Feature Model Configuration Reuse Scheme for Self-Adaptive Systems

Most large-scale systems including self-adaptive systems utilize feature models(FMs)to represent their complex architectures and benefit from the reuse of commonalities and variability information.Self-adaptive systems(SASs)are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite contexts.However,reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and resources.The process of configuration reuse can be a better alternative to some contexts to reduce computational time,effort and error-prone.Nevertheless,systems’complexity can be reduced while the development process of systems by reusing elements or components.FMs are considered one of the new ways of reuse process that are able to introduce new opportunities for the reuse process beyond the conventional system components.While current FM-based modelling techniques represent,manage,and reuse elementary features to model SASs concepts,modeling and reusing configurations have not yet been considered.In this context,this study presents an extension to FMs by introducing and managing configuration features and their reuse process.Evaluation results demonstrate that reusing configuration features reduces the effort and time required by a reconfiguration process during the run time to meet the required scenario according to the current context.

The Analysis of Unified Software Engineering Reuse （USER） Using Stable Analytical Model, Design of Structure and Architectural Patterns

The wearisome enthusiasm for making reasonable structures for programming reuse has gone before for whatever period of time that item has existed. Accepting particular intense structures are made for ensuring an abnormal state ofrensability from one suspect to the accompanying. The unavoidable slant for dares to ask for extensive alterations, paying little mind to being proposed for most noteworthy reusability, remains strong affirmation of this reality. Programming reusability makes examination of stable examination; arrange, likewise, plan outlines a range of tremendous interest. By extrapolating the unfaltering thoughts that use programming consistent quality show and the Knowledge Maps, we attempt to comprehend programming plans that do not require unrestrained modifications, changes or, then again augment. Such cases works kind of a structure, to the most recent inquiries could be incorporated rely on simply the development of the circumstance to which that is associated. Suitability of such methodology must be displayed in the paper.

Research status and application of artificial intelligence large models in the oil and gas industry

This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.

A Knowledge-reuse Based Intelligent Reasoning Model for Worsted Process Optimization

The textile process planning is a knowledge reuse process in nature, which depends on the expert’s knowledge and experience. It seems to be very difficult to build up an integral mathematical model to optimize hundreds of the processing parameters. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel knowledge-reuse based hybrid intelligent reasoning model (HIRM) for worsted process optimization. The model architecture and reasoning mechanism are respectively described. An applied case with HIRM is given to demonstrate that the best process decision can be made, and important processing parameters such as for raw material optimized.

Influences of Co-Flow and Counter-Flow Modes of Reactant Flow Arrangement on a PEMFC at Start-Up

To investigate the influences of co-flowand counter-flowmodes of reactant flowarrangement on a proton exchange membrane fuel cell(PEMFC)during start-up,unsteady physical and mathematical models fully coupling the flow,heat,and electrochemical reactions in a PEMFC are established.The continuity equation and momentum equation are solved by handling pressure-velocity coupling using the SIMPLE algorithm.The electrochemical reaction rates in the catalyst layers(CLs)of the cathode and anode are calculated using the Butler-Volmer equation.The multiphase mixture model describes the multiphase transport process of gas mixtures and liquid water in the fuel cell.After validation,the influences of co-flow and counter-flow modes on the PEMFC performance are investigated,including the evolution of the current density,flow field,temperature field,and reactant concentration field during start-up,as well as the steady distribution of the current density,reactant concentration,andmembrane water content when the start-up stabilizes.Co-flow and counter-flow modes influence the current density distribution and temperature distribution.On the one hand,the co-flow mode accelerates the start-up process of the PEMFC and leads to a more evenly distributed current density than the counter-flow mode.On the other hand,the temperature difference between the inlet and outlet sections of the cell is up to 10.1℃ under the co-flow mode,much larger than the 5.0℃ observed in the counter-flow mode.Accordingly,the counter-flowmode results in a more evenly distributed temperature and a lower maximum temperature than the co-flow case.Therefore,in the flow field design of a PEMFC,the reactant flow arrangements can be considered to weigh between better heat management and higher current density distribution of the cell.

Product Model Evolvement and Configuration Knowledge Reuse Method

Configuration knowledge is a dynamic information set which is evolving and enriching on and on. Product model is the instantiation of configuration knowledge and the evolution of configuration knowledge is the essential inherent reason which causes the models dynamic evolvement. In the traditional model evolvement process, the inheriting and reuse of configuration knowledge was always ignored. Aim at solving the above problem, the multistage rhombus evolution mode of configuration knowledge is discussed in this paper. The product model based on configuration knowledge is put forward in different levels to achieve the models dynamic evolvement and automatic upgrading. The evolving configuration knowledge drives the product model to evolve directly according to the rule of up-layer evolvement. Furthermore, a new configuration knowledge reuse and optimization technology is presented to inheriting and reuse the foregone configuration knowledge in the course of model evolvement. At last, the air separation equipment which is related with the project is taken as an example to illuminate that the presented model evolvement and configuration knowledge reuse technology are validity and practical.

Spatial structure optimization of mountainous abandoned mine land reuse based on system dynamics model and CLUE-S model

The mountainous abandoned mine land is often distributed in the fomi of fragmented patches. Therefore, it can greatly promote the reuse value of abandoned mine land and relieve the pressure of land demand to realize the rational reuse of abandoned mine land based on the future land use structure and spatial layout of mountainous area. In this paper, optimization of the spatial structure of mountainous abandoned mine land reuse is realized through the system dynamics model and CLUE-S model. Mentougou district, Beijing, China is selected as the research area. System dynamics model with feedback functions is constructed to simulate land use structure from 2011 to 2025, which is taken as the quanfiiative constraint on spatial structure optimization. CLUE-S model with neighborhood analysis function is applied to simulate future land use spatial structure. The simulation result layer is superimposed with the abandoned mine land distribution layer and the optimized spatial structure of abandoned mine land reuse then is determined, checked by reuse suitability evaluation. The result shows that abandoned mine land can be fully optimized as other land use types according to demand, and the reuse directions are water conservancy facilities land, urban land, rural residential land, tourism land, garden land, woodland and grassland. The trend of abandoned mine land reuse tend to be consistent with land use types of neighboring patches. This study can provide theoretical reference for the practices of mountainous abandoned mine land reuse.

FUZZY OPTIMIZATION MODEL OF MAINTENANCE DESIGN FOR PRODUCT LEVEL REUSE

Most used products must be maintained before they are reused. The modelingmethod for maintenance design of product level reuse based on quality function deployment ispresented. A fuzzy linear optimization model is developed under financial uncertainty. Objective ofthe model is to maximize improvement rate of customer satisfaction level. Maintenance cost constrainis fuzzy. The algorithm for solution to the model is given. Its optimized results not only giveattention to satisfaction degree of cost constraint, but also maximize objective value. Anillustrative example involved water bump reuse is studied and the results show that the proposedmodel can effectively help maintenance planner determine the better design scheme.

Pollutants removal and simulation model of combined membrane process for wastewater treatment and reuse in submarine cabin for long voyage

A laboratory scale test was conducted in a combined membrane process （CMP） with a capacity of 2.91 m3/d for 240 d to treat the mixed wastewater of humidity condensate, hygiene wastewater and urine in submarine cabin during prolonged voyage. Removal performance of chemical oxygen demand （COD）, ammonia nitrogen （NH4^＋-N）, turbidity and anionic surfactants （LAS） was investigated under different conditions. It was observed that the effluent COD, NH4^＋-N, turbidity and LAS flocculated in ranges of 0.19-0.85 mg/L, 0.03-0.18 mg/L, 0.0-0.15 NTU and 0.0-0.05 mg/L, respectively in spite of considerable fluctuation in corresponding influent of 2120-5350 mg/L, 79.5-129.3 mg/L, 110-181.1NTU and 4.9-5.4 mg/L. The effluent quality of the CMP could meet the requirements of mechanical water and hygiene water according to the class I water quality standards in China （GB3838-2002）. The removal rates of COD, NH4^＋-N, turbidity and LAS removed in the MBR were more than 90%, which indicated that biodegradation is indispensable and plays a major role in the wastewater treatment and reuse. A model, built on the back propagation neural network （BPNN） theory, was developed for the simulation of CMP and produced high reliability. The average error of COD and NH4^＋-N was 5.14% and 6.20%, respectively, and the root mean squared error of turbidity and LAS was 2.76% and 1.41%, respectively. The results indicated that the model well fitted the laboratory data, and was able to simulate the removal of COD, NH4^＋-N, turbidity and LAS. It also suggested that the model proposed could reflect and manage the operation of CMP for the treatment of the mixed wastewaters in submarine.

Knowledge-reuse-oriented Product Modeling and Knowledge Management in Digital Design

Mostly product design knowledge and experience exists in design handbook or expert’s brain. During design process,designer has to refer to many handbooks and design materials,and design solution is hard to be reused. In order to deal with these deficiencies in digital design,this paper focuses on knowledge-reuse-oriented product modeling and knowledge management. Design knowledge is used to guide design process,and it is embedded into product model along with design process. Through analyzing design process,mechanical product knowledge is classified into four basic types that include calculation formula,design rule,engineering check and parameter spectrum etc. In order to manage and encapsulate design knowledge the concept of knowledge component(KCOM) is proposed. Design knowledge base can be organized as a hierarchy tree of KCOM. Knowledge reuse in KCOM level is the reuse of whole object in knowledge base,and knowledge reuse in item level is the reuse of basic knowledge type. Finally knowledge reuse approaches between knowledge base and CAD system is presented.

Implications of de Facto Reuse on Future Regulatory Developments for Beaufort-Jasper Water & Sewer Authority in Okatie, South Carolina, USA

A significant portion of the national water supply can be attributed to de facto or unplanned potable reuse, though the extent of its contribution is difficult to estimate. Fortunately, the contribution of Water Resource Recovery Facility (WRRF) effluent to waters that supply drinking water treatment plants has been documented by some communities. In the United States (US), among the top 25 most impacted drinking water treatment plants by upstream WRRF, 16% of the influent flow to the drinking water treatment plant under average streamflow and up to 100% under low-flow conditions is WRRF effluent. Currently, the full extent of de facto reuse in the US may be much higher because of population growth. The scenario is no different for Beaufort-Jasper Water and Sewer Authority (BJWSA) in South Carolina, US, with contributions to the Savannah River originating from numerous WRRF and other upstream dischargers. South Carolina coastal utilities such as BJSWA are considering direct and indirect potable reuse options, driven by disposal limitations and challenges. Currently, South Carolina does not have a framework, guidelines, or regulations for reuse, but discussions have started among the regulated community. In addition to understanding the extent of de facto reuse, the state will need to develop standards and best practices to enable future adoption of planned potable reuse solutions to water resources challenges. Such guidance should address human health risk management and technical considerations regarding treatment in addition to other factors, including source control, storage, fail-safe operation, monitoring, non-cost factors, and public acceptance. This study conducted a mapping assessment specific to BJWSA, sampled at four locations on Savannah River, and observed that de facto reuse is approximately 4.6% to 5.9% during low-flow months and is within the range generally observed nationwide. When coupled with evidence that planned potable reuse can improve human health and environmental risks, this practice is a meaningful option in the water supply portfolio for many utilities.

A Study on the Reuse Modes and Renovation Strategies of Contemporary Chinese Urban Industrial Buildings

With the progress of urbanization in China,the pace of urban renewal is accelerating.Various factors have prompted the transformation of industrial buildings in the city.Following the transformation,old industrial buildings have shown a new look with diversification and modernization.This article briefly describes contemporary China.The background of industrial building renovation and the analysis of the redevelopment and utilization modes as well as renovation strategies in conjunction with case studies provide a summary and enlightenment for the renovation of industrial heritage buildings in the city.

Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

Effects of spot size on the operation mode of Ga As photoconductive semiconductor switch employing extrinsic photoconductivity

To guide the illuminating design to improve the on-state performances of gallium arsenide(GaAs)photoconductive semiconductor switch(PCSS),the effect of spot size on the operation mode of GaAsPCSS based on a semi-insulating wafer with a thickness of 1 mm,triggered by a 1064-nm extrinsic laser beam with the rectangular spot,has been investigated experimentally.It is found that the variation of the spot size in length and width can act on the different parts of the output waveform integrating the characteristics of the linear and nonlinear modes,and then significantly boosts the PCSS toward different operation modes.On this basis,a two-channel model containing the active and passive parts is introduced to interpret the relevant influencing mechanisms.Results indicate that the increased spot length can peak the amplitude of static domains in the active part to enhance the development of the nonlinear switching,while the extended spot width can change the distribution of photogenerated carriers on both parts to facilitate the linear switching and weaken the nonlinear switching,which have been proved by comparing the domain evolutions under different spot sizes.

Damage constitutive model of lunar soil simulant geopolymer under impact loading

Lunar base construction is a crucial component of the lunar exploration program,and considering the dynamic characteristics of lunar soil is important for moon construction.Therefore,investigating the dynamic properties of lunar soil by establishing a constitutive relationship is critical for providing a theoretical basis for its damage evolution.In this paper,a split Hopkinson pressure bar(SHPB)device was used to perform three sets of impact tests under different pressures on a lunar soil simulant geopolymer(LSSG)with sodium silicate(Na_(2)SiO_(3))contents of 1%,3%,5%and 7%.The dynamic stressestrain curves,failure modes,and energy variation rules of LSSG under different pressures were obtained.The equation was modified based on the ZWT viscoelastic constitutive model and was combined with the damage variable.The damage element obeys the Weibull distribution and the constitutive equation that can describe the mechanical properties of LSSG under dynamic loading was obtained.The results demonstrate that the dynamic compressive strength of LSSG has a marked strain-rate strengthening effect.Na_(2)SiO_(3) has both strengthening and deterioration effects on the dynamic compressive strength of LSSG.As Na_(2)SiO_(3) grows,the dynamic compressive strength of LSSG first increases and then decreases.At a fixed air pressure,5%Na_(2)SiO_(3) had the largest dynamic compressive strength,the largest incident energy,the smallest absorbed energy,and the lightest damage.The ZWT equation was modified according to the stress response properties of LSSG and the range of the SHPB strain rate to obtain the constitutive equation of the LSSG,and the model’s correctness was confirmed.

Transition from a filamentary mode to a diffuse one with varying distance from needle to stream of an argon plasma jet

Plasma jet has extensive application potentials in various fields, which normally operates in a diffuse mode when helium is used as the working gas. However, when less expensive argon is used, the plasma jet often operates in a filamentary mode. Compared to the filamentary mode, the diffuse mode is more desirable for applications. Hence, many efforts have been exerted to accomplish the diffuse mode of the argon plasma jet. In this paper, a novel single-needle argon plasma jet is developed to obtain the diffuse mode. It is found that the plasma jet operates in the filamentary mode when the distance from the needle tip to the central line of the argon stream(d) is short. It transits to the diffuse mode with increasing d. For the diffuse mode, there is always one discharge pulse per voltage cycle, which initiates at the rising edge of the positive voltage. For comparison, the number of discharge pulse increases with an increase in the peak voltage for the filamentary mode. Fast photography reveals that the plasma plume in the filamentary mode results from a guided positive streamer,which propagates in the argon stream. However, the plume in the diffuse mode originates from a branched streamer, which propagates in the interfacial layer between the argon stream and the surrounding air. By optical emission spectroscopy,plasma parameters are investigated for the two discharge modes, which show a similar trend with increasing d. The diffuse mode has lower electron temperature, electron density, vibrational temperature, and gas temperature compared to the filamentary mode.

Suppression of the m/n=2/1 tearing mode by electron cyclotron resonance heating on J-TEXT

Stabilization of tearing modes and neoclassical tearing modes is of great importance for tokamak operation.Electron cyclotron waves(ECWs)have been extensively used to stabilize the tearing modes with the virtue of highly localized power deposition.Complete suppression of the m/n=2/1 tearing mode(TM)by electron cyclotron resonance heating(ECRH)has been achieved successfully on the J-TEXT tokamak.The effects of ECW deposition location and power amplitude on the 2/1 TM suppression have been investigated.It is found that the suppression is more effective when the ECW power is deposited closer to the rational surface.As the ECW power increases to approximately 230 k W,the 2/1 TM can be completely suppressed.The island rotation frequency is increased when the island width is reduced.The experimental results show that the local heating inside the magnetic island and the resulting temperature perturbation increase at the O-point of the island play dominant roles in TM suppression.As the ECW power increases,the 2/1 island is suppressed to smaller island width,and the flow shear also plays a stabilizing effect on small magnetic islands.With the stabilizing contribution of heating and flow shear,the 2/1 TM can be completely suppressed.

Investigation on the roles of equilibrium toroidal rotation during edge-localized mode mitigated by resonant magnetic perturbations

The effects of equilibrium toroidal rotation during edge-localized mode(ELM)mitigated by resonant magnetic perturbation(RMP)are studied with the experimental equilibria of the EAST tokamak based on the four-field model in the BOUT++code.As the two main parameters to determine the toroidal rotation profiles,the rotation shear and magnitudes were separately scanned to investigate their roles in the impact of RMPs on peeling-ballooning(P-B)modes.On one hand,the results show that strong toroidal rotation shear is favorable for the enhancement of the self-generated E×B shearing rate<ω_(E×B)>with RMPs,leading to significant ELM mitigation with RMP in the stronger toroidal rotation shear region.On the other hand,toroidal rotation magnitudes may affect ELM mitigation by changing the penetration of the RMPs,more precisely the resonant components.RMPs can lead to a reduction in the pedestal energy loss by enhancing the multimode coupling in the turbulence transport phase.The shielding effects on RMPs increase with the toroidal rotation magnitude,leading to the enhancement of the multimode coupling with RMPs to be significantly weakened.Hence,the reduction in pedestal energy loss by RMPs decreased with the rotation magnitude.In brief,the results show that toroidal rotation plays a dual role in ELM mitigation with RMP by changing the shielding effects of plasma by rotation magnitude and affecting<ω_(E×B)>by rotation shear.In the high toroidal rotation region,toroidal rotation shear is usually strong and hence plays a dominant role in the influence of RMP on P-B modes,whereas in the low rotation region,toroidal rotation shear is weak and has negligible impact on P-B modes,and the rotation magnitude plays a dominant role in the influence of RMPs on the P-B modes by changing the field penetration.Therefore,the dual role of toroidal rotation leads to stronger ELM mitigation with RMP,which may be achieved both in the low toroidal rotation region and the relatively high rotation region that has strong rotational shear.

Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice--A Systematic Review

Forecasting travel demand requires a grasp of individual decision-making behavior.However,transport mode choice(TMC)is determined by personal and contextual factors that vary from person to person.Numerous characteristics have a substantial impact on travel behavior(TB),which makes it important to take into account while studying transport options.Traditional statistical techniques frequently presume linear correlations,but real-world data rarely follows these presumptions,which may make it harder to grasp the complex interactions.Thorough systematic review was conducted to examine how machine learning(ML)approaches might successfully capture nonlinear correlations that conventional methods may ignore to overcome such challenges.An in-depth analysis of discrete choice models(DCM)and several ML algorithms,datasets,model validation strategies,and tuning techniques employed in previous research is carried out in the present study.Besides,the current review also summarizes DCM and ML models to predict TMC and recognize the determinants of TB in an urban area for different transport modes.The two primary goals of our study are to establish the present conceptual frameworks for the factors influencing the TMC for daily activities and to pinpoint methodological issues and limitations in previous research.With a total of 39 studies,our findings shed important light on the significance of considering factors that influence the TMC.The adjusted kernel algorithms and hyperparameter-optimized ML algorithms outperform the typical ML algorithms.RF(random forest),SVM(support vector machine),ANN(artificial neural network),and interpretable ML algorithms are the most widely used ML algorithms for the prediction of TMC where RF achieved an R2 of 0.95 and SVM achieved an accuracy of 93.18%;however,the adjusted kernel enhanced the accuracy of SVM 99.81%which shows that the interpretable algorithms outperformed the typical algorithms.The sensitivity analysis indicates that the most significant parameters influencing TMC are the age,total trip time,and the number of drivers.

Fixed-Time Sliding Mode Control With Varying Exponent Coefficient for Modular Reconfigurable Flight Arrays

The modular system can change its physical structure by self-assembly and self-disassembly between modules to dynamically adapt to task and environmental requirements. Recognizing the adaptive capability of modular systems, we introduce a modular reconfigurable flight array(MRFA) to pursue a multifunction aircraft fitting for diverse tasks and requirements,and investigate the attitude control and the control allocation problem by using the modular reconfigurable flight array as a platform. First, considering the variable and irregular topological configuration of the modular array, a center-of-mass-independent flight array dynamics model is proposed to allow control allocation under over-actuated situations. Secondly, in order to meet the stable, fast and accurate attitude tracking performance of the MRFA, a fixed-time convergent sliding mode controller with state-dependent variable exponent coefficients is proposed to ensure fast convergence rate both away from and near the system equilibrium point without encountering the singularity. It is shown that the controller also has fixed-time convergent characteristics even in the presence of external disturbances. Finally,simulation results are provided to demonstrate the effectiveness of the proposed modeling and control strategies.