A data and physical model dual-driven based trajectory estimator for long-term navigation

Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.

Displacement field reconstruction in landslide physical modeling by using a terrain laser scanner e Part 2:Application and large strain/displacement and water effect analysis

Deformation analysis is fundamental in geotechnical modeling.Nevertheless,there is still a lack of an effective method to obtain the deformation field under various experimental conditions.In this study,we introduce a processebased physical modeling of a pileereinforced reservoir landslide and present an improved deformation analysis involving large strains and water effects.We collect multieperiod point clouds using a terrain laser scanner and reconstruct its deformation field through a point cloud processing workflow.The results show that this method can accurately describe the landslide surface deformation at any time and area by both scalar and vector fields.The deformation fields in different profiles of the physical model and different stages of the evolutionary process provide adequate and detailed landslide information.We analyze the large strain upstream of the pile caused by the pile installation and the consequent violent deformation during the evolutionary process.Furthermore,our method effectively overcomes the challenges of identifying targets commonly encountered in geotechnical modeling where water effects are considered and targets are polluted,which facilitates the deformation analysis at the wading area in a reservoir landslide.Eventually,combining subsurface deformation as well as numerical modeling,we comprehensively analyze the kinematics and failure mechanisms of this complicated object involving landslides and pile foundations as well as water effects.This method is of great significance for any geotechnical modeling concerning large-strain analysis and water effects.

Displacement field reconstruction in landslide physical modeling by using a terrain laser scanner e Part 1:Methodology,error analysis and validation

Laser scanning technology has been widely used in landslide aspects.However,the existing deformation analysis based on terrain laser scanners can only provide limited information,which is insufficient for understanding landslide kinematics and failure mechanisms.To overcome this limitation,this paper proposes an automated method for processing point clouds collected in landslide physical modeling.This method allows the acquisition of quantitative three-dimensional(3D)deformation field information.The results show the organized and spatially related point cloud segmentation in terms of spherical targets.The segmented point clouds can be fitted to determine the locations of all preset targets and their corresponding location changes.The proposed method has been validated based on theoretical analysis and numerical and physical tests,which indicates that it can batch-process massive data sets with high computational efficiency and good noise resistance.Compared to existing methods,this method shows a significant potential for understanding landslide kinematics and failure mechanisms and advancing the application of 3D laser scanning in geotechnical modeling.

Rainfall-triggered waste dump instability analysis based on surface 3D deformation in physical model test

Landslide is the second largest natural disaster after earthquake. It is of significance to study the evolution laws and failure mechanism of landslides based on its surface 3D deformation information. Based on the rainfall-triggered waste dump instability model test, we studied the failure mechanisms of the waste dump by integrating surface deformation and internal slope stress and proposed novel parameters for identifying landslide stability. We developed a noncontact measurement device, which can obtain millimeter-level 3D deformation data for surface scene in physical model test;Then we developed the similar materials and established a test model for a waste dump. Based on the failure characteristics of slope surface, internal stress of slope body and displacement contours during the whole process, we divided the slope instability process in model test into four stages: rainfall infiltration and surface erosion, shallow sliding, deep sliding, and overall instability. Based on the obtained surface deformation data, we calculated the volume change during slope instability process and compared it with the point displacement on slope surface. The results showed that the volume change can not only reflect the slow-ultra acceleration process of slope failure, but also fully reflect the above four stages and reduce the fluctuations caused by random factors. Finally, this paper proposed two stability identification parameters: the volume change rate above the slip surface and the relative velocity of volume change rate. According to the calculation of these two parameters in model test, they can be used for study the deformation and failure mechanism of slope stability.

Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

Cascade failure modeling and resilience analysis of mine cyber physical systems under deliberate attacks

Guided by the intelligent construction of coal mines and integrating the concept of the Cyber-Physical System(CPS),a novel approach to a coal mine information-physical fusion system is proposed.This concept emerges from the advancement of intelligent mines and the growing need for enhanced safety in coal mine operations.From a system safety perspective,this approach aims to effectively evaluate security issues by better integrating the informational and physical layers of intelligent mines.Currently,research in areas such as power grids and water networks has widely adopted concepts of cascade failures and robustness.It is suggested that the CPS framework be adapted to the mining sector.Considering the critical role of coal mines in China's energy security and their vulnerability to cyber attacks,a mine-specific CPS system is designed.This system incorporates a model of mine information-physical fusion,including networks for mine operations,management,and control,tailored to the unique conditions of mine shafts and underground settings.Utilizing Markov process theory,the paper delves into the theoretical study of the cascade failure process under deliberate attack strategies.This analysis is essential to effectively assess the safety issues within the information-physical system,providing vital support for fault prediction and safety analysis.The model of cascading failures in the mine information-physical system is developed,and based on an analysis of resilience and robustness,the study identifies key factors influencing the security of mine information-physical systems.Critical factors affecting the reliability of these systems include the number of system nodes,node coupling,edge count,and the interconnection methods of the dual-layer dependency network.The paper concludes by discussing the challenges in analyzing the security of information-physical systems and suggesting directions for future research.

Physical exercise and synaptic protection in human and pre-clinical models of multiple sclerosis

In multiple sclerosis,only immunomodulato ry and immunosuppressive drugs are recognized as disease-modifying therapies.Howeve r,in recent years,several data from pre-clinical and clinical studies suggested a possible role of physical exe rcise as disease-modifying therapy in multiple sclerosis.Current evidence is sparse and often conflicting,and the mechanisms underlying the neuroprotective and antinflammatory role of exercise in multiple sclerosis have not been fully elucidated.Data,mainly derived from pre-clinical studies,suggest that exe rcise could enhance longterm potentiation and thus neuroplasticity,could reduce neuroinflammation and synaptopathy,and dampen astrogliosis and microgliosis.In humans,most trials focused on direct clinical and MRI outcomes,as investigating synaptic,neuroinflammato ry,and pathological changes is not straightfo rward compared to animal models.The present review analyzed current evidence and limitations in research concerning the potential disease-modifying therapy effects of exercise in multiple sclerosis in animal models and human studies.

Research on physical explosion crater model of high-pressure natural gas pipeline

In this study,Hypermesh and LS-DYNA numerical simulation software are used to build a multi domain coupling model of natural gas pipeline,including soil,pipeline,TNT explosive and air domain,and the non-reflection boundary conditions are set for the model.The TNT equivalent method is used to convert the physical explosion amount of natural gas pipeline into 1387.38 kg TNT explosive amount.The simulation results show that the physical explosion of pipeline forms an approximate elliptical crater with a width of 12.68 m and a depth of 4.12 m;the TNT equivalent of the model is corrected by comparing the crater simulation value and the size value of the crater calculated by the PRCI empirical formula under the same laying condition,and the correction coefficient is selected as O.9,and the cor-rected TNT equivalent is 1248.64 kg:the modified model crater size is 3.72 m deep and 12.66 m wide,compared with the crater size obtained from the field test,the error of crater depth and width calculated by the modified model simulation is 5.7%and 15.5%respectively.

An internal ballistic model of electromagnetic railgun based on PFN coupled with multi-physical field and experimental validation

To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.

3D seismic forward modeling from the multiphysical inversion at the Ketzin CO_(2) storage site

From June 2008 to August 2013,approximately 67 kt of CO_(2) was injected into a deep saline formation at the Ketzin pilot CO_(2) storage site.During injection,3D seismic surveys have been performed to monitor the migration of sequestered CO_(2).Seismic monitoring results are limited by the acquisition and signal-to-noise ratio of the acquired data.The multiphysical reservoir simulation provides information regarding the CO_(2) fluid behavior,and the approximated model should be calibrated with the monitoring results.In this work,property models are delivered from the multiphysical model during 3D repeated seismic surveys.The simulated seismic data based on the models are compared with the real data,and the results validate the effectiveness of the multiphysical inversion method.Time-lapse analysis shows the trend of CO_(2) migration during and after injection.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

Physical model investigation on effects of drainage condition and cement addition on consolidation behavior of tailings slurry within backfilled stopes

Estimation of stressses within the tailings slurry during self-weight consolidation is a critical issue for cost-effective barricade design and efficient backfill planning in underground mine stopes.This process requires a good understanding of self-weight consolidation behaviors of the tailings slurry within practical stopes,where many factors can have significant effects on the consolidation,including drainage condition and cement addition.In this paper,the prepared tailings slurry with different cement contents(0,4.76wt%,and 6.25wt%)was poured into1.2 m-high columns,which allowed three drainage scenarios(undrained,partial lateral drainage near the bottom part,and full lateral drainage boundaries)to investigate the effects of drainage condition and cement addition on the consolidation behavior of the tailings slurry.The consolidation behavior was analyzed in terms of pore water pressure(PWP),settlement,volume of drainage water,and residual water content.The results indicate that increasing the length of the drainage boundary or cement content aids in PWP dissipation.In addition,constructing an efficient drainage boundary was more favorable to PWP dissipation than increasing cement addition.The final stable PWP on the column floor was not sensitive to cement addition.The final settlement of uncemented tailings slurry was independent of drainage conditions,and that of cemented tailings slurry decreased with the increase in cement addition.Notably,more pore water can drain out from the cemented tailings slurry than the uncemented tailings slurry during consolidation.

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

Unleashing the Power of Information Theory: Enhancing Accuracy in Modeling Physical Phenomena

When building a model of a physical phenomenon or process, scientists face an inevitable compromise between the simplicity of the model (qualitative-quantitative set of variables) and its accuracy. For hundreds of years, the visual simplicity of a law testified to the genius and depth of the physical thinking of the scientist who proposed it. Currently, the desire for a deeper physical understanding of the surrounding world and newly discovered physical phenomena motivates researchers to increase the number of variables considered in a model. This direction leads to an increased probability of choosing an inaccurate or even erroneous model. This study describes a method for estimating the limit of measurement accuracy, taking into account the stage of model building in terms of storage, transmission, processing and use of information by the observer. This limit, due to the finite amount of information stored in the model, allows you to select the optimal number of variables for the best reproduction of the observed object and calculate the exact values of the threshold discrepancy between the model and the phenomenon under study in measurement theory. We consider two examples: measurement of the speed of sound and measurement of physical constants.

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Petrophysical parameters inversion for heavy oil reservoir based on a laboratory-calibrated frequency-variant rock-physics model

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.

2024 Adult Compendium of Physical Activities:A third update of the energy costs of human activities

Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.