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Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Title Influence of Subslab Aggregate Permeability of SSV Performance Permalink
| Content Provider | Semantic Scholar |
|---|---|
| Author | Nematollahi, Alireza |
| Copyright Year | 2008 |
| Abstract | The effectiveness of the technique of subslab ventilation (SSV) for limiting radon entry into basements was investigated through complementary experimentation and numerical modeling. Determination of the impact of subslab aggregate permeability on SSV performance was a primary objective. Subslab pressure fields resulting from SSV were measured in six well-characterized basements, each with a different combination of soil and aggregate permeability. The relationship between air velocity and pressure gradient within the three types of aggregate installed beneath the basement slabs was measured in the laboratory. A new numerical model of SSV was developed and verified with the field data. This model simulates non-Darcy flow in the aggregate. We demonstrate that non-Darcy effects significantly impact SSV performance. Field data and numerical simulations indicate that increasing the aggregate permeability within the investigated range of 2.xlO-8 m 2 to 3.xlOm 2 substantially improves the extension of the subslab pressure field due to SSV operation. Subslab pressure field extension also improves as soil permeability decreases between 10-9 m 2 and 10m• With a slab-wall gap thickness of 1 mm and the range of aggregate permeability investigated, further reductions in soil permeability do not significantly improve the subslab pressure field extension. Sealing of cracks in the slab and excavation of a small pit where the SSV pipe penetrates the slab also dramatically improve this pressure field extension. A large ratio of aggregate permeability to soil permeability reduces the need for large depressurizations at the SSV pit. Our findings are consistent with the results of prior field studies; however, our understanding of SSV is improved and the dependence of SSV performance on the relevant parameters can now be quantified with the model. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://cloudfront.escholarship.org/dist/prd/content/qt8v1843x8/qt8v1843x8.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
