Full-scale model tests and nonlinear analysis of prestressed concrete simply supported box girders

Full-scale model tests were carried out on a 30 m span prestressed concrete box girder and a 20 m span prestressed concrete hollow slab. Failure models were prestressed reinforcement tensile failure and crashing of roof concrete, respectively. The ductility indexes of the box girder and hollow slab were 1.99 and 1.23, respectively, according to the energy viewpoint. Based on the horizontal section hypothesis, the nonlinear computation procedure was established using the limited banding law, and it could carry out the entire performance analysis including the unloading, mainly focusing on the ways to achieve the unloading curves computation through stress-strain, moment-curvature and load-displacement curves. Through the procedure, parameters that influence on the bearing capacity, deformation performance and ductility of the structures were analyzed. Those parameters were quantity of prestressed reinforcement and tension coefficients of prestressed reinforcement. From the analysis, some useful conclusions can be obtained.

Full-scale modeling of chemical experiments

Computational chemistry methods are playing an increasingly pivotal role in chemical experiments.From quantum chemistry simulations to finite element simulations,researchers can always find an appropriate simulation method to elucidate the specific mechanisms at a certain resolution scale.However,in organic or inorganic synthesis,the synthesis mechanisms span multiple spatial and temporal scales of chemical experiments.Furthermore,the intricate nature of these mechanisms renders it impossible for any single simulation method to provide a comprehensive depiction of the entire process.In this perspective,using zeolite and polymer synthesis simulations as examples,we stress the significance of fullscale modeling techniques for chemical experiments and urge the corresponding sophisticated simulation platform.

Resistance of full-scale beams against close-in explosions.Numerical modeling and field tests

This paper explores the performances of a finite element simulation including four concrete models applied to a full-scale reinforced concrete beam subjected to blast loading. Field test data has been used to compare model results for each case. The numerical modelling has been, carried out using the suitable code LS-DYNA. This code integrates blast load routine(CONWEP) for the explosive description and four different material models for the concrete including: Karagozian & Case Concrete, Winfrith, Continuous Surface Cap Model and Riedel-Hiermaier-Thoma models, with concrete meshing based on 10, 15, and 20 mm. Six full-scale beams were tested: four of them used for the initial calibration of the numerical model and two more tests at lower scaled distances. For calibration, field data obtained employing pressure and accelerometers transducers were compared with the results derived from the numerical simulation. Damage surfaces and the shape of rupture in the beams have been used as references for comparison. Influence of the meshing on accelerations has been put in evidence and for some models the shape and size of the damage in the beams produced maximum differences around 15%. In all cases, the variations between material and mesh models are shown and discussed.

Thickness regression for backfill grouting of shield tunnels based on GPR data and CatBoost&BO-TPE:A full-scale model test study

Ground penetrating radar(GPR)is a vital non-destructive testing(NDT)technology that can be employed for detecting the backfill grouting of shield tunnels.To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods,the CatBoost&BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms.A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz,with known backfill grouting thickness.The model test helps address the limitation of not knowing the grout body condition in actual field detection.The data were then used to create machine learning datasets.The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic(EM)propagation law in mediums.The research shows that:(1)the CatBoost&BO-TPE model exhibited outstanding performance in both experimental and numerical data,achieving R^(2)values of 0.9760,0.8971,0.8808,and 0.5437 for numerical data and test data at 400 and 900 MHz.It outperformed extreme gradient boosting(XGBoost)and random forest(RF)in terms of performance in the backfill grouting thickness regression;(2)compared with the full-waveform GPR data,the feature selection method proposed in this paper can promote the performance of the model.The selected features within the 5–30 ns of the A-scan can yield the best performance for the model;(3)compared to GPR data at 900 MHz,GPR data at 400 MHz exhibited better performance in the CatBoost&BO-TPE model.This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters;(4)the application results of the trained CatBoost&BO-TPE model in engineering are in line with the patterns observed through traditional processing methods,yet they demonstrate a more quantitative and objective nature compared to the traditional method.

Experimental investigations on small-and full-scale ship models with polyurea coatings subjected to underwater explosion

Nowadays, the mitigation of damage to a ship caused by the underwater explosion attracts more and more attention from the modern ship designers. In this study, two kinds of scale tests were conducted to investigate the effects of polyurea coatings on the blast resistance of hulls subjected to underwater explosion. Firstly, small-scale model tests with different polyurea coatings were carried out. Results indicate that polyurea has a better blast resistance performance when coated on the front face, which can effectively reduce the maximum deflection of the steel plate by more than 20% and reduce the deformation energy by 35.7%-45.4%. Next, a full-scale ship(approximately 50 m × 9 m) under loadings produced by the detonation of 33 kg of spherical TNT charges was tested, where a part of the ship was coated with polyurea on the front face(8 mm + 24 mm) and not on the contrast area. Damage characteristics on the bottom were statistically analyzed based on a 3D scanning technology, indicating that polyurea contributes to enhancing the blast protection of the ship. However, damage results of this test were different from those of the small-scale tests. Moreover, the deformation area of the bottom with polyurea was greatly increased by 40.1% to disperse explosion energy, a conclusion that cannot be drown from the small-scale tests.

Metagenomic Insight Reveals the Microbial Structure and Function of the Full-Scale Coking Wastewater Treatment System:Gene-Based Nitrogen Removal

Microbial communities play crucial roles in pollutant removal and system stability in biological systems for coking wastewater(CWW)treatment,but a comprehensive understanding of their structure and functions is still lacking.A five month survey of four sequential bioreactors,anoxic 1/oxic 1/anoxic 2/oxic 2(A1/O1/A2/O2),was carried out in a full-scale CWW treatment system in China to elucidate operational performance and microbial ecology.The results showed that A1/O1/A2/O2 had excellent and stable performance for nitrogen removal.Both total nitrogen(TN;(17.38±6.89)mgL1)and ammonium-nitrogen(NH4 t-N;(2.10±1.34)mg·L^(-1))in the final biological effluent satisfied the Chinese national standards for CWW.Integrated analysis of 16S ribosome RNA(rRNA)sequencing and metagenomic sequencing showed that the bacterial communities and metagenomic function profiles of A1 and O1 shared similar functional structures,while those of A2 significantly varied from those of other bioreactors(p<0.05).The results indicated that microbial activity was strongly connected with activated sludge function.Nitrosospira,Nitrosomonas,and SM1A02 were responsible for nitrification during the primary anoxic-oxic(AO)stage and Azoarcus and Thauera acted as important denitrifiers in A2.Nitrogen cycling-related enzymes and genes work in the A1/O1/A2/O2 system.Moreover,the hao genes catalyzing hydroxylamine dehydrogenase(EC 1.7.2.6)and the napA and napB genes catalyzing nitrate reductase(EC 1.9.6.1)played important roles in the nitrification and denitrification processes in the primary and secondary AO stages,respectively.The mixed liquor suspended solids(MLSS)/total solids(TS),TN removal rate(RR),total organic carbon(TOC)(RR),and NH_(4)^(+)t-N(RR)were the most important environmental factors for regulating the structure of core bacterial genera and nitrogen-cycling genes.Proteobacteria were the potential main participants in nitrogen metabolism in the A1/O1/A2/O2 system for CWW treatment.This study provides an original and comprehensive understanding of the microbial community and functions at the gene level,which is crucial for the efficient and stable operation of the full-scale biological process for CWW treatment.

Full-Scale Isogeometric Topology Optimization of Cellular Structures Based on Kirchhoff-Love Shells

Cellular thin-shell structures are widely applied in ultralightweight designs due to their high bearing capacity and strength-to-weight ratio.In this paper,a full-scale isogeometric topology optimization(ITO)method based on Kirchhoff-Love shells for designing cellular tshin-shell structures with excellent damage tolerance ability is proposed.This method utilizes high-order continuous nonuniform rational B-splines(NURBS)as basis functions for Kirchhoff-Love shell elements.The geometric and analysis models of thin shells are unified by isogeometric analysis(IGA)to avoid geometric approximation error and improve computational accuracy.The topological configurations of thin-shell structures are described by constructing the effective density field on the controlmesh.Local volume constraints are imposed in the proximity of each control point to obtain bone-like cellular structures.To facilitate numerical implementation,the p-norm function is used to aggregate local volume constraints into an equivalent global constraint.Several numerical examples are provided to demonstrate the effectiveness of the proposed method.After simulation and comparative analysis,the results indicate that the cellular thin-shell structures optimized by the proposed method exhibit great load-carrying behavior and high damage robustness.

A Non-geometrically Similar Model for Predicting the Wake Field of Full-scale Ships

The scale effect leads to large discrepancies between the wake fields of model-scale and actual ships, and causes differences in cavitation performance and exciting forces tests in predicting the performance of actual ships. Therefore, when test data from ship models are directly applied to predict the performance of actual ships, test results must be subjected to empirical corrections. This study proposes a method for the reverse design of the hull model. Compared to a geometrically similar hull model, the wake field generated by the modified model is closer to that of an actual ship. A non-geometrically similar model of a Korean Research Institute of Ship and Ocean Engineering （KRISO）’s container ship （KCS） was designed. Numerical simulations were performed using this model, and its results were compared with full-scale calculation results. The deformation method of getting the wake field of full-scale ships by the non-geometrically similar model is applied to the KCS successfully.

Mathematical modeling and full-scale shaking table tests for multi-curve buckling restrained braces

Buckling restrained braces （BRBs） have been widely applied in seismic mitigation since they were introduced in the 1970s. However, traditional BRBs have several disadvantages caused by using a steel tube to envelope the mortar to prevent the core plate from buckling, such as： complex interfaces between the materials used, uncertain precision, and time consumption during the manufacturing processes. In this study, a new device called the multi-curve buckling restrained brace （MC-BRB） is proposed to overcome these disadvantages. The new device consists of a core plate with multiple neck portions assembled to form multiple energy dissipation segments, and the enlarged segment, lateral support elements and constraining elements to prevent the BRB from buckling. The enlarged segment located in the middle of the core plate can be welded to the lateral support and constraining elements to increase buckling resistance and to prevent them from sliding during earthquakes. Component tests and a series of shaking table tests on a full-scale steel structure equipped with MC-BRBs were carried out to investigate the behavior and capability of this new BRB design for seismic mitigation. The experimental results illustrate that the MC-BRB possesses a stable mechanical behavior under cyclic loadings and provides good protection to structures during earthquakes. Also, a mathematical model has been developed to simulate the mechanical characteristics of BRBs.

Behavior of transporting pipeline sections without and with hydrogen exposure based on full-scale tests

Pipeline transport of hydrogen is one of today’s economic and environmental challenges.In order to find safe and reliable application of both existing gas and build new pipelines,it is essential to carry out tests on full-scale pipeline section,including the potentially more dangerous places than the main pipe,the girth welds.For the investigations,pipeline sections of P355NH steel with girth welds were prepared and exposed to pure hydrogen at twice the maximum allowable operating pressure for 41 days.Subsequently,full-scale burst tests were carried out and specimens were cut and prepared from the typical locations of the failed pipeline sections for mechanical,and macro-and microstructural investigations.The results obtained were evaluated and compared with data from previous full-scale tests on pipeline sections without hydrogen exposure.The results showed differences in the behavior of pipeline sections loaded in different ways,with different characteristics of the materials and the welded joints,both in the cases without hydrogen exposure and in the cases exposed to hydrogen.

Full-scale Water Modeling on Flow Field of Continuous Casting Mold

In the continuous casting process of aluminum killed steel grades,nozzle clogging is a common problem.Argon is usually injected into the casting channel through stoppers or nozzles to minimize clogs;however,complex two-phase flow regimes appear,and the flow in the mold might deteriorate.This could result in a higher defect rate in the cast product and should be avoided as much as possible.Therefore,it is important to understand the interaction between process conditions and the refractory products used and their impact on the flow pattern in the mold.In this study,a full-scale water model was established to simulate the slab casting process.Three nozzle shapes and three immersion depths were applied to investigate the flow behavior and liquid level fluctuations by the full-scale water model.The relationship between the flow behavior and continuous casting parameters was evaluated.The results provide guidance for the design and production of the refractory nozzle and the operation of the continuous casting plant.

Stiffness Degradation Modeling for Composite Wind Turbine Blades Based on Full-Scale Fatigue Testing

In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.

Theoretical and Experimental Sets of Choice Anode/Cathode Architectonics for High-Performance Full-Scale LIB Built-up Models

To control the power hierarchy design of lithium-ion battery(LIB)builtup sets for electric vehicles(EVs),we offer intensive theoretical and experimental sets of choice anode/cathode architectonics that can be modulated in full-scale LIB built-up models.As primary structural tectonics,heterogeneous composite superstructures of full-cell-LIB(anode//cathode)electrodes were designed in closely packed flower agave rosettes TiO2@C(FRTO@C anode)and vertical-star-tower LiFePO4@C(VST@C cathode)building blocks to regulate the electron/ion movement in the three-dimensional axes and orientation pathways.The superpower hierarchy surfaces and multi-directional orientation components may create isosurface potential electrodes with mobile electron movements,in-to-out interplay electron dominances,and electron/charge cloud distributions.This study is the first to evaluate the hotkeys of choice anode/cathode architectonics to assemble different LIB-electrode platforms with high-mobility electron/ion flows and high-performance capacity functionalities.Density functional theory calculation revealed that the FRTO@C anode and VST-(i)@C cathode architectonics are a superior choice for the configuration of full-scale LIB built-up models.The integrated FRTO@C//VST-(i)@C full-scale LIB retains a huge discharge capacity(~94.2%),an average Coulombic efficiency of 99.85%after 2000 cycles at 1 C,and a high energy density of 127 Wh kg?1,thereby satisfying scale-up commercial EV requirements.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Fuzzy Model Free Adaptive Control for Rotor Blade Full-Scale Static Testing

To eliminate the node traction coupling during wind turbine blade full-scale static testing,a model free adaptive control algorithm is presented based on fuzzy control performance function compensation. Based on the universal model theory,the fuzzy model free adaptive control( FMFAC) algorithm is designed by configuring the spot static testing experiences as compensation function F( ·). Then the algorithm implementation process is provided and its quick convergence is proved. Using software to establish static load coupling model of multi-nodes,simulate and verify the validity of FMFAC algorithm,which is applied to wind turbines blade full-scale static testing. The results show that the adaptive decoupling ability of FMFAC is better. The traction of four load points can stay steady and change coordinately. Process error is not over ± 6 k N. The error rate is lower than 1% in special phase.This algorithm effectively eliminates the traction coupling of the static testing process,and makes wind turbine blade testing steadily.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

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。

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。