Monte Carlo Simulations Research Articles

Reliability Genetic Algorithms Optimization RGAO Approach Based FORM and Monte Carlo Simulation: Application for Bridge Structures

Reliability Genetic Algorithms Optimization RGAO Approach Based FORM and Monte Carlo Simulation: Application for Bridge Structures

In Silico Drug Encapsulation Using 2-Hydroxypropyl-β-CD, Tyrosine Kinase and Tyrosinase Inhibition of Dinuclear Cu(II) Carboxylate Complexes

In recent years, copper carboxylate complexes have garnered significant interest for biological applications. This study focuses on 20 Cu(II) carboxylate complexes selected from our previous research. Due to the hydrophobic nature of these complexes, the 2-hydroxypropyl-β-cyclodextrin (2HPβCD) was employed as a carrier to reduce toxicity and increase solubility for controlling drug delivery. Monte Carlo calculations were performed to confirm the interaction between the optimized structures of Cu(II) complexes and 2HPβCD, forming a host-guest system. All the structures were simulated and optimized using DFT-D calculations in Material Studio 2017. The results indicated that a neutral medium is more favorable for the adsorption of these complexes into 2HPβCD. More negative binding energy values suggested strong and energetically favorable adsorption on 2HPβCD. Complexes 4, 5, and 7 exhibited the highest interaction, making them excellent candidates for drug delivery systems. DFT-D calculations were also used to investigate the release of complexes, revealing that complexes 5, 14, and 19 were difficult to release due to their lowest energy. In contrast, complexes 8, 9, and 16 were found to be most efficient to release due to weak non-covalent interactions with 2HPβCD as we can predict from binding energy obtained by DFT-D. No specific trend was observed in the interaction of the complexes with 2HPβCD. Additionally, the effects of these complexes on c-kit tyrosine kinase and Mushroom tyrosinase were studied by molecular docking. The results demonstrated that all the complexes interacted with the active site of respective receptors through hydrophobic interactions. Complexes containing 1,10-phenanthroline and 2,2-bipyrdine were identified as having a strong, spontaneous binding ability with receptors.

Investigation on the methane emissions from permeation of urban gas polyethylene pipes under the background of hydrogen-mixed natural gas transportation

Methane, a more potent greenhouse gas than carbon dioxide, aggravates the greenhouse effect of ecological environment through its emissions. When transporting hydrogen-mixed natural gas through urban polyethylene pipes, methane will be emitted due to the permeation characteristic of polyethylene pipe material. Therefore, it is crucial to pay attention to the methane emissions from permeation of polyethylene pipes for protecting the environment and climate. In this paper, the solubility and diffusion coefficients of methane within hydrogen-mixed natural gas in polyethylene pipe materials are calculated through the Monte Carlo method and molecular dynamics simulation to determine the permeation coefficient of methane. Simultaneously, the methane emissions and equivalent carbon dioxide emissions of the hydrogen-mixed natural gas in polyethylene pipes are investigated. Results indicate the methane solubility coefficient decreases with increasing temperature and hydrogen mixing ratio. The methane diffusion and permeation coefficients increase with the rising temperature and pressure, and decreasing hydrogen mixing ratio. The pressure exerts minor influence while the temperature and hydrogen mixing ratio have more significant impact. That is, the lower the temperature and the higher the hydrogen mixing ratio, the less methane emissions caused by permeation. Therefore, the effective reduction of methane emissions can be achieved by adding the insulation layer to mitigate the impact of high temperature and increasing the hydrogen mixing ratio. For example, for the polyethylene pipe with the operating pressure of 4 bar and the size specification of SDR11, when the temperature drops from 300 K to 260 K, the methane emissions of hydrogen-mixed natural gas with hydrogen mixing ratios of 0 vol%, 20 vol%, 50 vol% and 80 vol% will be drastically reduced by 73.3%, 74.4%, 77.2% and 78.5% respectively, and when 20 vol%∼80 vol% hydrogen are mixed in the natural gas at 260 K, 300 K and 310 K, the methane emissions will be effectively reduced by 26.7%∼85.6%, 23.3%∼82.1% and 23.9%∼82.4% respectively. The findings of this study can serve as guidance for reducing the methane emissions from permeation of polyethylene pipes transporting hydrogen-mixed natural gas.

Determination of the moment–rotation relation of continuous timber–concrete composite floors based on the component method

Timber–concrete composite (TCC) combines the advantages of timber and reinforced concrete construction. In multi-storey buildings, the design of TCC floors is often governed by the deformation serviceability requirements. One way to improve deformation serviceability is through the design of continuous floor systems. However, the current practice of TCC slab systems is often limited to load-carrying as single-span beams. This paper presents an analytical model based on the component method for determining the moment–rotation relation of continuous TCC slabs in the range with negative bending moments. The investigations involve the development of load–displacement curves for the individual force-transmitting components, including timber and reinforced concrete, followed by their assembly into a component model. The model has been verified using finite element calculations and the results demonstrate that the moment–rotation relation of continuous TCC systems can be accurately captured. As the variability of the material properties strongly influences the stiffness of the joint and therefore the deformation and stresses in the TCC slab, a probabilistic analysis of the material parameters was performed using the Monte Carlo method. The probabilistic investigations show that the variability of the input parameters has a significant impact on the joint stiffness, with notable scattering observed in the moment–rotation relation, especially in the range of the cracking phase of the concrete. The results from the probabilistic investigations enable initial statements about the joint stiffness of continuous timber–concrete composite slabs in ranges with negative bending moments.

Riverine sediment geochemistry and its dispersal pattern on the western Sunda Shelf

Understanding sediment provenance in continental shelf basins is essential for reconstructing paleoenvironmental changes, enhancing insights into sedimentary dynamics, and elucidating their contributions to the global carbon cycle. To decipher sediment provenances and enhance comprehension of the sediment dispersal patterns and the factors governing geochemical compositions on the Sunda Shelf, we conducted an exhaustive analysis of trace elemental concentrations and the isotopic ratios of strontium (87Sr/86Sr) and neodymium (εNd) in the silicate fractions of 35 surface sediment samples. These samples were collected from the western Sunda Shelf and its proximate major river end-members, namely, the Mekong, Rajang, Pahang, and Kelantan Rivers. Through the application of various statistical methodologies, including classical cluster analysis, Principal Component Analysis (PCA), the La-Sc-Th discrimination diagram, and an array of elemental ratios, we identified three distinct geochemical provinces on the Sunda Shelf. Each province is defined by unique geochemical signatures indicative of varied sediment sources or provenances. This distinction was primarily attributed to pronounced sediment heterogeneity, reflecting lithologic variances from the diverse river end-members. In pursuit of a holistic understanding of sediment provenance in the region, SrNd isotopic data was also integrated from prior studies encompassing the eastern Sunda Shelf and the southern South China Sea. By utilizing the SrNd mixing model, complemented with Monte-Carlo simulations, we estimated the sediment contributions from surrounding river end-members to the southern South China Sea basin. According to the model, the Mekong River emerges as the principal sedimentary source of the Sunda continental shelf and the southern South China Sea, attributed to its substantial sediment outputs. Additionally, the model has identified significant contributions from the Rajang, Pahang, and Kelantan rivers, particularly in offshore regions near their estuaries. Further, this study revealed the previously underappreciated influence of South China's rivers, namely the Red and Pearl Rivers, on the eastern Sunda Shelf and deeper southern South China Sea region beyond the continental shelf. This study not only delineates the dominant sediment sources influencing the Sunda Shelf and the South China Sea but also underscores the importance of considering a broad spectrum of river end-members to understand sedimentary dynamics in an active marine environment.

Flexural reliability of corroded RC beams strengthened with CFRP sheets considering longitudinal corrosion non-uniformity of steel bars

The corrosion of steel bars in RC beams along the longitudinal direction is usually non-uniform, thereby increasing the variabilities of failure mode and flexural behavior of corroded RC beams strengthened by CFRP sheets. This paper analyzed the flexural reliabilities of CFRP sheet-strengthened corroded RC beams, which considered the corrosion non-uniformities of longitudinal steel bars along the beam length. Based on the failure mode-based calculation method and Monte-Carlo simulation, the beams were discretized into a series of units along the beam length and the failure probabilities of the beams were considered as the failure probabilities of the serial units. Meanwhile, the occurrence probabilities of failure modes at bending failure were also studied. Parametric analysis results showed that the occurrence probabilities of failure modes were affected by steel reinforcement corrosion degrees, CFRP strengthening ratios and initial strains at concrete tensile edge. Meanwhile, the longitudinal corrosion non-uniformity could significantly affect the occurrence probabilities of different failure modes and degrade the flexural reliabilities; e.g., for RC beams under third-point bending, when the corrosion degree is 0.3, the predicted reliability index with considering longitudinal corrosion non-uniformity can be 28.3% lower than that without. The proposed reliability calculation method could accurately assess the impacts of longitudinal corrosion non-uniformity on flexural reliabilities and lay a solid foundation for calibrating design factors used in CFRP sheet-based strengthening designs, thereby contributing to both evaluating the safety of existing CFRP sheet-strengthened corroded RC beams and designing the strengthening CFRP sheets for existing corroded RC beams, which improve the safety and maintenance of existing RC structures in corrosive environments.

Analysis and optimization of cesium dynamics for the HUST negative ion source

The high-density beam in the NBI negative ion source relies on surface production on the converter with low work function, which is facilitated by cesium injection. Maintaining the appropriate cesium conditions during the source operation sequence is essential for achieving optimal cesium coverage on the converter. To better understand cesium cycle in the source and to enhance beam production performance during operation sequences, analysis of cesium dynamics and optimization of cesium operation have been carried out. The analysis model is established based on the Monte-Carlo method with cesium sources, cesium transport and surface process during the operation sequence considered. Cesium distribution and converter surface coverage can be obtained from the model using input parameters from the HUST negative ion source. For the operation in the HUST negative ion source, the influence of temperature settings and time sequence is discussed, with suggested parameters for cesium injection proposed to achieve appropriate cesium coverage on converter surface through operation sequences.

Experimental and molecular simulation study of CO2 adsorption in ZIF-8: Atomic heat contributions and mechanism

We successfully synthesised ZIF-8 using the solvothermal method at room temperature to study CO2 adsorption storage at 273 and 298 K up to 35 bar. Characterisation methods such as BET, SEM-EDS, XRD, and TGA were used to measure the physical and composition properties of ZIF-8. Grand canonical Monte Carlo (GCMC) simulation was conducted to compare with experimental data and get inside of the CO2 adsorption mechanism by calculating the isosteric heat and its fluid–fluid and solid–fluid contributions. The second was also split into fluid–solid atom contributions to understand in detail the interaction between CO2 and ZIF-8. The analyses revealed that there are three main stages during the CO2 adsorption gas–solid atom contributions, developing, pore-filling and densification. During the developing and pore-filling stages the largest fluid–solid atom contribution to the isosteric heat is CO2-C2 interactions, indicating that the CO2 is adsorbed close to the hexagonal windows of the ZIF-8 structure, while during the densification stage the largest contribution is CO2-N interactions. Where C2 and N refers to C-atom and N-atom, respectively in NCH group of the solid framework. This is because CO2 changes its orientation to be able to accommodate more molecules in the pore cavity. This work provides a better understanding of the adsorption mechanism of CO2 on ZIF-8 and shows how molecular simulation can be used to improve the understanding gas adsorption storage on metal–organic frameworks.

Sodium titanate (Na2Ti4O9) nanoribbons for effective removal of organic dyes from water: Experimental and computational studies

In this work, Na2Ti4O9 nanoribbons (NTRs) were synthesized using the hydrothermal method for its potential application in water treatment. The NTRs were characterized by X-ray diffraction, field emission scanning electron microscopy, energy dispersive X-ray spectroscopy, transmission electron microscopy, zeta potential, Fourier Transform infrared spectroscopy, and surface area analyzer. The adsorption of organic dyes, including cationic methyl green (MeG) and methylene blue (MB) model pollutants, onto the NTRs was explored for the first time. Various parameters such as pH, adsorbent dose, initial dye concentration, regeneration, contact time, the effect of temperature, and thermodynamics were studied to determine the efficiency of NTRs for removing both dyes from water. A variety of isotherm and kinetic models were applied to fit the dye adsorption data at pH 7.0, providing insights into the adsorption mechanism and process kinetics. Kinetic data for both dyes fit well with pseudo-second-order and mixed 1,2-order models. The isotherm data agreed well with Langmuir-Freundlich and Sips models. At the studied temperatures of 298.2, 318.2, and 328.2 K, the maximum adsorption capacities for MeG (353.2, 367.7, and 443.2 mg·g−1) are significantly higher than for MB (29.3, 52.6, and 67.2 mg·g−1), indicating a stronger affinity for MeG, with adsorption efficiency improving as temperature increases. The MeG samples at 328.2 K exhibited interesting behavior. After adsorption, the samples became colorless, with a final pH near 7.0, indicating effective dye removal. However, the color faintly reappeared at pH 4.0, suggesting pH-dependent behavior and incomplete dye removal. The adsorption mechanism on the NTRs surface was investigated using Monte Carlo and molecular dynamics simulations.

Real-space investigation of polarons in hematite Fe2O3.

In polarizable materials, electronic charge carriers interact with the surrounding ions, leading to quasiparticle behavior. The resulting polarons play a central role in many materials properties including electrical transport, interaction with light, surface reactivity, and magnetoresistance, and polarons are typically investigated indirectly through these macroscopic characteristics. Here, noncontact atomic force microscopy (nc-AFM) is used to directly image polarons in Fe2O3 at the single quasiparticle limit. A combination of Kelvin probe force microscopy (KPFM) and kinetic Monte Carlo (KMC) simulations shows that the mobility of electron polarons can be markedly increased by Ti doping. Density functional theory (DFT) calculations indicate that a transition from polaronic to metastable free-carrier states can play a key role in migration of electron polarons. In contrast, hole polarons are significantly less mobile, and their hopping is hampered further by trapping centers.

Mechanistic effects of graphitization and oxygen functional groups on benzene competitive adsorption of porous carbon under high humidity conditions

Porous carbon is an ideal adsorbent for the elimination of volatile organic compounds (VOCs) attributed to their price, availability and excellent adsorption capacity. However, there are significant variation in the adsorption capacity and adsorption selectivity of different precursors for VOCs under humid conditions after modification because of the differences in their own structural properties. In this study, graphitized hydrophobic porous carbon with excellent specific surface area was successfully synthesized by selecting bamboo fiber, maize, coconut husk and coal as precursors and potassium hydroxide as an activator. Among them, the dynamic adsorption capacity of benzene in the sample with bamboo fiber as precursor was maintained at 74.7% under the high humidity condition (RH90%) compared with the dry state (RH0%). Grand Canonical Monte Carlo (GCMC) simulations and weak interaction force analyses showed that enhanced dispersion attraction between graphitized carbon surfaces and benzene molecules in comparison to disordered carbon surfaces. The existence of oxygen functional groups enhanced the interaction between porous carbon and water through hydrogen bonding leading to preferential adsorption of water molecules, which resulting in the decrease of their adsorption performance in wet condition. This research provided theoretical and experimental views of the effects of graphitization and oxygen functional groups on the competitive adsorption capture of benzene and water by porous carbon, which further provided a reliable approach to synthesizing porous carbon with high adsorption capture for benzene removal in high humidity environments.

Removal of phosphate from wastewater using zirconium/iron embedded chitosan/alginate hydrogel beads: An experimental and computational perspective

Adsorptive removal of phosphate plays a crucial role in mitigating eutrophication. Herein, the Zr/Fe embedded chitosan/alginate hydrogel bead (Zr/Fe/CS/Alg) is reported as an effective phosphate adsorbent. This polymer nanocomposite is synthesized by the in-situ reduction of the metals on the polymer matrix. The synthesized adsorbent was characterized by the FTIR, SEM-EDX, TGA, BET, and XPS. The adsorbent showed a maximum phosphate adsorption capacity of 221.72 mg/g at pH 3. The experimental data fit well with the Freundlich isotherm and pseudo-second-order kinetics model, indicating a heterogeneous multilayer surface formation and a chemisorption-dominated adsorption process. Density Functional Theory (DFT) and Monte Carlo (MC) calculations revealed high negative adsorption energy due to the chemisorption of phosphate on the adsorbent. Hence, the major interactions such as electrostatic attraction, hydrogen bonding, and inner-sphere complexation of phosphate adsorption and Zr/Fe/CS/Alg hydrogel beads were investigated from the experimental and computational analysis. The negative values of thermodynamic parameters indicated a spontaneous, exothermic, and less random adsorption process. The synthesized adsorbent exhibited excellent selectivity toward phosphate and maintained 73 % efficiency after six adsorption/desorption cycles. The Zr/Fe/CS/Alg hydrogel beads reduced the phosphate concentration in real wastewater samples from 19.02 mg/L to 0.985 mg/L, suggesting that these nanocomposite hydrogel beads could be a promising adsorbent for real-world applications.

An Efficient Method for Batch Derivation of Detached Eclipsing Binary Parameters: Analysis of 34,907 OGLE Systems

Detached eclipsing binary (EB) systems are crucial for measuring the physical properties of stars that evolve independently. Large-scale time-domain surveys have released a substantial number of light curves for detached EBs. Utilizing the Physics of Eclipsing Binaries package in conjunction with Markov Chain Monte Carlo (MCMC) methods for batch parameter derivation poses significant computational challenges, primarily due to the high computational cost and time demands. Therefore, this paper develops an efficient method based on the neural network model and the stochastic variational inference method (denoted NNSVI) for the rapid derivation of parameters for detached EBs. For studies involving more than three systems, the NNSVI method significantly outperforms techniques that combine MCMC methods in terms of parameter inference speed, making it highly suitable for the batch derivation of large numbers of light curves. We efficiently derived parameters for 34,907 detached EBs, selected from the Optical Gravitational Lensing Experiment catalog and located in the Galactic bulge, using the NNSVI method. A catalog detailing the parameters of these systems is provided. Additionally, we compared the parameters of two double-lined detached EBs with those from previous studies and found the estimated parameters to be essentially identical.

An implicit unified gas-kinetic particle method with large time steps for gray radiation transport

For a long time, efficient algorithms for high-dimensional equations, represented by photon radiation transport, have been one important topic in the development of computational methods for particle transport processes. In this paper, we present an implicit unified gas-kinetic particle (IUGKP) method for multiscale gray radiative transfer. Based on the integral solution of the radiative transfer equation, the photon transport processes are categorized into non-equilibrium transport processes with a large photon free path and equilibrium transport processes with a small photon free path. The long-path processes are solved by an implicit Monte Carlo (IMC) method, and the short-path processes are solved by an implicit diffusion system. The closure formulation of photon distribution is derived from the local integral solution of the radiative transfer equation to couple the IMC and diffusion system. The improvement of the proposed IUGKP method over UGKP method is that particles can be tracked continuously instead of just until the first collision, making simulation with large time steps possible. The IUGKP method has the properties of asymptotic-preserving (AP) and regime-adaptive (RA). The AP property states that the IUGKP method converges to the consistent numerical methods for the asymptotic limiting equations of RTE in the limiting regimes. The RA property states that the computational accuracy of the IUGKP method adapts to the regimes. In this paper, the mathematical proof of the AP and RA properties is presented, and the multiscale numerical tests are performed to demonstrate the accuracy and efficiency of the IUGKP method.

Treatment for essential tremor: a systematic review and Bayesian Model-based Network Meta-analysis of RCTs

Essential tremor (ET) significantly impacts patients' daily lives and quality of life, presenting a considerable challenge in clinical practice. In recent years, novel therapeutic regimens have been investigated in randomized controlled trials (RCTs). This study aims to investigate and evaluate the relative efficacy and safety of various therapeutic interventions for ET. We did a systematic review and Bayesian Model-based Network Meta-analysis (NMA) of RCTs. Following PRISMA-NMA guidelines, a comprehensive database search was conducted up to April 1, 2024 to identify RCTs focused on ET treatments. The Bayesian Markov Chain Monte Carlo (MCMC) method was utilized for the analysis, evaluating the relative efficacy and safety of treatments using standardized mean difference (SMD) and log odds ratios (log ORs), respectively. Additionally, the Surface Under the Cumulative Ranking Curve (SUCRA) was applied to assess the relative efficacy of the treatment modalities. PROSPERO registration: CRD42023415752. This study included 33 RCTs involving 1251 patients, covering 19 oral medication treatments and six non-oral medication treatments. NMA showed that deep brain stimulation (DBS) (SMD=-4.93; 95% CI: [-7.73,-2.13]), CX-8998 (SMD=-2.69; 95% CI: [-5.26,-0.14]), atenolol (SMD=-2.36; 95% CI: [-4.70,-0.10]), and propranolol (SMD=-1.59; 95% CI: [-2.25,-0.67]) showed relative efficacy compared to placebo, with DBS demonstrating relative efficacy compared to 15 other treatment methods. However, GRADE assessment indicated that the evidence level for these conclusions was "low" or "very low." According to SUCRA rankings, DBS (0.97) ranked first in relative efficacy, followed by CX-8998 (0.80), thalamotomy (0.79), atenolol (0.76), metoprolol (0.66), propranolol (0.64), magnetic resonance guided focus ultrasound (MR-FUS) (0.624), ICI-118551 (0.620), nimodipine (0.61) and phenobarbitone (0.59). In terms of safety, as a network graph could not be constructed, DBS and thalamotomy were excluded from the NMA, while other effective treatments showed no significant differences in safety compared to placebo. Our study results indicate that CX-8998, propranolol, and atenolol demonstrate relative efficacy and safety in treating ET. DBS is effective for medication-resistant ET and ranks first in relative efficacy, though our NMA lacks safety data for DBS. Given the low overall grade of evidence, these results should be applied cautiously in clinical practice. Further large-scale, head-to-head RCTs are needed. This work was supported by grants from the National Nature Science Foundation of China (Grant No. 82271459).

Implicit modular coupled heat transfer analysis for functionally graded materials using the SVC-FMC method

Functionally graded materials have found extensive applications in the aerospace industry and solar energy systems due to their excellent performance in enhancing heat transfer/insulation. Developing corresponding theoretical frameworks for the coupled radiation and conduction heat transfer (CRCHT) is crucial for unlocking their full potential and expanding their applicability in various high-performance and critical applications. Considering the limitations of existing frameworks in addressing CRCHT problems in practical applications, such as the explicit iteration procedure and the linearization assumption, a fully implicit framework as the source value caching function Monte Carlo (SVC-FMC) method is proposed based on the null collision reverse Monte Carlo and the Green's Function Markov Superposition Monte Carlo, which are suitable for solving the radiative transfer equation and the energy equation within non-uniform media. The accuracy of the proposed method is validated with different heat transfer systems. It was observed that the maximum root mean square error during the verification process did not exceed 0.08, thereby demonstrating the efficacy of SVC-FMC in analyzing CRCHT processes involving gradient materials. Results reveal that the material properties that transcend the functional distribution form will augment the strengthening effect of heat transfer/insulation. The scattering characteristics significantly influence the strengthening effect caused by refractive index distribution.

Real-time modeling of transient crustal deformation through the quantification of uncertainty deduced from GNSS data

We propose a new method for real-time uncertainty monitoring of earthquake and volcano source models using data from the global navigation satellite system (GNSS) and explore its application concerning observation station placement. The Geospatial Information Authority of Japan operates two main types of GNSS earth observation network system (GEONET) coordinates for crustal deformation monitoring on different time scales: post-processing analysis values and real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD uses the Markov Chain Monte Carlo (MCMC) method termed real-time automatic uncertainty estimation of a coseismic single rectangular model using GNSS data (RUNE) for single rectangular fault model estimation to handle uncertainty. Thus far, no GNSS monitoring system can automatically detect transient crustal deformation events, such as volcanic activity and earthquake swarms, on timescales of a day or less. We extended RUNE and developed a core program for a new monitoring system for earthquake and volcanic source models and their uncertainties. Our program achieved automatic and stable MCMC utilization for rectangular fault, dike, Mogi, and spheroid models by increasing the computational speed, improving search efficiency, and adjusting hyperparameters. The program automatically determines the standard deviation of the likelihood function assuming a normal distribution with weights for each observation station. The calculation time was within 15 s for 1 × 106 samples on a standard 1U server. We assessed the reliability of the developed method using synthetic and observed GNSS data from the 2015 Sakurajima volcanic event. The results were consistent with the assumed model and previous studies and indicated an advantage in automatically quantifying uncertainty in a short computation time. Based on MCMC samples, we developed a new visualization algorithm to indicate areas on a map in which the number of observation stations should be expanded. We assessed the reliability using data from the 2023 Noto Peninsula earthquake [Mj 6.5]. The results indicate that the algorithm is helpful in studying the placement of stations. The above model extensions and their application are essential to achieve a rapid quantitative understanding of disaster events near urban areas and for utilizing this information in emergency response activities.Graphical

Stochastic Nonlinear Model Updating in Structural Dynamics Using a Novel Likelihood Function within the Bayesian-MCMC Framework

The study presents a novel approach for stochastic nonlinear model updating in structural dynamics, employing a Bayesian framework integrated with Markov Chain Monte Carlo (MCMC) sampling for parameter estimation by using an approximated likelihood function. The proposed methodology is applied to both numerical and experimental cases. The paper commences by introducing Bayesian inference and its constituents: the likelihood function, prior distribution, and posterior distribution. The resonant decay method is employed to extract backbone curves, which capture the non-linear behaviour of the system. A mathematical model based on a single degree of freedom (SDOF) system is formulated, and backbone curves are obtained from time response data. Subsequently, MCMC sampling is employed to estimate the parameters using both numerical and experimental data. The obtained results demonstrate the convergence of the Markov chain, present parameter trace plots, and provide estimates of posterior distributions of updated parameters along with their uncertainties. Experimental validation is performed on a cantilever beam system equipped with permanent magnets and electromagnets. The proposed methodology demonstrates promising results in estimating parameters of stochastic non-linear dynamical systems. Through the use of the proposed likelihood functions using backbone curves, the probability distributions of both linear and non-linear parameters are simultaneously identified. Based on this view, the necessity to segregate stochastic linear and non-linear model updating is eliminated.

Constraining the equation of state parametrization in Hořava-Lifshitz gravity

In this paper, we investigate the late-time cosmic accelerated expansion using various equations of state parametrizations within the framework of Hořava-Lifshitz gravity. We utilize Markov Chain Monte Carlo (MCMC) analysis to constrain the parameters of each proposed model, employing observational Hubble data and Type Ia supernovae. Additionally, we analyze and plot the deceleration parameters for each model. Our findings suggest that the Universe has recently transitioned from a phase of deceleration to acceleration in all the models considered. We also analyzed the behavior of the energy conditions for each proposed model within the framework of Hořava-Lifshitz gravity, specifically at the present epoch (z=0). To further assess the effectiveness of these models, we apply both the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) to compare their performance against the standard ΛCDM model. Our results provide valuable insights into how different models perform relative to ΛCDM, offering a comprehensive evaluation of their viability in describing the Universe's accelerated expansion.

Reliability and Sensitivity Analysis of Composite All-Movable Fin Flutter

Uncertainties widely existing in composite aircraft structures make flutter reliability and sensitivity analysis highly necessary. In this work, a probabilistic approach is proposed for reliability and sensitivity analysis of composite all-movable fin flutter. To be specific, an adaptive method based on basis-adaptive polynomial chaos expansion (PCE) is developed to estimate the probability of failure, and the basis-adaptive PCE-based Sobol indices are used for measuring the contributions of input variables to the reliability over their entire uncertainty ranges. A composite beam and a composite plate are analyzed to test the accuracy and efficiency of the proposed approach. The finite element model of composite all-movable fin flutter is approximated by the basis-adaptive PCE model, which is adaptively updated by the FBR learning function. The weighed K-means strategy is added to accelerate the convergence speed and reduce the number of iterations. Then the basis-adaptive PCE model is combined with numerical simulation for reliability and sensitivity analysis of composite all-movable fin flutter. Based on the results of Monte Carlo simulation, compared with adaptive support vector regression, kriging, and the traditional PCE method, it is found that the accuracy and effectiveness of the proposed method are the best for reliability and sensitivity analysis of composite all-movable fin flutter.