Results 161 to 170 of about 119,541 (309)

Numerical simulation of mechanical properties of a new type of assembly shear wall horizontal connection device. [PDF]

Sci Rep
Tian P, Fu C, Niu J, Wang J, Xie Z, Xiong E.   +5 more
europepmc   +1 more source

Numerical analysis of reinforced concrete shear keys in immersion joints

, 2017
Immersion joints are susceptible to be damaged first under various loadings due ito their smaller stiffhess compared to the adjacent tunnel elements. The induced Ideformations and the forces in the joint are transferred by shear keys.
Taerwe, Luc, Xiao, Wenhao, Yuan, Yong
core  

Spheres, tears, and spears: Regulating the perimeter and circularity of millimeter‐sized alginate hydrogel beads

AIChE Journal, EarlyView.
Abstract Generating hydrogel beads pertains to many engineering applications. We examined two alginate‐based fluids at three concentrations of alginate, cAG$$ {c}_{\mathrm{AG}} $$. We used the “Map of Misery” to determine which material property (viscosity, elasticity, and inertia) drives droplet formation.
Conor G. Harris, Katherine D. Bandettini, Hannah K. Gedde, Lewis Semprini, Kaitlin C. Fogg, Willie E. Rochefort   +5 more
wiley   +1 more source

Lateral Resistance of Modular CFS Shear Wall Connected with Rectangular Steel Tubes and Its Contribution to Frame Structures. [PDF]

Materials (Basel)
Kang Y, Mei J, Wu X, Wang L.
europepmc   +1 more source

Analytical ultrasonics for structural materials [PDF]

The application of ultrasonic velocity and attenuation measurements to characterize the microstructure of structural materials is discussed. Velocity measurements in cast stainless steel are correlated with microstructural variations ranging from ...
Kupperman, D. S.
core   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source

Digital twin-based machine learning framework for predicting nonlinear seismic response of reinforced concrete shear walls using analytical data. [PDF]

Sci Rep
Kuria KK, Kegyes-Brassai O.
europepmc   +1 more source

Treatments on Polypropylene Macro Synthetic Fibers for Improving Adhesion in Structural Concrete Reinforcement: A Systematic Review

Journal of Applied Polymer Science, EarlyView.
Surface functionalization of polypropylene macrofibers to enhance fiber‐matrix interfacial bonding. ABSTRACT Concrete is the most used higher compressive strength‐building material, albeit brittle to tensile, and flexural loads. Polypropylene (PP) synthetic polymeric macrofibres are commonly employed as reinforcement material to prevent this situation ...
Elena Saccani, Ylenia Ruberto, Daniel Milanese, Corrado Sciancalepore   +3 more
wiley   +1 more source

Carbon reduction potential and selection strategies of emerging construction-phase technologies. [PDF]

Sci Rep
Liu Z, Xia Z, Li J, Wang Y, Zhang Y, Li X, Yang Q.   +6 more
europepmc   +1 more source

Thin and Compact Versus Thick and Porous Fouling Layers in the Emulsion Polymerization of Acrylates and Vinyl Acetates Studied In Situ With a Quartz Crystal Microbalance (QCM)

Journal of Applied Polymer Science, EarlyView.
ABSTRACT Building on a quartz crystal microbalance with dissipation monitoring (QCM‐D), fouling in emulsion polymerization was compared between acrylate dispersions stabilized with a mobile, anionic surfactant and dispersions of poly(vinyl acetate‐co‐vinyl neodecanoate), PVAc, stabilized with polyvinyl alcohol, PVOH.
K. M. Hoffmann, O. Sidorow, W. Augustin, S. Scholl, A. Langhoff, D. Johannsmann   +5 more
wiley   +1 more source