Results for “maximum-flow”

NASA NTRS1982

Comparison of two- and three-dimensional flow computations with laser anemometer measurements in a transonic compressor rotor

Two and three dimensional inviscid solutions for the flow in a transonic axial compressor rotor at design speed are compared with probe and laser anemometers measurements at near-stall and maximum-flow operating points. Experimental details of the laser anemometer system and computational details of the two dimensional axisymmetric code and three dimensional Euler code are described. Comparisons are made between relative Mach number and flow angle contours, shock location, and shock strength. A procedure for using an efficient axisymmetric code to generate downstream pressure input for computationally expensive Euler codes is discussed. A film supplement shows the calculations of the two operating points with the time-marching Euler code.

Chima, R. V.↗

NASA NTRS1947

Performance of Compressor of XJ-41-V Turbojet Engine: Compressor Static-Pressure Rise at Equivalent Compressor Speeds of 5000, 7000, 8000, and 9000 rpm - 3

At the request of the Air Materiel Command, Army Air Forces, an investigation is being conducted at the NACA Cleveland laboratory to determine the performance characteristics of the XJ-41-V turbojet-engine compressor. The static-pressure variation in the direction of flow through the compressor was presented in reference 1 for an equivalent speed of 8000 rpm. An analysis of these pressure indicated that the maximum-flow limitation of the compressor was caused by separation, which reduced the effective flow area at the vaned-collector entrance. As a result of this analysis, the flow area at the vaned-collector entrance was increased to obtain larger mass flows. The area increase was obtained by cutting back the entrance edges of the collector vanes, which resulted in an increased vaneless-diffuser radius. Comparative performance of the original and revised compressors at an equivalent speed of 8000 rpm is presented. The static-pressure rise through the compressor, determined from static pressures at the impeller entrance and the vaned-collector exit, is also presented together with the compressor adiabatic efficiency and the mass flow over an equivalent speed range from 5000 to 9000 rpm. These static-pressure data are presented for the purpose of correlating the compressor performance with the turbojet-engine performance.

Creagh, John W. R.↗

NASA NTRS2009

Computing Bounds on Resource Levels for Flexible Plans

A new algorithm efficiently computes the tightest exact bound on the levels of resources induced by a flexible activity plan (see figure). Tightness of bounds is extremely important for computations involved in planning because tight bounds can save potentially exponential amounts of search (through early backtracking and detection of solutions), relative to looser bounds. The bound computed by the new algorithm, denoted the resource-level envelope, constitutes the measure of maximum and minimum consumption of resources at any time for all fixed-time schedules in the flexible plan. At each time, the envelope guarantees that there are two fixed-time instantiations one that produces the minimum level and one that produces the maximum level. Therefore, the resource-level envelope is the tightest possible resource-level bound for a flexible plan because any tighter bound would exclude the contribution of at least one fixed-time schedule. If the resource- level envelope can be computed efficiently, one could substitute looser bounds that are currently used in the inner cores of constraint-posting scheduling algorithms, with the potential for great improvements in performance. What is needed to reduce the cost of computation is an algorithm, the measure of complexity of which is no greater than a low-degree polynomial in N (where N is the number of activities). The new algorithm satisfies this need. In this algorithm, the computation of resource-level envelopes is based on a novel combination of (1) the theory of shortest paths in the temporal-constraint network for the flexible plan and (2) the theory of maximum flows for a flow network derived from the temporal and resource constraints. The measure of asymptotic complexity of the algorithm is O(N O(maxflow(N)), where O(x) denotes an amount of computing time or a number of arithmetic operations proportional to a number of the order of x and O(maxflow(N)) is the measure of complexity (and thus of cost) of a maximumflow algorithm applied to an auxiliary flow network of 2N nodes. The algorithm is believed to be efficient in practice; experimental analysis shows the practical cost of maxflow to be as low as O(N1.5). The algorithm could be enhanced following at least two approaches. In the first approach, incremental subalgorithms for the computation of the envelope could be developed. By use of temporal scanning of the events in the temporal network, it may be possible to significantly reduce the size of the networks on which it is necessary to run the maximum-flow subalgorithm, thereby significantly reducing the time required for envelope calculation. In the second approach, the practical effectiveness of resource envelopes in the inner loops of search algorithms could be tested for multi-capacity resource scheduling. This testing would include inner-loop backtracking and termination tests and variable and value-ordering heuristics that exploit the properties of resource envelopes more directly.

Muscvettola, Nicola↗