A model reactor is used to investigate the extent to which the overall performance and detailed flowfield structure of a non-premixed swirl-stabilized distributed reaction are sensitive to modest changes in inlet conditions (e.g., fuel injection angle, inlet geometry, and swirl vane solidity). Measurements of combustor performance are based on exhaust plane species concentration profiles (HC, CO2, CO, O2), combustion efficiency, and visual observation of combustor stability. The detailed flowfield structure is established by spatially mapping the axial and azimuthal velocity fields using two-component laser anemometry, and the temperature field using a thermocouple probe. The results show that relatively modest changes in inlet conditions can dramatically affect the flowfield structure. As an example, for the model reactor evaluated the addition of a small step at the outer boundary of the swirler yields significantly lower centerline axial velocities and a more uniform thermal structure in the recirculation zone. Furthermore, a modest reduction in swirl vane solidity transforms the aerodynamic structure of the recirculation zone from an off-axis to a central, on-axis structure. These results explain, in part, the contradictory conclusions drawn from data acquired in non-premixed swirl-stabilized distributed reactions, and establish that comparisons and generalizations of such flows require, at a minimum, (1) careful measurements and specification of the inlet conditions, (2) detailed measurements of the flow structure, and (3) an assessment of the effects of modest changes in key operating and configurational variables. © 1988 Combustion Institute.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.