Suppose there was a tool that could predict the likelihood of whether your building would fail. What if this tool could also provide you with information to help decrease risk factors? Liberty Building Forensics Group (LBFG) for the National Council of Architectural Registration Boards (NCARB) believe we have created that tool.
NCARB, which represents nearly 40,000 architects worldwide, is launching a new online continuing education monograph that captures the updated version of a formerly released manual and provides CEU credits for registered architects. The monograph contains moisture-prediction guidelines adapted from a mold and moisture manual developed for the Disney Corporation and CH2M Hill in the early 1990s. These guidelines, tested on thousands of hotels, resorts, student housing, multifamily, and healthcare buildings, are as accurate now as they were 20 years ago.
The guidelines reflect institutional knowledge gleaned from industry experts who investigated thousands of building failures. They discovered that certain steps seemed to help a building succeed and other decisions virtually guaranteed a building to fail.
They also realized that a fundamental problem in the building process was the absence of appropriate collaboration between building scientists, architects, building owners, and product manufacturers during construction. Constructive cooperation along the way should help all parties to make better sense of cause and effect, since the predictability in building moisture is staggering.
"If a building is going to have mold and moisture failures, it usually does so within the first two years – often before it officially launches, and usually in a massive, catastrophic manner," said LBFG Vice-President Richard Scott, AIA, NCARB. "We have seen numerous instances of buildings running into multi-million-dollar problems before they are even occupied. Our hope is that these guidelines will help prevent these kinds of failures in the future."
This newly updated NCARB Online Monograph course is designed to help educate readers about the connections between predictive factors and almost certain outcomes.