Kevin Polanco

+ About

How I got here.

It started with a mix of Star Wars, racing games, real racing like F1, and a love for fighter jets and planes. Different things, same pull.

Then I learned what simulation actually was, and it looked like a video game. Games are one of my biggest hobbies, and CFD felt like a sandbox version of one: build the thing, run it, and test and upgrade based on how the simulation unfolds.

The work has stayed in one place and moved across a lot of scales. A 400 by 400 metre field site surveyed with drones, ground-penetrating radar and LiDAR. Hydrokinetic turbine blades compared three profiles at a time. A 450 micrometre microchannel where the flow never leaves laminar and the geometry has to do all the mixing. A launch vehicle at Mach 3. What connects them is the same discipline each time: set the simulation up carefully enough that the answer means something.

Most of that has been in ANSYS Fluent, with stretches in MOOSE for finite element multiphysics and OpenFOAM alongside it. The habit that runs through all of it is checking the solver against something else. Published literature for the micromixer, blade element theory for the turbines, hand calculations for the senior design structure, RASAero II for the rocket. A number that only one method produced is a number I do not trust yet.

B.S. in Mechanical Engineering from Binghamton in May 2026, and starting the M.S. at NYU Tandon this fall.

Kevin Polanco standing beside RED II Mary on the launch rail at a desert launch site, the sun low behind them. — RED II “Mary” on the rail, the morning of the launch.

+ Selected work

External aerodynamics at Mach 3.

Mach number contour on the symmetry plane of the RED 2 launch vehicle at a Mach 3 free-stream, showing shock interaction at the nosecone and at the fins.

ME 541 · CFD Project

External Aerodynamics of Rocket Geometry

RED 2 “Mary” / ANSYS Fluent and Mechanical

Two questions drove the study: what shock forms around the vehicle and what forces it puts on the structure, and how you assess aerodynamic performance before flight.

Mach 3

Far-field inlet

18,295,306

Mesh cells

0.992

Avg orthogonal quality

49 m

Spherical far field

Domain and boundary conditions

The 2.4 m vehicle sits inside a spherical enclosure 49 m in diameter, roughly 20.4 times the vehicle length. Literature and industry practice suggest about 10x, but a sphere lets the flow deflect in any direction, which matters once angle of attack is introduced. The domain is sized to keep the shock properly captured and the flow from choking, and was increased past the recommendation to avoid meshing errors.

Inlet	Mach 3, direction-vector far field; outlet inferred
Reference	101,325 Pa atmospheric
Symmetry	Plane cut through the vehicle centerline
Regime	Steady state, compressible
Refinement	Two bodies of influence: 3.6 m first volume, 4.9 m second at 10% of domain diameter

The spherical fluid domain seen end on, with the small rectangular body of influence and the vehicle at its centre. — **Domain against vehicle.** The sphere is 49 m across; the green box is the body of influence and the vehicle inside it is 2.4 m. That ratio is the whole argument for the far-field size.

Close view of the body of influence box containing the rocket outline. — **Body of influence.** The refinement volume the vehicle sits inside, sized so the shock is captured without meshing the whole sphere finely.

A launch vehicle lifting off from a desert launch pad, spectators watching from a concrete blockhouse in the foreground. — **Launch day.** The vehicle this study was run for, off the pad.

Meshing strategy

Named selections on the fins, body, nosecone and nosecone tip each carry their own curvature-based sizing, with the tip and nosecone held to a tighter maximum than the body and fins. The two bodies of influence are volumes set aside for fine meshing.

Nosecone / tip	0.0001 m local min, 0.005 m max
Body / fins	0.0001 m local min, 0.009 m max
Boundary layer	20 layers, last-ratio, 0.0001 m first height
Surface mesh	0.01 to 0.5 m, 3 cells per gap
Volume mesh	Poly-hexcore, 0.0001 to 0.4906 m
Quality	Avg skewness 0.0104, avg orthogonality 0.992

The spherical far-field domain meshed, with the rocket visible as a small void at its centre. — **The 49 m spherical far field**, cut to show the interior. The vehicle is the small void at the centre, roughly 20.4 times smaller than the domain.

Mesh refinement inside the rectangular body of influence around the vehicle. — **Body of influence.** Cell size steps down sharply on entering the refinement volume, so resolution is spent where the shock and the vehicle are.

Poly-hexcore mesh around the fin can, fins shown in blue against the yellow field mesh. — **Fins**, held to a 0.009 m maximum with their own curvature sizing.

Mesh across the transition from the body tube to the nosecone. — **Body to nosecone transition**, where the sizing tightens from 0.009 m to 0.005 m.

Close-up of the nosecone tip showing twenty stacked inflation layers wrapping the surface. — **Nosecone tip.** Twenty inflation layers at a 0.0001 m first height, which is what buys the y+ control.

Wall y-plus on the vehicle surface, scale 0.35 to 117.30. — **Wall y+** on the surface, 0.35 to 117.30, against a 0.0005 m wall-spacing target from a flat-plate estimate.

Numerical method

k-omega SST, chosen for adverse pressure gradients and shock capture in aerospace external flow.
Density-based solver, per ANSYS guidance for high-speed compressible external flow and shock resolution.
Ideal gas law, since density is not constant in compressible flow.
Sutherland equation for temperature-dependent viscosity across the field.
Courant number 1 at startup to prevent divergence, below the 5 to 10 ANSYS suggests, traded for stability.

Convergence monitors

Residuals alone do not prove a converged aerodynamic answer, so drag, pitching moment and drag coefficient were monitored as integrated quantities. Two cases were run, at zero incidence and at 15 degrees angle of attack, and reading them side by side is what makes the force numbers make sense.

Case 1 — no angle of attack

Drag force against iteration for the no-angle-of-attack case, decaying from about 1550 newtons to roughly 1060 newtons by 5000 iterations. — **Drag** settles near **1060 N** on the half model over 5000 iterations. This is the case the RASAero comparison uses.

Pitching moment against iteration for the no-angle-of-attack case, oscillating early then flattening near zero. — **Pitching moment** rings down and holds at roughly **0.4 N·m**, effectively zero. That is what a symmetric vehicle at zero incidence should give, and it is the check that the case is set up right.

Drag coefficient against iteration for the no-angle-of-attack case, settling near 1730. — **Drag coefficient** settles near **1730**, which is wrong by inspection. The force is right and the coefficient is not, so the reference values were never set for this run.

Case 2 — 15 degree angle of attack

Drag force against iteration for the second case, overshooting to 5600 newtons and settling near 4900 newtons. — **Drag** overshoots to about 5600 N near iteration 150, then settles near **4900 N**, against roughly 1060 N for the same half model at zero incidence.

Pitching moment against iteration for the second case, undershooting to about negative 14,100 newton metres and settling near negative 12,190. — **Pitching moment** undershoots to about -14,100 N·m and holds near **-12,190 N·m**. Putting the vehicle at incidence is what generates it, and it is the load the fins and airframe have to carry.

Drag coefficient against iteration for the second case, settling near 0.0077. — **Drag coefficient** settles at **0.0077**, a physically sensible value. Reference values were set correctly here.

Scaled residuals over 1420 iterations for continuity, the velocity components, energy, k and omega. — **Scaled residuals** for this case, falling steadily through 1420 iterations, with omega below 1e-7 and k flat near 6e-6.

Verification

The simulation runs on half the rocket, split on the symmetry plane, so the force it reports is half the force on the whole vehicle. Any comparison against a full-vehicle hand calculation has to account for that before the two numbers mean anything.

RASAero II	418 lb, 1858 N, full vehicle
Expected half	929 N across the symmetry plane
CFD, Case 1	1075 N on the half model, monitor settling near 1060 N
Doubled	2150 N, or 483 lb, full vehicle

Two independent methods, roughly 15% apart, which is a reasonable place to be for a low-order tool against a RANS solve on a vehicle this slender.

Conclusions Shock formation came as expected, with visible shock interaction as the flow reaches the end of the nosecone and then on to the fins. Deflection is relatively small.

Limitations and future work

Case 1 reports a drag coefficient near 1730 while Case 2 reports 0.0077 on the same geometry. The forces are fine in both; the reference values behind the coefficient were only set in one of them. It is recorded here rather than quietly dropped, because the monitor that catches it is the same one that proves the force converged.
Field contours and mesh views come from successive exports as the setup was refined, so scale maxima differ slightly between figures.
Shrink the far field.
Run it transient rather than steady state.
Move from one-way to two-way fluid-structure interaction.
Add parameter sets.

+ Research

Microfluidics, hydrokinetic turbines, and drone-based detection.

Weaving-flow micromixer for higher mixing efficiency

Research Assistant, McNair Summer Intern / Lead: Prof. Jifu Tan / June–August 2025

Mixing at low Reynolds numbers is laminar, so the geometry has to do the work. The question was how far a 30° barrier angle gets you within 450 µm.

Read the methodClose

Built a 3D transient multiphysics simulation in MOOSE, the open-source C++ finite element framework, modelling laminar microfluidic mixing through passive scalar transport.
Evaluated density, viscosity, diffusivity and wall-temperature effects at low Reynolds numbers for lab-on-a-chip systems.
Automated mesh generation, boundary conditions, solver configuration and post-processing so geometry revisions did not each cost a manual rebuild.
Benchmarked against published HVW literature and matched 89.9% mixing efficiency at Re = 5 within 450 µm for a 30° barrier angle.
Presented methodology, validation and modelling limitations to 300+ scholars and faculty at the University at Buffalo Summer Research Conference.

The poster carries the governing scalar transport, continuity and incompressible Navier-Stokes equations, alongside the meshed 3D X-shaped micromixer geometry.

Kevin Polanco standing beside his research poster on computational fluid dynamic simulation of a hydrofoil for hydrokinetic turbines with a CRO module. — Hydrokinetic Turbines with CRO Module, McNair Scholars poster.

Desalination using hydrokinetic turbines with a CRO module

Research Assistant, McNair Summer Intern / Lead: Prof. Cosan Daskiran / June–July 2024

A feasibility study of a hydrokinetic turbine driving centrifugal reverse osmosis, where the blade profile is the variable under test.

Read the methodClose

Modelled the turbine and centrifugal reverse osmosis concept using Blade Element Momentum and Blade Element Theory, quantifying expected turbine performance to support feasibility analysis and design limitations.
Validated blade profile selection with high-order CFD measured against BET/BEM, running 15 turbulent ANSYS Fluent cases across 3 NACA profiles.
Presented to 50+ faculty and research participants, documenting constraints and tradeoffs in a poster and technical briefings.

Work with M. Baker, H. Prince and A. Türkyılmaz. The 2D NACA 4412 hydrofoil case ran at Re = 3 million on 350,340 nodes and 348,867 elements.

Drones with hyperspectral imaging and LiDAR to locate unexploded ordnance

Team Lead / Binghamton University / August 2021–December 2022

Twenty-six inert munitions laid out on a known grid, so that each sensor could be judged on what it actually detected against the environment.

Read the methodClose

Led a 6-person field campaign for UAS-based UXO detection across a 400 m × 400 m site, integrating GPR, hyperspectral imaging, LiDAR and ArcGIS analysis.
Planned a controlled layout of 26 inert munitions: 3 MBRL, 2 TM-62 anti-tank, 3 VPMA-3 and 18 PFM-1 anti-personnel.
Evaluated sensor-specific detection strengths against the environment rather than treating the sensor suite as one instrument.
Presented findings at the European Geosciences Union conference, attended by 14,000+ participants.

+ Student teams

Eight engineers, one set of simulation standards.

AeroBing Rocketry. Velocity pathlines behind the club mark.

Kevin Polanco and five members of the simulations team standing around the finished RED II Mary vehicle, Kevin holding a laptop showing the CFD result. — The simulations team, with RED II “Mary” assembled and the Mach field open on the laptop.

AeroBing Rocketry Research Group

Simulations Team Lead, Aug 2025–May 2026 / Member Aug 2022–Aug 2025

Eight undergraduate engineers running CFD and FEA in parallel on one shared server, against one set of standards, so that a design decision made in simulation actually holds up in fabrication.

Read the methodClose

Owned end-to-end external aerodynamics analysis for student launch vehicles, leading 8 undergraduate engineers running parallel CFD and FEA studies on a shared remote desktop server.
Evaluated compressible turbulent flow, RANS and LES, in ANSYS Fluent to assess y+ control, time-step convergence and aeroelastic deformation risk before fabrication.
Set team simulation standards covering meshing convergence, simulation accuracy and hand-calculation verification, and oversaw projects for future vehicles across multiple concurrent subteams.
Designed the carbon fiber fins for RED 2 “Mary”, iterating geometry from low-order calculations in RASAero II and AeroFinSim, high-order work in MATLAB, and coupled FSI from Fluent into Mechanical, for a 35% increase in stability margin.

Static fire

Motor static fire on the test stand.

Two AeroBing members holding the assembled RED II Mary airframe horizontally in the machine shop. — The airframe out of the rack, nose cone to fin can.

RED II Mary standing upright on its stand in the Binghamton engineering lab. — RED II “Mary” on the stand, finished.

The full AeroBing Rocketry Research Group, around twenty five members, gathered around the vehicle in the machine shop. — **AeroBing Rocketry Research Group.** The simulations team is one of several concurrent subteams.

+ Coursework

Two design projects, one built and one simulated.

A sectioned rocket motor casing showing the charred and burned-through HTPB insulation liner inside. — What an uncharacterised liner looks like after a burn.

Insulation characterization apparatus

ME SDP 124 / Secretary, FEA and instrumentation / Aug 2025–May 2026

AeroBing builds its rockets from scratch and insulates them with HTPB liner, but the liner has never been characterised. So the margin against burn-through is guesswork. This apparatus measures its thermal conductivity.

Read the methodClose

Why it matters

If the liner fails, hot gases escape through the insulation and burn through, and an extreme burn-through takes the casing with it. The famous case is the Challenger SRB joint: same physics, different scale. Design margin against that requires knowing the liner’s thermal conductivity, and until now it was tested iteratively per rocket rather than characterised once.

Target

Measurand	Thermal conductivity k, roughly 0.2 to 0.4 W/m·K, under a controlled ΔT
Sensitivity	Down to 0.2 W/mK, tolerance 0.1 W/mK
Method	Heat flow meter, ASTM C518
Reference	Phenolic sample of known conductivity, for transducer calibration

Why a heat flow meter

Fully standardised under ASTM C518, with documentation and proven repeatability.
Works on elastomeric samples like HTPB liner, which probe-based transient methods do not.
Builds from accessible materials, aluminium plates and steel supports, and is straightforward to fabricate with available machining.
Guarded hot plate, cut bar, transient hot wire and transient line source were all considered and eliminated on manufacturing constraints, budget, documentation, or measurement error on this sample material.

The stack

A sandwich configuration, modular so parts swap out, with tuned sample compression. Eight thermoelectric coolers, four above and four below, hold the plates near isothermal and set a one-dimensional gradient. A heat flux transducer in the stack outputs a voltage proportional to the through-thickness heat flow, and the metered region keeps convection and edge losses negligible.

Exploded assembly. Cold plate heat sink, cold plate with TECs, phenolic sample, hot plate with the heat flux transducer, hot plate heat sink, alignment dowels, and the base plate with its fan.

My part

Ran ANSYS Mechanical FEA with hand calculations to verify support stress, deflection, buckling resistance and manufacturability before fabrication.
Resolved instrumentation and thermal control limits by implementing PWM controllers and a 16-bit LabJack U6 DAQ for microvolt-level thermopile signals, with RTDs logging plate and sample face temperatures.
Wired, soldered, troubleshot and validated the Peltier sensor system against the phenolic reference.
Coordinated a $1.5K build across AeroBing, faculty and the Watson Fabrication Lab, sourcing components and tracking orders, returns, schedules and requirements.
Authored major portions of the 57-page report and the design review presentations through prototype handoff.

ANSYS static structural total deformation of the apparatus frame, maximum 2.2010e-4 metres. — **Apparatus deformation** under load, maximum 2.2010e-4 m across the plate stack and supports.

ANSYS static structural total deformation of a single alignment dowel, maximum 3.4157e-6 metres. — **Alignment dowel**, maximum 3.4157e-6 m. Four steel dowels carry support and alignment, bolted to the base plate and press-fit into the bottom heat sink.

Team

Aleksander Skrodzki, team lead. Kevin Polanco, secretary. Sam Rossberg, procurement. Julian Hu, finance. Faculty advisor Dr. Chiarot, sponsor Malcolm John.

SOLIDWORKS render of the chevron turbofan nacelle with serrated triangular trailing edge scallops. — Chevron nacelle, serrated trailing edge.

Commercialization of supersonic flight: turbofan CFD

Junior design / Individual project / Jan–May 2025

Baseline against chevron nacelle on a Trent 1000 at 35,000 ft. On exit-plane RMS pressure the two came out 0.1 dB apart.

Read the methodClose

Developed baseline and chevron nacelle geometries for a Rolls-Royce Trent 1000 in SOLIDWORKS.
Constructed a 15 m far-field CFD domain with near-wall and shock-region mesh refinement.
Ran compressible SST k-omega RANS simulations across inlet-angle sweeps at 35,000 ft, comparing drag and exit-plane pressure and velocity trends.
Estimated acoustic performance from exit-plane RMS pressure: 181.4 dB baseline against 181.5 dB chevron.
Documented methodology, verification and fidelity limitations in a 21-page report.

Geometry and field results

SOLIDWORKS render of the baseline turbofan nacelle with a plain circular trailing edge. — **Baseline nacelle**, plain trailing edge. Everything else held constant.

Static pressure contour around the chevron nacelle, scale 2.04e3 to 6.27e4 pascals. — **Static pressure**, 2.04e3 to 6.27e4 Pa. The chevron scallops are resolved individually at the trailing edge.

Velocity magnitude contour around the nacelle showing the exhaust jet extending downstream, scale 0 to 696 metres per second. — **Velocity magnitude**, 0 to 696 m/s, with the exhaust jet running downstream to the exit plane where the acoustic estimate was taken.

+ Personal

Built for the fun of it.

AI HK

Windows desktop voice assistant / Python

A voice assistant styled after HK-47 from Knights of the Old Republic, sitting on a global hotkey.

Front desk, 2022 to 2026.

Kevin Polanco at the tutorial center front desk in graduation regalia, hands clasped, smiling. — Last day at the desk, four years on.

EOP & SSS Tutorial Center

Front Desk Supervisor / Binghamton, NY / Aug 2022–May 2026

Front desk of the tutorial center, held alongside everything above.

See moreClose

Kevin Polanco in graduation regalia shaking hands with his supervisor at the tutorial center. — Signing off with the tutorial center staff.

+ Tools

What I run.

Simulation

ANSYS Fluent
ANSYS Mechanical & ACP
OpenFOAM
MOOSE
ParaView
Gmsh

CAD

SOLIDWORKS
Inventor
Creo

Programming

MATLAB
Python
C++

Coursework

CFD
Heat Transfer
Fluid Mechanics
Applied Fluids

+ Education

Binghamton, then NYU Tandon.

New York University, Tandon School of Engineering

Master of Science in Mechanical Engineering

Expected May 2028

Binghamton University, State University of New York

Bachelor of Science in Mechanical Engineering, Thomas J. Watson College of Engineering and Applied Science

May 2026

+ Contact

Get in touch.

Open to conversations about aerodynamics, CFD and anything moving fast enough to form a shock.

Kevinpmail911@gmail.com linkedin.com/in/11kevinpolanco11

How I got here.

External aerodynamics at Mach 3.

External Aerodynamics of Rocket Geometry

Domain and boundary conditions

Meshing strategy

Numerical method

Convergence monitors

Case 1 — no angle of attack

Case 2 — 15 degree angle of attack

Field results

Fluid to structure

Verification

Limitations and future work

Microfluidics, hydrokinetic turbines, and drone-based detection.

Weaving-flow micromixer for higher mixing efficiency

Desalination using hydrokinetic turbines with a CRO module

Drones with hyperspectral imaging and LiDAR to locate unexploded ordnance

Eight engineers, one set of simulation standards.

AeroBing Rocketry Research Group

Static fire

Two design projects, one built and one simulated.

Insulation characterization apparatus

Why it matters

Target

Why a heat flow meter

The stack

My part

Team

Commercialization of supersonic flight: turbofan CFD

Geometry and field results

Built for the fun of it.

AI HK

Front desk, 2022 to 2026.

EOP & SSS Tutorial Center

What I run.

Simulation

CAD

Programming

Coursework

Binghamton, then NYU Tandon.

Get in touch.