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With the improvement of environmental awareness, green logistics, as a kind of logistics mode that can realize the unity of economic benefits and environmental benefits, has been paid more and more attention by the academia and the industry. However, how to effectively evaluate the operation effect of green logistics is still a problem to be solved. To solve this problem, this paper proposes a green logistics evaluation index system based on factor analysis, and verifies its effectiveness through simulation data. In the process of building and validating the model, rigorous mathematical modeling methods were used, combined with a large number of actual data. The results show that the evaluation index system of this study can accurately predict the operation effect of green logistics, and provide a practical evaluation tool for enterprises. Finally, the model is optimized to further improve its prediction accuracy. This study is of great significance to theoretical research and practical application. [ABSTRACT FROM AUTHOR]

AbstractNuclear performance analysis is of great significance for fuel design optimization and the safe operation of a reactor. Considering the design requirements of the China initiative Accelerator Driven System (CiADS) project, it is necessary to develop relevant fuel performance analysis tools to predict fuel performance evolution during service. The Fuel Element Analysis Tool for Undercritical Reactor Engineering (FEATURE) code, based on the advanced multiphysics coupling platform COMSOL software, is under development in this context, with a current focus on oxide fuel for fast reactors. This paper mainly conducts preliminary comparative verification of the oxygen redistribution, plutonium redistribution, and fission gas release modules of the FEATURE code through model examples, code-to-code evaluation, and experimental data. The results indicate that the FEATURE code exhibits good accuracy and reliability in simulating oxygen and plutonium redistribution, as well as fission gas release, making it suitable for integrated coupling calculations. [ABSTRACT FROM AUTHOR]

There has been an explosion of data collected about sports. Because such data is extremely rich and complex, machine learning is increasingly being used to extract actionable insights from it. Typically, machine learning is used to build models and indicators that capture the skills, capabilities, and tendencies of athletes and teams. Such indicators and models are in turn used to inform decision-making at professional clubs. Designing these indicators requires paying careful attention to a number of subtle issues from a methodological and evaluation perspective. In this paper, we highlight these challenges in sports and discuss a variety of approaches for handling them. Methodologically, we highlight that dependencies affect how to perform data partitioning for evaluation as well as the need to consider contextual factors. From an evaluation perspective, we draw a distinction between evaluating the developed indicators themselves versus the underlying models that power them. We argue that both aspects must be considered, but that they require different approaches. We hope that this article helps bridge the gap between traditional sports expertise and modern data analytics by providing a structured framework with practical examples. [ABSTRACT FROM AUTHOR]

This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment (SWEX) was conducted. We further refine our study area to the Montecito region owing to some of the highest wind measurements occurring at or near surface station MTIC1, situated on the coast-facing slope overlooking the area. Fires are not uncommon in this area, and the difficulty of egress makes the population particularly vulnerable. Area forecasters often use the sea-level pressure difference (Δ SLP) between Santa Barbara Airport (KSBA) and locations to the north such as Bakersfield (KBFL) to predict Sundowner windstorm occurrence. Our analysis indicates that Δ SLP by itself is prone to high false alarm rates and offers little information regarding downslope wind onset, duration, or magnitude. Additionally, our analysis shows that the high-resolution rapid refresh (HRRR) model has limited predictive skill overall for forecasting winds in the Montecito area. The HRRR, however, skillfully predicts KSBA-KBFL Δ SLP, as does GraphCast, a machine learning weather prediction model. Using a logistic regression model we were able to predict the occurrence of winds exceeding 9 m s − 1 with a high probability of detection while minimizing false alarm rates compared to other methods analyzed. This provides a refined and easily computed algorithm for operational applications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Problem-solving in geotechnical engineering requires multiple types of laboratory tests, which may utilize static or dynamic methods. During dynamic tests, whether using a centrifuge in NG or a shaking table in 1G, a soil container is always required to ensure that the soil inside represents the free field case during dynamic loading. Therefore, it is necessary to understand the specifications of different types of soil containers in order to choose the most appropriate one. This study summarizes the specifications of different types of soil containers and provides insight into selecting the most suitable one for dynamic tests. Laminar soil containers have been shown to reflect the most similar performance of the soil sample to free field conditions, so this study reviews the specifications of existing setups in chronological order. To evaluate the performance of generally adopted mechanisms of movement for laminar containers, 3D numerical model analyses are performed in this study. The numerical evaluation suggests that the roller mechanism does not amplify the applied motion, while the flexible sealant may exhibit excessive deformations. This study offers valuable insights into geotechnical dynamic testing of soils in laboratory settings and serves as a guide for designing an enhanced laminar soil container. [ABSTRACT FROM AUTHOR]

To ensure the uniformity of material removal during surface grinding of screw rotors, a mathematical model for the material removal depth of screw rotors is established, considering the impact of abrasive wear on grinding removal depth. Based on the theory of elastic-plastic deformation and the wear pattern of abrasive particles during grinding, a theoretical model for the removal rate of single abrasive material is established. The wear of abrasive particles is divided into two stages: the rapid wear stage and the stable wear stage. Based on the number of abrasive particles per unit contact area and the rule of abrasive cutting edge, the maximum cutting depth of abrasive particles is calculated by numerical integration and contact pressure, and the mathematical model of macroscopic material removal rate based on abrasive belt wear is established. The model consideres the wear of the sand belt. The maximum error of the predicted value is 9.6%, and the minimum error is 4.1% compared with the experimental value. The experimental data fully verify the effectiveness of the model, and can provide a theoretical basis for ensuring the profile accuracy of the screw rotor.

Ensemble modelling has become a significant technique in the field of machine learning, as it utilises the combined knowledge of multiple base models to improve the accuracy of predictions in different domains. Nevertheless, the effectiveness of ensemble predictions relies on the implementation of post-processing techniques that enhance and optimize the outputs of the ensemble. This study explores the domain of ensemble data post-processing, utilizing a machine learning-focused methodology to thoroughly assess and contrast a variety of post-processing methods. TIGGE Ensemble data from ECMWF and NCEP were used from 2010 to 2020. Research covers machine learning approaches post-processing methods such as BMA, cNLR, HXLR, OLR, logreg, hlogreg, QM were applied. The probabilistic forecasts were validated using the Brier Score (BS), Area Under Curve (AUC) of Receiver Operator Characteristics (ROC) plots and reliability plots. The cNLR and BMA strategies for post-processing performed exceptionally well with BS value of 0.10 and RPS value of 0.11 at all grid points for both methods. The ROC–AUC values for the cNLR and BMA methods were found to be 91.87 and 91.82%, respectively. The results show that improved post-processing techniques can be helpful to predict the flood in advance with accurate precision and warning. HIGHLIGHTS A comprehensive evaluation of TIGGE ensemble precipitation forecast using post-processing methods for the Sabarmati River Basin.; Improve forecast accuracy by cNLR, BMA, logreg, hlogreg, HXLR, and OLR are used.; Brier Score (BS), reliability plots, and AUC and ROC plots are used to rigorously compare post-processing algorithms for model verification.;

A method for developing a numerical rotor model and its further verification based on the results of virtual static structural and modal tests was proposed. Approbation of the method was performed on a model of a low pressure rotor of a high-bypass turbofan engine constructed in a software system for rotor dynamics simulation DYNAMICS R4. Refined on the basis of the results of virtual static structural tests, the model of the rotor main force action line showed good agreement in frequencies and mode shapes with the results of a finite element model, obtained during a virtual modal test.

A novel application of spring-loaded inverted pendulum model is proposed in this study. In particular, we use this model to find the existence of so-called fixed points, which correspond to actual running gaits, as functions of model parameters such as stiffness and energy. Applying the model to experimental data allows us to draw justifiable conclusions on mechanical energy minimisation for running gaits. The data were collected during a study witch 105 athletes. Force was measured using a pressure plate integrated in a treadmill. Kinematic data were recorded using two high-speed video cameras and an accelerometer placed on the back sacral localization. Each athlete completed trials by running at four different targeted velocities (9, 12.5, 16, 19.5 km/h). Running velocity influenced the values of the leg spring stiffness approximations, while the values of stiffness, determined using data from the pressure plate and camera, vary only slightly. The mechanical energy corresponding to periodic running gaits was studied with leg stiffness determined from the experiment. The mechanical energy of the runner slightly exceeded the minimum value of energy required for the existence of fixed points in the model. These results contribute to the general understanding of running gaits in terms of mechanical energy optimization. [ABSTRACT FROM AUTHOR]

A variety of mathematical models have been developed to simulate the biochemical and physico-chemical aspects of the anaerobic digestion (AD) process to treat organic wastes and generate biogas. However, all these models, including the most widely accepted and implemented Anaerobic Digestion Model No.1, remain incapable of adequately representing the material balance of AD and are therefore inherently incapable of material conservation. The absence of robust mass conservation constrains reliable estimates of any kinetic parameters being estimated by regression of empirical data. To address this issue, the present work involved the development of a "framework" for a mass-conserving atomistic mathematical model which is capable of mass conservation, with a relative error in the range of machine precision value and an atom balance with a relative error of ±0.02% whilst obeying the Henry's law and electroneutrality principle. Implementing the model in an Excel spreadsheet, the study calibrated the model using the empirical data derived from batch studies. Although the model shows high fidelity as assessed via inspection, considering several constraints including the drawbacks of the model and implementation platform, the study also provides a non-exhaustive list of limitations and further scope for development. [ABSTRACT FROM AUTHOR]

Recently, new constitutive tensile models for describing the post-cracking behaviour of fibre reinforced concrete for different performance classes were developed by the author(s). The models are based on test data on notched beams with macro fibres, including one type of glass fibres and two polypropylene fibres. Nowadays, a wide range of macro fibres for reinforcing concrete mixtures is available. The objective of this paper is thus to examine whether the newly developed models are applicable for other FRC mixtures. For this purpose, the experimental results of 236 three-point bending tests on notched beams, obtained from Vrijdaghs et al. and the international company Bekaert, are compared with the model predictions. The results indicate that the proposed model for performance class a & b and class c exhibit a higher accuracy at CMOD1 than the model in MC10 and EC2 (next version). However, further optimization is required at CMOD3 for the model of performance class a & b and class d. A strong correlation is also found between the experimental fR1-values, as well as the fR3-values, and the predicted compression zone height of the beam cross-section at midspan by use of those new constitutive models. Moreover, this paper also proposes a modification to the model of Oettel et al. for better estimating the residual flexural tensile strength of FRC mixtures with 4D Dramix fibres. [ABSTRACT FROM AUTHOR]

This study focuses on the real-time precipitation forecast products of the GRAPES_MESO regional ensemble forecast model, which is developed by the Numerical Weather Prediction Center of the China Meteorological Administration and is initialized 1–3 days in advance at 12:00 UTC. Using a national-level homogenized precipitation grid dataset from surface meteorological stations as observational data, a frequency matching method (FMM) is employed to correct precipitation forecasts for different precipitation intensity levels, including light rain, moderate rain, heavy rain, and torrential rain. Case studies and statistical tests (TS scores) are conducted to compare the forecast performance before and after correction. The results indicate that the model's Cumulative Distribution Function (CDF) curves deviate from observations, and the longer the lead time, the more significant the error. The correction coefficients (CCs) show an increasing trend with the growth of precipitation intensity, indicating that for larger precipitation amounts and longer lead times, larger CCs are needed, highlighting the necessity of correction. Analyzing two precipitation events in South China in July 2019, the FMM results in an increase in precipitation intensity and a widening of the range of heavy precipitation. The corrected precipitation magnitudes are closer to the observations. The statistical tests using TS scores reveal that the FMM has a certain correction effect on the overall precipitation forecast in the South China region, especially for longer lead times and higher precipitation intensities, where the correction effect is more significant. The necessity of frequency matching correction becomes more apparent for heavier precipitation, and the correction effect becomes more significant with longer lead times. [ABSTRACT FROM AUTHOR]

Copyright of Diamond & Abrasives Engineering is the property of Zhengzhou Research Institute for Abrasives & Grinding and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the framework of AfriCultuReS project, operational deterministic weather forecasts provide valuable information on the expected weather conditions over the African continent as a part of federation of services within the project. In this study, we investigate the performance of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) over pilot regions in Africa by utilizing available surface observations, satellite and reanalysis data. The verification period covers two consecutive years (June 2018–May 2020). In addition, we assess the ability of the model to provide skillful forecasts through three high-impact precipitation events that occurred during this period. The results show that the model presents both positive and negative biases with respect to its predicted near surface air temperature, underestimates the near surface relative humidity and the mean sea-level pressure, while overestimates the wind speed at 10 m. The neighborhood-based statistical verification of the 24-h accumulated precipitation reveals that the model forecasts the precipitation events more accurately as the verification area is increasing but at higher precipitation thresholds its performance deteriorates. Different variability, errors and correlation between simulated and observed precipitation exist in each forecast lead day and region. A range of model behavior and forecast skill is found with respect to the examined three precipitation events. Skillful forecasts up to four days ahead were provided in the cases of the Tropical Cyclone IDAI and the flash flooding events in northern Tunisia, while the lowest performance was found in the region of the West African Monsoon. [ABSTRACT FROM AUTHOR]

In this study, a heat and mass transfer model for hot air drying of wheat grain piles based on the discrete-continuous medium assumption method was established to understand the wet heat transfer law inside the wheat grain pile during the drying process. Simulations using COMSOL Multiphysics software were then carried out to study the heat transfer and moisture migration in the porous pile structure of wheat under the conditions of 20 °C ambient temperature, 60 °C air temperature, and 1 m/s air speed. The model was validated in combination with wheat hot air-drying experiments. The experimental results showed that the established model can reflect the drying process of the grain pile well, and the experimental values were in good agreement with the predicted values. The temperature, humidity, and flow fields in the wheat pile were unevenly distributed. The temperature distribution of the wheat pile showed a high temperature in the edge region and a low temperature in the center region, the maximum temperature difference reached around 8 °C. The moisture distribution of the pile showed the opposite trend, with lower moisture in the edge region and higher moisture in the center region. The humidity of the upper layer of wheat in the grain pile showed an upward trend over a period of time due to the influence of rising steam, the maximum moisture difference reached about 15%. The velocity of the edge region with a large pore rate was large, and obvious vortex regions were found in the grain layer. The local speed reaches about 5 times the inlet wind speed. Based on the CFD-DEM medium coupling method, the complex pore structure within the grain stacking structure can be accurately constructed, and a mathematical model can be established on this basis, providing a new approach for simulating the moisture and heat transfer of grain stacking structures. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate performance sensitivity to the Cumulus Parameterization Scheme (CPS) used for the Weather Research and Forecasting (WRF) model to predict the atmospheric river‐related precipitation (ARP) event with 206 and 57 mm, highest and area‐averaged precipitation (AAP) per 24‐h, respectively, that occurred over the central mountainous basins of Iran on 31 March 2019. For this purpose, experiments were designed using the 12 (almost all) CPSs available in WRF v4. To verify the predicted precipitation (from the inner 4‐km domain), both point‐scale and grid‐scale comparisons were performed against gauge‐ and satellite‐based observational data at three accumulation time‐scales (12‐, 18‐, and 24‐h) and in three distinct sub‐regions. All scores obtained from the different statistical metrics used, are in complete agreement with a strongly dependent performance of WRF on the CPS used. In addition, the use of Kain‐Fritsch, KF‐CuP, and Grell‐3 CPSs could provide a realistic picture of impending heavy precipitation for WRF. Contrary, the New SAS, Tiedtke, and Zhang‐McFarlane CPSs did not perform satisfactorily in predicting the ARP event. As a result, CPSs with the "momentum transport" option in their modification mechanism are unlikely to adequately simulate the conversion of incoming low‐level moisture from atmospheric river to precipitation. However, precipitation predictions are more accurate at the 24‐h accumulation time‐scale than at the 12‐ and 18‐h. Also, a dry bias in the predictions is expected as the terrain elevation and accumulation time‐scale decrease and the distance from the core of the precipitation field increases. [ABSTRACT FROM AUTHOR]

This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment (SWEX) was conducted. We further refine our study area to the Montecito region owing to some of the highest wind measurements occurring at or near surface station MTIC1, situated on the coast-facing slope overlooking the area. Fires are not uncommon in this area, and the difficulty of egress makes the population particularly vulnerable. Area forecasters often use the sea-level pressure difference (ΔSLP) between Santa Barbara Airport (KSBA) and locations to the north such as Bakersfield (KBFL) to predict Sundowner windstorm occurrence. Our analysis indicates that ΔSLP by itself is prone to high false alarm rates and offers little information regarding downslope wind onset, duration, or magnitude. Additionally, our analysis shows that the high-resolution rapid refresh (HRRR) model has limited predictive skill overall for forecasting winds in the Montecito area. The HRRR, however, skillfully predicts KSBA-KBFL ΔSLP, as does GraphCast, a machine learning weather prediction model. Using a logistic regression model we were able to predict the occurrence of winds exceeding 9 m s−1 with a high probability of detection while minimizing false alarm rates compared to other methods analyzed. This provides a refined and easily computed algorithm for operational applications.

This study introduces and formalizes the concept of classical soundness for robustness diagrams and loop controls. This concept has not been established and formalized in previous literature for this type of workflow model. Although this concept may vary in syntax across different types of workflows (e.g. workflow nets, business process modeling and notation, Petri nets), this study adopts the well-known overarching semantic of classical soundness, which requires that every activity or work done by a system that is determinable from its workflow model observes proper termination and liveness. In the meantime, we discount reset-bound subsystems in our analysis of the classical soundness of our target model. We define classical soundness, along with the formalism and design strategies, to achieve proper termination and liveness on this model in both structural and behavioral aspects of the activities therein. Finally, we establish and prove the time and space complexity of proving classical soundness under these aspects for this model. [ABSTRACT FROM AUTHOR]

Much of the current code provisions for designing slab-column connections against punching shear are based on empirically derived formulations based on tests of partial scale isolated slab-column specimens. Although many experiments have been conducted on shear reinforced concrete flat slabs supported on columns, due to cost or time constraints, there are still many parameters that have not been adequately studied in the laboratory. These tests can be supplemented by analytical results of properly calibrated nonlinear finite element analysis (NLFEA) to enhance the existing experimental database and formulate rational design recommendations for future codes. This paper presents a rational approach for calibrating an NLFEA model in ABAQUS using interior and edge slab-column connection specimens. The calibration includes a study to determine how to effectively model the shear reinforcement and shear reinforced area. This further includes a detailed analysis of the modeling of the shear reinforcing elements to ensure appropriate rotational capability of the shear reinforced region of the slab without significantly reducing the predicted capacity of the model. The calibrated models show good agreement with test data based on load-deflection, moment-curvature, and bolt strain behavior. [ABSTRACT FROM AUTHOR]

With the benefits of small turning radius and high trafficability, the articulated steering half-track tractor had been widely utilized in orchard and small spaced farmland. To study the dynamic performance of the articulated steering half-track tractor and provide a model basis for studying the path tracking control, an accurate multi-body dynamic model of the tractor was required. In this study, the crucial parameters in the dynamic model construction of the tractor were investigated. Firstly, the topology model of the components of the half-track tractor was built by RecurDyn, in which the movement subs and driver functions were given. Secondly, considering the difference of dynamic characteristic of the articulated steering tractor with respect to different pavement hardnesses, the soft and hard pavement models were constructed by employing the harmonic superposition method. Finally, the simulations of the half-track tractor under straight-line and swerve had been conducted on the two types of pavements, and the simulation results were compared with the experimental and theoretical results. The results indicated that the average speed error of the dynamic model on hard pavement and farmland soft pavement were 2.7% and 2.1% compared with the real tractor tests. At the same time, the straight-line driving offset errors of the dynamic model on the two pavements were 1.6% and 3.8% for the front wheels and the rear wheels offset errors were 3.9% and 2.4%, respectively. Furthermore, the turning radius error under front wheel steering was 8.2% and the error under articulated steering was 5.3%. It is proved that the established dynamic model had high accuracy, which provides an efficient approach to analyze the dynamic features of the half-track tractor. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University: Engineering Science is the property of Editorial Office of Journal of Zhengzhou University: Engineering Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article is devoted to the study of a nitrogen supply system for cooling an experimental device designed for testing in a pulsed reactor with a graphite moderator. To analyze emergency situations caused by disruption of the nitrogen supply system in the cooling paths of the fuel assembly cover and the experimental device power housing, a mathematical model has been developed to describe thermodynamic processes in a system of interconnected tanks that simulate individual sections of the experimental device hydrodynamic cooling system in a pulsed graphite reactor and implemented in the mathematical interactive package for engineering calculations in MATLAB/Simulink. To study the normal operation of the system and analyze possible emergencies, the cooling system of the experimental device was presented in the form of groups of interconnected sections of the hydrodynamic system-tanks, with specified volumes and hydraulic resistances of pipelines connecting these tanks. Verification of the model, calculations of the experimental device cooling system normal operation mode, calculations of emergency situations caused by a violation of the nitrogen supply system normal operation in the cooling paths of the fuel assembly cover were carried out, in particular, it was found that for the cooling system of the experimental device WF-2, the breakdown of the gearbox P-12 can cause depressurization of the fuel assembly cover and an increase in pressure in the power housing, the opening of the safety valve prevents exceeding the pressure limit in the housing, the device maintains integrity even in emergency situations, without being subjected to destruction of the power elements of the structure at a pressure of up to 8 MPa. [ABSTRACT FROM AUTHOR]

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration–time curve, AUC; maximum serum concentration, Cmax; clearance, CL) being within 0.8‐ to 1.25‐fold, 56/62 within 0.67‐ to 1.5‐fold, and 61/62 within 0.5‐ to 2.0‐fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8‐ to 1.25‐fold, 27/31 within 0.67‐ to 1.5‐fold, and all were within 0.5‐ to 2.0‐fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development. [ABSTRACT FROM AUTHOR]

Abstract The present study aimed to evaluate performance sensitivity to the Cumulus Parameterization Scheme (CPS) used for the Weather Research and Forecasting (WRF) model to predict the atmospheric river‐related precipitation (ARP) event with 206 and 57 mm, highest and area‐averaged precipitation (AAP) per 24‐h, respectively, that occurred over the central mountainous basins of Iran on 31 March 2019. For this purpose, experiments were designed using the 12 (almost all) CPSs available in WRF v4. To verify the predicted precipitation (from the inner 4‐km domain), both point‐scale and grid‐scale comparisons were performed against gauge‐ and satellite‐based observational data at three accumulation time‐scales (12‐, 18‐, and 24‐h) and in three distinct sub‐regions. All scores obtained from the different statistical metrics used, are in complete agreement with a strongly dependent performance of WRF on the CPS used. In addition, the use of Kain‐Fritsch, KF‐CuP, and Grell‐3 CPSs could provide a realistic picture of impending heavy precipitation for WRF. Contrary, the New SAS, Tiedtke, and Zhang‐McFarlane CPSs did not perform satisfactorily in predicting the ARP event. As a result, CPSs with the “momentum transport” option in their modification mechanism are unlikely to adequately simulate the conversion of incoming low‐level moisture from atmospheric river to precipitation. However, precipitation predictions are more accurate at the 24‐h accumulation time‐scale than at the 12‐ and 18‐h. Also, a dry bias in the predictions is expected as the terrain elevation and accumulation time‐scale decrease and the distance from the core of the precipitation field increases.

This study focuses on the real-time precipitation forecast products of the GRAPES_MESO regional ensemble forecast model, which is developed by the Numerical Weather Prediction Center of the China Meteorological Administration and is initialized 1–3 days in advance at 12:00 UTC. Using a national-level homogenized precipitation grid dataset from surface meteorological stations as observational data, a frequency matching method (FMM) is employed to correct precipitation forecasts for different precipitation intensity levels, including light rain, moderate rain, heavy rain, and torrential rain. Case studies and statistical tests (TS scores) are conducted to compare the forecast performance before and after correction. The results indicate that the model’s Cumulative Distribution Function (CDF) curves deviate from observations, and the longer the lead time, the more significant the error. The correction coefficients (CCs) show an increasing trend with the growth of precipitation intensity, indicating that for larger precipitation amounts and longer lead times, larger CCs are needed, highlighting the necessity of correction. Analyzing two precipitation events in South China in July 2019, the FMM results in an increase in precipitation intensity and a widening of the range of heavy precipitation. The corrected precipitation magnitudes are closer to the observations. The statistical tests using TS scores reveal that the FMM has a certain correction effect on the overall precipitation forecast in the South China region, especially for longer lead times and higher precipitation intensities, where the correction effect is more significant. The necessity of frequency matching correction becomes more apparent for heavier precipitation, and the correction effect becomes more significant with longer lead times.

This research aims to extend the isothermal continuum mechanical modeling framework of hydraulic fracturing in porous materials to account for the non-isothermal processes. Whereas the theory of porous media is used for the macroscopic material description, the phase-field method is utilized for modeling the crack initiation and propagation. We proceed in this study from a two-phase porous material consisting of thermomechanically interacting pore fluid and solid matrix. The heat exchange between the fluid in the crack and the surrounding porous environment through the diffusive fracture edges is carefully studied, and new formulations here are proposed. Besides, temperature-dependent solid and fluid material parameters are taken into account, which is of particular importance in connection with fluid viscosity and its effect on post-cracking pressure behavior. This continuum mechanical treatment results in strongly coupled partial differential equations of the mass, the momentum, and the energy balance of the thermally non-equilibrated constituents. Using the finite element method, two-dimensional initial-boundary-value problems are presented to show, on the one hand, the stability and robustness of the applied numerical algorithm in solving the emerged strongly coupled problem in the convection-dominated heat transport state. On the other hand, they show the capability of the modeling scheme in predicting important instances related to hydraulic fracturing and the role of the temperature field in this process. Additionally, they show the importance of using stabilization techniques, such as adding an artificial thermo-diffusivity term, to mitigate temperature fluctuations at high flow velocity. [ABSTRACT FROM AUTHOR]

The final model for rail transportation is the introduction of full digitalization to support communication and transport services, which will be available to the public in the future. The process of digitalization is based on models that reproduce the real physical structures present in the transport network. Due to the high complexity of the structure and its mapping, it is necessary to find methods that automatically verify the proposed created model. This approach supports manual activities that, at this moment, are not sufficient. Automatization's description requires a formal approach. Such a description has been developed as part of a research project, "The Digital Railway. The digital twin of the ETCS application. Virtual prototyping and simulation of operational scenarios." In this paper, a formal model of the ETCS application has been proposed, and a formal approach to its verification is described. [ABSTRACT FROM AUTHOR]

In this paper, the problem of suboptimal stabilization of an object with discrete time, output and control uncertainties, and bounded external perturbation is considered. The autoregressive nominal model coefficients, uncertainty amplification coefficients, norm and external disturbance offset are assumed to be unknown. The quality indicator is the worst-case asymptotic upper bound of the output modulus of the object. The solution of the problem in conditions of non-identifiability of all unknown parameters is based on the method of recurrent target inequalities and optimal online estimation, in which the quality index of the control problem serves as an identification criterion. A non-linear replacement of the unknown parameter perturbations that reduces the optimal online estimation problem to a fractional linear programming problem is proposed. The performance of adaptive suboptimal control is illustrated by numerical simulation results. [ABSTRACT FROM AUTHOR]

In this paper, three types of hybrid monopiles are proposed for 3MW OWTs in offshore areas where the batholith is shallowly buried. Three-dimensional FE models are established considering the soil-structure-interaction (SSI) to calculate the bearing performances of these monopiles. Model verification is conducted through comparisons with existing numerical results. The static bearing performance and dynamic character under the serviceability limit state (SLS) in silty sand and normally consolidated (NC) clay are investigated. In the static analysis, we focus on the lateral deflection and the rotation at the mudline, whereas in the modal analysis, we focus on the natural frequencies of the OWTs. Results show that the circular skirt performs better than square fins in improving the bearing performance of traditional monopiles, and the improving effect increases with the length of the additional components. In addition, the improving effect is more obvious in NC clay than in silty sand. [ABSTRACT FROM AUTHOR]

A simplified inverter–motor stator system model is presented in the paper. The model is based on elementary dynamic blocks described by differential equations. The paper presents the results of research aimed at verifying the model on different devices with different types of inverters and motors. Model accuracy coefficients have been developed for all examined cases, confirming the high conformity of the model to the measured speeds and torques of asynchronous motors. The model was also used to simulate the operation of a drive system with a synchronous motor, obtaining high compliance of speed and torque mapping. The presented cases of verification of a simplified model confirm the possibility of using it to model different devices fed by frequency inverters, controlled both manually and automatically. The presented model, using simple description, ensures high accuracy of speed and torque mapping. It should be emphasized that most parameters in the presented model are calculated for motors and inverters based on data sheets. • The simplified model of the system: inverter–motor stator is presented. • Experimental verification confirming good mapping of speed and torques of motor. • Verification performed on different types of machines, motors and inverters. • Model can be used to modeling both synchronous and asynchronous motors. • Inputting only parameters from data sheets of motors and inverters. [ABSTRACT FROM AUTHOR]

Industrial control systems (ICS) are required to be operated safely under cyberattacks. Fallback control is necessary for the safe operation of ICS. As one of fallback control systems, we develop a resilient third-party monitoring system. This system consists of Programmable Logic Controllers (PLCs) for normal control and for fallback control. The normal PLC controls field devices, and the fallback PLC takes over the control after the normal PLC is attacked. The fallback control of this paper is the control takeover of a robot arm control system. To quickly transition to this fallback control, it is necessary to incorporate a supervisor function to manage each PLC function in an integrated manner. This paper aims to propose a modeling method of ICS functions and its analysis method to ensure that the supervisor can work properly under cyberattacks. For modeling, we use UPPAAL, specializing in formal verification by timed automata. We implement the models of each PLC and supervisor on UPPAAL. To quantitatively analyze whether the supervisor can really realize the incident response during cyberattacks, we give the specifications necessary for fallback control to the supervisor model using Timed Computation Tree Logic (TCTL) and verify its feasibility. [ABSTRACT FROM AUTHOR]

Peristaltic flow is important in many biological processes, including digestion, and forms an important component of any in silico model of the stomach. There is a clear need to verify the simulations of such flows. An analytical solution was identified that can be used for model verification, which gives an equation for the net volumetric flow over a cycle for an applied sinusoidal wall motion. Both a smooth particle hydrodynamics (SPH) code (from the CSIRO), which is being used to develop a stomach model that includes wall motion, buoyancy, acid secretion and food breakdown, and the Ansys Fluent Finite Volume Method (FVM) solver, that is widely used in industry for complex engineering flows, are used in this exercise. Both give excellent agreement with the analytic solution for the net flow over a cycle for a range of occlusion ratios of 0.1–0.6. Very similar velocity fields are obtained with the two methods. The impact of parameters affecting solution stability and accuracy are described and investigated. Having validated the moving wall capability of the SPH model it can be used with confidence in stomach simulations that include wall motion. [ABSTRACT FROM AUTHOR]

In order to study the performance differences of different ensemble forecast products for temperature and precipitation forecasts in Chongqing, based on the Chongqing Convective-scale Ensemble Prediction System (CQCEPS) which has been operationally implemented, a comprehensive comparison and analysis are carried out for the differences as well as temporal and spatial distribution characteristics in the forecast performance of ensemble forecast application products of surface elements such as the control forecast of 24 h cumulative precipitation and 2 m temperature, ensemble mean forecast and ensemble quantile forecast for the whole year of 2020, as well as the probability matched mean forecast of 24 h cumulative precipitation. The results show that (1) the precipitation prediction performance of each ensemble forecast product decreases with the increase of predicting lead time. When predicting lead time is consistent, ensemble mean forecast, probability matched mean forecast, and 60% and higher quantile forecasts are better than control forecast. The 90% quantile forecast is the best among quantile forecast products. (2) In summer and autumn, the forecast results of each product are quite different, and the 90% quantile forecast, probability matched mean forecast and ensemble mean forecast are better than others. (3) The SEEPS scores of control forecast, ensemble mean forecast, probability matched mean forecast and the 90% quantile forecast show higher accuracy in eastern Sichuan and poorer accuracy in the southeast and northeast of Chongqing, indicating that the prediction performance may have a certain relationship with the terrain. (4) For temperature forecasts with different lead times, overall, the ensemble mean forecast performs the best among all of the prediction products, and the 70% quantile forecast performs the best among all quantile products.

The emergence and development of systems of systems (SoSs) have expanded the complexity and adaptability of systems engineering. Due to the heterogeneity of its constituent systems, designing and analyzing an SoS faces enormous challenges. Therefore, the verification of an SoS is important in its design phase. However, related methods and techniques are still in the preliminary research state, mainly for requirements verification and system verification, and a lack of efforts in design verification for SoSs. Aiming to provide the ability to detect hazardous states at the design phase, we worked on a novel method for automatically generating test cases for model verification in SoSs. Considering the characteristics of SoSs, the method adopts fault injection and model-based system engineering as the foundations to extend the automated generation capability of test cases. This paper proposes an automatic test generation (ATG) method for an SoS based on fault injection and model-based systems engineering (MBSE). It is meant to generate test cases that can be used to check the effectiveness of fault detection or identification in SoSs and for the effective testing of their constituent systems (CSs). This paper discusses scenario generation and ATG in linear temporal logic and designs an algorithm to generate traces as test suites, taking into account the constraints of the models. By establishing a concept alignment example (CAE) as the experimental use case, three test scenarios are generated automatically, showing that the use of the proposed ATG method provides a reasonable hazardous detection capability for verification in SoS design. The main contributions of the paper are (1) the description of the proposed two-phase ATG approach with fault-centric modeling activities and generation-related activities; (2) the explanation of the designed ATG algorithm at both high and low levels; and (3) the discussion of the experiment in an emergency response CAE with three generated test scenarios. [ABSTRACT FROM AUTHOR]

Verification processes of rainfall-runoff modeling are important to improve the skill of hydrological models to reproduce water cycles in river basins. It is ideal that newly developed models are compared with many benchmarking conventional models in many river basins as part of the verification process. However, this robust verification is timeconsuming if model developers prepare data and models from scratch. Here we present a useful dataset which can accelerate the robust verification of hydrological models. Our newly developed dataset, Multi-model Ensemble for Robust Verification of hydrological modeling in Japan (MERV-Jp), provides runoff simulation by 44 calibrated conceptual hydrological models in 135 Japanese river basins as well as meteorological forcing which is necessary to drive conceptual hydrological models. By comparing simulated runoff with river discharge observations which are not used for the calibration of hydrological models, we find that the best models in the 44 models can reproduce observed river runoff with KGE larger than 0.6 in most of the 135 river basins, so that the runoff simulation of MERV-Jp is reasonably accurate. MERV-Jp is publicly available to support all hydrological model developers to robustly verify their model improvement. [ABSTRACT FROM AUTHOR]

The working eigenvectors of a truck chassis are determined experimentally using an electrodynamic vibrator over a broad range of exciting frequencies. A method is proposed and adopted for selecting the working eigenvectors of the chassis, which are compared with its intrinsic vibrations, as determined by calculation. Comparison of the experimental data with the numerical calculations confirms the model for global eigenvectors at frequencies up to 35 Hz. [ABSTRACT FROM AUTHOR]