Modeling of Ship Maneuvering Motion Using Neural Networks

In this paper, Neural Networks （NNs） are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.

Modeling of turbulent,isothermal and cryogenic cavitation under attached conditions

Cavitation is often triggered when the fluid pres- sure is lower than the vapor pressure at a local thermo- dynamic state. The present article reviews recent progress made toward developing modeling and computational strat- egies for cavitation predictions under both isothermal and cryogenic conditions, with an emphasis on the attached cav- ity. The review considers alternative cavitation models along Reynolds-averaged Navier-Stokes and very lager eddy simu- lation turbulence approaches to ensure that the computational tools can handle flows of engineering interests. Observing the substantial uncertainties associated with both modeling and experimental information, surrogate modeling strategies are reviewed to assess the implications and relative impor- tance of the various modeling and materials parameters. The exchange between static and dynamic pressures under the influence of the viscous effects can have a noticeable impact on the effective shape of a solid object, which can impact the cavitation structure. The thermal effect with respect to evaporation and condensation dynamics is examined to shed light on the fluid physics associated with cryogenic cav- itation. The surrogate modeling techniques are highlighted in the context of modeling sensitivity assessment. Keywords

Application of 3-D Geoscience Modeling Technology for the Estimation of Solid Mineral Reserves

Applying new approaches, methods, and technologies for the estimation of reserves can effectively improve the efficiency and accuracy of assessments of solid mineral resources. After analyzing the development of 3-D geoscience modeling technology （3-D GMT）, this paper discusses the application of 3-D GMT for the estimation of solid mineral reserves, emphatically introducing its workflow and two key technologies, 3-D orebody surface modeling, and property modeling. Moreover, the paper analyzes the limitations of traditional methods, such as the section method and geological block method, and points out the advantages of 3-D GMT： building more accurate 3-D orebody models, expressing the internal inhomogeneous attributes of an orebody, reducing the potential for errors in the estimation of reserves, and implementing dynamic estimations of reserves.

Lumped parameter analytic modeling and behavioral simulation of a 3-DOF MEMS gyro-accelerometer

A new analytical model of a 3-degree-of-freedom （3-DOF） gyro-accelerometer system consisting of a 1-DOF drive and 2-DOF sense modes is presented. The model constructs lumped differential equations associated with each DOFof the system by vector analysis. The coupled differential equations thus established are solved analytically for their responses in both the time and frequency domains. Considering these frequency response equations, novel device design concepts are derived by forcing the sense phase to zero, which leads to a certain relationship between the structural frequencies, thereby causing minimization of the damping effect on the performance of the system. Furthermore, the feasibility of the present gyro-accelerometer structure is studied using a unique discriminatory scheme for the detection of both gyro action and linear acceleration at their events. This scheme combines the formulated settled transient solution of the gyro-accelerometer with the processes of synchronous demodulation and filtration, which leads to the in-phase and quadrature components of the system＇s output signal. These two components can be utilized in the detection of angular motion and linear acceleration. The obtained analytical results are validated by simulation in a MATLAB/Simulink environment, and it is found that the results are in excellent agreement with each other.

An automatic unified modeling method of geological object and engineering object based on tri-prism(TP)

For the interaction relation between geological object and engineering object in some fields related to water conservancy and hydropower, a unified modeling idea was proposed. On the basis of summarizing both advantages and disadvantages of existing modeling methods, an automatic unified modeling method of both engineering and geological objects based on tri-prism(TP) model was presented. Through the lossless correction algorithm of deviated drill holes contained in this method, the real deviated drill holes could be corrected into the equivalent virtual vertical ones. And the correction accuracy fully meets the requirements of unified modeling. With the virtual vertical drilling data, TIN construction of both cover layer and other stratums would be built in order to obtain the 3D geological model. Then, the engineering design data would be introduced into the 3D geological model for achieving unified modeling. For this process, the volume subdividing and restructuring principles were introduced to deal with the spatial relationships between engineering object and geological object. In order to improve the efficiency of unified modeling, the reconstruction of TIN based on constraint information was also applied in this method. At last, the feasibility and validation of the unified modeling method as well as its relevant key algorithms were verified by specific experiments and analysis of results.

Effects of Three Typical Resistivity Models on Pulsed Inductive Plasma Acceleration Modeling

The effects of three different typical resistivity models（Spitzer, Z＆L and M＆G） on the performance of pulsed inductive acceleration plasma are studied. Numerical results show that their influences decrease with the increase of the plasma temperature. The significant discriminations among them appear at the plasma temperature lower than 2.5 eV, and the maximum gap of the pulsed inductive plasma accelerated efficiency is approximately 2.5%.Moreover, the pulsed inductive plasma accelerated efficiency is absolutely related to the dynamic impedance parameters, such as voltage, inductance, capacitance and flow rate. However, the distribution of the efficiency as a function of plasma temperature with three resistivity models has nothing to do with the dynamic impedance parameter.

Modeling and identification for soft sensor systems based on the separation of multi-dynamic and static characteristics

Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.

Integrating artificial neural networks and geostatistics for optimum 3D geological block modeling in mineral reserve estimation:A case study

In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.

MODELING OF FMS BASED ON UML AND OPNS

As the main component of computer integrated manufacturing system (CIMS), flexible manufacturing system (FMS) should be an open system with reusability and extenchaility. Moreover, as FMS is a complex asynchronous concurrent system, its model also should have the abilities to express the concurrency in the system and to analyze the behavior of the system. It is difficult to use any one method to model such a complex system as FMS. A modeling method using Object-oriented modeling language-unified modeling language (UML) and object-Oriented Petri nets (OPNs) is proposed. Class diagram in UML is used to represent the static relations among the objects in FMS. OPNs are used to model the dynamic behavior of the objects and conduct performance analysis. OPNs also can be used to identify the attributes and operations of the objects. The model can describe the system integrally and can be used to design FMS control software naturally.

Contouring error modeling and simulation of a four-axis motion control system

A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.

Torsional stiffness modeling and optimization of the rubber torsion bushing for a light tracked vehicle

Taking the rubber torsion bushing of a certain type of all-terrain tracked vehicle as the research object,a theoretical model of torsional stiffness was proposed according to the non-linear characteristics of rubber components and structural feature of the suspension. Simulations were carried out under different working conditions to obtain root mean square of vertical weighted acceleration as the evaluation index for ride performance of the all-terrain tracked vehicle,with a dynamics model of the whole vehicle based on the theoretical model of the torsional stiffness and standard road roughness as excitation input. Response surface method was used to establish the parametric optimization model of the torsional stiffness. The evaluation index showed that ride performance of the vehicle with optimized torsional stiffness model of suspension was improved compared with previous model fromexperiment. The torsional stiffness model of rubber bushing provided a theoretical basis for the design of the rubber torsion bushing in light tracked vehicles.

Modeling of Inner Surface Modification of a Cylindrical Tube by Plasma-Based Low-Energy Ion Implantation

The inner surface modification process by plasma-based low-energy ion implantation（PBLEII）with an electron cyclotron resonance（ECR）microwave plasma source located at the central axis of a cylindrical tube is modeled to optimize the low-energy ion implantation parameters for industrial applications.In this paper,a magnetized plasma diffusion fluid model has been established to describe the plasma nonuniformity caused by plasma diffusion under an axial magnetic field during the pulse-off time of low pulsed negative bias.Using this plasma density distribution as the initial condition,a sheath collisional fluid model is built up to describe the sheath evolution and ion implantation during the pulse-on time.The plasma nonuniformity at the end of the pulse-off time is more apparent along the radial direction compared with that in the axial direction due to the geometry of the linear plasma source in the center and the difference between perpendicular and parallel plasma diffusion coefficients with respect to the magnetic field.The normalized nitrogen plasma densities on the inner and outer surfaces of the tube are observed to be about 0.39 and 0.24,respectively,of which the value is 1 at the central plasma source.After a 5μs pulse-on time,in the area less than 2 cm from the end of the tube,the nitrogen ion implantation energy decreases from 1.5 keV to 1.3 keV and the ion implantation angle increases from several degrees to more than 40°;both variations reduce the nitrogen ion implantation depth.However,the nitrogen ion implantation dose peaks of about 2×10^（10）-7×10^（10）ions/cm^2 in this area are 2-4 times higher than that of 1.18×10^（10）ions/cm^2 and 1.63×10^（10）ions/cm^2 on the inner and outer surfaces of the tube.The sufficient ion implantation dose ensures an acceptable modification effect near the end of the tube under the low energy and large angle conditions for nitrogen ion implantation,because the modification effect is mainly determined by the ion implantation dose,just as the mass transfer process in PBLEII is dominated by low-energy ion implantation and thermal diffusion.Therefore,a comparatively uniform surface modification by the low-energy nitrogen ion implantation is achieved along the cylindrical tube on both the inner and outer surfaces.

A new generic reaction for modeling fluid catalytic cracking risers

A new generic reaction in the form of PC_i→PC_m+[i,m]→PC_m+λi,m coke+surplusage has been proposed for describing the catalytic cracking behavior of petroleum narrow cuts or pseudo-components(PCs),where the rate constant formula is derived from the transition state theory and the coking amount is correlated to the properties of the intermediate substance [i,m].In composing the cracking reaction network for feedstock and product oils,only the product PC m of the proposed generic reaction is used,which together with a criterion for excluding exothermic reactions,distinctly reduces the number of reactions in the network.With the proposed cracking reaction scheme coupled with special pseudo-components,a predictive one-dimensional steady state model for fluid catalytic cracking risers is formulated in the sense that for a given riser and given catalyst,the model parameters are independent of stock oils,product schemes and other operational conditions.The great correlating and predicting capability of the resulted model is tested with production data in different scenarios of four commercial risers.

Observation on the Effect of Parental Participation in Nursing Under the IMCHB Model in Neonatal Hypoxic-Ischemic Encephalopathy

Objective:To investigate the clinical effects of parental participation in nursing under the Interaction Model of Client Health Behavior(IMCHB)model in neonatal hypoxic-ischemic encephalopathy(HIE).Methods:The First Affiliated Hospital of Gannan Medical University included 46 newborns with HIE admitted from October 2021 to October 2023 into the study population.They were divided into a control group and an observation group according to the random number table method,with the control group adopting routine nursing,and the observation group implementing parental participation in nursing under the IMCHB model.The indicators of physical,intellectual,and psychomotor development of the two groups were compared before and after nursing.Results:The physical,intellectual,and psychomotor development of the observation group was higher than that of the control group after 3 months of nursing,and the difference was statistically significant(P<0.05).Conclusion:The implementation of the IMCHB model of parental participation in the clinical care of HIE neonates can further promote their physical,intellectual,and psychomotor development.

Comparison of machine learning models for gully erosion susceptibility mapping

Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,especially in the Northern provinces.A number of studies have been recently undertaken to study this process and to predict it over space and ultimately,in a broader national effort,to limit its negative effects on local communities.We focused on the Bastam watershed where 9.3%of its surface is currently affected by gullying.Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability.However,unlike the bivariate statistical models,their structure does not provide intuitive and quantifiable measures of environmental preconditioning factors.To cope with such weakness,we interpret preconditioning causes on the basis of a bivariate approach namely,Index of Entropy.And,we performed the susceptibility mapping procedure by testing three extensions of a decision tree model namely,Alternating Decision Tree(ADTree),Naive-Bayes tree(NBTree),and Logistic Model Tree(LMT).We dichotomized the gully information over space into gully presence/absence conditions,which we further explored in their calibration and validation stages.Being the presence/absence information and associated factors identical,the resulting differences are only due to the algorithmic structures of the three models we chose.Such differences are not significant in terms of performances;in fact,the three models produce outstanding predictive AUC measures(ADTree=0.922;NBTree=0.939;LMT=0.944).However,the associated mapping results depict very different patterns where only the LMT is associated with reasonable susceptibility patterns.This is a strong indication of what model combines best performance and mapping for any natural hazard-oriented application.

New partial cooperation model for bilevel programming problems

Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level does not depend on the leader’s decision. A new model is proposed to solve this deficiency. It is proved the feasibility of the new model when the reaction set of the lower level is lower semicontinuous. And the numerical results show that the new model has optimal solutions when the reaction set of the lower level is discrete, lower semi-continuous and non-lower semi-continuous.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Applicability of five models to simulate water infiltration into soil with added biochar

As a soil amendment, biochar can reduce soil bulk density, increase soil porosity, and alter soil aggregates and thus affect the infiltration. Researchers have proposed and revised several theoretical models to describe the process of soil infiltration. Although these models have been successfully used to evaluate the soil infiltration in different scenarios in agricultural fields, little effort has been devoted to assess their performances in arid and semi-arid soils after the addition of biochar. A laboratory experiment was performed to study the infiltration characteristics of two typical Loess Plateau soils at three particle sizes（2–1, 1–0.25, and 〈0.25 mm） and five biochar application amounts（0, 10, 50, 100, and 150 g/kg）. The performance of five models（i.e., the Philip model, Kostiakov model, Mezencev model, USDA-NRCS model, and Horton model） in simulating the infiltration process was then evaluated based on the adjusted coefficient of determination and a reduced Chi-Square test. Results indicated that the Horton model best simulated the water-infiltration process in an aeolian sandy soil with added biochar. However, the Mezencev model best simulated the infiltration process in a loamy clay soil（Eum-Orthic Anthrosol）. The three-parameter model, i.e., Mezencev and Horton models can better describe the relationship between cumulative infiltration and infiltration time. In conclusion, biochar reduced the soil infiltration capacity of the aeolian sandy soil and increased that of the Eum-Orthic Anthrosol.

Turbulence and cavitation models for time-dependent turbulent cavitating flows

Cavitation typically occurs when the fluid pressure is lower than the vapor pressure at a local thermodynamic state, and the flow is frequently unsteady and turbulent. To assess the state-of-the-art of computational capabilities for unsteady cavitating flows, different cavitation and turbulence model combinations are conducted. The selected cavitation models include several widely-used models including one based on phenomenological argument and the other utilizing interface dynamics. The k-e turbulence model with additional implementation of the filter function and density correction function are considered to reduce the eddy viscosity according to the computed turbulence length scale and local fluid density respectively. We have also blended these alternative cavitation and lustrate that the eddy viscosity turbulence treatments, to ilnear the closure region can significantly influence the capture of detached cavity. From the experimental validations regarding the force analysis, frequency, and the cavity visualization, no single model combination performs best in all aspects. Furthermore, the implications of parameters contained in different cavitation models are investigated. The phase change process is more pronounced around the detached cavity, which is better illustrated by the interfacial dynamics model. Our study provides insight to aid further modeling development.

DPM simulation in an underground entry: Comparison between particle and species models

The diesel particulate matter(DPM) emission from diesel powered equipment in underground mines can cause health hazards including cancer to the miners. The understanding of the DPM propagation pattern under realistic mining condition is required for selecting proper DPM control strategies and to improve working practices in underground mines. In this paper, three dimensional simulations of DPM emission from the exhaust tail pipe of a load-haul-dump(LHD) vehicle and its subsequent distribution inside an isolated zone in the typical underground mine are carried out using two different solution models available in Ansys Fluent. The incoming fresh air into the isolated zone is treated as a continuous phase and DPM is treated either as a continuous phase(gas) or as a secondary discrete phase(particle). Species transport model is used when DPM is treated as gas and discrete phase model is used when DPM is assumed to behave like a particle. The distributions of DPM concentration inside the isolated zone obtained from each method are presented and compared. From the comparison results, an accurate and economical solution technique for DPM evaluation can be selected.