This paper describes an analysis method for an inertial particle separator system modeled as a multi-element airfoil configuration. The analysis method is implemented in a numerical tool that is able to perform impingement analysis using spherical, nonspherical particles as well as water droplets for a range of Reynolds number (10 4 Re 5 10 5 ). A limitations of the analysis tool is that it lacks an appropriate particle rebound model for the treatment of particle-wall collisions. The usefulness of the analysis tool is its use in conjunction with a multipoint inverse design tool for the design of a multi-element airfoil based inertial particle separator system model in an inverse fashion as opposed to the direct design methods being employed currently for this task. With such a design and analysis tool at hand, the design space can be explored as well as tradeoff studies can be performed that can aid in the development of a more efficient design methodology for multi-element airfoil based inertial particle separator systems.= Runge-Kutta coefficients used to integrate the momentum equation l 0 ; n 0 = trajectory direction vector l 1 ; n 1 = airfoil panel plane direction vector m p = particle mass, p V p n = surface normal vector p = ambient pressure Re = Reynolds number based on particle diameter, a D eq U= a r p = particle position r p;i x p;i ; z p;i = particle current position during trajectory integration r p;i1 x p;i1 ; z p;i1 = particle new position during trajectory integration S = particle surface projection on the U * perpendicular plane S p = particle surface area s = airfoil panel surface arc length,= trajectory parametric equation parameter t 1 , t 2 = airfoil panel parametric equation parameters U = magnitude of particle relative velocity in body reference frame, jUj U = particle relative velocity in body reference frame, V a V p U 0 = initial particle relative velocity in body reference frame V a = freestream velocity in body reference frame, u a i w a k V i u i ; w i = current particle velocity during the trajectory integration V i1 u i1 ; w i1 = new particle velocity during the trajectory integration V p = particle volume V p = particle velocity in body reference frame, dr p =dt V 1 = unperturbed freestream velocity in wind reference frame, u 1 i w 1 k V 0 a = initial freestream velocity in body reference frame V 0 p = initial particle velocity in body reference frame u= axes in wind reference frame x p ; z p = axes in body reference frame x 0 ; z 0 = initial particle location in wind reference frame x 1 ; z 1 , x 2 ; z 2 = airfoil panel coordinates z = pressure head = geometric angle of attack with respect to airfoil chord line = impingement efficiency, dz 0 =ds x = step along the x axis z = step along the z axis = angle between the z p axis and z axis a = ambient air viscosity a = ambient air density p = particle mass density = time step in Runge-Kutta integration = shear stress = shape factor

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Laser induced heating processes are important when a laser is used as a machine tool in industry, since the quality of the machining process strongly depends on the heating mechanism. The present study examines a heat transfer model that provides useful information on the laser induced interaction mechanism. Steady state and time dependent heating models are introduced and temperature profiles inside the materials are predicted. Using appropriate assumptions, the time for the surface temperature to reach 90% of its steady state value is estimated. To validate the theoretical predictions, experiments are performed to measure the surface temperature of the irradiated spot during the laser heating pulse. It is found that, during the use of a pulsed laser in the drilling process, as the heating progresses the drilling velocities rise while the liquid depth and time to reach steady state fall, in this case, the energy consumed for evaporation is higher than losses through conduction.

In this study, an experimental and numerical investigation was carried out to obtain lift, drag, and pitching moment data on 65 degree delta and 65/40 degree double-delta wings. The experimental tests were conducted at the King Fahd University of Petroleum and Minerals low-speed wind-tunnel facility, whereas the numerical tests were performed using the commercial computational fluid dynamics software FLUENT. Results from both experiments and numerical predictions were compared to other experimental data found in literature as well as to the theory of Polhamus. The results of comparison of surface pressure coefficient distribution and vortex breakdown location show good agreement with experiments. Overall, the comparison of result shows good agreement between different experimental studies as well as good agreement with the computational fluid dynamics predictions and the theoretical calculations.

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