JOA® GCM™ / Vo crit™ technology

The basis of our technology is developing effective air flow patterns to capture contaminants based on their characteristics and emission source. We then provide guaranteed exhaust airflows at each hood by applying specific flow patterns within extraction ducting to ensure maximum re-entrainment of particles and in turn, minimize settlement that will occur on the duct wall. JOA® has developed patented engineering techniques as well as our own computer simulation program for creating a “living model” of the customers’ system.

JOA V0crit

Critical Velocity with VoCrit™
From laboratory and wind tunnel testing, dust emission samples are analyzed to determine the optimum velocity required for minimum deposition maximum re-entrainment of particles into the pipe core. Particle data such as aerodynamic shape, bulk density and adhesion forces are entered into our dynamic software model, VoCrit™. This unique model calculates all the forces present on air borne particulate that is being conveyed in an extraction system. Upon completion of VoCrit™ analysis, it determines the optimum conveyance velocity minimizing risk of fouling the ducting of the extraction system. This software was developed with the cooperation of the University of Delft in The Netherlands.

JOA Advanced Scenario Modeling with GCM large

Advanced Scenario Modeling with GCM™
GCM™, Graphic Computational Modeling, , is a proprietary computational work flow tool, based on JOA® patented technologies, to design, visualize, and balance dust and vapor extraction systems. This model operates on an iterative basis resulting in precise system balancing for both critical velocity and static pressure. The GCM™ ensures that all equipment meets expected requirements and provides a basis for ensuring that maximum diversity of operation is possible without plugging the extraction system. In addition, the GCM allows for creation of a “Living Model” of your dust and vapor extraction system such that alterations or retrofits can be accurately modeled. This allows the plant to make smart decisions on how to change or upgrade the system while maintaining optimum system performance.