Organic sheets made out of fiber-reinforced thermoplastics are able to make a crucial contribution to increase the lightweight potential of a design. They show high specific strength- and stiffness properties, good da...Organic sheets made out of fiber-reinforced thermoplastics are able to make a crucial contribution to increase the lightweight potential of a design. They show high specific strength- and stiffness properties, good damping characteristics and recycling capabilities, while being able to show a higher energy absorption capacity than comparable metal constructions. Nowadays, multi-material designs are an established way in the automotive industry to combine the benefits of metal and fiber-reinforced plastics. Currently used technologies for the joining of organic sheets and metals in large-scale production are mechanical joining technologies and adhesive technologies. Both techniques require large overlapping areas that are not required in the design of the part. Additionally, mechanical joining is usually combined with “fiber-destroying” pre-drilling and punching processes. This will disturb the force flux at the joining location by causing unwanted fiber- and inter-fiber failure and inducing critical notch stresses. Therefore, the multi-material design with fiber-reinforced thermoplastics and metals needs optimized joining techniques that don’t interrupt the force flux, so that higher loads can be induced and the full benefit of the FRP material can be used. This article focuses on the characterization of a new joining technology, based on the Cold Metal Transfer (CMT) welding process that allows joining of organic sheets and metals in a load path optimized way, with short cycle times. This is achieved by redirecting the fibers around the joining area by the insertion of a thin metal pin. The path of the fibers will be similar to paths of fibers inside structures found in nature, e.g. a knothole inside of a tree. As a result of the bionic fiber design of the joint, high joining strengths can be achieved. The increase of the joint strength compared to blind riveting was performed and proven with stainless steel and orthotropic reinforced composites in shear-tests based on the DIN EN ISO 14273. Every specimen joined with the new CMT Pin joining technology showed a higher strength than specimens joined with one blind rivet. Specimens joined with two or three pin rows show a higher strength than specimens joined with two blind rivets.展开更多
This study establishes amultiscale andmulti-material topology optimization model for thermoelastic lattice structures(TLSs)consideringmechanical and thermal loading based on the ExtendedMultiscale Finite ElementMethod...This study establishes amultiscale andmulti-material topology optimization model for thermoelastic lattice structures(TLSs)consideringmechanical and thermal loading based on the ExtendedMultiscale Finite ElementMethod(EMsFEM).The corresponding multi-material and multiscale mathematical formulation have been established with minimizing strain energy and structural mass as the objective function and constraint,respectively.The Solid Isotropic Material with Penalization(SIMP)interpolation scheme has been adopted to realize micro-scale multi-material selection of truss microstructure.The modified volume preserving Heaviside function(VPHF)is utilized to obtain a clear 0/1 material of truss microstructure.Compared with the classic topology optimization of single-material TLSs,multi-material topology optimization can get a better structural design of the TLS.The effects of temperatures,size factor,and mass fraction on optimization results have been presented and discussed in the numerical examples.展开更多
A new design technique for the long life hot forging die has been proposed. By finite element analysis, the reason .for the failure of hot forging die was analyzed and it was concluded that thermal stress is the main ...A new design technique for the long life hot forging die has been proposed. By finite element analysis, the reason .for the failure of hot forging die was analyzed and it was concluded that thermal stress is the main reason for the failure of hot forging die. Based on this conclusion, the whole hot forging die was divided into the substrate part and the heat-resistant part according to the thermal stress distribution. Moreover, the heat-resistant part was further subdivided into more zones and the material of each zone was reasonably selected to ensure that the hot forging die can work in an elastic state. When compared with the existing techniques, this design can greatly increase the service life because the use of multi-materials can alleviate the thermal stress in hot forging die.展开更多
The assimilation of functionally graded (or multi-) materials into architecture is deemed to enable the rethinking of current architectural design practice and bring back material considerations at the heart of the ea...The assimilation of functionally graded (or multi-) materials into architecture is deemed to enable the rethinking of current architectural design practice and bring back material considerations at the heart of the early design process. In response, the paper outlines a functionally graded material (FGM) design workflow that departs from standard early-stage CAD, which is typically performed via computer elements devoid of materiality. It then analyses this workflow from a theoretical perspective, namely through Edwin Hutchins’ materially anchored conceptual blending, Lambros Malafouris’ Material Engagement Theory (MET) and John Searle’s concepts of intentionality. The aim is to demonstrate that due to the superimposition of material considerations that precede and succeed the CAD operation, working with material-less entities during early-stage FGM design is not logically sustainable. Additionally, multi-materiality allows for the questioning of authorship in the design process and leads to a repositioning of agency from the subject to the locus of engagement with digital materials and their affordances.展开更多
In this paper,the thin-walled structures with lattices and stiffeners manufactured by additive manufacturing are investigated.A design method based on the multi-material topology optimization is proposed for the simul...In this paper,the thin-walled structures with lattices and stiffeners manufactured by additive manufacturing are investigated.A design method based on the multi-material topology optimization is proposed for the simultaneous layout optimization of the lattices and stiffeners in thin-walled structures.First,the representative lattice units of the selected lattices are equivalent to the virtual homogeneous materials whose effective elastic matrixes are achieved by the energy-based homogenization method.Meanwhile,the stiffeners are modelled using the solid material.Subsequently,the multi-material topology optimization formulation is established for both the virtual homogeneous materials and solid material to minimize the structural compliance under mass constraint.Thus,the optimal layout of both the lattices and stiffeners could be simultaneously attained by the optimization procedure.Two applications,the aircraft panel structure and the equipment mounting plate,are dealt with to demonstrate the detailed design procedure and reveal the effect of the proposed method.According to numerical comparisons and experimental results,the thin-walled structures with lattices and stiffeners have significant advantages over the traditional stiffened thin-walled structures and lattice sandwich structures in terms of static,dynamic and anti-instability performance.展开更多
Soft robots, inspired by the flexibility and versatility of biological organisms, have potential in a variety of applications. Recent advancements in magneto-soft robots have demonstrated their abilities to achieve pr...Soft robots, inspired by the flexibility and versatility of biological organisms, have potential in a variety of applications. Recent advancements in magneto-soft robots have demonstrated their abilities to achieve precise remote control through magnetic fields, enabling multi-modal locomotion and complex manipulation tasks. Nonetheless, two main hurdles must be overcome to advance the field: developing a multi-component substrate with embedded magnetic particles to ensure the requisite flexibility and responsiveness, and devising a cost-effective,straightforward method to program three-dimensional distributed magnetic domains without complex processing and expensive machinery. Here, we introduce a cost-effective and simple heat-assisted in-situ integrated molding fabrication method for creating magnetically driven soft robots with three-dimensional programmable magnetic domains. By synthesizing a composite material with neodymium-iron-boron(NdFeB) particles embedded in a polydimethylsiloxane(PDMS) and Ecoflex matrix(PDMS:Ecoflex = 1:2 mass ratio, 50% magnetic particle concentration), we achieved an optimized balance of flexibility, strength, and magnetic responsiveness. The proposed heat-assisted in-situ magnetic domains programming technique,performed at an experimentally optimized temperature of 120℃, resulted in a 2 times magnetization strength(9.5 mT) compared to that at 20℃(4.8 m T), reaching a saturation level comparable to a commercial magnetizer. We demonstrated the versatility of our approach through the fabrication of six kinds of robots, including two kinds of two-dimensional patterned soft robots(2D-PSR), a circular six-pole domain distribution magnetic robot(2D-CSPDMR), a quadrupedal walking magnetic soft robot(QWMSR), an object manipulation robot(OMR), and a hollow thin-walled spherical magneto-soft robot(HTWSMSR). The proposed method provides a practical solution to create highly responsive and adaptable magneto-soft robots.展开更多
Multi-material 3D sand printing has gained significant attention;however,research has mainly focused on materials and mechanisms,with limited exploration of optimizing the sand-laying process through numerical simulat...Multi-material 3D sand printing has gained significant attention;however,research has mainly focused on materials and mechanisms,with limited exploration of optimizing the sand-laying process through numerical simulations.In this study,we investigated the dynamic behavior of sand particles during a vibratory sand-laying process for multi-material additive manufacturing using discrete element simulations.The objective is to enable precise control over the amount and distribution of sand for multi-material printing.In this study,we combined experiments and simulations to calibrate the contact parameters of different sands and establish a relationship between the curing agent content and surface energy of sand particles.A model for the vibratory fall of multimaterial sand was developed to study the motion characteristics of sand particles.This allows for macro-control over the sand spreading flow and high-quality multi-material sand laying.The results show that the flow rate of falling sand increases with decreasing surface energy of the particles,wider spreader openings,and higher vibration frequencies.For silica and chromite sands,when their surface energy ranged from 0.15 to 25 J·m^(2)and0.01-0.03 J·m^(2),respectively,and the sand spreader opening was 6 mm with a vibration frequency of 500 Hz,the sand flow rates of both materials became nearly identical.However,a higher sand paving speed and height increased the scattering of sand particles outside the target area,thereby decreasing the paving quality.The results accomplished in this study enable precise and uniform sand particle deposition and offers guidelines for optimizing sand speed and height,thus expanding the application of multi-material sand 3D printing in complex and high-performance manufacturing.展开更多
The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique cha...The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI ...Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety...Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.展开更多
This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of m...This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design.The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads.The topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation model.The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function.Furthermore,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)problem.Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle.The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design variables.Finally,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.展开更多
Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in...Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.展开更多
This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with ...This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is adopted.The sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology optimization.Under dividing the design domain,the volume fraction of each preset gradient layer is extracted.Based on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient layer.The periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in sub-regions.Then,the method of moving asymptotes(MMA)is introduced to iteratively update the design variables.Several numerical examples are presented to verify the validity and applicability of the proposed method.The results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.展开更多
In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With th...In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.展开更多
Tungsten(W)and stainless steel(SS)are well known for the high melting point and good corrosion resistance respectively.Bimetallic W-SS structures would offer potential applications in extreme environments.In this stud...Tungsten(W)and stainless steel(SS)are well known for the high melting point and good corrosion resistance respectively.Bimetallic W-SS structures would offer potential applications in extreme environments.In this study,a SS→W→SS sandwich structure is fabricated via a special laser powder bed fusion(LPBF)method based on an ultrasonic-assisted powder deposition mechanism.Material characterization of the SS→W interface and W→SS interface was conducted,including microstructure,element distribution,phase distribution,and nano-hardness.A coupled modelling method,combining computational fluid dynamics modelling with discrete element method,simulated the melt pool dynamics and solidification at the material interfaces.The study shows that the interface bonding of SS→W(SS printed on W)is the combined effect of solid-state diffusion with different elemental diffusion rates and grain boundary diffusion.The keyhole mode of the melt pool at the W→SS(W printed on SS)interface makes the pre-printed SS layers repeatedly remelted,causing the liquid W to flow into the sub-surface of the pre-printed SS through the keyhole cavities realizing the bonding of the W→SS interface.The above interfacial bonding behaviours are significantly different from the previously reported bonding mechanism based on the melt pool convection during multiple material LPBF.The abnormal material interfacial bonding behaviours are reported for the first time.展开更多
文摘Organic sheets made out of fiber-reinforced thermoplastics are able to make a crucial contribution to increase the lightweight potential of a design. They show high specific strength- and stiffness properties, good damping characteristics and recycling capabilities, while being able to show a higher energy absorption capacity than comparable metal constructions. Nowadays, multi-material designs are an established way in the automotive industry to combine the benefits of metal and fiber-reinforced plastics. Currently used technologies for the joining of organic sheets and metals in large-scale production are mechanical joining technologies and adhesive technologies. Both techniques require large overlapping areas that are not required in the design of the part. Additionally, mechanical joining is usually combined with “fiber-destroying” pre-drilling and punching processes. This will disturb the force flux at the joining location by causing unwanted fiber- and inter-fiber failure and inducing critical notch stresses. Therefore, the multi-material design with fiber-reinforced thermoplastics and metals needs optimized joining techniques that don’t interrupt the force flux, so that higher loads can be induced and the full benefit of the FRP material can be used. This article focuses on the characterization of a new joining technology, based on the Cold Metal Transfer (CMT) welding process that allows joining of organic sheets and metals in a load path optimized way, with short cycle times. This is achieved by redirecting the fibers around the joining area by the insertion of a thin metal pin. The path of the fibers will be similar to paths of fibers inside structures found in nature, e.g. a knothole inside of a tree. As a result of the bionic fiber design of the joint, high joining strengths can be achieved. The increase of the joint strength compared to blind riveting was performed and proven with stainless steel and orthotropic reinforced composites in shear-tests based on the DIN EN ISO 14273. Every specimen joined with the new CMT Pin joining technology showed a higher strength than specimens joined with one blind rivet. Specimens joined with two or three pin rows show a higher strength than specimens joined with two blind rivets.
基金the National Natural Science Foundation of China(Nos.U1906233,11732004,Jun Yan,No.12002278,Zunyi Duan)the Key R&D Program of Shandong Province(2019JZZY010801,Jun Yan)the Fundamental Research Funds for the Central Universities(DUT20ZD213,DUT20LAB308,DUT21ZD209,Jun Yan,G2020KY05308,Zunyi Duan).
文摘This study establishes amultiscale andmulti-material topology optimization model for thermoelastic lattice structures(TLSs)consideringmechanical and thermal loading based on the ExtendedMultiscale Finite ElementMethod(EMsFEM).The corresponding multi-material and multiscale mathematical formulation have been established with minimizing strain energy and structural mass as the objective function and constraint,respectively.The Solid Isotropic Material with Penalization(SIMP)interpolation scheme has been adopted to realize micro-scale multi-material selection of truss microstructure.The modified volume preserving Heaviside function(VPHF)is utilized to obtain a clear 0/1 material of truss microstructure.Compared with the classic topology optimization of single-material TLSs,multi-material topology optimization can get a better structural design of the TLS.The effects of temperatures,size factor,and mass fraction on optimization results have been presented and discussed in the numerical examples.
基金the National Natural Science Foundation of China （No. 50675165）.
文摘A new design technique for the long life hot forging die has been proposed. By finite element analysis, the reason .for the failure of hot forging die was analyzed and it was concluded that thermal stress is the main reason for the failure of hot forging die. Based on this conclusion, the whole hot forging die was divided into the substrate part and the heat-resistant part according to the thermal stress distribution. Moreover, the heat-resistant part was further subdivided into more zones and the material of each zone was reasonably selected to ensure that the hot forging die can work in an elastic state. When compared with the existing techniques, this design can greatly increase the service life because the use of multi-materials can alleviate the thermal stress in hot forging die.
文摘The assimilation of functionally graded (or multi-) materials into architecture is deemed to enable the rethinking of current architectural design practice and bring back material considerations at the heart of the early design process. In response, the paper outlines a functionally graded material (FGM) design workflow that departs from standard early-stage CAD, which is typically performed via computer elements devoid of materiality. It then analyses this workflow from a theoretical perspective, namely through Edwin Hutchins’ materially anchored conceptual blending, Lambros Malafouris’ Material Engagement Theory (MET) and John Searle’s concepts of intentionality. The aim is to demonstrate that due to the superimposition of material considerations that precede and succeed the CAD operation, working with material-less entities during early-stage FGM design is not logically sustainable. Additionally, multi-materiality allows for the questioning of authorship in the design process and leads to a repositioning of agency from the subject to the locus of engagement with digital materials and their affordances.
基金supported by the National Natural Science Foundation of China(No.12172294,51735005,12032018).
文摘In this paper,the thin-walled structures with lattices and stiffeners manufactured by additive manufacturing are investigated.A design method based on the multi-material topology optimization is proposed for the simultaneous layout optimization of the lattices and stiffeners in thin-walled structures.First,the representative lattice units of the selected lattices are equivalent to the virtual homogeneous materials whose effective elastic matrixes are achieved by the energy-based homogenization method.Meanwhile,the stiffeners are modelled using the solid material.Subsequently,the multi-material topology optimization formulation is established for both the virtual homogeneous materials and solid material to minimize the structural compliance under mass constraint.Thus,the optimal layout of both the lattices and stiffeners could be simultaneously attained by the optimization procedure.Two applications,the aircraft panel structure and the equipment mounting plate,are dealt with to demonstrate the detailed design procedure and reveal the effect of the proposed method.According to numerical comparisons and experimental results,the thin-walled structures with lattices and stiffeners have significant advantages over the traditional stiffened thin-walled structures and lattice sandwich structures in terms of static,dynamic and anti-instability performance.
基金supported by National Natural Science Foundation of China(Grant Nos.62473277,62473275,62133004,52105072,and 62073230)Jiangsu Provincial Outstanding Youth Program(Grant No.BK20230072)+5 种基金National Key R&D Program of China(Grant Nos.2022YFC3802302 and 2023YFB4705600)Suzhou Industrial Foresight and Key Core Technology Project(Grant No.SYC2022044)Zhejiang Provincial Natural Science Foundation of China(Grant No.LZ24E050004)Shenzhen Polytechnic High-level Talent Start-up Project(Grant No.6023330006K)Shenzhen Science and Technology Program(Grant No.JCYJ20210324132810026)a Grant from Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems,Grants from Jiangsu QingLan Project and Jiangsu 333 high-level talents.
文摘Soft robots, inspired by the flexibility and versatility of biological organisms, have potential in a variety of applications. Recent advancements in magneto-soft robots have demonstrated their abilities to achieve precise remote control through magnetic fields, enabling multi-modal locomotion and complex manipulation tasks. Nonetheless, two main hurdles must be overcome to advance the field: developing a multi-component substrate with embedded magnetic particles to ensure the requisite flexibility and responsiveness, and devising a cost-effective,straightforward method to program three-dimensional distributed magnetic domains without complex processing and expensive machinery. Here, we introduce a cost-effective and simple heat-assisted in-situ integrated molding fabrication method for creating magnetically driven soft robots with three-dimensional programmable magnetic domains. By synthesizing a composite material with neodymium-iron-boron(NdFeB) particles embedded in a polydimethylsiloxane(PDMS) and Ecoflex matrix(PDMS:Ecoflex = 1:2 mass ratio, 50% magnetic particle concentration), we achieved an optimized balance of flexibility, strength, and magnetic responsiveness. The proposed heat-assisted in-situ magnetic domains programming technique,performed at an experimentally optimized temperature of 120℃, resulted in a 2 times magnetization strength(9.5 mT) compared to that at 20℃(4.8 m T), reaching a saturation level comparable to a commercial magnetizer. We demonstrated the versatility of our approach through the fabrication of six kinds of robots, including two kinds of two-dimensional patterned soft robots(2D-PSR), a circular six-pole domain distribution magnetic robot(2D-CSPDMR), a quadrupedal walking magnetic soft robot(QWMSR), an object manipulation robot(OMR), and a hollow thin-walled spherical magneto-soft robot(HTWSMSR). The proposed method provides a practical solution to create highly responsive and adaptable magneto-soft robots.
基金supported by the Jiangsu Provincial Basic Research Program(Natural Science Foundation)Youth Fund(Grant No.BK20230885)the International Joint Laboratory of Sustainable Manufacturing,Ministry of Education and Fundamental Research Funds for Central Universities(Grant No.NG2024012)Major Project on Fundamental Research of Aero-Engines and Gas Turbines,Ministry of Industry and Information Technology Special Project on High-Quality Development(Grant No.J2022-Ⅶ-0006-0048)。
文摘Multi-material 3D sand printing has gained significant attention;however,research has mainly focused on materials and mechanisms,with limited exploration of optimizing the sand-laying process through numerical simulations.In this study,we investigated the dynamic behavior of sand particles during a vibratory sand-laying process for multi-material additive manufacturing using discrete element simulations.The objective is to enable precise control over the amount and distribution of sand for multi-material printing.In this study,we combined experiments and simulations to calibrate the contact parameters of different sands and establish a relationship between the curing agent content and surface energy of sand particles.A model for the vibratory fall of multimaterial sand was developed to study the motion characteristics of sand particles.This allows for macro-control over the sand spreading flow and high-quality multi-material sand laying.The results show that the flow rate of falling sand increases with decreasing surface energy of the particles,wider spreader openings,and higher vibration frequencies.For silica and chromite sands,when their surface energy ranged from 0.15 to 25 J·m^(2)and0.01-0.03 J·m^(2),respectively,and the sand spreader opening was 6 mm with a vibration frequency of 500 Hz,the sand flow rates of both materials became nearly identical.However,a higher sand paving speed and height increased the scattering of sand particles outside the target area,thereby decreasing the paving quality.The results accomplished in this study enable precise and uniform sand particle deposition and offers guidelines for optimizing sand speed and height,thus expanding the application of multi-material sand 3D printing in complex and high-performance manufacturing.
基金supported by the National Natural Science Foundation of China(Grant No.52172356)the Hunan Provincial Natural Science Foundation of China(Grant No.2022JJ10012).
文摘The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
基金supported by the Hong Kong Polytechnic University(1-WZ1Y,1-W34U,4-YWER).
文摘Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
文摘Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.
基金supported by the National Natural Science Foundation of China(Grant 52175236).
文摘This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design.The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads.The topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation model.The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function.Furthermore,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)problem.Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle.The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design variables.Finally,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.
基金The project supported by the National Natural Science Foundation of China (59805001,10332010) and Key Science and Technology Research Project of Ministry of Education of China (No.104060)
文摘Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.
基金This work is supported by the Natural Science Foundation of China(Grant 51705268)China Postdoctoral Science Foundation Funded Project(Grant 2017M612191).
文摘This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is adopted.The sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology optimization.Under dividing the design domain,the volume fraction of each preset gradient layer is extracted.Based on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient layer.The periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in sub-regions.Then,the method of moving asymptotes(MMA)is introduced to iteratively update the design variables.Several numerical examples are presented to verify the validity and applicability of the proposed method.The results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.
基金the support by National Key Research and Development Program of China(2018YFA0703000)National Natural Science Foundation of China(Grant No.52105310)+1 种基金Natural Science Foundation of Zhejiang Province(Grant No.LDQ23E050001)the Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study(Grant No.SN-ZJU-SIAS-004)。
文摘In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.
基金funded by the Engineering and Physical Science Research Council(EPSRC),UK(Grant Nos.EP/P027563/1 and EP/M028267/1)the Science and Technology Facilities Council(STFC)(Grant No.ST/R006105/1)the Bridging for Innovators Programme of Department for Business,Energy and Industrial Strategy(BEIS),UK.
文摘Tungsten(W)and stainless steel(SS)are well known for the high melting point and good corrosion resistance respectively.Bimetallic W-SS structures would offer potential applications in extreme environments.In this study,a SS→W→SS sandwich structure is fabricated via a special laser powder bed fusion(LPBF)method based on an ultrasonic-assisted powder deposition mechanism.Material characterization of the SS→W interface and W→SS interface was conducted,including microstructure,element distribution,phase distribution,and nano-hardness.A coupled modelling method,combining computational fluid dynamics modelling with discrete element method,simulated the melt pool dynamics and solidification at the material interfaces.The study shows that the interface bonding of SS→W(SS printed on W)is the combined effect of solid-state diffusion with different elemental diffusion rates and grain boundary diffusion.The keyhole mode of the melt pool at the W→SS(W printed on SS)interface makes the pre-printed SS layers repeatedly remelted,causing the liquid W to flow into the sub-surface of the pre-printed SS through the keyhole cavities realizing the bonding of the W→SS interface.The above interfacial bonding behaviours are significantly different from the previously reported bonding mechanism based on the melt pool convection during multiple material LPBF.The abnormal material interfacial bonding behaviours are reported for the first time.
