Making The Mactaquac Dam New Again

FLOW-3D HYDRO Case Studies

Making The Mactaquac Dam New Again

FLOW-3D HYDRO computational fluid dynamics (CFD) software answers important questions about the future of New Brunswick’s historic Mactaquac Dam.

This material was provided by Jason Shaw, Discipline Director – Hydrotechnical Engineering, Hatch Ltd.

Damming streams and rivers to generate electricity is nothing new. Beginning with Appleton, Wisconsin’s construction of the Vulcan Street Plant on the Fox River in 1882 — the world’s first hydroelectric power plant — dams now account for more than 70% of all renewable energy across the globe.

From the Grand Coulee and Chief Joseph dams in Washington State to the Mica and W.A.C. Bennett dams in British Columbia, the United States and Canada boast nearly 3,000 hydroelectric stations, powering more than 50 million homes and generating approximately 80% of the renewable energy consumed in North America.

Designing these massive objects has long been one of the most demanding of engineering activities. For starters, there are the structural concerns that come with pouring several million tons of concrete, followed by the need to manage many megawatts of electricity. But it is determining the optimal way of passing water through, over, and around dams and spillways that has perhaps proven to be one of the most challenging design aspects of dam building, requiring costly physical models, lengthy analyses, and no small amount of educated guesswork.

Fortunately, hydraulic design has become much easier over recent decades thanks to the development of computational fluid dynamics (CFD) software. CFD is now an indispensable tool for dam designers and anyone who needs to understand what makes water and other fluids behave as they do, and how to effectively harness their immense power.

Straddling the St. John River

The Mactaquac Generating Station ranks high on the list of Canada’s essential dams. Located at the intersection of the Mactaquac River and the St. John River, this embankment dam sits twelve miles upstream from Fredericton, New Brunswick’s capital. Its six turbines generate 660 megawatts of power, making it the largest hydroelectric facility in the Canadian Maritime provinces.  According to its operator, NB Power, the 55-meter tall, 518-meter long structure supplies approximately 12% of the province’s homes and businesses with electricity.

The Mactaquac Dam courtesy of NB Power

The Mactaquac Dam was completed in 1968 and intended to last 100 years. But as with any large-scale infrastructure project, unanticipated problems can sometimes occur, some of which might fail to emerge for years or even decades after the foundation is laid. Such is the case with the Mactaquac Dam, where an adverse chemical phenomenon known as alkali-aggregate reaction (AAR) caused the concrete to swell and crack, resulting in significant and ongoing annual maintenance and repair costs.

Granted, CFD analysis would neither have predicted nor prevented this particular problem, but it can help to answer the question of how to refurbish the structure. Is it enough to simply replace the faulty concrete, or will a significant redesign be necessary? This is where Jason Shaw and his team at Hatch comes into the picture.

Building relationships

A Project Manager and Hydraulic Engineer at Hatch Inc., Shaw and the other 9,000 professionals at the Mississauga, Ontario-based consulting firm have extensive experience in a range of industries, among them civil engineering, mining, oil and gas, and all manner of infrastructure design and development, power generation facilities included.

They’ve also had a long-term relationship with NB Power. “In 2004, Hatch acquired Acres International, an engineering consultancy with expertise in dams and hydropower,” said Shaw. “They were the original designer of Mactaquac and have since become part of our energy group. As such, we’ve had a longstanding relationship with NB Power, and we continue to do work for them, not only Mactaquac life-extension, but other facilities as well.”

Shaw explained that alkali-aggregate reaction is very difficult to manage. In the Mactaquac Dam’s case, high amounts of silica in the locally-quarried greywacke—a type of sandstone used to make the concrete—caused a chemical reaction between it and the alkaline limestone found in cement. The result is a viscous gel that, in the presence of water, expands over time, leading to spalling, cracking, and rebar exposure.

Rendering of Spillway Baffle Blocks courtesy of ASI Marine Report Underwater Inspection of Mactaquac Generating Station
Rendering of Spillway Baffle Blocks courtesy of ASI Marine Report Underwater Inspection of Mactaquac Generating Station

“One area of concern is the spillway, where the baffle blocks and end sill have seen significant deterioration,” said Shaw. “But it’s really everything about the dam that’s in jeopardy. Because the concrete is squeezing on the gate guides, for example, you get to the point where the spillway gates are at risk of binding. And in the powerhouse, it’s pushing on the concrete that holds the power generation units, causing them to shift location and become ‘out-of-round’. The consequences are gradual but distortions are inevitable, leading to the requirement for a complex structural remediation.”

To avoid this, NB Power commissioned Hatch to study the problem and provide options on how to move forward. Since AAR issues were discovered in the 1980s, the Hatch team has installed sensors throughout the structure to monitor structural movement and concrete performance. They continue to analyze the ongoing alkali-aggregate reaction in an effort to understand how the concrete is deteriorating and ways extend the life of the project. NB Power and Hatch even pioneered cutting small, strategic spaces and gaps in the dam using diamond wire saws to relieve internal stresses and manage deformations.

Saving the spillway

Over the course of the project, NB Power determined their best option was to refurbish the dam by repairing and improving the damaged portions. A major part of this plan included a hydraulic analysis to determine the best approach. This helped answer questions about whether the operating conditions of the existing structure may have accelerated erosion of the spillway, and if any modifications could be made to reduce this risk. Much of that analysis was based on Hatch’s extensive use of CFD software to determine which parts of the spillway structures need replacing and what designs would provide the best results.

That software comes from Flow Science Inc. of Santa Fe, New Mexico, developers of FLOW-3D HYDRO. “We’ve had a relationship with Flow Science for close to 30 years,” said Shaw. “In fact, I’d say we were probably one of the early adopters, although now practically everyone in the industry is using it and it’s far from novel to use CFD on projects like this.”

Prior to CFD, the only alternative would have been to perform the analysis using a scaled physical model. Shaw noted that this is not only time-consuming, but if multiple iterations are needed, it may promote schedule delays and escalate project development costs. Additional factors related to the scaling of the physical model can also lead to questionable conclusions. CFD, on the other hand, allows engineers to iterate at scale as much as necessary. Various scenarios are easily tested, solutions applied, and the optimal design quickly determined. Physical models are still used, but as a means of validation rather than experimentation.

“CFD fills a crucial gap,” said Shaw. “It allows designers to examine a range of different scenarios that would otherwise be very costly to replicate. This allows you to fine-tune a design and, when you’re ready, check it against the physical model—if they agree, it eliminates any question marks.”

Moving downstream

This was exactly the case with the Mactaquac project, where the first phase of the project was validating the CFD model against measurements from a past physical modeling study of the site. This critical stage of the study allowed the engineers to quantify uncertainty and build confidence in the results of the CFD simulations. Shaw and his team were able to compare these physical model results against the newly-created 3D CFD model of the dam and its surrounding area. They soon found reasonable correlation between the two, providing them with a high degree of confidence that they were on the right track and that their CFD analyses were correct.

A 3D model is only as good as its calibration and validation. If you can’t provide that, then you don’t know where you stand, regardless of the approach. Despite the need for this critical step, however, CFD is a necessary part of the analysis train, if you will. It represents a more precise and more accurate way of analyzing a complex problem. These studies have served as a basis for making decisions about the dam’s future rehabilitation.

A comparison of the physical model results and the CFD simulation results.

After successful validation of the CFD model, the next phase of the study used FLOW-3D HYDRO to evaluate the existing conditions in the deteriorated spillway. Engineers compared estimates of water depths, jump containment, velocities and pressures on the aprons related to energy dissipation, and erosion and cavitation potential for the concrete structures as well as the tailrace areas downstream from each structure. CFD simulations illustrated hydraulic performance for each of these variables, allowing the team to accurately evaluate the three proposed refurbishment options. Ultimately, the CFD model results led the design team to recommend restoration of the original spillway dimensions, adding two new baffle blocks, and modifying the spillway end sill. The CFD results also raised concerns that cavitation may have played a role in the concrete erosion, which led to further recommendations for modified baffle block designs.

CFD simulation results of existing conditions with deteriorated concrete.
CFD simulation result comparison of 3 refurbishment options

A great deal of work remains before the Mactaquac Generating Station is restored. FLOW-3D HYDRO has allowed Hatch to identify the best approach moving forward, giving them a solid footing to plan and design future improvements and refurbishment. It allowed them to pinpoint the most effective way to improve hydraulic performance and reduce the risk of future erosion in the most efficient and cost-effective possible way.

“The intent here is to move forward with project development using CFD analyses and continue to sharpen the pencil,” said Shaw. “I’m very confident that we will derive design solutions that will ensure hydraulic spill performance at Mactaquac which will meet the objective of ensuring a safe design.”

What’s New in FLOW-3D (x) 2022R1

FLOW-3D (x) 2022R1 Release
FLOW-3D (x) 2022R1 Release

What's New in FLOW-3D (x) 2022R1

FLOW-3D (x) 2022R1 marks a significant development upgrade to the workflow automation and design optimization capabilities of FLOW-3D (x). The development objectives for this release center around performance and improved user experience.

FLOW-3D (x) is a powerful, versatile, and intuitive connectivity and automation platform, which includes a native optimization engine specifically designed for CFD applications. Whether you want to automate running FLOW-3D models through a parameter sweep, extracting key data to create post-processing deliverables, or you want to run dedicated optimization projects, refining geometry from dynamically connect CAD models or by sweeping through flow conditions, FLOW-3D (x) has all the features needed to perform these tasks in a clear and efficient manner. Remote execution, running simulations in parallel, and fully integrated batch post-processing are some of the new features that make FLOW-3D (x) 2022R1 an integral tool for our FLOW-3D user community.


Parallel execution of FLOW-3D simulations for automation and optimization tasks

With 2022R1, FLOW-3D (x) can now run multiple FLOW-3D simulations in parallel. By evolving from serial to parallel execution, users can now make the most of available computational resources, vastly accelerating the time to completion of automated parameter sweeps and gaining valuable insight sooner.

Parallel execution of simulations
Depending on available license resources, the number of concurrent executions to use in the automation or optimization project is easily set in the FLOW-3D (x) execution widget.

Execution of FLOW-3D simulations on remote nodes

Hand-in-hand with the ability to execute FLOW-3D nodes in parallel, we recognized the need to be able to make the most efficient use of computational resources that might be remote and distributed across multiple workstations on a network. With FLOW-3D (x) 2022R1, users can define execution nodes as remote nodes. Users can decide which nodes, local or remote, to run FLOW-3D executions in order to best make use of their computational resources.

Simulation on remote nodes
In addition to running FLOW-3D (x) and FLOW-3D executions on a local workstation, remote nodes are easily configured in order to take advantage of remote computing resources.

Full integration with FLOW-3D POST and Python automation

Automated post-processing using FLOW-3D POST state files is now fully integrated into the workflow automation supported by FLOW-3D (x). The latest release of FLOW-3D POST 2022R1 allows users to create macros, state files, and Python-driven advanced batch automation. These advanced post-processing features are integrated into the FLOW-3D (x) 2022R1 release under a dedicated post-processing node, as well as under dedicated Python script execution nodes.

Advanced post-processing
With the integration of FLOW-3D POST post-processing capabilities into FLOW-3D (x), users can now automate their entire optimization process, from geometry or CFD mode parameter sweep through post-processed graphical deliverables.

User experience

Streamlined definition of optimization targets

A simplified definition of optimization targets has been added, allowing users to directly define targets rather than having to define a minimization goal.

Simplified definition of optimization targets
The new “target” class of objectives is now available in FLOW-3D (x) 2022R1.

Streamlined layout of user interface

Based on user feedback from the original release of FLOW-3D (x), the user interface now delivers a clear, intuitive experience even for large, complex optimization projects. Superior clarity of node and workflow definitions, improved layout optimization tasks and population selection, and dedicated nodes for all FLOW-3D products are some of the improvements delivered in this release.

Streamlined layout of interface
A more compact, streamlined workflow graphical representation is just one of the many user interface improvements delivered in FLOW-3D (x) 2022R1.

Data analysis and plot formatting upgrades

In keeping with efforts to streamline FLOW-3D (x) model setup and execution for the user, the data analytics graphical representation widget allows for clear, simple access to the most important data from your project simulations. Plot definition has been simplified and plot formatting improved. A new type of chart allows filtered data to be exported as text and images at custom resolution.

Dr. Tony Hirt, Founder of Flow Science, Inc. Receives the John Campbell Award

Santa Fe, NM, May 11, 2022 — Flow Science, Inc. founder Dr. C.W. “Tony” Hirt was awarded the prestigious John Campbell Medal at the Institute of Cast Metals Engineers award ceremony on March 25, 2022, in London. Dr. Hirt received the award for his unique, long-lasting contributions to the science and practice of metal casting through his development of the CFD software FLOW-3D and its casting-specific version, FLOW-3D CAST.

Dr. John Campbell presented the award to Dr. Hirt, “In gratitude for making significant, really significant benefit to the foundry industry which we continue to enjoy to this day.” The award was accepted on behalf of Dr. Hirt by Flow Science’s Chief Technology Officer, Dr. Michael Barkhudarov.

The John Campbell Medal is awarded to an individual who has made a sustained contribution to the science and understanding of metal casting through research and development. Each year, the Institute writes to leading international castings research organizations and individuals, including Dr. John Campbell, the relevant Department Heads of the University of Birmingham and Mississippi State University, CAST-CSIRO, VDG and Cti, requesting nominations for an award shortlist.

Tony’s contribution to simulation is not only in developing useful modeling tools based on fundamental principles of physics but mentoring several generations of engineers that continue in his steps. The award is also welcome as a recognition that simulation tools have become an integral part of casting design and production as the industry matures and evolves, commented Dr. Michael Barkhudarov.

Dr. Hirt pioneered the Volume-of-Fluid (VOF) method while working at the Los Alamos National Lab. He went on to found Flow Science in 1980. FLOW-3D is a direct descendant of his development of the VOF method. This approach was expanded and perfected in FLOW-3D to the TruVOF technology, with cutting-edge and groundbreaking improvements in speed and accuracy in the simulation of flow with different liquid and gas interfaces. Today, Flow Science products offer complete multi-physic solutions with diverse modeling capabilities, including fluid-structure interaction, moving objects, and multiphase flows.

About Flow Science

Flow Science, Inc. is a privately held software company specializing in computational fluid dynamics software for industrial and scientific applications worldwide. Flow Science has distributors and technical support services for its FLOW-3D products in nations throughout the Americas, Europe, Asia, the Middle East, and Australasia. Flow Science is headquartered in Santa Fe, New Mexico.

Media Contact

Flow Science, Inc.

683 Harkle Rd.

Santa Fe, NM 87505

+1 505-982-0088

Optimization of a Sand Casting with FLOW-3D CAST

Optimization of a Sand Casting with FLOW-3D CAST

This blog was contributed by Malte Leonhard, Flow Science Deutschland.

The goal of a casting simulation is to predict casting defects and find the corrective measures to avoid such defects. To achieve this, the casting simulation must accurately predict the physical results. In this article, we illustrate a validation of FLOW-3D CAST by comparing simulation results with experimental findings. For this validation, we selected an aluminum casting with significant porosity defects. The extent of the porosities meant that the casting would not fulfill the functional specification and would be rejected.

Optimization of casting design and runner/riser system supported by simulation

In order to verify that FLOW-3D CAST can reliably predict such casting defects, the existing casting was simulated and the results compared with the real casting defects. This video shows that the FLOW-3D CAST defect analysis correctly reproduced the defects and their position.

The simulation results suggested that reversing the casting direction might be beneficial, so the casting part was rotated by 180° in the mold. Next, the runner and riser system were modified so that most of the risers were integrated into the runner (“hot risers”).

Additionally, design changes of the casting, which we will discuss later in the article, were introduced in order to achieve a directed solidification to the risers and to avoid porosities in the casting.

Finally, chills were applied in areas of large mass accumulations to reduce shrinkage defects.

A filling and solidification simulation showed that these measures significantly reduced the casting defects. These simulation results were again validated by X-rays. Near the “cold risers”, those not integrated into the runner system, not all defects could be avoided due to the risers’ insufficient size.

In the last version, the two cold risers were enlarged. Minor design changes of the casting were introduced to improve the directional solidification to the risers.

Compared to the original design, the casting quality was substantially improved and the amount of return scrap reduced. The use of chills improved the quality in critical areas within the casting. Overall, the casting process is now more efficient and cost-effective for the foundry.

Design modifications of the casting

In many cases it is not sufficient to optimize the runner and riser system to achieve a sufficient casting quality. Instead, the design of the casting itself needs to be changed for the sake of “castability”.

The functional design of a casting often includes mass accumulations that prove problematic in the casting process. To achieve a high-quality microstructure, the wall thickness should always increase towards the risers according to the thermal modulus method.

To illustrate the effect of the casting design modifications, two geometry versions with identical runner and riser systems are compared. The adjustments are shown in the figure below. Several wall thicknesses and ribs between material accumulations have been enlarged.

For demonstration purposes, the two marked ribs will be examined. In both cases, porosities occur at the junctions, which is not acceptable.

By increasing the wall thicknesses of the ribs, the junctions are connected to the feeders adjacent to the casting edge and a directed solidification toward the risers is achieved.

The video shows large porosities in the initial version on the left side due to large hot spots within the casting where solidification-induced shrinkage creates a deficit.

In the optimized version on the right, the melt solidifies in the direction of the risers. This means that the deficit can be compensated by the riser and no porosity is created in the casting.

This validation shows a good correlation between reality and simulation in FLOW-3D CAST. The software is an effective tool for the development of castings, casting systems, feeder dimensions/shapes, and casting processes to ensure optimal quality and efficiency.

Exploring Ray Tracing in FLOW-3D POST

Exploring Ray Tracing in FLOW-3D POST

In the world of CFD, we use FLOW-3D POST to learn about our processes, analyze, visualize, and communicate the results of our simulations. We can now use the ray tracing option to increase the quality of our images and videos. While the ray tracing tool may not be necessary for every day simulation work, it is a great tool for presentation and outbound materials. Simulations can now be rendered with realistic-looking materials, depth of field, and lighting, and shadows to better engage viewers and guide them to the most interesting aspects of the results.

What is Ray Tracing?

The rendering engine works by setting up a geometric scene. First, we need a scene object or component. This will be our 3D simulation model that exists in a 3D dimensional space. Next, we choose a virtual camera or viewpoint, which will define the perspective of our image. Third, we need an image plane, which will be perpendicular to our viewing direction. The image plane is divided into pixels and is where the final image will be constructed. User:Henrik    CC BY-SA 4.0

The ray tracing engine can now start filling in the pixels on the image plane. View rays are constructed from the camera viewpoint, through the center of each pixel on the image plane, and then extend out into to the scene object. When the ray intersects our object, the color of the intersection point is determined and sent back to its respective pixel in the image plane. This process is done for every pixel in the image plane to construct an image.

Shadows and Lighting

Another variable we can specify in our ray tracing calculation is lighting. Light sources will affect the shade and intensity of the colors sent to the image plane from our view ray. This effect is defined mathematically by the rendering equation, which was first introduced by James Kajiya from CalTech in 1986. For a basic understanding, the equation can be broken down into three factors. Keeping these factors in mind will help guide you as you start incorporating light sources into your simulation.

1. How much light is incoming or falling on our scene object?

Here we can consider the intensity of our light source, the distance from the light source to the scene object, and the orientation of the scene object with respect to the light source.

2. How does the surface of our scene object reflect the light?

This is where we can consider the material of our object. Different materials have different reflectivity. For instance, materials can be shiny like water or dull like concrete. In FLOW-3D POST we have many material definitions ready to use. Note that dull objects are defined as diffuse and shinier objects are defined as specular.

3. Where is the location of your camera or viewpoint?

Moving the viewing angle will influence the perceived light reflection.

Ray Tracing in FLOW-3D POST

With a component selected, select Enable Ray Tracing in the Properties section. From here you can use either the OSPray Raycaster or OSPray Pathtracer engines for rendering. The path tracing approach is considered a more accurate representation of lighting and illumination, but this calculation can be more computationally intensive.

Now you can start exploring the ray tracing back end. You can experiment with materials from the pre-loaded options or define them from an imported material library:

  • Adjust camera properties such as focal point and depth of field using the adjust camera panel
  • Background settings can be defined as backplate or environment 

We have had success using the backplate to define a ground or floor to the object. Finally, the light inspector can be used to set up your light sources; this includes area lights for softer shadows.

With this overview of ray tracing, you now can start incorporating ray tracing and light sources to create photo-realistic renderings of your simulation results. We will be following up this post with some of our suggested settings that our team likes to use for different applications.

Stay tuned for our next blog on the animation view and keyframing features in FLOW-3D POST.

At Flow Science we develop innovative solutions that help our customers conceptualize, create, and analyze their simulations with confidence. If you would like more information or a personal demonstration of FLOW-3D POST, please send an email to

Thank you and stay tuned for our next post!

Ajit D'Brass

Ajit D'Brass

Metal Casting Engineer at Flow Science

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