Model Simulations Research Articles

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater-groundwater within or near the crop rooting zone-as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

Real-time prediction model of passenger thermal comfort for intelligent cabin

This article establishes a joint model of intelligent cabin and human thermal sensation, following experimental verification. And 12000 sets of datasets are obtained through joint model simulation under 120 random working conditions. Subsequently, a real-time prediction model of passenger thermal comfort is established and is trained using the Catboost algorithm based on the datasets. Finally, under various working conditions, the calculation results of the real-time prediction model were compared with these of the joint model and steady-state prediction model separately. The results indicate that the real-time prediction model can predict the passenger thermal comfort under unstable thermal environment, while the steady-state prediction model cannot. And compared to the accurate value calculated by joint model, the average mean absolute error (MAE) and mean absolute percent error (MAPE) of the real-time prediction model is 0.025 and 1.58 %, respectively. This indicates that the real-time prediction model established in this article has good accuracy.

Novel hybrid BTMS by considering safety and driving cycle under extreme fast charge/discharge rates

A battery thermal management system integrating phase change material and mini-channels, with a focus on safety and economic considerations, is proposed to enhance thermal performance across various working conditions, safety scenarios, and realistic driving cycles while minimizing energy consumption. A battery thermal model and PCM simulation model were developed and validated using experimental data. Numerical analyses were conducted to compare the combination of PCM and liquid cooling (hybrid cooling) with fully liquid cooling under different charge/discharge rates and realistic driving cycles, evaluating their safety characteristics, power consumption, and thermal efficiency. The results demonstrated that the hybrid cooling approach can effectively maintain both the maximum temperature and the temperature difference within a desirable range, even when the inlet velocity is reduced from 0.12 to 0.05 m/s compared to liquid cooling. Additionally, the hybrid BTMS provides better working conditions for the battery pack, requiring only 4 × 10−5 W of pumping power compared to 16 × 10−5 W in the liquid cooling system. This underscores the capability of the designed BTMS to cool high-capacity battery packs with significantly lower fluid flow rates. Furthermore, the performance of the proposed cooling system was examined in the event of liquid channel failure, with results showing that the hybrid BTMS can successfully maintain the battery's maximum temperature within an allowable range during fast charge/discharge processes. Lastly, evaluations under realistic driving conditions revealed the superiority of hybrid cooling in reducing peak temperatures and minimizing battery temperature variation.

Modeling the selective attenuation of thin film composite membranes: Implementing the mass transfer perspective

Numerous experiments have demonstrated that the porous support layer limits the diffusion behavior and leads to a reduction in permeability of thin film composite (TFC) membranes. Although this geometric restriction has been described using empirical models, it is still rough and unable to describe the effect of support layer on selectivity, an accurate theoretical model to quantitatively calculate the permeation performance of TFC membranes is lacking. In this study, an equivalent theoretical model is proposed to describe the mass transfer process of TFC membrane, by properly handling the tangential diffusion at the interface between the selective layer and the support layer. Both the computational fluid dynamics (CFD) simulations performed in this work and experimental data in some literatures prove the validity of the equivalent model. Analysis of the theoretical model and CFD simulation results show that: Restriction factor Ψ is independent of the solubility coefficients but dependent of the diffusion coefficients and support layers, which would alter the TFC membrane selectivity to the diffusing species with different diffusion coefficients. Tuning the structural parameters of the support layer is an effective way to bring the performance of TFC membranes closer to that of ideal free-standing membranes. Among them, High surface porosity of the support layer is the most critical factor affecting TFC membrane performance, both for permeability and selectivity.

A sedimentary lipid biomarker record of Holocene temperature variations and drought events in northern China

Holocene hydroclimate changes are crucial not only for predicting future climate changes, but also for understanding their impacts on ancient societies. However, our knowledge about severe drought events in East Asia during the Holocene is largely fragmentary and the pattern of temperature changes is still uncertain. Here, we, for the first time, present high-resolution quantitative records of temperature and drought events in northern China throughout the Holocene from a well-dated loess-paleosol sequence (Weinan) on the southern Chinese Loess Plateau (CLP). Our inferred temperatures, derived from glycerol dialkyl glycerol tetraethers (GDGTs), indicate that the early-to-mid Holocene experienced warm conditions, with temperatures ranging from ∼17.7 to 20.2 °C. This was followed by a cooler late Holocene, which contrasts with the results of climate model simulations. In addition, our hydroclimate record reveals that severe drought conditions occurred during both the early and late Holocene. These intensified drought events coincide with the demise of several Chinese dynasties. We propose that the colder climate during the late Holocene led to a strengthening of the East Asian winter monsoon and a weakening of the East Asian summer monsoon over northern China, as well as the southward shift of the Intertropical Convergence Zone (ITCZ), causing more severe drought conditions during the late Holocene compared to the early Holocene. Our results extend the East Asian Holocene climate records, highlighting the importance of understanding how hydroclimate extremes may have impacted human civilization in East Asia.

Optimization design of low-carbon building thermal energy based on optical sensing and virtual reality image scene reconstruction

With the intensification of global climate change and energy crisis, the design of low-carbon buildings has gradually become a research hotspot in the field of architecture. Effective thermal optimization design not only reduces energy consumption, but also improves the comfort and sustainability of the building. This study aims to explore the optimization design of low-carbon building heat energy based on light sensing technology, combined with virtual reality image scene reconstruction, to provide an innovative design method to achieve intelligent management and optimization of building heat energy. Through the introduction of light sensing technology, the light intensity and heat distribution inside and outside the building are monitored, and the combination of data analysis and model simulation is used to evaluate the heat use of the building. On this basis, virtual reality scenes are constructed to reconstruct the heat flow and distribution of buildings, providing designers with intuitive visualization tools. The research shows that the design method based on light sensing can effectively identify the areas of heat waste in the building, and reduce the energy consumption of the building by optimizing the window layout, adding greening and improving the thermal management system. Virtual reality image scene reconstruction makes the design process more intuitive, helps the design team to quickly adjust and optimize, and improves the efficiency and accuracy of the design.

Assessing the suitability of the SLEUTH cellular automata model for capturing heterogeneous urban growth in developing cities: A case study in Northern Nigeria

Cellular automata (CA) models like SLEUTH (an acronym for slope, land use, excluded area, urban extent, transport-network and hill shade) have predominantly been developed and applied in developed countries. Modeling can serve as a tool to guide policy measures in facing urbanization challenges. However, developing cities have peculiar differences (heterogeneity, poor planning, and low infrastructure) thus the existing modeling approaches may not be able to apprehend heterogeneous urban growth. This research will use selected cities with similar spatial extents as controls but disparate urban extents, and growth indices to analyze the performance of SLEUTH simulations. Presumably, a comparison of the model simulations of the cities would display some significant differences, due to these variations and the scale of observation that has to be used for the model simulations. The results for the successfully calibrated cities (Kano/Funtua couple: 0.48/0.02. Katsina/Kaduna: 0.48/0.83 respectively) showed that in each city couple, the more expansive city with the most compact urban settlement pattern had a higher prediction accuracy, also predicted images of the cities showed underestimation of the urban areas over the years with the exception of Katsina city. The study further showed the model's effectiveness in modeling cities in developing countries, such as Nigeria. It is recommended that the type of urban growth experienced by cities be taken into consideration when implementing SLEUTH. Limitations of the study are centered on the inherent limitations of the model, the possibility of the occurrence of errors in data preparation, the scale and urban settlement type, which play an important role in the success of the calibration. Future research could be focused on adding other relevant inputs to the model and creating a metric that ascertains the best satellite image resolutions for a particular study area's growth coefficient values.

Study on the combustion characteristics and reaction mechanism of aluminum/alcohol-based nanofluid fuel

Enhancing the volumetric energy density of fuels is a crucial approach in the exploration of efficient energy sources. As a commonly used high-energy additive, Aluminum nanoparticles (Al NPs) holds broad application prospects. This study delves into the effects of Al NPs on the combustion characteristics of methanol and ethanol fuels through in-depth analysis of single droplet combustion and spray combustion experiments involving alcohol-based nanofluid fuels. The experiments revealed that adding Al NPs significantly enhances fuel combustion efficiency, shortening both the combustion life and ignition delay time. Spray combustion tests demonstrated that adding 2 wt% Al NPs increased the maximum and average flame propagation speeds of ethanol fuel spray by 48.93 % and 47.94 %, respectively, while the maximum explosion pressure rose from 0.66MPa to 0.83MPa, with a reduced time to reach peak explosion pressure by 106ms. Based on the SEM and XRD characterization results of the combustion residues and the analysis of flame morphology, a physical model of the alcohol-based nanofluid fuel spray combustion flame was established. Numerical simulations of the gas-phase kinetics model showed that the generation rates of radicals such as H, O, and OH were significantly increased with the addition of Al NPs, intensifying the combustion reaction. The findings provide a theoretical basis for future fuel design and combustion performance optimization.

Analysis of SIS epidemic model in bi-uniform hypernetworks

To describe the dynamics of epidemic spread with multiple individuals interacting with each other, we develop a susceptible-infected-susceptible (SIS) spread model with collective and individual contagion in general hypernetworks with higher-order interactions. The constructed model is applied to a bi-uniform hypernetwork to obtain a mean-field model for the SIS model. The threshold value at which an epidemic can spread in the bi-uniform hypernetwork is obtained and analyzed dynamically. By analysis, the model leads to bistability, in which a disease-free equilibrium and an endemic equilibrium coexist. Finally, numerical simulations of the developed model are carried out to give the effect of the proportion of individual contagion hyperedges on the spread of an epidemic.

Computational insights from the thermal spike model into mesoporous silica behavior during swift heavy ion irradiation

Mesoporous silica materials are pivotal in various scientific domains due to their unique properties and versatile applications. However, understanding their response to irradiation, particularly from Swift Heavy Ions (SHI), remains limited. We address this gap by investigating experimental mesoporous silica behavior under 12 MeV Carbon and 92 MeV Xenon bombardment using the Three-Dimensional Thermal Spike Model (3DTS) simulation. Our computational simulations reveal localized heating effects and provide mechanistic insights into experimental observations, shedding light on pore closure and different observed damage patterns. This study is the first application of this model to porous silica and deepens our knowledge of the mechanism of structural evolution under ion bombardment.

Discovery of potential 1,2,4-triazole derivatives as aromatase inhibitors for breast cancer: pharmacophore modelling, virtual screening, docking, ADMET and MD simulation

ABSTRACT Hormone receptor (HR)-positive breast cancer represents tumours that express estrogen and/or progesterone enzymes, which play a crucial role in the growth and proliferation of breast cancer cells. Aromatase inhibitors (AIs) are drugs that inhibit the enzyme aromatase, involved in the biosynthesis of estrogen and are used for the treatment of HR-positive breast cancer. The USFDA-approved nonsteroidal AIs contain 1,2,4-triazole heterocycle. So, in the present study, we screened seventy-eight 1,2,4-triazole analogues from different literature resources and generated a pharmacophore model. After several validation protocols, Hypo1 was selected as the best model and was used as a 3D query for screening 1,2,4-triazole analogues (15,583) obtained from the CHEMBL database. A dataset containing 320 ligands with estimated activity (IC50< 0.1 µM) was subjected to molecular docking against the aromatase enzyme (PDB ID: 3S79). Amongst the 320 ligands, 30 compounds exhibited better binding energy compared to the standard drug letrozole. These 30 hits were further considered for the design of two novel molecules which were initially assessed for their ADMET properties followed by pharmacophore mapping, docking and molecular dynamics simulation. The in silico findings suggest that both the designed molecules can be considered drug-like candidates for the treatment of breast cancer through aromatase inhibition.

FMCW Laser Fuze Structure with Multi-Channel Beam Based on 3D Particle Collision Scattering Model under Smoke Interference.

In the environment of smoke and suspended particles, the accurate detection of targets is one of the difficulties for frequency-modulated continuous-wave (FMCW) laser fuzes to work properly in harsh conditions. To weaken and eliminate the significant influence caused by the interaction of different systems in the photon transmission process and the smoke particle environment, it is necessary to increase the amplitude of the target echo signal to improve the signal-to-noise ratio (SNR), which contributes to enhancing the detection performance of the laser fuze for the ground target in the smoke. Under these conditions, the particle transmission of photons in the smoke environment is studied from the perspective of three-dimentional (3D) collisions between photons and smoke particles, and the modeling and Unity3D simulation of FMCW laser echo signal based on 3D particle collision is conducted. On this basis, a laser fuze structure based on multiple channel beam emission is designed for the combined effect of particle features from different systems and its impact on the target characteristics is researched. Simulation results show that the multiple channel laser emission enhances the laser target echo signal amplitude and also improves the anti-interference ability against the combined effects of multiple particle features compared with the single channel. Through the validation based on the laser prototype with four-channel beam emitting, the above conclusions are supported by the experimental results. Therefore, this study not only reveals the laser target properties under the 3D particle collision perspective, but also reflects the reasonableness and effectiveness of utilizing the target characteristics in the 3D particle collision mode to enhance the detection performance of FMCW laser fuze in the smoke.

Identification of Individuals of Two Takin Subspecies Using Biological and Ecological Criteria in Eastern Himalayas of China.

Limited background data are available on the Mishmi takin (Budorcas taxicolor taxicolor) and Bhutan takin (Budorcas taxicolor whitei) subspecies in the Eastern Himalayas of China because of the lack of systematic field investigations and research. Therefore, mature-animal ecological methods were used to evaluate these takin subspecies' phenotypic characteristics, distribution range, activity rhythm, and population size. From 2013 to 2022, 214 camera traps were installed for wild ungulate monitoring and investigation in all human-accessible areas of the Eastern Himalayas, resulting in 4837 distinguishable takin photographs. The external morphological characteristics were described and compared using visual data. Artificial image correction and related technologies were used to establish physical image models based on the differences between subspecies. MaxEnt niche and random encounter models obtained distribution ranges and population densities. Mishmi takins have a distribution area of 17,314 km2, population density of 0.1729 ± 0.0134 takins/km2, and population size of 2995 ± 232. Bhutan takins have a distribution area of 25,006 km2, population density of 0.1359 ± 0.0264 takins/km2, and population size of 3398 ± 660. Long-term monitoring data confirmed that the vertical migration within the mountain ecosystems is influenced by climate. Mishmi takins are active at 500-4500 m, whereas Bhutan takins are active at 1500-4500 m. The two subspecies were active at >3500 m from May to October yearly (rainy season). In addition, surveying combined with model simulation shows that the Yarlung Zangbo River is not an obstacle to migration. This study provides basic data that contribute to animal diversity knowledge in biodiversity hotspots of the Eastern Himalayas and detailed information and references for species identification, distribution range, and population characteristics.

Seeking a pathway towards a more sustainable human-water relationship by coupled model – From a perspective of socio-hydrology

It is essential to systematically consider social, economic, and natural endowments in managing and allocating water resources. However, few studies have comprehensively quantitatively evaluated the allocation of regional water resources from a socio-hydrology perspective and provided recommendations. To explore this research gap, we have constructed a tightly coupled framework that integrates system dynamics models and optimization algorithms to carry out an innovative redistribution of water resources in Shaanxi Province. The system dynamics model simulation results showed that the error was almost always within 10% over the research period, indicating robust simulation capability and laying a solid foundation for subsequent model coupling. The coupled model achieves convergence in approximately 30 generations by formulating the optimization problem with four individual objectives. Optimizing four objectives concurrently results in convergence around the 150th generation. The optimized Pareto solution sets visually demonstrate the trade-offs between different objectives. In the optimized water allocation schedule, the water consumption in Yulin exhibits a change of 1.22 ×108m3, reflecting the most significant optimization effects on agricultural and domestic water allocation. The results indicated that the comprehensive Gini coefficient typically ranged between 0.2 and 0.3. Over the period from the year 2010–2021, the Gini coefficient exhibited a declining trend, signifying a positive trajectory in water resource allocation throughout the research period and a high level of fairness. The annual total green WF of grain in Weinan was the highest at 14.26 ×108m3, followed by Xianyang at 9.52 ×108m3, and the lowest in Tongchuan at 0.54 ×108m3. The annual average amount of blue WF of grain is the highest in Hanzhong, at 11.33 ×108m3, followed by Weinan at 9.60 ×108m3, and the lowest in Tongchuan at 0.14 ×108m3. The coupled framework proposed in this study exhibits significant innovation, scalability, and practical efficiency. It can inspire future research and decision-making and holds the potential for application in other regions.

On the grain level deformation of BCC metals with crystal plasticity modeling: Application to an RPV steel and the effect of irradiation

Capturing realistic deformation behavior in BCC metals at the polycrystal scale is an important aspect of predicting the material’s strength and failure. Furthermore, local deformation/strength heterogeneity also influences the lifetime and its assessments in reactor pressure vessel (RPV) steels, especially with accumulating irradiation doses during long-term operational conditions. This work utilizes a micromorphic crystal plasticity (CP) model for BCC materials with the capability to address temperature-dependent stress–strain response and irradiation effects relevant to RPV materials. The microstructure of the investigated material was characterized prior to and during testing using electron microscopy experiments, which are used for finite element model generation and simulation result validation. To analyze the validity of the model to predict strain localization under monotonic tensile loading, micro digital image correlation (DIC) was employed jointly with the CP simulations. Different modeling choices, such as the use Schmid/non-Schmid laws and gradient based CP modeling, greatly affected the capability of the model to represent similar magnitudes in strain localization and grain reorientation. The requirement for experimental measurements, including image based analyses, on a microstructural level as a validation tool for CP modeling is clearly demonstrated.

Diurnal cycles of rain storms over South China during the presummer rainy season

The variation characteristics of rain storms (RSs) are closely related to complex internal physical processes and external dynamic and thermodynamic conditions. Using a 17-year observational rainfall dataset from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), the diurnal cycles of various RS characteristics and their responses to the South China Sea Summer Monsoon (SCSSM) are investigated in South China (SC) during the presummer rainy season (PSRS). Before SCSSM outbreaks, the RSs in the western inland region of SC (WSC) have stronger precipitation intensities and convective features due to orographic lifting, especially at night, while those in the eastern inland region of SC (ESC) have higher RS occurrence frequencies with higher moisture transport, especially in the afternoon. The onset of the SCSSM leads to abundant moisture and sufficient convective available potential energy over the entire SC area, resulting in significant increases in the occurrence frequency, convective fraction, and precipitation top height of RSs. In the WSC, the weakened upward motion and smaller convective inhibition limit RS development, resulting in weaker rainfall intensity. In the ESC, a particularly unstable atmosphere and enhanced low-level moisture transport in the afternoon lead to a larger three-dimensional size, more active convection, and greater precipitation intensity in the RSs. These results offer fresh insight into the diurnal variation in rainfall during the PSRS and can be effectively used to evaluate numerical model simulations.

An analysis of pipe spool supply chain in shipbuilding using 2-stage queuing model and discrete event simulation

Pipe spool supply in Korean shipbuilding industry consists of a complex supply chain comprising manufacturing and painting vendors. Major Korean shipyards with the most competitive edge have applied various policies and techniques to control the pipe spool supply chain and prevent production delays related to supply delays in pipe spools. Although research has been done on implementing the policies and techniques, there has been a gap on the theoretical consideration of pipe spool supply chain characteristics using a simulation model. Therefore, this study proposes an analytical method based on queueing model to analyze the characteristics of the pipe spool supply chain and also proposes a simulation model based on discrete event simulation (DES) to verify it. In addition, a numerical experiment using DES for the M/G/1 queuing model is conducted to examine the effect of time variability in the spool supply chain. From the more reliable experimental results, control parameters and management insights to manage the supply chain optimality are proposed and the effectiveness of policies that have been implemented by major shipyards is verified.

Study on non-uniform circumferential temperature distribution of annular fuel in the tight lattice configuration of a lead-bismuth cooled fast reactor

To guarantee the safe operation of nuclear reactors and protect fuel elements from being damaged under long-term thermal stress, analyzing the circumferential temperature distribution of the outer cladding of nuclear fuel rods in reactors with tight lattice structures is crucial. In this work, a mathematical and physical model was established through theoretical analysis to calculate the circumferential temperature distribution of the outer cladding of an annular fuel rod. The proposed model provides an analytical expression for the circumferential temperature distribution, and the key factors influencing this distribution are determined. The results of the mathematical-physical model and numerical simulation are then combined through numerical fitting. Consequently, a numerical fitting equation is obtained under the steady-state condition of the lead-bismuth reactor using annular fuel and compared with the numerical simulation data acquired via computational fluid dynamics. The results demonstrate that the proposed numerical fitting equation has high accuracy and can serve as a valuable computational tool for analyzing the circumferential temperature of fuel claddings during the operation of lead-bismuth reactors with annular fuels.

The Stiffness and Damping Characteristics of a Rubber-Based SMA Composite Shock Absorber with a Hyper-Elastic SMA-Constitutive Model Considering the Loading Rate.

Shock absorbers are essential in enhancing vehicle ride comfort by mitigating vibrations. However, traditional rubber shock absorbers are constrained by their fixed stiffness and damping properties, limiting their adaptability to varying loads and thus affecting the ride comfort, especially under extreme road conditions. Shape Memory Alloys (SMAs), known for their intelligent material properties, offer a unique solution by adjusting stiffness and damping in response to temperature changes or strain rates, making them ideal for advanced vibration control applications. This study builds upon the Auricchio constitutive model to propose an enhanced SMA hyper-elastic constitutive model that accounts for different loading rates. This new model elucidates the impact of loading rates on the stiffness and damping characteristics of SMAs. Additionally, we introduce an innovative circular rubber-based SMA composite vibration reduction structure. Through a parameterized model and finite element simulation, we comprehensively analyze the stiffness and damping properties of the composite damper under various loading rates and harmonic excitations. Our findings suggest a novel approach to improving the vehicle ride comfort, offering significant potential for engineering applications and practical value.

Vertical structure and transport characteristic of aerosol and O3 during the emergency control period in Wuhan, China, using vehicle-lidar observations

During the Lunar New Year of 2020, the Chinese government implemented a strict nationwide lockdown to prevent the spread of the COVID-19, which may have led to changes in the distribution of pollutants. To enhance our understanding of the three-dimensional evolution of pollutants under special control scenarios, this study used vehicle lidar to obtain vertical profiles of aerosols and ozone (O3) in Wuhan during the pandemic. Combined with ground observations and WRF-Chem model simulation results, we explored the evolution characteristics of pollutants. The results showed that the fine particulate matter (PM2.5) concentration near the ground in Wuhan City was significantly reduced (40%) during the emission control period. The aerosol concentration decreased rapidly with an increase in height, and the maximum loading height was consistent with the atmospheric boundary layer height. Conversely, due to factors such as the reduction of the precursor nitrogen dioxide (NO2) and rising temperatures, the near-ground O3 concentration increased by 59%. Despite the significant reduction in emission sources, lidar observations still captured distinct aerosol transport layers on March 7 and March 10, 2020. These transport layers gradually descended, affecting the ground-level aerosol concentration. Additionally, one typical process of O3 external transport was observed in the vertical direction. Our study provides a theoretical basis for a deeper understanding of the spatiotemporal distribution characteristics of pollutants during special control scenarios, aiding policymakers in formulating effective air pollution control strategies.