Predicting the velocity, the temperature and the heat transfer rates within compressible boundary layers remains a challenging problem. Under compressibility and high Reynolds conditions, the density variations become very significant, resulting in high heat transfer rates. The net result is an altering of the dynamics within the boundary layer that is significantly different from its laminar counterpart. Physical properties, such as the specific heat capacities, the viscosity and the thermal conductivity, which are often considered constant, now vary with respect to temperature, creating a strong coupling between the velocity and the temperature fields. Despite the progress made in this field of research, a common issue frequently expressed in the literature is the difficulty in acquiring high quality time-resolved velocity and temperature data in compressible flows, especially near the wall. The major objective of this study is to demonstrate the capabilities of the Integral-Differential Scheme (IDS) by solving the flow field challenges within compressible boundary layers. It was demonstrated that IDS have the capability of accurately solving the full Navier-Stokes equations under realistic conditions. In the case of the compressible boundary layer, the IDS capture the flow field physics. However, it was demonstrated that the IDS is highly sensitive to grid resolution as well as the prescribed boundary conditions.

Drug–target association plays an important role in drug discovery, drug repositioning, drug synergy prediction, etc. Currently, a lot of drug-related databases, such as DrugBank and BindingDB, have emerged. However, these databases are separate, incomplete and non-uniform with different criteria. Here, we integrated eight drug-related databases; collected, filtered and supplemented drugs, target genes and experimentally validated (highly confident) associations and built a highly confident drug–target (HCDT: http://hainmu-biobigdata.com/hcdt) database. HCDT database includes 500 681 HCDT associations between 299 458 drugs and 5618 target genes. Compared to individual databases, HCDT database contains 1.1 to 254.2 times drugs, 1.8–5.5 times target genes and 1.4–27.7 times drug–target associations. It is normative, publicly available and easy for searching, browsing and downloading. Together with multi-omics data, it will be a good resource in analyzing the drug functional mechanism, mining drug-related biological pathways, predicting drug synergy, etc. Database URL: http://hainmu-biobigdata.com/hcdt

Cleaning out the pulverized coal deposited at the bottom of a coalbed methane (CBM) well is key to achieving continuous CBM drainage and prolonging the workover period. In this study, Fluent is used in conjunction with the standard k-ε model and the Eulerian-Eulerian model to simulate and analyse jet erosion of deposited pulverized coal particles. The depth and width of the stable erosion pit that is formed by jet-impacting deposited pulverized coal under different conditions are determined and provide a theoretical basis for the cleanout of pulverized coal in the bottom of a CBM well. In this paper, the three parameters of the jet target distance, nozzle diameter and nozzle outlet flow velocity are selected to perform an orthogonal simulation. The change trends in the depth and width of the scouring pit with time are determined. The results show that jet impacting of deposited pulverized coal can be categorised into four stages, periods of rapid growth, stability, jet swing and dynamic stability. A sensitivity analysis shows that the nozzle outlet flow velocity has the strongest influence on the depth of the scouring pit among the selected parameters. The depth of the jet impact pit can reach the maximum depth at t = 3 s, while the width of the impact pit can reach the maximum after t = 7 s. This can provide key design parameters for CBM well pulverized coal impacting operation. It is of great significance for capacity damage control during CBM well workover operation.

Computational Fluid Dynamics (CFD) analysis are widely used in modern risk assessment procedure in order to understand detonations during a given situation or an accident. Combustion regimes including deflagration, detonation transition and detonation are extremely important. Hydrodynamic instabilities during detonation make it even harder to simulated. Numerous lingering numerical challenges still exists in the areas of simulating gas detonation flows. Among these challenges is the inability of many high order numerical schemes to simulated gas denotation and wave propagation without getting into regions of negative density or negative pressure. Many existing high order schemes, which may have proven record of accomplishment in terms of their accuracies and efficiencies in handling complex flow fields, will often times facilitate the development of negative density or negative pressure in their efforts to simulate the physics associated with the time evolution of gas detonation flow fields. This effort describes the application of a positivity-preserving density and pressure scheme, named the Integro-Differential scheme (IDS), to the detonation gas dynamic problem. Among the problems of interest to this study are the 1-D shock tube problem, 2-D explosion problem and implosion detonations problems. The purpose of solve 1-D problem is to prove IDS has acceptable numerical stability and less dissipation as a computational fluid dynamics (CFD) scheme. Of particular interest to this paper is the implosion detonations problem. The implosion problem was analyzed on a square domain of dimension: 0 <= x <= 0.3; 0 <= y <= 0.3, with reflecting walls, and with zero initial velocities. The results indicated that the IDS was able to successfully capture the flow physics within the implosion problem. And the wall pressure and temperature data from the 2-D unsteady result and use extract line way to analysis.

Potentially, for hypersonic access to space vehicles, the scramjet engine is the propulsion system of choice and will be required to operate in a variety of flight conditions. In many cases, the freestream dynamic pressure may be held constant, however, the Mach numbers may range from 4 to 12. Operating in such a broad Mach range, will in turn require the combustor to accommodate varying conditions. Computational Fluid Dynamics as an engineering tool has been used in this paper to analyze be fluid field physics within a scramjet isolator. Currently, with proven capability to diagnose scramjet isolator design challenges, especially those tools that will predict and prevent unstarts, are lacking. To overcome these challenges, the Integro-Differential Scheme (IDS), which was developed and improved in Ref [1–2], is used in the computational analyses’ aspects of this effort. In addition, the numerical model is designed with back-pressure manipulation capability that seeks to influence the real-time flow behavior within the isolator based on experiment. The base-line scramjet isolator is model after a Mach 1.8 isolator with a length to height ratio of 8.40 has been simulated in this paper. The aerodynamic conditions used in the design of the numerical model was extracted from the experimental data presented in Ref. [3]. The flow physics within the isolator numerical model was studied under two sets of back pressure conditions; namely, (a) natural designed condition and (b) fixed adverse conditions. It is noteworthy to mention, backpressure studies were conducted through the use of ‘smooth’ and ‘discrete’ pressure jumps. In addition, the backpressure conditions were allowed to vary real-time as the flow structures within the isolator were observed. The engineering analysis conducted herein demonstrated results that are in excellent agreement with the available experimental data. It was observed that under design conditions, the isolator flow field consisted of an oblique shock train, which was strongest closest to the entrance of the isolator. Also, it was observed during each ‘discrete’ change in back pressure value, a wave, comprising of a coupled pair of oblique shocks and a normal shock, resembling the ‘lambda shock pattern’ emerges from the exit of the isolator. During each test, this ‘lambda shock’ travels to the front of the isolator, interacting with and dominating each set of reflected waves along its path. In each case, the lambda shock interacts with the front-most and strongest pair of oblique shocks, rocking back and forth before the entire isolator flow field settles down into a new configuration. This process intensifies as the back pressure discrete jump increases in strength, and the oblique shock train transformed into a form that closely mimics a normal shock train, with the strongest ‘lambda shock’ at the head of the isolator. In general, it appears as if the isolator flow patterned itself as a flexible spring within the constant area duct, constantly modifying its ‘net shock strength’ to accommodate the rising back pressures and while pushing the leading lambda shock small increments towards the entrance. The results showed that at a PBP with α = 2.1, the leading lambda shock moves rapidly towards the entrance, and with a PBP with α = 2.2 the isolator reach to ‘unstarts’ condition. In the end, different data sets have been provided with the relationship of backpressure variation and 1st ‘lambda’ location versus time by using IDS simulation.