究了一定浓度的F127水溶液随温度升高引起的溶胶－凝胶转变以及凝胶－溶胶转变的Reentrant相行为，发现体系在低温区域的溶胶－凝胶转变遵循相同的机理，而在中等温度和较高温度以及不同浓度区域中的凝胶－溶胶转变遵循不同的机理。 5. 极性基团饱和度和溶剂条件对两亲性聚合物在溶液中的聚集行为和凝胶化影响的研究：用改进后的八位置键涨落模型，针对两亲性聚合物在不同溶剂条件的溶液建立了粗粒化模型，以两亲性聚合物中极性基团的饱和度，溶剂条件和高分子浓度为变量，考察了其对链构象、聚集及其凝胶化的影响。 6. 多糖水溶液凝胶化的流变和小角中子散射研究：用流变和SANS考察了两个多糖水溶液中物理凝胶化过程，针对由氢键主导的水基凝胶体系的典型特征进行了讨论，从分子链构象，聚集体结构及其关联以及流变特征等方面对聚强电解质角叉胶（Carrageenan）水溶液和聚弱电解质明胶（Pectin）水溶液进行了详细的讨论。考察了不同多糖的种类（聚合物链的电荷密度），盐的种类和浓度，溶液温度等对凝胶化和凝胶结构的影响，分析了不同多糖溶液的凝胶化机理。

Effect of polydispersity on the self-assembly structure of diblock copolymers under various confined states: A Monte Carlo study

We studied the self-assembly of polydisperse diblock copolymers under various confined states by Monte Carlo simulation. When the copolymers were confined within two parallel walls, it was found that the ordered strip structures appeared alternately with the increase in wall width. Moreover, the wall width at which the ordered structure appeared tended to increase with an increase in the polydispersity index (PDI). On the other hand, the simulation results showed that the copolymers were likely to form ordered concentric strip structures when they were confined within a circle wall.

Grafting of maleic anhydride onto linear polyethylene: A Monte Carlo study

Monte Carlo simulation was used to study the graft of maleic anhydride (MAH) onto linear polyethylene (PE-g-MAH) initiated by dicumyl peroxide (DCP). Simulation results revealed that major MAH monomers attached onto PE chains as branched graft at higher MAH content. However, at extremely low MAH content, the fraction of bridged graft was very close to that of branched graft. This conclusion was somewhat different from the conventional viewpoint, namely, the fraction of bridged graft was always much lower than that of branched graft under any condition. Moreover, the results indicated that the grafting degree increased almost linearly to MAH and DCP concentrations. On the other hand, it was found that the amount of grafted MAH dropped sharply with increasing the length of grafted MAH, indicating that MAH monomers were mainly attached onto the PE chain as single MAH groups or very short oligomers. With respect to the crosslink of PE, the results showed that the fraction of PE-(MAH)(n)-PE crosslink structure increased continuously, and hence the fraction of PE-PE crosslink decreased with increasing MAH concentration.

Conveniencia económica del empleo de seguros para riesgos climáticos en la producción agrícola : un análisis mediante simulación Monte Carlo

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Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Vacancy-assisted domain-growth in asymmetric binary alloys: A Monte Carlo Study

A Monte Carlo simulation study of the vacancy-assisted domain growth in asymmetric binary alloys is presented. The system is modeled using a three-state ABV Hamiltonian which includes an asymmetry term. Our simulated system is a stoichiometric two-dimensional binary alloy with a single vacancy which evolves according to the vacancy-atom exchange mechanism. We obtain that, compared to the symmetric case, the ordering process slows down dramatically. Concerning the asymptotic behavior it is algebraic and characterized by the Allen-Cahn growth exponent x51/2. The late stages of the evolution are preceded by a transient regime strongly affected by both the temperature and the degree of asymmetry of the alloy. The results are discussed and compared to those obtained for the symmetric case.