Single Aggregate Research Articles

A computational framework for testing hypotheses of the minimal mechanical requirements for cell aggregation using early annual killifish embryogenesis as a model.

Introduction: Deciphering the biological and physical requirements for the outset of multicellularity is limited to few experimental models. The early embryonic development of annual killifish represents an almost unique opportunity to investigate de novo cellular aggregation in a vertebrate model. As an adaptation to seasonal drought, annual killifish employs a unique developmental pattern in which embryogenesis occurs only after undifferentiated embryonic cells have completed epiboly and dispersed in low density on the egg surface. Therefore, the first stage of embryogenesis requires the congregation of embryonic cells at one pole of the egg to form a single aggregate that later gives rise to the embryo proper. This unique process presents an opportunity to dissect the self-organizing principles involved in early organization of embryonic stem cells. Indeed, the physical and biological processes required to form the aggregate of embryonic cells are currently unknown. Methods: Here, we developed an in silico, agent-based biophysical model that allows testing how cell-specific and environmental properties could determine the aggregation dynamics of early Killifish embryogenesis. In a forward engineering approach, we then proceeded to test two hypotheses for cell aggregation (cell-autonomous and a simple taxis model) as a proof of concept of modeling feasibility. In a first approach (cell autonomous system), we considered how intrinsic biophysical properties of the cells such as motility, polarity, density, and the interplay between cell adhesion and contact inhibition of locomotion drive cell aggregation into self-organized clusters. Second, we included guidance of cell migration through a simple taxis mechanism to resemble the activity of an organizing center found in several developmental models. Results: Our numerical simulations showed that random migration combined with low cell-cell adhesion is sufficient to maintain cells in dispersion and that aggregation can indeed arise spontaneously under a limited set of conditions, but, without environmental guidance, the dynamics and resulting structures do not recapitulate in vivo observations. Discussion: Thus, an environmental guidance cue seems to be required for correct execution of early aggregation in early killifish development. However, the nature of this cue (e.g., chemical or mechanical) can only be determined experimentally. Our model provides a predictive tool that could be used to better characterize the process and, importantly, to design informed experimental strategies.

β-Carotene, a Potent Amyloid Aggregation Inhibitor, Promotes Disordered Aβ Fibrillar Structure

The aggregation of amyloid beta (Aβ) into fibrillar aggregates is a key feature of Alzheimer's disease (AD) pathology. β-carotene and related compounds have been shown to associate with amyloid aggregates and have direct impact on the formation of amyloid fibrils. However, the precise effect of β-carotene on the structure of amyloid aggregates is not known, which poses a limitation towards developing it as a potential AD therapeutic. In this report, we use nanoscale AFM-IR spectroscopy to probe the structure of Aβ oligomers and fibrils at the single aggregate level and demonstrate that the main effect of β-carotene towards modulating Aβ aggregation is not to inhibit fibril formation but to alter the secondary structure of the fibrils and promote fibrils that lack the characteristic ordered beta structure.

Bi-objective aggregate production planning for managing plan stability

Uncertainties in demand causes recurrent changes and revisions in a production plan, which may create anxiety in organizations and a state of instability throughout the supply chain. This study proposes a bi-objective aggregate production planning model (BO-APP), where plan stability is incorporated as a second objective alongside the traditional cost objective. The proposed BO-APP model is compared here to a classical single objective aggregate production planning model (APP) as well as to an alternate model called flexible requirements profile-based aggregate production planning model (FRP-APP), which aims to control plan stability by introducing dynamically changing bounds over the planning horizon. Numerical results on five industry-based cases show that both the BO-APP and FRP-APP models consistently generate plans with significantly less variability compared to the traditional APP model, while resulting in comparable planning costs. In addition, the BO-APP shows a better cost and stability performance combination, while the FRP-APP seems to give more flexibility to the planners for controlling the stability level.

Heterogeneous and Surface-Catalyzed Amyloid Aggregation Monitored by Spatially Resolved Fluorescence and Single Molecule Microscopy

Amyloid aggregation is associated with many diseases and may also occur in therapeutic protein formulations. Addition of co-solutes is a key strategy to modulate the stability of proteins in pharmaceutical formulations and select inhibitors for drug design in the context of diseases. However, the heterogeneous nature of this multicomponent system in terms of structures and mechanisms poses a number of challenges for the analysis of the chemical reaction. Using insulin as protein system and polysorbate 80 as co-solute, we combine a spatially resolved fluorescence approach with single molecule microscopy and machine learning methods to kinetically disentangle the different contributions from multiple species within a single aggregation experiment. We link the presence of interfaces to the degree of heterogeneity of the aggregation kinetics and retrieve the rate constants and underlying mechanisms for single aggregation events. Importantly, we report that the mechanism of inhibition of the self-assembly process depends on the details of the growth pathways of otherwise macroscopically identical species. This information can only be accessed by the analysis of single aggregate events, suggesting our method as a general tool for a comprehensive physicochemical characterization of self-assembly reactions.

Effect of coarse aggregate grading optimization on temperature, thermal stress and compressive strength of carbon fiber-reinforced concrete by ohmic heating curing

The ohmic heating (OH) method is demonstrated to be promising for the curing of carbon fiber-reinforced mortar under ultra-low temperature condition. For the large-scale application in engineering and the reduction of carbon emission, the addition of coarse aggregates is necessary. However, coarse aggregates also influence on the temperature distribution and mechanical strength of OH cured concrete. This study proposed an optimization process of coarse aggregate gradation by combining particle packing theory with thermal simulation. The gradation was firstly decided by modified Andreasen & Andersen curve, and then optimized by the numerical simulation of temperature and thermal stress, in order to relieve the high thermal stress gradient in cold condition. The experimental results showed that the compressive strength of the samples with coarse aggregates of both 5–10 mm and 10–16 mm cured by 2 days OH curing at −20 °C reached 51.94 MPa, which was higher than samples including single aggregate diameter level, presenting a comparable strength value with 7 days room temperature (RT) curing. In addition, the microstructure and hydration products of concrete with OH and RT curing were compared and analyzed. This work will provide better guidance on the optimization design of mix proportion of carbon fiber-reinforced concrete for promoting the development of OH curing of concrete in large-scale practical applications.

Sugarcane Bagasse as Aggregate in Composites for Building Blocks

Each year, hundreds of millions of tons of processed sugarcane generate, by weight, 25 to 30% of bagasse as waste, whose destination is combustion for energy cogeneration. This research proposes an alternative and more sustainable use for this waste. The use of sugarcane bagasse (SCB) as the single aggregate in composites for building blocks was studied. The raw bagasse was used without any treatment. As the binder, aerial lime and/or soil were used. Both provided enough mechanical strength for non-load-bearing walls. The composite of SCB with soil achieved the best performance in terms of mechanical resistance: 2.6 MPa in compressive strength and 2.1 MPa in bending strength, while the composite of SCB with lime achieved 1.76 MPa and 1.7 MPa, respectively. The higher number of fibers in the SCB/lime mixture provides better thermal insulation than clay brick or conventional concrete, such as “hempcrete”. The lime composites obtained greater water resistance and less loss of mechanical strength when saturated. However, the higher water absorption coefficient makes it necessary to apply a waterproof mortar on surfaces exposed to the weather. The replacement of supplied blocks by SCB blocks can offer a better and more economical solution that improves the quality of the built environment and is more ecofriendly.

Adaptation and validation of a coding algorithm for the Charlson Comorbidity Index in administrative claims data using the SNOMED CT standardized vocabulary

ObjectivesThe Charlson comorbidity index (CCI), the most ubiquitous comorbid risk score, predicts one-year mortality among hospitalized patients and provides a single aggregate measure of patient comorbidity. The Quan adaptation of the CCI revised the CCI coding algorithm for applications to administrative claims data using the International Classification of Diseases (ICD). The purpose of the current study is to adapt and validate a coding algorithm for the CCI using the SNOMED CT standardized vocabulary, one of the most commonly used vocabularies for data collection in healthcare databases in the U.S.MethodsThe SNOMED CT coding algorithm for the CCI was adapted through the direct translation of the Quan coding algorithms followed by manual curation by clinical experts. The performance of the SNOMED CT and Quan coding algorithms were compared in the context of a retrospective cohort study of inpatient visits occurring during the calendar years of 2013 and 2018 contained in two U.S. administrative claims databases. Differences in the CCI or frequency of individual comorbid conditions were assessed using standardized mean differences (SMD). Performance in predicting one-year mortality among hospitalized patients was measured based on the c-statistic of logistic regression models.ResultsFor each database and calendar year combination, no significant differences in the CCI or frequency of individual comorbid conditions were observed between vocabularies (SMD ≤ 0.10). Specifically, the difference in CCI measured using the SNOMED CT vs. Quan coding algorithms was highest in MDCD in 2013 (3.75 vs. 3.6; SMD = 0.03) and lowest in DOD in 2018 (3.93 vs. 3.86; SMD = 0.02). Similarly, as indicated by the c-statistic, there was no evidence of a difference in the performance between coding algorithms in predicting one-year mortality (SNOMED CT vs. Quan coding algorithms, range: 0.725–0.789 vs. 0.723–0.787, respectively). A total of 700 of 5,348 (13.1%) ICD code mappings were inconsistent between coding algorithms. The most common cause of discrepant codes was multiple ICD codes mapping to a SNOMED CT code (n = 560) of which 213 were deemed clinically relevant thereby leading to information gain.ConclusionThe current study repurposed an important tool for conducting observational research to use the SNOMED CT standardized vocabulary.

Label-Free Detection of β-Sheet Polymorphism.

The ability to detect and characterize multiple secondary structures or polymorphs within peptide and protein aggregates is crucial to treatment and prevention of amyloidogenic diseases, production of novel biomaterials, and many other applications. Here we report a label-free method to distinguish multiple β-sheet configurations within a single peptide aggregate using two-dimensional infrared spectroscopy. By calculating the transition dipole strength (TDS) spectrum from the ratio of linear and two-dimensional signals, we can extract maximum TDS values which provide higher sensitivity to vibrational coupling, and thus specifics of protein structure, than vibrational frequency alone. TDS spectra of AcKFE8 aggregates reveal two distinct β-sheet structures within fibers that appear homogeneous by other techniques. Furthermore, TDS spectra taken during early stages of aggregation show additional peaks that may indicate the presence of more weakly coupled β-sheet structures. These results demonstrate a unique and powerful spectroscopic method capable of distinguishing multiple oligomeric and polymorphic motifs throughout the aggregation using only native vibrational modes.

Constructing a New Measure of Macropartisanship Disaggregated by Race and Ethnicity

AbstractMacropartisanship is a measure of aggregate trends in party identification in the mass public that allows researchers to track partisanship dynamically. In previous research, macropartisanship was found to vary in concert with major political events and forces like presidential approval and the economy. However, studying macropartisanship as an aggregate trend assumes that group dynamics within the measure are equivalent. We present a series of new measures of macropartisanship using Stimson’s (2018) dyad ratio approach disaggregated by race and ethnicity. We detail the creation of measures for White, Latino, and Black macropartisanship from 1983 to 2016 using more than 500 surveys from CBS News and CBS/New York Times. The resulting data collection is publicly available and can be downloaded in monthly, quarterly, or yearly format. Our initial analysis of these data show that thinking about macropartisanship as a single aggregate measure masks important and significant variation in our understanding of party identification. Change in the measures are uncorrelated. Latino macropartisanship is more volatile and responds more to economic conditions, Black macropartisanship is very stable and has become more Democratic in response to increased polarization, while White macropartisanship has become less responsive to economic conditions as has become more Republican as Republicans have moved to the right.

Direct observation of heterogeneous formation of amyloid spherulites in real-time by super-resolution microscopy

Protein misfolding in the form of fibrils or spherulites is involved in a spectrum of pathological abnormalities. Our current understanding of protein aggregation mechanisms has primarily relied on the use of spectrometric methods to determine the average growth rates and diffraction-limited microscopes with low temporal resolution to observe the large-scale morphologies of intermediates. We developed a REal-time kinetics via binding and Photobleaching LOcalization Microscopy (REPLOM) super-resolution method to directly observe and quantify the existence and abundance of diverse aggregate morphologies of human insulin, below the diffraction limit and extract their heterogeneous growth kinetics. Our results revealed that even the growth of microscopically identical aggregates, e.g., amyloid spherulites, may follow distinct pathways. Specifically, spherulites do not exclusively grow isotropically but, surprisingly, may also grow anisotropically, following similar pathways as reported for minerals and polymers. Combining our technique with machine learning approaches, we associated growth rates to specific morphological transitions and provided energy barriers and the energy landscape at the level of single aggregate morphology. Our unifying framework for the detection and analysis of spherulite growth can be extended to other self-assembled systems characterized by a high degree of heterogeneity, disentangling the broad spectrum of diverse morphologies at the single-molecule level.

Matrix free polymer nanocomposites from amphiphilic hairy nanoparticles: Solvent selectivity and mechanical properties

Matrix free polymer nanocomposite of spherical nanoparticles with shells made of amphiphilic homopolymer was studied in molecular dynamics experiments. The amphiphilic homopolymer was presented as sequence of identical monomer units, each containing two beads having different affinity to solvent. The self-assembly in solution of such hairy nanoparticles was studied depending on solvent quality and selectivity for different polymer concentrations. Two of the most characteristic morphologies were identified and described. The first one is a structure resembling a mixture of sea hedgehogs. There is a nanoparticle in the core of a hedgehog, and the spines consist of several grafted chains. Hedgehogs float freely, do not aggregate with other nanoparticles, their solutions have a low moduli of elasticity and viscosity up to a fairly high polymer concentration. The second morphology is thin membrane lamellae assembled from amphiphilic homopolymers. In this case, the nanoparticles are joined into a single network-like aggregate at very low polymer concentrations. Such networks possess a unique porous structure and demonstrate high elasticity and viscosity moduli. These findings could be useful for molecular design of smart materials, that are able to reversibly assemble, disintegrate on request and repair damage by self-healing mechanism. • Nanoparticles, coated with amphiphilic homopolymers, are studied. • Such nanoparticles can self-assemble either into gels or into “hedgehogs” mixture. • Gels have membrane-like, porous structure, and demonstrate elastic and viscous response. • Core-shell filaments preserve aggregation and favor uniform distribution of “hedgehogs”. • Structure type is determined by solvent quality and selectivity.

Numerical investigation of hydrolysis failure of aggregates in loess

Large numbers of aggregates in loess are vital components of the skeletal structure of loess. In this study, a simulation of the water stability of aggregates using coupled computational fluid dynamics and the discrete-element method (CFD–DEM) is presented. For the simulation, the ‘fixed coarse-grid’ method of the Particle Flow Code in 3 Dimensions (PFC3D) software program was employed to simulate the particle–fluid coupling. With respect to the degradation law, a customised code was developed using Python, which transformed through the CFD–DEM model the hydrolysis of cement into the degradation process for the bond strength between particles. Under the action of different hydraulic gradients, the rate of hydrolysis of the aggregates increased rapidly with an increase in water pressure, and many piles of particles were denuded from the aggregates, thus causing the destruction of the aggregates. At the same time and under the same water pressure, the rate of hydrolysis of the multi-aggregates was always lower than that of the single aggregate. Also, the density and porosity of the aggregates would affect, to varying degrees, the water stability.

Early-age concrete strength development monitoring using piezoelectric self-emission and detection (SED) and coda wave energy (CWE)

The property of concrete is very significant to structural safety, and the early hydration process plays a critical role in the final concrete property. This paper develops a self-emission and detection (SED) principle with a single piezoelectric smart aggregate (SA) transducer, which is used as both an actuator and a sensor, to monitor the concrete early age strength development. The signal analysis is carried out by the coda wave energy (CWE). Experiments of concrete specimens with and without the SAs were conducted. Experimental results show a high correlation between the strength of early-age concrete and the CWE and non-linear fitting is used to establish the relationship between them. The proposed CWE features a simple analysis method, and the SED principle does not require consideration of the matching between the transmitting transducer and the receiving sensor, such as frequency range, sensitivity. Furthermore, the proposed method can be used as a reference for health monitoring of other structures and has good application prospects.

Study on the chemical structure characterization and emulsification-stripping of heavy oil

The viscosity of heavy oil is of great importance on crude oil recovery, and the intrinsic relationship between the molecular structure of heavy oil and its viscosity is still unclear. To this end, the chemical structure of heavy oil is characterized by Scanning Electron Microscopy (SEM) and Diffusion-ordered Spectroscopy (DOSY). The relationship between the molecular structure and viscosity of heavy oil is revealed. The morphology of molecular aggregates is dominated by spherical particles, vesicles and films, and the corresponding viscosity increases sequentially. DOSY show that the heavy oil molecules rapidly gathered into aggregates with increasing concentrations. If the saturated aggregation concentration (maximum degree of aggregation) is exceeded, the volume of the single aggregate remains generally fixed but its quantity begins to increase. In addition, the structure-activity relationship between chemical agents and emulsification-stripping, including their mechanism of effect are systematically studied by interfacial tension (IFT), emulsification and micromodel experiments. The results show that the hydrophilic-lipophilic balance (HLB) values of surfactants that stabilize the emulsions are between 13.7 and 14.5. There is no obvious consistency between the emulsification effect of the surfactant and its IFT, and the stripping effect depends on its permeation and wetting action on the solid interface. The formation of emulsions in porous media mainly depends on the rotational disturbance and shear fracture of the displacing fluid, and the wettability of the solid surface determines the peeling rate of the oil film. Comparing with the blockage of large-sized emulsions, the migration of small-sized droplets in the channels as a continuous phase contributes more to the enhanced oil recovery.

Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems.

Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve themselves of the load of dealing with redundant data contents. This must be protected to prevent the theft of personal belongings, and privacy must be improved as well. Different research projects have been suggested to ensure the safe management of the information included within the data content. The security of current research projects, on the contrary, still needs improvement. As a result, this method has been suggested to address the security concerns associated with cloud computing. The primary goal of this study effort is to offer a safe environment for cloud users while also increasing the profit of cloud resource providers by managing and securely delivering data contents to the cloud users. The bulk of sectors, including business, finance, military, and healthcare industry, do not store data in cloud-based storage systems. This technique is used to attract these kinds of customers. Increasing public acceptance, medical researchers are drawn to cloud computing because it allows them to store their study material in a centralized location and distribute and access it in a more flexible manner. They were collected from numerous individuals who were being evaluated for medical care at the time. Scalable and enhanced key aggregate cryptosystem is a protected data protection method that provides highly effective security in the healthcare industry. When parties interested in a dispute disagree on the outflow of sensitive information, this technique manages the disputes and ensures the data security deployment of a cloud-based intelligent health monitoring system for the parties involved. The encrypted data structure of medical and healthcare prescriptions is recorded as they move through the hands of patients and healthcare facilities, according to the technique recommended. The double encryption approach is used in order to raise the overall degree of security. An encryption class is created by referring to the Ciphertext ID during the encryption procedure. The keyholder is a master secret key that facilitates in the recovery of the secret keys of various monsters and creatures by acting as a conduit between them. It is transferred and stored as a single aggregate for the benefit of the patient or customer in order to make decryption more convenient and efficient. A safe connection between cloud-based intelligent health monitoring systems and healthcare organizations and their patients may be established via the use of a key aggregation cryptosystem and a double encryption approach, according to the researchers. Because of this, when compared to earlier techniques, the findings reveal that the research methodology provides high levels of security in terms of confidentiality and integrity, in addition to excellent scalability.

Enhanced soot particle ice nucleation ability induced by aggregate compaction and densification

Abstract. Soot particles, acting as ice nucleating particles (INPs), can contribute to cirrus cloud formation, which has an important influence on climate. Aviation activities emitting soot particles into the upper troposphere can potentially impact ice nucleation (IN) in cirrus clouds. Pore condensation and freezing (PCF) is an important ice formation pathway for soot particles in the cirrus regime, which requires the soot INP to have specific morphological properties, i.e., mesopore structures. In this study, the morphology and pore size distribution of two kinds of soot samples were modified by a physical agitation method without any chemical modification by which more compacted soot sample aggregates could be produced compared to the unmodified sample. The IN activities of both fresh and compacted soot particles with different sizes, 60, 100, 200 and 400 nm, were systematically tested by the Horizontal Ice Nucleation Chamber (HINC) under mixed-phase and cirrus-cloud-relevant temperatures (T). Our results show that soot particles are unable to form ice crystals at T>235 K (homogeneous nucleation temperature, HNT), but IN is observed for compacted and larger-sized soot aggregates (>200 nm) well below the homogeneous freezing relative humidity (RHhom) for T< HNT, demonstrating PCF as the dominating mechanism for soot IN. We also observed that mechanically compacted soot particles can reach a higher particle activation fraction (AF) value for the same T and RH condition compared to the same aggregate size fresh soot particles. The results also reveal a clear size dependence for the IN activity of soot particles with the same degree of compaction, showing that compacted soot particles with large sizes (200 and 400 nm) are more active INPs and can convey the single importance of soot aggregate morphology for the IN ability. In order to understand the role of soot aggregate morphology for its IN activity, both fresh and compacted soot samples were characterized systematically using particle mass and size measurements, comparisons from TEM (transmission electron microscopy) images, soot porosity characteristics from argon (Ar) and nitrogen (N2) physisorption measurements, as well as soot–water interaction results from DVS (dynamic vapor sorption) measurements. Considering the soot particle physical properties along with its IN activities, the enhanced IN abilities of compacted soot particles are attributed to decreasing mesopore width and increasing mesopore occurrence probability due to the compaction process.

Enhancing the Impact Strength of Prepacked Aggregate Fibrous Concrete Using Asphalt-Coated Aggregates.

The brittleness of plain concrete represents a significant issue to the integrity of concrete structures when subjected to impact loading. Recent rapid industrialization has attracted researchers to find a solution for concrete brittleness and enhance its ductility. In light of this, the prepacked aggregate fibrous concrete (PAFC) with single and double precoated coarse aggregates using asphalt is proposed and examined. Nine different mixtures were designed using polypropylene and steel fibre of 3% dosage with single and double asphalt-coated aggregates. Specimens were prepared with natural aggregate and 100% C-graded asphalt-coated aggregate to evaluate their impact strength. The ACI Committee 544 drop-weight impact standard was followed in the testing of all specimens. Results indicated that using asphalt-coated aggregate can improve the impact energies of concrete. The impact energy at cracking and failure of the single asphalt-coated aggregate specimen was 1.55 and 2.11 times higher, while the double-coated aggregate specimens exhibited 1.73 and 2.56 times greater than the natural aggregate specimen, respectively. The contribution of fibres in enhancing the impact resistance is remarkable compared to the single- and double-coated aggregates used in PAFC.

Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)

In this paper, we examine vehicle owners’ adoption of five different types of partially automated features (PAFs); lane keeping system, backup camera (BUC), adaptive cruise control (ACC), automatic braking system (ABS), and blind spot monitoring; as well as PAF effects on vehicle miles of travel (VMT). The joint modeling of PAF adoption and VMT is achieved using both individual demographic characteristics as well as psycho-social characteristics. A Generalized Heterogeneous Data Model (GHDM) is estimated, which controls for possible self-selection effects in PAF adoption based on VMT, and thus is able to provide “true” PAF effects on VMT. Our analysis specifically indicates that ignoring this self-selection can lead to a significant underestimation of the VMT increase due to PAF adoption. The results also indicate that women and older individuals (65 years or older) appear to be more inclined to invest in assistive PAFs, because of a perception that these assistive features still leave the human driver in control. However, women are less likely than men to invest in the more active ABS PAF because of heightened safety concerns with technology. In terms of PAF effects on VMT, PAFs focusing on lateral movement assistance appear to have a smaller VMT effect than those that serve longitudinal movement assistance. The highest estimated VMT change of 2,462 miles (13.8% change) is for the case when the package of BUC, ACC, and ABS is installed for middle-aged men. The highest percentage VMT change (40%), though, is for the same package of BUC, ACC, and ABS for older women. Overall, there are considerable variations in VMT impact across demographic groupings, suggesting that a single aggregate percentage improvement in safety benefits may suffer from the well-known ecological fallacy.

Study on preparation and mechanical properties of 3D printed concrete with different aggregate combinations

3D printed concrete (3DPC) properties are closely related to the characteristics of coarse aggregates and fine aggregates. In this paper, the role of recycled aggregates in 3DPC is considered and the printable inks with different aggregate combinations were well prepared. The mechanical properties of 3DPC containing different aggregates were compared and analyzed, and the effect of recycled aggregates on the development of concrete properties was further investigated under different curing conditions. The results showed that the full recycled aggregate reduced the 3DPC interlayer deformation by 3.1 mm at a height of 120 mm, and the minimum anisotropic compressive strength of it was 16.36 MPa, approximately 67.15% of that of the cast-in-place one. And compared to the full replacement of recycled coarse aggregates, the full replacement of recycled fine aggregates in air curing facilitates the improvement of the mechanical properties of the concrete, with an increase of 4.1 MPa at 28d, but with a negative impact in standard curing. In addition, the reduction in mechanical properties with the combination of fully recycled coarse and fine aggregates is less than the sum of the reduction with the single aggregate, under any type of maintenance or pouring.

Homogenization of the elastic-viscoplastic damage behavior of asphalt mixtures based on the mesomechanical Mori–Tanaka method

To improve the efficiency and accuracy in characterizing the nonlinear behavior of multi-phased asphalt mixtures and to further facilitate asphalt pavement design based on the nonlinear properties, this study proposes a homogenized method for the elastic-viscoplastic-damage constitutive model. The Drucker–Prager-type yield surfaces and non-association flow rule were employed to describe the viscoplastic strain of asphalt materials. The continuum damage mechanics (CDM) were incorporated to characterize the evolutions of internal micro-cracks or micro-voids in structures. The mesomechanical Mori–Tanaka (MT) method was used to yield the homogenized nonlinear strain components within multi-phase structures. The proposed constitutive model was then implemented in finite element (FE) simulations based on a self-developed subroutine. Several case studies were conducted, in which composite structures with one inclusion were simulated under constant stress and strain loading rate. Amongst the composite structures, the inclusions with various volume contents and shapes were taken into account. In addition, the influence of air voids in structures was considered by defining the zero stiffness for inclusions. The results indicated that the nonlinear behavior of composite with single aggregate or air void can be effectively represented using the proposed method. Furthermore, by coupling the homogenized nonlinear constitutive relation into the locally homogenous model from previous work, not only was the viscoplastic-damage behavior of the composite with multiple inclusions effectively demonstrated by the definition of the nonlinear material, but the internal heterogeneous feature was also precisely represented by the local cells. Therefore, the proposed homogenized method can effectively predict the viscoplastic and damage behavior of asphalt mixtures with various inclusions by simply specifying the parameters in the FE simulations.