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This paper addressed the flexural behaviour (i.e., maximum load, ductility index, flexural strength and stiffness) of laminated veneer lumber (LVL) beams strengthened by 2-layer flax-glass hybrid fibre reinforced polymer (HFRP) exposed to hygrothermal (50℃ and 95% RH) and weathering (cyclic water spray-ultraviolet radiation) conditions for one month. Effects of environmental exposure and fabric sequences on flexural behaviour of LVL-HFRP beams were studied. LVL-FG and LVL-GF beams (inner plies bonded to LVL were flax and glass fibres, respectively) were tested under four-point bending. Tensile test on HFRP flat coupons was also conducted to provide the tensile parameters of HFRP in LVL-HFRP beams. This study showed that the hygrothermal and weathering exposures reduced the maximum load (by 11.4-32.2%), flexural strength (by 19.1-40.0%) and increased the ductility index (by 18.3-41.7%) of LVL-HFRP beams. The hygrothermal exposure did not affect flexural stiffness. The fabric sequence affected the flexural behaviour of LVL-HFRP beams. LVL-GF beams showed lower maximum load and flexural strength than those of the LVL-FG beams, which was attributed to the HFRP delamination in the LVL-GF beams. A theoretical prediction model for the ultimate bending moments of LVL-HFRP beams was used, and the calculated values showed a good agreement with the experiments.

For solving the discretized three-temperature energy linear systems, Xu et al. proposed a physical-variable based coarsening two-level iterative method (PCTL algorithm) in 2009 and verified its efficiency by numerical experiments in practical applications. In this paper, we study in detail the specific convergence property of the PCTL algorithm based on the theory of algebraic multigrid method (AMG),and give a reasonable upper bound on the convergence factor, which provides a theoretical guarantee for the PCTL algorithm. Moreover, we also analyse the algebraic features that affect the convergence of the PCTL algorithm, such as diagonal dominance and coupling strength, hoping provides theoretical guidance for the applications and algorithm optimization of the PCTL algorithm., Comment: 18 pages, 4 figures

In this paper, single-lap shear tests were performed to investigate the bond behaviour between flax-glass hybrid fibre reinforced polymer composite (HFRP) and laminated veneer lumber (LVL) joints. Epoxy was used as polymer matrix of the HFRP and adhesive to bond LVL and HFRP to be joints. Digital image correlation (DIC) technique was used to measure the strain distribution of the LVL-HFRP joints for determining their bond-slip relationship. The effects of fibre fabric sequence of the HFRP and bond length on average shear strength, maximum shear stress, bond-slip relationship and fracture energy of the LVL-HFRP joints were evaluated. The test results showed that the bond length had a significant influence on the average shear strength, i.e., as the bond length increased, the average shear strength of the joints decreased. The fibre fabric stacking sequence of HFRP also affected the bond behaviour of the joints significantly at a bond length of 200 mm. It was found that the specimens of LVL bonded with flax fabric layer of HFRP had higher average shear strength, maximum shear stress and interfacial fracture energy than the LVL joints bonded with the glass fabric layer of HFRP.

Distributed optical fiber temperature sensing technology has the potential to be used to determine the cast-in-situ pile integrity. This study proposed an arrangement of optical fibers for obtaining the pile integrity in situ, and it provided a calculation model for the temperature distribution. A model pile was constructed with the dimensions of 1.5 m × 0.5 m × 0.5 m. The fibers were implanted parallel to the center axis of the pile with a spacing of 0.04 m. The heat conduction area generated because of the heating of the fiber in the center of the pile was tested. The test results indicated that the heating conduction area was limited for certain heating powers. Furthermore, for the heating conduction area and heating power, care must be taken while arranging the optical fibers in the piles to determine the integrity.

Composite materials, which consist of at least two components (i.e., reinforcement and matrix), have been widely applied in modern industries such as aviation, construction, and automotive engineering. The interphase between reinforcements and the matrix is critical to the overall performance of resulting composite materials because it transfers stress from the matrix to reinforcements. In this chapter, various reinforcement and matrix materials and their composites are introduced. The mechanisms of forming interphase between reinforcements and matrices are elaborated based on the adhesion theory. Several conventional interphases of composite materials, such as fiber/metal, fiber/ceramic, and fiber/polymer interphases are discussed in detail. The microstructures of the interphase and their correlation to resulting mechanical properties are also presented. Finally, future research trends in this field are summarized for the prospects and advances in composite interphase.

Snow-melting pavement with electric heating pipes (SMP-EHP) is used to mitigate the accumulated snow problem for large longitudinal slopes or slippery roads. To improve its operation efficiency, the structural model and thermal simulations of the SMP-EHP were studied. The electric heating pipe’s embedded spacing (s) and embedded depth (d), the heating power (P) and the wind velocity (v) were considered as the input parameters. The total heating time (THT) and the lost energy rate (LER) for the melting process were considered as the prediction responses. The prediction models for THT and LER were proposed by using Response Surface Methodology (RSM). The single input parameter’s effects on prediction responses and the interactions between them were analyzed by the assisted thermal simulation. The rationality of the prediction models and simulations were validated by statistical analysis and experiments. Additionally, for decreasing THT, LER, a multi-objective optimization on THT and the lost energy (LE) was built through the genetic algorithm. Through optimization, the recommended parameters are proposed. The results and suggestions could efficiently guide the operation of SMP-EHP.

The method of ice-snow melting pavement (ISMP) with electric heating pipes is presented to achieve the purpose of environmental protection, intelligence, and high efficiency. In order to determine the thermal field of the ISMP and prejudge the feasibility of heating schemes, two thermal field prediction models are proposed in this paper. The one is a theory model based on line heat source theory and virtual image method, the other is a semi-empirical formula based on theory model and experiment discussion. The effectiveness of the two models is verified by the heating experiment results of concrete slabs with electric heating pipes. Differences and advantages in the two models are compared. In summary, the theory model has the wider range of applications than the semi-empirical formula, but the semi-empirical formula is closer to the practice, and easier to conduct calculation than the theory model.

The automatically snow-melting system with the electric heating pipes (AS-EHP) is applied in infrastructures (concrete pavement, parking apron, garage entrances and municipal road) in cold regions to mitigate the accumulated snow problem. In order to reduce the energy consumption (EC) and improve the energy utilization rate (EUR) of AS-EHP, the analysis about EC and EUR is investigated. The melting process of AS-EHP is divided into two phases which include preheating the infrastructures and melting. The influence and sensitivity analysis between the inputs (the pipes' embedded spacing and embedded depth, heating power and wind velocity) and the outputs (EC and EUR) are found and compared in two phases by thermal simulation. The applicability and rationality of the simulation are verified by snow melting experiments. According to the simulation, decreasing embedded spacing and depth in phase 1 and phase 2 could reduce EC and improve EUR. In the two phases, the heating power is suggested to be 100 W/m-140 W/m under the condition that the heating pipe’ embedded spacing is 0.10 m–0.25 m, the depth is 0.06 m–0.12 m, and the wind velocity is 0 m/s–15 m/s. The results and suggestions could be used to efficiently guide the scheme design and operation control of AS-EHP in infrastructures.

The equivalent plasticity strain (EPS) of snow-melting heated pavement concrete that exposed to inner elevated temperatures is analyzed with finite element simulations. An optimal mix proportion of the concrete with high thermal conductivity was obtained through mechanical and thermal experiments, which helps facilitate reducing the damage in snow-melting pavement. A three-dimensional (3D) finite element model is developed based on the concrete damage plastic (CDP) model with parameters. The EPS is considered as the performance evaluation index for damage in snow-melting heated pavement concrete. Based on the results of finite element simulations, the EPS of snow-melting heated pavement concrete that exposed to inner elevated temperatures was analyzed under different pavement structures and external conditions. Furthermore, two EPS prediction models were proposed: the one is for EPS and the inner elevated temperature, the other is for EPS and five key factors. The outputs of 3D finite element simulations were verified by an experiment result. It indicated that numerical results agreed with experimental results very well. A prediction and evaluation method of damage for snow-melting heated pavement concrete was established as well.

A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters. Given a set of configurations and a large dataset randomly split into training and testing set, we study how to efficiently select the best configuration with approximately the highest testing accuracy when trained from the training set. To guarantee small accuracy loss, we develop a solution using confidence interval (CI)-based progressive sampling and pruning strategy. Compared to using full data to find the exact best configuration, our solution achieves more than two orders of magnitude speedup, while the returned top configuration has identical or close test accuracy., Comment: Full version of an AAAI 2019 conference paper

Distributed optical fiber sensors based on Brillouin scattering are emerging as valid alternatives for monitoring the health of civil structures and applications in geological engineering. The measurements are made by establishing a correlation between fiber strain and temperature in the frequency shift of Brillouin backscattered light induced by a monochromatic light pulse. The monitored strain consists of two parts: stress strain and temperature strain. This article presents an application of Brillouin optical time domain reflectometry in measuring stabilizing pile deformation over time. In the process of pile construction, the hydration heat of cement raises the temperature of the pile, thus causing errors in pile strain monitoring. So, the effect of temperature on strain should be considered. A finite element model built on the basis of monitoring objects and their geological environment is proposed to eliminate the influence of hydration heat on pile strain. The results indicated that the changed temperature resulting from hydration takes approximately three months to reach the same level as the ground temperature, in agreement with the monitoring results. The magnitude of the relative strain caused by hydration temperature was on the order of 10−4 microns and should be considered in the three-month monitoring data after the construction of piles. Factors that may affect calculation accuracy are discussed on the basis of the experimental and numerical results.

The relative ease of collaborative data science and analysis has led to a proliferation of many thousands or millions of versions of the same datasets in many scientific and commercial domains, acquired or constructed at various stages of data analysis across many users, and often over long periods of time. Managing, storing, and recreating these dataset versions is a non-trivial task. The fundamental challenge here is the storage-recreation trade-off: the more storage we use, the faster it is to recreate or retrieve versions, while the less storage we use, the slower it is to recreate or retrieve versions. Despite the fundamental nature of this problem, there has been a surprisingly little amount of work on it. In this paper, we study this trade-off in a principled manner: we formulate six problems under various settings, trading off these quantities in various ways, demonstrate that most of the problems are intractable, and propose a suite of inexpensive heuristics drawing from techniques in delay-constrained scheduling, and spanning tree literature, to solve these problems. We have built a prototype version management system, that aims to serve as a foundation to our DataHub system for facilitating collaborative data science. We demonstrate, via extensive experiments, that our proposed heuristics provide efficient solutions in practical dataset versioning scenarios.

Organizations and teams collect and acquire data from various sources, such as social interactions, financial transactions, sensor data, and genome sequencers. Different teams in an organization as well as different data scientists within a team are interested in extracting a variety of insights which require combining and collaboratively analyzing datasets in diverse ways. DataHub is a system that aims to provide robust version control and provenance management for such a scenario. To be truly useful for collaborative data science, one also needs the ability to specify queries and analysis tasks over the versioning and the provenance information in a unified manner. In this paper, we present an initial design of our query language, called VQuel, that aims to support such unified querying over both types of information, as well as the intermediate and final results of analyses. We also discuss some of the key language design and implementation challenges moving forward., Comment: Theory and Practice of Provenance, 2015

A temporal graph is a graph in which connections between vertices are active at specific times, and such temporal information leads to completely new patterns and knowledge that are not present in a non-temporal graph. In this paper, we study traversal problems in a temporal graph. Graph traversals, such as DFS and BFS, are basic operations for processing and studying a graph. While both DFS and BFS are well-known simple concepts, it is non-trivial to adopt the same notions from a non-temporal graph to a temporal graph. We analyze the difficulties of defining temporal graph traversals and propose new definitions of DFS and BFS for a temporal graph. We investigate the properties of temporal DFS and BFS, and propose efficient algorithms with optimal complexity. In particular, we also study important applications of temporal DFS and BFS. We verify the efficiency and importance of our graph traversal algorithms in real world temporal graphs.

As computer clusters are found to be highly effective for handling massive datasets, the design of efficient parallel algorithms for such a computing model is of great interest. We consider (��, k)-minimal algorithms for such a purpose, where �� is the number of rounds in the algorithm, and k is a bound on the deviation from perfect workload balance. We focus on new (��, k)-minimal algorithms for sorting and skew equijoin operations for computer clusters. To the best of our knowledge the proposed sorting and skew join algorithms achieve the best workload balancing guarantee when compared to previous works. Our empirical study shows that they are close to optimal in workload balancing. In particular, our proposed sorting algorithm is around 25% more efficient than the state-of-the-art Terasort algorithm and achieves significantly more even workload distribution by over 50%., 18 pages