基于RSM算法的烟叶含水率监测

为探讨将随机子空间RSM(Random Subspace Method)算法应用于烤烟烟叶含水率的监测中,采摘贵烟8号烟叶样本,在09:00-12:00时间段进行可见光采样,并对图像亮度进行梯度处理,以此模拟全天光线变化。采用烟叶样本实测含水率和图像RGB三阶颜色矩数据作为数据集,对样本使用RSM算法建立含水率回归模型,并与LM(Levenberg Marquardt)神经网络算法和支持向量机(Support Vector Machine,SVM)算法进行比较。结果表明,基于烟叶RGB颜色矩的RSM算法具有较好的应用效果,其回归模型决定系数R 2为0.9202,均方根误差(RMSE)为0.56%,相对分析误差(RPD)为3.5483。故基于随机子空间RSM算法的烟叶含水率回归模型具有较好的稳定性,能实现对烟叶含水率的监测。

基于RSM法的柴油机进气系统参数优化研究

开展进气参数优化是改善柴油机“气油配合”状态,提高柴油机动力性、经济性和排放性的关键。以1台高压共轨柴油机为研究对象,结合已有实验数据搭建了柴油机GT-Power一维性能仿真模型,在最大扭矩工况点处,以进气压力、进气温度、进气门开启角、排气门开启角为变量进行单变量扫值,研究了扭矩和有效燃油消耗率随进气系统参数变化的规律。基于RSM法构建了扭矩和有效燃油消耗率的二次回归模型,得出了影响扭矩和有效燃油消耗率权重排序,开展了平衡最大扭矩和最低有效燃油消耗率的多目标优化,并得到了优化标定参数。实验结果显示:进气压力、进气温度、进气门开启角、排气门开启角分别为2.27 bar、369 K、459°CA、255°CA时,参数组合使得扭矩提升到311.08 N·m,较原机提升了6.51%;有效燃油消耗率降低到204.11 g/(kW·h),较原机降低了6.25%;最大气缸压力为154 bar,涡轮前排气温度为883 K,未超限制要求。这表明RSM法用于柴油机进气系统参数协同优化是可行的,优化后达到了相应的目标要求。

基于决策树特征提取与RSM_LightGBM的涡扇发动机RUL预测

针对现有航空发动机剩余使用寿命预测(RUL)精度低及传感器监测参数提取困难等问题,提出了一种基于决策树特征提取与随机搜索算法优化LightGBM的航空发动机RUL预测模型。首先,对航空发动机历史监测参数进行分析,利用决策树算法计算监测参数对发动机寿命周期的重要性贡献程度,提取重要特征后对数据进行归一化处理,降低数据量纲对预测模型的影响;其次,根据航空发动机的历史衰退特征,为发动机设置阈值标签,表征发动机的性能退化特点。最后,利用随机搜索算法对LightGBM中的超参数进行寻优,获得RMSE最小值。在CMAPSS数据集上进行了实验验证。结果表明,与其他构建模型的最优值相比,所提方法在多个评价指标下具有更好的综合性能,有效提升了航空发动机RUL预测的精准度。

A Review on Sources,Extractions and Analysis Methods of a Sustainable Biomaterial:Tannins

Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.

Optimization of Preparation Conditions of Modified Oyster Shell Powder/Ce-N-TiO2 by Response Surface Methodology (RSM)

A new composite photocatalyst of modified oyster shell powder/Ce-N-TiO2 was prepared by sol-gel method. Based on single factor experiment, Ce doping rate, N doping rate and calcination temperature were taken as input variables. Based on the central composite design (BBD) response surface model, two functional relationship models between three independent variables and glyphosate removal rate were established to evaluate the influence degree of independent variables and interaction on catalyst. The significance of the model and regression coefficient was tested by variance analysis. The analysis of the obtained data showed that the degradation performance of the composite photocatalyst was significantly affected by the calcination temperature and the rate of N doping, while the rate of Ce doping had little effect;at the calcination temperature of 505.440°C, the degradation rate of glyphosate reached the maximum of 82.15% under the preparation conditions of 17.057 mol% N doping and 0.165 mol% Ce doping, respectively.

Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

RSM优化焚烧底灰胶凝材料及安全性评价

为了将生活垃圾焚烧底灰(MSWI-BA)进行资源化利用,基于响应面中心复合试验法(RSM-CCD)研究了不同活性激发方式对经过预处理的MSWI-BA水泥胶砂试块28 d抗压强度的影响.结果表明:活性激发MSWI-BA胶凝材料具有较好的胶凝活性;采用RSM-CCD得到,掺10%MSWI-BA水泥胶砂试块在最佳试验条件下的28 d抗压强度计算值为46.04 MPa,实测值为46.15 MPa,二者符合较好,为MSWI-BA的资源化利用提供了一种解决方法;MSWI-BA胶凝材料的安全性较好,重金属浸出性能满足GB 30760—2014《水泥窑协同处置固体废物技术规范》的要求.

Material point method simulation of hydro-mechanical behaviour in twophase porous geomaterials: A state-of-the-art review

The material point method(MPM)has been gaining increasing popularity as an appropriate approach to the solution of coupled hydro-mechanical problems involving large deformation.In this paper,we survey the current state-of-the-art in the MPM simulation of hydro-mechanical behaviour in two-phase porous geomaterials.The review covers the recent advances and developments in the MPM and their extensions to capture the coupled hydro-mechanical problems involving large deformations.The focus of this review is aiming at providing a clear picture of what has or has not been developed or implemented for simulating two-phase coupled large deformation problems,which will provide some direct reference for both practitioners and researchers.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

基于RSM-BBD的多源煤基固废胶结体配比及性能研究

本工作采用响应面法(RSM)Box-Behnken Design(BBD)模式对脱硫石膏、气化细渣和炉底渣等多源煤基固废进行配比优选,并研究了最优配比胶结体的力学性能、孔隙结构、热稳定性、微观结构等特性。结果表明:(1)气化细渣掺量对胶结体的1 d强度影响最大,脱硫石膏掺量对胶结体3 d和7 d强度影响最大,两种固废的交互作用对胶结体早期强度影响最显著,表现为负效应;在粉煤灰与矸石质量比为0.4∶1和质量浓度为80%的条件下,获得脱硫石膏、气化细渣和炉底渣的最优质量比为0.2∶0.1∶0.1,并分析了最优配比胶结体的压缩变形和破坏特征。(2)研究了胶结体的微观特性:胶结体内存在密集细颈型封闭孔隙,孔直径范围在5~3.7×10^(5) nm,微孔较少,以中、大孔为主;胶结体在55~65℃和90~120℃区间出现游离水和结晶水的吸热脱水反应,在600~700℃区间出现结构水、羟基水的脱除和水化产物的分解,在800℃累计失重约8%。(3)煤基固废胶结体的水化反应以水泥为主,固废之间未发生化学反应,水化产物为少量短杆状钙矾石相和薄层绒状C-S-H凝胶;钙矾石中少量Al^(3+)被Si^(4+)取代,少量SO_(4)^(2-)被CO_(3)^(2-)取代。

基于CCD-RSM联用D-最优混料设计优化抗下肢静脉血栓颗粒制剂工艺的研究

目的 采用星点设计-效应面法(CCD-RSM)联用D-最优混料设计,优化抗下肢静脉血栓颗粒的制剂工艺。方法 以溶媒用量、煎煮时间为主要考察因素,以有效成分丹酚酸B和多糖含量及干膏收率的总评归一值(OD)为评价指标,采用CCD-RSM确定最佳提取工艺;以颗粒吸湿率为评价指标,结合溶化性、成型率、休止角等,利用D-最优混料设计优选最佳成型工艺。结果 最佳提取工艺:采用8倍量水提取2次,每次100 min。成型工艺为浸膏与辅料比例1:2,辅料间比例为可溶性淀粉:糊精:蔗糖=0.452:0.518:0.030。结论 优选的制剂工艺条件稳定、可行,可为抗下肢静脉血栓颗粒的生产提供依据。

Sparse Modal Decomposition Method Addressing Underdetermined Vortex-Induced Vibration Reconstruction Problem for Marine Risers

When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Numerical manifold method for thermo-mechanical coupling simulation of fractured rock mass

As a calculation method based on the Galerkin variation,the numerical manifold method(NMM)adopts a double covering system,which can easily deal with discontinuous deformation problems and has a high calculation accuracy.Aiming at the thermo-mechanical(TM)coupling problem of fractured rock masses,this study uses the NMM to simulate the processes of crack initiation and propagation in a rock mass under the influence of temperature field,deduces related system equations,and proposes a penalty function method to deal with boundary conditions.Numerical examples are employed to confirm the effectiveness and high accuracy of this method.By the thermal stress analysis of a thick-walled cylinder(TWC),the simulation of cracking in the TWC under heating and cooling conditions,and the simulation of thermal cracking of the SwedishÄspöPillar Stability Experiment(APSE)rock column,the thermal stress,and TM coupling are obtained.The numerical simulation results are in good agreement with the test data and other numerical results,thus verifying the effectiveness of the NMM in dealing with thermal stress and crack propagation problems of fractured rock masses.

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

基于RSM和MOPSO的轴承沟道磨削工艺参数优化

探究角接触球轴承内圈沟道精磨工艺参数与加工质量的响应关系,确定最优工艺参数组,提高沟道加工质量。采用响应面法(RSM)与多目标粒子群优化(MOPSO)算法优化影响沟道加工质量的磨削深度、砂轮线速度和工件转速。首先利用RSM建立以沟道表面粗糙度和圆度误差为响应的显著不失拟模型;然后通过方差分析和响应曲面图研究工艺参数对响应的交互影响规律;最后采用MOPSO算法对模型进行多目标优化,利用K-means聚类法求解最优解集的折衷解,并进行试验验证。结果表明,磨削深度和砂轮线速度对沟道表面粗糙度和圆度误差影响极显著,工件转速对圆度误差的影响极显著,对表面粗糙度的影响显著;磨削深度与工件转速的交互作用对表面粗糙度影响显著,砂轮线速度与工件转速、磨削深度的交互作用对圆度误差影响显著。最优工艺参数组经试验验证,表面粗糙度和圆度误差较优化前分别减小了8.14%和16.03%。基于RSM和MOPSO算法结合的回归模型整体和单个变量显著,且有较高的预测精度,寻优后的工艺参数组可获得良好的优化效果。