Abstract
This paper describes our continued effort in the development of the model-based rapid redesign methodology. In the prior work (Chen et al. in ASME J Mech Des 129:283–294, 2007), we have explored and applied various decomposition patterns for rapid redesign to effectively control design change propagation. Since the decomposition process for redesign is not activated until the presence of a redesign request, this prior work represents a reactive approach where a new set of decomposition patterns should be generated in accordance with a different redesign request input. As an extension to our redesign methodology, this paper presents a proactive approach to complement the existing methodology for rapid redesign. In this approach, the decomposition patterns capturing generic decomposed structures of a given design model are created in advance and stored in a design library before any redesign request emerges. These pre-generated patterns are able to address any upcoming redesign request without further decomposition procedures in redesign. This proactive approach is developed in a new framework of pattern-based reasoning that is built on the mechanism “case → pattern → strategy.” Two methodological components, Proactive Redesign Decomposition and Redesign Condition Analysis, are introduced along with a redesign application to an existing air-cooled condenser for illustration. This redesign approach is particularly useful when it requires only minor yet frequent modifications for the existing design.
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Notes
Another logical result is the uncoupled matrix, which shows no interaction between the formed clusters. This case will not be discussed as design change propagation can be well controlled within the clusters. Further analysis is not necessary.
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Appendix: Description of parameters (columns) and functions (rows) for the example problem
Appendix: Description of parameters (columns) and functions (rows) for the example problem
Column / row | Description |
---|---|
C 1 | Tube outer diameter (m) |
C 2 | Tube inner diameter (m) |
C 3 | Tube pitch (m) |
C 4 | Tube wall thickness (m) |
C 5 | Air specific heat (kJ/kgK) |
C 6 | Air density (kg/m3) |
C 7 | Air viscosity (Ns/m2) |
C 8 | Air conductivity (W/m·K) |
C 9 | Fin material conductivity (W/mK) |
C 10 | Additive heat resistance due to dust, etc. (m2 K/W) |
C 11 | Surface condition factor (irregular: 0.11; regular: 0.07) |
C 12 | Evaporating temperature (°C) |
C 13 | Outdoor air temperature (°C) |
C 14 | Leaving air temperature (°C) |
C 15 | Condensing temperature (refrigerant saturation, °C) |
C 16 | Logarithm mean temperature between air and refrigerant (°C) |
C 17 | Vertical portion of total fin and tube area (m2) |
C 18 | Horizontal portion of total fin and tube area (m2) |
C 19 | Average area of 1-m long tube surface (m2) |
C 20 | Total fin and tube area (m2) |
C 21 | Ratio of A ∑ to tube inner surface area (8 ~ 10) |
C 22 | Ratio of net flow area to face air area |
C 23 | Heat transfer area (m2) |
C 24 | Face air velocity (m/s) |
C 25 | Net flow area velocity (m/s) |
C 26 | Efficiency of fin and tube |
C 27 | Efficiency of fin |
C 28 | Refrigerant heat transfer coefficient (W/m2 K) |
C 29 | Air-side heat transfer coefficient (W/m2 K) |
C 30 | Air-side equivalent heat transfer coefficient (W/m2 K) |
C 31 | Overall heat transfer conductance (W/m2 K) |
C 32 | Total length of (fin and) tube (m) |
C 33 | Total number of tubes |
C 34 | Length per tube (m) |
C 35 | Number of tube rows (2 ~ 4) |
C 36 | Number of tubes per row |
C 37 | Width of condenser (m) |
C 38 | Cooling capacity (W) |
C 39 | Heat rejection load (W) |
C 40 | Air mass flow rate (kg/s) |
C 41 | Heat flux (200 ~ 300 W/m2) |
C 42 | Reynolds number |
C 43 | Air-side resistance (air pressure drop, Pa) |
C 44 | Factor related to ϕ k vs. ϕ 0 |
C 45 | Refrigerant thermal property coefficient (W3 N/m6K3 s) |
C 46 | Exponential factor (variable) for K calculation |
C 47 | Exponential factor (variable) for K calculation |
C 48 | Coefficient (variable) related to air flow |
C 49 | Coefficient (variable) related to fin and tube structure |
C 50 | Air flow resistance correction coefficient |
C 51 | Cross-sectional equivalent diameter of air flow (m) |
C 52 | Dimensionless equivalent fin height (m) |
C 53 | Fin pitch (m) |
C 54 | Fin thickness (m) |
C 55 | Fin height (m) |
C 56 | Fin length along air flow direction (m) |
Row | |
R 1 | Compute heat rejection load for condenser |
R 2 | |
R 3 | |
R 4 | Select “plate fin with disordered rows of tubes”, and compute the related structural parameters |
R 5 | |
R 6 | |
R 7 | |
R 8 | |
R 9 | |
R 10 | |
R 11 | |
R 12 | |
R 13 | Compute cool air flow mass flow rate |
R 14 | |
R 15 | Compute air related velocities |
R 16 | |
R 17 | Set refrigerant heat transfer coefficient |
R 18 | |
R 19 | Set air-side equivalent heat transfer coefficient |
R 20 | |
R 21 | |
R 22 | |
R 23 | |
R 24 | |
R 25 | |
R 26 | |
R 27 | |
R 28 | |
R 29 | |
R 30 | |
R 31 | Set overall heat transfer conductance |
R 32 | |
R 33 | Compute log-mean temperature |
R 34 | Find heat flux, and determine heat transfer area |
R 35 | |
R 36 | Configure condenser structural parameters |
R 37 | |
R 38 | |
R 39 | |
R 40 | Compute air pressure drop |
R 41 |
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Li, S., Chen, L. Pattern-based reasoning for rapid redesign: a proactive approach. Res Eng Design 21, 25–42 (2010). https://doi.org/10.1007/s00163-009-0069-2
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DOI: https://doi.org/10.1007/s00163-009-0069-2