•Coarse aggregate (CA) with 5–16 mm is selected to produce ECC in this study.•The ECC with moderate CA increases the tensile property of ECC and the maximum strain reaches 7.9% at 0.21 water/binder ...ratio (w/b).•The CA increases the compressive strength and elastic modulus.•The ECC with 30% CA content reduces the total shrinkage by about 60%, compared to conventional ECC.•CA can achieve good mechanical properties and make ECC greener and economic. For some specific application scenarios, CA-ECC is a better choice.
Coarse aggregate (CA) is one of the major components in normal cement concrete. However, CA is excluded from the mixture of Engineered Cementitious Composites (ECC), due to its negative effects on material’s tensile behavior. This brings some issues to ECC, such as high shrinkage, high production cost, and insufficient greenness. In an attempt to improve ECC without losing its advantages in tensile properties, the authors challenged to develop ECC with a high volume fraction of CA. In the present study, the authors experimentally studied the influences of CA content and water to binder (w/b) ratio on mechanical properties, shrinkage, and material sustainability. The test results indicated that ECCs mixed with moderate CA not only maintain strong strain-hardening and multiple-cracking characteristics, but also have similar tensile stress and tensile strain capacity, as compared with the conventional ECC. The maximum value of strain capacity of CA-ECC reached 7.9 % at 0.21w/b, and the average tensile strain of all mixtures exceeded 2 %. Moreover, CA was experimentally verified capable to reduce shrinkage, carbon footprint, energy consumption and producing cost simultaneously. The carbon footprint, energy consumption and cost of CA30-ECC18 were reduced by 33.1 %, 24.4 % and 36.1 %, compared to conventional ECC. The present study preliminarily verified the feasibility of producing ECC with coarse aggregate.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this article, a fusion estimation scheme is proposed for stochastic uncertain systems with time-correlated fading channels (TFCs). A batch of random variables obeying Gaussian distributions is ...employed to describe the parameter uncertainties. The sensor communicates with the local filter through a TFC where the evolution of the channel coefficient is characterized by a certain dynamic process with one-step correlated noises. For further analyzing the effects of TFCs, a class of additional variables is first introduced by augmenting the dynamics of channel coefficients and the concerned system. Then, a new group of modified local filters is developed and the unbiasedness of local filters is examined by means of inductive method. Furthermore, the filter gains which minimize the local filtering error covariances are designed for the modified local filters in the simultaneous presence of stochastic uncertainties and TFCs. Subsequently, the cross-covariances among local estimates are computed iteratively and, based on the obtained cross-covariances as well as the unbiased local estimates and their corresponding filtering error covariances, a fusion estimate is obtained by using weighted least square fusion method. Finally, the effectiveness of the proposed fusion estimation scheme is verified by two examples.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
23.
10.1016/j.jfranklin.2022.01.032 Tan, Hailong; Shen, Bo; Li, Qi
Journal of the Franklin Institute,
03/2022, Volume:
359, Issue:
5
Journal Article
Peer reviewed
In this article, a fusion estimation scheme is proposed for stochastic uncertain systems with time-correlated fading channels (TFCs). A batch of random variables obeying Gaussian distributions is ...employed to describe the parameter uncertainties. The sensor communicates with the local filter through a TFC where the evolution of the channel coefficient is characterized by a certain dynamic process with one-step correlated noises. For further analyzing the effects of TFCs, a class of additional variables is first introduced by augmenting the dynamics of channel coefficients and the concerned system. Then, a new group of modified local filters is developed and the unbiasedness of local filters is examined by means of inductive method. Furthermore, the filter gains which minimize the local filtering error covariances are designed for the modified local filters in the simultaneous presence of stochastic uncertainties and TFCs. Subsequently, the cross-covariances among local estimates are computed iteratively and, based on the obtained cross-covariances as well as the unbiased local estimates and their corresponding filtering error covariances, a fusion estimate is obtained by using weighted least square fusion method. Finally, the effectiveness of the proposed fusion estimation scheme is verified by two examples.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper is concerned with the adaptive event-triggered recursive state estimation (RSE) issue for a class of nonlinear complex dynamical networks (CDNs) with random coupling parameter, missing ...measurements (MMs) and coding-decoding-based communication mechanism (CDBCM). First of all, a random variable uniformly distributed in a fixed interval is adopted to model the varying topologies. Then, the Bernoulli random sequence with uncertain statistical properties is considered to characterize the phenomenon of MMs subject to the uncertain occurrence probability situation. Furthermore, in order to ensure the security and reliability of the shared network channel, the adaptive event-triggered scheduling strategy (AETSS) and CDBCM are both employed to govern the data transmission thereby enhancing the communication quality. The aim of this paper is to present an RSE scheme for a class of stochastic CDNs such that for all MMs, AETSS and CDBCM, the state estimation error covariance (SEEC) is given the SEEC upper bound (SEECUB) is derived. Then, the state estimator gain matrix (SEGM) is parameterized by means of optimizing the trace of SEECUB. Moreover, the monotonicity of the trace of SEECUB with respect to the available missing probability is clarified detailed. Finally, an illustrative simulation is executed for the purpose of verifying the validity of the proposed RSE scheme.
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A novel ratiometric and reversible chemosensor 4-((2-(Benzodthiazol-2-yl)phenyl)ethynyl)-N,N-diethylaniline (BT-1) based on ortho-arylethynyl benzothiazole with large Stokes shift (Δλ≈190 nm) was ...designed and synthesized to recognize Cu2+. Copper ion induces a remarkable fluorescence enhancement and causes formation of a BT-1-Cu complex. The clamp-on coordination mode of BT-1 to Cu2+ was demonstrated using Job's plot, mass spectrum (MS) and DFT calculations. The calculations also indicate that Cu2+ was chelated to BT-1 through N and alkyne instead of S and alkyne. The probe could quantify Cu2+ with the detection limit of 3.2 × 10−9 M. The in vitro imaging results indicated that the probe BT-1 was membrane-permeable and could be applied into the recognition of Cu2+ ions in living cells.
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1.A novel ratiometric and reversible fluorescence probe with a large stokes shift based on a new clamp-on unit.2.It is the first example that utilizes aryl alkyne coordination in the determination of copper ions.3.The probe BT-1 was membrane-permeable and could be applied into the recognition of Cu2+ ions in living cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper is concerned with the dynamic event-triggered set-membership state estimation issue for a class of multirate networked systems subject to unknown but bounded disturbance and noise. To ...economize the limited communication resource when performing the desired networked estimation task, a dynamic event-triggered transmission mechanism is proposed to significantly reduce the frequency of sensor data transmissions. A key issue of the addressed problem is to construct a zonotopic outer approximation set to bound the set of states that are consistent with the disturbed system model and the noisy measured outputs. With the help of a prediction-update-correction method, we design a zonotope that is guaranteed to enclose all possible system states due to the unknown disturbance and noise. Then, the size of such a zonotope is minimized by properly designing an introduced correlation matrix at each iteration. Subsequently, the estimation performance is analyzed under the developed zonotopic estimation method. A sufficient condition is further established to ensure the boundedness of the size of the obtained zonotope. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed method.
•A new zonotopic SMSE problem is studied with multirate strategy and DET mechanisms.•An efficient zonotopic estimation method is proposed to obtain the desired zonotope.•A formal analysis procedure is provided to ensure the boundedness of the zonotope.
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In this paper, the event-based state and unknown input estimation (SUIE) problem is investigated for a class of stochastic systems subject to parameter uncertainties and stochastic nonlinearities. ...For the purpose of reducing the energy consumption in data transmission, an event-triggering protocol is employed to regulate whether the current measurement is transmitted by the sensor. Utilising the event-triggered measurement, a recursive estimator is constructed to concurrently estimate the state and the unknown input. The upper bounds of estimation error covariances are given explicitly for both the state and the unknown input estimates. By means of the completing-the-square technique and Lagrange multiplier method, the estimator gain matrices are designed which minimise the obtained upper bounds. Finally, a numerical example is given to show the effectiveness of the proposed SUIE method.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
Abstract
Fringe projection profilometry (FPP) is a widely used non-contact 3D measurement method. Though maturing in the last decade, it remains a significant challenge when facing the phase ...unwrapping of measured object surfaces in a single-shot measurement setting. With the rapid development of deep learning techniques, the adoption of a data-driven approach is gaining popularity in the field of optical metrology. This study proposes a new absolute phase recovery method based on the devised single-stage deep learning network. The aim is to ensure high-quality absolute phase recovery from a single-shot fringe projection measurement. Unlike most existing approaches, where the numerators and denominators of the wrapped phases and the fringe orders are predicted in various stages, the proposed method acquires the wrapped phases and the corresponding fringe orders within a single network, i.e. it can predict both wrapped phases and the corresponding fringe orders directly and simultaneously from the single fringe pattern projected in the single-shot mode based on a unified Y-shaped network. Experiments on benchmark datasets and models have demonstrated the effectiveness and efficiency of the technique, especially in terms of high-quality recovery of absolute phase information by using the lightweight single-stage network, and enabling the FPP-based phase 3D measurements in an online manner.
In this paper, the recursive filtering problem is considered for stochastic systems over filter-and-forward successive relay (FFSR) networks. An FFSR is located between the sensor and the remote ...filter to forward the measurement. In the successive relay, two cooperative relay nodes are adopted to forward the signals alternatively, thereby existing switching characteristics and inter-relay interferences (IRI). Since the filter-and-forward scheme is employed, the signal received by the relay is retransmitted after it passes through a linear filter, The objective of the paper is to concurrently design optimal recursive filters for FFSR and stochastic systems against switching characteristics and IRI of relays. First, a uniform measurement model is proposed by analyzing the transmission mechanism of FFSR. Then, novel filter structures with switching parameters are constructed for both FFSR and stochastic systems. With the help of the inductive method, filtering error covariances are presented in the form of coupled difference equations. Next, the desired filter gain matrices are further obtained by minimizing the trace of filtering error covariances. Moreover, the stability performance of the filtering algorithm is analyzed where the uniform bound is guaranteed on the filtering error covariance. Finally, the effectiveness of the proposed filtering method over FFSR is verified by a three-order resistance-inductance-capacitance circuit system.
This paper is concerned with the dynamic event-triggered non-fragile H∞ control problem for the body slip angle of electric vehicles subject to parameter variations of vehicle controllers. Dynamics ...of electric vehicles with an onboard vision system is characterized by a linear model in which the body slip angle, the yaw rate, the lateral offset at the preview point and the vehicle heading angle are chosen as state variables. To reduce the energy consumption in signal transmission, a dynamic event-triggering mechanism is adopted to manage the data transmission between sensors and vehicle controllers. Our aim is to design a non-fragile event-triggered controller such that, for all possible parameter variations in controller gains, all the system states are asymptotically stable and the H∞ performance requirement is met. With the help of the Lyapunov theory, an existence condition of the desired controller is established first and then the desired controller gains are designed in terms of a feasible solution to a matrix inequality. Finally, the effectiveness of the proposed non-fragile H∞ control approach is verified in the electric vehicles.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
