But what makes them tick? How do they transform a simple rotation into the steady flow that powers humans’ daily lives? And how can one simulate and analyze their performance to achieve the epitome of design excellence?

This is where SimScale Turbomachinery CFD steps in, your ultimate solution for simulating centrifugal pump designs and calculating their feasibility.

What Is a Centrifugal Pump?

A centrifugal pump is a hydraulic machine designed to transport fluids by converting rotational kinetic energy from an external source (e.g., an electric motor) into hydrodynamic energy. This transformation makes it possible for fluids to move from one place to another with impressive efficiency and scale.

Before engineering simulation tools like SimScale, engineers relied heavily on manual calculations and physical tests. Optimizing designs meant repeated physical testing, which was both time-consuming and tedious. Today, with cloud-native engineering simulation software, engineers can visualize flow patterns, pressure zones, and potential areas of cavitation within the digital environment. If inefficiencies are detected, modifications can be made instantly to the digital model and re-simulated.

How Does a Centrifugal Pump Work?

Key Components of a centrifugal pump

The main components of a centrifugal pump are:

• Impeller: The spinning part with curved blades. Fluid enters through its center, called the ‘eye,’ and exits by being pushed out through the blades.
• Casing: The housing that surrounds the impeller. Two main types of casings exist – volute and diffuser.
  • Volute casings have a curved shape, helping increase fluid pressure as the fluid flows.
  • Diffuser casings use stationary blades to increase fluid pressure.
• Shaft: Connects the impeller to the motor, allowing the impeller to spin.

In addition, centrifugal pumps also require shaft sealings (mechanical seals or packing rings) to prevent fluid leakage, a shaft sleeve to protect the shaft and position the impeller-shaft combo precisely, and bearings to minimize friction between the rotating shaft and the stator.

These parts can be divided into the pump’s wet end and mechanical end.

• The wet end components are responsible for the pump’s hydraulic performance; these are the impeller and the casing. In some designs, the first radial bearing can also belong to the wet end, where it is water-filled.
• The mechanical end components support the impeller within the casing; these are the shaft, shaft sleeve, sealing, and bearings.

Working Principle of Centrifugal Pump

When the electric motor turns the shaft, the impeller starts spinning (typically rotating at speeds ranging from 500-5000 rpm). This draws fluid into the pump. The spinning impeller pushes the fluid outwards.

The design of the casing then guides this fluid (either volute or diffuser), increasing its speed and pressure. The fluid exits the pump, typically from an outlet at the top of the casing.

Pump Comparison: Centrifugal vs Positive Displacement

Pumps are used to move fluids in different settings. Generally, the two main types of pumps are positive displacement pumps and centrifugal pumps. Positive displacement pumps keep a constant flow rate, whereas centrifugal pumps’ flow rate varies based on the fluid pressure. The choice of pump largely depends on the pump’s working principle, fluid viscosity, and application.

Positive displacement pumps are suitable for high-viscosity fluids and are used in food processing, oil refining, and pharmaceuticals. Centrifugal pumps, on the other hand, are suitable for low-viscosity fluids and are used in water treatment, irrigation, and heating/cooling systems.

The following table provides a direct comparison between centrifugal pumps and positive displacement pumps in terms of their operating principle, fluid type, flow rate, and more.

Types of Centrifugal Pump

Centrifugal pumps are a subset of dynamic axisymmetric turbomachinery. There are different types of centrifugal pumps that can be categorized based on specific criteria, such as impeller types, design codes, and applications. Here is a brief overview of the three main types of centrifugal pumps: radial pumps, axial pumps, and mixed pumps.

1. Radial Pumps

In radial pumps, fluid flows radially outward from the impeller’s center, perpendicular to the main axis. This type of centrifugal pump is used in cases where flow is restricted, and the goal is to increase the discharge pressure. Therefore, radial pump design is ideal for applications that require a high-pressure and low-flow rate pump, such as water supply, irrigation, and industrial processes.

2. Axial Pumps

Axial pumps work by moving the fluid in a parallel direction to the axis of the impeller. The operation of axial pumps is akin to that of propellants. Their most notable usage comes into play when there is a large flow rate and relatively low-pressure head required, such as fire pumps and large-scale irrigation systems.

3. Mixed Pumps

Mixed pumps combine the features of radial and axial pumps. They are capable of delivering high flow rates and pressures, making them ideal for applications such as sewage treatment and power generation.

Radial Pump vs Axial Pump vs Mixed Pump

Here is a table that summarizes the key differences between the three types of centrifugal pumps.

Single-Stage, Two-Stage, or Multi-Stage Centrifugal Pumps

Another way of classifying centrifugal pumps is by the number of impellers they have (or the number of stages), and they can be referred to as single-stage, two-stage, and multi-stage centrifugal pumps. A single-stage pump has one impeller, a two-stage pump has two impellers, and a multi-stage pump has three or more impellers.

• Single-stage pumps are the simplest and most common type of centrifugal pump. They are well-suited for applications where medium flow rates and pressures are required.
• Two-stage pumps are more efficient than single-stage pumps at delivering high pressures. They are often used in applications such as firefighting and industrial processes.
• Multi-stage pumps are the most efficient type of centrifugal pump, but they are also the most expensive. They are used in applications where very high pressures are required, such as oil and gas production and chemical processing.

Applications of Centrifugal Pump

Centrifugal pumps are used in a wide range of applications that involve turbomachinery, including:

• Water Supply: Whether it’s pumping water to homes, industrial plants, or agricultural fields, centrifugal pumps ensure a steady water flow.
• General Industrial Processes: Since many manufacturing processes rely on the consistent movement of fluids, centrifugal pumps help in transferring chemicals. For example, in a petrochemical plant or circulating coolant in machinery.
• Cooling Systems: In HVAC (Heating, Ventilation, and Air Conditioning) systems, centrifugal pumps circulate coolant to maintain temperature balance.
• Sewerage: Centrifugal pumps remove unwanted water, especially in areas prone to flooding or in construction sites.
• Oil and Energy Sector: In oil refineries and power plants, centrifugal pumps transport crude oil and hot liquids.
• Food & Beverage Industry: Safe and consistent transfer of liquids, like juices, syrups, and dairy products, is crucial. Centrifugal pumps offer a contamination-free and efficient solution.
• Wastewater Treatment: For processing and recycling wastewater, these pumps facilitate the movement of water through various stages of treatment.

Advantages of Centrifugal Pump

Centrifugal pumps offer advantages that can be quite useful in a variety of settings and applications:

1. Corrosion Resistance

Many fluids can rapidly corrode pumps, but corrosion-resistant centrifugal pumps can manage different fluids without deteriorating, thanks to the corrosion-resistant properties of their materials. Businesses see an increased return on investment (ROI) as the pumps last longer and require fewer replacements, maintenance, or repairs.

2. High Energy- and Cost-Efficiency

Centrifugal pumps use less power to move liquids, making them cost-effective. Any mechanical engineer would appreciate the savings they offer in terms of energy costs and efficiency gains.

3. Straightforward Design

When you look at a centrifugal pump, you see simplicity in action. These pumps don’t have countless parts, making them easier to produce, set up, and look after. In the long run, their design can lead to fewer repairs and a longer life.

Given their design simplicity and established principles of operation, engineers can use computational fluid dynamics (CFD) and other simulation tools to model their behavior under different conditions.

4. Stable Flow

For processes that need a steady liquid supply, centrifugal pumps are the go-to. They deliver a continuous flow, making sure everything runs as it should. This predictability can be crucial, especially when consistency is key to quality control in production lines.

5. Compact Design

Centrifugal pumps, with their compact form, are a perfect solution. They can fit adequately into tight spots, making them a smart choice for workshops and factories where every inch counts.

Disadvantages of Centrifugal Pump

While their advantages can prove effective in industrial applications, centrifugal pumps also have some drawbacks:

1. Inefficiency with High-Viscosity Feeds

Centrifugal pumps are best suited for liquids that have a viscosity range between 0.1 and 200 cP. With high-viscosity fluids like mud or slurry, their performance drops because they need to overcome greater resistance, and maintaining the desired flow rate demands higher pressure.

2. Priming Required Before Use

Centrifugal pumps can’t just start up on their own when they’re dry; they need to be primed or filled with the liquid first. This limitation means they might not be ideal for applications with intermittent liquid supply.

3. Susceptibility to Cavitation and Vibrations

Cavitation occurs when vapor bubbles form in the liquid being pumped due to sudden pressure changes, and then collapse when they reach areas of higher pressure. This phenomenon can lead to intense shock waves that damage the pump’s impeller and casing. The aftermath of cavitation is often visible as pitting or erosion on the impeller and the casing.

Centrifugal Pump Simulation With SimScale

By utilizing Turbomachinery CFD in SimScale, engineers can analyze their centrifugal pump’s performance and efficiency and identify areas of improvement in the design to ensure optimal operation. This analysis and design optimization can be further accelerated thanks to SimScale’s cloud-native nature, which enables engineers to run multiple simulations in parallel directly on their web browser without having to worry about any hardware limitations or installation complexities. They can also collaborate with team members and customer support in real time by simply sharing the link to their simulation project. As a result, engineers are empowered to innovate faster and optimize their pump designs more efficiently using SimScale’s powerful CFD solvers.

Here’s how SimScale helps the mechanical industry in centrifugal pump simulation:

1. Robust Meshing

SimScale’s Subsonic CFD solver provides a robust meshing strategy, generating an automated body-fitted mesh which is crucial for capturing the fluid flow accurately within and around the pump geometry.

2. Flow Analysis

SimScale allows for the analysis of various flow regimes including incompressible, compressible, laminar, and turbulent flows. This is essential in understanding how the fluid will behave under different operating conditions.

3. Cavitation Simulation

Cavitation, a common challenge in centrifugal pumps, can be simulated to understand its impact on pump performance. SimScale’s subsonic multiphase CFD solver computes the space occupied by each phase, providing insights into cavitation effects in pumps.

4. Pump Curve Generation

SimScale enables engineers to either input existing pump curve data or calculate pump curves for new designs by running parametric studies. This is crucial for ensuring the pump meets the desired performance criteria across a range of operating conditions.

5. Transient Analysis

The platform supports full transient analysis, modeling fluid flow in a time-accurate manner, which is vital for capturing the dynamic behavior of the pump under various operational scenarios.

Simulate Your Centrifugal Pump Design in SimScale

Centrifugal pumps have revolutionized industries with their efficiency, compact design, and ability to move fluids at varying rates and pressures. While centrifugal pumps come with their set of challenges, advancements in engineering simulation and CFD tools like SimScale have enabled engineers to optimize designs and predict performance. Sign up below and start simulating now, or request a demo from one of our experts. You may also follow one of our step-by-step tutorials, such as the advanced tutorial on Fluid Flow Simulation Through a Centrifugal Pump.

The post Centrifugal Pump: Design, Working Principle, & Simulation appeared first on SimScale.

This integration provides functionality for users interested in seamlessly creating CAD models of turbomachinery products such as turbines, pumps, compressors, and fans and running simulations to evaluate their blade profiles, pressure-flow characteristics, and efficiency requirements in SimScale.

CFD & FEA for Turbomachinery Modeling

Utilizing computational fluid dynamics (CFD) and finite element analysis (FEA) presents a valuable methodology for the design and analysis of pumps and turbomachinery systems, encompassing fluid, thermal, and structural behavior. CFD and FEA involve employing mathematical simulations within software programs to replicate the mechanics of fluids and structures, enabling the assessment of realistic assumptions.

These simulations encompass various heat transfer mechanisms, including conduction, convection, and radiation, as well as fundamental fluid behavior such as compressibility and turbulence. Consequently, CFD provides crucial insights into the behavior of moving fluids, offering data on parameters like velocity, temperature, and pressure. It also enables predictions regarding phenomena like cavitation, which arises when inadequate pressure at the pump’s suction end causes liquid to vaporize. In parallel, FEA empowers engineers to calculate loads, stresses, and failure points within pump and turbomachinery designs, facilitating comprehensive structural analysis.

Seamless Workflow from CAD to Simulation

With CFturbo, users can create completely new CAD geometries of turbomachinery products and modify existing designs. CFturbo guides the user step-by-step through the complete design process of a turbomachine, starting from as little as an initial design point as the input.

The CFturbo software now includes an export interface that lets its users export geometry from CFturbo and start simulating immediately in SimScale. The workflow is enabled using the SimScale application programming interface (API), which reads the exported 3D STEP file and related model settings from CFturbo and makes these simulation-ready for use in SimScale. Users can then follow the easy-to-use interface in SimScale to run simulations, post-process the results, and create insightful and compelling visualizations.

Key Benefits of the CFturbo-SimScale Combined Workflow

Simulation in the cloud leverages scalable high-performance computing with flexible pricing models and is a cheaper alternative to traditional desktop-based software tools. SimScale users for turbomachinery modeling also benefit from a binary tree-based mesher that results in a high-quality and more efficient mesh compared to competitive tools. The key advantages of using the CFturbo-SimScale combined workflow include:

• Fast simulation time and the ability to perform scenario analysis in parallel using design point parametrization; even for intricate geometries, users benefit from accelerated simulation setup, runtime, and stable simulation convergence that lead to faster insights and design decisions.
• Accurate simulations that allow users to create a full performance curve for a given design point and iterate on the baseline design
• Leveraging the above for design of experiment (DoE) and optimization studies using third-party tools–enabled by the strong APIs in CFturbo and SimScale that come with examples and documentation on how to get started quickly.

Turbomachinery Modeling: From Pump Design to Simulation

Designing the Pump in CFturbo

An end-suction close-coupled (ESCC) centrifugal pump is designed in CFturbo. The following design features and operation requirements of the pump’s design point, or best efficiency point (BEP), are used as inputs to rapidly create the pump design from scratch:

With the combination of the design point’s flow rate, pressure head, and rotational speed defined, the corresponding machine type is categorized as a medium-pressure centrifugal pump.

Pump Design Exported to SimScale for Simulation

The pump design that is generated based on an ideal design point requirement, however, will not necessarily perform exactly as intended. This is why a simulation tool such as SimScale is needed to predict and validate its actual performance. The CAD model and design conditions are seamlessly exported to SimScale and are ‘simulation-ready’. We have simulated five flow rates in parallel, and a 640K cell mesh is auto-generated when hitting the simulate button:

• The full pump curve of five operating points is run in 40 minutes
• Compute cost of obtaining the full pump curve is 10 core hours (CHs), equating to less than $3 USD of computing cost.

The SimScale Subsonic simulation predicted that the generated pump design’s pressure head at the design point flow rate would be 3.3% less than the specific pressure head.

The shaft power and efficiency of the design point / BEP simulation results are as follows:

Looking at multiple operating conditions and their corresponding performance, a pump performance curve is generated using SimScale. The set of flow rates used is highlighted below, and the results of the simulation are plotted in the following pump curves.

Webinar with CFturbo

Watch this webinar where experts from SimScale and CFturbo walk you through the automated design-simulation workflow.

Attend Webinar

The post Boost Your Turbomachinery Modeling with SimScale & CFturbo appeared first on SimScale.

A heat circulator pump is a centrifugal pump designed to circulate heated fluids in closed systems like boilers, hot water pumping, etc., or open systems like swimming pools. Such pumps are subjected to high-temperature fluids and low-pressure heads in the circulating region, relative to the system pressure. Some common applications where heat circulator pumps are employed include underfloor heating systems, boilers and hot water circulators in buildings, ventilation, air conditioners, heat recovery systems, industrial recovery systems, etc. 

If not designed efficiently, heat circulator pumps can be the biggest energy drains in a heating or cooling system. The EU has placed stringent requirements on the design of circulator pumps, in-line with the aspiration to transition to a low-carbon economy by 2050. The “Energy-related Products (ErP)” directive of 2009 established an ecodesign framework for the design and operation of many ErP products including heat circulator pumps. Under this directive, manufacturers are required to comply with the prescribed energy and resource efficiency standards in order for their products to be sold in the EU.

The efficiency of heat circulator pumps is rated based on their ‘Energy Efficiency Index (EEI)’. EEI is a measure of how much the power input of the pump is lower than the prescribed power input. For example, an EEI of 0.21 means that the pump only utilizes 21% of the threshold power input. Thus, the lower the EEI value, the better the efficiency rating of the circulator pump. KSB, a world leader in pump and valve manufacturing, has a range of high-efficiency products like the Calio (EEI ≤ 0.2) and Calio Z (EEI ≤ 0.23). Read on to learn how KSB continues to innovate on the ecodesign of heat circulator pumps by using a simulation-driven approach in SimScale.

KSB Heat Circulator Pump Design and Optimization: Project Objectives

EEI is governed by the average power consumption across the load profile, compared to the reference hydraulic power. Typically, power consumption at 4 weighted flow rates, as shown in the hydraulic curve below, is used to evaluate the EEI. The weighted flow rate, Q_100%, is taken as the flow rate where (Q x H) is maximum and that is extrapolated to get the weighted flow rates Q_75%, Q_50%, and Q_25%, and the corresponding Power ‘P’ at those flow rates. 

Using the control curve shown in green, the weighted average electrical input power is calculated (Eq. 1) and is then used to compute the EEI of the specified circulator (Eq. 2).

Eq. (1) P_el,avg = 0.06 x P_L,100% + 0.15 x P_L,75% + 0.35 x P_L,50% + 0.44 x P_L,25%   

Eq. (2) EEI = (P_el,avg / P_hyd,ref) x C                            

where: 

P_hyd,ref = reference power

C = calibration factor ~ 0.49

Currently, the pump rarely ever operates at the best efficiency point. Motor power is usually limited which shifts the Q_100% to the left, resulting in a new control curve (dashed green line in figure 1). This means that the final EEI is now dependent on the motor as well as other systems components, most of which get finalized only in the final stage of the production process. 

This is the precise problem that the turbomachinery expert at KSB Germany, Toni Klemm, was faced with. How does one quickly select an impeller design, subject to specific EEI requirements, at the last stage of the production cycle? Does one leave the impeller design until late in the production process, risking a longer time to market as well as higher prototyping costs?

SimScale, in partnership with Friendship Systems AG, the makers of CAD design and shape optimization software CAESES, provided a cost-effective, simulation-driven approach to solve KSB’s problem. A hydraulic toolchain was developed to create a surrogate model of the pump impeller, which can be queried to select the right design based on the system requirements before production. 

Overview of SimScale – CAESES Workflow

CAESES is a powerful CAD modeling and shape optimization software, which can be integrated with any simulation-driven optimization loop. Its dependency-based modeling approach is fully automated and it comes with inbuilt strategies for flexible parametric design and shape optimization. 

SimScale’s turbomachinery solver combines best-in-class CFD techniques with cloud computing to accelerate simulation-driven design and analysis of pumps and turbomachinery. The solver accuracy is close to 2% in comparison to test data and a designer can calculate an entire pump curve, by simultaneously running multiple simulations in the cloud, in 15 minutes. This is possible using input parameterization for fast design prototyping and CAD associativity for easy geometry variation. A simple application programming interface (API) enables the integration of the turbomachinery solver with third-party optimization and design of experiment (DoE) tools. 

In this case study, the parametric CAD geometry of the heat pump impeller was generated in CAESES, which was connected with SimScale via the API for running a DoE to evaluate the parametric hydraulic performance curves. The CFD-driven performance characteristics for different designs were fed back to CAESES for surrogate model creation and optimization. 

The CAESES – SimScale workflow can be summarized as:

DoE in SimScale: Simulation Setup and Results

14 design variables were chosen for CAD parameterization in CAESES. These include:

Number of blades

Meridional contours (3 parameters)

Blade angle distributions 
• 2 parameters for LE and TE blade angles
• 2 parameters for the hub to shroud variation of LE blade angle
• 6 parameters for shape control of beta functions between LE and TE

For each design variant, 3 flow rates needed to be run (0.7, 0.85, 1.1 x Q/Q opt). A simple python script enabled the transfer of Parasolid CAD geometry and simulation inputs from CAESES to SimScale’s turbomachinery solver, where geometry meshing and simulations were run. The CFD simulations assumed incompressible, steady state, fully turbulent flow across the pump impeller, and further input condition parameterization was employed to run all three flow rates per geometry variant together. This enables automatic calculation of the performance curve including the pressure head across the impeller, shaft power, and efficiency, which are sent back to CAESES. The flow around the impeller for changing the blade exit angle and the corresponding performance curves are shown in Figure 2.

A massive DoE comprising 377 design variants (900+ simulations in total) was run in parallel in SimScale to evaluate the hydraulic performance of each variant and send it back to CAESES. The DoE statistics are given below:

Surrogate Model Creation and Optimization in CAESES

The DoE results from SimScale include 9 output parameters (head, efficiency, and power for 3 flow rates) as shown in Figure 3. Using these, surrogate models were created in CAESES by leveraging the inbuilt RSMtools feature and response surfaces for each of them can be visualized.

Next Steps

Optimizations on the surrogate models for minimal EEI are being planned. This needs measured performance curves for the full pump configuration, which will be approximated from the impeller-only DoE results. Testing of the surrogate models is also in progress, where the average power consumption at the weighted flow rates now computed should lead to lower EEI.

Faster Innovation With Simulation-Driven Design in SimScale

Using cloud-native simulation in SimScale accelerates product innovation by opening up a vast design space that is otherwise not possible due to cost and time constraints. In this case study, we saw how KSB company combined the DoE results from SimScale with optimization strategies in CAESES to develop a novel methodology for the rapid selection of circulator pump impellers while adhering to EU’s ecodesign regulations. A turnaround of 1.5 days for a DoE of 300+ designs at a compute cost of $300 is the perfect motivation for companies to embed cloud-native simulations in their product development cycles, from conceptual design all the way to production.

Be sure to watch the on-demand webinar to hear the full story on heat circulator pump optimization from Toni Klemm (KSB) and Mattia Brenner (Friendship Systems AG).

The post Design and Optimization of KSB Heat Circulator Pump Using SimScale and CAESES appeared first on SimScale.

Forced convection cooling is an essential component of modern electronics where high power density devices and enclosures generate heat that needs dissipating. In many cases, natural ventilation-based heat rejection is not always enough, and fans must be used. Fan performance can be complex and based on several variables that need accurate representation in any modeling and analysis. Fan manufacturers provide a fan curve that describes the relationship between static pressure, power demand, speed, and efficiency values per-flow rate. This information is essential for cooling purposes, so we need to model the fan curve when possible. The pressure flow characteristics described by manufacturer fan curves dictate how the volume flow from a fan is affected by pressure drop. Most fan manufacturers provide this data based on standardized testing according to international standards.

Engineers evaluating different fan types and sizes in their device designs must be able to account for the fan curve and trust that it is a true reflection of how the fan might perform in real-world conditions. Creating a digital twin of the fan curve is an excellent way to simulate its performance. The SimScale platform is a cloud-native engineering simulation tool for general purpose flow, thermal and structural analysis. A typical application is the analysis of electronics enclosures for thermal management, specifically, scenario testing multiple cooling strategies. Fan behavior can be simulated in several ways in SimScale. A boundary condition where the fan inlet is placed can have a direct mass flow applied to it as a velocity inlet with appropriate fluid material properties and ambient temperature. Alternatively, a momentum source can be defined to represent the flow from a fan, and, most recently, engineers can now upload fan-curve data in a tabular format directly into the SimScale platform and use it as a boundary condition.

Thermal Performance of a Raspberry Pi Computer

To demonstrate some of the fan modeling features in SimScale, we have simulated a Raspberry Pi computer using a publicly available 3D model of the device taken from GrabCAD. A conjugate heat transfer simulation with forced convection (fan) is used to model the computer using standard 30 mm fans for cooling. We have used manufacturer data for the fan performance, which comes in four different model types; each has a fan-curve providing data on volumetric flow rate and pressure drop (static) at ambient conditions. We have taken the 3D model and simplified it using the CADmode editing features in SimScale. The study is not interested in geometric changes to the enclosure, only in fan and cooling performance.

We can directly upload the manufacturer fan curve data and derive the fan operating points explicitly using simulation. We want to show how the manufacturer’s data can be applied to the former. We can extract the fan specification sheet data into a spreadsheet to upload into SimScale and perform a complete thermal analysis of a Raspberry Pi. In the latter case, we can conduct a flow rate study using simulation to derive the fan operating point, e.g. at what flow rate can we generate the given pressure drop and derive a system resistance curve. Using the parallel simulation capabilities in SimScale, we can run multiple operating points simultaneously and begin to generate the fan curve for evaluating how efficient these fans are for cooling purposes and whether they adequately cool the computer chips in the enclosure. This approach is instrumental when the full fan curve data is not available or to assess in-situ fan performance in the system or device (the manufacturer data is for a simple test setup).

A simplified evaluation might look like this:

• Use the original CAD model and a fan curve as the baseline case
• Derive operating points from simulation
• Derivation of system resistance curve from flow rate study
• Cooling efficiency comparison with different fan models
• Compare to directly uploading manufacturer data

We have used the conjugate heat transfer (CHT) analysis type in SimScale. The CHT analysis type allows for the simulation of heat transfer between solid and fluid domains by exchanging thermal energy at the interfaces between them. Typical applications of this analysis type include heat exchangers, cooling of electronic equipment, and general-purpose cooling and heating systems. A multi-region mesh is required for a CHT simulation to have a clear definition of the interfaces in the computational domain. With the interfaces adequately defined, this is automatically taken care of in SimScale and, in this case, generates a five million cell mesh. For the simulation setup – fan inlet and pressure outlet boundary conditions are used, the air is used for the flow region, and several materials are specified for the chips and electronic components, including Copper, PCBs, Silicon for chips, and Aluminum for heat sinks. Power values represent the CPU (3 watts) and more minor chips (0.25 watts). The air inlet is ambient at 19.85 ℃, and a CSV file is used to upload the fan curve for later use. 

Thermal Simulation of Electronics Cooling

We can visualize heat removal on the chips by looking at surface area average temperatures. The images show up to 392 K on the CPU (max). SimScale will also extract point-specific data and pressure drop across inlets and outlets. Fan inlets show a 4.78 pascal (0.5 mmAq) pressure difference at a flow rate of 7.55e-4 m3/s, and this matches the fan curve data sheet for the baseline model (L). The fan outlets are at 0 gauge pressure as intended. We can easily switch the fan curve data to simulate a more robust fan (H) for comparison. Doing this shows us a 10 pascal (1 mmAq) pressure drop, and the two are compared in the image below. By doing this analysis, we can start generating a system curve for the enclosure (Raspberry Pi) derived from simulating various fan operating points (Orange line in the image below). Running ten simulations of different operating points in parallel, we generated the entire system curve for the Raspberry Pi in two hours. Chip cooling performance based on comparing the two fans is also shown, with the more substantial model H fan better at removing heat.

Fans as Momentum Sources

In some cases, modeling the fan as a momentum source might be needed. Momentum sources can be used to simulate fans, ventilators, propellers, and other similar fluid acceleration devices without having to model the exact geometry of the device. For instance, users might want to model a fan whose dimensions and output velocity are known. With this feature, it is possible to assign average velocities or fan curves to volumes of interest. An external flow domain is needed here to act as the air supply for the CAD opening where the fan would be, and a momentum source is used to define the flow behavior. Users can upload the fan curve, decide which direction the flow is going, and add a geometry primitive cylinder as the source. The external flow domain is used because flow enters the fan as it would do in a reality where the fan inlet is the interface of internal and external boundaries.

Summary 

Simulation is now considered essential to optimizing electronic product design and performance. Using multiple methods to represent complex fan performance, engineers can quickly evaluate the cooling impact of fan types, and using the parallel simulation capabilities in SimScale, a more comprehensive range of scenarios can be evaluated. In summary:

• Fan curves: allows modeling of fans based on fan curves (flow rate to pressure drop relation)
• Fan boundary condition: users can specify a fan inlet or fan outlet as a boundary condition to model fans that are placed at the edge/outside of the enclosure domain.
• Fan Momentum Source: allows modeling of internal fans as a momentum source that are embedded within the model.

Furthermore, in the same platform, engineers can perform virtual shaker table tests, structural analysis, and more specialist fluid flow analysis using the same CAD model and simulation environment. 

To learn more, watch the fan modeling webinar below:

The post Electronics Cooling Using Fans appeared first on SimScale.

Access to simulation tools is critical at all design stages of pump and turbomachinery design to minimize performance issues later in product development. Simulation using SimScale can be used for cavitation modeling to understand its effect on the performance of real-life pumps.

A rotating machinery engineer working on a new product or component can import and edit their CAD model in SimScale to perform multiple analysis types such as computational fluid dynamics (CFD), structural, and thermal using automated workflows and intuitive user interfaces. A thorough treatment of the cavitation phenomenon and parametrically studying pump geometry is possible thanks to the practically unlimited computational power of engineering simulation in the cloud.

In this article, we demonstrate how to set up the process of a cavitation simulation, including how to identify cavitating flow and the essential design factors influencing the onset of cavitation, such as the net positive suction head required (NPSHR), cavitation number, and inlet sizing.

Fast and Accurate Pump Simulation

The advanced physics solvers in SimScale allow designers and engineers to study and optimize pressure drop and force behavior, evaluate fluid flow patterns, and manage cavitation effects. The SimScale Subsonic CFD solver is a multi-purpose analysis type designed explicitly for turbomachinery, propellers, and, more generally, anything that rotates within a fluid. It includes a robust meshing strategy that produces an automated and robust hexahedral cell mesh, using the body-fitted Cartesian meshing technique that significantly reduces mesh generation times by an order of magnitude.

It uses a finite volume-based solver optimized to handle a wide range of flow regimes, including: 

• Incompressible (isochoric)
• Compressible
• Laminar
• Turbulent

The highly parallelized meshing algorithm gives a higher quality mesh requiring much fewer cells to attain comparable accuracy to traditional discretization schemes. This technique leads to faster convergence and hence, faster simulations.

The Subsonic analysis type simulates incompressible and compressible flow, with turbulence modeled using the RANS equations and the k-epsilon turbulence model. A powerful feature of this analysis type is the built-in parametric capability for defining velocity inlet boundary conditions. At the simulation setup stage, users can define multiple inlet flow rates simultaneously that are then simulated simultaneously; these can also be uploaded using a spreadsheet with pump curve data.

Using Simulation to Study Cavitation in Pumps

Cavitation is the formation of vapor bubbles in low-pressure and high-velocity regions of liquids. In this example of a centrifugal pump, we are interested in using simulation to inform the adverse effects of cavitation that can cause damage to equipment, such as wearing impeller vanes, erosion of mechanical bearings, seals, and valves, and unwanted noise and vibration. Cavitation can also reduce flow performance for a pump. 

When the cavitation bubbles collapse, they generate shock waves that create mechanical vibration and acoustics noise. Cavitation in pumps is a critical real-world effect that SimScale factors into the CFD simulation of pumps, water turbines, marine propellers, or any rotating machine immersed in a fluid.

The compressible effects of the vaporization are modeled within the cavitation model separately from the incompressible CFD flow modeling. Since the overall flow volume is water in this example, an incompressible fluid, then incompressible flow modeling is selected. Cavitation properties of the water, or any other fluid, are characterized by setting the bulk modulus (or fluid elasticity), the saturation pressure, and its molecular weight, all defined in the materials library. The local flow characteristics, along with these material properties, determine the extent of the cavitation within the flow domain.

SimScale computes the space occupied by each phase (volume fraction), and the cavitation results are shown as the volume fraction of gas in the liquid.

Pump Simulation Setup

A simple workflow is required to complete the analysis for the centrifugal pump. 

Import & Prepare Geometry

Users can import many types of standard CAD file formats and use CAD connections with tools such as Onshape, Solidworks, AutoCAD, and more. The CADmode feature in SimScale allows users to perform basic CAD operations, extract the flow volume and define a cylinder as the rotating zone within the platform.

The pump geometry is imported from Onshape. The flow volume domain is extracted using the Internal Flow Volume extraction tool in CAD mode, and a cylinder is created to define the rotating portion of the pump.

Simulation Set Up

The next step is to create a Subsonic analysis type simulation from this flow volume geometry. The main steps an engineer would undertake to define the simulation are to assign: the flow material, the inlet and outlet flow conditions, and the rotational velocity of the pump.

Selecting the Subsonic analysis item at the top of the navigation sidebar gives access to toggle the cavitation modeling and time-dependency of the simulation (whether the simulation models steady-state or transient flow behavior). For this case, the material and cavitation properties of water are already integrated into the extensive SimScale materials library. However, other fluids can be defined based on their density, viscosity, and cavitation properties and saved in the database.

The flow rate going through the pump can be defined either at the inlet or outlet face, depending on the operating conditions the engineer wants to define; this can mean the pump system can be defined by a suction flow rate, a discharge flow rate, or a specified pressure difference. The flow rate condition can also be parameterized to a progression of flow rates so that multiple simulations at different flow rate conditions can be run in parallel.

The rotational velocity of the pump blades is defined within the Advanced Concepts → Rotating zones section, where the rotation axis also needs to be specified.

In the case of this centrifugal pump geometry, the following boundary conditions have been applied:

Case A: Varying Discharge Flow Rates

• Inlet – flow rate sweep from 1 L/s to 11 L/s using velocity inlet boundary conditions.
• Outlet – pressure outlet (1 atm) boundary conditions modeling ambient conditions.
• Impeller – rotational speed around the vertical axis set to 500 radians/s
• Physics – incompressible, fully turbulent flow

Case B: Varying Suction Pressure Heads

• Inlet – flow rate of 11 L/s using velocity inlet boundary conditions.
• Outlet – pressure outlet sweep from 3.4m to 6.2m of water head pressure
• Impeller – rotational speed around the vertical axis set to 500 radians/s
• Physics – incompressible, fully turbulent flow

Meshing

The meshing process discretizes the flow domain into a finite set of cell volumes that aims to match the original geometry. Within the Subsonic analysis type, the workflow for generating the mesh is automated and robust in capturing varying levels of geometry detail; the user defines the level of mesh fineness on a sliding scale from 1 to 10.

The automated meshing process generates a body-fitted Cartesian mesh, ensuring the mesh quality is highly orthogonal. A manual process of defining the minimum, maximum, and target cell size is also available for further control of the process. For this centrifugal pump geometry used in this case, the mesh size was on the order of ~500K cells.

Post-processing 

The SimScale platform’s field results visualization tool allows engineers to understand the flow behavior throughout the entire flow domain. Some significant quantities to look at for a pump application include the pressure distribution, the flow velocity along with the velocity vectors, and the cavitation effects.

Cavitation is modeled within SimScale using the gas volume fraction quantity so the intensity of cavitation can be visualized just like any other field quantity. The use of cutting planes can give a planar view of the distribution of these field quantities, but the iso-volume feature presents the regions where specific field quantities fit within certain criteria; this can be used to get 3D insights on key flow behavior attributes that are of interest to the engineer, such as the extent of the cavitation behind pump blades.

The total gas mass fraction is visualized in SimScale, shown in the image below. In a region with a high volume mass fraction, there is a high chance of cavitation developing. When the flow hits the leading edge of the impeller, it accelerates and then creates low pressure. If this pressure drops below the fluid’s vapor pressure (water), it can lead to cavitation.

In this case, cavitation is seen around the impeller extending into the inlet pipe due to air bubbles trapped in the entire volute casing.

Understanding Cavitation in Pumps

We have simulated two-pump flow rates to ascertain the adverse effects of cavitation. The images below show significantly less cavitation with a higher flow rate of 11 L/s than 1 L/s. In the latter scenario, the higher pressure at the outlet creates an intense cavitation effect around the impeller. With this simulation setup, users might continue with additional flow rates and perform an optimization study on flow rate vs cavitation propensity.

Additionally, users can duplicate the entire setup and swap the geometry with an alternative CAD model design. This step would preserve all the simulation parameters and boundary conditions, and multiple pump designs can be evaluated in parallel. CAD Geometry variants to consider exploring should include various volute casing shapes, length of inlet and outlet pipes, and even the impeller profile. 

SimScale can also simulate all the points on a pump curve in parallel using the fast and accurate subsonic analysis type. Manufacturers provide performance curves that tabulate static pressure, power, rotational speed, and efficiency values per-flow rate conditions. This data is used for selecting and sizing pumps.

SimScale allows engineers to directly input the manufacturer’s data and simulate its performance. When designing new pumps, SimScale can calculate the pump curve for a design by running parametric studies that solve for a range of pressure/flow points. The highly parallelized algorithm allows a parametric study to run nearly simultaneously as simulating a single pressure/flow condition.

Other pump analysis types include static/dynamic loading, stress, and vibration analysis using the structural simulation capabilities in SimScale, making the platform a powerful tool for turbomachinery engineers.

Webinar: An Introduction to Cavitation Analysis in SimScale

This on-demand webinar shows a step-by-step demo of the cavitation modeling capability available in SimScale to understand its effect on the performance of a real-life pump. Gain a thorough characterization of the phenomenon of cavitation in pumps, along with an understanding of the design factors that lead to cavitation:

The post Analysis of Cavitation Effects in Pumps appeared first on SimScale.

Automated Mesh Refinement

A robust, automated body-fitted mesher with local refinement has been specifically developed for turbomachinery/pump applications. This new capability consists of two related features: An improved automated global mesher and the semi-automated local refinement feature. Together they provide users with more granular mesh control around areas of interest such as rotor/impeller blades, rotor wake, or any small features that could be important to factor into a simulation. 

The resultant body-fitted meshes are highly optimized and yield accurate results whilst considerably reducing the numerical problem size. Thus yielding proportionally faster solution times and consumption of fewer CPU core hours boosting an engineer’s productivity. Here are some examples: 

Automated Global Mesher

The new global mesher is very robust and able to handle complex CAD geometry with minimal cleanup. When Automatic Mesh settings are chosen, a Fineness slide bar is available allowing a value between 1 to 10 to be set as shown below:

Below is an example of the new mesher applied to a drone/UAV quadcopter, where the new global mesher achieved approximately a 50% reduction in mesh size (number of cells) with the same accuracy, and a 20-30% reduction in solver runtime.

Local Mesh Refinement

This feature allows a user to specify a target cell (element) size for the model contained within a defined geometry primitive (either a cylinder or cartesian box), and as such enables both fine or coarser mesh regions to be defined.

The mesh coarsening approach can be effectively used to reduce the numerical problem size (the number of cells/elements) substantially by defining a relatively coarse mesh in less important regions of the model such as in the upstream or downstream far field. Any number of refinement regions can be defined with independent degrees of refinement, plus this feature can also be used in conjunction with SimScale’s automatic global mesher that acts on the entire model for further control over the meshing. Here’s an example of the local mesh refinement applied to the impeller region of an axial centrifugal compressor:

Workflow Enhancements

We’ve also released several workflow enhancements to help users accelerate parametric design iterations and save time when setting up their simulations.

Onshape^® CAD Associativity

A very common workflow is to swap geometries being simulated in a project to compare the performance of similar variants. In such cases, with most simulation tools, the user will have to re-assign all of the loads and boundary conditions to the geometry, and this can take a significant amount of time. This new feature automates the assignments and/or retains as many assignments as possible between similar geometries when using geometry from Onshape®. This makes it very easy to run simulations with multiple versions of a part or assembly, and can even be automated through the use of the Simscale API. Note that this is a distinct feature from parametric geometric variation where one or more dimensions are varied per simulation.

Personal Material Library

While commonly used materials like steel, iron, aluminum, etc are provided in the default material library, users are able to create custom materials within a project. The new Personal Material Library extends this functionality by allowing users to create their very own Materials Library that can be shared across projects.

Visual Result Comparison

Users can investigate two models side-by-side, matching field result viewing angles, cut plans, contours, and legends allowing for a direct comparison. This feature is valuable in highlighting differences (or similarities) in results, especially when simulating variations of the same design. The two side-by-side comparison views can also be decoupled, allowing independent exploration of each model. This can be very useful when generating images for reports/presentations, for example when an engineer needs to maintain global context while showing a zoomed-in or rotated view at the same time.

Cloud-Native Simulation for Turbomachinery Applications

SimScale is committed to making fast and accurate simulation accessible to designers and engineers involved with developing turbomachinery, pumps, and propellers enabling simulation adoption throughout the product’s lifecycle. Our proprietary simulation technology is already helping companies in this industry realize significant product research, development and manufacturing costs, and resource savings, which in turn allows them to bring better, innovative products to market faster.

Learn even more in our on-demand webinar, Automated Mesh Refinement and Advanced Physics for Rotating Machinery. See how local mesh refinement can be used to create high-quality meshes for rotating machinery applications while optimizing simulation turnaround time and core-hour utilization:

The post Automated Mesh Refinement and Workflow Enhancements for Turbomachinery and Pumps appeared first on SimScale.

In this blog article, we discuss a centrifugal pump use case where engineers are faced with the challenge of optimizing the pump design based on seven parametric variables. A fully integrated and automated workflow is used, linking three cloud-based CAE solutions: Onshape, SimScale, and the engineering tools offered by ESTECO.

Onshape: Cloud-Native CAD

The simulation workflow starts with a mechanical CAD model of the centrifugal pump, which is designed in Onshape. Onshape offers a cloud-native product development solution that enables designers and engineers to access their design documents and collaborate from anywhere, on any device.

The model has seven key geometric parts to it that have been parameterized, allowing for design variations that can be automated. These include the blade angle, thickness, radius, number of blades, inlet length, and diffuser dimensions.

Each variation in the above parameters gives a new CAD model generated in Onshape. Using the APIs, these CAD variants are pushed from Onshape to SimScale, for simulation and analysis. 

ESTECO: Multidisciplinary Design Optimization

The centrifugal pump CAD model has seven geometric design parameters. Engineers might want to evaluate 10 values per parameter, to begin with, giving up to 1 million possible design variants that would need testing. This represents an extremely large solution space that would be time and cost-prohibitive to explore. A method is needed to downsize the number of potential final design values without compromising on optimum efficiency.

Using the integrated workflow between Onshape, SimScale, and the optimization tools offered by ESTECO, the 1 million design permutations are reduced to only 65, using Multidisciplinary Design Optimization (MDO) available in modeFRONTIER (from ESTECO).

This optimization technology is game-changing for two reasons: The design update process is fully automated, and the optimization is driven by a highly efficient self-adaptive algorithm capable of searching for the global optimum within the solution domain, using a very limited number of design iterations and therefore bypassing the classical trial-and-error approach. This objective-driven optimization step intelligently chooses which parameters to change and optimizes the design for maximum efficiency, as defined by the engineer.

SimScale: Cloud-Native CFD Simulation

The SimScale platform provides an API layer that allows access to all of the different physics and simulation capabilities in addition to geometric parameters. In this case, SimScale is used to perform an incompressible CFD analysis on each of the 65 CAD geometry variants.

All 65 CAD models are simulated in parallel using a single simulation setup for meshing, boundary conditions, material properties, and solver parameters. SimScale will output results for physical variables such as total head, pressure drop, flow velocity, temperature, etc., that can be used to calculate pump efficiency and feed into the optimization algorithms.

Modeling, Simulation, and Optimization with Cloud-Native Software Stacks

Once the simulations are complete, engineers can receive notifications and begin to analyze the results in SimScale or third-party tools. In this example, the simulation process workflow, together with the defined optimization strategy, is then uploaded to the VOLTA platform to execute the runs in a distributed environment.

Optimization results are then post-processed in the VOLTA Advisor tool, using advanced visualization tools to address the optimized centrifugal pump design directly in the browser. Results can be easily shared with members of the project team. This workflow also includes a feedback loop. Using ESTECO’s tools, engineers can then select which parameters to alter during run-time in order to continuously optimize the design further. 

By adopting a modern cloud-native CAD and simulation tool workflow together with process automation and decision optimization stacks, organizations can implement a design-simulate-optimize workflow in their product development cycle.

Whitepaper: Engineering Design, Simulation, and Shape Optimization

To learn more about the power and value of geometric parameterization of a simulation model coupled with design optimization feedback, download our whitepaper:

Download Whitepaper

The post Modeling, Simulation, and Optimization with Onshape and ESTECO appeared first on SimScale.

A turbomachine transfers energy between a rotor and a fluid. In this way, mechanical energy is converted into pressure or head. Usually in turbomachinery design, an engineer’s main goals are efficiency, reliability, performance, and extended lifespan. Roughly put, a machine should perform as well as possible, for the longest time possible, efficiently recover as much energy as possible, and require as little maintenance as possible. While these factors are in the direct interest of manufacturers, suppliers, and customers, additional considerations such as noise pollution or emissions output are increasing in importance due to tightening regulations on environmental impact and an increased demand for comfort. All of these aspects require careful calculation in the design phase.

Turbomachinery Design Our Case: Centrifugal Pump Design with CFD

As an example of turbomachinery, this case simulates a common pump type; a centrifugal pump. This type of pump converts rotational energy into energy in a fluid via a rotating element. In the aim of maximizing efficiency, it is crucial to reduce loss of energy in order to ensure that the machine is harnessing as much power as possible. Energy losses could occur, for example, due to friction or recirculation. Computational fluid dynamics, or CFD, makes it possible to quantify performance in the form of torque, axial thrust, pressure drop, and velocity of flow at any point inside the domain to identify areas that could be optimized for efficiency.

There are many design aspects that can affect the efficiency of a pump such as casing, shrouding, number of impeller blades, or blade angle, to name a few. Focusing on the impeller, changes could be made to its size, such as by increasing diameter , however this would increase mass and therefore lead to greater energy loss. Trying to find the trade-off between impeller size and mass presents a challenge to engineers seeking maximum efficiency.

In the case of the centrifugal pump design with a central impeller, CFD is a beneficial tool in analyzing efficiency. Using CFD an engineer can analyze the performance of a design, easily changing parameters to see how flow is affected and creating a pump curve for efficiency.

With CFD, it is much simpler and faster to try to find the most efficient design based on the best scenario at a specific speed. Simulating designs allows for fluid flow analysis without the need for physical prototyping, which can consume both time and costs.

Simulation Setup

The simulation was set up using an incompressible, steady-state analysis with a K-Omega SST turbulence model. This type of analysis is robust and well-suited to applications with rotating components. Where some pumps may be used for substances such as oil, sewage, or food and beverages, this pump will be used for water and so the fluid type selected was water at 20°C.

For this project, the geometry was imported as three volumes; the impeller volume, a volume for the rotating region, and the fluid flow volume. The part that could be considered the most challenging is the impeller itself as it is constantly rotating. For this reason, the additional volume of the rotating zone is included and a multi-reference frame method (MRF) applied.

The MRF method is a simple and less computationally demanding way to analyze the behavior of a rotating element without having to rotate the geometry in a simulation. It gives a reliable approximation of transient rotating motion at an instance of time. For this analysis, the angular rotational velocity of the rotating zone is set to 350 rad/s. The inlet is inputted as a volumetric flow rate of 0.004 m3/s, a parameter that can be easily changed to simulate different operating conditions, in parallel runs. And the outlet face has its pressure set at 0 Pa, which can be monitored, alongside the inlet face for both average and integral results.

Results

The results of this CFD analysis reveal many opportunities for design optimization. In particular, certain changes in velocity and pressure demonstrate areas where energy is lost. The flow velocity pattern of this analysis shows a few key areas where energy is lost. Flow velocity clearly diminishes past the cutwater, and flow recirculation occurs around the eye of the impeller. This recirculated fluid does not contribute to pump performance, and adjustments should be made to recover this lost energy, such as changes to the shroud geometry.

As fluid enters the spiral volute of a pump, it is transformed into pressure energy. In the ideal design, the pressure increase experienced in this region is smooth and gradual. In the initial run of this design however, there is a sudden decrease in velocity at the beginning of the spiral volute. This is sure to negatively impact the efficiency of the pump and should be reviewed.

Taking a closer look at the particle traces simulation, flow vortices can be seen at the entrance of the pump, a common phenomenon that uses up energy without contributing to power output. In this case, the impeller rotation is inducing a vortex at the inlet. To limit this effect, the engineer could decide to include fins in the pump housing to create a more efficient design.

The isosurface results reveal valuable insights for performance optimization. Extremely low pressures in the corners of the impeller blades, close to the eye, suggest the risk of pump cavitation. Pump cavitation not only represents wasted energy consumption, but can also cause significant damage and premature failure of the impeller and surrounding components. Excessive noise also becomes an issue in this case due to shockwaves.

Centrifugal Pump Analysis Conclusion

This simulation demonstrates how useful CFD can be in identifying areas in a design that negatively impact on efficiency. Using results such as these, an engineer can make informed design decisions to optimize a turbomachinery design for improved overall performance, reliability, and value—all from the comfort of their web browser.

If you are interested in finding out more information surrounding this topic, make sure to check out the following:

• Introduction to Pumps & Water Turbines
• Turbomachinery Pump Curves
• Simulating Rotating Zones with MRF
• Public Project: Simulation of Centrifugal Pump

The post Optimizing Efficiency in Centrifugal Pump Design appeared first on SimScale.

Pump Curve What is a Pump Curve?

Performance curves usually include three things—an efficiency curve, a pressure curve, and a power curve, and these all have use and meaning when analyzing a system that includes pumps.

Pump Curve Efficiency Curves

Efficiency curves describe the efficiency at each operating point of the pump; where the peak efficiency of the pump will produce the most power output with the least power input. The efficiency of turbomachinery depends upon whether it is recovering energy or providing it. In this case, a pump is providing energy to a fluid and therefore the efficiency is the ratio of power out of the system and power into the system.

Pump Curve Power Out and Pressure Difference Curve

The power out of the system is measured from the flow. To measure this, power is the volumetric flow rate multiplied by the pressure difference across the system. In terms of recovering this information from CFD, we can monitor the average pressure at the inlet and outlet boundaries to obtain the pressure difference, and then observe an area integral to calculate the flow rate if it is unknown.

Pump Curve Power Curves

Power, in this case, is the shaft power (measured sometimes in brake horsepower or BHP) of the pump required by the driving mechanism to maintain the specified flow rate. This is usually provided by a motor or engine. The power into the system is the amount of power applied to the shaft of the pump to generate the pressure difference.

Rotational power is calculated by multiplying the torque, or moment force about the center (the shaft rotational axis), and the spin speed of the shaft in radians per second.

Torque is obtained from CFD results using the surface pressures. SimScale automatically calculates the torque about a point and axis by selecting the faces of interest (the impeller) and specifying the rotational axis and point. Torque is taken directly from the platform and is available under result controls as forces and moments.

Pump Curve How to Read a Pump Curve

Pressure head shows the reader what flow rate can be maintained at a given pressure head, i.e., if the pump needs to supply flow to a tank at pressure 1 from a tank at pressure 2, what flow rate can it maintain? This defines the operating point a pump has to operate at, and pump curves can define the efficiency, flow rate, and power required at this condition. Different pump curves can be compared to select the correct pump for the application at hand.

The pressure difference is usually described as head—where the head is height—and can be obtained from pressure. This may be in feet or meters, and the units will be displayed.

Our Case: Pump Curve through CFD

The objectives of our simulation case were to analyze the pump’s design, as well as obtain enough information about its operating capabilities to create a pump curve characteristic. Through CFD evaluation of the pump CAD model, we were able to achieve this in the process stated below.

The Simulation Setup

The CFD simulation used a steady-state incompressible flow, with turbulence model k-omega SST model, with a rotating zone model.

Next, the mesh was set up using a hex-dominant parametric, with added refinements to the layers, surface, volume, and cell zone.

For this simulation, various fixed flow rates were applied rather than testing at different pressure differences. This produced more reliable data for the pump curve. The simplest way to assess whether the pump is producing high pressure or low pressure is setting the pressure at the outlet at 0 Pascals (Pa). The pressure outlet is not of particular relevance to this case, as it is an incompressible flow simulation. Anything above 0 Pa is high, anything below this is low.

A centrifugal pump is essentially an impeller pump, meaning it includes a rotating impeller at its core. To properly simulate this, a rotating zone should be established where anything inside this volume is “spinning”. Dealing with internal geometries, it can sometimes be difficult to fit this zone perfectly within the main geometry. For this reason, the rotating zone extends outside to avoid problems such as poor mesh quality. At this stage, it is important to ensure the center of rotation is accurate and equal to the defined center of rotation in the rotating zone. Instead of rotating the geometry inside, the rotational force should be applied at the wall and fluid domain to give a reliable approximation. In our case study, the force rotates around the rotating axis at 157 radians per second.

How to Read a Pump Curve: Which Results Are Relevant?

In the results control, the key focus when assessing efficiency is the ratio of power entering the inlet and power exiting the outlet. The pressure difference between the pressure at the inlet and pressure at the outlet shows the power that the pump is pushing out, in terms of flow. This is obtained through area averages, and monitoring average pressures at regular intervals such as every 10 seconds. This CFD simulation provides a vast amount of data in the force plot. Looking at the force plot, the pressure moment in the rotating axis reveals the necessary torque applied to the impeller to maintain conditions at the given angular velocity.

Using these key results in the characteristic pump curve enables a reliable reading of the pump’s performance efficiency. This enables you, or your customer, to better understand how the centrifugal pump will perform in a turbomachinery application or compare it to other products or pump designs.  

To learn more about how to read pump curves, fill out this short form and watch the webinar here now. 

Other Turbomachinery Resources:

• Learn more about centrifugal pump design
• Learn more about simulation-driven pump optimization
• Learn more about water turbines like the Francis turbine
• Learn about water turbine vs. impeller pump design
• Learn how to optimize your propeller design

The post Pump Curve: How to Assess Turbomachinery Performance with SimScale appeared first on SimScale.

With the many varieties of available pump configurations, a proper design is the most important requirement for any facility. 20% of the total energy consumed globally is used to run a pump of one sort or another—yet, two-thirds of these pumps use 60% more energy than is required. To ensure energy efficiency and prevent equipment failure, it is important to be able to predict and evaluate the pump’s performance under different operating conditions. This is where computational fluid dynamics (CFD) tools come to your aid.

To illustrate how CFD or flow simulation can help engineers improve the performance of a centrifugal pump design, we hosted a free 30-minute webinar .Watch the recording below.

Watch Webinar Recording

Centrifugal Pump Why You Should Care About Simulation

The cost and performance of any physical product are typically determined quite early in the design process. The stage when you begin to explore the design space and define your product concept is when the most impactful design decisions are made. After that, the rate at which the production costs are realized is much slower.

Simulation is one of the tools that play a fundamental role in those early product development stages, allowing engineers to make more informed design decisions earlier in the process. For the final product, this can mean lower production costs, more efficient energy consumption, lower failure risk, and more.

Centrifugal Pump Design Why SimScale?

Why aren’t all designers using simulation yet? Several barriers have prevented a more widespread adoption of simulation software by engineers and designers—and here’s how SimScale is aiming to challenge this status quo:

• Accessibility: Traditional software needs to be installed locally on expensive high-performing computers, most of which remain idle most of the time. With SimScale, all computations are cloud-based—all that is needed is a web browser.

• Operating costs: Standard commercial simulation software packages are notoriously expensive. With SimScale, there is an option to start simulating right away with a free Community Plan.

• Know-how: Most modern tools are designed for experts and experienced simulation engineers. To bridge that knowledge gap, SimScale offers a large public projects library, free training, and live support chat.

Centrifugal Pump Engineering Problem

Cutaway view of a centrifugal pump (Source: By Fantagu [Public domain], from Wikimedia Commons)

A centrifugal pump essentially consists of an impeller rotating in a casing called volute. Fluid enters the eye (center) of the impeller and exits through the space between the impeller blades to the space between the impeller and casing walls. The velocity of fluid elements is in both tangential and radial directions, as the impeller rotates. The velocity and pressure both increase as the fluid flows through the impeller. Since the rotational mechanical energy is transferred to the fluid, at the discharge side of the impeller, both the pressure and kinetic energy of the water will rise. At the suction side, water is getting displaced, so a negative pressure will be induced at the eye. This low pressure helps to suck a freshwater stream into the system again, and this process continues.

The impeller is the most vital part of a centrifugal pump design. Successful impellers have been developed with many years of analysis and developmental work. The vanes (blades) of the best impellers curve backwards by design. These backwards-curved vanes have a blade angle of less than 90 degrees and are the most preferred vane type in the industry due to their self-stabilizing power consumption characteristics. This means that with an increase in flow rate, the power consumption of the pump stabilizes after a limit.

Centrifugal Pump Design Centrifugal Pump Design Optimization Study

The complexity of the flow in a turbomachine is primarily due to the 3D-developed structures involving turbulence, secondary flows, unsteadiness, etc. The centrifugal pump design process was initially based on empirical correlation, a combination of model testing, and engineering experience. Nowadays, however, the design demands a detailed understanding of the internal flow—something that is possible with the aid of CFD.

CFD simulation makes it possible to visualize the flow conditions inside a centrifugal pump and provides valuable information about the pump’s hydraulic design. Simulation results are used to calculate and predict the performance of a centrifugal pump, which replaces the lengthy and expensive physical experiments of the past. A great deal of work is saved, in addition to shortening the entire design cycle.

Centrifugal Pump Project Overview

For our case study, we will use this simulation project as a template: Centrifugal Pump Design Optimization with CFD.

This project simulates a typical centrifugal water pump using the steady-state, multiple reference frame (MRF) method and the k-omega SST turbulence model. The pressure-velocity coupling is performed through the SIMPLE algorithm. The MRF zone is assigned a rotational velocity of 157.08 rad/s (1500 rpm). The project is concerned with the influence of (1) the outlet blade angle, and (2) the number of blades on the performance of a centrifugal water pump. The performance characteristic curves, as well as the local and global flow variables, are numerically predicted using SimScale for impellers with three different outlet blade angles (i.e., 13, 23 and 33 degrees), and three different numbers of blades (i.e., 6, 8 and 10).

The centrifugal pump design under consideration has inlet and outlet diameters of 150mm and 151.5mm respectively, and its impeller diameter is 340mm. The domain is the geometry, which was meshed using the ‘snappy-hex-mesh’ on the SimScale platform. The resulting mesh consists of approximately 4.5 million cells, which is shown in the figure below.

Centrifugal Pump Design (1) Effect of Outlet Blade Angle Variation

Outlet blade angle – 13, 23 and 33 degrees

Centrifugal Pump Flow Parameters

• Number of Blades = 8
• K-Omega SST Turbulence Model
• Steady-State, Incompressible Flow
• Multi-Reference-Frame (MRF) Method
• Impeller Rotational Velocity = 1500 rpm
• Inlet Volumetric Flow Rate = 540 cubic meters per hour
• Volute Casing Outlet Face — Pressure Outlet (0 Gauge Pressure)

The pressure contour results show that the maximum pressure difference (208.4 KPa) between the pump inlet and outlet occurs in the pump with blade outlet angle of 33 degrees and the least at 13 degrees (116.6 KPa), and the pump outlet is set as pressure outlet with fixed value, 0 gauge pressure boundary condition.

Centrifugal Pump Design (2) Effect of Variation of Number of Blades

Number of blades: 6, 8 and 10 blades

Centrifugal Pump Flow Parameters

• Outlet Blade Angle = 33 Deg
• K-Omega SST Turbulence Model
• Steady-State, Incompressible Flow
• Multi-Reference-Frame (MRF) method
• Impeller Rotational Velocity = 1500 rpm
• Inlet Volumetric Flow Rate = 540 cubic meters per hour
• Volute Casing Outlet Face — Pressure Outlet (0 gauge pressure)

From the pressure contour results, it can be seen that the maximum pressure difference (230.5 KPa) between the pump inlet and outlet occurs in the pump with ten blades and the least at six blades (161.04 KPa).

Centrifugal Pump Design Performance Comparison Between Pumps With 8 and 10 Blades (Blade Angle 30 Degrees)

Best Efficiency Point

Best efficiency point (BEP) is the flow at which the pump operates at the highest or optimum efficiency for a given impeller diameter. BEP for this pump is obtained at the flow rate of 432 cubic meters per hour. In addition, the maximum efficiencies obtained for pumps with eight blades and ten blades are 60.5% and 62.04%, respectively.

Head at Best Efficiency Point

Since the BEP occurs at a flow rate of 432 units, that flow rate also intersects the pump curve at a point equal to head of 26.65 meters, and 28.33 meters for pumps with eight blades and ten blades, respectively.

Centrifugal Pump Conclusion

As demonstrated in this case study, the centrifugal pump is a simple but essential device. Seemingly minor design changes, such as the outlet blade angle or the number of blades, can substantially impact the performance of the pump. With the multitude of available centrifugal pump design configurations, physically testing each one of them or relying on experience alone would make the design process unnecessarily long and expensive. The same design experiments can be carried out using numerical analysis and simulation, achieving equally accurate results within a few minutes or hours.

This is just one example of how CFD tools can help engineers evaluate their pumping equipment designs. The SimScale Public Projects Library has a wide selection of simulation templates covering various design aspects of industrial equipment and machinery, commercial and industrial fans, valves, and many more. In addition, you can fill in this short form to download a case study about how a ducting system design was investigated and optimized using the SimScale cloud-based platform.

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