To properly control the reaction kinetics and fresh properties evolution in conventional alkali-activated materials (AAMs), a conceptual design of two-stream AAMs has been proposed in this study. This is achieved by dividing the solid and liquid components in AAMs, including blast furnace slag (BFS) and electric arc furnace slag (EFS) precursors, as well as aqueous sodium hydroxide and silicate activators into two separate streams A and B, where a very limited reactivity is expected in individual streams to ensure sufficient workability retention. Moreover, a final-stage intermixing is required to combine individual stream mixtures and trigger the major activation reaction. Fresh and hardened properties of combined mixtures were checked at different stages. The microstructure and reaction products were investigated to understand the strength development. Low dynamic rheological parameters and good workability retention have been detected in all individual stream mixtures, accompanied by limited exothermic heat flows after the initial dissolution confirmed by calorimetry tests. Further, Portland cement (PC) is partially blended into stream A to alter the early stiffening process in combined mixtures and meet various setting demands after intermixing. However, this might lead to a reduction in mechanical properties, associated with the formation of porous microstructures and an increase in the Ca/Si ratio in reaction products. Eventually, the conceptual design is validated in different scenarios including self-compacting and 3D-printing concrete applications.

In this work, we present a mass, energy, enstrophy and vorticity conserving (MEEVC) mixed finite element discretization for two-dimensional incompressible Navier-Stokes equations as an alternative to the original MEEVC scheme proposed in A. Palha and M. Gerritsma (2017) [5]. The present method can incorporate general boundary conditions. Conservation properties are proven. Supportive numerical experiments with both exact and inexact quadrature are provided.

In isogeometric analysis, constructing bijective and low-distorted parameterizations is a fundamental task. Compared with the planar problem, the volumetric case is more challenging in both robustness and efficiency. In this paper, we present a robust and efficient volumetric parameterization method based on the idea of penalty functions and the Jacobian regularization technique. The proposed method does not require an already bijective initialization and thus avoids an extra foldover elimination step. The main contributions of this work lie in three aspects. First, a new objective function that characterizes the volume distortion is established using the Divergence Theorem. Second, we employ a novel penalty function for the Jacobian regularization. The full analytical gradient of the objective function is also deduced to enhance the numerical stability in gradient-based optimization. Third, we develop a reduced numerical integration strategy to accelerate the new algorithm. Several numerical examples demonstrate that our method significantly outperforms the current competitive approaches both in terms of robustness and efficiency.

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines.

In this paper, we will show that the equivalence of a div-grad Neumann problem and a grad-div Dirichlet problem can be preserved at the discrete level in 3-dimensional curvilinear domains if algebraic dual polynomial representations are employed. These representations will be introduced. Proof of the equivalence at the discrete level follows from the construction of the algebraic dual representations. A 3-dimensional test problem in curvilinear coordinates will illustrate this approach.

Prevention of mechanical and finally electrochemical failures of lithium batteries is a critical aspect to be considered during their design and performance, especially for those with high specific capacities. Internal failure is observed as one of the most serious factors, including loss of electrode materials, structure deformation and dendrite growth. It usually incubates from atomic/molecular level and progressively aggravates along with lithiation. Understanding the internal failure is of great importance for developing solutions of failure prevention and advanced anode materials. In this research, different internal failure processes of anode materials for lithium batteries are discussed. The progress on observation technologies of the anode failure is further summarized in order to understand their mechanisms of internal failure. On top of them, this review aims to summarize innovative methods to investigate the anode failure mechanisms and to gain new insights to develop advanced and stable anodes for lithium batteries.

To meet the high temperature and anti-reveling properties required in open-graded friction course, high content polymer modified asphalt (HCPMA) is gradually widely used in China, but the rheological, chemical and aging characteristic is not clear yet. In this paper, HCPMA with different SBS content and different base asphalt are prepared, and Pressure Aging Vessel (PAV) aging was conducted to simulate the long-term aging condition. The chemical and rheological evaluation of HCPMA before and after aging were tracked with Fourier transform infrared, gel permeation chromatography test, dynamic shear oscillatory test, master curve and multiple stress creep and recovery test. The results show that firstly, the aging of HCPMA is combined with hardening of asphalt and degradation of Styrene–butadiene–styrene (SBS) polymer. Furthermore, the addition of high content of SBS polymer can reduce the formation of carbonyl, but the degradation rate of SBS polymer is not related to the content of SBS or the type of base asphalt. Besides, HCPMA with a higher SBS content will have better rheological properties, but in consideration of economy, 9% is optimum dosage. At last, HCPMA prepared with Esso asphalt as base binder exhibits better rheological properties than HCPMA prepared with SK asphalt. However, the rheology difference reduces with the increase of SBS content and after PAV aging.

While some studies have observed the beneficial impact of mergers and acquisitions (M&As) on a firm's innovation performance in developed countries, others have found the consequences to be neutral or even negative. This article develops an integrated framework to elucidate how the combination of technological relatedness and product relatedness between acquiring and target firms affects post-innovation performance of technology-driven M&As. This performance is investigated by using a set of parameters, namely R&D input, patent and product activity, and the financial results from commercialisation. We conducted case studies on China's high-tech firms derived from three diverse industry sectors, and the empirical results indicate that both types of relatedness between the partners of technology-driven M&As are conducive to the intensification of R&D expenditures. The acquisition of similar technologies and products has more significant effects on R and D input and output, and M&As without technology relatedness have better financial performance, since they lead acquirers to new technology sectors or sub-sectors. In comparison, M&As with technological complementarity and product complementarity have negative effects on related innovation processes in the short term.

What are the implications of big data in terms of big impacts? Our research focuses on the question, 'How are data analytics involved in policy analysis to create complementary values?' We address this from the perspective of bibliometrics. We initially investigate a set of articles published in Nature and Science, seeking cutting-edge knowledge to sharpen research hypotheses on what data science offers policy analysis. Based on a set of bibliometric models (e.g., topic analysis, scientific evolutionary pathways, and social network analysis), we follow up with studies addressing two aspects: (1) we examine the engagement of data science (including statistical, econometric, and computing approaches) in current policy analyses by analyzing articles published in top-level journals in the areas of political science and public administration; and (2) we examine the development of policy analysis-oriented data analytic models in top-level journals associated with computer science (including both artificial intelligence and information systems). Observations indicate that data science contribution to policy analysis is still an emerging area. Data scientists are moving further than policy analysts, due to technical difficulties in exploiting data analytic models. Integrating artificial intelligence with econometrics is identified as a particularly promising direction.