Biomass Combustion CFD Optimization
Budget: $250 – $750 USD
I need a detailed CFD study that zeroes-in on how our biomass-fired system burns solid fuel and, above all, how its combustion efficiency can be improved. The set-up already runs reliably, yet flue-gas data hint at unburnt carbon and avoidable heat losses.
You will receive:
• 3-D CAD of the furnace and ducting
• Operating boundary conditions (airflows, temperatures, pressure drops)
• Ultimate/proximate analysis of the biomass feedstock and current stack measurements
Your tasks are to:
• Build and calibrate a reactive flow model for biomass (solid-fuel) combustion in Ansys Fluent, OpenFOAM, Star-CCM+ or an equivalent solver you are comfortable with
• Capture devolatilisation, char burnout, radiation and turbulence with appropriate sub-models
• Run sensitivity simulations on air staging, swirl, particle size and residence time to reveal efficiency bottlenecks
• Summarise findings and quantify the projected gain in thermal efficiency from each recommended change
Acceptance criteria:
1. Mesh independence demonstrated.
2. Model validation against the supplied temperature and flue-gas data within ±5 %.
3. Clear, actionable recommendations supported by comparative contour plots and KPIs.
Please indicate which solver and turbulence/combustion schemes you prefer and the estimated turnaround for the first set of results.
You will receive:
• 3-D CAD of the furnace and ducting
• Operating boundary conditions (airflows, temperatures, pressure drops)
• Ultimate/proximate analysis of the biomass feedstock and current stack measurements
Your tasks are to:
• Build and calibrate a reactive flow model for biomass (solid-fuel) combustion in Ansys Fluent, OpenFOAM, Star-CCM+ or an equivalent solver you are comfortable with
• Capture devolatilisation, char burnout, radiation and turbulence with appropriate sub-models
• Run sensitivity simulations on air staging, swirl, particle size and residence time to reveal efficiency bottlenecks
• Summarise findings and quantify the projected gain in thermal efficiency from each recommended change
Acceptance criteria:
1. Mesh independence demonstrated.
2. Model validation against the supplied temperature and flue-gas data within ±5 %.
3. Clear, actionable recommendations supported by comparative contour plots and KPIs.
Please indicate which solver and turbulence/combustion schemes you prefer and the estimated turnaround for the first set of results.