The tensile stress–strain response of a fiber reinforced concrete dominates the performance under many loading conditions and applications. To represent this property as an average equivalent response, a back-calculation process from flexural testing is employed. The procedure is performed by model fitting of the three-point and four-point bending load deflection data on two types of macro synthetic polymeric fibers, one type of steel fiber and one type of Alkali Resistant (AR) glass fiber. A strain softening tensile model is used to simulate the behavior of different FRC types and obtain the experimental flexural response. The stress–strain model for each age, fiber type and dosage rate is simulated by means of the inverse analysis procedure, using closed-form moment–curvature relationship and load–deflection response of the piecewise-linear material. The method of approach is further applied to one external data set for High Performance Fiber Reinforced Concrete (HPFRC) with two different types of steel fibers and validated by tensile test results reported. Results of back-calculation of stress–strain responses by tri-linear tensile model for all mixtures are compared and correlated with the corresponding standard method parameters used for post crack behavior characterization and a regression analysis for comparative evaluation of test data is presented.
This paper focuses on the factors influencing Energy Management Behaviour (EMB) at the individual level. By reviewing academic literature, conducting surveys in Beijing, Shanghai and Guangzhou, the author builds an integrated behavioural energy management model of the Chinese energy consumers. This paper takes the vague term of EMB and redefines it as a function of two separate behavioural concepts: Energy Management Intention (EMI), and the traditional Energy Saving Intention (ESI).
Secondly, the author conducts statistical analyses on these two behavioural concepts. EMI is the main driver behind an individual’s EMB. EMI is affected by Behavioural Attitudes, Subjective Norms, and Perceived Behavioural Control (PBC). Among these three key factors, PBC exerts the strongest influence. This implies that the promotion of the energy management concept is mainly driven by good application user experience (UX). The traditional ESI also demonstrates positive influence on EMB, but its impact is weaker than the impacts arising under EMI’s three factors. In other words, the government and manufacturers may not be able to change an individual's energy management behaviour if they rely solely on their traditional promotion strategies. In addition, the study finds that the government may achieve better promotional results by launching subsidies to the manufacturers of these kinds of applications and smart appliances.
First, I propose a surface fluid registration system, which extends the traditional image fluid registration to surfaces. With surface conformal parameterization, the complexity of the proposed registration formula has been greatly reduced, compared to prior methods. Inverse consistency is also incorporated to drive a symmetric correspondence between surfaces. After registration, the multivariate tensor-based morphometry (mTBM) is computed to measure local shape deformations. The algorithm was applied to study hippocampal atrophy associated with Alzheimer's disease (AD).
Next, I propose a ventricular surface registration algorithm based on hyperbolic Ricci flow, which computes a global conformal parameterization for each ventricular surface without introducing any singularity. Furthermore, in the parameter space, unique hyperbolic geodesic curves are introduced to guide consistent correspondences across subjects, a technique called geodesic curve lifting. Tensor-based morphometry (TBM) statistic is computed from the registration to measure shape changes. This algorithm was applied to study ventricular enlargement in mild cognitive impatient (MCI) converters.
Finally, a new shape index, the hyperbolic Wasserstein distance, is introduced. This algorithm computes the Wasserstein distance between general topological surfaces as a shape similarity measure of different surfaces. It is based on hyperbolic Ricci flow, hyperbolic harmonic map, and optimal mass transportation map, which is extended to hyperbolic space. This method fills a gap in the Wasserstein distance study, where prior work only dealt with images or genus-0 closed surfaces. The algorithm was applied in an AD vs. control cortical shape classification study and achieved promising accuracy rate.
Unidirectional glass fiber reinforced polymer (GFRP) is tested at four initial strain rates (25, 50, 100 and 200 s-1) and six temperatures (−25, 0, 25, 50, 75 and 100 °C) on a servo-hydraulic high-rate testing system to investigate any possible effects on their mechanical properties and failure patterns. Meanwhile, for the sake of illuminating strain rate and temperature effect mechanisms, glass yarn samples were complementally tested at four different strain rates (40, 80, 120 and 160 s-1) and varying temperatures (25, 50, 75 and 100 °C) utilizing an Instron drop-weight impact system. In addition, quasi-static properties of GFRP and glass yarn are supplemented as references. The stress–strain responses at varying strain rates and elevated temperatures are discussed. A Weibull statistics model is used to quantify the degree of variability in tensile strength and to obtain Weibull parameters for engineering applications.