A Basic Guide to Reverse Engineering

Reverse Engineering, or back engineering, is a term used for the process of examining an object to see how it works in order to duplicate or enhance the object when you don’t have the original drawings/models or manufacturing information about an object.

There are two major reasons reverse engineering is used:

  1.  create replacement parts to maintain the function of older machines;
  2.  improve the function of existing machines while meeting all existing constraints.

 

Figure 1 Uses of Reverse Engineering
Figure 1: Uses of Reverse Engineering

Reverse engineering is extremely important in turbomachinery for replacement parts in turbines or compressors which have been operating for many years. Documentation, reports and drawings for a significant amount of these machines is not available due to a variety of reasons, therefore keeping these important machines running is a challenge. One of the options to deal with this issue is to buy the modern analogue of the machine, which is not always feasible due to economic constraints or that there is no replacement available.  Reverse engineering of the worn out parts might be the best option in the majority of cases.

In any case, the process to recovery original geometry of the object is the first and major step for all reverse engineering projects, whether you want just replacing/replicate parts or proceed with an upgrade to the machine.

Basic Steps to Any Reverse Engineering Project

Any reverse engineering process consist of the following phases:

  1. Data collection: The object needs to be taken apart and studied.  Starting in ancient times, items were disassembles and careful hand measurements were taken to replicate items.  Today, we employ advanced laser scanning tool and 3D modeling techniques to record the required information in addition to any existing documentation, drawings or reports which exists.
  2. Data processing: Once you have the data, it needs to be converted to useful information.  Computers are essential for this stage as it can involve the processing of billions of coordinates of data converting this information into 2D drawings or 3D models by utilizing CAD systems.
  3. Data modeling: This step was not available in beginning of reverse engineering. People just tried to replicate and manufacture a similar object based on the available data. Nowadays, engineers can utilize digital modelling, which represents all details of the geometrical and operational conditions of the object through a range of operation regimes. Typically, performance analysis and structural evaluation are done at this stage, by utilizing thermo/aerodynamic analytical tool, including 3D CFD and FEA approaches.
  4. Improvement/redesign of the object: If required, this is the step where innovations can be created to improve the effectiveness of the object based on the collected data about the object’s geometry and operation.
  5. Manufacturing: After the part is been modeled and meets the design requirements, the object can be manufactured to replace a worn out part, or to provide increased functionality.
Reverse Engineering in Today’s World

It very common to find the situations where reverse engineering is necessary for parts replacement, particularly with turbomachinery – steam or gas turbines, compressors and pumps. Many of these machines have been in operation for many years and experienced damaging effects of use over that time – like water droplets and solid particles erosion, corrosion, foreign objects, and unexpected operating conditions. Besides these expected needed repairs, some other reasons for reverse engineering might arise from a components part failure, as well as part alterations needed due to previous overhauls and re-rates.

All the conditions mentioned above require not only recovering the original geometry but also an understanding of the unit’s history, material properties and current operating conditions.

This article focuses on reverse engineering objects which have experienced significant change in their geometry due to the challenges of long term operation and their shape could not be directly recovered by traditional methods – like direct measurement or laser scanning.  Pictures below are examples of such objects – steam turbines blading with significant damage of the airfoils with different causes such as mechanical, water/solid particle erosion, and deposit.

Figure 2 Water droplet erosion on steam turbines long blades
Figure 2: Water droplet erosion on steam turbines long blades
Figure 3 Steam turbine blading with mechanical damage
Figure 3: Steam turbine blading with mechanical damage
Figure 4 Steam turbine control stage nozzles solid particle erosion
Figure 4 Steam turbine control stage nozzles solid particle erosion
Figure 5 Deposits on Rotating Blades
Figure 5: Deposits on Rotating Blades

In the situations shown above, recovering the original geometry may be impossible if an engineer only has the undamaged portion of original part to work with. Which means that relying on undamaged portion of an original part it may be impossible to recover the needed portion due to significant level of damage.

Looking at the eroded turbine blading in Figure 1, recovering these airfoils with sufficient accuracy based on only a scan of the original part, would be very difficult, if not impossible, considering that 1/3 to ½ of the needed profile is wiped out by erosion.

In order to recover the full airfoil shape for turbines / compressors / or pumps blading, the information about flow conditions – angles, velocities, pressure, temperature – is required to recreate the airfoils profiles and a complete 3D blade.

In many cases with significant blading damage, the information obtained from aero/thermodynamic analysis is the only source of the information available for a designer and the only possible way to recover turbomachinery blading. In fact, in such a situation, the new variant of the airfoils is developed based on aero/thermodynamic information and by considering the remaining portion of the part, which would be the most accurate representation of the original variant. A structural evaluation should also be performed for any recovered part to ensure blading structural reliability in addition to the aero/thermodynamic study.

All of these engineering steps require employment of dedicated engineering design and analysis tools, which can perform:

  • – Accurate modelling of the turbo machinery flow path,
  • – 1D/2D aero/thermodynamic analysis and in some cases 3D CFD,
  • – Profiling and 3D staking of the blading,
  • – Structural evaluation, including 3D FEA tools.

SoftInWay’s team offers a comprehensive set of turbomachinery design and analysis tools within the integrated AxSTREAM® platform, which covers many steps, required for reverse engineering activities.

In Figure 6 below, a process diagram shows how AxSTREAM® products are used for reverse engineering.

Process Diagram
Figure 6: Process diagram of AxSTREAM® products use in reverse engineering

After data collection, most of the geometry recovering steps are processed by AxSTREAM® modules:

  • AxSLICE™ to process original geometry data, available from the scanned cloud of points.
  • AxSTREAM® solver to perform 1D/2D aero/thermodynamic
  • AxSTREAM® profiler to recover profile shape and 3D airfoil stacking.
  • AxSTRESS™ for structural evaluation and 3D design.
  • AxCFD™ for detailed aerodynamic analysis and performance evaluation.

Geometry recovered in this way is now ready to be used to develop detailed 3D CAD models and 2D drawings for further technological and/or manufacturing processing.

As an example of such capabilities, Figure 7 demonstrates the reverse engineering process for the 1000 mm last stage of 200 MW steam turbine with significantly damaged blades due to water erosion.

It is possible to recognize and extract the profile angles with a specialized tool – AxSLICE™, obtain slices on the desired number of sections and insert the extracted geometric data to an AxSTREAM® project.

200 MW steam turbine water eroded 1000mm last stage blade reverse engineering process using AxSTREAM and upgraded variant of the blade
Figure 7: 200 MW steam turbine water eroded 1000mm last stage blade reverse engineering process using AxSTREAM® and upgraded variant of the blade.

The AxSTREAM® platform can provide seamless reverse engineering process for all components of complex turbomachinery.

Meet an Expert! 

Boris Frolov Dr. Boris Frolov is the Director of Engineering at SoftInWay, Inc. and manages all of the turbomachinery consulting activities. He has over 35 years of experience in steam/gas turbines design, analysis and testing.

Earning his PhD in turbine stages optimization with controlled reaction, he is an expert in steam turbines aerodynamics and long buckets aeromechanics. Dr. Frolov has over 50 publications and 7 registered patents and he shares this vast knowledge as a lecturer in steam turbines, gas dynamics and thermodynamics for students studying power engineering sciences. Prior to joining SoftInWay, he was the engineering manager at GE Steam Turbines.

An Introduction to Bearing Instability

Hydrodynamic bearings operating at high speeds encounter instability problems of oil whirl and whip. Instability may ruin not only the bearings but the entire machine. It is well-known that hydrodynamics bearings play an important role in determining and controlling the vibrations of a rotating machinery, because of the springs and dampers, and bearings strongly influence the critical speed and imbalance response. Under certain conditions, the bearings can create rotor instability which results in significant self-excited vibrations.

The types of stability here are for a balanced journal and are mentioned below. If, as time increases, the trajectory of the journal center goes to a point of the clearance circle and remains there indefinitely, then the bearing is considered to exhibit “point stability,” Fig. 1(a). If, as time increases, the trajectory does not go to a point, as shown in Fig. 1(b) and (c), then the bearing, is considered to exhibit “point instability”. Two types of instability are shown in Figure 1. In Fig 1(b) the trajectory continues to increases without bound, ultimately reaching the limit of the clearance circle, therefore, this case is called “unbounded “. As time increases eases, if the trajectory closes on itself forming a limit cycle, as shown in Fig 1(c), then the trajectory can be said to be “orbitally stable”.

Types of Stability
Figure. 1 Types of stability

Satisfactory dynamic characteristics are essential to good bearing design. Hence it is very important for the designers to predict the journal center motion trajectories. AxSTREAM Bearing™ is used to calculate the hydrodynamic characteristics based on the mass-conserving mathematical model by applying the finite difference method with the successive over-relaxation (SOR) algorithm.

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Study of a Supercritical CO2 Power Cycle Application in a Cogeneration Power Plant

This is an excerpt from a technical paper, presented at the ASME Power & Energy Conference in Pittsburg, Pennsylvania USA and  written by Oleksii Rudenko, Leonid Moroz, and  Maksym Burlaka.  Follow the link at the end of the post to read the full study! 

Introduction

Supercritical CO2 operating in a closed-loop recompression Brayton cycle has the potential of equivalent or higher cycle efficiency versus supercritical or superheated steam cycles at similar temperatures [2]. The current applications of the supercritical CO2 Brayton cycle are intended for the electricity production only and the questions which are related to the building of CHP plants based on Supercritical CO2 technology were not considered yet.

CHP is the concurrent production of electricity or mechanical power and useful thermal energy (heating and/or cooling) from a single source of energy. CHP is a type of distributed generation, which, unlike central station generation, is located at located at or near the point of consumption. Instead of purchasing electricity from a local utility and then burning fuel in a furnace or boiler to produce thermal energy, consumers use CHP to improve efficiency and reduce greenhouse gas (GHG) emissions. For optimal efficiency, CHP systems typically are designed and sized to meet the users’ thermal base load demand. CHP is not a single technology but a suite of technologies that can use a variety of fuels to generate electricity or power at the point of use, allowing the heat that would normally be lost in the power generation process to be recovered to provide needed heating and/or cooling. This allows for much greater improvement in overall fuel efficiency, therefore resulting in lower costs and CO2 emissions. CHP’s potential for energy saving is vast.

It should be noted that CHP may not be widely recognized outside industrial, commercial, institutional, and utility circles, but it has quietly been providing highly efficient electricity and process heat to some of the most vital industries, largest employers, urban centers, and campuses. While the traditional method of separately producing useful heat and power has a typical combined efficiency of 45 %, CHP systems can operate at efficiency levels as high as 80 % (Figure 1) [1].

Figure 1 - CHP Process Flow Diagram
Figure 1. CHP Process Flow Diagram.

Taking into consideration the high efficiency of fuel energy utilization of CHP plants and the high potential of the supercritical CO2 technology, the latter should be also considered as the base of future CHP plants. The comparison with traditional Steam based CHP plants also should be performed.

The study of CHP plant concepts were performed with the use of the heat balance calculation tool AxCYCLE™ [3].

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Role of AxSTREAM® in Radial Turbine Design

Radial turbines are quite popular for turbochargers and micro-gas turbines. They can also be found in compact power sources like in auxiliary power units of aircrafts. In short, they are suitable in power generation applications where expansion ratios are high and mass flow rates are relatively small. In a radial turbine, the flow enters radially and exits either axially or radially depending on whether it is an inflow or outflow type radial turbine. The most commonly used type of radial turbine is a radial-inflow turbine, in which the working fluid flows from a larger radius to a smaller radius. A centripetal turbine is very similar in appearance to the centrifugal compressor, but the flow direction is reverse. Figure 1 shows the radial-inflow turbine on the left and radial-outflow turbine on the right.

Radial-inflow turbine on the left; Radial-outflow turbine on the right
Figure 1: Radial-inflow turbine on the left; Radial-outflow turbine on the right

Nowadays, the popularity of radial-outflow turbines, in which the flow moves in the opposite direction (from the center to the periphery), is growing. With recent advancement in waste heat recovery applications, there has been a renewed interest in this type of turbines. These radial-outflow turbines are most commonly used in applications based on organic Rankine cycles (ORC).

The radial-outflow turbine design was first invented by the Ljungström brothers in 1912, however it was rarely used for a number of reasons. One of which was related to the decrease of turbine-specific work due to the increase of the peripheral velocity from inlet to outlet while expanding the vapor. Another reason was the usage of steam as a working fluid. It is known from thermodynamics that the expansion of steam is characterized by high enthalpy drops, high volumetric flows and high volumetric ratios. Thus, a significant number of stages are needed to convert the enthalpy drop of the fluid into mechanical energy.

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Modern Approaches and Significance of Multiphase Flow Modeling

Introduction

Corresponding with the development of industrial technology in the middle of the nineteenth century, people  dealt with multiphase flows but the decision to describe them in a rigorous mathematical form was first made only 70 years ago. As the years progressed, development of computers and computation technologies led to the revolution in mathematical modeling of mixing and multiphase flows. There are a few periods, which could describe the development of this computation:

«Empirical Period» (1950-1975)

There were a lot of experiments which were done during this period. All models were obtained from experimental or industrial facilities which is why using them was difficult for different cases.

«Awakening Period» (1975-1985)

Because of sophisticated, expensive and not universal experiments, the researchers’ attention was directed to the physical processes in multiphase flows.

«Modeling Period» (1985-Present)

Today, the models for multi-flow calculation using the equations of continuity together with equations of energy conservation are obtained, which allow describing phase’s interaction for different flow regimes. (A.V. Babenko, L. B. Korelshtein – Hydraulic calculation two phase gas liquid course: modern approach // Calculations and modeling journal. – 2016. – TPА 2 (83) 2016. – P.38-42.)

Technology Development

Since the time of industrial development, installation designs have undergone great changes. For example, there are shell and tube evaporators for freeze systems where the heat transfer coefficient has increased 10 times over during the last 50 years. These results are a consequence of different innovation decisions. Developments led to research into mini-channels systems, which is the one of the methods to increase intensification of phase transition. Research has shown that heat exchange systems with micro and nano dimensions have a much greater effect than the macrosystems with channels dimensions ≤3-200 mm.

In order to organize fundamental research, it is very important to understand hydro, gas dynamics and heat changes in two-phase systems with the phase transition. At present, the number of researchers using advanced CFD-programs has increased. Our team is one of the lead developers of these program complexes.

Mathematical modeling of compressible multiphase fluid flows is interesting with a lot of scientific directions, and has big potential for practical use in many different engineering fields. Today it is no secret that environmental issues are some of the most commonly discussed questions in the world. People are trying to reduce the emissions of combustion products. One of the methods to decrease emissions is the organization of an environmentally acceptable process of fuel burning with reduced yields of nitrogen and sulfur. The last blog (http://blog.softinway.com/en/modern-approach-to-liquid-rocket-engine-development-for-microsatellite-launchers/) discussed numerical methods, which can calculate these tasks with minimal time and cost in CFD applications.

Waste Heat Boiler
Picture 1 – Waste heat boiler http://tesiaes.ru/?p=6291

For more effective use of energy resources and low-potential heat utilization, the choice of the Organic Rankine Cycle (ORC) is justified. Due to the fact that heat is used and converted to mechanical work, it is important to use a fluid with a boiling temperature lower than the boiling temperature of water at atmospheric pressure (with working flow-boiling temperature about 100⁰C). The usage of freons and hydrocarbons in these systems makes a solution impossible without taking into account the changes of working fluid phases. Read More

Modern Approach to Liquid Rocket Engine Development for Microsatellite Launchers

Microsatellites have been carried to space as secondary payloads aboard larger launchers for many years. However, this secondary payload method does not offer the specificity required for modern day demands of increasingly sophisticated small satellites which have unique orbital and launch-time requirements. Furthermore, to remain competitive the launch cost must be as low as $7000/kg. The question of paramount importance today is how to design both the liquid rocket engine turbopump and the entire engine to reduce the duration and cost of development.

The system design approach applied to rocket engine design is one of the potential ways for development duration reduction. The development of the design system which reduces the duration of development along with performance optimization is described herein.

The engineering system for preliminary engine design needs to integrate a variety of tools for design/simulation of each specific component or subsystem of the turbopump including thermodynamic simulation of the engine in a single iterative process.

The process flowchart, developed by SoftInWay, Inc., integrates all design and analysis processes and is presented in the picture below.

Execution Process Flow Chart
Execution Process Flow Chart

The preliminary layout of the turbopump was automatically generated in CAD tool (Block 11). The developed sketch was utilized in the algorithm for mass/inertia parameters determination, secondary flow system dimensions generations, and for the visualization of the turbopump configuration. The layout was automatically refined at every iteration. Read More

Hydrodynamic Journal Bearings Optimization Considering Rotor Dynamics Restrictions

This is an excerpt from a technical paper, presented at the ASME Turbo Expo 2018 Conference in Oslo, Norway and written by Leonid Moroz, Leonid Romanenko, Roman Kochurov, and Evgen Kashtanov. Follow the link at the end of the post to read the full study! 

Introduction

High-performance rotating machines usually operate at a high rotational speed and produce significant static and dynamic loads that act on the bearings. Fluid film journal bearings play a significant role in machine overall reliability and rotor-bearing system vibration and performance characteristics. The increase of bearings complexity along with their applications severity make it challenging for the engineers to develop a reliable design. Bearing modeling should be based on accurate physical effects simulation. To ensure bearing reliable operation, the design should be performed based not only on simulation results for the hydrodynamic bearing itself but also, taking into the account rotor dynamics results for the particular rotor-bearing system, because bearing characteristics significantly influence the rotor vibration response.

AxSTREAM Bearing

Numbers of scientists and engineers have been involved in a journal bearing optimal design generation. A brief review of works dedicated to various aspects of bearing optimization is presented in [1]. Based on the review it can be concluded, that the performance of isolated hydrodynamic bearing can be optimized by proper selection of the length, clearance, and lubricant viscosity. Another conclusion is that the genetic algorithms and particle swarm optimization can be successfully applied to optimize the bearing design. Journal bearings optimizations based on genetic algorithms are also considered in [2-5]. The studies show the effectiveness of the genetic algorithms. At the same time, the disadvantages of the approach are high complexity and a greater number of function evaluations in comparison with numerical methods, which require significantly higher computational efforts and time for the optimization. A numerical evolutionary strategy and an experimental optimization on a lab test rig were applied to get the optimal design of a tilting pad journal bearing for an integrally geared compressor in [6]. The final result of numerical and experimental optimizations was tested in the field and showed that the bearing pad temperature could be significantly decreased. Optimal journal bearing design selection procedure for a large turbocharger is described in [7]. In this study power loss, rotor dynamics instability, manufacturing, and economic restrictions are analyzed. To optimize the oil film thickness by satisfying the condition of maximizing the pressure in a three lobe bearing, the multi-objective genetic algorithm was used in [8]. In the reviewed studies the optimization has been performed for ‘isolated’ bearing and influence on rotor dynamics response was not considered.

For higher reliability and longer life of rotating mechanical equipment, the vibration of the rotor-bearing system and of the entire drivetrain should be as low as possible. A good practice
for safe rotor design typically involves the avoidance of any resonance situation at operating speeds with some margins. One common method of designing low vibration equipment is to have a separation margin between the critical natural frequencies and operating speed, as required by API standard [9]. The bearing design and parameters significantly influence rotor-bearing system critical speeds. Thus, to guarantee low rotor vibrations, the critical speeds separation margins should be ensured at rotor-bearing system design/optimization stage

Conjugated optimization for the entire rotor-bearing system is a challenging task due to various conflicting design requirements, which should be fulfilled. In [10] parameters of
rotor-bearing systems are optimized simultaneously. The design objective was the minimization of power loss in bearings with constraints on system stability, unbalance sensitivities, and
bearing temperatures. Two heuristic optimization algorithms, genetic and particle-swarm optimizations were employed in the automatic design process.

There are several objective functions that are considered by researchers to optimize bearing geometry, such as:

– Optimum load carrying capacity [5];
– Minimum oil film thickness and bearing clearance optimization [1, 6, 8];
– Power losses minimization [6, 7];
– Rotor dynamics restrictions;
– Manufacturing, reliability and economics restrictions [7]

The most common design variables which are considered in reviewed works are clearance, bearing length, diameter, oil viscosity, and oil supply pressure.

Finding the minimum power loss or optimal load carrying capacity together with the entire rotor-bearing system dynamics restrictions, require to employ optimization techniques, because accounting the effects from all considered parameters significantly enlarge the analysis process. Several numerical methods, such as FDM and FEM are usually employed to solve this complex problem and calculation process can sometimes be time-consuming and takes a large amount of computing capacity. To leverage this optimization tasks, efficient algorithms are needed.

In the current study, the optimization approach, which is based on DOE and best sequences method (BSM) [11, 12] and allows to generate journal bearings with improved characteristics was developed and applied to 13.5 MW induction motor application. The approach is based on coupled analysis of bearing and entire rotor-bearing system dynamics to satisfy API standard requirements.

Problem Formulation and Analysis Methods Description

The goal of the work is to increase reliability and efficiency for the 13.5 MW induction motor prototype (Fig. 1) by oil hydrodynamic journal bearings optimization.

Rotor of 13.5 MW Induction Motor
Figure 1: Rotor of 13.5 MW Induction Motor

The motor operating parameters and rotor characteristics are presented below:

– Rated speed rpm: 1750
– Minimum operating speed rpm: 1750
– Maximum operating speed rpm: 1750
– Mass of the rotor kg: 6509
– Length of the rotor mm: 3500

Initially, for the motor application, plain cylindrical journal bearings were chosen to support the rotor. The scheme of the DE (drive end) and NDE (non-drive end) baseline bearings designs
is presented in Fig. 2. For baseline designs, bearing loads were 35 kN for DE and 28 kN for NDE bearing.

Plain Cylindrical Bearing
Figure 2: Plain Cylindrical Bearing

The methodology for the bearing characteristics simulation is based on the mass-conserving mathematical model, proposed by Elrod & Adams [13], which is by now well-established as the
accurate tool for simulation in hydrodynamic lubrication including cavitation.

Read full paper here 

Design of Waste Heat Recovery Systems Based on Supercritical ORC for Powerful Gas and Diesel Engines

This is an excerpt from a technical paper, presented at the ASME ORC 2015 Conference in Brussels, Belgium and  written by Oleksii Rudenko, Leonid Moroz, Maksym Burlaka, and Clement Joly.  Follow the link at the end of the post to read the full study! 

1. Introduction

Internal combustion piston engines are among the largest consumers of liquid and gaseous fossil fuels all over the world. Despite the introduction of new technologies and constant improving of engines performances they still are relatively wasteful. Indeed, the efficiency of modern engines rarely exceeds 40-45% (Seher et al. (2012), Guopeng et al. (2013)) and the remainder of the fuel energy usually dissipates into the environment in the form of waste heat. The heat balance diagram of typical engine is given in Figure 1. As is evident from Figure 1, besides the mechanical work energy the heat balance includes a heat of exhaust gas, a heat of charge air, a Jacket Water (JW) heat, a heat of lubricating oil and a radiation heat. The energy from all the heat sources except the last one (radiation), due to its ultra-low waste heat recovery potential, can be used as heat sources for WHRS (Paanu et al. (2012)) and are considered here.

Heat Balance Diagram
Figure 1: Typical heat balance diagram for CAT engine (Caterpillar (2011))

Waste heat utilization is a very current task because it allows to reduce the harmful influence of ICPE operation on the environment as well as to obtain additional energy and to reduce the load on the engine’s cooling system. Different WHRS can produce heat energy, mechanical energy or electricity and combinations of the converted energy forms exist as well. In general, the type of WHRS to be used is determined by the engine type, fuel cost, available energy customers and other factors. In the presented paper, only WHRS for mechanical power and electricity production were considered because these kinds of energy are preferable for this type of applications and they can be easily converted into other forms of energy.

For vehicle engines the WHRS based on Organic Rankine Cycle (ORC) are the most commercially developed (Paanu et al. (2012)). Because of strict restrictions on weight and dimensions, the
mentioned systems typically operate on the base of a simple or recuperated ORC and utilize only high temperature waste heat from the exhaust gases and the exhaust gas recirculation. They usually produce mechanical power or electricity. More complex cycles and a larger number of heat sources are used for waste heat recovery from powerful internal combustion engines where additional weight and dimensions are not crucial factors. Waste heat from stationary, marine and another more powerful ICPE can be recovered using a typical steam bottoming cycle. Steam WHRS allow utilizing almost all a high temperature waste heat and partially utilizing a low temperature heat. The high efficiency steam WHRS are presented in (MAN Diesel & Turbo (2012), Petrov (2006)), they provide up to 14.5% of power boost for the engine.

Addition of the internal heat recuperation to a WHR cycle:

  1. Appropriate working fluid selection;
  2. Increment of initial parameters of bottoming cycle up to supercritical values;
  3. Maximize waste heat utilization due to the usage of low temperature heat sources;
  4. Bottoming cycle complexification or usage of several bottoming cycles with different fluids
    (Maogang (2011)).



This paper focuses on the development of new WHRS as an alternative to high efficiency steam bottoming cycles by accounting for the latest progress in the field of waste heat recovery. The
application range of the proposed system extends to powerful and super powerful ICPEs.

The goal of the presented work is the development of a new, high efficiency WHRS for powerful and super powerful ICPEs based on ORC principles. To solve the assigned task, a thorough study of the currently existing works was performed and the best ideas were combined. The principles of the maximum waste heat utilization, maximum possible initial cycle parameters, recuperation usage and single working fluid were assumed as a basis for the new WHRS design.

Read the full paper here

Computational Fluid Dynamics for Centrifugal Pumps

Pumps are important for many common systems which deal with water, such as heating circulating flows, consumer or industrial water supply, fountains, and fire protection systems.

Pumps are classified into two major categories: Rotodynamic pumps and positive displacement pumps (piston pumps). Rotodynamic pumps can be further classified as axial pumps, centrifugal (radial) pumps, or mixed pumps.

Centrifugal pumps are the devices which impart energy to the fluid (liquid) by means of rotating impeller vanes, and the fluid exits radially from the pump impeller. Such pumps are simple, efficient, reliable, relatively inexpensive, and easily meet the pumping system requirements for filtration. This is a great pump choice for moving liquids from one place to another using pressure.

Types of Rotodynamic Pumps
Figure 1. Types of Rotodynamic Pumps

Centrifugal Pump Design

A centrifugal pump is a very common component in turbomachines, but as with any component, it still needs continual improvement in the design methodology, from conceptual level to the final product development including testing at different levels. The challenge is to design a pump with improved efficiency while minimizing the possibility of cavitation.

Need of Numerical Simulation

Years ago, engineers performed prototype testing at each level of design to check the performance (which was very costly and time consuming). Now with advancements in the computation technology and resources, it is comparatively easier to design high efficiency pumps within a short duration of time. These simulations can be done with a computer, so, the number of physical prototypes required is greatly reduced. The main advantage of numerical simulation is that it allows engineers to virtually test the CAD model early in the design process, and provides flexibility for engineers to iterate the design until getting the required performance.

Computational Fluid Dynamics for Centrifugal Pumps

Computational fluid dynamics (CFD) replaces the huge number of testing requirement. This not only shortens the design cycle time but also significantly reduces development cost.

In a CFD model, the region of interest, a pump impeller flow-path for example, is subdivided into a large number of cells which form the grid or mesh. The PDEs (partial differential equations) can be rewritten as algebraic equations that relate the velocity, pressure, temperature, etc. in a cell to those in all of the cell’s immediate neighbors. The resulting set of equations can then be solved iteratively, yielding a complete description of the flow throughout the domain.

To accomplish CFD simulations, there are several software programs available, but user must select a very well validated software that can provide and easy user interface, automatic mesh generation and flexibility to modify the geometry to perform optimization without needing to move to some other software platform.

In the current trend, automatic mesh generation tools like AxCFD™ are employed in the AxSTREAM® software platforms which reduces the turbomachines meshing complications and generate good quality mesh in considerably short timeframe which can capture the accurate flow features needed. Figure 2 shows the discretized impeller and pressure contour after CFD analysis.

Discretized Impeller and Pressure Contour After CFD Analysis
Figure 2. Discretized Impeller and Pressure Contour After CFD Analysis

AxCFD™, in AxSTREAM® platform, provides user an opportunity to perform CFD analysis by applying standard methods of full three-dimensional CFD, axisymmetric CFD (meridional), and blade-to-blade analysis. User can even perform optimization of the blade profiles and other geometrical parameters within the AxSTREAM® platform and perform CFD simulation without altering any CFD settings.

An Introduction to Accurate HVAC System Modeling

HVAC (Heat, Ventilation and Air Conditioning) is all about comfort, and comfort is a subjective feeling associated with many parameters like air quality, air temperature, surrounding surface temperature, air flow and relative humidity. For example, while it is easy to understand how the temperature of the air in your living impacts how good you feel, the surfaces with which you are in contact also strongly affect your comfort. For example, last night I got out of bed to clean up after my dog who thought it would be a good idea to swallow (and give back) her chew toy. If I was wearing my slippers, it would have been much easier to go back to sleep between the warm bed sheets without the discomfort of waiting my cold feet warm up to normal temperature.

Speaking of sleep discomfort, many stem from HVAC imbalances.  If you wake up in the middle of the night quite thirsty, then you should probably check how dry your bedroom is. The recommended range is 40-60% relative humidity. A higher humidity puts you at risk for mold while lower humidity can lead to respiratory infections, asthma, etc.

Now that we know how HVAC contributes to our comfort, let’s look at the HVAC unit as a system and see its role, functioning and simulation at a high level. The following examples provided are for a house, but similar concepts apply to residential buildings, offices, and so on.

Controlling Temperature

The easiest parameter to control is the air temperature. It can be set by a thermostat and regulated according to a heating or cooling flow distributed from the HVAC unit to the different rooms through ducting. Without the introduction of thermally-different-than-ambient air, the house will heat or cool itself based on a combination of outside conditions and how well the building is insulated. Therefore, to keep a constant temperature a certain amount of energy must be used to provide heating (or cooling) at the same rate the house is losing (or gaining) heat.  This is a match of the house load and heating/cooling capacity. Figure 1 provides a graph of the energy needed.

Illustration of dependency of house load and heating capacity on outside temperature
Figure 1 Illustration of dependency of house load and heating capacity on outside temperature

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