Fragile X Messenger Ribonucleoprotein 1(FMR1)gene mutations lead to fragile X syndrome,cognitive disorders,and,in some individuals,scoliosis and craniofacial abnormalities.Four-month-old(mo)male mice with deletion of ...Fragile X Messenger Ribonucleoprotein 1(FMR1)gene mutations lead to fragile X syndrome,cognitive disorders,and,in some individuals,scoliosis and craniofacial abnormalities.Four-month-old(mo)male mice with deletion of the FMR1 gene exhibit a mild increase in cortical and cancellous femoral bone mass.However,consequences of absence of FMR1 in bone of young/aged male/female mice and the cellular basis of the skeletal phenotype remain unknown.We found that absence of FMR1 results in improved bone properties with higher bone mineral density in both sexes and in 2-and 9-mo mice.The cancellous bone mass is higher only in females,whereas,cortical bone mass is higher in 2-and 9-mo males,but higher in 2-and lower in 9-mo female FMR1-knockout mice.Furthermore,male bones show higher biomechanical properties at 2mo,and females at both ages.Absence of FMR1 increases osteoblast/mineralization/bone formation and osteocyte dendricity/gene expression in vivo/ex vivo/in vitro,without affecting osteoclasts in vivo/ex vivo.Thus,FMR1 is a novel osteoblast/osteocyte differentiation inhibitor,and its absence leads to age-,site-and sex-dependent higher bone mass/strength.展开更多
In order to study omithopter flight and to improve a dynamic model of flapping propulsion, a series 0f tests are conducted on a flapping-wing blimp. The blimp is designed and constructed from mylar plastic and balsa w...In order to study omithopter flight and to improve a dynamic model of flapping propulsion, a series 0f tests are conducted on a flapping-wing blimp. The blimp is designed and constructed from mylar plastic and balsa wood as a test platform for aerodynamics and flight dynamics. The blimp, 2.3 meters long and 420 gram mass, is propelled by its flapping wings. Due to buoyancy the wings have no lift requirement so that the distinction between lift and propulsion can be analyzed in a flight platform at low flight speeds. The blimp is tested using a Vicon motion tracking system and various initial conditions are tested including accelerating flight from standstill, decelerating from an initial speed higher than its steady state, and from its steady-state speed but disturbed in pitch angle. Test results are used to estimate parameters in a coupled quasi-steady aerodynamics/Newtonian flight dynamics model. This model is then analyzed using Floquet theory to determine local dynamic modes and stability. It is concluded that the dynamic model adequately describes the vehicle＇s nonlinear behavior near the steady-state velocity and that the vehicle＇s linearized modes are akin to those of a fixed-wing aircraft.展开更多
We propose a theoretical model for spatial variations of the temperature varianceσ2(z,r)(z is the dis-tance from the sample bottom and r the radial coordinate)in turbulent Rayleigh-Bénard convection(RBC).Adaptin...We propose a theoretical model for spatial variations of the temperature varianceσ2(z,r)(z is the dis-tance from the sample bottom and r the radial coordinate)in turbulent Rayleigh-Bénard convection(RBC).Adapting the“attached-eddy”modelofshearflowtothe plumesofRBC,wederivedanequationforσ2 which is based on the universal scaling of the normalized RBC temperature spectra.This equation in-cludes both logarithmic and power-law dependences on z/λth,whereλth is the thermal boundary layer thickness.The equation parameters depend on r and the Prandtl number Pr,but have only an extremelyweak dependence on the Rayleigh number Ra Thus our model provides a near-universal equation for thetemperature variance profile in turbulent RBC.展开更多
The parametric surrogate models for partial differential equations(PDEs)are a necessary component for many applications in computational sciences,and the convolutional neural networks(CNNs)have proven to be an excelle...The parametric surrogate models for partial differential equations(PDEs)are a necessary component for many applications in computational sciences,and the convolutional neural networks(CNNs)have proven to be an excellent tool to generate these surrogates when parametric fields are present.CNNs are commonly trained on labeled data based on one-to-one sets of parameter-input and PDE-output fields.Recently,residual-based deep convolutional physics-informed neural network(DCPINN)solvers for parametric PDEs have been proposed to build surrogates without the need for labeled data.These allow for the generation of surrogates without an expensive offline-phase.In this work,we present an alternative formulation termed deep convolutional Ritz method(DCRM)as a parametric PDE solver.The approach is based on the minimization of energy functionals,which lowers the order of the differential operators compared to residualbased methods.Based on studies involving the Poisson equation with a spatially parameterized source term and boundary conditions,we find that CNNs trained on labeled data outperform DCPINNs in convergence speed and generalization abilities.The surrogates generated from the DCRM,however,converge significantly faster than their DCPINN counterparts,and prove to generalize faster and better than the surrogates obtained from both CNNs trained on labeled data and DCPINNs.This hints that the DCRM could make PDE solution surrogates trained without labeled data possibly.展开更多
Osteoarthritis(OA)of the knee joint is a degenerative disease initiated by mechanical stress that affects millions of individuals.The disease manifests as joint damage and synovial inflammation.Post-traumatic osteoart...Osteoarthritis(OA)of the knee joint is a degenerative disease initiated by mechanical stress that affects millions of individuals.The disease manifests as joint damage and synovial inflammation.Post-traumatic osteoarthritis(PTOA)is a specific form of OA caused by mechanical trauma to the joint.The progression of PTOA is prevented by immediate post-injury therapeutic intervention.Intra-articular injection of anti-inflammatory therapeutics(e.g.corticosteroids)is a common treatment option for OA before end-stage surgical intervention.However,the efficacy of intra-articular injection is limited due to poor drug retention time in the joint space and the variable efficacy of corticosteroids.Here,we endeavored to characterize a four-arm maleimide-functionalized polyethylene glycol(PEG-4MAL)hydrogel system as a‘mechanical pillow’to cushion the load-bearing joint,withstand repetitive loading and improve the efficacy of intra-articular injections of nanoparticles containing dexamethasone,an anti-inflammatory agent.PEG-4MAL hydrogels maintained their mechanical properties after physiologically relevant cyclic compression and released therapeutic payload in an on-demand manner under in vitro inflammatory conditions.Importantly,the on-demand hydrogels did not release nanoparticles under repetitive mechanical loading as experienced by daily walking.Although dexamethasone had minimal protective effects on OA-like pathology in our studies,the PEG-4MAL hydrogel functioned as a mechanical pillow to protect the knee joint from cartilage degradation and inhibit osteophyte formation in an in vivo load-induced OA mouse model.展开更多
Adhesive hydrogels have been recently proposed as a potential option to seal and treat gastric perforation(GP)which causes high mortality despite advancements in surgical treatments.However,to be effective,the hydroge...Adhesive hydrogels have been recently proposed as a potential option to seal and treat gastric perforation(GP)which causes high mortality despite advancements in surgical treatments.However,to be effective,the hydrogels must have sufficient tissue adhesiveness,tough mechanical property,tunable biodegradability and ideally are easy to apply and form.Herein,we report an adhesive and resilient hydrogel for the sealing and treatment of gastric perforation.The hydrogel consists of a bioactive,transglutaminase(TG)-crosslinked gelatin network and a dynamic,borate-crosslinked poly-N-[Tris(hydroxymethyl)methyl]acrylamide(PTH)network.The hydrogel can be formed in situ,facilitating easy delivery to the GP and allowing for precise sealing of the defects.In vivo experiments,using a perforated stomach mouse model,shows that the adhesive hydrogel plug effectively seals GP defects and promotes gastric mucosa regeneration.Overall,this hydrogel represents a promising biomaterial for GP treatment.展开更多
A data-driven model reduction strategy is presented for the representation of random polycrystal microstructures.Given a set of microstructure snapshots that satisfy certain statistical constraints such as given low-o...A data-driven model reduction strategy is presented for the representation of random polycrystal microstructures.Given a set of microstructure snapshots that satisfy certain statistical constraints such as given low-order moments of the grain size distribution,using a non-linear manifold learning approach,we identify the intrinsic low-dimensionality of the microstructure manifold.In addition to grain size,a linear dimensionality reduction technique(Karhunun-Lo´eve Expansion)is used to reduce the texture representation.The space of viable microstructures is mapped to a low-dimensional region thus facilitating the analysis and design of polycrystal microstructures.This methodology allows us to sample microstructure features in the reduced-order space thus making it a highly efficient,low-dimensional surrogate for representing microstructures(grain size and texture).We demonstrate the model reduction approach by computing the variability of homogenized thermal properties using sparse grid collocation in the reduced-order space that describes the grain size and orientation variability.展开更多
We introduce an ultrasound elastography method for examining the ACL. It consisted of imaging the distal ACL while applying a drawer test and analyzing the resulting displacement and strain maps, where a map refers to...We introduce an ultrasound elastography method for examining the ACL. It consisted of imaging the distal ACL while applying a drawer test and analyzing the resulting displacement and strain maps, where a map refers to how a variable is distributed spatially throughout an image. Our method was applied to healthy knees of cadaveric sheep to determine whether 1) our method can consistently generate displacements and strain maps in healthy ACLs;2) displacement and strain maps are repeatable;and 3) healthy ACLs experience similar maps. We found that our method could consistently provide displacements and strain maps of the distal ACL region. Moreover, these ACLs experienced displacement and strain maps that were positively-correlated between trials, knees, and specimens. This correlation was statistically significant between pairs of trials and between left and right knees (p < 0.05). These results suggest that the maps are indeed repeatable and similar for healthy ACLs.展开更多
A turbulent flow is maintained by an external supply of kinetic gradients. The scale at which energy is supplied greatly differs energy, which is eventually dissipated into heat at steep velocity from the scale at whi...A turbulent flow is maintained by an external supply of kinetic gradients. The scale at which energy is supplied greatly differs energy, which is eventually dissipated into heat at steep velocity from the scale at which energy is dissipated, the more so as the turbulent intensity （the Reynolds number） is larger. The resulting energy flux over the range of scales, intermediate between energy injection and dissipation, acts as a source of time irreversibility. As it is now possible to follow accurately fluid particles in a turbulent flow field, both from laboratory experiments and from numerical simulations, a natural question arises： how do we detect time irreversibility from these Lagrangian data？ Here we discuss recent results concerning this problem. For Lagrangian statistics involving more than one fluid particle, the distance between fluid particles introduces an intrinsic length scale into the problem. The evolution of quantities dependent on the relative motion between these fluid particles, including the kinetic energy in the relative motion, or the configuration of an initially isotropic structure can be related to the equal-time correlation functions of the velocity field, and is therefore sensitive to the energy flux through scales, hence to the irreversibility of the flow. In contrast, for single- particle Lagrangian statistics, the most often studied velocity structure functions cannot distinguish the ＂arrow of time＂. Recent observations from experimental and numerical simulation data, however, show that the change of kinetic energy following the particle motion, is sensitive to time-reversal. We end the survey with a brief discussion of the implication of this line of work.展开更多
Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulat...Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulation and comfort,the opposite is desirable,namely,increasing the fabric pore size under increasing humid and sweating conditions for enhanced ventila-tion and cooling,and a decreased pore size under cold and dry conditions for heat retention.This paper describes a novel approach to create such an unconventional fabric by emulating the structure of the plant leaf stomata by designing a water responsive polymer system in which the fabric pores increase in size when wet and decrease in size when dry.The new fabric increases its moisture permeability over 50%under wet conditions.Such a water responsive fabric can find various applications including smart functional clothing and sportswear.展开更多
橡胶类材料存在着超弹性、时间相关性、率相关性和渐进损伤行为.作者之前的工作提出了一种超弹性损伤模型去描述软材料的应变软化行为(Lu et al.,2020).模型在单根分子链应变能函数中引入损伤变量D,然后将宏观变形和单链分子的伸长率联...橡胶类材料存在着超弹性、时间相关性、率相关性和渐进损伤行为.作者之前的工作提出了一种超弹性损伤模型去描述软材料的应变软化行为(Lu et al.,2020).模型在单根分子链应变能函数中引入损伤变量D,然后将宏观变形和单链分子的伸长率联系在一起.本文改进了之前的模型,通过引入以Prony级数为基础的非线性黏弹性理论使得模型可以表征时间相关黏性效应.本文进一步将建立的有限变形黏-超弹性损伤本构模型在有限元软件ABAQUS中通过用户自定义子程序UMAT实现.本文利用文献中丙烯酸聚合物在单轴拉伸下的实验数据来校准本构模型的10个参数:包括4个弹性参数和6个黏性参数.利用ABAQUS模拟丙烯酸聚合物复杂几何形状试样的单轴拉伸和应力松弛,仿真结果与实验数据一致性较好.展开更多
This work reports a three-dimensional polymer interdigitated pillar electrostatic actuator that can produce force densities 5-10×higher than those of biological muscles.The theory of operation,scaling,and stabili...This work reports a three-dimensional polymer interdigitated pillar electrostatic actuator that can produce force densities 5-10×higher than those of biological muscles.The theory of operation,scaling,and stability is investigated using analytical and FEM models.The actuator consists of two high-density arrays of interdigitated pillars that work against a restoring force generated by an integrated flexure spring.The actuator architecture enables linear actuation with higher displacements and pull-in free actuation to prevent the in-use stiction associated with other electrostatic actuators.The pillars and springs are 3D printed together in the same structure.The pillars are coated with a gold-palladium alloy layer to form conductive electrodes.The space between the pillars is filled with liquid dielectrics for higher breakdown voltages and larger electrostatic forces due to the increase in the dielectric constant.We demonstrated a prototype actuator that produced a maximum work density of 54.6μJ/cc and an electrical-tomechanical energy coupling factor of 32%when actuated at 4000 V.The device was operated for more than 100,000 cycles with no degradation in displacements.The flexible polymer body was robust,allowing the actuator to operate even after high mechanical force impact,which was demonstrated by operation after drop tests.As it is scaled further,the reported actuator will enable soft and flexible muscle-like actuators that can be stacked in series and parallel to scale the resulting forces.This work paves the way for high-energy density actuators for microrobotic applications.展开更多
We develop an efficient,adaptive locally weighted projection regression(ALWPR)framework for uncertainty quantification(UQ)of systems governed by ordinary and partial differential equations.The algorithm adaptively sel...We develop an efficient,adaptive locally weighted projection regression(ALWPR)framework for uncertainty quantification(UQ)of systems governed by ordinary and partial differential equations.The algorithm adaptively selects the new input points with the largest predictive variance and decides when and where to add new localmodels.It effectively learns the local features and accurately quantifies the uncertainty in the prediction of the statistics.The developed methodology provides predictions and confidence intervals at any query input and can dealwithmulti-output cases.Numerical examples are presented to show the accuracy and efficiency of the ALWPR framework including problems with non-smooth local features such as discontinuities in the stochastic space.展开更多
基金supported by the National Institutes of Health R01-AR053643Veterans Research Administration Merit Award I01BX00515+7 种基金a Research Support Funds Grant(RSFG),Indiana University Purdue University Indianapolis-Office of the Vice Chancellor for Research,Indianapolis to LIP.supported by ASBMR Fund for Research and Education Research and Collaborative Grant Programsupported by the National Institutes of Health R01AG067997 to CJHsupported by the IUPUI Diversity Scholars Research Program(DSRP)Diversity Summer Undergraduate Research Opportunity Program(DS-UROP)Indiana CTSI Student Summer Research ProgramIUPUI work study programsupported by the Life Health Science Internship(LHSI)。
文摘Fragile X Messenger Ribonucleoprotein 1(FMR1)gene mutations lead to fragile X syndrome,cognitive disorders,and,in some individuals,scoliosis and craniofacial abnormalities.Four-month-old(mo)male mice with deletion of the FMR1 gene exhibit a mild increase in cortical and cancellous femoral bone mass.However,consequences of absence of FMR1 in bone of young/aged male/female mice and the cellular basis of the skeletal phenotype remain unknown.We found that absence of FMR1 results in improved bone properties with higher bone mineral density in both sexes and in 2-and 9-mo mice.The cancellous bone mass is higher only in females,whereas,cortical bone mass is higher in 2-and 9-mo males,but higher in 2-and lower in 9-mo female FMR1-knockout mice.Furthermore,male bones show higher biomechanical properties at 2mo,and females at both ages.Absence of FMR1 increases osteoblast/mineralization/bone formation and osteocyte dendricity/gene expression in vivo/ex vivo/in vitro,without affecting osteoclasts in vivo/ex vivo.Thus,FMR1 is a novel osteoblast/osteocyte differentiation inhibitor,and its absence leads to age-,site-and sex-dependent higher bone mass/strength.
文摘In order to study omithopter flight and to improve a dynamic model of flapping propulsion, a series 0f tests are conducted on a flapping-wing blimp. The blimp is designed and constructed from mylar plastic and balsa wood as a test platform for aerodynamics and flight dynamics. The blimp, 2.3 meters long and 420 gram mass, is propelled by its flapping wings. Due to buoyancy the wings have no lift requirement so that the distinction between lift and propulsion can be analyzed in a flight platform at low flight speeds. The blimp is tested using a Vicon motion tracking system and various initial conditions are tested including accelerating flight from standstill, decelerating from an initial speed higher than its steady state, and from its steady-state speed but disturbed in pitch angle. Test results are used to estimate parameters in a coupled quasi-steady aerodynamics/Newtonian flight dynamics model. This model is then analyzed using Floquet theory to determine local dynamic modes and stability. It is concluded that the dynamic model adequately describes the vehicle＇s nonlinear behavior near the steady-state velocity and that the vehicle＇s linearized modes are akin to those of a fixed-wing aircraft.
基金the National Natural Science Foundation of China(Grants 11772111 and91952101)the Max Planck Partner Group.
文摘We propose a theoretical model for spatial variations of the temperature varianceσ2(z,r)(z is the dis-tance from the sample bottom and r the radial coordinate)in turbulent Rayleigh-Bénard convection(RBC).Adapting the“attached-eddy”modelofshearflowtothe plumesofRBC,wederivedanequationforσ2 which is based on the universal scaling of the normalized RBC temperature spectra.This equation in-cludes both logarithmic and power-law dependences on z/λth,whereλth is the thermal boundary layer thickness.The equation parameters depend on r and the Prandtl number Pr,but have only an extremelyweak dependence on the Rayleigh number Ra Thus our model provides a near-universal equation for thetemperature variance profile in turbulent RBC.
基金supported by the Laboratory Directed Research and Development Program at Sandia National Laboratories(No.218328)。
文摘The parametric surrogate models for partial differential equations(PDEs)are a necessary component for many applications in computational sciences,and the convolutional neural networks(CNNs)have proven to be an excellent tool to generate these surrogates when parametric fields are present.CNNs are commonly trained on labeled data based on one-to-one sets of parameter-input and PDE-output fields.Recently,residual-based deep convolutional physics-informed neural network(DCPINN)solvers for parametric PDEs have been proposed to build surrogates without the need for labeled data.These allow for the generation of surrogates without an expensive offline-phase.In this work,we present an alternative formulation termed deep convolutional Ritz method(DCRM)as a parametric PDE solver.The approach is based on the minimization of energy functionals,which lowers the order of the differential operators compared to residualbased methods.Based on studies involving the Poisson equation with a spatially parameterized source term and boundary conditions,we find that CNNs trained on labeled data outperform DCPINNs in convergence speed and generalization abilities.The surrogates generated from the DCRM,however,converge significantly faster than their DCPINN counterparts,and prove to generalize faster and better than the surrogates obtained from both CNNs trained on labeled data and DCPINNs.This hints that the DCRM could make PDE solution surrogates trained without labeled data possibly.
基金the National Institutes of Health[R01-AI132738-01A1 awarded to A.S.,R21-AR064034 awarded to M.C.H.v.d.M.]the National Science Foundation CAREER award[DMR-1554275 awarded to A.S.]+2 种基金3M Non-Tenured Faculty Award(awarded to A.S.),Cornell CCMR[NSF DMR-1719875]Cornell Sloan and Colman Diversity Fellowships(awarded to T.A.W.)GAANN Fellowship(awarded to D.T.H.).
文摘Osteoarthritis(OA)of the knee joint is a degenerative disease initiated by mechanical stress that affects millions of individuals.The disease manifests as joint damage and synovial inflammation.Post-traumatic osteoarthritis(PTOA)is a specific form of OA caused by mechanical trauma to the joint.The progression of PTOA is prevented by immediate post-injury therapeutic intervention.Intra-articular injection of anti-inflammatory therapeutics(e.g.corticosteroids)is a common treatment option for OA before end-stage surgical intervention.However,the efficacy of intra-articular injection is limited due to poor drug retention time in the joint space and the variable efficacy of corticosteroids.Here,we endeavored to characterize a four-arm maleimide-functionalized polyethylene glycol(PEG-4MAL)hydrogel system as a‘mechanical pillow’to cushion the load-bearing joint,withstand repetitive loading and improve the efficacy of intra-articular injections of nanoparticles containing dexamethasone,an anti-inflammatory agent.PEG-4MAL hydrogels maintained their mechanical properties after physiologically relevant cyclic compression and released therapeutic payload in an on-demand manner under in vitro inflammatory conditions.Importantly,the on-demand hydrogels did not release nanoparticles under repetitive mechanical loading as experienced by daily walking.Although dexamethasone had minimal protective effects on OA-like pathology in our studies,the PEG-4MAL hydrogel functioned as a mechanical pillow to protect the knee joint from cartilage degradation and inhibit osteophyte formation in an in vivo load-induced OA mouse model.
基金partially supported by the Novo Nordisk Company,the Juvenile Diabetes Research Foundation(JDRF,2-SRA-2018-472-S-B)the Hartwell Foundationthe Cornell Center for Materials Research Shared Facilities which are supported through the NSF MRSEC program(DMR-1719875).
文摘Adhesive hydrogels have been recently proposed as a potential option to seal and treat gastric perforation(GP)which causes high mortality despite advancements in surgical treatments.However,to be effective,the hydrogels must have sufficient tissue adhesiveness,tough mechanical property,tunable biodegradability and ideally are easy to apply and form.Herein,we report an adhesive and resilient hydrogel for the sealing and treatment of gastric perforation.The hydrogel consists of a bioactive,transglutaminase(TG)-crosslinked gelatin network and a dynamic,borate-crosslinked poly-N-[Tris(hydroxymethyl)methyl]acrylamide(PTH)network.The hydrogel can be formed in situ,facilitating easy delivery to the GP and allowing for precise sealing of the defects.In vivo experiments,using a perforated stomach mouse model,shows that the adhesive hydrogel plug effectively seals GP defects and promotes gastric mucosa regeneration.Overall,this hydrogel represents a promising biomaterial for GP treatment.
基金support from the Computational Mathematics program of AFOSR(grant F49620-00-1-0373),the DOE Office of Science ASCR(award DE-SC0004910)the Materials Design and Surface Engineering program of the NSF(award CMMI-0757824)+1 种基金the Mechanical Behavior of Materials program Army Research Office(proposal to Cornell University No.W911NF0710519)an OSD/AFOSR MURI09 award to Cornell University on uncertainty quantification.
文摘A data-driven model reduction strategy is presented for the representation of random polycrystal microstructures.Given a set of microstructure snapshots that satisfy certain statistical constraints such as given low-order moments of the grain size distribution,using a non-linear manifold learning approach,we identify the intrinsic low-dimensionality of the microstructure manifold.In addition to grain size,a linear dimensionality reduction technique(Karhunun-Lo´eve Expansion)is used to reduce the texture representation.The space of viable microstructures is mapped to a low-dimensional region thus facilitating the analysis and design of polycrystal microstructures.This methodology allows us to sample microstructure features in the reduced-order space thus making it a highly efficient,low-dimensional surrogate for representing microstructures(grain size and texture).We demonstrate the model reduction approach by computing the variability of homogenized thermal properties using sparse grid collocation in the reduced-order space that describes the grain size and orientation variability.
文摘We introduce an ultrasound elastography method for examining the ACL. It consisted of imaging the distal ACL while applying a drawer test and analyzing the resulting displacement and strain maps, where a map refers to how a variable is distributed spatially throughout an image. Our method was applied to healthy knees of cadaveric sheep to determine whether 1) our method can consistently generate displacements and strain maps in healthy ACLs;2) displacement and strain maps are repeatable;and 3) healthy ACLs experience similar maps. We found that our method could consistently provide displacements and strain maps of the distal ACL region. Moreover, these ACLs experienced displacement and strain maps that were positively-correlated between trials, knees, and specimens. This correlation was statistically significant between pairs of trials and between left and right knees (p < 0.05). These results suggest that the maps are indeed repeatable and similar for healthy ACLs.
基金grateful to the Max Planck Society for continuous support to our research.financial support from ANR(contract TEC 2),the Alexander von Humboldt Foundation,and the PSMN at the Ecole Normale Sup′erieure de Lyon
文摘A turbulent flow is maintained by an external supply of kinetic gradients. The scale at which energy is supplied greatly differs energy, which is eventually dissipated into heat at steep velocity from the scale at which energy is dissipated, the more so as the turbulent intensity （the Reynolds number） is larger. The resulting energy flux over the range of scales, intermediate between energy injection and dissipation, acts as a source of time irreversibility. As it is now possible to follow accurately fluid particles in a turbulent flow field, both from laboratory experiments and from numerical simulations, a natural question arises： how do we detect time irreversibility from these Lagrangian data？ Here we discuss recent results concerning this problem. For Lagrangian statistics involving more than one fluid particle, the distance between fluid particles introduces an intrinsic length scale into the problem. The evolution of quantities dependent on the relative motion between these fluid particles, including the kinetic energy in the relative motion, or the configuration of an initially isotropic structure can be related to the equal-time correlation functions of the velocity field, and is therefore sensitive to the energy flux through scales, hence to the irreversibility of the flow. In contrast, for single- particle Lagrangian statistics, the most often studied velocity structure functions cannot distinguish the ＂arrow of time＂. Recent observations from experimental and numerical simulation data, however, show that the change of kinetic energy following the particle motion, is sensitive to time-reversal. We end the survey with a brief discussion of the implication of this line of work.
基金supported by Prof.Fan’s Faculty Startup Fund of the College of Human Ecology,Cornell Universitysupported by the National Science Foundation under Award Number DMR-1719875acknowledge Dr.Xia Zeng for equipment guidance and support,Charles V.Beach and Vincent Chicone for their assistance with the mask fabrication.Finally,the PI,Prof.Fan would like to acknowledge the funding support of RGC GRF project#15213920 and Hong Kong Polytechnic University Project of Strategic Importance#ZE1H for further analysis of the experimental data and improvement of the manuscript.
文摘Due to fiber swelling,textile fabrics containing hygroscopic fibers tend to decrease pore size under wet or increasing humid-ity and moisture conditions,the reverse being true.Nevertheless,for personal thermal regulation and comfort,the opposite is desirable,namely,increasing the fabric pore size under increasing humid and sweating conditions for enhanced ventila-tion and cooling,and a decreased pore size under cold and dry conditions for heat retention.This paper describes a novel approach to create such an unconventional fabric by emulating the structure of the plant leaf stomata by designing a water responsive polymer system in which the fabric pores increase in size when wet and decrease in size when dry.The new fabric increases its moisture permeability over 50%under wet conditions.Such a water responsive fabric can find various applications including smart functional clothing and sportswear.
基金This work was supported by the National Natural Science Foundation of China(Grant No.11922210).
文摘橡胶类材料存在着超弹性、时间相关性、率相关性和渐进损伤行为.作者之前的工作提出了一种超弹性损伤模型去描述软材料的应变软化行为(Lu et al.,2020).模型在单根分子链应变能函数中引入损伤变量D,然后将宏观变形和单链分子的伸长率联系在一起.本文改进了之前的模型,通过引入以Prony级数为基础的非线性黏弹性理论使得模型可以表征时间相关黏性效应.本文进一步将建立的有限变形黏-超弹性损伤本构模型在有限元软件ABAQUS中通过用户自定义子程序UMAT实现.本文利用文献中丙烯酸聚合物在单轴拉伸下的实验数据来校准本构模型的10个参数:包括4个弹性参数和6个黏性参数.利用ABAQUS模拟丙烯酸聚合物复杂几何形状试样的单轴拉伸和应力松弛,仿真结果与实验数据一致性较好.
基金This work was supported by the DARPA SHRIMP program.This work was performed in part at the Cornell NanoScale Facility,a member of the National Nanotechnology Coordinated Infrastructure(NNCI),which is supported by the National Science Foundation(Grant NNCI-2025233).
文摘This work reports a three-dimensional polymer interdigitated pillar electrostatic actuator that can produce force densities 5-10×higher than those of biological muscles.The theory of operation,scaling,and stability is investigated using analytical and FEM models.The actuator consists of two high-density arrays of interdigitated pillars that work against a restoring force generated by an integrated flexure spring.The actuator architecture enables linear actuation with higher displacements and pull-in free actuation to prevent the in-use stiction associated with other electrostatic actuators.The pillars and springs are 3D printed together in the same structure.The pillars are coated with a gold-palladium alloy layer to form conductive electrodes.The space between the pillars is filled with liquid dielectrics for higher breakdown voltages and larger electrostatic forces due to the increase in the dielectric constant.We demonstrated a prototype actuator that produced a maximum work density of 54.6μJ/cc and an electrical-tomechanical energy coupling factor of 32%when actuated at 4000 V.The device was operated for more than 100,000 cycles with no degradation in displacements.The flexible polymer body was robust,allowing the actuator to operate even after high mechanical force impact,which was demonstrated by operation after drop tests.As it is scaled further,the reported actuator will enable soft and flexible muscle-like actuators that can be stacked in series and parallel to scale the resulting forces.This work paves the way for high-energy density actuators for microrobotic applications.
文摘We develop an efficient,adaptive locally weighted projection regression(ALWPR)framework for uncertainty quantification(UQ)of systems governed by ordinary and partial differential equations.The algorithm adaptively selects the new input points with the largest predictive variance and decides when and where to add new localmodels.It effectively learns the local features and accurately quantifies the uncertainty in the prediction of the statistics.The developed methodology provides predictions and confidence intervals at any query input and can dealwithmulti-output cases.Numerical examples are presented to show the accuracy and efficiency of the ALWPR framework including problems with non-smooth local features such as discontinuities in the stochastic space.
