Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Swelling pressure evolution characterization of strong expansive soil considering the influence of reserved expansion deformation

Numerous engineering cases have demonstrated that the expansive soil channel slope remains susceptible to damage with the implementation of a rigid or closed protective structure. It is common for the protective structure to experience bulging failure due to excessive swelling pressure. To investigate the swelling pressure properties of expansive soil, the constant volume test was employed to study the influence of water content and reserved expansion deformation on the characteristics of swelling pressure in strong expansive soils, and also to explore the evolution mechanism of the swelling pressure. The findings demonstrate that the swelling pressure-time curve can be classified into swelling pressure-time softening and swelling pressure-time stability type. The swelling pressuretime curve of the specimen with low water content is the swelling pressure-time softening type, and the softening level will be weakened with increasing reserved expansion deformation. Besides, the maximum swelling pressure Psmax decreases with increasing water content and reserved expansion deformation, especially for expansion ratio η from 24% to 37%. The reserved deformation has little effect on reducing Psmax when it is beyond 7% of the expansion rate. The specimen with low water content has a more homogeneous structure due to the significant expansion-filling effect, and the fracture and reorganization of the aggregates in the specimens with low water content cause the swelling pressure-time softening behavior. In addition, the proposed swelling pressure-time curve prediction model has a good prediction on the test results. If necessary, a deformation space of about 7% expansion rate is recommended to be reserved in the engineering to reduce the swelling pressure except for keeping a stable water content.

Expansion of human umbilical cord derived mesenchymal stem cells in regenerative medicine

BACKGROUND Stem cells are undifferentiated cells that possess the potential for self-renewal with the capacity to differentiate into multiple lineages.In humans,their limited numbers pose a challenge in fulfilling the necessary demands for the regeneration and repair of damaged tissues or organs.Studies suggested that mesenchymal stem cells(MSCs),necessary for repair and regeneration via transplantation,require doses ranging from 10 to 400 million cells.Furthermore,the limited expansion of MSCs restricts their therapeutic application.AIM To optimize a novel protocol to achieve qualitative and quantitative expansion of MSCs to reach the targeted number of cells for cellular transplantation and minimize the limitations in stem cell therapy protocols.METHODS Human umbilical cord(hUC)tissue derived MSCs were obtained and re-cultured.These cultured cells were subjected to the following evaluation pro-cedures:Immunophenotyping,immunocytochemical staining,trilineage differentiation,population doubling time and number,gene expression markers for proliferation,cell cycle progression,senescence-associatedβ-galactosidase assay,human telomerase reverse transcriptase(hTERT)expression,mycoplasma,cytomegalovirus and endotoxin detection.RESULTS Analysis of pluripotent gene markers Oct4,Sox2,and Nanog in recultured hUC-MSC revealed no significant differences.The immunophenotypic markers CD90,CD73,CD105,CD44,vimentin,CD29,Stro-1,and Lin28 were positively expressed by these recultured expanded MSCs,and were found negative for CD34,CD11b,CD19,CD45,and HLA-DR.The recultured hUC-MSC population continued to expand through passage 15.Proliferative gene expression of Pax6,BMP2,and TGFb1 showed no significant variation between recultured hUC-MSC groups.Nevertheless,a significant increase(P<0.001)in the mitotic phase of the cell cycle was observed in recultured hUC-MSCs.Cellular senescence markers(hTERT expression andβ-galactosidase activity)did not show any negative effect on recultured hUC-MSCs.Additionally,quality control assessments consistently confirmed the absence of mycoplasma,cytomegalovirus,and endotoxin contamination.CONCLUSION This study proposes the development of a novel protocol for efficiently expanding stem cell population.This would address the growing demand for larger stem cell doses needed for cellular transplantation and will significantly improve the feasibility of stem cell based therapies.

Significant lake expansion has accelerated permafrost degradation on the Qinghai-Tibet Plateau

In recent years, lakes on the Qinghai-Tibet Plateau have become more responsive to climate change. In September 2011, Zonag Lake in Hoh Xil experienced sudden drainage, the water eventually flowed into Yanhu Lake, which caused Yanhu Lake to continue to expand. The potential collapse of Yanhu Lake could directly threaten the operational safety of the adjacent Qinghai-Tibet Highway, Qinghai-Tibet Railway. To explore the implications of expanding lakes on the surrounding permafrost, we selected Hoh Xil Yanhu Lake on the Qinghai-Tibet Plateau to study the effect of lake expansion on permafrost degradation. The permafrost degradation in the Yanhu Lake basin from October 2017 to December 2022 was inverted using Sentinel-1 satellite image data and small baseline subset interferometry synthetic aperture radar(SBAS-In SAR) technology. Additionally, permafrost degradation from February 2007 and February 2010 was analyzed using advanced land observing satellite phased array-type L-band synthetic aperture radar(ALOS PALSAR) satellite images and differential interferometric synthetic aperture radar(D-In SAR) technique. The results showed that the permafrost around Yanhu Lake experienced accelerated degradation. Prior to the expansion of Yanhu Lake, the average annual deformation rate along the line of sight(LOS) direction was 6.7 mm/yr. After the expansion, the rate increased to 20.9 mm/yr. The integration of spatial-temporal distribution maps of surface subsidence, Wudaoliang borehole geothermal data, meteorological data, Yanhu Lake surface area changes, and water level changes supports the assertion that the intensified permafrost degradation could be attributed to lake expansion rather than the rising air temperature. Furthermore, permafrost degradation around Yanhu Lake could impact vital infrastructure such as the adjacent Qinghai-Tibet Highway and Qinghai-Tibet Railway.

Exact Tail Asymptotics for a Queueing System with a Retrial Orbit and Batch Service

This paper discusses a queueing system with a retrial orbit and batch service, in which the quantity of customers’ rooms in the queue is finite and the space of retrial orbit is infinite. When the server starts serving, it serves all customers in the queue in a single batch, which is the so-called batch service. If a new customer or a retrial customer finds all the customers’ rooms are occupied, he will decide whether or not to join the retrial orbit. By using the censoring technique and the matrix analysis method, we first obtain the decay function of the stationary distribution for the quantity of customers in the retrial orbit and the quantity of customers in the queue. Then based on the form of decay rate function and the Karamata Tauberian theorem, we finally get the exact tail asymptotics of the stationary distribution.

Reinforcement learning based adaptive control for uncertain mechanical systems with asymptotic tracking

This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.

Modeling Method of C/C-ZrC Composites and Prediction of Equivalent Thermal Conductivity Tensor Based on Asymptotic Homogenization

This article proposes a modeling method for C/C-ZrC composite materials.According to the superposition of Gaussian random field,the original gray model is obtained,and the threshold segmentation method is used to generate the C-ZrC inclusion model.Finally,the fiber structure is added to construct the microstructure of the three-phase plain weave composite.The reconstructed inclusions can meet the randomness of the shape and have a uniform distribution.Using an algorithm based on asymptotic homogenization and finite element method,the equivalent thermal conductivity prediction of the microstructure finite element model was carried out,and the influence of component volume fraction on material thermal properties was explored.The sensitivity of model parameters was studied,including the size,mesh sensitivity,Gaussian complexity,and correlation length of the RVE model,and the optimal calculation model was selected.The results indicate that the volume fraction of the inclusion phase has a significant impact on the equivalent thermal conductivity of the material.As the volume fraction of carbon fiber and ZrC increases,the equivalent thermal conductivity tensor gradually decreases.This model can be used to explore the impact of materialmicrostructure on the results,and numerical simulations have studied the relationship between structure and performance,providing the possibility of designing microstructure based on performance.

Research on the Generation Mechanism and Suppression Method of Aerodynamic Noise in Expansion Cavity Based on Hybrid Method

The expansion chamber serves as the primary silencing structure within the exhaust pipeline.However,it can also act as a sound-emitting structure when subjected to airflow.This article presents a hybrid method for numerically simulating and analyzing the unsteady flow and aerodynamic noise in an expansion chamber under the influence of airflow.A fluid simulation model is established,utilizing the Large Eddy Simulation(LES)method to calculate the unsteady flow within the expansion chamber.The simulation results effectively capture the development and changes of the unsteady flow and vorticity inside the cavity,exhibiting a high level of consistency with experimental observations.To calculate the aerodynamic noise sources within the cavity,the flow field results are integrated using the method of integral interpolation and inserted into the acoustic grid.The acoustic analogy method is then employed to determine the aerodynamic noise sources.An acoustic simulation model is established,and the flow noise source is imported into the sound field grid to calculate the sound pressure at the far-field response point.The calculated sound pressure levels and resonance frequencies show good agreement with the experimental results.To address the issue of airflow regeneration noise within the cavity,perforated tubes are selected as a means of noise suppression.An experimental platformfor airflow regeneration noise is constructed,and experimental samples are processed to analyze and verify the noise suppression effect of perforated tube expansion cavities under different airflow velocities.The research findings indicate that the perforated tube expansion cavity can effectively suppress low-frequency aerodynamic noise within the cavity by impeding the formation of strong shear layers.Moreover,the semi-perforated tube expansion cavity demonstrates the most effective suppression of aerodynamic noise.

Asymptotic normality of error density estimator in stationary and explosive autoregressive models

In this paper,we consider the limit distribution of the error density function estima-tor in the rst-order autoregressive models with negatively associated and positively associated random errors.Under mild regularity assumptions,some asymptotic normality results of the residual density estimator are obtained when the autoregressive models are stationary process and explosive process.In order to illustrate these results,some simulations such as con dence intervals and mean integrated square errors are provided in this paper.It shows that the residual density estimator can replace the density\estimator"which contains errors.

The Negative Thermal Expansion Property of NdMnO_(3) Based on Pores Effect and Phase Transition

A novel negative thermal expansion(NTE) material NdMnO_(3) was synthesized by solid-state method at 1 523 K. The crystal structure, phase transition, pores effect and negative expansion properties of NdMnO_(3) were investigated by variable temperature X-ray diffraction(XRD), scanning electron microscope(SEM) and variable temperature Raman spectra. The compound exhibits NTE properties in the orderly O' phase crystal structure. When the temperature is from 293 to 759 K, the ceramic NdMnO_(3) shows negative thermal expansion of-4.7×10^(-6)/K. As temperature increases, the ceramic NdMnO_(3) presents NTE property range from 759 to 1 007 K. The average linear expansion coefficient is-18.88×10^(-6)/K. The physical mechanism of NTE is discussed and clarified through experiments.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

An Interpolation Method for Karhunen-Loève Expansion of Random Field Discretization

In the context of global mean square error concerning the number of random variables in the representation,the Karhunen–Loève(KL)expansion is the optimal series expansion method for random field discretization.The computational efficiency and accuracy of the KL expansion are contingent upon the accurate resolution of the Fredholm integral eigenvalue problem(IEVP).The paper proposes an interpolation method based on different interpolation basis functions such as moving least squares(MLS),least squares(LS),and finite element method(FEM)to solve the IEVP.Compared with the Galerkin method based on finite element or Legendre polynomials,the main advantage of the interpolation method is that,in the calculation of eigenvalues and eigenfunctions in one-dimensional random fields,the integral matrix containing covariance function only requires a single integral,which is less than a two-folded integral by the Galerkin method.The effectiveness and computational efficiency of the proposed interpolation method are verified through various one-dimensional examples.Furthermore,based on theKL expansion and polynomial chaos expansion,the stochastic analysis of two-dimensional regular and irregular domains is conducted,and the basis function of the extended finite element method(XFEM)is introduced as the interpolation basis function in two-dimensional irregular domains to solve the IEVP.

An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.

THE LOGARITHMIC SOBOLEV INEQUALITY FOR A SUBMANIFOLD IN MANIFOLDS WITH ASYMPTOTICALLY NONNEGATIVE SECTIONAL CURVATURE

In this note,we prove a logarithmic Sobolev inequality which holds for compact submanifolds without a boundary in manifolds with asymptotically nonnegative sectional curvature.Like the Michale-Simon Sobolev inequality,this inequality contains a term involving the mean curvature.

Higher-order expansions of powered extremes of logarithmic general error distribution

In this paper,Let M_(n)denote the maximum of logarithmic general error distribution with parameter v≥1.Higher-order expansions for distributions of powered extremes M_(n)^(p)are derived under an optimal choice of normalizing constants.It is shown that M_(n)^(p),when v=1,converges to the Frechet extreme value distribution at the rate of 1/n,and if v>1 then M_(n)^(p)converges to the Gumbel extreme value distribution at the rate of(loglogn)^(2)=(log n)^(1-1/v).

Can Industrial Structure Upgrading Restrain Industrial Land Expansion?Evidence from China

China has made great achievements in industrial development and is transforming into a powerful manufacturing country.Meanwhile,the industrial land scale is also expanding.However,whether industrial structure upgrading achieves the purpose of restraining industrial land expansion remains unanswered.By calculating the industrial land structure index(ILSI)and industrial land expansion scale(ILES),this study analyzed their temporal and spatial distribution characteristics at both regional and city levels from 2007to 2020 in China.Results show that industrial land expansion presents a different trend in the four regions,the ILES in the eastern region is the largest,and the speed of industrial land expansion has declined since 2013,but it has gradually increased since 2016.The ILSI of the eastern and central regions is higher than that of the western and northeastern regions.Furthermore,a spatial Durbin model(SDM)has been established to estimate the spatial effect of industrial structure upgrading on industrial land expansion from 2007 to2020.Notably,industrial structure upgrading has not slowed industrial land expansion.The eastern and western regions require a greater amount of industrial land while upgrading the industrial structure.The improvement of the infrastructure level and international trade level has promoted industrial land expansion.

Adaptive Space Expansion for Fast Motion Planning

The sampling process is very inefficient for sam-pling-based motion planning algorithms that excess random sam-ples are generated in the planning space.In this paper,we pro-pose an adaptive space expansion(ASE)approach which belongs to the informed sampling category to improve the sampling effi-ciency for quickly finding a feasible path.The ASE method enlarges the search space gradually and restrains the sampling process in a sequence of small hyper-ellipsoid ring subsets to avoid exploring the unnecessary space.Specifically,for a con-structed small hyper-ellipsoid ring subset,if the algorithm cannot find a feasible path in it,then the subset is expanded.Thus,the ASE method successively does space exploring and space expan-sion until the final path has been found.Besides,we present a particular construction method of the hyper-ellipsoid ring that uniform random samples can be directly generated in it.At last,we present a feasible motion planner BiASE and an asymptoti-cally optimal motion planner BiASE*using the bidirectional exploring method and the ASE strategy.Simulations demon-strate that the computation speed is much faster than that of the state-of-the-art algorithms.The source codes are available at https://github.com/shshlei/ompl.

Modification of streamer-to-leader transition model based on radial thermal expansion in the sphere-plane gap discharge at high altitude

Historically,streamer-to-leader transition studies mainly focused on the rod-plane gap and low altitude analysis,with limited attention paid to the sphere-plane gap at high altitude analysis.In this work,sphere-plane gap discharge tests were carried out under the gap distance of 5 m at the Qinghai Ultra High Voltage(UHV)test base at an altitude of 2200 m.The experiments measured the physical parameters such as the discharge current,electric field intensity and instantaneous optical power.The duration of the dark period and the critical charge of streamer-toleader transition were obtained at high altitude.Based on radial thermal expansion of the streamer stem,we established a modified streamer-to-leader transition model of the sphere-plane gap discharge at high altitude,and calculated the stem temperature,stem radii and the duration of streamer-to-leader transition.Compared with the measured duration of sphere-plane electrode discharge at an altitude of 2200 m,the error rate of the modified model was 0.94%,while the classical model was 6.97%,demonstrating the effectiveness of the modified model.From the comparisons and analysis,several suggestions are proposed to improve the numerical model for further quantitative investigations of the leader inception.

THE ASYMPTOTIC BEHAVIOR AND OSCILLATION FOR A CLASS OF THIRD-ORDER NONLINEAR DELAY DYNAMIC EQUATIONS

In this paper,we consider a class of third-order nonlinear delay dynamic equations.First,we establish a Kiguradze-type lemma and some useful estimates.Second,we give a sufficient and necessary condition for the existence of eventually positive solutions having upper bounds and tending to zero.Third,we obtain new oscillation criteria by employing the Potzsche chain rule.Then,using the generalized Riccati transformation technique and averaging method,we establish the Philos-type oscillation criteria.Surprisingly,the integral value of the Philos-type oscillation criteria,which guarantees that all unbounded solutions oscillate,is greater than θ_(4)(t_(1),T).The results of Theorem 3.5 and Remark 3.6 are novel.Finally,we offer four examples to illustrate our results.

Enhanced Differentiable Architecture Search Based on Asymptotic Regularization

In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search space with different complexity according to various operations.Meanwhile rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture search.With this in mind,we propose a faster and more efficient differentiable architecture search method,AllegroNAS.Firstly,we introduce a more efficient search space enriched by the introduction of two redefined convolution modules.Secondly,we utilize a more efficient architectural parameter regularization method,mitigating the overfitting problem during the search process and reducing the error brought about by gradient approximation.Meanwhile,we introduce a natural exponential cosine annealing method to make the learning rate of the neural network training process more suitable for the search procedure.Moreover,group convolution and data augmentation are employed to reduce the computational cost.Finally,through extensive experiments on several public datasets,we demonstrate that our method can more swiftly search for better-performing neural network architectures in a more efficient search space,thus validating the effectiveness of our approach.