Numerical Simulation of Low Reynolds Number Fluid-Structure Interaction with Immersed Boundary Method

AbstractThis article introduces a numerical scheme on the basis of semi-implicit method for pressure-linked equations (SIMPLE) algorithm to simulate incompressible unsteady flows with fluid-structure interaction. The Navier-Stokes equation is discretized spatially with collocated finite volume method and Eulerian implicit method in time domain. The hybrid method that combines immersed boundary method (IBM) and volume of fluid (VOF) method is used to deal with rigid body motion in fluid domain. The details of movement of immersed boundary (IB) and calculation of VOF are also described. This method can be easily applied to any existing finite-volume-based computational fluid dynamics (CFD) solver without complex operation, with which fluid flow interaction of arbitrarily complex geometry can be realized on a fixed mesh. The method is verified by low Reynolds number flows passing both stationary and oscillating cylinders. The drag and lift coefficients acquired by the study well accord with other published results, which indicate the reasonability of the proposed method

Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning

Recent advancements enlarge the capabilities of large language models (LLMs) in zero-shot image-to-text generation and understanding by integrating multi-modal inputs. However, such success is typically limited to English scenarios due to the lack of large-scale and high-quality non-English multi-modal resources, making it extremely difficult to establish competitive counterparts in other languages. In this paper, we introduce the Ziya-Visual series, a set of bilingual large-scale vision-language models (LVLMs) designed to incorporate visual semantics into LLM for multi-modal dialogue. Composed of Ziya-Visual-Base and Ziya-Visual-Chat, our models adopt the Querying Transformer from BLIP-2, further exploring the assistance of optimization schemes such as instruction tuning, multi-stage training and low-rank adaptation module for visual-language alignment. In addition, we stimulate the understanding ability of GPT-4 in multi-modal scenarios, translating our gathered English image-text datasets into Chinese and generating instruction-response through the in-context learning method. The experiment results demonstrate that compared to the existing LVLMs, Ziya-Visual achieves competitive performance across a wide range of English-only tasks including zero-shot image-text retrieval, image captioning, and visual question answering. The evaluation leaderboard accessed by GPT-4 also indicates that our models possess satisfactory image-text understanding and generation capabilities in Chinese multi-modal scenario dialogues. Code, demo and models are available at ~\url{https://huggingface.co/IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1}

An improved viscous/acoustic splitting method by analyzing source effects

The origin and effect of each term in the equations of the viscous/acoustic splitting (VAS) method are studied in this paper. With its rigorous mathematical derivation, the VAS method could be an improved version of Lighthill’s acoustic analogy method (referred to here as the ILAA method). The ILAA method contains a new monopole acoustic source due to the time derivative of the incompressible pressure and a modified quadrupole acoustic source due to the increment in momentum flux and viscous stress from the compressible/incompressible flow. Based on the incompressible Navier–Stokes equations, the VAS method is also considered as an ILAA method in which the quadrupole acoustic source is due to the compressible momentum flux, compressible viscous stress and the incompressible pressure. A source decomposition method is proposed by which the sound waves are sorted by the source terms. We analyze the effects of each source in the VAS method and propose an improved VAS (IVAS) method by distinguishing between an unstable source and acoustic radiation sources. Using the IVAS method suppresses the pseudo-sound waves that are excited by the additional unstable source that is generated by the waves spreading in a non-uniform velocity field, and the radiating quadrupole source in the ILAA method (VAS method) is retained to the utmost extent

Modeling the Data Provenance of Relational Databases Supporting Full-Featured SQL and Procedural Languages

Data provenance is information about where data come from (provenance data) and how they transform (provenance transformation). Data provenance is widely used to evaluate data quality, trace errors, audit data, and understand references among data. Current studies on data provenance in relational database management systems (RDBMS) still have limitations in supporting full-featured SQL or procedural languages. With these challenges in mind, we present a formal definition of provenance data and provenance transformation for relational data. Then, we propose a solution to support data provenance in relational databases, including provenance graphs and provenance routes. Our method not only solves the complicated problem of modeling provenance in DBMS but also is capable of extending procedural languages in SQL. We also present ProvPg, a PostgreSQL-based prototype database system supporting data provenance in multiple granularities. ProvPg implements extraction, calculation, query, and visualization of provenance. We perform TPC-H tests for ProvPg and PostgreSQL, respectively. Experimental results show that ProvPg addresses the vision of supporting data provenance with little extra computation overhead for the execution engine, which indicates that our model is applicable to lineage tracing applications

A Four-Hierarchy method for the design of organic Rankine cycle (ORC) power plants

In this paper, a practical and general-adapted optimization and decision-making method is proposed for thermal systems designed for a wide range of energy field regarding organic Rankine cycle and thermodynamic cycles. This method is composed of four progressive hierarchies including modelling, optimization, scheme comparison and decision-making. To demonstrate the Four-Hierarchy method, performance of a basic trans-critical ORC and a recuperative trans-critical ORC are analyzed and compared. The NSGA-II algorithm is adopted to obtain the Pareto optimal frontier. Four decision-making methods which are Shannon Entropy, modified LINMAP, TOPSIS and TLFDM are applied for evaluating the Pareto set points. Furthermore, the final Pareto-optimal solution is determined by the root-mean-square difference, correlation coefficient and standard deviation in the Taylor diagram. The optimal results indicate that the final Pareto-optimal solution often appears at LINMAP and TLFDM points. In contrast with basic trans-critical ORC, the recuperative trans-critical ORC can always improve the system’s thermodynamic performance. But the techno-economics is only enhanced when the energy grade of heat source is sufficient. The most beneficial improvement is the average reduction of heat transfer area per net output power by more than 27.0% and 30.0% in the medium temperature and high temperature geothermal reservoirs, respectively. Based on the case study, the presented method has proved its application value, and has shown its promising applicability in a wide range of energy field regarding organic Rankine cycle and thermodynamic cycles for energy conversion

Multiwinner Voting for Energy-Efficient Mobile Sink Rendezvous Selection in Wireless Sensor Network

Recent studies have demonstrated the advantage of applying mobile sink to prevent the energy-hole problem and prolong network lifetime in wireless sensor network. However, most researches treat the touring length constraint simply as the termination indicator of rendezvous point selection, which leads to a suboptimal solution. In this paper, we notice that the optimal set of rendezvous points is unknown but deterministic and propose to elect the set of rendezvous points directly with the multiwinner voting-based method instead of step-by-step selection. A weighted heuristic voter generation method is introduced to choose the representative voters, and a scoring rule is also well designed to obtain a satisfying solution. We also employ an iterative schema for the voting score update to refine the solution. We have conducted extensive experiments, and the results show that the proposed method can effectively prolong the network lifetime and achieve the competitive performance with other SOTA methods. Compared to the methods based on step-by-step selection, the proposed method increases the network lifetime by 23.2% and 10.5% on average under the balanced-distribution and unbalanced-distribution scenarios, respectively

Pure thiophene–sulfur doped reduced graphene oxide: synthesis, structure, and electrical properties

Here we propose, for the first time, a new and green ethanol-thermal reaction method to synthesize highquality and pure thiophene–sulfur doped reduced graphene oxide (rGO), which establishes an excellent platform for studying sulfur (S) doping effects on the physical/chemical properties of this material. We have quantitatively demonstrated that the conductivity enhancement of thiophene–S doped rGO is not only caused by the more effective reduction induced by S doping, but also by the doped S atoms, themselves. Furthermore, we demonstrate that the S doping is more effective in enhancing conductivity of rGO than nitrogen (N) doping due to its stronger electron donor ability. Finally, the dye-sensitized solar cell (DSCC) employing the S-doped rGO/TiO₂ photoanode exhibits much better performance than undoped rGO/TiO₂, N-doped rGO/TiO₂ and TiO₂ photoanodes. It therefore seems promising for thiophene–S doped rGO to be widely used in electronic and optoelectronic devices