The cement-based additive manufacturing, commonly known as 3D concrete printing, facilitates the use of advanced cementitious materials in construction as this construction technique minimizes waste and enables the optimal placement of the material. 3D printable cementitious mixtures should have specific consistency for successful manufacturing. In particular, they should be extruded smoothly during the printing process while maintain their shape after deposition, both of which are closely related to the rheological properties of cementitious mixture. The use of graphene in cementitious composites has been widely explored in recent years and it was shown that graphene can improve the mechanical properties and durability of cementitious composites. However, the rheological properties and printability characteristics of graphene-reinforced cementitious materials still remain underexplored. This study investigates the effects of graphene nanoplatelets (GNPs) on rheological and printability characteristics of GNP-reinforced cementitious composites. GNPs are added into cementitious mixtures, designed for 3D concrete printing applications, at concentration of 0%, 0.05%, 0.10%, 0.15%, 0.20%, and 0.25% by weight of cement. GNPs are first dispersed into water through the help of ultrasonic treatment and a polycarboxylate-based superplasticizer. The dispersion quality of GNPs is assessed through UV-vis absorption spectroscopy, optical microscopy, and Raman spectroscopy. Then, the rheological properties of GNP-reinforced mortar composites are studied using a shear rheometer via stress-growth tests, shear rate ramp up-down tests, and structural recovery tests.
This paper investigates the rheological and printability characteristics of PVA fiber-reinforced cementitious composites. To fabricate 3D printable strain hardening cementitious mixtures, ordinary Portland cement, fly ash, silica fume, fine sand, water, and a polycarboxylate-based superplasticizer are used. The effects of a modified starch-based viscosity modifying agent and nano clay on the rheological properties of these mixtures are explored. A shear rheometer with a building materials cell and vane motor is used for rheological tests. First, stress-growth tests are conducted to determine the static yield stress evolution curves for the PVA fiber-reinforced cement composites. A constant low shear rate is applied to minimize the viscous contributions to yield stress. Then, structural recovery tests are conducted by applying three different shear rates that mimic initial rest, extrusion, and after deposition conditions of printable mixtures and the change in apparent viscosity is observed. Next, structural build-up of PVA fiber-reinforced cementitious composites is assessed through constant shear rate rheology tests at different rest intervals. Finally, the buildability of the PVA fiber-reinforced cementitious composites is evaluated using a 3D concrete printer equipped with a 15 mm diameter nozzle and screw pump.
Despite being most widely used construction materials, cement-based composites are brittle materials with low tensile strength and susceptible to cracking, especially under harsh environments. Over the past three decades, numerous studies have been conducted to enhance the mechanical properties and durability of cementitious composites through the use of various nanomaterials such as carbon nanotubes (CNTs) and carbon nanofibers (CNFs). More recently, graphene nanoplatelets (GNPs) has emerged as an ideal 2D nano-reinforcement for composite materials due to their favorable mechanical, thermal and electrical properties. However, the effects of different dispersing agents and particle size and surface area of GNPs on the mechanical properties of cement-based composites needs to be further investigated. This paper explores the influence of GNP addition on the mechanical properties and durability of cement-based composites. Two types of GNPs with different lateral size (<2 μm and 25 μm) and specific surface area (300 m2/g and 120 m2/g) are used in this study. The GNP concentration is set to be 0.1% by weight of cement in all mixtures. In order to study the effect of dispersion agents, four different dispersion method are utilized to disperse and stabilize GNP particles in aqueous solution. Compressive strength and flexural strength tests are conducted to assess the mechanical properties, while sorptivity test and surface resistivity measurement are carried out to evaluate the durability. In order to explore the effect of GNPs on hydration process of cement mortar, mechanical properties tests are conducted at 7 day and 28 day curing ages and thermal gravimetric analyses are conducted.
KEYWORDS: Digital image correlation, Structural health monitoring, 3D modeling, Data modeling, Finite element methods, Cameras, Sensors, Optimization (mathematics), Mechanical sensors, Beam shaping
Structural health monitoring (SHM) describes a decision-making framework that is fundamentally guided by state change detection of structural systems. This framework typically relies on the use of continuous or semi-continuous monitoring of measured response to quantify this state change in structural system behavior, which is often related to the initiation of some form of damage. Measurement approaches used for traditional SHM are numerous, but most are limited to either describing localized or global phenomena, making it challenging to characterize operational structural systems which exhibit both. In addition to these limitations in sensing, SHM has also suffered from the inherent robustness inherent to most full-scale structural systems, making it challenging to identify local damage. These challenges highlight the opportunity for alternative strategies for SHM, strategies that are able to provide data suitable to translate into rich information. This paper describes preliminary results from a refined structural identification (St-ID) approach using fullfield measurements derived from high-speed 3D Digital Image Correlation (HSDIC) to characterize uncertain parameters (i.e. boundary and constitutive properties) of a laboratory scale structural component. The St-ID approach builds from prior work by supplementing full-field deflection and strain response with vibration response derived from HSDIC. Inclusion of the modal characteristics within a hybrid-genetic algorithm optimization scheme allowed for simultaneous integration of mechanical and modal response, thus enabling a more robust St-ID strategy than could be achieved with traditional sensing techniques. The use of full-field data is shown to provide a more comprehensive representation of the global and local behavior, which in turn increases the robustness of the St-Id framework. This work serves as the foundation for a new paradigm in SHM that emphasizes characterizing structural performance using a smaller number, but richer set of measurements.
Conventional seismic design of reinforced concrete structures relies on yielding of steel reinforcement to dissipate energy while undergoing residual deformations. Therefore, reinforced concrete structures subjected to strong earthquakes experience large permanent displacements and are prone to severe damage or collapse. Shape memory alloys (SMAs) have gained increasing acceptance in recent years for use in structural engineering due to its attractive properties such as high corrosion resistance, excellent re-centering ability, good energy dissipation capacity, and durability. SMAs can undergo large deformations in the range of 6-8% strain and return their original undeformed position upon unloading. Due to their appealing characteristics, SMAs have been considered as an alternative to traditional steel reinforcement in concrete structures to control permanent deformations. However, the behavior of SMAs in combination with concrete has yet to be explored. In particular, the bond strength is important to ensure the composite action between concrete and SMA reinforcements. This study investigates the bond behavior between SMA bars and concrete through pull-out tests. To explore the size effect on bond strength, the tests are performed using various diameters of SMA bars. For the same diameter, the tests are also conducted with different embedment length to assess the effect of embedment length on bond properties of SMA bars. To monitor the slippage of the SMA reinforcement, an optical Digital Image Correlation method is used and the bond-slip curves are obtained.
This study investigates the optimum design parameters of a superelastic friction base isolator (S-FBI) system through a multi-objective genetic algorithm and performance-based evaluation approach. The S-FBI system consists of a flat steel- PTFE sliding bearing and a superelastic NiTi shape memory alloy (SMA) device. Sliding bearing limits the transfer of shear across the isolation interface and provides damping from sliding friction. SMA device provides restoring force capability to the isolation system together with additional damping characteristics. A three-story building is modeled with S-FBI isolation system. Multiple-objective numerical optimization that simultaneously minimizes isolation-level displacements and superstructure response is carried out with a genetic algorithm (GA) in order to optimize S-FBI system. Nonlinear time history analyses of the building with S-FBI system are performed. A set of 20 near-field ground motion records are used in numerical simulations. Results show that S-FBI system successfully control response of the buildings against near-fault earthquakes without sacrificing in isolation efficacy and producing large isolation-level deformations.
This study proposes a passive control device based on superelastic behavior of shape memory alloys (SMAs) and investigates the device performance for improving response of steel frame structures subjected to multi-level seismic hazards. The device, named as Superelastic Viscous Damper (SVD), exhibits both re-centering and energy-dissipating capabilities and consists of SMA elements and a viscoelastic (VE) damper. SMA elements are mainly used as recentering unit and the viscoelastic damper is employed as energy dissipation unit. The VE damper consists of two layers of VE material bonded with three steel plates. Energy is dissipated through the shear deformation of VE material. Each SMA element forms a continuous loop; wrapping the loops around the outer two plates improves compactness and efficiency. An analytical model of a three-story benchmark steel building with the installed SVDs is developed to determine the response of the structure under a ground motion input. A neuro-fuzzy model is used to capture nonlinear behavior of the SMA elements of the SVD. Nonlinear response history analyses are conducted at MCE level seismic hazard. A suite of 22 ground motion records is employed in dynamic analysis. Peak interstory drift, peak absolute floor acceleration, and residual story drift are selected as the primary demand parameters. Results shows that SVDs can effectively mitigate dynamic response of steel frame structures under strong ground motions and enhance their post-earthquake functionality.
This paper investigates the effectiveness of two adaptive control strategies for modulating control force of piezoelectric
friction dampers (PFDs) that are employed as semi-active devices in combination with laminated rubber bearings for
seismic protection of buildings. The first controller developed in this study is a direct adaptive fuzzy logic controller. It
consists of an upper-level and a sub-level direct fuzzy controller. In the hierarchical control scheme, higher-level
controller modifies universe of discourse of both premise and consequent variables of the sub-level controller using
scaling factors in order to determine command voltage of the damper according to current level of ground motion. The
sub-level fuzzy controller employs isolation displacement and velocity as its premise variables and command voltage as
its consequent variable. The second controller is based on the simple adaptive control (SAC) method, which is a type of
direct adaptive control approach. The objective of the SAC method is to make the plant, the controlled system, track the
behavior of the structure with the optimum performance. By using SAC strategy, any change in the characteristics of the
structure or uncertainties in the modeling of the structure and in the external excitation would be considered because it
continuously monitors its own performance to modify its parameters. Here, SAC methodology is employed to obtain the
required force which results in the optimum performance of the structure. Then, the command voltage of the PFD is
determined to generate the desired force. For comparison purposes, an optimal controller is also developed and
considered in the simulations together with maximum passive operation of the friction damper. Time-history analyses of
a base-isolated five-story building are performed to evaluate the performance of the controllers. Results reveal that developed adaptive controllers can successfully improve seismic response of the base-isolated buildings against various types of earthquakes.
The seismic response of a multi-span continuous bridge isolated with novel superelastic-friction base isolator (S-FBI) is
investigated under near-field earthquakes. The isolation system consists of a flat steel-Teflon sliding bearing and a
superelastic NiTi shape memory alloy (SMA) device. Sliding bearings limit the maximum seismic forces transmitted to
the superstructure to a certain value that is a function of friction coefficient of sliding interface. Superelastic SMA
device provides restoring capability to the isolation system together with additional damping characteristics. The key
design parameters of an S-FBI system are the natural period of the isolated, yielding displacement of SMA device, and
the friction coefficient of the sliding bearings. The goal of this study is to obtain optimal values for each design
parameter by performing sensitivity analyses of the isolated bridge. First, a three-span continuous bridge is modeled as a
two-degrees-of-freedom with S-FBI system. A neuro-fuzzy model is used to capture rate-dependent nonlinear behavior
of SMA device. A time-dependent method which employs wavelets to adjust accelerograms to match a target response
spectrum with minimum changes on the other characteristics of ground motions is used to generate ground motions used in the simulations. Then, a set of nonlinear time history analyses of the isolated bridge is performed. The variation of the peak response quantities of the isolated bridge is shown as a function of design parameters. Also, the influence of temperature variations on the effectiveness of S-FBI system is evaluated. The results show that the optimum design of the isolated bridge with S-FBI system can be achieved by a judicious specification of design parameters.
Base isolation is an effective method of reducing seismic response of bridges during an earthquake. Rubber isolators are
one of the most common types of base isolation systems. As an alternative to conventional rubber isolators such as high
damping rubber bearing and lead rubber bearing, smart rubber bearing systems with shape memory alloys (SMAs) have
been proposed in recent years. As a class of smart materials, shape memory alloys shows excellent re-centering and
considerable damping capabilities which can be exploited to obtain an efficient seismic isolation system. This paper
explores effectiveness of shape memory alloy/rubber-based isolation systems for protecting bridges against seismic loads
by performing a sensitivity analysis. The isolation system considered in this study consists of a laminated rubber bearing
which provides lateral flexibility while supplying high vertical load-carrying capacity and an auxiliary device made of
multiple loops SMA wires. The SMA device offers additional energy dissipating and re-centering capability. A threespan
continuous bridge is modeled with SMA/rubber-based isolation system. Numerical simulations of the bridge are
conducted for various historical ground motions that are spectrally matched to a target design spectrum. The normalized
yield strength, yield displacement and pre-stress level of the SMA device and ambient temperature are selected as
parameters of the sensitivity study. The variation of seismic response of the bridge with considered parameters is
assessed. The optimum values of the normalized yield strength and the yield displacement of the SMA device is found
to be in the range of 0.20-0.25 and 40-50 mm, respectively. Also, the SMA/rubber-based isolation system is observed to
be more effective when the SMA device is pre-stressed. In addition, it is found that ambient temperature considerably
affects the performance of the bridge isolated by SMA/rubber-based isolators.
This paper proposes a neuro-fuzzy model of NiTi shape memory alloy (SMA) wires that is capable of capturing behavior
of superelastic SMAs at different temperatures and at various loading rates while remaining simple enough to realize
numerical simulations. First, in order to collect data, uniaxial tensile tests are conducted on superelastic wires in the
temperature range of 0 ºC to 40 ºC, and at the loading frequencies of 0.05 Hz to 2 Hz that is the range of interest for
seismic applications. Then, an adaptive neuro-fuzzy inference system (ANFIS) is employed to construct a model of
SMAs based on experimental input-output data pairs. The fuzzy model obtained from ANFIS training is validated by
using an experimental data set that is not used during training. Upon having a model that can represent behavior of
superelastic SMAs at various ambient temperature and loading-rates, nonlinear simulation of a multi-span continuous
bridge isolated by rubber bearings that is equipped with SMA dampers is carried out. Response of the bridge to a
historical earthquake record is presented at different ambient temperatures in order to evaluate the effect of temperature
on the performance of the structure. It is shown that SMA damping elements can effectively decrease peak deck
displacement and the relative displacement between piers and superstructure in an isolated bridge while recovering all
the deformations to their original position.
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