Combining Monte Carlo Simulations Research Articles

Combined multi-objective optimization and robustness analysis framework for building integrated energy system under uncertainty

The optimal design of building integrated energy system is sensitive to the variation of uncertain parameters. For addressing the tradeoff of uncertainty and optimality-robustness, this study proposes a combined multi-objective optimization and robustness analysis framework for optimal design of building integrated energy system. The proposed framework includes two parts. In the optimization part, on the basis of scenario generation for capturing the uncertainties of renewable energy sources and energy demands, two-stage multi-objective stochastic mixed-integer nonlinear programming is conducted to optimize the system‘s economic and environmental objectives. Two decision-making methods are introduced to identify the final optimum solution from the obtained Pareto frontier. In the robustness-analysis part, a combined Monte Carlo simulation and optimization method is implemented to verify the robustness of the optimal solutions. The two parts of the framework are integrated to investigate the case of a hotel in Beijing, China. The results indicate that compared with the stochastic model, the deterministic model underestimates the annual total cost. Achieving economic and environmental optimum is conflicting and needs a trade-off through decision making. Moreover, in the robustness analysis, an acceptable robustness value is identified, considering both the selected objectives and the operation constraints’ probability of failure. The Shannon-entropy-based final optimum solution exhibits the best comprehensive performance, with an annual total cost of $695 × 103/year, an annual carbon emissions of 2100 tons/year, and an 8.81% probability of failure.

C2H4 and C2H6 adsorption-induced structural variation of pillared-layer CPL-2 MOF: A combined experimental and Monte Carlo simulation study

Coordination pillared-layer metal-organic frameworks (CPL-MOFs), such as CPL-2, are interesting versatile and porous materials with the potential for gas adsorption and separation. CPL-2 shows the unusual and gradual linker rotation upon the adsorption of ethylene (C2H4) and ethane (C2H6), leading to a fully reversible adsorption isotherm specifically under the conditions studied. Grand canonical Monte Carlo (GCMC) simulations showed that it is impossible to accommodate the experimentally observed loadings of C2H4 and C2H6 in CPL-2 using the crystallographic structure reported in the literature. According to the simulation findings, the pore expansion might be initiated by the clockwise 4,4'-bipyridine (bpy) pillar linker rotation. The pillar rotation leads to the enlarged pore volume, rendering additional adsorption sites, which are not present in the pristine structure. In situ synchrotron PXRD experiments for C2H4 and C2H6 adsorption on CPL-2 confirmed the occurrence of pore expansion in CPL-2 MOF. The combined experimental and simulation study shows for the first time that the linker rotation in CPL-2 can result in a adsorption isotherm without hysteresis. This work developed a real insight into the nature of pillared-layer MOFs, and the revealed structural changes could be potentially exploited to enhance alkene and alkane working capacities of such microporous materials.

Adsorption of CO and desorption of CO2 interacting with Pt (111) surface: a combined density functional theory and Kinetic Monte Carlo simulation

The adsorption of CO and desorption of CO2 interacting with the Pt (111) surface was investigated using Kinetic Monte Carlo (kMC) simulation. The processes involved an elementary oxidation/reduction reaction (ORR). In comparison with standard density functional theory (DFT), kMC can simulate systems at practical time scale since it is concerned with the elementary reactions of the CO and O2 molecules adsorbed in the surface of the Pt system. The DFT results provide reliable estimates for adsorption and desorption energy barriers. The standard Arrhenius' equation serves as a working model to define the temperature dependence of individual elementary reaction rates (k). By incorporating the proper k obtained from DFT calculations into the kMC simulations, the study was able to reproduce acceptable result in agreement with practical microscopic reaction step occurring in the exhaust of gasoline engines. Thus, the kMC provides useful insight in the involved ORR steps in the interaction of CO and O2 with Pt. The ORR is sensitive to O–O dissociation compared with CO adsorption

Bayesian combined forecasts and Monte Carlo simulations to improve inflation rate predictions in Romania

In this paper we applied the regression approach and Bayesian inference to obtain more accurate forecasts of the inflation rate in the case of the Romanian economy. The necessity of using the most accurate forecasts for the inflation rate is required by the realisation of economic criteria for the accession to the eurozone and by the inflation targeting strategy of the National Bank of Romania. Considering the assumption that simple econometric models provide better forecasts than complex models, in this paper we combined various forecasts from individual models using as prior information the expectations of experts. The empirical findings for Romanian inflation rate forecasts over the horizon of 2016-2018 indicated that a fixed effects model performed better than other simple models (autoregressive moving average model, dynamic model, simple and multiple linear model, VAR, Bayesian VAR, simultaneous equations model). The Bayesian combined forecasts that used experts’ predictions as priors, with a shrinkage parameter tending to infinity, improved the accuracy of all predictions using individual models, outperforming also naive forecasts and zero and equal weights forecasts. However, predictions based on Monte Carlo simulation outperformed all the scenarios in terms of the mean error and mean absolute error.

Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk.

In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.

Line sampling-based local and global reliability sensitivity analysis

Local reliability sensitivity (RS) and global RS can provide useful information in reliability-based design optimization, but the algorithm for solving them is still a challenge, especially in case of small failure probability and high dimensionality. In this paper, a novel method by combining Monte Carlo simulation (MCS) with line sampling (LS), an efficient method for estimating small failure probability in case of the high dimensionality, is proposed to evaluate local RS and global RS simultaneously. Since the proposed method employs LS samples to approximately screen out the failure samples from the MCS sample set, the proposed method possesses both the efficiency of the LS and the accuracy of the MCS. One numerical example and two engineering examples illustrate the accuracy and the efficiency of the proposed method.

Simulations of the effect of diffusion on asymmetric spin echo based quantitative BOLD: An investigation of the origin of deoxygenated blood volume overestimation

Quantitative BOLD (qBOLD) is a technique for mapping oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) in the human brain. Recent measurements using an asymmetric spin echo (ASE) based qBOLD approach produced estimates of DBV which were systematically higher than measurements from other techniques. In this study, we investigate two hypotheses for the origin of this DBV overestimation using simulations and consider the implications for experimental measurements. Investigations were performed by combining Monte Carlo simulations of extravascular signal with an analytical model of the intravascular signal. Hypothesis 1DBV overestimation is due to the presence of intravascular signal which is not accounted for in the analysis model. Intravascular signal was found to have a weak effect on qBOLD parameter estimates. Hypothesis 2DBV overestimation is due to the effects of diffusion which are not accounted for in the analysis model. The effect of diffusion on the extravascular signal was found to result in a vessel radius dependent variation in qBOLD parameter estimates. In particular, DBV overestimation peaks for vessels with radii from 20 to 30 μm and is OEF dependent. This results in the systematic underestimation of OEF. ImplicationsThe impact on experimental qBOLD measurements was investigated by simulating a more physiologically realistic distribution of vessel sizes with a small number of discrete radii. Overestimation of DBV consistent with previous experiments was observed, which was also found to be OEF dependent. This results in the progressive underestimation of the measured OEF. Furthermore, the relationship between the measured OEF and the true OEF was found to be dependent on echo time and spin echo displacement time.The results of this study demonstrate the limitations of current ASE based qBOLD measurements and provide a foundation for the optimisation of future acquisition approaches.

Modeling the impacts of coastal land use changes on regional carbon balance in the Chiku coastal zone, Taiwan

The Chiku coastal zone in Taiwan is characterized by dynamic aquaculture and tourism sectors around the lagoon ecosystem. Recent research efforts focused on the carbon absorption capacity and the interactions between the aquaculture industry and the lagoon. Further exploring land use dynamics in Chiku would enable integration of the findings of these studies into a more comprehensive framework of analysis and would improve estimation of the regional carbon balance. We built a system dynamics model to simulate land use change in this area. This model describes the long-term impact of human activities in the area, mimics their synchronous development in the long term, and thereby provides a basis for estimating the overall carbon balance of the area by combining Monte Carlo simulation and decision tree analysis. Our results suggest that the carbon absorption capacity can be sustainably enhanced by appropriate management actions, such as market prices stabilization for aquaculture and agriculture products and/or the limitation of constructed land development.

Wind Energy Generation Assessment at Specific Sites in a Peninsula in Malaysia Based on Reliability Indices

This paper presents a statistical analysis of wind speed data that can be extremely useful for installing a wind generation as a stand-alone system. The main objective is to define the wind power capacity’s contribution to the adequacy of generation systems for the purpose of selecting wind farm locations at specific sites in Malaysia. The combined Sequential Monte Carlo simulation (SMCS) technique and the Weibull distribution models are employed to demonstrate the impact of wind power in power system reliability. To study this, the Roy Billinton Test System (RBTS) is considered and tested using wind data from two sites in Peninsular Malaysia, Mersing and Kuala Terengganu, and one site, Kudat, in Sabah. The results showed that Mersing and Kudat were best suitable for wind sites. In addition, the reliability indices are compared prior to the addition of the two wind farms to the considered RBTS system. The results reveal that the reliability indices are slightly improved for the RBTS system with wind power generation from both the potential sites.

Economic performance and risk of farming systems specialized in perennial crops: An analysis of Italian hazelnut production

Assessing farm profitability and economic risk is important to support farmers' decisions. Several factors affect yields and product prices, in turn influencing farmers' income level and economic risk. However, the literature has often neglected to explicitly account for the role of product quality. This is particularly important for crops such as hazelnut because farmers' prices vary according to the quality of the harvested product. Furthermore, it seems fundamental to disentangle the role of parameters influencing farm results, noticeably yield, product price and quality. This is because farmers select their risk management tools to satisfy their needs, but these are often suitable for managing the risk of only one of these parameters.Deploying a large sample of individual farm data over ten years, the profitability and risk of hazelnut production in the four main production areas in Italy are assessed. The analysis is performed by using a set of risk indicators, which are based on the distribution of the gross margin for hazelnuts. The results of this analysis suggest that Campania and Lazio are generally the most profitable regions while Sicily is the least profitable. Risk is quite high in all regions with Campania facing the lowest risk level. The sensitivity analysis, performed by combining Monte Carlo simulations and stepwise regression techniques, permits to establish that the most important parameter generating risk is yield, followed by product quality and, to a lesser extent, market price. These results suggest that hazelnut farmers could reduce their risk by using production insurances; there is also potential to develop tools suited to managing risks related to product quality.

Investigating CO2 Sorption in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) through Computational Studies

A combined Monte Carlo (MC) simulation and periodic density functional theory (DFT) study of CO2 sorption was performed in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn), a family of hybrid ultramicroporous m...

Regulating Second-Harmonic Generation by van der Waals Interactions in Two-dimensional Lead Halide Perovskite Nanosheets.

The flexible organic amine cations on the interfaces of two-dimensional (2D) hybrid organic-inorganic perovskite nanosheets could form relaxed structures, which would lead to exotic optoelectronic properties but are hard to understand. Here, the unusual interfacial relaxation of nanosheets exfoliated from an orthorhombic 2D lead halide perovskite, [(C6H5CH2NH3)2]PbCl4, is interrogated via ultrafast second-harmonic generation (SHG) spectroscopy. The in-plane SHG intensity anisotropy of these nanosheets is found to decrease with reducing layer thickness. Combined first-principles calculations and Monte Carlo simulations reveal that the induced second-order polarization arises primarily from the (C6H5CH2NH3)+ cations; and these organic amine cations form significantly reorganized conformations with decreasing nanosheet thickness due to weakened van der Waals interactions. Because the orientations of organic components at the interface determine their electric properties and specifically the dipolar susceptibility, the resulting structure leads to striking changes in the SHG properties.

Validation of combined Monte Carlo and photokinetic simulations for the outcome correlation analysis of benzoporphyrin derivative-mediated photodynamic therapy on mice.

.We compare previously reported benzoporphyrin derivative (BPD)-mediated photodynamic therapy (PDT) results for reactive singlet oxygen concentration (also called singlet oxygen dose) on mice with simulations using a computational device, Dosie™, that calculates light transport and photokinetics for PDT in near real-time. The two sets of results are consistent and validate the use of the device in PDT treatment planning to predict BPD-mediated PDT outcomes in mice animal studies based on singlet oxygen dose, which showed a much better correlation with the cure index than the conventional light dose.

A Hybrid Monte Carlo Simulation and Multi Label Classification Method for Composite System Reliability Evaluation

This paper presents a new approach for reliability evaluation of composite power systems by combining Monte Carlo simulation and multi label k-nearest neighbor (MLKNN) algorithm. MLKNN is a classification technique in which target vector of each instance is assigned into multiple classes. In this paper, MLKNN is used to classify states (failure or success at system or bus level) of a complete power system without requiring optimal power flow (OPF) analysis, except in the training phase. As a result, the computational burden to perform OPF is reduced dramatically. For illustration, the proposed method is applied to the IEEE 30 BUS Test System and IEEE Reliability Test System. The obtained results from various case studies demonstrate that MLKNN based reliability evaluation provides promising results in both classification accuracy and computation time in evaluating the composite power system reliability.

Secondary Fluorescence Correction for Characteristic and Bremsstrahlung X-Rays Using Monte Carlo X-ray Depth Distributions Applied to Bulk and Multilayer Materials

Secondary fluorescence effects are important sources of characteristic X-ray emissions, especially for materials with complicated geometries. Currently, three approaches are used to calculate fluorescence X-ray intensities. One is using Monte Carlo simulations, which are accurate but have drawbacks such as long computation times. The second one is to use analytical models, which are computationally efficient, but limited to specific geometries. The last approach is a hybrid model, which combines Monte Carlo simulations and analytical calculations. In this article, a program is developed by combining Monte Carlo simulations for X-ray depth distributions and an analytical model to calculate the secondary fluorescence. The X-ray depth distribution curves of both the characteristic and bremsstrahlung X-rays obtained from Monte Carlo program MC X-ray allow us to quickly calculate the total fluorescence X-ray intensities. The fluorescence correction program can be applied to both bulk and multilayer materials. Examples for both cases are shown. Simulated results of our program are compared with both experimental data from the literature and simulation data from PENEPMA and DTSA-II. The practical application of the hybrid model is presented by comparing with the complete Monte Carlo program.

Acridine-based thiosemicarbazones as novel inhibitors of mild steel corrosion in 1 M HCl: synthesis, electrochemical, DFT and Monte Carlo simulation studies.

Electrochemical, surface morphology, density functional theory and Monte Carlo simulation methods were employed in investigating the effects of (2E,2′E)-2,2′-(3,3,6,6-tetramethyl-9-phenyl-3,4,6,7-tetrahydroacridine-1,8(2H,5H,9H,10H)-diylidene)bis(N-phenylhydrazinecarbothioamide) (IAB-NP), (2E,2′E)-2,2′-(3,3,6,6-tetramethyl-9-phenyl-3,4,6,7-tetrahydroacridine-1,8(2H,5H,9H,10H)-diylidene)bis(N-(2,4-difluorophenyl)hydrazinecarbothioamide)IAB-ND) and (2E,2′E)-2,2′-(3,3,6,6-tetramethyl-9-phenyl-3,4,6,7-tetrahydroacridine-1,8(2H,5H,9H,10H)-diylidene)bis(N-(2-fluorophenyl) hydrazinecarbothioamide) (IAB-NF) on mild steel corrosion in 1 M HCl solution. From the studies, compounds IAB-NP, IAB-ND and IAB-NF inhibit mild steel corrosion in the acid and the protection efficiencies were found to increase with the increase in concentration of each compound. At the optimum inhibitor concentration of 1.5 × 10−4 M, the inhibition efficiencies (%) of the compounds are in the order IAB-NF (90.48) > IAB-ND (87.48) > IAB-NP (85.28). Potentiodynamic polarization measurements revealed that all the compounds acted as mixed-type corrosion inhibitors. Experimental data for the adsorption of the studied molecules on a mild steel surface in 1 M HCl fitted into the Langmuir adsorption isotherm and the standard free energies of adsorption (ΔGoads) suggested both physisorption and chemisorption mechanisms. Scanning electron microscopy analyses confirmed the formation of a protective film on the mild steel surface by the inhibitor molecules, resulting in protection of the metal from corrosive electrolyte ions. The experimental findings were corroborated by both theoretical density functional theory and Monte Carlo simulation studies.

RGB Camera-Based Imaging of Oxygen Saturation and Hemoglobin Concentration in Ocular Fundus

We propose a red, green, blue (RGB)-based oximetry to assess the ocular fundus and determine its oxygen saturation (SO2) and hemoglobin concentration. The oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, and SO2 were estimated employing a method that combines Monte Carlo simulation of light transport in the fundus tissue with a multiple regression analysis. In this study, a single-layer model of the ocular fundus was employed for the Monte Carlo simulation. We constructed an experimental apparatus for measuring the fundus of a rat's eye using an RGB detector and investigated the physiological response that occurs upon a change in the fraction of inspired oxygen (FiO2). The resultant images of oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, total hemoglobin concentration, and SO2 indicated that the response was caused by the defective oxygenation of the blood. The results of the present study indicate the possibility of oximetry based on the RGB images of a fundus.

Full energy peak efficiency calibration for the assay of large volume radioactive waste drums in a segmented gamma scanner

Large volume radioactive waste drums with low/intermediate level of alpha activity, generated in radiochemical laboratories, are in general screened for special nuclear materials (SNM) in a segmented gamma scanner (SGS) before disposal. The assay methodology traditionally requires a standard drum of identical geometry and thereby making the procedure relying on the availability of a true standard, which is often difficult to organize. Here, we report a non-conventional absolute segmented gamma scanning (ASGS) methodology for the assay of 200 L waste drums, avoiding the use of a standard drum. The present analysis employ the full energy peak (FEP) efficiency, ingeniously determined using a standard 152Eu point source. From combined experiment and Monte Carlo simulation, it has been established that, the FEP efficiencies of the detector for a 200 L cylindrical sample can be well reproduced using a point source. While verifying the applicability of the point source FEP efficiencies for the assay of plutonium in 200 L drums, an energy dependent bias has been seen, which confirms the presence of lump attenuation in addition to the general matrix attenuation. An infinite energy extrapolation of apparent mass approach has been adopted for the assay of large volume waste drums which takes care of the gamma-ray attenuation from all sources that is otherwise difficult to correct for in a sample drum of unknown history.

Capacitive Organic Anode Based on Fluorinated-Contorted Hexabenzocoronene: Applicable to Lithium-Ion and Sodium-Ion Storage Cells.

Conducting polymer‐based organic electrochemical capacitor materials have attracted attention because of their highly conductive nature and highly reversible redox reactions on the surface of electrodes. However, owing to their poor stabilities in aprotic electrolytes, alternative organic electrochemical capacitive electrodes are being actively sought. Here, fluorine atoms are introduced into contorted hexabenzocoronene (cHBC) to achieve the first small‐molecule‐based organic capacitive energy‐storage cells that operate at high current rates with satisfactory specific capacities of ≈160 mA h g−1 and superior cycle capabilities (>400) without changing significantly. This high capacitive behavior in the P21/c crystal phase of fluorinated cHBC (F—cHBC) is caused mainly by the fluorine atoms at the end of each peripheral aromatic ring. Combined Monte Carlo simulations and density functional theory (DFT) calculations show that the most electronegative fluorine atoms accelerate ion diffusion on the surface to promote fast Li+ ion uptake and release by an applied current. Moreover, F—cHBC has potential applications as the capacitive anode in Na‐ion storage cells. The fast dynamics of its capacitive behavior allow it to deliver a specific capacity of 65 mA h g−1 at a high current of 4000 mA g−1.

Sensitivity analysis of potential capacity and safety of flow corridor to self-separation parameters

ABSTRACTA flow corridor is a new class of trajectory-based airspace that encloses groups of flights which fly along the same path in one direction and accept responsibility for separation from each other. A well-designed corridor could reduce the airspace complexity, decrease the workload of air traffic controllers and increase the airspace capacity. This paper analyses the impact of different self-separation parameters on capacity and conflicts of the flow corridor. Both the quantitative impact and interaction effects of pairs of parameters are evaluated using the combined discrete-continuous model and Monte Carlo simulation method. The simulation results show that although the initial separation is the dominating factor, the interactions between initial separation and separation buffer, minimum separation, extra switch buffer, extra threshold buffer and velocity difference threshold also have some significant impacts on the capacity and conflicts for the flow corridor.