Modeling time-dependent mechanical behavior of hard rock considering excavation-induced damage and complex 3D stress states

To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength parameters.The proposed model is implemented in a self-developed numerical code,i.e.CASRock.The reliability of the model is validated through experiments.It is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced damage.The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the model.Finally,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

1 Introduction.With the continuous growth of the global population,the energy demand continues to increase.However,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],etc.To resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable development.Thereinto,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060.It is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

Application of a 2 Parameter Weibull Distribution in Modeling of State Holding Time in HIV/AIDS Transition Dynamics

This study investigates the application of the two-parameter Weibull distribution in modeling state holding times within HIV/AIDS progression dynamics. By comparing the performance of the Weibull-based Accelerated Failure Time (AFT) model, Cox Proportional Hazards model, and Survival model, we assess the effectiveness of these models in capturing survival rates across varying gender, age groups, and treatment categories. Simulated data was used to fit the models, with model identification criteria (AIC, BIC, and R2) applied for evaluation. Results indicate that the AFT model is particularly sensitive to interaction terms, showing significant effects for older age groups (50 - 60 years) and treatment interaction, while the Cox model provides a more stable fit across all age groups. The Survival model displayed variability, with its performance diminishing when interaction terms were introduced, particularly in older age groups. Overall, while the AFT model captures the complexities of interactions in the data, the Cox model’s stability suggests it may be better suited for general analyses without strong interaction effects. The findings highlight the importance of model selection in survival analysis, especially in complex disease progression scenarios like HIV/AIDS.

Four-Electron Systems in the Impurity Hubbard Model. Second Triplet State. Spectra of the System in the ν-Dimensional Lattice Zν

We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.

Degenerate States in Nonlinear Sigma Model with SU(2) Symmetry

Entanglement in quantum theory is a peculiar concept to scientists. With this concept we are forced to re-consider the cluster property which means that one event is irrelevant to another event when they are fully far away. In the recent works we showed that the quasi-degenerate states induce the violation of cluster property in antiferromagnets when the continuous symmetry breaks spontaneously. We expect that the violation of cluster property will be observed in other materials too, because the spontaneous symmetry breaking is found in many systems such as the high temperature superconductors and the superfluidity. In order to examine the cluster property for these materials, we studied a quantum nonlinear sigma model with U(1) symmetry in the previous work. There we showed that the model does have quasi-degenerate states. In this paper we study the quantum nonlinear sigma model with SU(2) symmetry. In our approach we first define the quantum system on the lattice and then adopt the representation where the kinetic term is diagonalized. Since we have no definition on the conjugate variable to the angle variable, we use the angular momentum operators instead for the kinetic term. In this representation we introduce the states with the fixed quantum numbers and carry out numerical calculations using quantum Monte Carlo methods and other methods. Through analytical and numerical studies, we conclude that the energy of the quasi-degenerate state is proportional to the squared total angular momentum as well as to the inverse of the lattice size.

Optimizing near-carbon-free nuclear energy systems:advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation

Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.

Shock Initiation Experiments with Modeling on a DNAN Based MeltCast Insensitive Explosive

2,4-dinitroanisole(DNAN)is a good replacement for 2,4,6-trinitrotoluene(TNT)in melt-cast explosives due to its superior insensitivity.With the increasing use of DNAN-based melt-cast explosives,the prediction of reaction violence and hazard assessment of the explosives subjected to shock is of great significance.This study investigated the shock initiation characteristics for a DNAN-based melt-cast explosive,DHFA,using the one-dimensional Lagrangian apparatus.The embedded manganin gauges in the apparatus record the pressure histories at four Lagrangian positions and show that shock-todetonation transition in DHFA needs a high input shock pressure.The experimental data are analyzed to calibrate the Ignition and Growth model.The calibration is performed using an objective function based on both pressure history and the arrival time of shock.Good agreement between experimental and calculated pressure histories indicates the high accuracy of the calibrated parameters with the optimization method.

Simulation of Start-Up Process of Turbofan Engine Based on Full-State Characteristics of Fan

Difficulties in obtaining component characteristics in the sub-idle state of rotor constrain the simulation capabilities of ground and windmill start-up processes for turbofan engines.This paper proposes a backbone feature method based on conventional characteristics parameters to derive the full-state characteristics of fan.The application of the fan’s full-state characteristics in component-level model of turbofan engine enables zero-speed iterative simulation for ground start-up process and windmill simulation for windmill start-up process,thereby improving the simulation capability of sub-idle state during turbofan engine start-up.

Stiffness Characteristics of a Basic Nonlinear Air Spring Model

This study predicts the characteristics of a compressible polytropic air spring model. A second-order nonlinear autonomous air spring model is presented. The proposed model is based on the assumption that polytropic processes occur. Isothermal and isentropic compression and expansion of the air within the spring chambers are the two scenarios that are taken into consideration. In these situations, the air inside the spring chambers compresses and expands, resulting in nonlinear spring restoring forces. The MATLAB/Simulink software environment is used to build a numerical simulation model for the dynamic behavior of the air spring. To quantify the values of the stiffnesses of the proposed models, a numerical solution is run over time for various values of the design parameters. The isentropic process case has a higher dynamic air spring stiffness than the isothermal process case, according to the results. The size of the air spring chamber and the area of the air spring piston influence the air spring stiffness in both situations. It is demonstrated that the stiffness of the air spring increases linearly with increasing piston area and decreases nonlinearly with increasing air chamber length. As long as the ratio of the vibration’s amplitude to the air spring’s chamber length is small, there is good agreement in both scenarios between the linearized model and the full nonlinear model. This implies that linear modeling is a reasonable approximation of the complete nonlinear model in this particular scenario.

Optimal state and branch sequence based parameter estimation of continuous hidden Markov model

A parameter estimation algorithm of the continuous hidden Markov model isintroduced and the rigorous proof of its convergence is also included. The algorithm uses theViterbi algorithm instead of K-means clustering used in the segmental K-means algorithm to determineoptimal state and branch sequences. Based on the optimal sequence, parameters are estimated withmaximum-likelihood as objective functions. Comparisons with the traditional Baum-Welch and segmentalK-means algorithms on various aspects, such as optimal objectives and fundamentals, are made. Allthree algorithms are applied to face recognition. Results indicate that the proposed algorithm canreduce training time with comparable recognition rate and it is least sensitive to the training set.So its average performance exceeds the other two.

Remaining Useful Life Model and Assessment of Mechanical Products: A Brief Review and a Note on the State Space Model Method

The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.

Coupled dynamic model of state estimation for hypersonic glide vehicle

Aiming at handling complicated maneuvers or other unpredicted emergencies for hypersonic glide vehicle tracking,three coupled dynamic models of state estimation based on the priori information between guidance variables and aerodynamics are presented. Firstly, the aerodynamic acceleration acting on the target is analyzed to reveal the essence of the target’s motion.Then three coupled structures for modeling aerodynamic parameters are developed by different ideas: the spiral model with a harmonic oscillator, the bank model with trigonometric functions of the bank angle and the guide model with the changing rule of guidance variables. Meanwhile, the comparison discussion is concluded to show the novelty and advantage of these models.Finally, a performance assessment in different simulation cases is presented and detailed analysis is revealed. The results show that the proposed models perform excellent properties. Moreover, the guide model produces the best tracking performance and the bank model shows the second; however, the spiral model does not outperform the maneuvering reentry vehicle(MaRV) model markedly.

A unified critical state model for geomaterials with an application to tunnelling

This paper is prepared in honour of Professor E.T.Brown for his outstanding contributions to rock mechanics and geotechnical engineering and also for his personal influence on the first author’s research career in geomechanics and geotechnical engineering.As a result,we have picked a topic that reflects two key research areas in which Professor E.T.Brown has made seminal contributions over a long and distinguished career.These two areas are concerned with the application of the critical state concept to modelling geomaterials and the analysis of underground excavation or tunnelling in geomaterials.Partially due to Professor Brown’s influence,the first author has also been conducting research in these two areas over many years.In particular,this paper aims to describe briefly the development of a unified critical state model for geomaterials together with an application to cavity contraction problems and tunnelling in soils.

Thermo-mechanical constitutive modeling of unsaturated clays based on the critical state concepts

A thermo-mechanical constitutive model for unsaturated clays is constructed based on the existingmodel for saturated clays originally proposed by the authors. The saturated clays model was formulatedin the framework of critical state soil mechanics and modified Cam-clay model. The existing model hasbeen generalized to simulate the experimentally observed behavior of unsaturated clays by introducingBishop＇s stress and suction as independent stress parameters and modifying the hardening rule and yieldcriterion to take into account the role of suction. Also, according to previous studies, an increase intemperature causes a reduction in specific volume. A reduction in suction （wetting） for a given confiningstress may induce an irreversible volumetric compression （collapse）. Thus an increase in suction （drying）raises a specific volume i.e. the movement of normal consolidation line （NCL） to higher values of voidratio. However, some experimental data confirm the assumption that this reduction is dependent on thestress level of soil element. A generalized approach considering the effect of stress level on themagnitude of clays thermal dependency in compression plane is proposed in this study. The number ofmodeling parameters is kept to a minimum, and they all have clear physical interpretations, to facilitatethe usefulness of model for practical applications. A step-by-step procedure used for parameter calibrationis also described. The model is finally evaluated using a comprehensive set of experimental datafor the thermo-mechanical behavior of unsaturated soils.2015 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. All rights reserved.

EQUATION OF STATE BASED HYDRATE MODEL FOR NATURAL GAS SYSTEMS CONTAINING BRINE AND POLAR INHIBITOR

A new thermodynamic model for gas hydrates was established by combining the modified Patel-Teja equation of state proposed for aqueous electrolyte systems and the simplified Holder -John multi -shell hydrate model. The new hydrate model is capable of predicting the hydrate formation/dissociation conditions of natural gas systems containing pure water/formation water (brine) and polar inhibitor without using activity coefficient model. Extensive test results indicate very encouraging results.

Qualitative analysis for state/event fault trees using formal model checking

A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.

Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

A PREDICTION OF THE VORTEX-RING STATE BOUNDARY BASED ON MODEL TESTS

To understand the vortex-ring state and to develop an approach for predicting its boundary, a series of model rotor tests of vertical descent and oblique descent have been conducted on a newly-built test apparatus - the Whirling Beam. The test results showed some unsteady aerodynamic behavior of the model rotor operating in the vortex-ring state. A very irregular variation of the rotortorque at low rate-of-descent was observed here for the first time. We considered it to be the start of the 'power settling' and determined the critical descent velocity according to this observation. A previous criterion for the vortex-ring state was modified to give a semi-empirical method for predicting the entire vortex-ring state boundary. The computed boundary shows a good correlation with the model test results and the flight experiences.

Co-Estimation of State of Charge and Capacity for Lithium-Ion Batteries with Multi-Stage Model Fusion Method

Lithium-ion batteries(LIBs)have emerged as the preferred energy storage systems for various types of electric transports,including electric vehicles,electric boats,electric trains,and electric airplanes.The energy management of LIBs in electric transports for all-climate and long-life operation requires the accurate estimation of state of charge(SOC)and capacity in real-time.This study proposes a multistage model fusion algorithm to co-estimate SOC and capacity.Firstly,based on the assumption of a normal distribution,the mean and variance of the residual error from the model at different ageing levels are used to calculate the weight for the establishment of a fusion model with stable parameters.Secondly,a differential error gain with forward-looking ability is introduced into a proportional–integral observer(PIO)to accelerate convergence speed.Thirdly,a fusion algorithm is developed by combining a multistage model and proportional–integral–differential observer(PIDO)to co-estimate SOC and capacity under a complex application environment.Fourthly,the convergence and anti-noise performance of the fusion algorithm are discussed.Finally,the hardware-in-the-loop platform is set up to verify the performance of the fusion algorithm.The validation results of different aged LIBs over a wide range of temperature show that the presented fusion algorithm can realize a high-accuracy estimation of SOC and capacity with the relative errors within 2%and 3.3%,respectively.

Existence for positive steady states of an eco-epidemiological model

An eco-epidemiological model with an epidemic in the predator and with a Holling type Ⅱ function is considered.A system with diffusion under the homogeneous Neumann boundary condition is studied.The existence for a positive solution of the corresponding steady state problem is mainly discussed.First,a prior estimates（positive upper and lower bounds） of the positive steady states of the reaction-diffusion system is given by the maximum principle and the Harnack inequation.Then,the non-existence of non-constant positive steady states by using the energy method is given.Finally,the existence of non-constant positive steady states is obtained by using the topological degree.