Simulation software that models airflow can be a boon to engineers when designing a clean room environment. By pinpointing potential problems early, such software can save time and reduce construction costs. The software—computational fluid dynamics (CFD)—also can be applied to an operational clean room environment to help identify the source of contamination problems and optimize the overall space.

However, for CFD to work effectively, the data must be clean and complete, and the model must have integrity. Based on the Navier-Stokes equations, CFD uses applied mathematics, physics and computational software to illustrate the flow of gas or liquid through a space and the effect it has on the objects it passes.

Architects and city planners use CFD to predict the effects of airflow around new buildings. Engineers use CFD to determine gas flow in manufacturing processes. CFD can also model temperature and humidity control in a space. A good CFD model can be thought of as a pre-construction step, enabling engineers to compare results of various facility options during the design phase. Based on preliminary plans, it allows engineers to visualize cause and effect prior to decision making.


Finding Problems Early

If engineers discover potential issues during the design phase of a project, it not only can save time, but it can also help reduce costs. Since construction costs are inherently high, it is important to avoid trial and error methods and patchwork solutions during the design phase. In a recent clean room design project, engineers found very little area for return airflow after technicians’ tools were included in the CFD analysis. The graphics in the software allowed engineers to see that the overall room layout worked well, so they decided to install two additional booster fans to increase the airflow rate. Measuring 2 feet by 4 feet and 18 inches in diameter, the backward-incline fans increased airflow by four times.

When certain groups involved in a project attempt to cut corners or fail to ask the right questions, errors can occur. In one clean room project, a tool group installed a number of utilities—including chemical, water, exhaust and air—without following a model or specific guidelines. In the end, they blocked all the typical airflow paths under the floor instead of using a routing matrix for directions on where to install them.

As a result of using an inexpensive method for installation, airflow pathways were being blocked from under the floor. For example, differential pressure between the bay and the chase was very high and all the air was being forced out the end of the bay instead of flowing through the floor within the bay. The air flowing through the hallway and the adjoining bay caused laminarity problems in that bay, since the floor had to manage more volume than normal.


Accurate Data Is Vital

Data integrity is the key to model effectiveness; the integrity of the input determines the integrity of the output. Unfortunately, many CFD models are generated based on incomplete data, either because complete data is not available or because the modeler has only input a portion of the data. As a result, the modeler may make certain assumptions that are not based on field-gathered information. It is essential to do cross measurements to balance data and validate that assumptions given are accurate.

When modeling air flow a clean room, everything in the room should be accounted for. The CFD model should not be based only on an open floor plan, because it will change when tools and other items are added. It should, however, encompass enough of an area, so it is important not to shrink the model down too small. Also, it is cost effective to put tools in a model even if they are phased in gradually.

Items that are often missed in the model are furnishings, tool boxes, carts, trash cans or any other solid objects blocking air paths. Even lightweight materials, such as plastic, plywood, or cardboard installed over floors, can be considered obstructions if they are too close to an air return.


Field Measurements Aid Modeling

Taking real-time measurements, such as opening doors and seeing how much air comes in and out, will help ensure model integrity. It will also help define the parameters of a problem area. A ribbon streamer can be used at trouble spots to measure how air flows and travels through a space.

Field measurements are centered on what is being modeled. These are abundant and unique to each situation, but some common examples include space dimensions, airflow in the space, and things that might obstruct it, such a process tools and utilities. Complex temperature measurements with multiple sensors go beyond the usual single-sensor temperature reading. Wind velocity measurements can provide information about exhaust stacks and air handlers, as well as the wind velocities inside the space. Field measurements could be focused in a number of areas, but the key is to conduct targeted tests to gather all the relevant data to make informed design choices.

It is always recommended to take field measurements twice and to do cross measurements to ensure numbers are accurate. Managers have a tendency to build a model based on drawings from their office, but they can’t see hidden issues not shown on paper. They need to visit the site to validate the assumptions they have made.

The volume of exhaust in a specific area is one measurement that might be overlooked at a facility. An area may have only a small amount of exhaust coming out of it, or the airflow may not be even. Airflow could be uneven due to heavy tool exhaust, which may cause the modeling software to replace it with air from another space.

There are ways to ensure that the model and measurements are done with certainty and integrity. One is to gradually widen the model until the results match what is being seen in the field. If measurements of problem and nonproblem areas are accurate, then the results of the model should start matching what is going on in real time.

Air fluid problems in a clean space are not well defined, which makes it difficult to determine if there is a laminarity issue, differential pressure problem, or a make-up air problem. Managers may need to guess what is going on behind the scenes, validating what is on paper, as well as looking at mechanical and equipment issues.


Experts Can Help

Pinpointing the right professionals to handle situations at a clean room facility can be challenging. Many individuals may have access to pertinent information, but one should verify who they are talking with and determine where their expertise lies. A good modeler not only understands what he is modeling, but also is confident about the validity of the data he is receiving. For air-flow related issues, most facilities have an air-balancing team on hand that knows the system inside and out.

Once an airflow issue has been identified, a CFD model can help engineers and operators develop solutions to correct problems. For example, laminarity and differential pressure problems were found to be disrupting airflow at one facility. As a result, booster fans were installed to increase airflow.

Integrity is one of the most important elements in effective CFD modeling. Data must be clean and accurate, which directly affects the validity of the model itself. A good model allows engineers to compare the results of various solutions, which helps save time and reduces or eliminates construction costs. Strengthening a CFD model’s integrity is a successful method for long-term project analysis and examination, saving time and cutting costs.

For more information on clean room design and analysis, call the SSOE Group at 503-439-8777 or visit


SSOE Helps Chip Maker Design, Build Clean Room

Based in Boise, ID, Micron Technology Inc. produces many forms of semiconductor devices, including dynamic random-access memory, flash memory and solid-state drives.

In 2012, Micron hired SSOE to engineer, design and support construction of multiple base-build systems, including installation of a clean room at the company’s facility in Nampa, ID. Working under a fast-track schedule, SSOE managed multiple onsite subcontractors as we converted the building into a 25,000-square-foot, ISO 4 clean room facility.

After meeting with Micron and examining the site, SSOE provided preliminary engineering and scope development services to clarify options for the facility. The existing structure required a thorough structural analysis to ensure that it could support future equipment installations. The structural scope included an exhaust stack support, utility racks, a bulk gas tank and the clean room ceiling.

Our process team created numerous systems including ultra-pure and hot ultra-pure water, solvent waste, chemical delivery systems, and bulk and specialty gases. SSOE designed the HVAC system for the clean production space, and we modified the existing HVAC system for the support areas.

Working closely with Micron’s engineers, we constructed the over-fire air systems to meet the requirements of the upgraded facility, and we modified the air handlers to change capacity as needed. The coordination of the bulk tank and chilled water systems required constant cross-discipline communication and careful schedule management. The utilities for tools and building services were also included in our scope, as were various control systems.

We laid out the facility for future tool installations, and we took care to include as much of the existing system as possible.

SSOE integrated Micron’s existing project documentation procedures with our own, which allowed for swift responses to critical questions and submittals. As a result of the success of this project, Micron has awarded us subsequent work, and we have built a profitable, ongoing partnership.