Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins

This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for visualization.To implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic algorithm.Transient thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical insulation.An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP.Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT.Moreover,manufacturability was verified based on a thermal-solid coupled finite element analysis.The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

A Research Review on the Key Technologies of Intelligent Design for Customized Products

The development of technologies such as big data and cyber-physical systems （CPSs） has increased the demand for product design. Product digital design involves completing the product design process using advanced digital technologies such as geometry modeling, kinematic and dynamic simulation, multi- disciplinary coupling, virtual assembly, virtual reality （VR）, multi-objective optimization （MOO）, and human-computer interaction. The key technologies of intelligent design for customized products include： a description and analysis of customer requirements （CRs）, product family design （PFD） for the customer base, configuration and modular design for customized products, variant design for customized products, and a knowledge push for product intelligent design. The development trends in intelligent design for customized products include big-data-driven intelligent design technology for customized products and customized design tools and applications. The proposed method is verified by the design of precision computer numerical control （CNC） machine tools.

Catalytic carbon dioxide hydrogenation to methane: A review of recent studies

Recently, various efforts have been put forward on the development of technologies for the synthesis of methane from CO2 and H-2, since it can offer a solution for renewable H-2 storage and transportation. In parallel, this reaction is considered to be a critical step in reclaiming oxygen within a closed cycle. Over the years, extensive fundamental research works on CO2 methanation have been investigated and reported in the literatures. In this updated review, we present a comprehensive overview of recent publications during the last 3 years. Various aspects on this reaction system are described in detail, such as thermodynamic considerations, catalyst innovations, the influence of reaction conditions, overall catalytic performance, and reaction mechanism. Finally, the future development of CO2 methanation is discussed. (C) 2016 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. and Science Press. All rights reserved.

CO_2 methanation over TiO_2–Al_2O_3 binary oxides supported Ru catalysts

TiO_2 modified Al_2O_3 binary oxide was prepared by a wet-impregnation method and used as the support for ruthenium catalyst. The catalytic performance of Ru/TiO_2–Al_2O_3catalyst in CO_2 methanation reaction was investigated. Compared with Ru/Al_2O_3 catalyst, the Ru/TiO_2–Al_2O_3catalytic system exhibited a much higher activity in CO_2 methanation reaction. The reaction rate over Ru/TiO_2–Al_2O_3 was 0.59 mol CO_2·(g Ru)1·h-1, 3.1 times higher than that on Ru/Al_2O_3[0.19 mol CO_2·(gRu)-1·h-1]. The effect of TiO_2 content and TiO_2–Al_2O_3calcination temperature on catalytic performance was addressed. The corresponding structures of each catalyst were characterized by means of H_2-TPR, XRD, and TEM. Results indicated that the averaged particle size of the Ru on TiO_2–Al_2O_3support is 2.8 nm, smaller than that on Al_2O_3 support of 4.3 nm. Therefore, we conclude that the improved activity over Ru/TiO_2–Al_2O_3catalyst is originated from the smaller particle size of ruthenium resulting from a strong interaction between Ru and the rutile-TiO_2 support, which hindered the aggregation of Ru nanoparticles.

Identification of the structure of Ni active sites for ethylene oligomerization on an amorphous silica-alumina supported nickel catalyst

The structure of Ni active sites supported on amorphous silica-alumina supports with different contents of Al_(2)O_(3)loadings in relation to their activities in ethylene oligomerization were investigated.Two kinds of Ni sites were detected by in situ FTIR-CO and H_(2)-TPR experiments,that are Ni^(2+)cations as grafted on weak acidic silanols and Ni^(2+)cations at ion-exchange positions.The ethylene oligomerization activities of these Ni/ASA catalysts were found an ascending tendency as the Al_(2)O_(3)loading decreased,which could be attributed to the enriched concentration of Ni^(2+)species on acidic silanols with a weaker interaction with the amorphous silica-alumina support.These Ni^(2+)species were more easily to be evolved into Ni^(+)species,which has been identified to be the active sites of ethylene oligomerization.Thus,it seems reasonable to conclude that Ni^(2+)species grafted on acidic silanols were the precursors of active sites.

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective decision making

Selective laser melting(SLM)is a unique additive manufacturing(AM)category that can be used to manufacture mechanical parts.It has been widely used in aerospace and automotive using metal or alloy powder.The build orientation is crucial in AM because it affects the as-built part,including its part accuracy,surface roughness,support structure,and build time and cost.A mechanical part is usually composed of multiple surface features.The surface features carry the production and design knowledge,which can be utilized in SLM fabrication.This study proposes a method to determine the build orientation of multi-feature mechanical parts(MFMPs)in SLM.First,the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives.Second,the estimation models of involved optimization objectives are established,and a set of alternative build orientations(ABOs)is further obtained by many-objective optimization.Lastly,a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs.The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process.Two case studies are reported to validate the proposed method with numerical results,and the effectiveness comparison is presented.Physical manufacturing is conducted to prove the performance of the proposed method.The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82,10.84,and 10.62μm,respectively.The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.

Customized Design for Ergonomic Products via Additive Manufacturing Considering Joint Biomechanics

This paper presents a customized design method for ergonomic products via additive manufacturing(AM)con-sidering joint biomechanics.An ergonomic customized design model can be built based on kinesiology involving human joint biomechanics.Manifolds of the human bone can be reconstructed from X-rays,computed tomog-raphy(CT),magnetic resonance imaging(MRI),and direct 3D scanning.The conceptual and detailed design of customized products were implemented on ergonomic shoes and insoles.A lightweight lattice structure with vari-able porosity was generated via structural topology optimization for an ergonomic customized design.Notably,the upper surface of the custom-made insole may adhere perfectly to the plantar surface of the patient,resulting in a lower peak plantar pressure.Finite element analysis(FEA)can be employed to simulate the static or dynamic biomechanical characteristics.The conceptual ergonomic products were forwarded to the machine and fabricated via AM,driven by visual digital twin techniques.The experiments proved that a customized design suitability method for wearable ergonomic products via 3D printing is specifically tailored to the rehabilitation needs of individual customers,while consuming the least cost,time,and materials.

Surface accuracy optimization of mechanical parts with multiple circular holes for additive manufacturing based on triangular fuzzy number

Surface accuracy directly affects the surface quality and performance of mechanical parts.Circular hole,especially spatial non-planar hole set is the typical feature and working surface of mechanical parts.Compared with traditional machining methods,additive manufacturing(AM)technology can decrease the surface accuracy errors of circular holes during fabrication.However,an accuracy error may still exist on the surface of circular holes fabricated by AM due to the influence of staircase effect.This study proposes a surface accuracy optimization approach for mechanical parts with multiple circular holes for AM based on triangular fuzzy number(TFN).First,the feature lines on the manifold mesh are extracted using the dihedral angle method and normal tensor voting to detect the circular holes.Second,the optimal AM part build orientation is determined using the genetic algorithm to optimize the surface accuracy of the circular holes by minimizing the weighted volumetric error of the part.Third,the corresponding weights of the circular holes are calculated with the TFN analytic hierarchy process in accordance with the surface accuracy requirements.Lastly,an improved adaptive slicing algorithm is utilized to reduce the entire build time while maintaining the forming surface accuracy of the circular holes using digital twins via virtual printing.The effectiveness of the proposed approach is experimentally validated using two mechanical models.

Performance design of a cryogenic air separation unit for variable working conditions using the lumped parameter model

Large-scale cryogenic air separation units(ASUs),which are widely used in global petrochemical and semiconductor industries,are being developed with high operating elasticity under variable working conditions.Different from discrete processes in traditional machinery manufacturing,the ASU process is continuous and involves the compression,adsorption,cooling,condensation,liquefaction,evaporation,and distillation of multiple streams.This feature indicates that thousands of technical parameters in adsorption,heat transfer,and distillation processes are correlated and merged into a large-scale complex system.A lumped parameter model(LPM)of ASU is proposed by lumping the main factors together and simplifying the secondary ones to achieve accurate and fast performance design.On the basis of material and energy conservation laws,the piecewise-lumped parameters are extracted under variable working conditions by using LPM.Takagi–Sugeno(T–S)fuzzy interval detection is recursively utilized to determine whether the critical point is detected or not by using different thresholds.Compared with the traditional method,LPM is particularly suitable for“rough first then precise”modeling by expanding the feasible domain using fuzzy intervals.With LPM,the performance of the air compressor,molecular sieve adsorber,turbo expander,main plate-fin heat exchangers,and packing column of a 100000 Nm3 O2/h large-scale ASU is enhanced to adapt to variable working conditions.The designed value of net power consumption per unit of oxygen production(kW/(Nm3 O2))is reduced by 6.45%.