Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Metal-N_(4) model single‐atom catalyst with electroneutral quadri‐pyridine macrocyclic ligand for CO_(2) electroreduction

Metal–N–C single‐atom catalysts,mostly prepared from pyrolysis of metalorganic precursors,are widely used in heterogeneous electrocatalysis.Since metal sites with diverse local structures coexist in this type of material and it is challenging to characterize the local structure,a reliable structure–property relationship is difficult to establish.Conjugated macrocyclic complexes adsorbed on carbon support are well‐defined models to mimic the singleatom catalysts.Metal–N_(4) site with four electroneutral pyridine‐type ligands embedded in a graphene layer is the most commonly proposed structure of the active site of single‐atom catalysts,but its molecular counterpart has not been reported.In this work,we synthesized the conjugated macrocyclic complexes with a metal center(Co,Fe,or Ni)coordinated with four electroneutral pyridinic ligands as model catalysts for CO_(2) electroreduction.For comparison,the complexes with anionic quadri‐pyridine macrocyclic ligand were also prepared.The Co complex with the electroneutral ligand expressed a turnover frequency of CO formation more than an order of magnitude higher than that of the Co complex with the anionic ligand.Constrained ab initio molecular dynamics simulations based on the well‐defined structures of the model catalysts indicate that the Co complex with the electroneutral ligand possesses a stronger ability to mediate electron transfer from carbon to CO_(2).

Model Order Reduction Methods for Discrete Systems via Discrete Pulse Orthogonal Functions

This paper explores model order reduction(MOR)methods for discrete linear and discrete bilinear systems via discrete pulse orthogonal functions(DPOFs).Firstly,the discrete linear systems and the discrete bilinear systems are expanded in the space spanned by DPOFs,and two recurrence formulas for the expansion coefficients of the system’s state variables are obtained.Then,a modified Arnoldi process is applied to both recurrence formulas to construct the orthogonal projection matrices,by which the reduced-order systems are obtained.Theoretical analysis shows that the output variables of the reducedorder systems can match a certain number of the expansion coefficients of the original system’s output variables.Finally,two numerical examples illustrate the feasibility and effectiveness of the proposed methods.

Metamodel-based Global Optimization Using Fuzzy Clustering for Design Space Reduction

High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strategy for engineering design optimization problems involving expensive black box models.

OptoGPT: A foundation model for inverse design in optical multilayer thin film structures

Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.

Experimental Study of Air Layer Drag Reduction with Bottom Cavity for A Bulk Carrier Ship Model

Air lubrication by means of a bottom cavity is a promising method for ship drag reduction. The characteristics of the bottom cavity are sensitive to the flow field around the ship hull and the effect of drag reduction, especially the depth of the bottom cavity. In this study, a ship model experiment of a bulk carrier is conducted in a towing tank using the method of air layer drag reduction (ALDR) with different bottom cavity depths. The shape of the air layer is observed, and the changes in resistance are measured. The model experiments produce results of approximately 20% for the total drag reduction at the ship design speed for a 25-mm cavity continuously supplied with air at Cq = 0.224 in calm water, and the air layer covers the whole cavity when the air flow rate is suitable. In a regular head wave, the air layer is easily broken and reduces the drag reduction rate in short waves, particularly when λ/Lw1 is close to one;however, it still has a good drag reduction effect in the long waves.

Acid deposition critical loads modeling for the simulation of sulfur exceedance and reduction in Guangdong, China

The current acid deposition critical loads in Guangdong, China were calculated using the PROFILE model with a 3 km × 3 km resolution. Calculations were carded out for critical loads of potential acidity, actual acidity, sulfur and nitrogen, with values in extents of 0-3.5, 0-14.0, 0-26.0 and 0-3.5 kmol/（hrnE.year）, respectively. These values were comparable to previously reported results and reflected the influences of vegetation and soil characteristics on the soil acid buffering capacity. Simulations of SO2 emission and sulfur deposition in this study showed that sulfur deposition core areas mirrored SO2 emission centers. The prediction of sulfur deposition after 20% and 40% reduction of SO2 emission suggested that the reduction of area sources contributed greatly to the decrease of sulfur deposition. Thus, abatement of area source emissions could be the primary way to mitigate sulfur deposition in Guangdong to meet both the provincial and national regulations of air pollution control.

Mathematical model of the direct reduction of dust composite pellets containing zinc and iron

Direct reduction of dust composite pellets containing zinc and iron was examined by simulating the conditions of actual production process of a rotary hearth furnace （RHF） in laboratory. A mathematical model was constructed to study the reduction kinetics of iron oxides and ZnO in the dust composite pellets. It was validated by comparing the calculated values with experimental results. The effects of furnace temperature, pellet radius, and pellet porosity on the reduction were investigated by the model. It is shown that furnace temperature has obvious influence on both of the reduction of iron oxides and ZnO, but the influence of pellet radius and porosity is much smaller. Model calculations suggest that both of the reduction of iron oxides and ZnO are under mixed control with interface reactions and Boudouard reaction in the early stage, but only with interface reactions in the later stage.

Micro-bubble Drag Reduction on a High Speed Vessel Model

Ship hull form of the underwater area strongly influences the resistance of the ship. The major factor in ship resistance is skin friction resistance. Bulbous bows, polymer paint, water repellent paint （highly water-repellent wall）, air injection, and specific roughness have been used by researchers as an attempt to obtain the resistance reduction and operation efficiency of ships. Micro-bubble injection is a promising technique for lowering frictional resistance. The injected air bubbles are supposed to somehow modify the energy inside the turbulent boundary layer and thereby lower the skin friction. The purpose of this study was to identify the effect of injected micro bubbles on a navy fast patrol boat （FPB） 57 m type model with the following main dimensions： L=2 450 ram, B=400 mm, and T=190 mm. The influence of the location of micro bubble injection and bubble velocity was also investigated. The ship model was pulled by an electric motor whose speed could be varied and adjusted. The ship model resistance was precisely measured by a load cell transducer. Comparison of ship resistance with and without micro-bubble injection was shown on a graph as a function of the drag coefficient and Froude number. It was shown that micro bubble injection behind the mid-ship is the best location to achieve the most effective drag reduction, and the drag reduction caused by the micro-bubbles can reach 6%-9%.

Composite Rotor Blade Design Optimization for Vibration Reduction with Aeroelastic Constraints

The paper presents an analytical study of the helicopter rotor vibratory loadreduction design optimization with aeroelastic stability constraints. The composite rotor blade ismodeled by beam type finite elements, and warping deformation is taken into consideration for2-dimension analysis, while the one-dimension nonlinear differential equations of blade motion areformulated via Hamilton's principle. The rotor hub vibratory loads is chosen as the objectivefunction, while rotor blade section construction parameter, composite material ply structure andblade tip swept angle as the design variables, and au-torotation inertia, natural frequency andaeroelastic stability as the constraints. A 3-bladed rotor is designed, as an example, based on thevibratory hub load reduction optimization process with swept tip angle and composite material. Thecalculating results show a 24. 9 percent-33 percent reduction of 3/rev hub loads in comparison withthe base-line rotor.

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

Background:As the market demands change,SMEs(small and medium-sized enterprises)have long faced many design issues,including high costs,lengthy cycles,and insufficient innovation.These issues are especially noticeable in the domain of cosmetic packaging design.Objective:To explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization.Methods:To accomplish this objective,the basic-element theory has been introduced and applied to the design and development system of the product family.Results:By examining the mapping relationships between the demand domain,functional domain,technology domain,and structure domain,four interrelated models have been developed,including the demand model,functional model,technology model,and structure model.Together,these models form the mechanism and methodology of product family modeling,specifically for cosmetic packaging design.Through an analysis of a case study on men’s cosmetic packaging design,the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design,and the design efficiency has been enhanced.Conclusion:The product family modeling technology employs a formalized element as a module configuration design language,permeating throughout the entire development cycle of cosmetic packaging design,thus facilitating a structured and modularized configuration design process for the product family system.The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design,while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

Model-based Predictive Control for Spatially-distributed Systems Using Dimensional Reduction Models

In this paper, a low-dimensional multiple-input and multiple-output （MIMO） model predictive control （MPC） configuration is presented for partial differential equation （PDE） unknown spatially-distributed systems （SDSs）. First, the dimension reduction with principal component analysis （PCA） is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies.

Parametric Optimization of Wheel Spoke Structure for Drag Reduction of an Ahmed Body

The wheels have a considerable influence on the aerodynamic properties and can contribute up to 25%of the total drag on modern vehicles.In this study,the effect of the wheel spoke structure on the aerodynamic performance of the isolated wheel is investigated.Subsequently,the 35°Ahmed body with an optimized spoke structure is used to analyze the flow behavior and the mechanism of drag reduction.The Fluent software is employed for this investigation,with an inlet velocity of 40 m/s.The accuracy of the numerical study is validated by comparing it with experimental results obtained from the classical Ahmed model.To gain a clearer understanding of the effects of the wheel spoke parameters on the aerodynamics of both the wheel and Ahmedmodel,and five design variables are proposed:the fillet angleα,the inside arc radius R1,the outside radius R2,and the same length of the chord L1 and L2.These variables characterize the wheel spoke structure.The Optimal Latin Hypercube designmethod is utilized to conduct the experimental design.Based on the simulation results of various wheel spoke designs,the Kriging model and the adaptive simulated annealing algorithm is selected to optimize the design parameters.The objective is to achieve the best combination for maximum drag reduction.It is indicated that the optimized spoke structure resulted in amaximum drag reduction of 5.7%and 4.7%for the drag coefficient of the isolated wheel and Ahmed body,respectively.The drag reduction is primarily attributed to changes in the flow state around the wheel,which suppressed separation bubbles.Additionally,it influenced the boundary layer thickness around the car body and reduced the turbulent kinetic energy in the wake flow.These effects collectively contributed to the observed drag reduction.

Slope analysis based on local strength reduction method and variable-modulus elasto-plastic model

Employing an ideal elasto-plastic model,the typically used strength reduction method reduced the strength of all soil elements of a slope.Therefore,this method was called the global strength reduction method(GSRM).However,the deformation field obtained by GSRM could not reflect the real deformation of a slope when the slope became unstable.For most slopes,failure occurs once the strength of some regional soil is sufficiently weakened; thus,the local strength reduction method(LSRM)was proposed to analyze slope stability.In contrast with GSRM,LSRM only reduces the strength of local soil,while the strength of other soil remains unchanged.Therefore,deformation by LSRM is more reasonable than that by GSRM.In addition,the accuracy of the slope's deformation depends on the constitutive model to a large degree,and the variable-modulus elasto-plastic model was thus adopted.This constitutive model was an improvement of the Duncan–Chang model,which modified soil's deformation modulus according to stress level,and it thus better reflected the plastic feature of soil.Most importantly,the parameters of the variable-modulus elasto-plastic model could be determined through in-situ tests,and parameters determination by plate loading test and pressuremeter test were introduced.Therefore,it is easy to put this model into practice.Finally,LSRM and the variable-modulus elasto-plastic model were used to analyze Egongdai ancient landslide.Safety factor,deformation field,and optimal reinforcement measures for Egongdai ancient landslide were obtained based on the proposed method.

Noise reduction mechanism of high-speed railway box-girder bridges installed with MTMDs on top plate

The issue of low-frequency structural noise radiated from high-speed railway(HSR) box-girder bridges(BGBs) is a significant challenge worldwide. Although it is known that vibrations in BGBs caused by moving trains can be reduced by installing multiple tuned mass dampers(MTMDs) on the top plate, there is limited research on the noise reduction achieved by this method. This study aims to investigate the noise reduction mechanism of BGBs installed with MTMDs on the top plate. A sound radiation prediction model for the BGB installed with MTMDs is developed, based on the vehicle–track–bridge coupled dynamics and acoustics boundary element method. After being verified by field tested results, the prediction model is employed to study the reduction of vibration and noise of BGBs caused by the MTMDs. It is found that installing MTMDs on top plate can significantly affect the vibration distribution and sound radiation law of BGBs. However, its impact on the sound radiation caused by vibrations dominated by the global modes of BGBs is minimal. The noise reduction achieved by MTMDs is mainly through changing the acoustic radiation contributions of each plate of the bridge. In the lower frequency range, the noise reduction of BGB caused by MTMDs can be more effective if the installation of MTMDs can modify the vibration frequency and distribution of the BGB to avoid the influence of small vibrations and disperse the sound radiation from each plate.

A Real-time Cutting Model Based on Finite Element and Order Reduction

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in real-time.Therefore,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time performance.The proposed model uses the finite element model to construct a deformation model of the virtual lung.Meanwhile,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation computation.In addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual lung.Then,the Bezier curve is adopted to draw the incision outline after the virtual lung has been cut.Finally,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual lung.Experimental results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

Maintenance decision-making method for manufacturing system based on cost and arithmetic reduction of intensity model

A cost-based selective maintenance decision-making method was presented.The purpose of this method was to find an optimal choice of maintenance actions to be performed on a selected group of machines for manufacturing systems.The arithmetic reduction of intensity model was introduced to describe the influence on machine failure intensity by different maintenance actions (preventive maintenance,minimal repair and overhaul).In the meantime,a resolution algorithm combining the greedy heuristic rules with genetic algorithm was provided.Finally,a case study of the maintenance decision-making problem of automobile workshop was given.Furthermore,the case study demonstrates the practicability of this method.

Experimental and Modeling Study on de-NO_x Characteristics of Selective Non-catalytic Reduction in O_2/CO_2 Atmosphere

An experimental study of thermal de-NOx using NH3 as reductant in 02/C02 atmosphere with the effect of S02 and different additives was performed in a drop tube furnace. Results show that the optimum temperature win- dow is 841-1184 ℃, and the optimum reaction temperature is about 900 ℃ with a de-NOx efficiency of 95.4%. A certain amount of S02 has an inhibiting effect on NO reduction. The effect of additives, including Na2C03, C2H5OH and FeCI3, on NO reduction by NH3 is also explored. The addition of Na2CO3 and FeCI3 is useful to widen the tem- perature window and shift the reaction to lower temperature for the efficiency is increased from 30.5% to 74.0% and 67.4% respectively at 800 ℃. Qualitatively, the modeling results using a detailed kinetic modeling mecha- nism represent well most of the process features. The effect of Na2CO3, C2H5OH and FeCI3 addition can be reproduced well by the Na2C03, C2H5OH and Fe（CO）5 sub-mechanism respectively. The reaction mechanism analysis shows that the effects of these additives on NO reduction are achieved mainly by promoting the produc- tion of OH radicals at lower temperature.

Design and applications of hollow‐structured nanomaterials for photocatalytic H2 evolution and CO2 reduction

Photocatalysis is considered a prospective way to alleviate the energy crisis and environmental pollution.It is therefore extremely important to design highly efficient photocatalysts for catalytic systems.In recent years,hollow‐structured materials have attracted considerable interest for application in energy conversion fields owing to their large specific surface areas,improved light absorption,and shortened charge carrier transfer path.Because they contain inner and outer surfaces,hollow‐structured materials can provide a superior platform for the deposition of other components.A number of hollow‐structured hierarchical systems have been designed and fabricated in recent decades.It is important to rationally design and construct complex hierarchical structures.In this review,general preparation approaches for hollow‐structured materials are presented,followed by a summary of the recent synthesis methods and mechanisms of typical hollow‐structured materials for applications in the photocatalytic field.Complex hollow‐structured hierarchical photocatalysts are classified into two types,hollow cocatalyst‐based and hollow host photocatalyst‐based,and the design principle and analysis of the photocatalytic reaction mechanism for photocatalytic H2 evolution and CO_(2) reduction are also introduced.The effects of hollow‐structured materials have also been investigated.This review provides a reference for the rational construction of advanced,highly efficient photocatalytic materials.

Exploring the contribution of oxygen reduction reaction to Mg corrosion by modeling assisted local analysis

Oxygen reduction reaction(ORR)has been disclosed in recent studies as a significant secondary cathodic process during magnesium corrosion.This work elaborates on the contribution of ORR to the total corrosion process of pure Mg at different impurity levels in NaCl electrolyte with the assistance of local techniques.A finite element based numerical model taking into account the contribution of ORR during the corrosion of the Mg test materials has been designed in this study considering the local oxygen concentration.Respective computational simulations were calibrated based on the experimental data and evaluated accordingly.Finally,the simultaneous monitoring of local concentration of H_(2) and O_(2),and the combined modeling study reveal the relation between ORR and hydrogen evolution reaction.