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This article introduces and formalizes a novel stochastic method that combines inverse simulation with the theory of generalized Polynomial Chaos (gPC) to solve and study inverse problems under uncertainty in energy system design applications. The method is particularly relevant to design tasks where only a deterministic forward model of a physical system is available, in which a target design quantity is an input to the model that cannot be obtained directly, but can be quantified reversely via the outputs of the model. In this scenario, the proposed method offers an analytical and direct approach to invert such system models. The method puts emphasis on user-friendliness, as it enables its users to conduct the inverse simulation under uncertainty directly in the gPC domain by redefining basic algebra operations for computations. Moreover, the method incorporates an optimization-based approach to integrate supplementary constraints on stochastic quantities. This feature enables the solution of inverse problems bounding the statistical moments of stochastic system variables. The authors exemplify the application of the proposed method with proof-of-concept tests in energy system design, specifically performing uncertainty quantification and sensitivity analysis for a Multi-Energy System (MES). The findings demonstrate the high accuracy of the method as well as clear advantages over conventional sampling-based methods when dealing with a small number of stochastic variables in a system or model. However, the case studies also highlight the current limitations of the proposed method such as slow execution speed due to the optimization-based approach and the challenges associated with, for example, the curse of dimensionality in gPC. [ABSTRACT FROM AUTHOR]

This article presents models to predict median horizontal elastic response spectral accelerations for 5% damping from earthquakes with moment magnitudes ranging from 3.5 to 7.25 occurring in the United Kingdom. This model was derived using the hybrid stochastic-empirical method based on an existing ground-motion model for California and a stochastic model for the UK that was developed specifically for this purpose. The model is presented in two consistent formats, both for two distance metrics, with different target end-users. Firstly, we provide a complete logic tree with 162 branches, and associated weights, capturing epistemic uncertainties in the depth to the top of rupture, geometric spreading, anelastic path attenuation, site attenuation and stress drop, which is more likely to be used for research. The weights for these branches were derived using Bayesian updating of a priori weights from expert judgment. Secondly, we provide a backbone model with three and five branches corresponding to different percentiles, with corresponding weights, capturing the overall epistemic uncertainty, which is tailored for engineering applications. The derived models are compared with ground-motion observations, both instrumental and macroseismic, from the UK and surrounding region (northern France, Belgium, the Netherlands, western Germany and western Scandinavia). These comparisons show that the model is well-centred (low overall bias and no obvious trends with magnitude or distance) and that the branches capture the body and range of the technically defensible interpretations. In addition, comparisons with ground-motion models that have been previously used within seismic hazard assessments for the UK show that ground-motion predictions from the proposed model match those from previous models quite closely for most magnitudes and distances. The models are available as computer subroutines for ease of use. [ABSTRACT FROM AUTHOR]

The article presents the results of the application of the stochastic method used to predict hydrocarbon-prospective geostructures of a concentric type within the Barents Sea region. According to the calculated values of stochastic parameters for the 21 geostructures of a concentric view in the waters of the Barents region, based on four different geoparameters a summary table of stochastic parameters was compiled and an encouraging forecast was made for 13 concentric geostructures promising for the search for new oil deposits within the Barents Sea region.

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Background: Gastrointestinal adenocarcinomas are a worldwide and some of the most important causes of death related to cancers. MLH1, PMS2, and K-Ras are some of the main molecules responsible for the control of cellular proliferation. They are widely used as biomarkers for the evaluation of the features of tumoral processes and the clinicopathological characteristics. They depend on the type of cells implied in the tumoral process, and it can be observed in the concentrations of them in different biological fluids. Maspin, also known as peptidase inhibitor 5 or serpin B5 is a tumor suppressor which inhibits invasion and angiogenesis and also regulates apoptosis, but it can also present oncogenic activity depending on tumor location and histology and on the subcellular maspin localization. Its correlations with gastric and colorectal carcinomas have been emphasized in a series of articles, and in this work, a method is used to quantify the concentrations of maspin in three biological fluids, allowing correlations with pathological features. Methods: Patients with their clinical and pathological features were selected from the database of the project GRAPHSENSGASTROINTES and used accordingly with the Ethics committee approval nr. 32647/2018 awarded by the County Emergency Hospital from Targu-Mures. Three kinds of samples have been analyzed (saliva, whole blood, and urine) using a stochastic method using stochastic microsensors. Results: The results obtained using stochastic sensors were correlated with the location of cancer, and there have been elaborated a series of criteria to differentiate gastric cancers from colorectal ones. Conclusions: There can be differentiation between the two types of cancers by using the concentrations of MLH1, PMS2, and K-Ras in saliva and urine samples or the levels of maspin in whole blood and urine or in whole blood, urine, and saliva. The data analysis led to a series of criteria for evaluation of the cancer location. Using only MLH1 and PMS2 concentrations in one of the two kinds of samples was only indicative and did not cover most cases. The use of the criteria only for MLH1 and PMS2 increased the probability of finding out the location, but the best results require the concentrations of K-Ras in the two kinds of samples as additional criteria. [ABSTRACT FROM AUTHOR]

The present study introduces a q-rung orthopair hesitant fuzzy stochastic method based on regret theory to capture the psychological behavior of decision makers (DMs) in decision making. For this, first, according to the score and variance function of q-rung orthopair hesitant fuzzy number (q-ROHFN), a novel group satisfaction degree is defined, which can precisely mirror the overall level and group divergence. And then, on this basis, an optimization model of criteria weights is constructed, and the Lagrange function is formulated to cope with the situation where the information about criteria weights is entirely unknown. Next, the regret value and the rejoice value are obtained by the provided regret-rejoice function, and the alternatives are ranked according to the total psychological perception values of DMs under multi-state situations. Lastly, a case study concerning stock investment is addressed to demonstrate the implantation of the provided method. Besides this, detailed sensitivity analysis and comparison with relevant literature are performed to discuss the stability and superiority of the presented method. [ABSTRACT FROM AUTHOR]

Direct numerical simulation, facilitated by the spectral element method, has been used to study collisions and agglomeration in particle‐laden fluid flows through a channel at shear Reynolds number. The particulate phase is simulated by deterministic Lagrangian particle tracking alongside a stochastic technique to resolve collisions. Interestingly, the implementation of agglomeration in the deterministic approach caused a major reduction in the particle collision rate. To determine the cause of this effect, analysis of the collision rate and location across the channel for different particle properties was performed. For systems without agglomeration, collisions between particles tend to be located on consistent streamlines, occurring between single pairs of particles. A numerical analysis of this effect confirmed the result, where inter‐particle collisions across the channel mostly took place between consistent particle pairs in close proximity. Repeat collisions are shown to be almost eliminated with the addition of the agglomeration mechanism. The impact and implications of this effect on the accuracy of the stochastic technique is discussed, and modifications are suggested to offer improvements while accounting for the repeat collisions. [ABSTRACT FROM AUTHOR]

This article provides estimates of the sea spray volume flux using joint statistics of wind and waves. This is achieved by combining the sea spray volume flux parameterization proposed by Xu et al. (2021) with the joint statistics of wind and waves provided by Bitner-Gregersen (2015). Both the sea spray volume flux formula and the joint statistics of wind and waves represent conditions for wind waves from the North-West Shelf of Western Australia. The expected value and the variance of the sea spray volume flux for a range of realistic wind and wave conditions are presented, as well as an illustrative example. Comparison is also made with data from Xu et al. (2021) showing a reasonable agreement for the relevant subset of the data.

This article addresses the effects of the air-sea drag coefficient on estimation of wind stress based on wind statistics. This is achieved by applying the same wind stress parameterizations chosen by Wrobel-Niedzwiecka et al. (2019) together with mean wind speed statistics from three locations in the North Atlantic and one location in the Northern North Sea. The expected values and the variances of the wind stress are provided. This study is complementary to that of Wrobel-Niedzwiecka et al. (2019), also demonstrating different results depending on the drag coefficient formula used.

The increased complexity of the transmission grid can endanger the operational security of the grid. Operational risk assessment, a stochastic tool, helps to enhance security. Contingency analysis and its impact quantification are the main constituents of operational risk assessment. In this study, different graphical methods are proposed to visualize operational risk contingency-based detailed results: heat-map and risk-based contingency chart. Through the heat-map, the system operator can determine which contingencies contribute most to the operational risk and would therefore be the most threatening contingencies for operational security of the grid. The "risk-based contingency chart" allows the system operator to analyze contingency cases from the probability and impact aspect in one chart. Both tools may be used in the control room for improved operational planning. In this study of contingency analysis and various types of network studies of severity factor quantification, the IEEE 39-Bus sample network is used in Power-Factory to analyze the contingencies behavior under different operational scenarios. [ABSTRACT FROM AUTHOR]

This study focuses on modeling spatial variation of earthquake ground motion using numerical methods. wave passage effect, incoherence effect and local site conditions effect are the effective parameters on this phenomenon which its investigated in simple 2D topography and 3D models near to real topography. Among the numerical methods, the BEM is a very effective tool for dynamic analysis of linear elastic bounded and unbounded media. The method is very attractive for wave propagation problems, because the discretization is done only on the boundary, requiring smaller meshes and systems of equations. Seismic behavior of the site under the S wave at different frequencies are presented. For the different points on this topography, the pattern of displacement in time domain, pattern of amplification is presented. The effective parameters on topographic amplification are time lag and amplification. To determine the coherence function after too much analysis, statistical relationships for wave frequency content and site geometry are presented. Comparing results of this relationships with real recorded samples shows good accuracy and efficiency for calculating coherence support recorded data at canyon bed and the points above that. Using this statistical relationships and amplification functions due to existing records, the possibility of generating non-uniform accelerations using one record in canyon bed is investigated.

• The effect of phase ratio of DSS was investigated using a stochastic method. • The pitting potential at different sweep velocities obeyed a normal distribution. • DSS showed better corrosion resistance when the phase ratio was 1:1. • The phase ratio affected the passive current density more significantly. The effect of the phase ratio of austenite and ferrite on the pitting potential (E pit) and passive current density of ASTM A890 grade 3A duplex stainless steel (DSS) was investigated using a stochastic method. The cumulative probability of the E pit value of DSS at different potential sweep velocities was linear, indicating that the pitting potential obeyed a normal distribution. In addition, the relationship between the pitting potential and the potential sweep velocity at various phase ratios was fitted by E pit ∝ log(v). The increase in ferrite promoted the sensitivity of the DSS to the potential sweep velocity. When the phase ratio of austenite and ferrite was 1:1, it showed better corrosion resistance. The phase ratio affected the passive current density more significantly than pitting potential. [ABSTRACT FROM AUTHOR]

In this article we investigate a family of stochastic gradient type methods for solving systems of linear ill-posed equations. The method under consideration is a stochastic version of the projective Landweberâ€"Kaczmarz method in LeitĂŁo and Svaiter (2016 Inverse Problems 32 025004) (see also LeitĂŁo and Svaiter (2018 Numer. Funct. Anal. Optim. 39 1153â€"80)). In the case of exact data, mean square convergence to zero of the iteration error is proven. In the noisy data case, we couple our method with an a priori stopping rule and characterize it as a regularization method for solving systems of linear ill-posed operator equations. Numerical tests are presented for two linear ill-posed problems: (i) a Hilbert matrix type system with over 108 equations; (ii) a big data linear regression problem with real data. The obtained results indicate superior performance of the proposed method when compared with other well-established random iterations. Our preliminary investigation indicates that the proposed iteration is a promising alternative for computing stable approximate solutions of large scale systems of linear ill-posed equations. [ABSTRACT FROM AUTHOR]

A stochastic method for modeling the lightweight aggregate concrete was proposed based on the mesoscopic components of the LWAC. The space of the material was first divided into several elements larger than the aggregate particle, and then the field of lightweight aggregate was formed in units of these elements according to a simplified function of probabilistic distribution based on Gaussian distribution. The spatial correlation was subsequently considered by modifying the aggregate field with the guidance of a correlation function and the distance between two elements. A prism made of LWAC from available literature was employed to calibrate the materials parameters necessary for finite element analysis. Then a tested column and a beam reported in the literature with a similar mixture of LWAC to the prism were modeled utilizing the proposed stochastic method. Finally, comparisons between test results and simulations were conducted. The proposed method showed an ignorable sensitivity to the element size and good precision to the performance of axial column, beam, and deep beam made of LWAC. [ABSTRACT FROM AUTHOR]

The robust design of microwave, millimeter-wave, or Terahertz components and structures incorporating manufacturing process tolerances would enhance the fabrication yield and thereby reduce the overall production cost. Based on the spectral stochastic finite element method (SSFEM) for material variations, a novel geometrical SSFEM (GSSFEM) is proposed to analyze dimensional uncertainty in 3-D microwave models. The Jacobian for Piola mapping is represented as a function of stochastic variables to capture mesh level uncertainties. Polynomial chaos expansion is used to approximate the electric field as a random process. The technique is validated by applying it to waveguide problems with uncertainty in geometric dimensions. GSSFEM results are compared with analytical formulations of the transmission coefficient for a physical insight and further with the Monte Carlo simulations for quantitative evaluation. The results using the proposed approach are in excellent agreement with conventional methods and are found to be faster than sparse grid stochastic collocation, while the scaling of the computational requirements with the number of degrees of freedom and stochastic dimension is as good as this efficient scheme. Furthermore, this approach has been employed to analyze uncertainty in multiple geometric parameters to compare their sensitivity. The proposed GSSFEM can be employed for analyzing the impact of fabrication tolerance of passive waveguide components at microwave frequencies and beyond. [ABSTRACT FROM AUTHOR]

After the discovery of the effectiveness of the stochastic methods for solving real life problems, these methods have been applied to a wide range of problems in two types; deterministic problems and stochastic problems. The general opinion takes part in applying these methods to stochastic problems since it is preferable for realistic results. Moreover, those methods can also be used in dealing with deterministic models. This study aims to show how stochastic approaches can be applied to deterministic models. Thus, an algorithm based on the Monte Carlo simulation has been presented for solving some systems of nonlinear differential equations. To discuss the behavior of such models, the population equations have been taken into consideration. The considered approach has been seen to produce more accurate results than numerical techniques. A detailed discussion about the results has also been given in this work.

Gerçek hayat problemlerini çözmek için stokastik yöntemlerin etkinliğinin keşfinden sonra bu yöntemler, deterministik ve stokastik olmak üzere iki tipteki geniş çaplı problemlere uygulanır oldular. Gerçekçi sonuçlar için tercih edilebilirliğinden dolayı bu yöntemleri stokastik problemlere uygulamak genel kanı olmuştur. Fakat bu yöntemler deterministik modellerle çalışmak için de kullanılabilir. Bu çalışma stokastik yöntemlerin deterministik modellere nasıl uygulanabileceğini göstermeyi amaçlamaktadır. Bu yüzden Monte Carlo simülasyonu temelli bir algoritma, lineer olmayan diferansiyel denklem sistemlerini çözmek için sunulmuştur. Bahsi geçen modellerin davranışlarını tartışmak için popülasyon denklemleri ele alınmıştır. Bu yaklaşımın sayısal tekniklerden daha doğru sonuçlar ürettiği görülmüştür. Bu çalışmada sonuçlar hakkında detaylı bir tartışma yapılmıştır.

With the development of traffic, many highways were built on the top of soil–rock slope (SRS). However, the effect of highway load on the SRS stability has never been studied comprehensively. Therefore, based on the statistical analysis, the stability of SRS considering additional loads of highway was studied. For generating a more realistic slope model, the identification algorithm of rock characteristic parameters was described considering rock ellipticity and long axis inclination angle; the corresponding rock contour establishing method and SRS establishing process were detailed, which could well consider rock content, ellipticity and long axis inclination angle. Applying the stochastic program, 522 stochastic numerical models and corresponding 12 physical models were created to study the influence of rock contents and long axis inclination angles on the SRS stability. The obtained results showed that the additional loads and dispersion degrees of stochastic analyzing results increased with the increase of rock contents, which were related to plastic developing modes (detour, through, scatter and contain modes) of SRS. By adjusting long axis inclination angles of rocks, it was observed that the minimum or maximum additional load was, respectively, obtained when this angle was parallel with or vertical to plastic belt. The effect of long axis inclination angles to the additional load (30.5%, 38.3% and 60.8% for 20%, 40% and 60% rock content) were concluded, which proved the necessity to consider long axis inclination angles of rocks in estimating SRS stability, especially in high rock content. According to numerical analysis results and the failure characteristic of physical models, three typical development modes of plastic belt of SRS were concluded when the load was on the top of slope, including deep, shallow and partial failure of SRS. In addition, it can also be found that the sliding body shows collapse (whole) modes when long axis inclination angles for rocks are vertical (parallel) to the plastic belt. [ABSTRACT FROM AUTHOR]

Drought risk management has gradually emerged as an important discipline and the traditional negative drought management changes to active drought management. Drought risk assessment and control are the core of drought risk management. In this study, based on precipitation anomaly (Pa) and soil moisture content anomaly index, the stochastic drought index model was established to calculate the drought distribution under different probability. Considering risk of disaster (H), vulnerability of the environment (S), exposure of the disaster bearing body (V), and disaster prevention and mitigation capability (C), a water resource optimization allocation model based on drought disaster risk assessment model was established to minimize the regional drought disaster risk. The developed models were used in Heilongjiang Province, China, and the results showed that: (1) the drought indexes based on the stochastic method can reflect the regional drought under different probabilities, providing managers with comprehensive drought information to manage the disaster; (2) the optimal allocation of water resources can reduce the risk of drought disaster in drought-prone months and drought-prone areas; and (3) studying drought risk assessment and regulation considering grain yield can be used to effectively understand and alleviate drought effects in the study area, reduce farmers' economic losses and ensure local food security. [ABSTRACT FROM AUTHOR]

The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017–2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter – the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy. [ABSTRACT FROM AUTHOR]

The urban development in Kuwait is growing rapidly in the past few years. Recently, a large number of new bridges, tall buildings and other infrastructures are constructed in Kuwait. The tallest sculptured tower in the world, the Al-Hmara tower is situated in the Kuwait city. Therefore, predicting ground motion and estimating the seismic hazard in the cities of Kuwait is of utmost importance in mitigating the seismic risk. In 1997, the Government of Kuwait assigned the task of establishing a Kuwait National Seismic Network (KNSN) to the Kuwait Institute for Scientific Research (KISR). The purpose of this network is to record seismic activity in and around Kuwait, which could help in conducting seismic hazard assessment studies. In our study, the seismic activity data recorded by KNSN was used to perform modeling and simulation of ground motion using the Stochastic Method. The most important seismic sources were identified and the largest and most powerful instrumental earthquakes were detected. Correspondingly, basic input parameters about the seismic source, path, and site effect were taken into consideration during ground motion simulation. The maximum expected magnitudes Mmax from each seismic source were also determined. The peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement (PGD) and response spectrum from both the largest recent earthquakes recorded by the Kuwait network and from the Mmax were calculated. Preliminary results obtained indicated that local induced seismic sources close to cities most affected the cities of Kuwait although they have small/moderate earthquakes compared to distant sources. [ABSTRACT FROM AUTHOR]

We performed stochastic and deterministic calculations to study simple bimolecular chemical kinetics with a neighborhood, necessary for solid‐state and viscous medium reactions. Regarding the standard deterministic method using ordinary differential equations (ODEs) to describe a bimolecular reaction with the neighborhood, we established a comparison that indicates, in this method, an implicit diffusion process. For example, the reaction is processed in a homogeneous medium, differently from the stochastic method without diffusion. The two methods coincide at the thermodynamic limit (containing little relative fluctuation) when added with the explicit diffusion process on the stochastic model. The irreversible reaction without diffusion was emulated using the ODEs of a reversible reaction, and the inherent residual concentration of the reactions with low or no diffusion occurring in solids or strong viscous media was obtained from pseudochemical equilibrium. [ABSTRACT FROM AUTHOR]

The Rouse equation is a well-known deterministic model for suspended concentrations. However, the transport of sediment particles is influenced by several random variables, such as non-uniform sediment size and turbulence structure. Experiments have demonstrated that the stochastic characteristics of turbulence structure, such as ejections and sweeps, can cause fluctuations in sediment concentrations. A new method is proposed to quantify the probabilistic sediment concentrations. In this study, the multiple-state discrete-time Markov chain and stochastic particle tracking model were used to simulate sediment transport with spatially and temporally varying probabilistic concentrations under the stochastic turbulence structure. Point estimate methods were adopted to estimate the variability of non-uniform sediment sizes. The proposed model was implemented for three cases. In the first case, the proposed model was validated against the experimental data. In the second case, spatial and temporal concentrations at high and low Rouse numbers with mean and non-uniform sediment sizes were compared. The result demonstrates that in the prediction with mean sediment sizes, the sediment concentration is overestimated near the bed, and the advection of the sediment concentration in the x-direction is underestimated. In the last case, higher-order statistical moments of the fluctuating concentrations were estimated through simulations using the proposed model. Simulation results conducted using the proposed method were compared with experimental data. The results revealed that the prediction results based on the proposed model are in good agreement with experimental data. [ABSTRACT FROM AUTHOR]

In this study, we investigate the dependencies between ground-motion intensity measures (GMIM) and earthquake magnitudes (M), in order to evaluate the dynamic stress parameter (Δσ) magnitude scaling. To achieve this, two types of datasets are used: a large subset of the NGA-West 2 (next generation attenuation) dataset including 1700 records from 426 sites and 271 earthquakes. The other datasets are generated through the stochastic method (Boore 2003) assuming various magnitude dependencies (constant and variable) of the stress parameter with magnitude. Adaptive neuro-fuzzy inference systems (ANFIS) are used to derive data-driven ground-motion prediction models (Ameur et al. 2018). Stiff soil (Vs30 > 500 m/s) data are selected and the ground-motion models are depending on two input parameters: the moment magnitude (Mw) and the hypocentral distance (Rhyp). Following Molkenthin et al. (2014), we assume that Δσ is the dominating controlling factor of GMIM for stiff site conditions at Rhyp = 30 km, at the frequency (f) = 3.33 Hz for moderate earthquakes in the magnitude range Mw = [4.5–6.5]. This study confirms that the relations between magnitude and stress parameter control the scaling of ground motions. We show that the magnitude-dependent stress drops better fit the latest generation of NGA-West 2 datasets and empirical ground-motion equations. We finally calibrate a relation between dynamic stress parameter and earthquake magnitude in the magnitude range Mw = [4.5–6.5]. [ABSTRACT FROM AUTHOR]

ABSTRACT: The goal of the present study was to assess the economic viability relating to the risk of replacing corn with pearl millet in diets with 80% concentration for feedlot cattle confined for 89 days. Replacement levels were: 0, 33, 66, and 100%. The risk was estimated using Monte Carlo simulation, Spearman’s rank correlation test between input variables, stochastic dominance, and analysis of sensitivity. The expected average values ± standard deviation for net present value (R$/animal) were ± 71.74 ± 283.32, 91.23 ± 285.18, 196.05 ± 273.79, and 223.80 ± 267.96 for diets containing 0, 33, 66, and 100% of pearl millet, respectively. The probability of ≥0 net present value was 63.4, 66.1, 78.4, and 82.4%, respectively. The net present values were statistically different (P

This study presents estimates of bedrock level peak ground motion at 2346 sites on a regular grid of 0.2° × 0.2° in northwestern (NW) Himalaya from 543 simulated sources, using the stochastic finite-fault, dynamic corner frequency method, with particular emphasis on Kashmir Himalaya. The earthquake catalogue used for simulating synthetic seismograms is compiled by including both pre-instrumental and instrumental era earthquakes of magnitude Mw ≥ 5, dating back to 260 AD. Acceleration time series thus generated are then integrated to obtain velocity and displacement time series, which are all used to construct a suite of hazard maps of the region. Expected PGA values for the Kashmir Himalaya and Muzaffarabad are found to be ~ 0.3–0.5 g and for the epicentral region of the 1905 Kangra event, to be 0.35 g. These values are consistent with other reported results for these areas e.g., Khattri et al. (Tectonophysics 108:93–134, 1984) and Parvez et al. (J Seismol, 2017. https://doi.org/10.1007/s10950-017-9682-0). The PGA values estimated in this study are in general found to be higher than those implied by the official seismic zoning map of India produced by the Bureau of Indian Standards (BIS in Indian Standard criteria for earthquake resistant design of structures part 1 general provisions and buildings (Fifth Revision), vol 1, no 5. Indian Standard, 2002). Even the acceleration-derived intensities for most regions are found to be higher compared with those observed, which apparently is due to the use of a longer duration catalogue (260 AD–2016) for simulation not covered by the observed intensity catalogue and higher magnitude ascribed to historical events. Major events in Kashmir Himalayas, such as those of 1555, 1885 and 2005, are simulated individually to allow comparison with available results. Simulated pseudo-acceleration and velocity response spectra for three sites near the 2005 Kashmir earthquake for which site conditions were available (Okawa in Strong earthquake motion recordings during the Pakistan, 2005/10/8, Earthquake, 2005. https://iisee.kenken.go.jp) are compared with observed spectra. This study provides a first-order ground motion database for safe design of buildings and other infrastructure in the NW Himalayan region. [ABSTRACT FROM AUTHOR]

Distribution feeder reconfiguration (DFR) and demand response (DR) are the common energy consumption management methods to enhance the operation quality of distribution networks (DNs). Moreover, DFR and DR may lead to system improvement through different aspects such as reliability, total cost, and power quality. Nevertheless, the high complexity of the new smart grids has caused a lot of uncertainty in the reconfiguration problem. Given that, the use of an adequate probabilistic framework is necessary to deal with such issues. Hence, the current study investigates the effect of DR on the DFR strategy in a stochastic environment as a single‐period and multiple‐objective model at peak load. A parametric probabilistic analysis is administrated based on unscented transform (UT) method to capture the load and generation uncertainties. High‐precision results and low computational burden are the outstanding features of the UT method. Furthermore, an improved version of Cuckoo search Algorithm (CSA) as an optimizing tool is proposed. The effectiveness of the suggested method is tested on the modified IEEE 32‐ and 69‐bus systems. Moreover, PDF and CDF functions of random output variables are plotted and compared to verify the proposed stochastic method. The results confirm the efficient operation of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The goal of the present study was to assess the economic viability relating to the risk of replacing corn with pearl millet in diets with 80% concentration for feedlot cattle confined for 89 days. Replacement levels were: 0, 33, 66, and 100%. The risk was estimated using Monte Carlo simulation, Spearman's rank correlation test between input variables, stochastic dominance, and analysis of sensitivity. The expected average values ± standard deviation for net present value (R$/animal) were ± 71.74 ± 283.32, 91.23 ± 285.18, 196.05 ± 273.79, and 223.80 ± 267.96 for diets containing 0, 33, 66, and 100% of pearl millet, respectively. The probability of ≥0 net present value was 63.4, 66.1, 78.4, and 82.4%, respectively. The net present values were statistically different (P<0.05), and the higher levels dominated the lower values. The items that most influenced the net present values were, in descending order, prices of unfinished and finished cattle, initial and final weights, prices of concentrate and forage, concentrate and forage consumption. Based on the results of the simulation, diet of 100% pearl millet exhibited the best economic viability. [ABSTRACT FROM AUTHOR]

The numerical simulation of the soot particle size distribution in flames is addressed by solving the balance equations for total number density and the probability density function of particle sizes, leading to a hybrid stochastic/fixed-sectional method for solving soot population balance equation. Well established models are introduced in these equations for the chemistry of PAH in ethylene combustion, for particle nucleation, growth, agglomeration and oxidation. These closures are combined with a stochastic approach, which drives the evolution of a fixed number of computational particles used to solve for the particle size distribution with a control of agglomeration and numerical roundoff error through a fixed sectional discretisation. A laminar sooting flame is simulated to compare the results against measurements and previous numerical simulations, confirming the validity of the novel approach in terms of accuracy and CPU efficiency. The relation between the mobility diameter, measured in the experiments, and the equivalent sphere diameter, introduced in the modeling, is discussed under this novel numerical framework. The influence of the fractal particle shape on the simulated particle size distribution is explored. Finally, Particle Size Distributions obtained from the hybrid method are compared to the ones obtained with a representative fixed-sectional method. [ABSTRACT FROM AUTHOR]

Optimal control of substrate feed rate in glycerolysis of vegetable oils was studied as a tool to improve monoacylglycerols (MAG) and diacylglycerols (DAG) production. Stochastic optimization strategy (Differential Evolutionary algorithm) was used to deal with the high complexity of the enzyme-catalyzed reactions dynamic behavior. Depending on the reaction system, optimal control of glycerol feed rate into the reaction showed to avoid enzymatic inhibition by the glycerol and improve acylglycerols yields up to 50% when compared to batch system. The obtained results showed that optimal control strategy can be used as an efficient tool to maximize the amount of desired product obtained by enzyme-catalyzed glycerolysis, particularly when the biocatalyst activity is significantly affected by substrate concentration. [ABSTRACT FROM AUTHOR]

After the discovery of the effectiveness of the stochastic methods for solving real life problems, these methods have been applied to a wide range of problems in two types; deterministic problems and stochastic problems. The general opinion takes part in applying these methods to stochastic problems since it is preferable for realistic results. Moreover, those methods can also be used in dealing with deterministic models. This study aims to show how stochastic approaches can be applied to deterministic models. Thus, an algorithm based on the Monte Carlo simulation has been presented for solving some systems of nonlinear differential equations. To discuss the behavior of such models, the population equations have been taken into consideration. The considered approach has been seen to produce more accurate results than numerical techniques. A detailed discussion about the results has also been given in this work. [ABSTRACT FROM AUTHOR]

Abstract We applied a stochastic method for the finite-fault modeling of strong ground motions to the 2016 Meinong, Taiwan earthquake. Newly developed attenuation models in Southern Taiwan with the frequency-dependent Q = 86.4f 0.73 and the high-frequency decay factor κ 0 were used in the synthetic model. The horizontal-to-vertical spectral ratios (HVSR) were calculated from weak motions and the Meinong mainshock and used for the site amplification correction of the synthetic waveforms produced by the stochastic ground motion simulation. Simulations incorporating the attenuation models and site correction improved the prediction of the S-wave envelope, duration, and peak ground acceleration (PGA). The nonlinear site response during the Meinong mainshock was identified by the degree of nonlinear site response (DNL), which is a summation of HVSR differences between weak motions and the Meinong mainshock as recorded by the Taiwan Strong Motion Instrument Program. The DNL showed a positive correlation with ground motion intensity. The surface site conditions influenced DNL strength. The percentage of PGA reduction calculated in this study can be an indicator of the spatial distribution of the degree of nonlinear soil effects on the Meinong earthquake in the time domain. Areas that had high levels of PGA reduction overlap with areas that had high liquefaction potential. Based on the residual analysis, forward directivity was identified in a 105° range in the northwestward direction. The amplification of forward rupture directivity was three times greater than the backward rupture directivity. Graphical Abstract .

The Ludian earthquake (MW 6.2) and Nepal earthquake (MW 7.8) are parameterized and then simulated using a new improved version of the stochastic point source method based on a proposed equivalent distance (REQL) measure. The improved method considers uniform slip distribution along the fault and is validated by comparing the simulated Fourier response spectrum. Simulated ShakeMaps of Ludian and Nepal earthquakes in terms of PGA also indicate that the results of the improved method are in good agreement with finite-fault method with high efficiency. [ABSTRACT FROM AUTHOR]

This study investigated the effect of hydrogen on reduction in area in relation to the storage time of a high carbon steel wire for C-Mn pre-stressed concrete in the context on hydrogen embrittlement of steel. The Monte Carlo Simulation method was employed for the probabilistic analysis. The concentration of hydrogen "C∞", the effective diffusion coefficient "De" these parameters were considered as random fields. The probabilistic response considered in the analysis was the reduction in area "Z". Numerical simulations that make use of second Fick's law were used for the computation of this response. A parametric study was undertaken to investigate the effect of the input and the statistical parameters of the random variables on the probability distribution functions of the response. Also, this study contributes to bring more elements of comprehension on the spatial and temporal variability of the input and output parameters. [ABSTRACT FROM AUTHOR]