Simple Modeling Approach Research Articles

Mendelian randomization study investigating the relationship between nutrients and polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) affects many women and is linked to nutrient intake, but the causal role of nutrients is unclear. Our study used Mendelian randomization (MR) to explore this relationship. We employed two-sample MR to investigate the causal effects of four macronutrients (carbohydrates, fats, sugars, proteins) and 12 micronutrients (vitamin A [retinol], folate, vitamin B6, vitamin B12, vitamin C [ascorbic acid], vitamin D, vitamin E [alpha-tocopherol], magnesium, calcium, iron, selenium, and zinc) on the risk of PCOS based on their circulating levels. We conducted analyses using the inverse variance-weighted method (IVW), MR-Egger regression, weighted median method, and simple model approach, with IVW as the primary method. To correct for multiple testing, the false discovery rate (FDR) method was applied. The reliability and potential bias of the results were assessed by sensitivity analysis and F-statistics. From a genetic standpoint, higher circulating vitamin A (retinol) levels were found to be a protective factor for PCOS and closely associated with the risk of PCOS, consistent with recent research findings. The inverse variance-weighted (IVW) estimation indicated a protective effect of vitamin A (retinol) on PCOS (IVWOR = 0.97, 95% CI: 0.95-0.99, P = 0.002, FDR_P = 0.03). However, no causal relationship was found between other nutrients and PCOS. In addition, MR-PRESSO and MR-Egger regression showed that our results were not affected by horizontal pleiotropy (P > 0.05). Finally, leave-one-out sensitivity analysis confirmed the robustness of MR Results. Our findings suggest that circulating vitamin A (retinol) levels influence the risk of PCOS, but further research is needed.

Frequency-dependent phase entrainment of cortical cell types during tACS: computational modeling evidence.

Transcranial alternating current stimulation (tACS) enables non-invasive modulation of brain activity, holding promise for clinical and research applications. Yet, it remains unclear how the stimulation frequency differentially impacts various neuron types.
Here, we aimed to quantify the frequency-dependent behavior of key neocortical cell types. We used both detailed (anatomical multicompartments) and simplified (three compartments) single-cell modeling approaches based on the Hodgkin--Huxley formalism to study neocortical excitatory and inhibitory cells under various-amplitude tACS frequencies within the 5-50 Hz range at rest and during basal 10 Hz activity. L5 pyramidal cells exhibited the highest polarizability at DC, ranging from 0.21 to 0.25 mm and decaying exponentially with frequency. Inhibitory neurons displayed membrane resonance in the 5-15 Hz range with lower polarizability, although bipolar cells had higher polarizability. Layer 5 PC demonstrated the highest entrainment close to 10 Hz, which decayed with frequency. In contrast, inhibitory neurons entrainment increased with frequency, reaching levels akin to PC. Results from simplified models could replicate phase preferences, while amplitudes tended to follow opposite trends in PC. tACS-induced membrane polarization is frequency-dependent, revealing observable resonance behavior. Whilst optimal phase entrainment of sustained activity is achieved in PC when tACS frequency matches endogenous activity, inhibitory neurons tend to be entrained at higher frequencies. Consequently, our results highlight the potential for precise, cell-specific targeting for tACS.

Modeling local scour around complex bridge supports using CFD and a shear-stresses-based simplified approach

This study presents a simplified numerical modeling approach that estimates the local scour depths around bridge supports based on the bed shear stresses. It is developed using 3D computational fluid dynamics and coding through ANSYS workbench scripting along with C++ language. The proposed model is called SCFDS (Simplified Computational Fluid Dynamics Scour). The model’s main idea is to lower the bed bathymetry at the locations affected by flow obstruction until the shear stresses reach stable target values. The developed model is assessed by applying it to a complex pier of a real bridge over the Nile-River, and its scour data is calculated using the Hec-18 empirical equations. The outcomes of the model’s assessment show that it can depict the local scour around complex bridge supports. The developed approach is a novel and efficient tool that can help the designers in simulating local scour in the vicinity of flow obstructions. However, more verification studies are necessary to reach a generalized conclusion.

Explanation of the excesses in associated di-photon production at 152 GeV in 2HDM

Statistically significant excesses exist at around 152 GeV in associated di-photon production (γγ + X) in the sidebands of SM Higgs analyses of ATLAS (using the full run-2 dataset). They are most pronounced in the single-τ, missing-transverse-energy, four-jet and ⩾ 1ℓ+ ⩾ 1b-jet channels (≈ 3σ) and can be explained by the Drell-Yan production of new Higgs bosons, i.e. pp → W*→ H±H0. We first examine the excesses in a simplified model approach, considering that H± decays to τν, WZ or tb. Both the τν and tb decay modes individually lead to a significance of ⪅ 4σ while for WZ one can obtain at most 3.5σ. This is because the decays of WZ lead to multiple leptons contributing to the two-lepton channel which does not show an excess at 152 GeV. Next, we consider two-Higgs-doublet models where the charged Higgs does not decay to WZ at tree-level, finding a significance of ⪆ 4σ for a branching ratio of the new neutral Higgs to photons of ≈2%. Even though this branching fraction is quite sizable, it can be obtained in composite models or via the Lagrangian term \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\lambda }_{6}{H}_{1}^{†}{H}_{1}{H}_{2}^{†}{H}_{1}$$\\end{document} + h.c. breaking the commonly imposed Z2 symmetry.

Protein language models learn evolutionary statistics of interacting sequence motifs

Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an open question. Motivated by a finding that pLM-based structure predictors erroneously predict nonphysical structures for protein isoforms, we investigated the nature of sequence context needed for contact predictions in the pLM Evolutionary Scale Modeling (ESM-2). We demonstrate by use of a "categorical Jacobian" calculation that ESM-2 stores statistics of coevolving residues, analogously to simpler modeling approaches like Markov Random Fields and Multivariate Gaussian models. We further investigated how ESM-2 "stores" information needed to predict contacts by comparing sequence masking strategies, and found that providing local windows of sequence information allowed ESM-2 to best recover predicted contacts. This suggests that pLMs predict contacts by storing motifs of pairwise contacts. Our investigation highlights the limitations of current pLMs and underscores the importance of understanding the underlying mechanisms of these models.

The effect of the floor-wall interaction on the post-elastic rocking behaviour of segmented CLT shear walls

This paper investigates the impact of floor-wall interaction on the lateral rocking behaviour of two-panel segmented Cross-Laminated Timber (CLT) shear walls through experimental testing and numerical analyses. The study extends a simplified equivalent spring modelling approach to the post-elastic domain to accurately simulate the effects of floor-wall interaction. Experimental withdrawal tests on four types of floor-to-wall connections, utilizing Fully Threaded Screws (FTSs) and Partially Threaded Screws (PTSs) at varying inclinations, revealed that FTSs exhibited higher stiffness and load-carrying capacity but lower deformation capacity compared to PTSs. The maximum force of FTS connections was about twice that of PTS connections, while PTS connections achieved ultimate displacements up to seven times greater. Numerical analyses using a parametric framework showed that floor-wall interaction increases the stiffness and lateral load-carrying capacity of segmented shear walls, with a significant reduction in deformation capacity. These analyses also demonstrated that the equivalent spring can effectively replicate the influence of floor-wall interaction on shear wall lateral response. Expressions for calculating the strength and ductility of this equivalent spring were developed, considering a limited set of geometric and mechanical parameters. These expressions provide a simplified yet accurate method for estimating the effects of floor-wall interaction. The findings suggest that understanding the interaction between floor and wall elements is crucial for optimizing the performance of segmented CLT shear walls in seismic and lateral load scenarios.

Simulation of Somatic Evolution Through the Introduction of Random Mutation to the Rules of Conway’s Game of Life

Abstract Introduction Conway’s Game of Life (GOL), and related cellular automata (CA) models, have served as interesting simulations of complex behaviors resulting from simple rules of interactions between neighboring cells, that sometime resemble the growth and reproduction of living things. Thus, CA has been applied towards understanding the interaction and reproduction of single-cell organisms, and the growth of larger, disorganized tissues such as tumors. Surprisingly, however, there have been few attempts to adapt simple CA models to recreate the evolution of either new species, or subclones within a multicellular, tumor-like tissue. Methods In this article, I present a modified form of the classic Conway’s GOL simulation, in which the three integer thresholds that define GOL (number of neighboring cells, below which a cell will “die of loneliness”; number of neighboring cells, above which a cell will die of overcrowding; and number of neighboring cells that will result in spontaneous birth of a new cell within an empty lattice location) are occasionally altered with a randomized mutation of fractional magnitude during new “cell birth” events. Newly born cells “inherit” the current mutation state of a neighboring parent cell, and over the course of 10,000 generations these mutations tend to accumulate until they impact the behaviors of individual cells, causing them to transition from the sparse, small patterns of live cells characteristic of GOL into a more dense, unregulated growth resembling a connected tumor tissue. Results The mutation rate and mutation magnitude were systematically varied in repeated randomized simulation runs, and it was determined that the most important mutated rule for the transition to unregulated, tumor-like growth was the overcrowding threshold, with the spontaneous birth and loneliness thresholds being of secondary importance. Spatial maps of the different “subclones” of cells that spontaneously develop during a typical simulation trial reveal that cells with greater fitness will overgrow the lattice and proliferate while the less fit, “wildtype” GOL cells die out and are replaced with mutant cells. Conclusions This simple modeling approach can be easily modified to add complexity and more realistic biological details, and may yield new understanding of cancer and somatic evolution.

Computational Fluid Dynamics Modelling of Hydrogen Production via Water Splitting in Oxygen Membrane Reactors.

The utilization of oxygen transport membranes enables the production of high-purity hydrogen by the thermal decomposition of water below 1000 °C. This process is based on a chemical potential gradient across the membrane, which is usually achieved by introducing a reducing gas. Computational fluid dynamics (CFD) can be used to model reactors based on this concept. In this study, a modelling approach for water splitting is presented in which oxygen transport through the membrane acts as the rate-determining process for the overall reaction. This transport step is implemented in the CFD simulation. Both gas compartments are modelled in the simulations. Hydrogen and methane are used as reducing gases. The model is validated using experimental data from the literature and compared with a simplified perfect mixing modelling approach. Although the main focus of this work is to propose an approach to implement the water splitting in CFD simulations, a simulation study was conducted to exemplify how CFD modelling can be utilized in design optimization. Simplified 2-dimensional and rotational symmetric reactor geometries were compared. This study shows that a parallel overflow of the membrane in an elongated reactor is advantageous, as this reduces the back diffusion of the reaction products, which increases the mean driving force for oxygen transport through the membrane.

System Dynamics Model of CO2 Pollution Stocks Changes Due to Emissions and Absorbent in Indonesia

Air pollution, including CO2 pollution, is a serious issue worldwide, including in Indonesia. This CO2 pollution can impact public health and the environment. In the context of economic development, activities in Indonesia are increasing, leading to higher CO2 emissions. The highest CO2 emissions come from deforestation, large-scale peatland fires, and, to a lesser extent, burning fossil fuels for energy. This research focuses on a simple System Dynamics model approach to understand the cause-and-effect relationship of changes in CO2 pollution stocks concerning emissions and absorption in Indonesia. The method used in this study is qualitative based on system dynamics. System dynamics is a method that can be used to create structures, predict behavior, and provide feedback. The System Dynamics model uses Powersim Studio 10 Express, covering the research period from 2020 to 2040. The results of the system dynamics model show two structures related to CO2 pollution stocks: a positive feedback (reinforcing loop) from CO2 emissions and a negative feedback (balancing loop) from CO2 absorbent. The behavior of the model is exponential growth, it’s also considered valid due to simulation results based on real data processing and statistical analysis, yielding an Average Means Error (AME) of 0.56%.

Dynamics System Modeling of Declining Agricultural Land Area Potentially Causing Jakarta Flood Disaster

The change or evolution of land use in the DKI Jakarta area has caused various environmental problems in the city that have an impact on disasters that occur from time to time. The conversion of agricultural land that has a relatively high ability to absorb water into built-up land has reduced the water absorption capacity because the built-up area is increasingly impermeable which is at risk of causing flood disasters. This research focuses on a simple dynamic system modeling approach to understand the cause-and-effect relationship of the decline in agricultural land area in the DKI Jakarta area. The method used in this research is a qualitative-based dynamic system, dynamic system is a method that can be used to form structures and predict behavior and feedback. Dynamic system modeling using Powersim Studi 10 Express software uses time specifications ranging from 2020 to 2070. The results of the dynamic system model of agricultural land decline can be said to be valid, where the dominant structure formed is Negative Feedback (Balancing Loop) with Exponential Decay behavior and Average Means Error (AME) test results obtained a value of 29.6%

Broadband multi-wavelength properties of M87 during the 2018 EHT campaign including a very high energy flaring episode

The nearby elliptical galaxy M87 contains one of only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (EHT). In 2018, more than two dozen multi-wavelength (MWL) facilities (from radio to gamma -ray energies) took part in the second M87 EHT campaign. The goal of this extensive MWL campaign was to better understand the physics of the accreting black hole M87*, the relationship between the inflow and inner jets, and the high-energy particle acceleration. Understanding the complex astrophysics is also a necessary first step towards performing further tests of general relativity. The MWL campaign took place in April 2018, overlapping with the EHT M87* observations. We present a new, contemporaneous spectral energy distribution (SED) ranging from radio to very high-energy (VHE) gamma -rays as well as details of the individual observations and light curves. We also conducted phenomenological modelling to investigate the basic source properties. We present the first VHE gamma -ray flare from M87 detected since 2010. The flux above 350 GeV more than doubled within a period of approx 36 hours. We find that the X-ray flux is enhanced by about a factor of two compared to 2017, while the radio and millimetre core fluxes are consistent between 2017 and 2018. We detect evidence for a monotonically increasing jet position angle that corresponds to variations in the bright spot of the EHT image. Our results show the value of continued MWL monitoring together with precision imaging for addressing the origins of high-energy particle acceleration. While we cannot currently pinpoint the precise location where such acceleration takes place, the new VHE gamma -ray flare already presents a challenge to simple one-zone leptonic emission model approaches, and it emphasises the need for combined image and spectral modelling.

Direct application of elasto-visco-plastic self-consistent crystal plasticity model to U-draw bending and springback of dual-phase high strength steel

The incremental elasto-visco-plastic self-consistent polycrystal model (ΔEVPSC) was utilized to describe the constitutive behavior of dual-phase 980 (DP980) steel. A simple baseline modeling approach was chosen: the hardening behavior of each constituent phase in the DP980 steel was described by a simple Voce hardening law without explicitly considering the back stress; and it was assumed that using the same single crystal elastic modulus for ferrite and martensite is sufficiently representative. The adequacy of this baseline modeling approach was evaluated by comparing various mechanical experimental data with model predictions in terms of the stress vs. strain curves obtained from uniaxial tension, tension-compression, and loading-unloading-loading (LUL) tests. Additionally, the evolution of experimental lattice strain data reported in literature was used to validate the phase-specific Voce hardening parameters. Despite its minimalistic modeling description, the baseline ΔEVPSC model successfully captured key features: 1) the Bauschinger effect, 2) the decrease in chord modulus, and 3) the non-linearity in the stress vs. strain curves resulting from the LUL test. All three mentioned characteristics are crucial for accurate prediction of springback in sheet metals. The ΔEVPSC model, interfaced with a finite element solver (Abaqus/standard) as the user material subroutine, was employed to simulate the Numisheet93 benchmark problem. The strip of DP980 was first U-drawn followed by springback. The model-predicted springback profile aligned well with the experimental results only when stress relaxation was properly considered, resulting in improved predictive accuracy compared to predictions based on a distortional plasticity model.

Numerical Calculation of the Oil Flow in a Truck Rear Axle Transmission and the Influence of Gear-Induced Air Flow

Abstract For the reliable operation of a gearbox, consistently sufficient lubrication of machine elements is necessary. Thus, the gearbox fluid flow plays an important role. The state of the art indicates that computational fluid dynamics (CFD) enables targeted support of the gearbox development process at an early stage. Computational time plays a prominent role in practical applications. The particle-based smoothed particle hydrodynamics (SPH) shows great potential for time-efficient calculations, especially with a simplified single-phase modeling approach. This study first examines the influence of gear-induced air flow on gearbox oil flow, focusing on a test gearbox to identify a suitable modeling approach for a truck rear axle transmission. The results indicate that the gear-induced air flow mainly impacts gearbox oil flow at higher circumferential speeds. For lower circumferential speeds, a single-phase model yields good results with significantly reduced computation times compared to a two-phase model. Applying the single-phase model to the truck rear axle transmission and comparing numerical results with experimental findings demonstrates a reliable representation of the oil flow characteristics.

Proposal of a scissor-based model for the non-linear analysis of RC beam-column joints strengthened by FRP

The paper presents a new simple modeling approach for studying the monotonic response of RC beam-column joints externally strengthened by Fiber Reinforced Polymer (FRP) materials. The approach assumes a parallel combination of the behavior of the joint in the unstrengthened configuration and the contribution of strengthening system. To achieve this, the common scissor model, where the behavior of joint shear panel is modeled through a rotational spring, is here modified by introducing an additional spring, arranged parallel to the concrete spring, to account for the contribution of strengthening system. Regarding the behavior of the additional spring, the authors proposed a multilinear simplified constitutive law by appropriately combining analytical models available from the literature with specific guidelines provided by Italian technical standards. The proposed model, implemented in the computer code OpenSees and validated against experimental case studies from the literature, demonstrates its strong capability to capture the contribution of the strengthening system on both the strength and ductility of joints.

The influence of temperature (up to 120 °C) on the thermal conductivity of variably porous andesite

The thermal conductivity of volcanic rock is an essential input parameter in a wide range of models designed to better understand volcanic and geothermal processes. However, although volcanoes and geothermal reservoirs are often characterised by temperatures above ambient, laboratory thermal conductivity measurements are often performed at ambient temperature. In addition, there are currently few data on the temperature dependence of thermal conductivity for andesite, a common volcanic rock. Here, we provide elevated-temperature (up to 120 °C) laboratory measurements of thermal conductivity for variably porous (∼0.05 to ∼0.6) and variably glassy andesites from Mt. Ruapheu (New Zealand) using the transient hot-strip method. Our data show that (1) the thermal conductivity of these andesites has little to no temperature dependence and, therefore, (2) there is also no influence of porosity on the temperature dependence of thermal conductivity. We compare our new data with compiled published data to show that the thermal conductivity of volcanic rocks may decrease, remain constant, or increase as a function of temperature. We show that the thermal conductivity of amorphous glass and crystalline material increase and decrease, respectively, as temperature increases. We therefore interpret the temperature dependence of the thermal conductivity of volcanic rock to be dependent on glass content. The thermal conductivity of the studied andesites, the microstructure of which can be characterised by phenocrysts within a variably glassy groundmass, has little to no temperature dependence because the decrease in the thermal conductivity of the crystalline materials, due to decreases in lattice thermal conductivity, is offset by the increase in the thermal conductivity of the amorphous glass. A simple modelling approach, using the temperature dependence of the thermal conductivity of glass and crystalline material, provides a crystal content of 0.26 for a thermal conductivity independent of temperature, a common crystal content for andesite dome rock. Our findings imply that calculations of heat transfer through partially glassy volcanic rocks need not consider a temperature-dependent thermal conductivity, but that decreases and increases in thermal conductivity with temperature should be expected for fully crystallised or devitrified volcanic rocks and completely glassy volcanic rocks, respectively. We highlight that more experimental studies are now required to assess the evolution of thermal conductivity as a function of temperature in a wide range of volcanic rocks with different crystallinities.

ILC sensitivity for leptophilic scalar dark matter

We explore the viability of detecting a leptophilic scalar dark matter (DM) at the International Linear Collider (ILC) in a simplified model approach. We present the constraints on the couplings of scalar DM with the standard model fermions ensuing from the relic density bounds deduced from the 2018 Planck data. We, then, present the reach of the ILC in terms of Λ, the scale of the effective theory, by performing a detailed analysis for the Z associated DM pair production (i.e. e + e − → 2 jets + ET , e + e − → μ + μ − + ET and e + e − → e + e − + ET ). We present the results for various run scenarios as 3σ contours in the m ϕ − Λ plane. We also analyze the effect of beam polarization on the sensitivity of this search. We find that for the process with two hadronic jets in the final state, ILC can probe Λ up to 1.76 TeV for s=1 TeV that can further enhance to 1.99 TeV, after the inclusion of polarization effects.

A Systematic Review of Modeling Approaches to Evaluate Treatments for Relapsed Refractory Multiple Myeloma: Critical Review and Considerations for Future Health Economic Models.

Multiple myeloma is a rare incurable hematological cancer in which most patients relapse or become refractory to treatment. This systematic literature review aimed to critically review the existing economic models used in economic evaluations of systemic treatments for relapsed/refractory multiple myeloma and to summarize how the models addressed differences in the line of therapy and exposure to prior treatment. Following a pre-approved protocol, literature searches were conducted on 17 February, 2023, in relevant databases for models published since 2014. Additionally, key health technology assessment agency websites were manually searched for models published as part of submission dossiers since 2018. Reported information related to model conceptualization, structure, uncertainty, validation, and transparency were extracted into a pre-defined extraction sheet. In total, 49 models assessing a wide range of interventions across multiple lines of therapy were included. Only five models specific to heavily pre-treated patients and/or those who were refractory to multiple treatment classes were identified. Most models followed a conventional simple methodology, such as partitioned survival (n = 28) or Markov models (n = 9). All included models evaluated specific interventions rather than the whole treatment sequence. Where subsequent therapies were included in the model, these were generally only considered from a cost and resource use perspective. The models generally used overall and progression-free survival as model inputs, although data were often immature. Sensitivity analyses were frequently reported (n = 41) whereas validation was only considered in less than half (n = 19) of the models. Published economic models in relapsed/refractory multiple myeloma rarely followed an individual patient approach, mainly owing to the higher need for complex data assumptions compared with simpler modeling approaches. As many patients experience disease progression on multiple treatment lines, there is a growing need for modeling complex treatment strategies, leading to more sophisticated approaches in the future. Maintaining transparency, high reporting standards, and thorough analyses of uncertainty are crucial to support these advancements.

The In-Plane Seismic Response of Infilled Reinforced Concrete Frames Using a Strut Modelling Approach: Validation and Applications

Reinforced Concrete (RC) buildings often rely on masonry walls to increase their rigidity and strength, distinguishing them from bare frames. Consequently, the lateral capacity of the RC frames is significantly impacted by the presence or absence of these walls. Numerical models are fundamental to understanding this behavior interaction, but the development of robust simplified models is still scarce. Based on this motivation, the reliability of a simplified numerical modelling approach was examined in this study and compared to several experimental tests. An optimized approach was implemented to determine the strut parameters, rather than relying on existing empirical formulae. The reliability of the initial stiffness, maximum strength, and energy dissipation was studied. From the results, the accuracy of the considered modelling strategy can be observed in different types of masonry elements (strong and weak units) with and without openings. The validated simulation approach reveals that the adopted macro-modelling procedure can accurately represent the behavior of infilled masonry frames. The maximum deviation of the prediction of the initial stiffness and maximum strength was found to be around 23% and 14%, respectively. These findings illustrate that the strut model effectively replicates real behavior with a satisfactory level of accuracy. However, using a consistent formula to define the strut can result in significant errors, particularly in strut width.

The general patterns of water flow in loess slope system and implications for slope geological security

Loess regions face significant challenges in quantifying hydrological processes and assessing geological environmental risks due to the prevalent development of preferential pathways and the limitations of existing monitoring technologies. To advance this knowledge, this study presents an improved electrical resistivity tomography (ERT) device, specifically designed for loess moisture observations. By refining the testing principle, power supply mode, and data collection method within the existing ERT framework, the new device offers unmanned operation, automatic data acquisition, remote transmission, and cost efficiency. It effectively tracks water movement and groundwater level fluctuations across various hydrological conditions, supporting long-term online monitoring of hydrological processes of loess slopes. Through the analysis of monitoring data and classification of 12 observed preferential flow types, water movement in loess systems can be generalized into four general patterns: uniform infiltration, preferential infiltration, inflowing diffusion, and lateral flow. This generalized scheme provides a simplified modeling approach for other researchers to quantify slope hydrodynamics and to assess geological safety risks involving preferential flow. Based on these insights and field investigations, a conceptual framework is proposed to elucidate the seepage-structure synergistic initiating mechanism of loess landslides. This framework suggests that water entry and movement patterns within the slope depend on the slope geological structure related to preferential pathways and the prevailing hydrological scenarios. Landslide occurs as the result of the progressive failure and reciprocal evolution between the slope hydrological environments and geological structure, which may also pose potential eco-hydrological risks. The outcome advances the development of slope hydrological monitoring technology and enhances the understanding of water movement laws and the associated geological environmental risks in loess slope systems, which is of vital importance to the early warning methods of loess landslides that account for preferential flow and for theoretical modeling of preferential flow in related disciplines.

Optimizing Coupled Fluid-Structure Simulations for Nuclear-Relevant Geometries

Abstract The numerical simulation of fluid-structure interactions (FSI) has gained interest to study flow-induced vibrations. Nevertheless, the high computational resources required by such simulations can represent a significant limitation for their application to industrial configurations. Therefore, simplified modeling approaches, when physically applicable, can represent an interesting compromise. This can be the case of slender structures (tubes, rods) often encountered in nuclear power plants. In this paper, an Euler–Bernoulli beam finite element model is implemented inside the computational fluid dynamics (CFD) code code_Saturne. With the goal of finding CFD methods less expensive than large eddy simulations (LES), unsteady Reynolds Navier–Stokes (URANS) and hybrid URANS/LES approaches are considered. The resulting fluid-structure model is able to calculate the vibration response of cantilever beams under a fluid flow, avoiding the necessity of CFD-finite element method (FEM) code coupling. The first part of the paper describes the model and its implementation: it allows to perform 2-way explicit fluid-structure coupling, using the Arbitrary Lagrangian-Eulerian approach to account for the structure deformations. Validation test cases are presented in the second part: first, the model is validated in terms of frequency, added mass, and damping for a cylinder vibrating in static air and water; then, the model is validated toward the vortex-induced resonance and lock-in mechanisms for a cylinder subjected to water cross-flow. The model is then applied to a real experimental configuration of two in-line cylinders in water cross-flow: the calculated vibrations are found to be in good agreement with the experimental measurements.