Meanline method for design and off-design turbine performance predictions
(2019) MVKM01 20191Department of Energy Sciences
- Abstract
- Early designs are often based on rough estimations and assumptions. Such is also the case when designing space turbines that power rocket engine fuel pumps which generally have obscure performance and size requirements. Often times, this leads to unique, single-use designs. This complicates and restricts the amount of possible testing. To aid in this early design process and to help predict turbine performance in various scenario, a one-dimensional meanline method program is developed in Python. It is able to perform calculations for various geometries and operating conditions by varying inlet conditions such as temperature, pressure, rotational speed and pressure ratios. The program itself makes use of general turbine knowledge with... (More)
- Early designs are often based on rough estimations and assumptions. Such is also the case when designing space turbines that power rocket engine fuel pumps which generally have obscure performance and size requirements. Often times, this leads to unique, single-use designs. This complicates and restricts the amount of possible testing. To aid in this early design process and to help predict turbine performance in various scenario, a one-dimensional meanline method program is developed in Python. It is able to perform calculations for various geometries and operating conditions by varying inlet conditions such as temperature, pressure, rotational speed and pressure ratios. The program itself makes use of general turbine knowledge with relevant literature in aerodynamic loss modeling, outlet angle calculations and pressure convergence. The accuracy of the program's output has been continuously validated against different types of turbines and shown adequate correlations to real-world performance data, down to half a percentage in relative error for certain cases. Case-specific tailoring to fit certain operating conditions and fast run times of approximately 5 seconds will provide the user with the possibility of performing turbine performance characteristics with ease. (Less)
- Popular Abstract (Swedish)
- Mänsklighetens intresse för rymden och allt bortom vår värld har alltid varit ett faktum.
Raketer har skjutits upp i det svarta sedan 1940-talet och utvecklingen av rymdutrustning
går ständigt framåt med ny teknik som konstant tänjer på gränserna för vad vi trodde var
möjligt. Dock leder nya tankar och idéer till ökad resursefterfrågan, särskilt i de tidigare
designstadien. Därför behövs metoder för att fastställa prestanda och karakteristik genom
snabba och resurssnåla simuleringsprogram - precis som detta examensarbete gjort.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8981907
- author
- Sjödin, Joel LU
- supervisor
- organization
- course
- MVKM01 20191
- year
- 2019
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Meanline program, space turbine, loss model, turbine predictions, early stage design
- report number
- LUTMDN/TMHP-19/5436-SE
- ISSN
- 0282-1990
- language
- English
- id
- 8981907
- date added to LUP
- 2019-06-11 14:17:02
- date last changed
- 2019-06-11 14:17:02
@misc{8981907, abstract = {{Early designs are often based on rough estimations and assumptions. Such is also the case when designing space turbines that power rocket engine fuel pumps which generally have obscure performance and size requirements. Often times, this leads to unique, single-use designs. This complicates and restricts the amount of possible testing. To aid in this early design process and to help predict turbine performance in various scenario, a one-dimensional meanline method program is developed in Python. It is able to perform calculations for various geometries and operating conditions by varying inlet conditions such as temperature, pressure, rotational speed and pressure ratios. The program itself makes use of general turbine knowledge with relevant literature in aerodynamic loss modeling, outlet angle calculations and pressure convergence. The accuracy of the program's output has been continuously validated against different types of turbines and shown adequate correlations to real-world performance data, down to half a percentage in relative error for certain cases. Case-specific tailoring to fit certain operating conditions and fast run times of approximately 5 seconds will provide the user with the possibility of performing turbine performance characteristics with ease.}}, author = {{Sjödin, Joel}}, issn = {{0282-1990}}, language = {{eng}}, note = {{Student Paper}}, title = {{Meanline method for design and off-design turbine performance predictions}}, year = {{2019}}, }