Search results

This paper aims to study the performance of hydrostatic turntables by using fluid structure interaction (FSI) and thermal effect coupled model.

A novel fluid-structure-thermal coupled model is set up to study the problem. The FSI technique and computational fluid dynamics (CFD) method are used by this new model, and the thermal effects are also considered. Hydrostatic turntables with different system parameters (oil supply pressure, oil recess depth and surface roughness) are studied under different working conditions (rotational speeds of turntable and exerted external loads). Performance characteristics obtained from this FSI-thermal coupled model and conventional model are presented and compared.

Theoretical predictions are in good agreement with the experimental data. The results of new FSI-thermal coupled model are more accurate than those of the old conventional model. To acquire better performance of the system, the novel FSI-thermal model becomes necessary for different hydrostatic turntable systems.

This developed model is a useful tool for studying hydrostatic turntables. To get an improved performance, a proper selection of design parameters of the system based on FSI-thermal model is essential.

Fabric has complicated anisotropic mechanical behavior because of the woven pattern and complex physical properties. However, most current fabric simulation models are not satisfied because the models are usually geometrical models with stiffness parameters.

In this paper, the authors present a modeling technique to simulate fabric with Riemann manifold. The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area. It decomposes the m × n matrix constituting the fabric into several batches and processes the fabric dots in batches. In this model, the distance between any two adjacent particles of the fabric's is assumed to be equal, and the area of the curved surface is always constant, and the inclination and decay of the ridge wave-curved surface are also considered.

As the result, the simulated shape is lifelike. In time cost performance, the model improves the efficiency of the fabric styling and meets the requirements of real-time simulation.

The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area.

The partition of unity of the standard meshless Galerkin method is used as basis in expressing the discontinuity of the contact surface displacement, particularly by adding discontinuous terms into the displacement mode, and constructing the discontinuous meshless displacement field function. In this study the contact surface equation is aimed to derive from the improved Coulomb friction contact model.

In this paper based on the basic idea of meshless method, an improved moving least squares approximation function (expansion method based on out of unit division) is applied to the analysis of two-dimensional contact problems.

On the basis of this equation after discrete processing, it is combined with the discrete form of the virtual work equation with added contact conditions, and eventually transformed into a standard linear complementary problem. Moreover, it is solved by using the Lemke algorithm, and a corresponding example is provided in this research.

The proposed method can effectively control the mutual embedding of the contact surface, and the stress distribution that is the same as the actual situation can be obtained on the contact surface.

This paper aims to provide a fabrication and measurement of a highly stretchable pressure sensor with a “V-type” array microelectrode on a grating PDMS substrate.

First, the “V-type” array structure on the silicon wafer was fabricated by the MEMS technology, and the fabrication process included ultra-violet lithography and silicon etching. The “V-type” array structure on the master mold was then replicated into polycarbonate, which served as an intermediate, negative mold, using a conventional nanoimprint lithography technique. The negative mold was subsequently used in the PDMS molding process to produce PDMS “V-type” array structures with the same structures as the master mold. An Ag film was coated on the PDMS “V-type” array structure surface by the magnetron sputtering process to obtain PDMS “V-type” array microelectrodes. Finally, a PDMS prepolymer was prepared using a Sylgard184 curing agent with a weight ratio of a 20:1 and applied to the cavity at the middle of the two-layer PDMS “V-type” array microelectrode template to complete hot-press bonding, and a pressure sensor was realized.

The experimental results showed that the PDMS “V-type” array microelectrode has high stretchability of 65 per cent, temperature stability of 0.0248, humidity stability of 0.000204, bending stability and cycle stability. Capacitive pressure sensors with a “V-type” array microelectrode exhibit ideal initial capacitance (111.45 pF), good pressure sensitivity of 0.1143 MPa-1 (0-0.35 Mpa), fast response and relaxation times (<200 ms), high bending stability, high temperature/humidity stability and high cycle stability.

The PDMS “V-type” array structure microelectrode can be used to fabricate pressure sensors and is highly flexible, crack-free and durable.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

Library science and information science, two subdisciplines of library and information science (LIS), are developed independently but interconnectedly. In this information age, LIS is in a special period of transformation and development, which has caused some changes in both library science and information science. By accurately capturing these changes and analyzing them, the authors can effectively map the development of LIS in the new century, thus providing a reference for the evolution and development of the field. The purposes of this paper are to explore the mainstream research fields and frontiers of library science and information science, respectively, since the new century, and to make a comparative analysis of the two subdisciplines.

By using CiteSpace to visualize LIS journals, this study draws knowledge maps of the two subdisciplines of LIS through the co-occurrence descriptors network. Using burst detection algorithm, this study detects words of high frequency variation by investigating the time frequency distribution.

The results show that the research focus of library science has experienced a change from traditional to digital library while information science has moved from information to data focus. This study also finds the similarities and differences between mainstream areas of library science and information science.

This study focuses on the evolution of library science and information science, and explores their mainstream research fields and frontiers in the 21st century. These findings will promote the transformation and development of LIS as well as provide research directions for scholars in the field.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

This paper aims to explore coopetition within the entrepreneurial ecosystem and answer the following two fundamental questions: How does coopetition affect the entrepreneurial learning and performance of startups? and What learning strategies should startups adopt to promote their growth in the coopetition activities?

Using the structural equation model and instrumental variable, this study used a sample of 371 startups to test the hypotheses. Data comes from startups in Jiangsu, Shanghai and Zhejiang, China.

This study finds that the coopetition-performance relationship of startups is marginally negative. This study also finds that exploitative learning and exploratory learning positively mediate this relationship. Ecosystem’s social capital can enhance the coopetition-exploration relationship, but the coopetition-exploitation relationship is not affected.

Many studies propose that the coopetition-performance relationship is ambiguous, which makes it meaningful to explore startups individually. Based on the resource-based view and the knowledge-based view, this study deepen the works of Bouncken and Fredrich (2016c), that is, how startups can learn and grow through coopetition activities. This study proposes that coopetition is one of the foundations of the ecosystem and explore the coopetition-performance relationship in this special context. Thus, the present paper adds to the budding literature on the effects of the entrepreneurial ecosystem and to the literature on coopetition.

The purpose of this study is to construct a Chinese information science resource ontology and to explore a new method for semiautomatic ontology construction.

More than 8,290 articles indexed in the Chinese Social Science Citation Index (CSSCI), covering the years 2001 to 2010, were included in this study. Statistical analysis, co-occurrence analysis, and semantic similarity methods were applied to the selected articles. The ontology was built using existing construction principles and methods, as well as categories and hierarchy definitions based on CSSCI indexing fields.

Seven categories were found to be relevant for the Chinese information science resource ontology, which, in this study, consists of a three-tier architecture, 78,291 instances, and 182,109 pairs of semantic relations. These results indicate the following: further improvements are required in ontology construction methods; resource ontology is a breakthrough concept in ontology studies; the combination of semantic similarities and co-occurrence analysis can quantitatively describe relationships between concepts.

This study pioneers the resource ontology concept. It is one of the first to combine informetric methods with semantic similarity to reveal deep relationships in textual data.

The purpose of this paper is to present a bibliometric analysis of scientific output of the knowledge management (KM), the aim being to offer an overview of research activity in this field and characterize its most significant aspects. In addition, this study aims to quantitatively analyze KM research trends, forecasts, and citations from 1993 to 2012 in Web of Science (WOS).

A total of 12,925 documents related to KM research were collected from following databases: Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citation Index, Conference Proceedings Citation Index-Science, and Conference Proceedings Citation Index-Social Science & Humanities. These documents were carefully reviewed and subjected to bibliometric data analysis techniques.

A number of research questions pertaining to patterns in scientific outputs, subject categories and major journals, author keywords frequencies, characteristics of the international collaboration, most cited papers and significant papers distribution of KM research were proposed and answered. In addition, there are five research sights on KM research are as follows: management science, computer science, information science, business, and engineering. Based on these findings, many implications emerged that improve one's understanding of the identity of KM as a distinct multi-discipline scientific field.

Comprehensiveness and inclusiveness of the analyzed KM-related data set in WOS because of some KM-centric journals are not indexed by Thomson Reuters.

The paper offers an overview and evaluation of research activity into the KM viewed through the WOS during 1993-2012.