科研成果

In this study, three shale samples from the Wolfcamp Formation in Permian basin were selected and studied for creep behavior using two different methods at macro- and micro-scale: triaxial and nanoindentation creep tests. The triaxial creep test showed the effects of axial differential stress on the creep behavior of shale rocks including the strain and contact creep modulus. As the axial differential stress increased, the creep strain value presented an increasing trend. Additionally, based on the grid nanoindentation creep experiments, three different mechanical phases were recognized in these samples; Phase 1: soft mechanical phase, Phase 2: intermediate, and Phase 3: hard mechanical phase. Based on the micro-scale results, at the same creep time periods, phase 1 (clay + organic matter) was found to have a smaller contact creep modulus and larger creep strain value than Phase 3 (quartz). Comparing the results from these two scales of measurements, the contact creep modulus from the triaxial test and the homogenized contact creep modulus from nanoindentation experiments showed some discrepancies. Based on the samples in this study, the contact creep modulus from the triaxial test varied from 0.5 to 4 times the value of the nanoindentation test. The differences between the contact creep modulus from the nanoindentation and triaxial test could be due to the creep strain amplitude. Considering Sample 1 as an example, the creep strain amplitude under the nanoindentation is inferred to be 0.069 which is not equal to the creep strain amplitude from the triaxial test (0.0052 under differential stress of 30 MPa). Ultimately, the contact creep modulus from the nanoindentation can fluctuate based on the samples’ content, while the reason for this is still a question that needs further study. Overall, this study is a preliminary investigation to help us understand how nanomechanical data in complex geomaterials can relate to traditional triaxial data.

The classical gradient-diffusion hypothesis has known deficiencies when applied to cooling applications. In this paper, the gene-expression programming (GEP) method, a machine learning approach, has been applied to develop scalar-flux models via symbolic regression. The scalar-flux, the unclosed term of the mean passive-scalar transport equation, is treated by considering the polynomial basis and scalar invariants available from computable Reynolds-averaged quantities. This method has been applied to develop and then assess a model for the test case of jet in crossflow. A high-fidelity database was first probed for insight into which of the candidate bases are the most suitable as modelling terms. The high dimensionality of the function space, spanned by the basis, was then reduced by basic statistical techniques. The resulting data-driven model is presented and tested for a range of different jet in crossflow cases. Compared with eddy-diffusivity models, the new model is shown to produce reliably more accurate results. This demonstrates that the current framework can be used for scalar-flux modelling in complex three-dimensional flows and has potential to provide generalized form closures with improved predictive accuracy for the same classes of flows they were trained on.

Increased human water use combined with climate change have aggravated water scarcity from the regional to global scales. However, the lack of spatially detailed datasets limits our understanding of the historical water use trend and its key drivers. Here, we present a survey-based reconstruction of China’s sectoral water use in 341 prefectures during 1965 to 2013. The data indicate that water use has doubled during the entire study period, yet with a widespread slowdown of the growth rates from 10.66 km3·y−2 before 1975 to 6.23 km3·y−2 in 1975 to 1992, and further down to 3.59 km3·y−2 afterward. These decelerations were attributed to reduced water use intensities of irrigation and industry, which partly offset the increase driven by pronounced socioeconomic development (i.e., economic growth, population growth, and structural transitions) by 55% in 1975 to 1992 and 83% after 1992. Adoptions for highly efficient irrigation and industrial water recycling technologies explained most of the observed reduction of water use intensities across China. These findings challenge conventional views about an acceleration in water use in China and highlight the opposing roles of different drivers for water use projections.

Thinking tools that assist by externalizing thought processes and conceptual structures so they can be manipulated potentially improve user learning. We propose the design of a sensemaking assistant that integrates many such tools. Our design emerged from an intensive study of sensemaking by users working on real tasks, providing a link from users to developers. Sensemaking is the process of forming meaningful representations and working with them to gain understanding, possibly communicated in a report, to support planning, decision‑making, problem‑solving, and informed action. At the heart of our design is a set of tightly integrated tools for representing and manipulating a conceptual space: tools for producing and maintaining concept maps, causal maps/influence diagrams, argument maps, with support through self-organizing semantic maps, importing concepts and relationships from external Knowledge Organization Systems, and inferring connections between texts; further a tool for organizing information items (documents, text passages notes, images) linked to the concept map. The sensemaking assistant we envision guides users through the sensemaking process; for each function it suggests appropriate cognitive processes and provides tools that automate tasks. The comprehensive sensemaking model introduced in specifies functions in the iterative process of sensemaking: Task analysis and planning; Gap identification (tools for both: brainstorming, finding documents on the task); information acquisition, data seeking and structure seeking (search tool: finding databases, query expansion, passage retrieval; summarization tool); information organization, building structure, instantiating structure, information synthesis / new ideas / emerging sense (conceptual space tools mentioned above); information presentation, creating reports (from concept map to outline, guide through the writing process, analyze draft writing for coherence and clarity). The system tracks sources. Users using a sensemaking assistant may well internalize good ways for intellectual processes and good conceptual organization in addition to learning a useful application. The paper will provide some evidence from the literature and propose further testing.

Based on the concepts of “ancient China studies” and “digital humanities” (DH) in the context of China, this paper first gives a brief review on the development and practice of DH cyberinfrastructure. Under a series of reflections and a brief investigation on ancient Chinese literatures and traditional humanistic activities, this paper puts forward a new DH cyberinfrastructure conceptual model for ancient China studies that can bring people, information, and computational tools together and allow humanistic scholars to perform in a new way and with higher efficiency. On the premise of actual practices to turn a conceptual model into reality, this paper discusses DH cyberinfrastructure and the future of academic libraries.