Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

Effect of stress-dependent microannulus aperture on well leakage

Debonding at the cement-casing interface is recognized as a principal failure mechanism leading to CO_(2) leakage in wells.This detachment gives rise to a microannulus,which notably possesses greater permeability than undamaged cement,undermining its sealing efficacy.Conventionally,the permeability of the microannulus is regarded as a uniform value throughout the well.However,fundamentally,a microannulus is one type of fracture,and its gap or aperture size is affected by the effective stress.In this work,we developed a unique experimental apparatus.This equipment facilitates the curing of cement inside a steel casing,the formation of a microannulus between the casing and the cement,and the investigation of the fluid flow dynamics along the microannulus under laboratory-replicated in situ conditions.The microannulus was formed by injecting fluid from one end of the setup,and receiving similar amount of fluid on the other end signified the development of the leakage channel.Additionally,strain gauges affixed to the casing’s external surface yielded key information on the microannulus’s opening and closure.We observed a noticeable decline in microannulus hydraulic aperture(or permeability)in relation to effective stress and an exponential equation fits their relationship.Our findings also indicate a distinct behavior when comparing liquid CO_(2) with water.Specifically,it is easier for liquid CO_(2) to create the microannulus.However,the hydraulic aperture range for this microannulus(0.7-6 mm)is considerably smaller than that created by water flow(2-17 mm).Finally,we integrated the stressdependent microannulus aperture size into the combined analysis of well mechanical integrity and well leakage.The outcomes consistently demonstrated that when factoring in the stress-dependent aperture sizes,the leakage rates are 3e5 times compared to a fixed aperture model.The traditional assumption of a constant aperture significantly underestimates fluid leakage risks.

Field test of high-power microwave-assisted mechanical excavation for deep hard iron ore

Microwave-assisted mechanical excavation has great application prospects in mines and tunnels,but there are few field experiments on microwave-assisted rock breaking.This paper takes the Sishanling iron mine as the research object and adopts the self-developed high-power microwave-induced fracturing test system for hard rock to conduct field experiments of microwave-induced fracturing of iron ore.The heating and reflection evolution characteristics of ore under different microwave parameters(antenna type,power,and working distance)were studied,and the optimal microwave parameters were obtained.Subsequently,the ore was irradiated with the optimal microwave parameters,and the cracking effect of the ore under the action of the high-power open microwave was analyzed.The results show that the reflection coefficient(standing wave ratio)can be rapidly(<5 s)and automatically adjusted below the preset threshold value(1.6)as microwave irradiation is performed.When using a right-angle horn antenna with a working distance of 5 cm,the effect of automatic reflection adjustment reaches the best among other antenna types and working distances.When the working distance is the same,the average temperature of the irradiation surface and the area of the high-temperature area under the action of the two antennas(right-angled and equal-angled horn antenna)are basically the same and decrease with the increase of working distance.The optimal microwave parameters are:a right-angle horn antenna with a working distance of 5 cm.Subsequently,in further experiments,the optimal parameters were used to irradiate for 20 s and 40 s at a microwave power of 60 kW,respectively.The surface damage extended 38 cm×30 cm and 53 cm×30 cm,respectively,and the damage extended to a depth of about 50 cm.The drilling speed was increased by 56.2%and 66.5%,respectively,compared to the case when microwaves were not used.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Role of CD36 in central nervous system diseases

CD36 is a highly glycosylated integral membrane protein that belongs to the scavenger receptor class B family and regulates the pathological progress of metabolic diseases.CD36 was recently found to be widely expressed in various cell types in the nervous system,including endothelial cells,pericytes,astrocytes,and microglia.CD36 mediates a number of regulatory processes,such as endothelial dysfunction,oxidative stress,mitochondrial dysfunction,and inflammatory responses,which are involved in many central nervous system diseases,such as stroke,Alzheimer’s disease,Parkinson’s disease,and spinal cord injury.CD36 antagonists can suppress CD36 expression or prevent CD36 binding to its ligand,thereby achieving inhibition of CD36-mediated pathways or functions.Here,we reviewed the mechanisms of action of CD36 antagonists,such as Salvianolic acid B,tanshinone IIA,curcumin,sulfosuccinimidyl oleate,antioxidants,and small-molecule compounds.Moreover,we predicted the structures of binding sites between CD36 and antagonists.These sites can provide targets for more efficient and safer CD36 antagonists for the treatment of central nervous system diseases.

Finding biomarkers of experience in animals

At a time when there is a growing public interest in animal welfare,it is critical to have objective means to assess the way that an animal experiences a situation.Objectivity is critical to ensure appropriate animal welfare outcomes.Existing behavioural,physiological,and neurobiological indicators that are used to assess animal welfare can verify the absence of extremely negative outcomes.But welfare is more than an absence of negative outcomes and an appropriate indicator should reflect the full spectrum of experience of an animal,from negative to positive.In this review,we draw from the knowledge of human biomedical science to propose a list of candidate biological markers(biomarkers)that should reflect the experiential state of non-human animals.The proposed biomarkers can be classified on their main function as endocrine,oxidative stress,non-coding molecular,and thermobiological markers.We also discuss practical challenges that must be addressed before any of these biomarkers can become useful to assess the experience of an animal in real-life.

From the perspective of experimental practice: High-throughput computational screening in photocatalysis

Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.

Experimental Investigation on Vertical Hydraulic Transport of Ores in Deepsea Mining

Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for industrial applications.In the present study,an indoor model test of the vertical hydraulic transport of particles was conducted.A noncontact optical method has been proposed to measure the local characteristics of the particles inside a vertical pipe,including the local concentration and particle velocity.The hydraulic gradient of ore transport was evaluated with various particle size distributions,particle densities,feeding concentrations and mixture flow velocities.During transport,the local concentration is larger than the feeding concentration,whereas the particle velocity is less than the mixture velocity.The qualitative effects of the local concentration and local fluid velocity on the particle velocity and slip velocity were investigated.The local fluid velocity contributes significantly to particle velocity and slip velocity,whereas the effect of the local concentration is marginal.A higher feeding concentration and mixture flow velocity result in an increased hydraulic gradient.The effect of the particle size gradation is slight,whereas the particle density plays a crucial role in the transport.

In-situ electrochemical study on the eff ects of Fe(Ⅲ)on kinetics of pyrite acidic pressure oxidation

Fe(Ⅲ)has been proved to be a more eff ective oxidant than dissolved oxygen at ambient temperature,however,the role of Fe(Ⅲ)in pyrite acidic pressure oxidation was rarely discussed so far.In this paper,in-situ electrochemical investigation was performed using a flow-through autoclave system in acidic pressure oxidation environment.The results illustrated that increasing Fe(Ⅲ)concentrations led to raising in redox potential of the solution,and decreased passivation of pyrite caused by deposition of elemental sulfur.Reduction of Fe(Ⅲ)at pyrite surface was a fast reaction with low activation energy,it was only slightly promoted by rising temperatures.While,the oxidation rate of pyrite at all investigated Fe(Ⅲ)concentrations increased obviously with rising temperatures,the anodic reaction was the rate-limiting step in the overall reaction.Activation energy of pyrite oxidation decreased from 47.74 to 28.79 kJ/mol when Fe(Ⅲ)concentration was increased from 0.05 to 0.50 g/L,showing that the reaction kinetics were limited by the rate of electrochemical reaction at low Fe(Ⅲ)concentrations,while,it gradually turned to be diffusion control with increasing Fe(Ⅲ)concentrations.

Analysis and experimental study on resistance-increasing behavior of composite high efficiency autonomous inflow control device

Bottom water coning is the main reason to reduce the recovery of horizontal bottom water reservoir. By water coning, we mean the oil-water interface changes from a horizontal state to a mound-shaped cone and breaks through to the wellbore. Autonomous inflow control device(AICD) is an important instrument maintain normal production after bottom water coning, however, the resistance increasing ability of the swirl type AICD is insufficient at present, which seriously affects the water control effect. Aiming this problem, this paper designs a multi-stage resistance-increasing and composite type AICD. The separation mechanism of oil-water two phases in this structure, the resistance form of oil-water single phase and the resistance-increasing principle of water phase are analyzed. Establishing the dual-phase multi-stage separation and resistance-increasing model, and verified by measuring the throttling pressure drop and oil-water volume fraction of the AICD, it is found that the composite type AICD has the effect of ICD and AICD at the same time, which can balance the production rate of each well section at the initial stage of production, delay the occurrence of bottom water coning. In the middle and later stages of production, water-blocking can be effectively increased to achieve water control and stable production.After structural sensitivity analysis, the influence law of various structural parameters on the water control performance of composite AICD was obtained. The simulation calculation results show that,compared with the existing swirl type AICD, composite AICD has higher sensitivity to moisture content,the water phase throttling pressure drop is increased by 4.5 times on average. The composite AICD is suitable for the entire stage of horizontal well production.

Sliding and damming properties of granular debris with different geometric configurations and grain size distributions

Granular debris plays a significant role in determining damming deposit characteristics. An indepth understanding of how variations in grain size distribution(GSD) and geometric configurations impact the behavior of granular debris during the occurrence of granular debris is essential for precise assessment and effective mitigation of landslide hazards in mountainous terrains. This research aims to investigate the impact of GSD and geometric configurations on sliding and damming properties through laboratory experiments. The geometric configurations were categorized into three categories based on the spatial distribution of maximum volume: located at the front(Type Ⅰ), middle(Type Ⅱ), and rear(Type Ⅲ) of the granular debris. Our experimental findings highlight that the sliding and damming processes primarily depend on the interaction among the geometric configuration, grain size, and GSD in granular debris. Different sliding and damming mechanisms across various geometric configurations induce variability in motion parameters and deposition patterns. For Type Ⅰ configurations, the front debris functions as the critical and primary driving component, with energy dissipation primarily occurring through inter-grain interactions. In contrast, Type Ⅱ configurations feature the middle debris as the dominant driving component, experiencing hindrance from the front debris and propulsion from the rear, leading to complex alterations in sliding motion. Here, energy dissipation arises from a combination of inter-grain and grain-substrate interactions. Lastly, in Type Ⅲ configurations, both the middle and rear debris serve as the main driving components, with the rear sliding debris impeded by the front. In this case, energy dissipation predominantly results from grainsubstrate interaction. Moreover, we have quantitatively demonstrated that the inverse grading in damming deposits, where coarse grain moves upward and fine grain moves downward, is primarily caused by grain sorting due to collisions among the grains and between the grain and the base. The impact of grain on the horizontal channel further aids grain sorting and contributes to inverse grading. The proposed classification of three geometric configurations in our study enhances the understanding of damming properties from the view of mechanism, which provides valuable insights for related study about damming granular debris.

Numerical Simulation on Radon Retardation Behavior of Covering Floats in Radon-Containing Water

Objective This study aimed to efficiently reduce the release of radon from water bodies to protect the environment.Methods Based on the sizes of the experimental setup and modular float,computational fluid dynamics(CFD)was used to assess the impact of the area coverage rate,immersion depth,diffusion coefficient,and radon transfer velocity at the gas–liquid interface on radon migration and exhalation of radon-containing water.Based on the numerical simulation results,an estimation model for the radon retardation rate was constructed.The effectiveness of the CFD simulation was evaluated by comparing the experimental and simulated variation values of the radon retardation rate with the coverage area rates.Results The effect of radon transfer velocity on radon retardation in water bodies was minor and insignificant according to the appropriate value;therefore,an estimation model of the radon retardation rate of the coverage of a radon-containing water body was constructed using the synergistic impacts of three factors:area coverage rate,immersion depth,and diffusion coefficient.The deviation between the experimental and simulated results was<4.3%.Conclusion Based on the numerical simulation conditions,an estimation model of the radon retardation rate of covering floats in water bodies under the synergistic effect of multiple factors was obtained,which provides a reference for designing covering floats for radon retardation in radoncontaining water.

Probing the peripheral self-generated magnetic field distribution in laser-plasma magnetic reconnection with Martin-Puplett interferometer polarimeter

Magnetic reconnection of the self-generated magnetic fields in laser-plasma interaction is an important laboratory method for modeling high-energy density astronomical and astrophysical phenomena.We use the Martin-Puplett interferometer(MPI)polarimeter to probe the peripheral magnetic fields generated in the common magnetic reconnection configuration,two separated coplanar plane targets,in laser-target interaction.We introduce a new method that can obtain polarization information from the interference pattern instead of the sinusoidal function fitting of the intensity.A bidirectional magnetic field is observed from the side view,which is consistent with the magneto-hydro-dynamical(MHD)simulation results of self-generated magnetic field reconnection.We find that the cancellation of reverse magnetic fields after averaging and integration along the observing direction could reduce the magnetic field strength by one to two orders of magnitude.It indicates that imaging resolution can significantly affect the accuracy of measured magnetic field strength.

Impacts of information about COVID-19 on pig farmers'production willingness and behavior:Evidence from China

This paper examines the impacts of information about COVID-19 on pig farmers'production willingness by using endorsement experiments and follow-up surveys conducted in 2020 and 2021 in China.Our results show that,first,farmers were less willing to scale up production when they received information about COVID-19.The information in 2020 that the second wave of COVID-19 might occur without a vaccine reduced farmers'willingness to scale up by 13.4%,while the information in 2021 that COVID-19 might continue to spread despite the introduction of vaccine reduced farmers'willingness by 4.4%.Second,farmers whose production was affected by COVID-19 were considerably less willing to scale up,given the access to COVID-19 information.Third,farmers'production willingness can predict their actual production behavior.

Multi-environment BSA-seq using large F3 populations is able to achieve reliable QTL mapping with high power and resolution: An experimental demonstration in rice

Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.

Dynamic Modeling and Experimental Verification of an RPR Type Compliant Paralle Mechanism with Low Orders

Efficiency of calculating a dynamic response is an important point of the compliant mechanism for posture adjustment.Dynamic modeling with low orders of a 2R1T compliant parallel mechanism is studied in the paper.The mechanism with two out-of-plane rotational and one lifting degrees of freedom(DoFs)plays an important role in posture adjustment.Based on elastic beam theory,the stiffness matrix and mass matrix of the beam element are established where the moment of inertia is considered.To improve solving efficiency,a dynamic model with low orders of the mechanism is established based on a modified modal synthesis method.Firstly,each branch of the RPR type mechanism is divided into a substructure.Subsequently,a set of hypothetical modes of each substructure is obtained based on the C-B method.Finally,dynamic equation of the whole mechanism is established by the substructure assembly.A dynamic experiment is conducted to verify the dynamic characteristics of the compliant mechanism.

Belief reliability:a scientific exploration of reliability engineering

This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.

Experimental Study on the Electrochemical Performance of PEMFC under Different Assembly Forces

Proton exchange membrane fuel cell(PEMFC)is of paramount significance to the development of clean energy.The components of PEMFC are assembled using many pairs of nuts and bolts.The assembly champing bolt torque is critical to the electrochemical performance and mechanical stability of PEMFC.In this paper,a PEMFC with the threechannel serpentine flow field was used and studied.The different assembly clamping bolt torques were applied to the PEMFC in three uniform assembly bolt torque and six non-uniform assembly bolt torque conditions,respectively.And then,the electrochemical performance experiments were performed to study the effect of the assembly bolt torque on the electrochemical performance.The test results show that the assembly bolt torque significantly affected the electrochemical performance of the PEMFC.In uniform assembly bolt torque conditions,the maximal power density increased initially as the assembly bolt torque increased,and then decreased on further increasing the assembly torque.It existed the optimum assembly torque which was found to be 3.0 N·m in this work.In non-uniform assembly clamping bolt torque conditions,the optimum electrochemical performance appeared in the condition where the assembly torque of each bolt was closer to be 3.0 N·m.This could be due to the change of the contact resistance between the gas diffusion layer and bipolar plate and mass transport resistance for the hydrogen and oxygen towards the catalyst layers.This work could optimize the assembly force conditions and provide useful information for the practical PEMFC stack assembly.

Unveiling the Re,Cr,and I diffusion in saturated compacted bentonite using machine-learning methods

The safety assessment of high-level radioactive waste repositories requires a high predictive accuracy for radionuclide diffusion and a comprehensive understanding of the diffusion mechanism.In this study,a through-diffusion method and six machine-learning methods were employed to investigate the diffusion of ReO_(4)^(−),HCrO_(4)^(−),and I−in saturated compacted bentonite under different salinities and compacted dry densities.The machine-learning models were trained using two datasets.One dataset contained six input features and 293 instances obtained from the diffusion database system of the Japan Atomic Energy Agency(JAEA-DDB)and 15 publications.The other dataset,comprising 15,000 pseudo-instances,was produced using a multi-porosity model and contained eight input features.The results indicate that the former dataset yielded a higher predictive accuracy than the latter.Light gradient-boosting exhibited a higher prediction accuracy(R2=0.92)and lower error(MSE=0.01)than the other machine-learning algorithms.In addition,Shapley Additive Explanations,Feature Importance,and Partial Dependence Plot analysis results indicate that the rock capacity factor and compacted dry density had the two most significant effects on predicting the effective diffusion coefficient,thereby offering valuable insights.

Comparison of nonlinear modeling methods for the composite rubber clamp

The cubic stiffness force model(CSFM)and Bouc-Wen model(BWM)are introduced and compared innovatively.The unknown coefficients of the nonlinear models are identified by the genetic algorithm combined with experiments.By fitting the identified nonlinear coefficients under different excitation amplitudes,the nonlinear vibration responses of the system are predicted.The results show that the accuracy of the BWM is higher than that of the CSFM,especially in the non-resonant region.However,the optimization time of the BWM is longer than that of the CSFM.