Fluidization and Transport of Vibrated Granular Matter:A Review of Landmark and Recent Contributions

We present a short retrospective review of the existing literature about the dynamics of(dry)granular matter under the effect of vibrations.The main objective is the development of an integrated resource where vital information about past findings and recent discoveries is provided in a single treatment.Special attention is paid to those works where successful synthetic routes to as-yet unknown phenomena were identified.Such landmark results are analyzed,while smoothly blending them with a history of the field and introducing possible categorizations of the prevalent dynamics.Although no classification is perfect,and it is hard to distillate general properties out of specific observations or realizations,two possible ways to interpret the existing results are defined according to the type of forcing or the emerging(ensuing)regime of motion.In particular,first results concerning the case where vibrations and gravity are concurrent(vertical shaking)are examined,then the companion situation with vibrations perpendicular to gravity(horizontal shaking)is described.Universality classes are introduced as follows:(1)Regimes where sand self-organizes leading to highly regular geometrical“pulsating”patterns(thin layer case);(2)Regimes where the material undergoes“fluidization”and develops an internal multicellular convective state(tick layers case);(3)Regimes where the free interface separating the sand from the overlying gas changes inclination or develops a kind a patterned configuration consisting of stable valleys and mountains or travelling waves;(4)Regimes where segregation is produced,i.e.,particles of a given size tend to be separated from the other grains(deep containers).Where possible,an analogy or parallelism is drawn with respect to the companion field of fluid-dynamics for which the assumption of“continuum”can be applied.

Unexpected divergence in magnetoreceptor MagR from robin and pigeon linked to two sequence variations

Birds exhibit extraordinary mobility and remarkable navigational skills,obtaining guidance cues from the Earth’s magnetic field for orientation and long-distance movement.Bird species also show tremendous diversity in navigation strategies,with considerable differences even within the same taxa and among individuals from the same population.The highly conserved iron and iron-sulfur cluster binding magnetoreceptor(MagR)protein is suggested to enable animals,including birds,to detect the geomagnetic field and navigate accordingly.Notably,MagR is also implicated in other functions,such as electron transfer and biogenesis of iron-sulfur clusters,raising the question of whether variability exists in its biochemical and biophysical features among species,particularly birds.In the current study,we conducted a comparative analysis of MagR from two different bird species,including the migratory European robin(Erithacus rubecula)and the homing pigeon(Columba livia).Sequence alignment revealed an extremely high degree of similarity between the MagRs of these species,with only three sequence variations.Nevertheless,two of these variations underpinned significant differences in metal binding capacity,oligomeric state,and magnetic properties.These findings offer compelling evidence for the marked differences in MagR between the two avian species,potentially explaining how a highly conserved protein can mediate such diverse functions.

Comparative Study on Results of Euler,Improved Euler and Run­ge-Kutta Methods for Solving the Engineering Unknown Problems

The paper presents the comparative study on numerical methods of Euler method,Improved Euler method and fourth-order Runge-Kutta method for solving the engineering problems and applications.The three proposed methods are quite efficient and practically well suited for solving the unknown engineering problems.This paper aims to enhance the teaching and learning quality of teachers and students for various levels.At each point of the interval,the value of y is calculated and compared with its exact value at that point.The next interesting point is the observation of error from those methods.Error in the value of y is the difference between calculated and exact value.A mathematical equation which relates various functions with its derivatives is known as a differential equation.It is a popular field of mathematics because of its application to real-world problems.To calculate the exact values,the approximate values and the errors,the numerical tool such as MATLAB is appropriate for observing the results.This paper mainly concentrates on identifying the method which provides more accurate results.Then the analytical results and calculates their corresponding error were compared in details.The minimum error directly reflected to realize the best method from different numerical methods.According to the analyses from those three approaches,we observed that only the error is nominal for the fourth-order Runge-Kutta method.

考虑过阻尼模态参与的改进复模态叠加法

为处理非比例阻尼系统可能出现的过阻尼模态,提出了一种改进的复模态叠加强迫振动分析方法,建议无论模态是否过阻尼,复模态振动分析时应成对使用复模态.以一个连接任意布置外部阻尼器的悬臂梁典型非比例阻尼系统为例,其第1阶模态会随阻尼系数的增加而过阻尼.在厘清复模态响应与实际动力响应关系的基础上阐述了采用改进复模态叠加法获得时域响应、传递函数和方差的完整理论方法.将方程分为实部和虚部,使得原复数域运动方程成为基于实数矩阵的增广状态空间方程,从而克服了采用复数矩阵计算时变响应的困难.此外,针对基于白噪声滤波的外部激励,提出了一种高效方差响应评估方法,降低了计算资源消耗.结果表明,相较于假设模态法,复模态叠加法的结果更接近于有限元结果.基于遍历法研究最优阻尼器参数和位置时,采用多个小阻尼阻尼器优于单个大阻尼阻尼器.

Deep Learning Applied to Computational Mechanics:A Comprehensive Review,State of the Art,and the Classics

Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.

Numerical simulation and printability analysis of fused deposition modeling with dual-temperature control

Ideal tissue engineering scaffolds need interconnected pores and high porosity to enable cell survival,migration,proliferation,and differentiation.However,obtaining a high-resolution structure is difficult with traditional one-temperature control fused deposition modeling(FDM).In this study,we propose a dual-temperature control method to improve printability.A numerical model is developed in which the viscosity is a function of temperature and shear rate to study the influence of two different temperature control modes.Quantitative tests are used to assess filament formation and shape fidelity,including one-dimensional filament printing,deposition at corners,fusion,and collapse.By using dual-temperature control,the width of the deposited poly(ε-caprolactone)filament is reduced to 50μm.The comparative results of both the experimental method and numerical simulation suggest that the dual-temperature control FDM can manufacture spatially arranged constructs and presents a promising application in tissue engineering。

Graph-based structural joint pose estimation in non-line-of-sight conditions

In post-earthquake surveys,it is difficult(and often infeasible)to observe and quantify displacements beyond line-of-sight(LOS),given seismic force-resisting and gravity systems exist completely or partially within a building′s enclosure.To overcome this limitation,we develop a novel framework that generalizes graph-based state estimation towards structural joint localization via engineered landmarks.These landmarks provide an indirect means to estimate residual displacements where direct LOS is unavailable.Within our framework,engineered landmarks define topologies of uniquely identifiable landmarks that are either visible or non-visible to a robot performing simultaneous localization and mapping(SLAM).Within the SLAM approach,factors encoding robot odometry and robot-to-visible landmark measurements are formulated for the cases of wireless sensing and fiducial object detection and tracking.Visible landmarks are rigidly attached to non-visible landmark subsets for each engineered landmark,where the complete set of non-visible landmarks form globally rigid and localizable connectivity graphs via range-based factors.Complimentary subsets of non-visible landmarks are embedded within the base structure and uniquely define joint pose via geometric factors.All factors are unified within a common graph to solve for the maximum a posteriori estimate of robot,landmark,and joint states via nonlinear least squares optimization.To demonstrate the applicability of our approach,we apply the Monte Carlo method over a parameterization of system noise to calculate residual joint pose error distributions,maximum average inter-story drift ratios,and related summary statistics for a 19-story nonlinear structural model.By performing nonlinear time history analyses over sets of service-level and maximum considered earthquakes,our parametric study gives insight into our method′s application towards post-earthquake building evaluation in non-LOS conditions.

Efficient thermal management and all-season energy harvesting using adaptive radiative cooling and a thermoelectric power generator

Passive daytime radiative cooling(PDRC) is useful for thermal management because it allows an object to emit terrestrial heat into space without the use of additional energy.To produce sub-ambient temperatures under direct sunlight,PDRC materials are designed to reduce their absorption of solar energy and to enhance their long-wavelength infrared(LWIR) emissivity.In recent years,many photonic structures and polymer composites have been studied to improve the cooling system of buildings.However,in cold weather(i.e. during winter in cold climates),buildings need to be kept warm rather than cooled due to heat loss.To overcome this limitation,temperature-responsive radiative cooling is a promising alternative.In the present study,adaptive radiative cooling(ARC) film fabricated from a polydimethylsiloxane/hollow SiO_(2) microsphere/thermochromic pigment composite was investigated.We found that the ARC film absorbed solar radiation under cold conditions while exhibiting radiative cooling at ambient temperatures above 40℃.Thus,in outdoor experiments,the ARC film achieved sub-ambient temperatures and had a theoretical cooling power of 63.2 W/m~2 in hot weather.We also demonstrated that radiative cooling with an energy harvesting system could be used to improve the energy management of buildings,with the thermoelectric module continuously generating output power using the ARC film.Therefore,we believe that our proposed ARC film can be employed for efficient thermal management of buildings and all-season energy harvesting in the near future.

A combined experimental and crystal plasticity study of grain size effects in magnesium alloys

This work presents a method to incorporate the micro Hall-Petch equation into the crystal plasticity finite element(CPFE) framework accounting for the microstructural features to understand the coupling between grain size, texture, and loading direction in magnesium alloys.The effect of grain size and texture is accounted for by modifying the slip resistances of individual basal and prismatic systems based on the micro Hall-Petch equation. The modification based on the micro Hall-Petch equation endows every slip system at each microstructural point with a slip system-level grain size and maximum compatibility factor, which are in turn used to modify the slip resistance. While the slip-system level grain size is a measure of the grain size, the maximum compatibility factor encodes the effect of the grain boundary on the slip system resistance modification and is computed based on the Luster-Morris factor. The model is calibrated using experimental stress-strain curves of Mg-4Al samples with three different grain sizes from which the Hall-Petch coefficients are extracted and compared with Hall-Petch coefficients predicted using original parameters from previous work. The predictability of the model is then evaluated for a Mg-4Al sample with different texture and three grain sizes subjected to loading in different directions. The calibrated parameters are then used for some parametric studies to investigate the variation of Hall-Petch slope for different degrees of simulated spread in basal texture,variation of Hall-Petch slope with loading direction relative to basal poles for a microstructure with strong basal texture, and variation of yield strength with change in grain morphology. The proposed approach to incorporate the micro Hall-Petch equation into the CPFE framework provides a foundation to quantitatively model more complicated scenarios of coupling between grain size, texture and loading direction in the plasticity of Mg alloys.

A novel multifunctional radioprotective strategy using P7C3 as a countermeasure against ionizing radiation-induced bone loss

Radiotherapy is a critical component of cancer care but can cause osteoporosis and pathological insufficiency fractures in surrounding and otherwise healthy bone.Presently,no effective countermeasure exists,and ionizing radiation-induced bone damage continues to be a substantial source of pain and morbidity.The purpose of this study was to investigate a small molecule aminopropyl carbazole named P7C3 as a novel radioprotective strategy.Our studies revealed that P7C3 repressed ionizing radiation(IR)-induced osteoclastic activity,inhibited adipogenesis,and promoted osteoblastogenesis and mineral deposition in vitro.We also demonstrated that rodents exposed to clinically equivalent hypofractionated levels of IR in vivo develop weakened,osteoporotic bone.However,the administration of P7C3 significantly inhibited osteoclastic activity,lipid formation and bone marrow adiposity and mitigated tissue loss such that bone maintained its area,architecture,and mechanical strength.Our findings revealed significant enhancement of cellular macromolecule metabolic processes,myeloid cell differentiation,and the proteins LRP-4,TAGLN,ILK,and Tollip,with downregulation of GDF-3,SH2B1,and CD200.These proteins are key in favoring osteoblast over adipogenic progenitor differentiation,cell matrix interactions,and shape and motility,facilitating inflammatory resolution,and suppressing osteoclastogenesis,potentially via Wnt/β-catenin signaling.A concern was whether P7C3 afforded similar protection to cancer cells.Preliminarily,and remarkably,at the same protective P7C3 dose,a significant reduction in triple-negative breast cancer and osteosarcoma cell metabolic activity was found in vitro.Together,these results indicate that P7C3 is a previously undiscovered key regulator of adipo-osteogenic progenitor lineage commitment and may serve as a novel multifunctional therapeutic strategy,leaving IR an effective clinical tool while diminishing the risk of adverse post-IR complications.Our data uncover a new approach for the prevention of radiation-induced bone damage,and further work is needed to investigate its ability to selectively drive cancer cell death.

Recent advances in lung-on-a-chip technology for modeling respiratory disease

Tissue engineering approaches,including those to functional lung tissues,are finely honed by the inclusion of upgraded devices that mimic biophysical and biochemical features in vivo.Perfusion culture is one of these essential biophysical characteristics enabled by the introduction of microfluidic devices in recent years.This review links the importance of dynamic culture for in vitro maintenance of functional lung cells to the modeling of respiratory disease.We identify and discuss different parameters for fabricating the requisite microfluidic models for lung cells,as well as their application in modeling lung diseases caused by external factors such as smoking and pollution.The possibility of creating a multi-organ-on-a-chip to establish a more physiologically relevant model is highlighted.Overall,the focus is on different prospects for the in vitro modeling approach and for lungs-on-a-chip for developing advanced,reliable technology to analyze the pathophysiology of respiratory diseases and screen potential treatments.

Physics problems in bio or bioinspired additive manufacturing

Additive manufacturing,also known as three-dimensional(3D)printing,has attracted increasing attention due to the innovations in materials science and manufacturing over recent decades[1].Recently,innovations in biocompatible materials and biology have enabled the extension of 3D printing techniques into bioadditive manufacturing,which focuses on the fabrication of 3D engineered native-like tissues/organs[2].Currently,bioadditive manufacturing technologies can be categorized into inkjet-based bioprinting,microextrusion-based bioprinting,digital light processing(DLP)bioprinting,electric field-assisted bioprinting,and fused deposition modeling(FDM),to name a few[3,4](Fig.1).Artificial tissues and organs with delicate structures,such as the heart[5]and liver[6],have been successfully fabricated using various bioadditive manufacturing techniques.

MXene:From synthesis to environment remediation

A new burgeoning family of two-dimensional(2D)transition metal carbides/nitrides,better known as MXenes,have received extensive attention because of their distinct properties,such as metallic conductivity,good hydrophilicity,large surface area,good mechanical stability,and biodegradability.About 40 different MXenes have been synthesized,and dozens more structures and properties have been theoretically predicted.However,the recent progress in MXenes development is not well covered in chronological order based on different applications.This review article focuses on emerging synthesis methods,the properties of MXenes,and mainly the applications of MXenes and MXene-based material family in environmental remediation,a comprehensive review of gaseous and aqueous pollutants treatment.

Design and realization of lung organoid cultures for COVID-19 applications

Coronavirus disease 2019(COVID-19),caused by severe acute respiratory syndrome coronavirus 2,has spread globally and threatens public health.Advanced in vitro models that recapitulate the architecture and functioning of specific tissues and organs are in high demand for COVID-19-related pathology studies and drug screening.Since three-dimensional in vitro cultures,such as self-assembled and engineered organoid cultures,surpass conventional two-dimensional cultures and animal models with respect to increased cellular complexity,an environment more relevant to humans,and reduced cost,they are promising platforms for understanding viral pathogenesis and developing new therapeutics.This review highlights the recent advances in self-assembled and engineered organoid technologies that are used for COVID-19 studies.The challenges and future perspectives are also discussed.

Analytical study of silane-based and wax-based additives on the interfacial bonding characteristics between natural rubber modified binder and different aggregate types

The modification of asphalt binder with natural rubber latex(NR)significantly improves the rutting and fatigue resistance of asphalt mixtures.However,NR-modified binder is prone to low workability and wettability due to its high viscosity.Therefore,this research focuses on examining the influences of silane and wax-based additives on the wettability of natural rubber-modified binders and the binder-aggregates adhesion performances.In this study,experimental and analytical approaches were used.The contact angles of asphalt binder were measured using a goniometer through the sessile drop method with three solvents:deionised water,formamide,and glycerol.The Cþþalgorithm was adopted to compute the surface free energy(SFE)elements of the asphalt binder.Analytical methods were employed to analyse the results based on the Young-Dupre equation,followed by linear regression to establish a correlation between the compatibility ratio(CR)and the SFE components.The results inferred that modified asphalt binders with additives possessed improved moisture resistance,wherein dry work adhesion values were less than 210 mJ/m^(2)under granite interfaces,whereas the limestone interface exhibited higher dry adhesion values of 340 mJ/m^(2)and below.Similar performance results were observed under wet adhesion conditions;with granite wet adhesive values observed below 120 mJ/m^(2),while limestone wet adhesion values were ascertained below 180 mJ/m^(2)for all tested samples and conditions.According to the spread–ability coefficient results,the limestone interface has greater spread-ability than granite interfaces.Meanwhile,compatibility ratio values indicated better compatibility of 1.9 or higher for tested samples under granite interfaces,whereas compatibility values of 1.7 and below were observed under limestone interfaces.

有机硅聚合物制备的陶瓷材料高温结晶与氧化机理研究进展

综述了高温结构陶瓷材料在高温条件下结晶机理及氧化理论 ,对各种理论模型进行了评介。其中重点介绍了Si-C - (O) - (N)体系的“无定型—成核—晶粒长大”结晶机理和Si -C -N体系的“分离—分解—结晶”结晶机理 ;并具体介绍了Si -C -N -O和Si - (B) -C -N高温氧化机理。

旋转进口畸变条件下轴流压气机叶顶间隙流非定常特征及其与旋转失速的关联性研究

本文采用数值模拟和实验测量相结合的方法,以叶顶间隙流的非定常流场特征为切入点,系统地研究了畸变情况下轴流压气机旋转失速的触发机理.研究结果表明:畸变影响区内叶片负载明显高于非畸变影响区;畸变影响区内逆压梯度的增大使得叶顶泄漏涡轨迹前移,当节流到一定程度时,叶顶泄漏流溢出,形成类尖脉冲扰动,类尖脉冲扰动的间歇性发展,最终诱发旋转失速。

旋转进口畸变与轴流压气机旋转失速相关联的模型与实验探索

本文自行设计了轴流压气机旋转进口畸变发生装置。基于M-G模型,建立了轴流压气机旋转畸变模型．采用数值模拟和实验测量相结合的方法研究了轴流压气机在发生旋转进口畸变情况下的失速过程．试图通过分析畸变扰动与旋转失速之间关联性来探索压气机失稳的触发机理．研究结果表明：在旋转畸变条件下,压气机旋转失速总是始发于畸变扰动位置．

丰度加权法分析冬虫夏草RAPD多态性高度差异及动态变化

目的：检测在冬虫夏草僵虫体、子座和子囊果部位多菌共存和差异表达导致的随机扩增多态性DNA（random amplified polymorphic DNA,RAPD）分子标记多态性及其在冬虫夏草成熟过程中的动态变化.方法：采用模糊、整体性RAPD分子标记多态性研究法,选用20条随机引物,应用ZUNIX丰度加权相似度公式和丰度加权聚类法,比对冬虫夏草3个成熟期僵虫体、子座和子囊果部位RAPD分子标记多态性,以及与中国被毛孢的差异.结果：丰度非加权算法忽略了RAPD共有扩增子的丰度差异,而丰度加权ZUNIX相似度算法和聚类法,将扩增子的丰度差异及其在冬虫夏草成熟过程中的动态变化所蕴含的全部菌物分子信息汇入分析,准确获取样本间相似度和构建聚类图.冬虫夏草全部样本的总相似度为0.42,小于总相异度0.58.3个成熟期子座样本的相似度为0.57,僵虫体为0.50.同株冬虫夏草的子座和僵虫体样本的相似度随着成熟过程出现低→高→低的变化.子囊果部位与成熟子座的相似度最高（0.87）,汇入一个聚类分枝;未成熟子座和僵虫体聚为另一分枝;这两个分枝聚为一群.而成熟中子座和僵虫体聚为一个分枝,与成熟僵虫体聚为另一群.中国被毛孢与冬虫夏草样本的相似度为0.55～0.69,与冬虫夏草聚类群之间被外群对照蛹虫草拟青霉分隔.结论：冬虫夏草各部位的RAPD分子标记多态性丰富,随着冬虫夏草的成熟而变化;冬虫夏草与中国被毛孢的RAPD多态性存在巨大差异,支持冬虫夏草是多菌和多种突变基因型菌共生的统一微生态系统的学说,不支持“冬虫夏草是一种真菌”和“中国被毛孢是冬虫夏草的无性世代”的学说.

湍流扩散多相流

湍流扩散多相流在许多工程和环境科学实际应用中十分常见.流体相中的湍流和扩散相的随机本质使得湍流扩散多相流中遇到的问题远比单一流体中遇到的湍流现象复杂得多.首先评述了湍流扩散多相流研究中实验技术和数值计算方面的现状、各自的优点与局限性,以及该领域研究中未来面临的挑战.主要关注湍流扩散多相流研究中以下3方面重点内容:颗粒、液滴和气泡的选择性聚积;湍流对流体相和扩散相耦合作用的影响以及颗粒物和气泡的存在对流体相中湍流的调节机制.