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ASME PTC 19.23-1980 scan — Guidance Manual for Model Testing
📐 ASME PTC 19.23-1980 is the Instruments and Apparatus supplement of the ASME Performance Test Codes dealing with model testing. It was prepared by PTC Committee 37, later designated 19.23, formed in March 1972, and approved as an American National Standard in January 1980. Its objective is to compile a compendium of techniques and methods for model testing, serving as a guide for those concerned with extending or supplementing prototype tests of equipment under the aegis of the Performance Test Codes — including centrifugal pumps, fans, compressors, hydraulic turbines, and steam turbines.
💡 The core value of model testing: when prototype testing is costly or impractical, a model scaled by similarity laws can be subjected to operating conditions unattainable on the prototype, predicting prototype performance at lower cost — or indicating remedial changes for a prototype not performing as predicted.
1. Definition of a Model and General Philosophy 📌
The Manual defines a model as a device, machine, structure, or system which can be used to predict the behavior of an actual and similar device, machine, structure, or system called the prototype. A physical model may be smaller than, the same size as, or larger than the prototype. Analogs are not included in Performance Test Code modeling at this time; only physical models are considered. The general philosophy includes:
- A model, built before the prototype, is an engineering design tool that overcomes economic or practical limitations of prototype testing;
- It may permit imposing operational conditions not attainable in prototype testing;
- It may indicate potential remedial changes to a prototype not performing as predicted;
- Wherever possible, relationships between model and prototype performance should be determined or confirmed experimentally;
- Models must be physically similar to the prototype and experience the same physical phenomena.
⚠️ Model testing is a broad and complex field with its own specialties: the Manual assumes the practitioner already understands dimensional homogeneity and dynamic similarity from a college-level fluid mechanics or heat transfer course. Systems such as steam generators, steam and gas turbines, and condensing equipment do not lend themselves to complete-system modeling — use component models and specialized methods.
2. Fundamental Theory of Similitude 📖
Sections 1 and 3 develop the theoretical background:
- Geometric similarity: all corresponding dimensions of model and prototype share one scale ratio;
- Dynamic similarity: the ratios of forces at corresponding points are the same — inertial, viscous, gravity, and pressure forces;
- Dimensional analysis: construct dimensionless groups from fundamental physical quantities;
- Characteristic length: a representative length used in similarity conversion;
- Referred quantities and specific speed: for pumps and turbomachinery conversions;
- Model-law derivation: derive model laws from basic physical laws, including the similarity laws of Reynolds and Froude.
| Dimensionless Group | Physical Meaning | Typical Applications |
|---|---|---|
| Reynolds number (Re) | Inertia / viscosity | Pipe flow, external flow, drag |
| Froude number (Fr) | Inertia / gravity | Open channels, free-surface waves, pump intake vortices |
| Mach number (Ma) | Velocity / speed of sound | Compressible flow, turbomachinery |
| Euler number (Eu) | Pressure / inertia | Cavitation, pressure-drop similarity |
| Strouhal number (St) | Unsteady / convective inertia | Vortex shedding, oscillating flow, blade-passing frequency |
| Nusselt number (Nu) | Convection / conduction | Heat-transfer similarity |
💡 The appendix “Land Chart of Dimensionless Numbers” classifies a large set of dimensionless groups by their physical domain — a practical quick-reference for selecting similarity parameters. In practice it is usually impossible to match every group; select the groups that govern the dominant physical process.
3. Typical Model-Testing Examples 🔬
Section 2 of the Manual presents a series of worked examples across different equipment types, illustrating the application of similarity laws:
| Example | Subject | Key Similarity Parameters |
|---|---|---|
| Example 1 | Oversized turbine stage flow model | Reynolds, Mach numbers |
| Example 2 | Pump intake vortex studies | Froude number, geometric similarity |
| Example 3 | Hydraulic turbine tests | Froude number, specific speed |
| Example 4 | Butterfly valve tests | Reynolds number, geometric similarity |
| Example 5 | Electrostatic precipitator gas-flow distribution | Geometric and flow similarity |
| Example 6 | Flow in furnaces and ducts (smoke and water-table tests) | Froude number (gravity-driven flow) |
| Example 7 | Cooling tower flow recirculation | Geometric similarity, buoyancy effects |
| Example 8 | Large compressor for the Tullahoma wind tunnel | Mach, Reynolds numbers |
| Example 10 | Model testing of large fans | Specific speed, similarity curves |
🚨 The most common cause of failed model tests: satisfying geometric similarity while ignoring dynamic similarity. If the dominant dimensionless group (e.g., Reynolds number) differs too much from the prototype, the flow regime — laminar/turbulent, separation location — may not be similar at all, even with an identical shape, and the results are invalid.
4. Engineering Practice Essentials 🛠️
- 🔍 Fix the similarity criteria first: identify which force families dominate the process to be predicted and select the dimensionless groups that must be matched, rather than chasing all groups simultaneously;
- 🔧 Scale ratio and manufacturing accuracy: balance model cost against scale effects (surface roughness, clearances); small-scale models need careful similarity corrections for roughness and gaps;
- 📊 Verify when possible: wherever conditions allow, confirm the model-to-prototype conversion relationship with limited prototype tests or existing data for similar units;
- 📋 Referred-quantity conversion: for rotating machines (pumps, fans, turbines), use specific speed and similarity curves for speed and size conversions, and record the conversion formulas and assumptions.
5. Frequently Asked Questions ❓
❓ Q: Must a model be smaller than the prototype?
A: No. A model may be smaller than, the same size as, or larger than the prototype, depending on the test purpose and practical constraints. The essence of a model is a similar device used to predict prototype behavior, not merely a scaled-down copy.
A: No. A model may be smaller than, the same size as, or larger than the prototype, depending on the test purpose and practical constraints. The essence of a model is a similar device used to predict prototype behavior, not merely a scaled-down copy.
❓ Q: Why is Reynolds-number similarity often the hardest to satisfy?
A: The Reynolds number couples velocity, characteristic length, and fluid viscosity. With a reduced-scale model, if velocity cannot be raised accordingly or the fluid changed, the Reynolds number inevitably differs from the prototype — and in many flows it directly governs drag and separation.
A: The Reynolds number couples velocity, characteristic length, and fluid viscosity. With a reduced-scale model, if velocity cannot be raised accordingly or the fluid changed, the Reynolds number inevitably differs from the prototype — and in many flows it directly governs drag and separation.
❓ Q: When an equipment test code exists, how should the model test be run?
A: Use the guiding principles, instruments, and measurement methods of the applicable test code (e.g., PTC 10, PTC 14, PTC 18) with only the modifications necessary because a model rather than a prototype is being tested; when no code exists, guidance may be requested from the PTC 19.23 Committee.
A: Use the guiding principles, instruments, and measurement methods of the applicable test code (e.g., PTC 10, PTC 14, PTC 18) with only the modifications necessary because a model rather than a prototype is being tested; when no code exists, guidance may be requested from the PTC 19.23 Committee.
🔍 Q: Why are systems like steam generators not recommended for complete-system modeling?
A: Such systems involve complex coupled phenomena — combustion, heat transfer, two-phase flow — that a single physical model cannot satisfy simultaneously under all similarity criteria. Engineering practice models key components (burners, tube banks, ducts) separately and combines results with empirical methods.
A: Such systems involve complex coupled phenomena — combustion, heat transfer, two-phase flow — that a single physical model cannot satisfy simultaneously under all similarity criteria. Engineering practice models key components (burners, tube banks, ducts) separately and combines results with empirical methods.
