Changes in flight stability characteristics at the advanced stage of aircraft design are complex and require thorough investigations. This paper examines the impact of wing strake modification on high-performance aircraft using computational fluid dynamics (CFD). The dynamic behaviour is calculated using the forced oscillation technique, while the effect of geometric variation on longitudinal stability characteristics is extensively studied. Steady-state experimental data is utilised to validate the computational setup. Static aerodynamic coefficients, dynamic stability derivatives and the positions of aerodynamic and pressure centres are employed to quantify the changes. Furthermore, the alterations in stability characteristics are correlated with flow physics. The results indicate a reduction in longitudinal static and dynamic stability at various flight conditions due to the proposed modification. This deliberate reduction was necessary to accommodate the installation of a fly-by-wire system. The discussed design changes have been effectively implemented on an in-service aircraft.

Natural ventilation can play an important role towards preventing the spread of airborne infections in indoor environments. However, quantifying natural ventilation flow rates is a challenging task due to significant variability in the boundary conditions that drive the flow. In the current study, we propose and validate an efficient strategy for using computational fluid dynamics to assess natural ventilation flow rates under variable conditions, considering the test case of a single-room home in a dense urban slum. The method characterizes the dimensionless ventilation rate as a function of the dimensionless ventilation Richardson number and the wind direction. First, the high-fidelity large-eddy simulation (LES) predictions are validated against full-scale ventilation rate measurements. Next, simulations with identical Richardson numbers, but varying dimensional wind speeds and temperatures, are compared to verify the proposed similarity relationship. Last, the functional form of the similarity relationship is determined based on 32 LES. Validation of the surrogate model against full-scale measurements demonstrates that the proposed strategy can efficiently inform accurate building-specific similarity relationships for natural ventilation flow rates in complex urban environments.

It is well known that vessels operating in the vicinity of a lateral bank experience a significant yaw moment and sway force. This bank effect has a major impact on the manoeuvring properties of the vessel and must therefore be properly understood to ensure the safe passage of the vessel through the restricted waterway. Accordingly, this study performs a series of simulations using commercial FLOW-3D® computational fluid dynamics (CFD) software and the KRISO 3600 TEU container ship model to examine the effects of the vessel speed and distance to bank on the magnitude and time-based variation of the yaw angle and sway force. The results show that for a given vessel speed, the yaw angle and sway force increase as the distance to bank reduces, while for a given distance between the ship and the bank, the yaw angle and sway force increase with an increasing vessel speed. In addition, it is shown that even when a vessel advances at a very low speed, it experiences a significant bank effect when operating in close vicinity to the bank. Overall, the results presented in this study confirm the feasibility of the CFD modelling approach as a means of obtaining detailed insights into the bank effect without the need for time-consuming and expensive ship trials.

Computational simulation of physical systems generally requires human experts to set up a simulation, run it, evaluate the quality of the simulation output, and repeatedly invoke the simulator with modified input until a satisfactory output quality is achieved. This reliance on human experts makes use of simulators by other programs difficult and unreliable, though invocation of simulators by other programs is critical for important tasks such as automated engineering design optimization. Presented is a framework for constructing intelligent controllers for computational simulators that can automatically detect a wide variety of problems that lead to low-quality simulation output, using a set of evaluation methods based on knowledge of physics and numerical analysis stored in a data/knowledgebase of models and simulations. An experimental implementation of this framework in an intelligent automated controller for a widely used computational fluid dynamics simulator is described.

Protective clothing provides laboratory and hazardous-materials workers, firefighters, military personnel, and others with the means to control their exposure to chemicals, biological materials, and heat sources. Depending on the specific application, the textile materials used in protective clothing must provide high performance in a number of areas, for example, impermeability to hazardous chemicals, breathability, light weight, low cost, and durability. Models based on computational fluid dynamics have been developed to predict the performance of protective clothing materials. Such models complement testing by enabling property data from laboratory materials tests to be used in predictions of the performance of integrated multilayer garments under varying environmental conditions.